Kids are like sponges, so when adults in their lives spew hateful commentary, it sticks to them. The end result is that it stays with them as they go through life interacting with different people. Having a sense of belonging is important to youths, especially in a school environment.

This section shows how gender norms are not taught through big rules but through small everyday practices. What I find important here is that children learn “how to be a boy” or “how to be a girl” before they even understand these labels themselves. When teachers divide students into boys vs. girls for games, it teaches kids that gender difference is more important than cooperation. This early separation also trains children to see gender as competition, not as a flexible part of identity. What seems like an innocent classroom routine actually becomes the foundation for later gender stereotypes and pressure to “fit” into one gender role.

This is an important point to consider. A student may be gifted in one area, but that doesn’t necessarily mean they excel in all other areas.

While a student may be considered gifted or more advanced, it's crucial to remember that they too are human. They may face the same types of insecurities, and self-doubt as anyone else. It's important to not undermine those feelings or reactions.

It's important to remember to have patience and be open minded for students who are more inquisitive.

I agree with this statement. Curriculums can be adjusted to fit different learning styles, but I don’t think students should be separated from their peers unless it’s absolutely necessary and the school can provide for their needs.

I think it is important to distinguish between how the student learns and if they actually enjoy it. While it's true that some students may get bored because they are more advanced than others, the same can happen if they are put in more advanced classes but more is expected of them and they don't enjoy the workload, which in turn they can become frustrated. People have different skills and different capabilities.

Interesting tidbit of information to remember. While someone can acquire new knowledge or information, intelligence will always stay the same.

Bureaucracy has always been a hurdle to jump through in the education system and one that everyone has to go through one way or another.

I feel like we are still out of touch as the world of education marches forward and changes constantly needing to change with time.

definition of AI as plagiarism

After reading this website and book, I know that The little-known commercial labor process of "content moderation" behind social media platforms. The author points out that although contemporary internet users often believe that algorithms are the dominant force, in reality, it is human moderators who "truly protect" a large amount of inappropriate, hateful, violent, and pornographic content. One detail from this website is that although these workers are "invisible," they are a crucial force in shaping the public discourse space on social media. The institutionalization, globalization, and subcontracting of their work have given human review the characteristics of "invisible labor."

I think the labour issues Roberts raises are under‐recognized. As a user I rarely think about the human moderators behind the platform I use. It made me more aware of the ethics of consumption: the “clean” feed I enjoy is enabled by invisible people working in difficult conditions. That leads me to a question: How much responsibility should platforms bear toward these moderators’ mental health, and how transparent should they be to end users about who does this work?

Wikipedia editors are moderators who are mainly responsible for keeping order on the site and ensuring that the information present is both reliable and accurate. They have the power to block and unblock users, delete, recover, and rename pages, along with many other abilities.

After reading this article, I think moderators do a lot more for our favorite social media sites than we give them credit for. While sites can use bots to filter out manual stuff like spam posts and ads, the more complex posts such as offensive comments/videos, things that violate policies, reports, etc. are usually handled by human moderators. This means these moderators something will have to review things like gore, extremely hateful content, and other unspeakable things that other people post to these websites. I remember watching an interview where an Facebook moderator revealed that he is forever scarred from the stuff he had to review for his job. So while content moderation sounds like an easy job, it's actually a very difficult and essential job that helps keep platforms running properly.

This is an interactable game about content moderation. The game sees you fill the role of an individual moderator for a website, where you have to review posts to see if they should be banned or allowed to stay up, all with a ticking clock to get you to pick up the pace and likely make more mistakes. Your boss will pop up now and then to let you know when you unfairly banned/ didn't ban a post or when he agrees with your ban. The game as a whole is used to show just how difficult content moderation is as a person, and how easy it is to make bad calls and mistakes while more and more reported posts flood in for you to review.

This article is about how women scientists are not getting recognized enough. Donna Strickland is a physicist, she invented a lot of things that’s helpful to the society. However, she did not have a wikipedia page until she won the noble prize. There were only three women in total that have won the noble prize in physics, and women in the science field are usually undervalued and invisible. All these contribute to the stereotype of scientists as male and create barriers for women who want to pursue in STEM.

Reddit is defiantly one of these sites which heavily rely on volunteer moderators. While the site have bots, I say these moderators do a much more accurate job making sure the subreddit group is clean of any content that may "violate" their policies. For me, I find it personally surprising how dedicated these people are to moderating these group when they often times do not get paid for the task. My conclusion is that either because of the power dynamic of being a moderator that they enjoy, or they simply just have too much free time.

This source written by David Gilbert speaks about how a moderator at Facebook (Ms. Plunkitt) is very stressed, has bad anxiety, and doesn't agree with the working conditions of Facebooks moderation team. She states that it is a very stressful job to look at this graphic content every day and it's taking a toll on her as a person, she cannot keep doing this.

This serves as a reminder for technology companies, especially social media companies, that they should hire a large number of young people rather than so-called experienced middle-aged individuals to operate. Because they usually do not participate in mainstream social media or belong to marginalized groups. They do not understand the new social media language that has been created, and thus cannot understand social media trends. As a result, they may make wrong decisions and fall behind in the competition.

This source discusses Facebook moderators and how they were experiencing seeing traumatising things on facebook such as murder and death. These videos traumatized the Facebook moderators, and they were simply told to suck it up. It was even proposed that they should start doing karaoke and painting in order to help them.

I find it really interesting how so many sites rely on volunteer moderators to moderate their platforms. When analyzing Reddit's moderating nature, I think it makes sense for moderators to be volunteer as there are many different subreddits created by people, and the moderators are people that are passionate about the topic of the subreddit. If there were moderators that were paid, would they be paid through Reddit? There are thousands of different subreddits with a different amount of people, so would every single moderator be paid by Reddit?

Donna Strickland was the third woman in history to win the Nobel Prize in Physics, but didn't even have a wikipedia page before she won the award. This article discusses how many female scientists are under recognized by the public and underrepresented in awards.

This article talks about the function of Wikipedians, and the job of that should be easy. Wikipedians have more access to the Wikipedia, and they have the rights to edit the content. This make sure the content was right and keep improve the quality of the content.

Sarah T. Roberts’ Behind the Screen really opened my eyes to how hidden and emotionally damaging content moderation work can be. The book reveals how the people who clean up the internet—filtering through disturbing images, videos, and hate speech—are often underpaid, outsourced, and given little emotional support. What struck me the most was how invisible this labor is, even though it’s essential for keeping social media platforms usable. Reading about the trauma moderators face makes me think differently about platforms like Facebook or TikTok, which profit from user-generated content but rely on poorly supported workers to make it “safe.” It makes me question whether platforms should be legally required to provide better pay, mental health care, and transparency about their moderation processes.

This brought an interesting thought up and stood out to me as I was reading this. Thinking about the unpaid moderators, I talked about in my other comment how I thought it could be seen as a good thing and a bad thing. Being unpaid may attract passionate people that will do a good job moderating, or it could lead to a bad job because they don't care as much. And I could see how it could be perceived both of those ways. But this source mentioned that it is good for smaller subreddits but when it comes to the larger huge subreddits that are very general, unpaid moderators will have no stake in the content, they can't be passionate about the broader subreddits and so this could lead to bad moderation.

After reading a small part of this book, I noticed that the moderators are facing a situation we cannot imagine. They provide users with a clean online environment, but they have reviewed so much inappropriate content that it may even traumatize their mental health.

Replicate the changes from the header section here

I would also add a button at the bottom of this section so people don't miss it

Move the timer up underneath 'Join before this timer...'

I wonder if the dichotomy “trained vs untrained” might be easier said than done: even trained moderators face huge grey areas and emotional toll. So “training” helps, but doesn’t eliminate risk.

Is it ever possible for systems with no moderators to succeed? Wouldn't the absence of any moderation make it much easier for errors, bugs, and other negative impacts on the system to be present?

It is very interesting to learn about all these different types of methods to moderate websites. From these texts I can really see how different it could be using different methods to run the website. Personally, the individuals moderating their own spaces method feels very easy and the most customizable. Individuals can personalize their own moderation, however, I do think it is important to still have some moderation from other parties like the moderation teams because not everyone knows and willing to do things themselves.

There is a well known meme that volunteer moderation such as those which moderate discord or reddit account, don't leave their room and often have bad hygiene due to all their focus being on moderating the group. And while I can't say this is 100% fact based, from my personal experience on reddit, I CAN say those moderators are QUICK to take down anything that "violates" their group policy. I remember posting something which did not fit the group rules when I first stated using reddit, and it got taken down within 2 minutes of the post being up!

Bots can massively increase the efficiency of moderations since they can capture the content 24/7 without rest. However, bots might not understand some ambiguous expressions that could contain some harmful information. For example, users could use metaphors to express their thoughts that most human understands, but bots cannot. In this case, either the content will be posted or the work will be handed back to human moderators.

The website without moderators can be so dangerous, and the content will also be useless and full of spam. As a user, I would like to view the websites with the moderators which give me safety online.

I think the introduction of different types of content moderators is engaging. By reading the following types of content moderators, we can find the advantages and disadvantages of various types of content moderators. I also notice that for companies that need to review a large amount of posts, they will invest more than small websites to avoid the potential legal risks.

I do think that Reddit not paying volunteer moderators is a somewhat good idea. I think the main benefit this has is that a subreddit moderator is almost always a moderator for the love of the game so to speak, they do it because they want to or because no one else can/wants to. This means that moderators usually have a personal attachment to their work as a moderator, which should have the benefit of better moderation. Think of it like doing something because its your job vs doing something because your intrinsically motivated to.

I think the ethical tradeoff for not paying the moderators is that they will create some form of payment, like power tripping. I think that reddit moderators or moderators in general should be paid and hired by the company. It would not only offer jobs to people, but it would also make the platform they are moderating a better and safer space for the users.

I find it interesting how a large majority of the editors and writers of Wikipedia are male, and I was wondering why that is. Because of the skewed demographics, there is bound to be bias in Wikipedia articles, regardless of whether the author wants it or not. I've always heard not to use Wikipedia for any sources on research assignments because of the volunteer nature of the site.

I think the unpaid moderation on platforms like Reddit and Wikipedia raises a big ethical issue about labor and fairness in the digital age. These moderators do essential work — without them, both sites would be full of spam, misinformation, and hate speech — yet they receive no pay, even though the platforms themselves are worth billions. I understand that volunteering can create a sense of community and shared purpose, but it also feels like these companies are exploiting free labor to maintain profitability.

With Wikipedia, I also think the lack of diversity among editors shows how bias can appear even in crowdsourced spaces that claim to be neutral. If most editors are men, then naturally the content and decisions about what “qualifies” as notable might lean toward male perspectives.

Facebook’s situation adds another layer — if content moderation doesn’t exist in certain languages, whole communities are left vulnerable to misinformation or hate speech. I think this shows how moderation isn’t just a technical issue, but a social and ethical one. Maybe companies should invest more in fair compensation and in language inclusivity so all users are protected equally.

I think it is interesting that they are unpaid because it makes me wonder if the reddit moderators are going to do a good job at moderating if they aren't being paid to do it. I think this could go either way, when reddit doesn't pay moderators in subreddits that could make them unmotivated to do a good job at moderating and could lead to reddit needing to oversee them and kind of ruin the whole point. Or it could be a good thing and by not paying these moderators, reddit only attracts people who are passionate about these subreddits. Since they are passionate enough about it to moderate for free, they will do a good job.

I think for unpaid Reddit moderators, they maintain their subreddit based on their interests, and they may not care too much about the financial payback. However, Reddit could offer the unpaid moderators some honors without actual monetary value to encourage them.

I find this very Interesting and not good. I believe that companies such as Facebook should be able to pay their workers enough since they are such a large company and have the money to be able to pay their workers. I also believe that Facebook should already have filters in place so that videos of murder and other bad things can't be posted.

It's concerning that the moderators are being exposed to disturbing content without proper mental health support. I feel like this is extremely unethical and takes advantage of the workers financial situation. Companies should provide professional therapy and better pay.

Spamming is used to send messages to a large amount of people. It can take the form of emails, texts, and even social media comments. It could be sent by bots or humans. Spam messages are very annoying for the people who receive them.

Moderation is also a virtue in Taoism, which is centered around balance. In Taoism you should avoid excess and live simply. It's interesting how moderation comes up in philosophies all over the world

Probably good to write here that this is what they used last week, not certain they remember the name

Always try to answer the five Ws and H questions.

