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Please note I assume there have not been many changes or additions to these resubmission given that they were already loved and got high impact evaluations - BUT if you substantially changed the application in between submissions please write that in the Notes..

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If your grant does not have percentiles but only Impact Scores, please input those instead. All we need is a way to see how consistent/inconsistent these scores are, for the first time, unfortunately, for "funded" grants. Feel free to share the Google Doc link in other platforms or here.

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All entries will be anonymous and only for aggregate analysis, share your name if you like, use an alias of some sort that you can later track and edit, if not. You can also message your scores to me. Whatever info you feel comfortable sharing. Also vent off, if you like! We all need it sometimes.

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I thought we could gather them somewhere and see for ourselves the level of variability and "chance" factor in getting NIH funding. Three reviewers loved your grant, great (great if you got it funded, of course) ! Would another three like it the same way in the next cycle!

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Ferhat Ay @ferhatay.bsky.social · 06/03/2026

I hope NIH will properly gather these statistics and share at some point but not holding my breath for anytime soon. The idea is to look at the destiny of grants that would have been funded in normal years but did not in 2025. Now that most of us resubmitted them and are getting "new" scores

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What a wonderful paper! Congrats

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Ferhat Ay @ferhatay.bsky.social · 02/03/2026

To accommodate decision timelines from RECOMB main conference and ISMB, we have now extended the submission deadline with RECOMB-RSG to March 13th, there will be no more extensions. Looking forward to have you join us in Greece! recomb-rsg.github.io

recomb-rsg.github.io

RECOMB-RSG 2026 | Regulatory Genomics Satellite

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Reposted by Ferhat Ay

2 PhD candidates in my group: Michal @malszycki.bsky.social and Lisa led this work. We are very thankful to Ay lab ( @ferhatay.bsky.social ) and Alev lab (ASHBi, Kyoto), who helped make our story more complete. This work was funded by @dfg.de in the framework of @spp2202.bsky.social

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Reposted by Ferhat Ay

Analysis of the evolution of this gene architecture and the presence of GC-rich isochores revealed that these features are specific to amniotes. By using the pA-RNA signal as a proxy for speckles we show the speckles are present in amniotes and absent in fish and invertebrates.

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Reposted by Ferhat Ay

The short & GC-rich introns emerged in amniotes and were once long and GC-poor (in fish). The emergence of this gene architecture coincides with the expansion of SON’s IDRs. IDRs of SON are necessary and sufficient to form functional speckles.

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