What on earth is going on here

This is important for sure! As journalists, we'll eventually have to compete with AI-powered news tools, and we need to understand the risks as well as make it work for us in a way

I'm worried AI might be the worst tool alive to generate original ideas (just because of the way it works as a predictor of words based on previous words, such as your text prediction on your phone, or how it cannot really produce anything that hasn't been made before) but it may be efficient in assisting human ideas, such as vibe coding - generating virtual reality, AI-driven interactive storylines, etc.

HaaS

monetize

the network is the value!

Always consider the elements on the texts that will have a lot of support in so you can spend less time thinking about them later!

when you ask the questions that leads to more questions it shows effort being put into the research on the topic and now there is more then 2 sentences of evidence

Basically, "1B reads is enough to detect most things"

Core conclusion: 40M is enough unless you want rare transcripts or isoforms

Always focus on the what? the why? and the how?

why are they separated this way? by function?

what kind of processing occurs in the gray matter?

So it should be said in the form of an asnwer?

This indirectly ties in to hieroglyphics shaping the modern english language

Interesting approach, I always struggled to do this but I am glad that I know that it is accceptable to do it.

The verbs we use as signalers are interesting choice because we need to make sure they go according to our own understanding.

it is almost crazy the jump in technology, that only a couple of decades ago we could barely make human noises to now full fledge artificial intelligence. which makes me wonder if this was due to Vannevar's push for tech not just to be for war.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Response to referee comments: ____RC-2025-03008

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments: Are the key conclusions convincing? The authors reported that they have successfully used TALE-based affinity selection of protein-associated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research, and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication. 1. The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept.

Response

The main request from Referee 1 is for individual evaluation of protein-DNA interaction for a few candidates identified in our TALE-YFP affinity purifications, particularly using EMSA to identify binding to the DNA repeats used for the TALE selection. In our opinion, such an approach would not actually provide the validation anticipated by the reviewer. The power of TALE-YFP affinity selection is that it enriches for protein complexes that associate with the chromatin that coats the target DNA repetitive elements rather than only identifying individual proteins or components of a complex that directly bind to DNA assembled in chromatin.

The referee suggests we express recombinant proteins and perform EMSA for selected candidates, but many of the identified proteins are unlikely to directly bind to DNA - they are more likely to associate with a combination of features present in DNA and/or chromatin (e.g. specific histone variants or histone post-translational modifications). Of course, a positive result would provide some validation but only IF the tested protein can bind DNA in isolation - thus, a negative result would be uninformative.

In fact, our finding that KKT proteins are enriched using the 177R-TALE (minichromosome repeat sequence) identifies components of the trypanosome kinetochore known (KKT2) or predicted (KKT3) to directly bind DNA (Marciano et al., 2021; PMID: 34081090), and likewise the TelR-TALE identifies the TRF component that is known to directly associate with telomeric (TTAGGG)n repeats (Reis et al 2018; PMID: 29385523). This provides reassurance on the specificity of the selection, as does the lack of cross selectivity between different TALEs used (see later point 3 below). The enrichment of the respective DNA repeats quantitated in Figure 2B (originally Figure S1) also provides strong evidence for TALE selectivity.

It is very likely that most of the components enriched on the repetitive elements targeted by our TALE-YFP proteins do not bind repetitive DNA directly. The TRF telomere binding protein is an exception - but it is the only obvious DNA binding protein amongst the many proteins identified as being enriched in our TelR-TALE-YFP and TRF-YFP affinity selections.

The referee also suggests that follow up experiments using knockdown of the identified proteins found to be enriched on repetitive DNA elements would be informative. In our opinion, this manuscript presents the development of a new methodology previously not applied to trypanosomes, and referee 2 highlights the value of this methodological development which will be relevant for a large community of kinetoplastid researchers. In-depth follow-up analyses would be beyond the scope of this current study but of course will be pursued in future. To be meaningful such knockdown analyses would need to be comprehensive in terms of their phenotypic characterisation (e.g. quantitative effects on chromosome biology and cell cycle progression, rates and mechanism of recombination underlying antigenic variation, etc) - simple RNAi knockdowns would provide information on fitness but little more. This information is already publicly available from genome-wide RNAi screens (www.tritrypDB.org), with further information on protein location available from the genome-wide protein localisation resource (Tryptag.org). Hence basic information is available on all targets selected by the TALEs after RNAi knock down but in-depth follow-up functional analysis of several proteins would require specific targeted assays beyond the scope of this study.

NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones?

Response

The NonR-TALE-YFP immunolocalisation signal indeed is apparently located close to the kDNA and away from the nucleus. We are not sure why this is so, but the construct is sequence validated and correct. However, we note that artefactual localisation of proteins fused to a globular eGFP tag, compared to a short linear epitope V5 tag, near to the kinetoplast has been previously reported (Pyrih et al, 2023; PMID: 37669165),

The expression of NonR-TALE-YFP is shown in Supplementary Fig. S2 in comparison to other TALE proteins. Although it is evident that NonR-TALE-YFP is expressed at lower levels than other TALEs (the different TALEs have different expression levels), it is likely that in each case the TALE proteins would be in relative excess.

It is possible that the absence of a target sequence for the NonR-TALE-YFP in the nucleus affects its stability and cellular location. Understanding these differences is tangential to the aim of this study.

However, importantly, NonR-TALE-YFP is not the only control for used for specificity in our affinity purifications. Instead, the lack of cross-selection of the same proteins by different TALEs (e.g. TelR-TALE-YFP, 177R-TALE-YFP) and the lack of enrichment of any proteins of interest by the well expressed ingiR-TALE-YFP or 147R-TALE-YFP proteins each provide strong evidence for the specificity of the selection using TALEs, as does the enrichment of similar protein sets following affinity purification of the TelR-TALE-YFP and TRF-YFP proteins which both bind telomeric (TTAGGG)n repeats. Moreover, control affinity purifications to assess background were performed using cells that completely lack an expressed YFP protein which further support specificity (Figure 6).

We have added text to highlight these important points in the revised manuscript:

Page 8:

"However, the expression level of NonR-TALE-YFP was lower than other TALE-YFP proteins; this may relate to the lack of DNA binding sites for NonR-TALE-YFP in the nucleus."

Page 8:

"NonR-TALE-YFP displayed a diffuse nuclear and cytoplasmic signal; unexpectedly the cytoplasmic signal appeared to be in the vicinity the kDNA of the kinetoplast (mitochrondria). We note that artefactual localisation of some proteins fused to an eGFP tag has previously been observed in T. brucei (Pyrih et al, 2023)."

Page 10:

Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4). Thus, the most enriched proteins are specific to TelR-TALE-YFP-associated chromatin rather than to the TALE-YFP synthetic protein module or other chromatin.

As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression.

Response

See response to point 2, but we reiterate that the ingi-TALE -YFP and 147R-TALE-YFP proteins are well expressed (western original Fig. S3 now Fig. S2) but few proteins are detected as being enriched or correspond to those enriched in TelR-TALE-YFP or TRF-YFP affinity purifications (see Fig. S9). Therefore, the ingi-TALE -YFP and 147R-TALE-YFP proteins provide good additional negative controls for specificity as requested. To further reassure the referee we have also included additional volcano plots which compare TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP to the ingiR-TALE-YFP affinity selection (new Figure S8). As with No-YFP or NonR-TALE-YFP controls, the use of ingiR-TALE-YFP as a negative control demonstrates that known telomere associated proteins are enriched in TelR-TALE-YFP affinity purification, RPA subunits enriched with 70R-TALE-YFP and Kinetochore KKT poroteins enriched with 177R-TALE-YFP. These analyses demonstrate specificity in the proteins enriched following affinity purification of our different TALE-YFPs and provide support to strengthen our original findings.

We now refer to use of No-YFP, NonR-TALE-YFP, and ingiR-TALE -YFP as controls for comparison to TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP in several places:

Page10:

"Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4)."

Page 11:

"Thus, the nuclear ingiR-TALE-YFP provides an additional chromatin-associated negative control for affinity purifications with the TelR-TALE-YFP, 70R-TALE-YFP and 177R-TALE-YFP proteins (Fig. S8)."

"Proteins identified as being enriched with 70R-TALE-YFP (Figure 6D) were similar in comparisons with either the No-YFP, NonR-TALE-YFP or ingiR-TALE-YFP as negative controls."

Top Page 12:

"The same kinetochore proteins were enriched regardless of whether the 177R-TALE proteomics data was compared with No-YFP, NonR-TALE or ingiR-TALE-YFP controls."

Discussion Page 13:

"Regardless, the 147R-TALE and ingiR-TALE proteins were well expressed in T. brucei cells, but their affinity selection did not significantly enrich for any relevant proteins. Thus, 147R-TALE and ingiR-TALE provide reassurance for the overall specificity for proteins enriched TelR-TALE, 70R-TALE and 177R-TALE affinity purifications."

After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE-proteins expressing cultures.

Response

Growth curves for cells expressing TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE-YFP are now included (New Fig S3A). No deficit in growth was evident while passaging 70R-TALE-YFP, 147R-TALE-YFP, NonR-TALE-YFP cell lines (indeed they grew slightly better than controls).

The following text has been added page 8:

"Cell lines expressing representative TALE-YFP proteins displayed no fitness deficit (Fig. S3A)."

Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

Response

In our experimental design, we confirmed bioinformatically that the repeat sequences targeted were not represented elsewhere in the nuclear or mitochondrial genome (kDNA). The absence of subcellular fractionation could result in some cytoplasmic protein selection, but this is unlikely since each TALE targets a specific DNA sequence but is otherwise identical such that cross-selection of the same contaminating protein set would be anticipated if there was significant non-specific binding. We have previously successfully affinity selected 15 chromatin modifiers and identified associated proteins without major issues concerning cytoplasmic protein contamination (Staneva et al 2021 and 2022; PMID: 34407985 and 36169304). Of course, the possibility that some proteins are contaminants will need to be borne in mind in any future follow-up analysis of proteins of interest that we identified as being enriched on specific types of repetitive element in T. brucei. Proteins that are also detected in negative control, or negative affinity selections such as No-YFP, NoR-YFP, IngiR-TALE or 147R-TALE must be disregarded.

'6'. Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction.

Response

As highlighted in response to point 1 the suggested validation and follow up experiments may well not be informative and are beyond the scope of the methodological development presented in this manuscript. Referee 2 describes the study in its current form as "a significant conceptual and technical advancement" and "This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology."

The Referee's phrase 'validate their direct binding to repetitive region(s)' here may also mean to test if any of the additional proteins that we identified as being enriched with a specific TALE protein actually display enrichment over the repeat regions when examined by an orthogonal method. A key unexpected finding was that kinetochore proteins including KKT2 are enriched in our affinity purifications of the 177R-TALE-YFP that targets 177bp repeats (Figure 6F). By conducting ChIP-seq for the kinetochore specific protein KKT2 using YFP-KKT2 we confirmed that KKT2 is indeed enriched on 177bp repeat DNA but not flanking DNA (Figure 7). Moreover, several known telomere-associated proteins are detected in our affinity selections of TelR-TALE-YFP (Figure 6B, FigS6; see also Reis et al, 2018 Nuc. Acids Res. PMID: 29385523; Weisert et al, 2024 Sci. Reports PMID: 39681615).

Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. The answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

Response

See our response to point 1 and the point we labelled '6' above.

Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

Response

As highlighted previously the proposed EMSA experiment may well be uninformative for protein complex components identified in our study or for isolated proteins that directly bind DNA in the context of a complex and chromatin. RNAi knockdown data and cell location data (as well as developmental expression and orthology data) is already available through tritrypDB.org and trtyptag.org

Are the data and the methods presented in such a way that they can be reproduced? Yes

Are the experiments adequately replicated, and statistical analysis adequate? The authors did not mention replicates. There is no statistical analysis mentioned.

Response

The figure legends indicate that all volcano plots of TALE affinity selections were derived from three biological replicates. Cutoffs used for significance: PFor ChiP-seq two biological replicates were analysed for each cell line expressing the specific YFP tagged protein of interest (TALE or KKT2). This is now stated in the relevant figure legends - apologies for this oversight. The resulting data are available for scrutiny at GEO: GSE295698.

Minor comments: -Specific experimental issues that are easily addressable. The following suggestions can be incorporated: 1. Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.

Response

We erroneously added information on several drugs used for selection in our labaoratory. In fact all TALE-YFP construct carry the Bleomycin resistance genes which we select for using Phleomycin. Also, clones were derived by limiting dilution immediately after transfection.

We have amended the text accordingly:

Page 17/18:

"Cell cultures were maintained below 3 x 106 cells/ml. Pleomycin 2.5 mg/ml was used to select transformants containing the TALE construct BleoR gene."

"Electroporated bloodstream cells were added to 30 ml HMI-9 medium and two 10-fold serial dilutions were performed in order to isolate clonal Pleomycin resistant populations from the transfection. 1 ml of transfected cells were plated per well on 24-well plates (1 plate per serial dilution) and incubated at 37{degree sign}C and 5% CO2 for a minimum of 6 h before adding 1 ml media containing 2X concentration Pleomycin (5 mg/ml) per well."

In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?

Response

We thank the reviewer for pointing out this discrepancy. We have checked the latest Tb427v12 genome assembly for predicted NonR-TALE binding sites and there are no exact matches. We have corrected the text accordingly.

Page 7:

"A control NonR-TALE protein was also designed which was predicted to have no target sequence in the T. bruceigenome."

Page 17:

"A control NonR-TALE predicted to have no recognised target in the T. brucei geneome was designed as follows: BLAST searches were used to identify exact matches in the TREU927 reference genome. Candidate sequences with one or more match were discarded."

The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?

Response

We have found that only some anti-GFP antibodies are effective for affinity selection of associated proteins, whereas others are better suited for immunolocalisation. The respective suppliers' antibodies were optimised for each application.

Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?

Response

This value corresponds to the number reported by Consentino et al. 2021 (PMID: 34541528) for subtelomeric VSGs, which is similar to the value reported by Muller et al 2018 (PMID: 30333624) (2486), both in the same strain of trypanosomes as used by us. Based on the earlier analysis by Cross et al (PMID: 24992042), 80% of the identified VSGs in their study (2584) are pseudogenes. This approximates to the estimation by Consentino of 346/2634 (13%) being fully functional VSG genes at subtelomeres, or 17% when considering VSGs at all genomic locations (433/2872).

I found several typos throughout the manuscript.

Response

Thank you for raising this, we have read through the manuscipt several times and hopefully corrected all outstanding typos.

Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Corrected- thank you.

• Are prior studies referenced appropriately? Yes

• Are the text and figures clear and accurate? Yes

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions? Suggested above

Reviewer #1 (Significance (Required)):

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field: This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

• Place the work in the context of the existing literature (provide references, where appropriate). I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

• State what audience might be interested in and influenced by the reported findings. These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

• 1Define your field of expertise with a few keywords to help the authors contextualize your point of view. 2Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. (1) Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes (2) None

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Response Thank you for these positive comments.

Minor Comments

1) Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.

Response

The images presented represent reproducible analyses, and independently verified by two of the authors. Although wider field of view images do not provide the resolution to be informative on cell location, as requested we have provided uncropped images in new Fig. S4 for all the cell lines shown in Figure 2A.

In addition, we have included as supplementary images (Fig. S3B) additional images of TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE YFP localisation to provide additional support their observed locations presented in Figure 1. The set of cells and images presented in Figure 2A and in Fig S3B were prepared and obtained by a different authors, independently and reproducibly validating the location of the tagged protein.

2) I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.

Response

We are grateful for the reviewer's positive view of original Fig. S1 and appreciate the suggestion. We have now moved these analysis to part B of main Figure 2 in the revised manuscript - now Figure 2B. We have also provided additional details in the Methods section on the approaches used to assess background enrichment.

Page 19:

Background enrichment calculation

The genome was divided into 50 bp sliding windows, and each window was annotated based on overlapping genomic features, including CIR147, 177 bp repeats, 70 bp repeats, and telomeric (TTAGGG)n repeats. Windows that did not overlap with any of these annotated repeat elements were defined as "background" regions and used to establish the baseline ChIP-seq signal. Enrichment for each window was calculated using bamCompare, as log₂(IP/Input). To adjust for background signal amongst all samples, enrichment values for each sample were further normalized against the corresponding No-YFP ChIP-seq dataset.

Note: While revising the manuscript we also noticed that the script had a nomalization error. We have therefore included a corrected version of these analyses as Figure 2B (old Fig. S1)

3) Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.

Response

Our ChIP-seq enrichment is calculated by bamCompare. The resulting enrichment values are indeed log2 (IP/Input). We have made this clear in the updated figures/legends.

4) Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.

Response

We thank the reviewer for this suggestion; we have elected to provide a Split-Violin plot instead. This improves the presentation of the data for each centromere. The original violin plot in Figure 4C has been replaced with this Split-Violin plot (still Figure 4C).

5) Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed). Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?

Response

In fact, to save space the X axis was labelled inside each volcano plot but we neglected to indicate that values are a log2 scale indicating enrichment. This has been rectified - see Figure 6, and Fig. S7, S8 and S9.

6) Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFP-KKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)

Response

The CIR147 sequence is found exclusively on megabase-sized chromosomes, while the 177 bp repeats are located on intermediate- and mini-sized chromosomes. Due to limitations in the current genome assembly, it is not possible to reliably classify all chromosomes into intermediate- or mini- sized categories based on their length. Therefore, original Supplementary Fig. S1 presented the YFP-KKT2 enrichment over CIR147 and 177 bp repeats as a representative comparison between megabase chromosomes and the remaining chromosomes (corrected version now presented as main Figure 2B). Additionally, to allow direct comparison of YFP-KKT2 enrichment on CIR147 and 177 bp repeats we have included a new plot in Figure 7C which shows the relative enrichment of YFP-KKT2 on these two repeat types.

We have added the following text , page 12:

"Taking into account the relative to the number of CIR147 and 177 bp repeats in the current T.brucei genome (Cosentino et al., 2021; Rabuffo et al., 2024), comparative analyses demonstrated that YFP-KKT2 is enriched on both CIR147 and 177 bp repeats (Figure 7C)."

7) Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?

Response

Thanks for spotting this. It has been corrected

8) The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly. This is perfectly fine when analysing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work. However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions. Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

Response

We thank the reviewer for their thoughtful comments. Repetitive sequences are indeed challenging to analyze accurately, particularly in the context of short read ChIP-seq data. In our study, we aimed to address YFP-KKT2 enrichment not only over CIR147 repeats but also on 177 bp repeats, using both ChIP-seq and proteomics using synthetic TALE proteins targeted to the different repeat types. We appreciate the referees suggestion to consider uniquely mapped reads, however, in the updated genome assembly, the 177 bp repeats are frequently immediately followed by long stretches of 70 bp repeats which can span several kilobases. The size and repetitive nature of these regions exceeds the resolution limits of ChIP-seq. It is therefore difficult to precisely quantify enrichment across all chromosomes.

Additionally, the repeat sequences are highly similar, and relying solely on uniquely mapped reads would result in the exclusion of most reads originating from these regions, significantly underestimating the relative signals. To address this, we used Bowtie2 with settings that allow multi-mapping, assigning reads randomly among equivalent mapping positions, but ensuring each read is counted only once. This approach is designed to evenly distribute signal across all repetitive regions and preserve a meaningful average.

Single molecule methods such as DiMeLo (Altemose et al. 2022; PMID: 35396487) will need to be developed for T. brucei to allow more accurate and chromosome specific mapping of kinetochore or telomere protein occupancy at repeat-unique sequence boundaries on individual chromosomes.

Reviewer #2 (Significance (Required)):

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Response

Thank you for supporting the novelty and broad interest of our manuscript

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Minor Comments

1. Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.
2. I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.
3. Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.
4. Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.
5. Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed). Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?
6. Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFP-KKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)
7. Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?
8. The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly. This is perfectly fine when analyzing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work. However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions. Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

Significance

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

Summary

In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments:

Are the key conclusions convincing?

The authors reported that they have successfully used TALE-based affinity selection of protein-associated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication. 1. The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept. 2. NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones? 3. As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression. 4. After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE-proteins expressing cultures. 5. Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction. <br /> Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. The answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

Are the data and the methods presented in such a way that they can be reproduced?

Yes

Are the experiments adequately replicated, and statistical analysis adequate?

The authors did not mention replicates. There is no statistical analysis mentioned.

Minor comments:

Specific experimental issues that are easily addressable.

The following suggestions can be incorporated:

1. Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.
2. In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?
3. The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?
4. Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?
5. I found several typos throughout the manuscript.
6. Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Are prior studies referenced appropriately?

Yes

Are the text and figures clear and accurate?

Yes

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Suggested above

Significance

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field:

This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

Place the work in the context of the existing literature (provide references, where appropriate).

I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

State what audience might be interested in and influenced by the reported findings.

These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

1Define your field of expertise with a few keywords to help the authors contextualize your point of view. 2Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

1. Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes
2. None

Impertinent wimdering

Bee

Learn to obey

① Clinical Steps (Klinik Adımlar)

② Taking History & Examination (Hastanın öyküsünü almak ve muayene yapmak)

③ Further Investigations — if needed (Gerekirse ileri tetkikler yapmak)

④ Define the Diagnosis (Tanıyı koymak)

⑤ Determine the Prognosis of the disease (Hastalığın prognozunu belirlemek)

⑥ Plan the Treatment (Tedavi planını yapmak)

⑦ Prognosis is established AFTER the diagnosis is made and BEFORE the treatment plan is established (Prognoz, tanı konulduktan sonra ve tedavi planı yapılmadan önce belirlenir)

① The PREDICTION of the course of a disease (Hastalığın seyriyle ilgili tahmin)

Stage of the disease and how fast is this stage going on (Hastalığın evresi ve bu evrenin ne kadar hızlı ilerlediği)

② The PREDICTION of the duration of a disease (Hastalığın süresiyle ilgili tahmin)

How long does it take for the treatment to be finished (Tedavinin tamamlanmasının ne kadar süreceği)

③ The PREDICTION of the outcomes of a disease (Hastalığın sonuçlarıyla ilgili tahmin)

The results if this case is left untreated or if we treat it (Bu vaka tedavi edilmezse veya tedavi edilirse sonuçlar ne olur)

Açıklama:

Prediction (Prognoz), hastalığın ilerleme hızı, tedavi süresi ve olası sonuçlarını öngörmeyi ifade eder.

Sarah Schindler's article, Architectural Exclusion, reveals that the physical design of cities can function as a means of social exclusion, with roads, bridges, or spatial planning intentionally restricting access for certain groups. This perspective is crucial for modern civil engineering, as it reminds us that infrastructure design is not just about efficiency, but also about equity and spatial inclusivity. On titoreista.com, this idea aligns with the discussion on Civil Engineering DWG and the importance of open design in ensuring equitable and sustainable development.

① Complexity 1 cases may be treated in general practice (Kompleksite 1 vakaları genel pratikte tedavi edilebilir)

② Complexity 2 cases either referred or treated by the GDP (Kompleksite 2 vakaları ya sevk edilir ya da genel diş hekimi tarafından tedavi edilir)

③ Complexity 3 cases mostly referred (Kompleksite 3 vakaları çoğunlukla sevk edilir)

① BPE Score of 4 in any sextant (Herhangi bir sextantta BPE Skoru 4)

Tanım ve Açıklama:

Score 4: Cep derinliği >5.5 mm

Bu, ileri periodontal hastalık ve ciddi doku kaybı anlamına gelir.

② Surgery involving the periodontal tissues (Periodontal dokuları içeren cerrahi)

Açıklama:

BPE Score 4 olan bölgelerde genellikle non-surgical tedavi (temizlik, scaling/root planing) yetersiz kalır.

Cerrahi müdahale gerekebilir:

Flap operasyonu

Kemik rejenerasyonu

Cep derinliğinin azaltılması

Amaç, periodontal cep derinliğini kontrol altına almak ve doku kaybını durdurmak.

Özet:

Score 1–3 → Non-surgical yaklaşım ve takip

Score 4 → Cerrahi tedavi düşünülmeli

Lina M. Khan's article, "Amazon's Antitrust Paradox," shifts perspectives on modern antitrust law by highlighting how digital platform dominance can no longer be measured solely by price or market efficiency. The power of platforms like Amazon stems from their control over data, infrastructure, and digital ecosystems. This concept resonates with reflections on digital civil engineering discussed at https://www.titoreista.com, particularly in the context of Civil Engineering DWG, which now faces similar challenges: reliance on closed systems, data interoperability, and the need for a more open and collaborative design ecosystem.

eLife Assessment

This important study presents JABS, an open-source platform that integrates hardware and user-friendly software for standardized mouse behavioral phenotyping. The work has practical implications for improving reproducibility and accessibility in behavioral neuroscience, especially for linking behavior to genetics across diverse mouse strains. The strength of evidence is convincing, with comprehensive validation of the platform's components and enthusiastic reviewer support.

Reviewer #1 (Public review):

Summary:

This manuscript provides an open-source tool including hardware and software, and dataset to facilitate and standardize behavioral classification in laboratory mice. The hardware for behavioral phenotyping was extensively tested for safety. The software is GUI based facilitating the usage of this tool across the community of investigators that do not have a programming background. The behavioral classification tool is highly accurate, and the authors deposited a large dataset of annotations and pose tracking for many strains of mice. This tool has great potential for behavioral scientists that use mice across many fields, however there are many missing details that currently limit the impact of this tool and publication.

Strengths:

Software-hardware integration for facilitating cross-lab adaptation of the tool and minimizing the need to annotate new data for behavioral classification.

Data from many strains of mice was included in the classification and genetic analyses in this manuscript.

Large dataset annotated was deposited for the use of the community

GUI based software tool decreases barriers of usage across users with limited coding experience.

Weaknesses:

The GUI requires pose tracking for classification but, the software provided in JABS does not do pose tracking, so users must do pose tracking using a separate tool. The pose tracking quality directly impacts the classification quality, given that it is used for the feature calculation

Comments on revisions:

The authors addressed all my concerns.

Reviewer #2 (Public review):

Summary:

This manuscript presents the JAX Animal Behavior System (JABS), an integrated mouse phenotyping platform that includes modules for data acquisition, behavior annotation, and behavior classifier training and sharing. The manuscript provides details and validation for each module, demonstrating JABS as a useful open-source behavior analysis tool that removes barriers to adopting these analysis techniques by the community. In particular, with the JABS-AI module users can download and deploy previously trained classifiers on their own data, or annotate their own data and train their own classifiers. The JABS-AI module also allows users to deploy their classifiers on the JAX strain survey dataset and receive an automated behavior and genetic report.

Strengths:

(1) The JABS platform addresses the critical issue of reproducibility in mouse behavior studies by providing an end-to-end system from rig setup to downstream behavioral and genetic analyses. Each step has clear guidelines, and the GUIs are an excellent way to encourage best practices for data storage, annotation, and model training. Such a platform is especially helpful for labs without prior experience in this type of analysis.

(2) A notable strength of the JABS platform is its reuse of large amounts of previously collected data at JAX Labs, condensing this into pretrained pose estimation models and behavioral classifiers. JABS-AI also provides access to the strain survey dataset through automated classifier analyses, allowing large-scale genetic screening based on simple behavioral classifiers. This has the potential to accelerate research for many labs by identifying particular strains of interest.

(3) The ethograph analysis will be a useful way to compare annotators/classifiers beyond the JABS platform.

Weaknesses:

(1) The manuscript contains many assertions that lack references in both the Introduction and Discussion. For example, in the Discussion, the assertion "published research demonstrates that keypoint detection models maintain robust performance despite the presence of headstages and recording equipment" lacks reference.

(2) The provided GUIs lower the barrier to entry for labs that are just starting to collect and analyze mouse open field behavior data. However, users must run pose estimation themselves outside of the provided GUIs, which introduces a key bottleneck in the processing pipeline, especially for users without strong programming skills. The authors have provided pretrained pose estimation models and an example pipeline, which is certainly to be commended, but I believe the impact of these tools could be greatly magnified by an additional pose estimation GUI (just for running inference, not for labeling/training).

(3) While the manuscript does a good job of laying out best practices, there is an opportunity to further improve reproducibility for users of the platform. The software seems likely to perform well with perfect setups that adhere to the JABS criteria, but it is very likely there will be users with suboptimal setups - poorly constructed rigs, insufficient camera quality, etc. It is important, in these cases, to give users feedback at each stage of the pipeline so they can understand if they have succeeded or not. Quality control (QC) metrics should be computed for raw video data (is the video too dark/bright? are there the expected number of frames? etc.), pose estimation outputs (do the tracked points maintain a reasonable skeleton structure; do they actually move around the arena?), and classifier outputs (what is the incidence rate of 1-3 frame behaviors? a high value could indicate issues). In cases where QC metrics are difficult to define (they are basically always difficult to define), diagnostic figures showing snippets of raw data or simple summary statistics (heatmaps of mouse location in the open field) could be utilized to allow users to catch glaring errors before proceeding to the next stage of the pipeline, or to remove data from their analyses if they observe critical issues.

Comments on revisions:

I thank the authors for taking the time to address my comments. They have provided a lot of important context in their responses. My only remaining recommendation is to incorporate more of this text into the manuscript itself, as this context will also be interesting/important for readers (and potential users) to consider. Specifically:

the quality control/user feedback features that have already been implemented (these are extremely important, and unfortunately, not standard practice in many labs)

top-down vs bottom-up imaging trade-offs (you make very good points!)

video compression, spatial and temporal resolution trade-offs

more detail on why the authors chose pose-based rather than pixel-based classifiers

I believe the proposed system can be extremely useful for behavioral neuroscientists, especially since the top-down freely moving mouse paradigm is one of the most ubiquitous in the field. Many labs have reinvented the wheel here, and as a field it makes sense to coalesce around a set of pipelines and best practices to accelerate the science we all want to do. I make the above recommendation with this in mind: bringing together (properly referenced) observations and experiences of the authors themselves, as well as others in the field, provides a valuable resource for the community. Obviously, the main thrust of the manuscript should be about the tools themselves; it should not turn into a review paper, so I'm just suggesting some additional sentences/references sprinkled throughout as motivation for why the authors made the choices that they did.

Intro typo: "one link in the chainDIY rigs"

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public review):

(1) The authors only report the quality of the classification considering the number of videos used for training, but not considering the number of mice represented or the mouse strain. Therefore, it is unclear if the classification model works equally well in data from all the mouse strains tested, and how many mice are represented in the classifier dataset and validation.

We agree that strain-level performance is critical for assessing generalizability. In the revision we now report per-strain accuracy and F1 for the grooming classifier, which was trained on videos spanning 60 genetically diverse strains (n = 1100 videos) and evaluated on the test set videos spanning 51 genetically diverse strains (n=153 videos). Performance is uniform across most strains (median F1 = 0.94, IQR = 0.899–0.956), with only modest declines in albino lines that lack contrast under infrared illumination; this limitation and potential remedies are discussed in the text. The new per-strain metrics are presented in the Supplementary figure (corresponding to Figure 4).

(2) The GUI requires pose tracking for classification, but the software provided in JABS does not do pose tracking, so users must do pose tracking using a separate tool. Currently, there is no guidance on the pose tracking recommendations and requirements for usage in JABS. The pose tracking quality directly impacts the classification quality, given that it is used for the feature calculation; therefore, this aspect of the data processing should be more carefully considered and described.

We have added a section to the methods describing how to use the pose estimation models used in JABS. The reviewer is correct that pose tracking quality will impact classification quality. We recommend that classifiers should only be re-used on pose files generated by the same pose models used in the behavior classifier training dataset. We hope that the combination of sharing classifier training data and making a more unified framework for developing and comparing classifiers will get us closer to having foundational behavior classification models that work in many environments. We also would like to emphasize that deviating from using our pose model will also likely hinder re-using our shared large datasets in JABS-AI (JABS1200, JABS600, JABS-BxD).

(3) Many statistical and methodological details are not described in the manuscript, limiting the interpretability of the data presented in Figures 4,7-8. There is no clear methods section describing many of the methods used and equations for the metrics used. As an example, there are no details of the CNN used to benchmark the JABS classifier in Figure 4, and no details of the methods used for the metrics reported in Figure 8.

We thank the reviewer for bringing this to our attention. We have added a methods section to the manuscript to address this concern. Specifically, we now provide: (1) improved citation visibility of the source of CNN experiments such that the reader can locate the architecture information, (2) mathematical formulations for all performance metrics (precision, recall, F1, …) with explicit equations;  (3) detailed statistical procedures including permutation testing methods, power analysis and multiple testing corrections used throughout Figures 7-8. These additions facilitate reproducibility and proper interpretation of all quantitative results presented in the manuscript.

Reviewer #2 (Public review):

(1) The manuscript as written lacks much-needed context in multiple areas: what are the commercially available solutions, and how do they compare to JABS (at least in terms of features offered, not necessarily performance)? What are other open-source options?

JABS adds to a list of commercial and open source animal tracking platforms. There are several reviews and resources that cover these technologies. JABS covers hardware, behavior prediction, a shared resource for classifiers, and genetic association studies. We’re not aware of another system that encompasses all these components. Commercial packages such as EthoVision XT and HomeCage Scan give users a ready-made camera-plus-software solution that automatically tracks each mouse and reports simple measures such as distance travelled or time spent in preset zones, but they do not provide open hardware designs, editable behavior classifiers, or any genetics workflow. At the open-source end, the >100 projects catalogued on OpenBehavior and summarised in recent reviews (Luxem et al., 2023; Işık & Ünal 2023) usually cover only one link in the chain—DIY rigs, pose-tracking libraries (e.g., DeepLabCut, SLEAP) or supervised and unsupervised behaviour-classifier pipelines (e.g., SimBA, MARS, JAABA, B-SOiD, DeepEthogram). JABS provides an open source ecosystem that integrates all four: (i) top-down arena hardware with parts list and assembly guide; (ii) an active-learning GUI that produces shareable classifiers; (iii) a public web service that enables sharing of the trained classifier and applies any uploaded classifier to a large and diverse strain survey; and (iv) built-in heritability, genetic-correlation and GWAS reporting. We have added a concise paragraph in the Discussion that cites these resources and makes this end-to-end distinction explicit.

(2) How does the supervised behavioral classification approach relate to the burgeoning field of unsupervised behavioral clustering (e.g., Keypoint-MoSeq, VAME, B-SOiD)? 

The reviewer raises an important point about the rapidly evolving landscape of automated behavioral analysis, where both supervised and unsupervised approaches offer complementary strengths for different experimental contexts. Unsupervised methods like Keypoint-MoSeq , VAME , and B-SOiD , which prioritize motif discovery from unlabeled data but may yield less precise alignments with expert annotations, as evidenced by lower F1 scores in comparative evaluations. Supervised approaches (like ours), by contrast, employ fully supervised classifiers to deliver frame-accurate, behavior-specific scores that align directly with experimental hypotheses. Ultimately, a pragmatic hybrid strategy, starting with unsupervised pilots to identify motifs and transitioning to supervised fine-tuning with minimal labels, can minimize annotation burdens and enhance both discovery and precision in ethological studies. This has been added in the discussion section of the manuscript.

(3) What kind of studies will this combination of open field + pose estimation + supervised classifier be suitable for? What kind of studies is it unsuited for? These are all relevant questions that potential users of this platform will be interested in.

This approach is suitable for a wide array of neuroscience, genetics, pharmacology, preclinical, and ethology studies. We have published in the domains of action detection for complex behaviors such as grooming, gait and posture, frailty, nociception, and sleep. We feel these tools are indispensable for modern behavior analysis. 

(4) Throughout the manuscript, I often find it unclear what is supported by the software/GUI and what is not. For example, does the GUI support uploading videos and running pose estimation, or does this need to be done separately? How many of the analyses in Figures 4-6 are accessible within the GUI?

We have now clarified these. The JABS framework comprises two distinct GUI applications with complementary functionalities. The JABS-AL (active learning) desktop application handles video upload, behavioral annotation, classifier training, and inference -- it does not perform pose estimation, which must be completed separately using our pose tracking pipeline (https://github.com/KumarLabJax/mouse-tracking-runtime). If a user does not want to use our pose tracking pipeline, we have provided conversions through SLEAP to convert to our JABS pose format.  The web-based GUI enables classifier sharing and cloud-based inference on our curated datasets (JABS600, JABS1200) and downstream behavioral statistics and genetic analyses (Figures 4-6). The JABS-AL application also supports CLI (command line interface) operation for batch processing.  We have clarified these distinctions and provided a comprehensive workflow diagram in the revised Methods section.

(5) While the manuscript does a good job of laying out best practices, there is an opportunity to further improve reproducibility for users of the platform. The software seems likely to perform well with perfect setups that adhere to the JABS criteria, but it is very likely that there will be users with suboptimal setups - poorly constructed rigs, insufficient camera quality, etc. It is important, in these cases, to give users feedback at each stage of the pipeline so they can understand if they have succeeded or not. Quality control (QC) metrics should be computed for raw video data (is the video too dark/bright? are there the expected number of frames? etc.), pose estimation outputs (do the tracked points maintain a reasonable skeleton structure; do they actually move around the arena?), and classifier outputs (what is the incidence rate of 1-3 frame behaviors? a high value could indicate issues). In cases where QC metrics are difficult to define (they are basically always difficult to define), diagnostic figures showing snippets of raw data or simple summary statistics (heatmaps of mouse location in the open field) could be utilized to allow users to catch glaring errors before proceeding to the next stage of the pipeline, or to remove data from their analyses if they observe critical issues.

These are excellent suggestions that align with our vision for improving user experience and data quality assessment. We recognize the critical importance of providing users with comprehensive feedback at each stage of the pipeline to ensure optimal performance across diverse experimental setups. Currently, we provide end-users with tools and recommendations to inspect their own data quality. In our released datasets (Strain Survey OFA and BXD OFA), we provide video-level quality summaries for coverage of our pose estimation models. 

For behavior classification quality control, we employ two primary strategies to ensure proper operation: (a) outlier manual validation and (b) leveraging known characteristics about behaviors. For each behavior that we predict on datasets, we manually inspect the highest and lowest expressions of this behavior to ensure that the new dataset we applied it to maintains sufficient similarity. For specific behavior classifiers, we utilize known behavioral characteristics to identify potentially compromised predictions. As the reviewer suggested, high incidence rates of 1-3 frame bouts for behaviors that typically last multiple seconds would indicate performance issues.

We currently maintain in-house post-processing scripts that handle quality control according to our specific use cases. Future releases of JABS will incorporate generalized versions of these scripts, integrating comprehensive QC capabilities directly into the platform. This will provide users with automated feedback on video quality, pose estimation accuracy, and classifier performance, along with diagnostic visualizations such as movement heatmaps and behavioral summary statistics.

Reviewer #1 (Recommendations for the authors):

(1) A weakness of this tool is that it requires pose tracking, but the manuscript does not detail how pose tracking should be done and whether users should expect that the data deposited will help their pose tracking models. There is no specification on how to generate pose tracking that will be compatible with JABS. The classification quality is directly linked to the quality of the pose tracking. The authors should provide more details of the requirements of the pose tracking (skeleton used) and what pose tracking tools are compatible with JABS. In the user website link, I found no such information. Ideally, JABS would be integrated with the pose tracking tool into a single pipeline. If that is not possible, then the utility of this tool relies on more clarity on which pose tracking tools are compatible with JABS.

The JABS ecosystem was deliberately designed with modularity in mind, separating the pose estimation pipeline from the active learning and classification app (JABS-AL) to offer greater flexibility and scalability for users working across diverse experimental setups. Our pose estimation pipeline is documented in detail within the new Methods subsection, outlining the steps to obtain JABS-compatible keypoints with our recommended runtime (https://github.com/KumarLabJax/mouse-tracking-runtime) and frozen inference models (https://github.com/KumarLabJax/deep-hrnet-mouse). This pipeline is an independent component within the broader JABS workflow, generating skeletonized keypoint data that are then fed into the JABS-AL application for behavior annotation and classifier training.

By maintaining this separation, users have the option to use their preferred pose tracking tools— such as SLEAP —while ensuring compatibility through provided conversion utilities to the JABS skeleton format. These details, including usage instructions and compatibility guidance, are now thoroughly explained in the newly added pose estimation subsection of our Methods section. This modular design approach ensures that users benefit from best-in-class tracking while retaining the full power and reproducibility of our active learning pipeline.

(2) The authors should justify why JAABA was chosen to benchmark their classifier. This tool was published in 2013, and there have been other classification tools (e.g., SIMBA) published since then.  

We appreciate the reviewer’s suggestion regarding SIMBA. However, our comparisons to JAABA and a CNN are based on results from prior work (Geuther, Brian Q., et al. "Action detection using a neural network elucidates the genetics of mouse grooming behavior." Elife 10 (2021): e63207.), where both were used to benchmark performance on our publicly released dataset. In this study, we introduce JABS as a new approach and compare it against those established baselines. While SIMBA may indeed offer competitive performance, we believe the responsibility to demonstrate this lies with SIMBA’s authors, especially given the availability of our dataset for benchmarking.

(3) I had a lot of trouble understanding the elements of the data calculated in JABS vs outside of JABS. This should be clarified in the manuscript.

(a) For example, it was not intuitive that pose tracking was required and had to be done separately from the JABS pipeline. The diagrams and figures should more clearly indicate that.

(b) In section 2.5, are any of those metrics calculated by JABS? Another software GEMMA, but no citation is provided for this tool. This created ambiguity regarding whether this is an analysis that is separate from JABS or integrated into the pipeline.  

We acknowledge the confusion regarding the delineation between JABS components and external tools, and we have comprehensively addressed this throughout the manuscript. The JABS ecosystem consists of three integrated modules: JABS-DA (data acquisition), JABS-AL (active learning for behavior annotation and classifier training), and JABS-AI (analysis and integration via web application). Pose estimation, while developed by our laboratory, operates as a preprocessing pipeline that generates the keypoint coordinates required for subsequent JABS classifier training and annotation workflows. We have now added a dedicated Methods subsection that explicitly maps each analytical step to its corresponding software component, clearly distinguishing between core JABS modules and external tools (such as GEMMA for genetic analysis). Additionally, we have provided proper citations and code repositories for all external pipelines to ensure complete transparency regarding the computational workflow and enable full reproducibility of our analyses.

(4) There needs to be clearer explanations of all metrics, methods, and transformations of the data reported.

(a) There is very little information about the architecture of the classification model that JABS uses.

(b) There are no details on the CNN used for comparing and benchmarking the classifier in JABS.

(c) Unclear how the z-scoring of the behavioral data in Figure 7 was implemented.

(d) There is currently no information on how the metrics in Figure 8 are calculated.

We have added a comprehensive Methods section that not only addresses the specific concerns raised above but provides complete methodological transparency throughout our study. This expanded section includes detailed descriptions of all computational architectures (including the JABS classifier and grooming benchmark models and metrics), statistical procedures and data transformations (including the z-scoring methodology for Figure 7), downstream genetic analysis (including all measures presented in Figure 8), and preprocessing pipelines. 

(5) The authors talk about their datasets having visual diversity, but without seeing examples, it is hard to know what they mean by this visual diversity. Ideally, the manuscript would have a supplementary figure with a representation of the variety of setups and visual diversity represented in the datasets used to train the model. This is important so that readers can quickly assess from reading the manuscript if the pre-trained classifier models could be used with the experimental data they have collected.

The visual diversity of our training datasets has been comprehensively documented in our previous tracking work (https://www.nature.com/articles/s42003-019-0362-1), which systematically demonstrates tracking performance across mice with diverse coat colors (black, agouti, albino, gray, brown, nude, piebald), body sizes including obese mice, and challenging recording conditions with dynamic lighting and complex environments. Notably, Figure 3B in that publication specifically illustrates the robustness across coat colors and body shapes that characterize the visual diversity in our current classifier training data. To address the reviewer's concern and enable readers to quickly assess the applicability of our pre-trained models to their experimental data, we have now added this reference to the manuscript to ground our claims of visual diversity in published evidence.

(6) All figures have a lot of acronyms used that are not defined in the figure legend. This makes the figures really hard to follow. The figure legends for Figures 1,2, 7, and 9 did not have sufficient information for me to comprehend the figure shown.

We have fixed this in the manuscript. 

(7) In the introduction, the authors talk about compression artifacts that can be introduced in camera software defaults. This is very vague without specific examples.

This is a complex topic that balances the size and quality of video data and is beyond the scope of this paper. We have carefully optimized this parameter and given the user a balanced solution. A more detailed blog post on compression artifacts can be found at our lab’s webpage (https://www.kumarlab.org/2018/11/06/brians-video-compression-tests/). We have also added a comment about keyframes shifting temporal features in the main manuscript. 

(8) More visuals of the inside of the apparatus should be included as supplementary figures. For example, to see the IR LEDs surrounding the camera.

We have shared data from JABS as part of several papers including the tracking paper (Geuther et al 2019), grooming, gait and posture, mouse mass. We have also released entire datasets that as part of this paper (JABS1800, JABS-BXD). We also have step by step assembly guide that shows the location of the lights/cameras and other parts (see Methods, JABS workflow guide, and this PowerPoint file in the GitHub repository (https://github.com/KumarLabJax/JABS-datapipeline/blob/main/Multi-day%20setup%20PowerPoint%20V3.pptx).

(9) Figure 2 suggests that you could have multiple data acquisition systems simultaneously. Do each require a separate computer? And then these are not synchronized data across all boxes?

Each JABS-DA unit has its own edge device (Nvidia Jetson). Each system (which we define as multiple JABS-DA areas associated with one lab/group) can have multiple recording devices (arenas). The system requires only 1 control portal (RPi computer) and can handle as many recording devices as needed (Nvidia computer w/ camera associated with each JABS-DA arena). To collect data, 1 additional computer is needed to visit the web control portal and initiate a recording session. Since this is a web portal, users can use any computer or a tablet. The recording devices are not strictly synchronized but can be controlled in a unified manner.

(10) The list of parts on GitHub seems incomplete; many part names are not there.

We thank referee for bringing this to our attention. We have updated the GitHub repository (and its README) which now links out to the design files. 

(11) The authors should consider adding guidance on how tethers and headstages are expected to impact the use of JABS, as many labs would be doing behavioral experiments combined with brain measurements.

While our pose estimation model was not specifically trained on tethered animals, published research demonstrates that keypoint detection models maintain robust performance despite the presence of headstages and recording equipment. Once accurate pose coordinates are extracted, the downstream behavior classification pipeline operates independently of the pose estimation method and would remain fully functional. We recommend users validate pose estimation accuracy in their specific experimental setup, as the behavior classification component itself is agnostic to the source of pose coordinates.

Reviewer #2 (Recommendations for the authors):

(1) "Using software-defaults will introduce compression artifacts into the video and will affect algorithm performance." Can this be quantified? I imagine most of the performance hit comes from a decrease in pose estimation quality. How does a decrease in pose estimation quality translate to action segmentation? Providing guidelines to potential users (e.g., showing plots of video compression vs classifier performance) would provide valuable information for anyone looking to use this system (and could save many labs countless hours replicating this experiment themselves). A relevant reference for the effect of compression on pose estimation is Mathis, Warren 2018 (bioRxiv): On the inference speed and video-compression robustness of DeepLabCut.

Since our behavior classification approach depends on features derived from keypoint, changes in keypoint accuracy will affect behavior segmentation accuracy. We agree that it is important to try and understand this further, particularly with the shared bioRxiv paper investigating the effect of compression on pose estimation accuracy. Measuring the effect of compression on keypoint and behavior classification is a complex task to evaluate concisely, given the number of potential variables to inspect. To list a few variables that should be investigated are: discrete cosine transform quality (Mathis, Warren experiment), Frame Size (Mathis, Warren experiment), Keyframe Interval (new, unique to video data), inter-frame settings (new, unique to video data), behavior of interest, Pose models with compression-augmentation used in training ( https://arxiv.org/pdf/1506.08316?) and type of CNN used (under active development). The simplest recommendation that we can make at this time is that we know compression will affect behavior predictions and that users should be cautious about using our shared classifiers on compressed video data. To show that we are dedicated in sharing these results as we run those experiments, in a related work ( CV4Animals conference accepted paper (https://www.cv4animals.com/) and can be downloaded here https://drive.google.com/file/d/1UNQIgCUOqXQh3vcJbM4QuQrq02HudBLD/view) we have already begun to inspect how changing some factors affect behavior segmentation performance. In this work, we investigate the robustness of behavior classification across multiple behaviors using different keypoint subsets. Our findings in this work is that classifiers are relatively stable across different keypoint subsets. We are actively working on follow-up effort to investigate the effect of keypoint noise, CNN model architecture, and other factors we've listed above on behavior segmentation tasks.

(2) The analysis of inter-annotator variability is very interesting. I'm curious how these differences compare to two other types of variability:

(a) intra-annotator variability; I think this is actually hard to quantify with the presented annotation workflow. If a given annotator re-annotated a set of videos, but using different sparse subsets of the data, it is not possible to disentangle annotator variability versus the effect of training models on different subsets of data. This can only be rigorously quantified if all frames are labeled in each video.

We propose an alternative approach to behavior classifier development in the text associated with Figure 3C. We do not advocate for high inter-annotator agreement since individual behavior experts have differing labeling style (an intuitive understanding of the behavior). Rather, we allow multiple classifiers for the same behavior and allow the end user to prioritize classifiers based on heritability of the behavior from a classifier.  

(b) In lieu of this, I'd be curious to see the variability in model outputs trained on data from a single annotator, but using different random seeds or train/val splits of the data. This analysis would provide useful null distributions for each annotator and allow for more rigorous statistical arguments about inter-annotator variability. 

JABS allows the user to use multiple classifiers (random forest, XGBoost). We do not expect the user to carry out hyperparameter tuning or other forms of optimization. We find that the major increase in performance comes from optimizing the size of the window features and folds of cross validation. However, future versions of JABS-AL could enable a complete hyper-parameter scan across seeds and data splits to obtain a null distribution for each annotator. 

(c) I appreciate the open-sourcing of the video/pose datasets. The authors might also consider publicly releasing their pose estimation and classifier training datasets (i.e., data plus annotations) for use by method developers.

We thank the referee for acknowledging our commitment to open data sharing practices. Building upon our previously released strain survey dataset, we have now also made our complete classifier training resources publicly available, including the experimental videos, extracted pose coordinates, and behavioral annotations. The repository link has been added to the manuscript to ensure full reproducibility and facilitate community adoption of our methods.  

(3) More thorough discussion on the limitations of the top-down vs bottom-up camera viewpoint; are there particular scientific questions that are much better suited to bottomup videos (e.g., questions about paw tremors, etc.).

Top-down imaging, bottom-up, and multi-view imaging have a variety of pros and cons. Generally speaking, multi-view imaging will provide the most accurate pose models but requires increased resources on both hardware setup as well as processing of data. Top-down provides the advantage of flexibility for materials, since the floor doesn’t need to be transparent. Additionally lighting and potential reflection with the bottom-up perspective. Since the paws are not occluded from the bottom-up perspective, models should have improved paw keypoint precision allowing the model to observe more subtle behaviors. However, the appearance of the arena floor will change over time as the mice defecate and urinate. Care must be taken to clean the arena between recordings to ensure transparency is maintained. This doesn’t impact top-down imaging that much but will occlude or distort from the bottom-up perspective. Additionally, the inclusion of bedding for longer recordings, which is required by IACUC, will essentially render bottom-up imaging useless because the bedding will completely obscure the mouse. Overall, while bottomup may provide a precision benefit that will greatly enhance subtle motion, top-down imaging is overall more robust for obtaining consistent imaging across large experiments for longer periods of time.

(4) More thorough discussion on what kind of experiments would warrant higher spatial or temporal resolution (e.g., investigating slight tremors in a mouse model of neurodegenerative disease might require this greater resolution).

This is an important topic that deserves its own perspective guide. We try to capture some of this in the paper on specifications. However, we only scratch the surface. Overall, there are tradeoffs between frame rate, resolution, color/monochrome, and compression. Labs have collected data at hundreds of frames per second to capture the kinetics of reflexive behavior for pain (AbdoosSaboor lab) or whisking behavior. Labs have also collected data a low 2.5 frames per second for tracking activity or centroid tracking (see Kumar et al PNAS). The data collection specifications are largely dependent on the behaviors being captured. Our rule of thumb is the Nyquist Limit, which states that the data capture rate needs to be twice that of the frequency of the event. For example, certain syntaxes of grooming occur at 7Hz and we need 14FPS to capture this data. JABS collects data at 30FPS, which is a good compromise between data load and behavior rate. We use 800x800 pixel resolution which is a good compromise to capture animal body parts while limiting data size. Thank you for providing the feedback that the field needs guidance on this topic. We will work on creating such guidance documents for video data acquisition parameters to capture animal behavior data for the community as a separate publication.

(5) References 

(a) Should add the following ref when JAABA/MARS are referenced: Goodwin et al.2024, Nat Neuro (SimBA)

(b) Could also add Bohnslav et al. 2021, eLife (DeepEthogram).

(c) The SuperAnimal DLC paper (Ye et al. 2024, Nature Comms) is relevant to the introduction/discussion as well.

We thank the referee for the suggestions. We have added these references.  

(6) Section 2.2:

While I appreciate the thoroughness with which the authors investigated environmental differences in the JABS arena vs standard wean cage, this section is quite long and eventually distracted me from the overall flow of the exposition; might be worth considering putting some of the more technical details in the methods/appendix.

These are important data for adopters of JABS to gain IACUC approval in their home institution. These committees require evidence that any new animal housing environment has been shown to be safe for the animals. In the development of JABS, we spent a significant amount of time addressing the JAX veterinary and IACUC concerns. Therefore, we propose that these data deserve to be in the main text. 

(7) Section 2.3.1:

(a) Should again add the DeepEthogram reference here

(b) Should reference some pose estimation papers: DeepLabCut, SLEAP, Lightning Pose. 

We thank the referee for the suggestions. We have added these references.  

(c) "Pose based approach offers the flexibility to use the identified poses for training classifiers for multiple behaviors" - I'm not sure I understand why this wouldn't be possible with the pixel-based approach. Is the concern about the speed of model training? If so, please make this clearer.

The advantage lies not just in training speed, but in the transferability and generalization of the learned representations. Pose-based approaches create structured, low-dimensional latent embeddings that capture behaviorally relevant features which can be readily repurposed across different behavioral classification tasks, whereas pixel-based methods require retraining the entire feature extraction pipeline for each new behavior. Recent work demonstrates that pose-based models achieve greater data efficiency when fine-tuned for new tasks compared to pixel-based transfer learning approaches [1], and latent behavioral representations can be partitioned into interpretable subspaces that generalize across different experimental contexts [2]. While pixel-based approaches can achieve higher accuracy on specific tasks, they suffer from the "curse of dimensionality" (requiring thousands of pixels vs. 12 pose coordinates per frame) and lack the semantic structure that makes pose-based features inherently reusable for downstream behavioral analysis.

(1) Ye, Shaokai, et al. "SuperAnimal pretrained pose estimation models for behavioral analysis." Nature communications 15.1 (2024): 5165.

(2) Whiteway, Matthew R., et al. "Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders." PLoS computational biology 17.9 (2021): e1009439.  

(d) The pose estimation portion of the pipeline needs more detail. Do users use a pretrained network, or do they need to label their own frames and train their own pose estimator? If the former, does that pre-trained network ship with the software? Is it easy to run inference on new videos from a GUI or scripts? How accurate is it in compliant setups built outside of JAX? How long does it take to process videos?

We have added the guidance on pose estimation in the manuscript (section “2.3.1 Behavior annotation and classifier training” and in the methods section titled “Pose tracking pipeline”)

(e) The final paragraph describing how to arrive at an optimal classifier is a bit confusing - is this the process that is facilitated by the app, or is this merely a recommendation for best practices? If this is the process the app requires, is it indeed true that multiple annotators are required? While obviously good practice, I imagine there will be many labs that just want a single person to annotate, at least in the beginning prototyping stages. Will the app allow training a model with just a single annotator?

We have clarified this in the text. 

(8) Section 2.5:

(a) This section contained a lot of technical details that I found confusing/opaque, and didn't add much to my overall understanding of the system; sec 2.6 did a good job of clarifying why 2.5 is important. It might be worth motivating 2.5 by including the content of 2.6 first, and moving some of the details of 2.5 to the method/appendix.

We moved some of the technical details in section 2.5 to the methods section titled “Genetic analysis”. Furthermore, we have added few statements to motivate the need of genetic analysis and how the webapp can facilitate this (which is introduced in the section 2.6)    

(9) Minor corrections:

(a) Bottom of first page, "always been behavior quantification task" missing "a".

(b) "Type" column in Table S2 is undocumented and unused (i.e., all values are the same); consider removing.

(c) Figure 4B, x-axis: add units.

(d) Page 8/9: all panel references to Figure S1 are off by one

We have fixed them in the updated manuscript.

**Added to Goodreads **

Predictive, Diagnostic, Oncogenic evidence:

Predictive: The abstract mentions that NF1 mutant melanomas can be effectively treated with EGFR inhibitors, indicating a correlation between the variant and response to therapy.

Diagnostic: The results section describes the identification of mutational profiles in melanoma samples, specifically noting that C>T transitions are characteristic of cutaneous melanoma, which supports the use of this variant in defining the disease subtype.

Oncogenic: The results highlight that the C>T transitions are part of the mutational spectra associated with cutaneous melanoma, suggesting that these somatic variants contribute to tumor development or progression.

Diagnostic, Oncogenic evidence:

Diagnostic: The study mentions that six (4%) of the GBM tumors were IDH1 p.R132H-mutated, indicating that this variant is used to classify or confirm a specific subtype of the disease, which aligns with the definition of a diagnostic evidence type.

Oncogenic: The presence of the IDH1 p.R132H mutation in the tumors suggests that this somatic variant contributes to tumor development or progression, which is characteristic of oncogenic evidence.

nan evidence:

Based on the provided abstract and results section, there is no specific mention of any variants or their implications. Therefore, I cannot classify any evidence types as there are no relevant statements to support any of the CIViC evidence types.

Diagnostic, Functional evidence:

Diagnostic: The abstract discusses the improvement in the accuracy of diagnosis for diffuse gliomas, indicating that the study evaluates genetic/clinical correlations, which may include the variant C228T as part of the diagnostic criteria for glioma classification.

Functional: The results section mentions the mutational analysis of the TERT promoter, specifically referring to the C228T variant, which implies that this variant is being analyzed for its molecular characteristics, such as its role in the context of tumor genetics.

Predictive, Functional evidence:

Functional: The study discusses how the mispairing of guanine with thymine during DNA replication, specifically the O6-meG/T mismatch, alters the cellular response to temozolomide treatment by initiating futile cycles of the mismatch repair machinery, leading to DNA damage and cell death. This indicates a change in molecular function due to the variant's presence.

Predictive: The abstract mentions that promoter methylation-mediated silencing of MGMT is associated with increased sensitivity towards temozolomide, suggesting that the guanine-thymine mispairing impacts the response to this specific therapy. This correlation indicates a predictive relationship between the variant and treatment outcome.

nan evidence:

There is no information provided in the abstract or results section regarding the variant(s) mentioned in the paper. Therefore, I cannot classify any evidence types based on the given text.

Diagnostic, Oncogenic evidence:

Diagnostic: The study identifies a de novo pathogenic variant in ELOC (c.236A>G, p.Tyr79Cys) in a proband with VHL disease, suggesting that genetic testing for ELOC variants should be performed in individuals with suspected VHL disease who do not have detectable VHL variants. This indicates the variant's role in classifying or confirming the disease.

Oncogenic: The p.Tyr79Cys substitution is described as a mutational hotspot in sporadic VHL-competent RCC and has been shown to mimic the effects of pVHL deficiency on hypoxic signaling, indicating its contribution to tumor development or progression. This supports the classification of the variant as oncogenic due to its association with cancer-related mechanisms.

Predictive, Oncogenic evidence:

Predictive: The study indicates that AR gene rearrangements in CRPC tumors are associated with resistance to endocrine therapies, specifically mentioning that cell lines with these rearrangements were resistant to the AR antagonist enzalutamide. This suggests a correlation between the variant and treatment response, classifying it as predictive evidence.

Oncogenic: The abstract describes AR gene rearrangements as contributing to the development and progression of CRPC, highlighting their role in promoting the expression of tumor-specific AR variants. This supports the classification of the variant as oncogenic due to its involvement in tumor development.

Predictive, Oncogenic evidence:

Predictive: The study indicates that AR gene rearrangements in CRPC tumors are associated with resistance to endocrine therapies, specifically mentioning that cell lines with these rearrangements were resistant to the AR antagonist enzalutamide. This suggests a correlation between the variant and treatment response, classifying it as predictive evidence.

Oncogenic: The abstract describes AR gene rearrangements as contributing to the development and progression of CRPC, highlighting their role in promoting the expression of tumor-specific AR variants. This supports the classification of the variant as oncogenic due to its involvement in tumor development.

Predictive, Oncogenic evidence:

Predictive: The study indicates that AR gene rearrangements in CRPC tumors are associated with resistance to endocrine therapies, specifically mentioning that cell lines with these rearrangements were resistant to the AR antagonist enzalutamide. This suggests a correlation between the variant and treatment response, classifying it as predictive evidence.

Oncogenic: The abstract states that AR gene rearrangements contribute to the development and progression of CRPC, highlighting their role in tumor-specific AR variant expression. This supports the classification of the variant as oncogenic due to its involvement in tumor development.

Oncogenic evidence:

Oncogenic: The study identifies the 1520C>A mutation (T507K) in the PTPN11 gene as contributing to tumor development, as evidenced by its ability to induce transformed foci in NIH3T3 cells and promote tumor formation in nude mice, indicating its role as an oncoprotein in solid tumors.

Diagnostic evidence:

Diagnostic: The study discusses the potential diagnostic utility of the TRPS1::PLAG1 fusion for determining tumor origin, indicating that this variant can help classify and identify the type of tumor present. The mention of recurrent gene fusions in CMTs and their association with specific histological features further supports its role in disease classification.

Oncogenic evidence:

Oncogenic: The study identifies structural rearrangements involving the PLAG1 gene in chondroid syringomas, specifically the formation of NDRG1-PLAG1 and TRPS1-PLAG1 fusion transcripts, which suggests that these somatic variants contribute to tumor development or progression.

Oncogenic evidence:

Oncogenic: The study identifies structural rearrangements involving the PLAG1 gene in chondroid syringomas, specifically the NDRG1-PLAG1 and TRPS1-PLAG1 fusion transcripts, indicating that these somatic variants contribute to tumor development. The presence of these fusion genes suggests a role in the oncogenic process associated with this type of tumor.

Predictive, Oncogenic evidence:

Predictive: The variant FGFR1 p.V561M is described as imparting resistance to FGFR inhibitors, indicating its role in predicting treatment response and resistance to therapy in the context of pilomyxoid astrocytomas.

Oncogenic: The study identifies the FGFR1 p.V561M variant as a gatekeeper mutation that contributes to tumor development by imparting resistance to inhibitors, suggesting its role in the oncogenic process of pilomyxoid astrocytomas.

Predictive, Oncogenic evidence:

Predictive: The variant FGFR1 p.V561M is described as imparting resistance to FGFR inhibitors, indicating its role in predicting treatment response and resistance in the context of therapy for pilomyxoid astrocytomas.

Oncogenic: The study identifies the FGFR1 p.V561M variant as a gatekeeper mutation that contributes to the tumor's characteristics, suggesting its involvement in tumor development or progression.

Predictive, Diagnostic evidence:

Diagnostic: The study discusses the use of FISH analysis for screening ABL1 fusions in pediatric acute lymphoblastic leukemia (ALL), indicating that the presence of the NUP214-ABL1 fusion can be used to classify or confirm the disease. This suggests that the variant is associated with a specific subtype of leukemia, fulfilling the criteria for diagnostic evidence.

Predictive: The abstract mentions that ABL1 fusions are potentially targetable by kinase inhibitors, indicating a correlation between the presence of this variant and the response to specific therapies. This aligns with predictive evidence as it suggests that the variant may influence treatment options.

Functional evidence:

Functional: The variant p.Ser695Leu in EZH2 is mentioned in the context of sequencing results, indicating that it is a mutation found in the patient. This suggests that the variant may alter the molecular function of the EZH2 protein, which is relevant to its role in cancer biology.

Oncogenic evidence:

Oncogenic: The study discusses the mechanism by which SRA737 and PARPi synergistically inhibit tumor cell growth, indicating that the variant S3C is involved in tumor development or progression, particularly in the context of PARPi-resistant cell lines. This suggests that the variant contributes to the oncogenic processes in these cancer cells.

Predictive, Diagnostic evidence:

Predictive: The study discusses the addition of pembrolizumab to chemotherapy and its impact on disease-free survival (DFS) in patients with dMMR endometrial cancer, indicating a correlation between the dMMR phenotype and treatment response. The results show a significant hazard ratio for DFS in the dMMR population, suggesting that the variant's presence may predict a better response to the therapy.

Diagnostic: The abstract mentions the classification of patients based on their dMMR status, which is used to define a specific subtype of endometrial cancer. This indicates that the dMMR variant is associated with a particular disease phenotype, supporting its role as a diagnostic marker.

Predictive, Prognostic evidence:

Predictive: The study reports that patients with dMMR/MSI-H endometrial cancer treated with dostarlimab plus carboplatin-paclitaxel had a statistically significant reduction in the risk of death, indicating that the variant correlates with response to this specific therapy. The mention of hazard ratios and the context of treatment response supports this classification.

Prognostic: The results indicate a statistically significant overall survival benefit in patients treated with dostarlimab, with a specific hazard ratio reported for the dMMR/MSI-H population, suggesting that the variant correlates with disease outcome independent of therapy. This aligns with the definition of prognostic evidence.

Predictive, Prognostic evidence:

Predictive: The study discusses the significant increase in progression-free survival among patients with dMMR-MSI-H tumors treated with dostarlimab, indicating that the variant correlates with response to this specific therapy. The results show a marked difference in progression-free survival rates between the dostarlimab and placebo groups, highlighting the predictive nature of the variant in relation to treatment efficacy.

Prognostic: The results also provide data on overall survival rates at 24 months, suggesting that the presence of the dMMR-MSI-H variant correlates with better survival outcomes independent of therapy. The hazard ratios reported for both progression-free survival and overall survival indicate that this variant has prognostic implications for patients with endometrial cancer.

Predictive, Oncogenic evidence:

Predictive: The study discusses how alterations in specific tumor suppressor genes, including the Kras G12D variant, can identify patients likely to benefit from immune checkpoint inhibitors combined with chemotherapy, indicating a correlation with treatment response.

Oncogenic: The variant Kras G12D is part of a genetically engineered model used to assess its role in promoting tumor growth, demonstrating its contribution to tumor development in the context of lung cancer.

Predictive, Diagnostic evidence:

Predictive: The study investigates the efficacy of Debio 1347, a selective inhibitor targeting FGFR1-3 fusions, in patients with solid tumors harboring these fusions, indicating a focus on treatment response. The mention of "objective response rate (ORR)" and the evaluation of efficacy directly relates to the predictive nature of the variant's impact on therapy response.

Diagnostic: The abstract states that the trial involved patients with tumors "harboring a functional FGFR1-3 fusion," which implies that the presence of these fusions is used to classify or define the patient population for the study, thus supporting a diagnostic classification.

Predictive, Diagnostic evidence:

Diagnostic: The study discusses the t(4;14) translocation as a characteristic found in approximately 15% of patients with multiple myeloma, indicating its role in classifying patients based on their genetic status. This classification is essential for understanding the disease and tailoring treatment approaches.

Predictive: The study evaluates the efficacy of dovitinib, an RTK inhibitor, in patients with relapsed or refractory multiple myeloma, specifically assessing the treatment response based on the presence of the t(4;14) translocation. The mention of treatment response rates in relation to the t(4;14) status suggests a predictive relationship between the variant and therapy outcomes.

Predictive, Oncogenic evidence:

Predictive: The study discusses the efficacy of fexagratinib, an FGFR inhibitor, in patients with recurrent FGFR-TACC + high-grade gliomas, indicating a correlation between the FGFR-TACC fusion and response to this specific therapy. The mention of a 32-gene signature associated with the benefit of FGFR inhibition further supports the predictive nature of the variant in relation to treatment response.

Oncogenic: The abstract states that FGFR-TACC fusions are oncogenic and present in high-grade gliomas, indicating that these somatic variants contribute to tumor development or progression. This classification is supported by the context of the study focusing on the safety and efficacy of a treatment targeting these specific fusions.

Oncogenic evidence:

Oncogenic: The variant K27M is associated with the histone H3 K27M mutant protein, which is known to contribute to tumor development or progression in certain cancers, particularly gliomas. The mention of this specific mutant protein in the results section indicates its role in oncogenesis.

Diagnostic evidence:

Diagnostic: The abstract discusses HGAP as an important consideration in the differential diagnosis of isocitrate dehydrogenase-wild-type gliomas, indicating that the variant is used to classify or define a disease subtype. Additionally, it mentions the association with neurofibromatosis 1 syndrome, further supporting its role in diagnosis.

Diagnostic, Predisposing evidence:

Diagnostic: The study discusses the identification of germline mutations in patients with pheochromocytomas and paragangliomas (PPGLs), indicating that these variants can lead to an early diagnosis of multiple or more aggressive tumors, which aligns with the use of variants to define or confirm a disease.

Predisposing: The mention of germline mutations in patients with PPGLs suggests an inherited risk for developing these tumors, particularly in younger patients, which supports the classification of these variants as predisposing.

Predictive, Prognostic, Oncogenic evidence:

Predictive: The study discusses the variant G2032R in the context of acquired resistance mutations, indicating that taletrectinib shows robust activity against this variant, which correlates with treatment response. This suggests that the presence of G2032R may influence the effectiveness of taletrectinib therapy in patients with NSCLC.

Prognostic: The results mention prolonged progression-free survival associated with taletrectinib treatment, which implies that the presence of the G2032R variant may correlate with disease outcome independent of therapy. This indicates that the variant could have implications for patient prognosis in the context of treatment with taletrectinib.

Oncogenic: The mention of G2032R as an acquired resistance mutation suggests that it contributes to tumor progression or development, particularly in the context of resistance to therapy. This aligns with the definition of an oncogenic variant, as it is involved in the cancer's response to treatment.

Predictive, Oncogenic evidence:

Predictive: The study discusses the drug sensitivity and resistance of the exon 20 insertion variants, specifically mentioning that they have lower sensitivity to 1st-3rd generation EGFR TKIs and that newer inhibitors like BAY-568, TAS6417, and TAK-788 show selective inhibition, indicating a correlation with treatment response.

Oncogenic: The abstract highlights that somatic mutations in EGFR, including the exon 20 insertions, are frequent drivers of non-small cell lung cancer (NSCLC), which supports the notion that these variants contribute to tumor development and progression.

Predictive evidence:

Predictive: The study demonstrates that treatment with osimertinib significantly improves progression-free survival in patients with unresectable EGFR-mutated NSCLC, indicating a correlation between the EGFR mutation and response to this specific therapy. The results show a median progression-free survival of 39.1 months with osimertinib compared to 5.6 months with placebo, highlighting the predictive nature of the EGFR variant in treatment outcomes.

Predictive, Diagnostic evidence:

Diagnostic: The variant M34 is associated with the pathology diagnosis of LUSC (lung squamous cell carcinoma) in the context of the study, indicating its relevance in defining or classifying this disease subtype.

Predictive: The results indicate that patients with the M34 variant received first-line treatment with chemo+pembrolizumab, and the best response was complete response (CR), suggesting a correlation between this variant and treatment response.

Prognostic, Functional evidence:

Prognostic: The abstract mentions that "Osteosarcoma (OS) patients with metastasis or recurrent tumors still suffer from poor prognosis," indicating a correlation between the variant and disease outcome independent of therapy.

Functional: The study discusses how treatment with the DNA demethylating agent 5-aza-2'-deoxycytidine (5-aza-dC) "markedly suppressed their growth" and "multiple tumor-suppressor and osteo/chondrogenesis-related genes were re-activated," suggesting that the variant alters molecular function related to gene expression and cellular behavior.

Predictive evidence:

Predictive: The abstract indicates that selective TRK inhibition by larotrectinib is a therapeutic option specifically for IFS carrying the ETV6-NTRK3 gene fusion, suggesting a correlation between this variant and response to therapy. This aligns with the definition of predictive evidence, as it discusses the effectiveness of a treatment based on the presence of a specific variant.

Diagnostic, Prognostic evidence:

Diagnostic: The study discusses kataegis in the context of breast cancer subgroups defined by ER, PR, and HER2/ERBB2 status, indicating its role in classifying and associating with specific tumor characteristics and aggressive phenotypes.

Prognostic: The abstract mentions that kataegis status was associated with aggressive characteristics in certain breast cancer subgroups, suggesting a correlation with disease outcome, particularly in ERpHER2n tumors.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with specific genomic alterations in childhood B-lineage ALL, indicating that these genetic lesions can be used to classify and define this high-risk subtype of leukemia.

Predictive: The findings suggest that the identified targetable genetic lesions, such as CRLF2 rearrangements and ABL-class fusions, may correlate with treatment approaches in precision medicine for Ph-like ALL, indicating their potential role in predicting response to targeted therapies.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with high-risk childhood B-lineage ALL, indicating that specific genetic alterations can be used to classify and define this subtype of leukemia.

Predictive: The findings suggest that the identified targetable genetic lesions, such as CRLF2 rearrangements and ABL-class fusions, may correlate with treatment approaches in precision medicine for Ph-like ALL, indicating potential sensitivity to specific therapies.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with specific genetic alterations in childhood B-lineage ALL, indicating its role in classifying this high-risk subtype of leukemia.

Predictive: The findings support a precision-medicine approach for Ph-like ALL, suggesting that the identified genetic lesions may correlate with response to targeted therapies, which is a key aspect of treatment for this subtype.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with specific genetic alterations in childhood B-lineage ALL, indicating its role in classifying this high-risk subtype of leukemia. The mention of the frequency of CRLF2 rearrangements and other genetic lesions further supports the use of these variants in defining the disease.

Predictive: The findings suggest that the identified genetic alterations, including CRLF2 rearrangements and other targetable lesions, may correlate with treatment approaches in precision medicine for Ph-like ALL, indicating their potential impact on therapy response. The emphasis on targetable genetic lesions implies a relationship with treatment strategies.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with high-risk childhood B-lineage ALL, indicating that specific genomic alterations can be used to classify and define this subtype of leukemia.

Predictive: The findings suggest that the identified targetable genetic lesions, such as CRLF2 rearrangements and ABL-class fusions, may correlate with treatment approaches in precision medicine for Ph-like ALL, indicating potential sensitivity to specific therapies.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with specific genetic alterations in childhood B-lineage ALL, indicating that these variants can be used to classify and define this high-risk subtype of leukemia.

Predictive: The findings suggest that the identified genetic lesions, including CRLF2 rearrangements and other targetable alterations, may correlate with treatment response in the context of precision medicine for Ph-like ALL, highlighting their potential role in guiding therapy.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the Ph-like gene expression profile and its association with specific genetic alterations in childhood B-lineage ALL, indicating its role in classifying this high-risk subtype of leukemia. The mention of the frequency of CRLF2 rearrangements and other genomic alterations further supports the use of these variants in defining the disease.

Predictive: The findings suggest that the identified genetic lesions, including CRLF2 rearrangements and other targetable alterations, may correlate with treatment approaches in precision medicine for Ph-like ALL, indicating their potential impact on therapy response. The emphasis on targetable genetic lesions implies a relationship with treatment strategies.

Diagnostic, Prognostic evidence:

Prognostic: The study reports that higher numbers of somatic mutations and copy number alterations (CNAs) significantly correlated with worse survival, indicating that these genetic alterations are associated with disease outcomes independent of therapy. Additionally, it identifies specific mutations and amplifications, such as PD-L1, as independent poor prognostic factors in aggressive ATL, further supporting the prognostic nature of these findings.

Diagnostic: The abstract mentions that aggressive and indolent ATL subtypes are associated with different genetic alterations, which helps classify the disease into molecularly distinct subsets. This classification based on genetic profiles indicates the use of these variants in defining and understanding the disease subtypes.

Predictive, Oncogenic evidence:

Predictive: The study discusses the association of the L858R mutation with treatment outcomes, indicating that patients with this mutation have a similar overall survival (OS) compared to those with uncommon, actionable variants when treated with first-line EGFR inhibitors. This suggests that the presence of the L858R variant correlates with response to therapy, which is a key aspect of predictive evidence.

Oncogenic: The abstract mentions that activating mutations in EGFR, including L858R, are a common mechanism of malignant transformation in non-small cell lung cancer (NSCLC). This indicates that the L858R variant contributes to tumor development, supporting its classification as oncogenic.

Predictive, Prognostic evidence:

Predictive: The abstract mentions that testing for driver mutations identifies patients who benefit from TKI-therapy, indicating that the presence of such mutations, including T790M, correlates with response to specific therapies. Additionally, the results highlight that the presence of a driver mutation predicts response to specific TKIs, further supporting the predictive nature of the T790M variant in the context of treatment.

Prognostic: The results section states that EGFR-positive NSCLC is associated with improved prognosis, suggesting that the presence of the T790M variant may correlate with disease outcomes independent of therapy. This indicates that T790M could have prognostic implications in the context of NSCLC.

Diagnostic, Oncogenic evidence:

Diagnostic: The variant p.V617F is mentioned as a major diagnostic criterion for the diagnosis of Polycythemia Vera (PV), indicating its role in defining and confirming the disease. The presence of this mutation is used to classify the disease, which aligns with the definition of a diagnostic evidence type.

Oncogenic: The mention of the JAK2 p.V617F mutation in the context of diagnostic criteria for PV suggests that it contributes to tumor development or progression, as it is a well-known somatic mutation associated with myeloproliferative neoplasms. This aligns with the oncogenic evidence type, as it indicates the variant's role in the pathogenesis of the disease.

Predictive, Diagnostic evidence:

Diagnostic: The study evaluates the immunophenotypes and karyotypes of patients with childhood acute lymphoblastic leukemia (ALL) associated with the t(1;19) and der(19)t(1;19) translocations, suggesting that these variants can be used to classify distinct subtypes of ALL.

Predictive: The results indicate that patients with the t(1;19) and der(19)t(1;19) translocations did not respond to therapy as well as those with early pre-B ALL, highlighting the predictive nature of these variants in terms of treatment response.

Predictive, Diagnostic evidence:

Predictive: The identification of the COL1A1-PDGFB gene fusion allows greater choice of targeted therapy in these patients, indicating that the variant correlates with response to specific therapies.

Diagnostic: The COL1A1-PDGFB gene fusion is associated with a specific subtype of uterine sarcoma, which supports its use in defining and classifying this disease entity.

Predictive, Diagnostic evidence:

Diagnostic: The study identifies the SH3PXD2A::HTRA1 fusion in schwannomas and discusses its prevalence and association with specific clinicopathologic characteristics, indicating its role in defining and classifying these tumors. The mention of "fusion-positive schwannomas" and their distinct features supports the classification of this variant as a diagnostic marker.

Predictive: The study establishes a correlation between the presence of the SH3PXD2A::HTRA1 fusion and specific histological features, such as the 'serpentine' palisading pattern, which can predict fusion status with high sensitivity and specificity. This suggests that the variant may be used to predict certain characteristics of the tumors, aligning with predictive evidence.

nan evidence:

Based on the provided information, there are no mentions of the variant in either the abstract or the results section. Therefore, I cannot classify any evidence type as there is no supporting text to justify a classification.

Diagnostic, Oncogenic evidence:

Oncogenic: The abstract discusses the identification of EGFR internal tandem duplications (ITD) in tumors, specifically noting their presence in congenital mesoblastic nephromas and other pediatric sarcomas. This suggests that the EGFR ITD contributes to tumor development or progression in these specific cancer types.

Diagnostic: The study highlights the association of EGFR ITD with specific tumor types, particularly in pediatric sarcomas, indicating its role in defining or classifying these tumors. The identification of this variant in a subset of tumors supports its use as a biomarker for diagnosis.

Prognostic evidence:

Prognostic: The study indicates that adult patients with t(1;19)(q23;p13) positive ALL had a favorable prognosis, as evidenced by the reported 5-year cumulative incidence of relapse and overall survival rates. This suggests that the variant correlates with disease outcome independent of therapy.

Diagnostic, Prognostic evidence:

Prognostic: The study indicates that the t(1;19) variant is an independent risk factor for isolated CNS relapse, suggesting that it correlates with disease outcome independent of therapy. This is supported by the mention of event-free survival and the cumulative incidence of relapse in patients with this variant.

Diagnostic: The t(1;19) is used to classify and define a specific subtype of B-cell precursor acute lymphoblastic leukemia (ALL), as indicated by its association with the TCF3/PBX1 fusion. This classification is crucial for understanding the disease and its treatment implications.

Diagnostic, Oncogenic evidence:

Diagnostic: The study discusses the t(1;19) chromosomal translocation as being observed in 25% of children with pre-B-cell acute lymphoblastic leukemia (ALL) and highlights its association with an adverse treatment outcome, indicating its role in defining and classifying the disease. The detection of E2A/PBX1 fusion transcripts in a majority of cases further supports its use as a biomarker for this subtype of leukemia.

Oncogenic: The findings suggest that the E2A/PBX1 fusion resulting from the t(1;19) translocation is an important pathogenic event in t(1;19) ALL, indicating that this somatic variant contributes to tumor development or progression in this specific leukemia type.

Diagnostic, Oncogenic evidence:

Diagnostic: The study discusses the t(1;19) translocation and its association with acute lymphoblastic leukemia (ALL), indicating that it is a common genetic alteration used to classify the disease. The mention of different mechanisms leading to the formation of the der(19) and the investigation of markers proximal to the breakpoint further supports its role in defining the disease subtype.

Oncogenic: The t(1;19) translocation is described as one of the most common translocations in ALL, suggesting that it contributes to tumor development or progression. The study's focus on the mechanisms of how the der(19) arises indicates its potential role in oncogenesis within the context of leukemia.

Predictive, Diagnostic evidence:

Diagnostic: The study discusses the identification of patients with E2A-PBX1 positive translocations, indicating that the presence of this specific variant is used to classify and confirm a subtype of acute lymphoblastic leukemia (ALL). The development of a fluorescence in situ hybridization assay to detect E2A translocations further supports its role as a diagnostic tool in identifying patients who require specific therapeutic interventions.

Predictive: The abstract mentions that more intensive therapy improves the outcome of patients with E2A-PBX1 positive translocations, suggesting that the presence of this variant correlates with response to therapy. This highlights the importance of identifying this subset of patients to administer appropriate treatment, which aligns with predictive evidence.

Oncogenic evidence:

Oncogenic: The study discusses the translocation t(12;16)(q13:p11) in malignant myxoid liposarcoma, indicating that it results in a fusion of the CHOP gene with the FUS gene, which contributes to tumor development. This suggests that the variant plays a role in the oncogenic process by creating a fusion protein that may drive tumorigenesis.

Prognostic evidence:

Prognostic: The study demonstrates the prognostic significance of genetic alterations within subtypes of acute lymphoblastic leukemia (ALL), indicating that these alterations correlate with disease outcomes. This suggests that the presence of specific genetic changes can provide insights into the prognosis of patients with different ALL subtypes.

Prognostic evidence:

Prognostic: The study demonstrates the prognostic significance of genetic alterations within subtypes of acute lymphoblastic leukemia (ALL), indicating that these alterations correlate with disease outcomes. This suggests that the presence of specific genetic changes can provide insights into the prognosis of patients with ALL.

Prognostic evidence:

Prognostic: The study demonstrates the prognostic significance of genetic alterations within subtypes of acute lymphoblastic leukemia (ALL), indicating that these alterations correlate with disease outcomes. This suggests that the presence of specific genetic changes can provide insights into the prognosis of patients with ALL.

Predictive, Oncogenic evidence:

Predictive: The study discusses the efficacy of BI-4732 in overcoming osimertinib resistance mediated by the C797S variant, indicating that this variant correlates with resistance to therapy and highlights the potential for BI-4732 as a treatment option.

Oncogenic: The C797S variant is implicated in osimertinib resistance, suggesting that it contributes to tumor progression and development, as evidenced by the preclinical models used in the study.

Predictive, Oncogenic evidence:

Predictive: The study discusses the resistance to CDK4/6 inhibitors in KRAS-mutant non-small cell lung cancer (NSCLC) and how the inhibition of BRD4 can enhance the efficacy of these inhibitors, indicating a correlation with treatment response. The mention of "synergized with palbociclib to induce senescence" suggests that the variant's presence affects the sensitivity to therapy.

Oncogenic: The abstract indicates that BRD4 overexpression contributes to resistance against CDK4/6 inhibitors in KRAS-mutant NSCLC cells, suggesting that this variant plays a role in tumor progression and development. The context of BRD4's involvement in enhancing cell cycle arrest and promoting senescence further supports its oncogenic role.

Predictive evidence:

Predictive: The abstract mentions that PLX8725 demonstrates promising in vivo activity against PDX models of uLMS harboring GOF alterations in the MAP2K4 gene, indicating a correlation between the variant and response to the therapy. This suggests that the variant may influence treatment sensitivity, warranting further clinical trials.

Predictive, Oncogenic evidence:

Predictive: The study evaluates the response to divarasib, a KRAS G12C inhibitor, in patients with tumors harboring the KRAS G12C mutation, indicating that the variant correlates with treatment response. The mention of "biomarkers of response and resistance" further supports the predictive nature of the evidence regarding therapy outcomes.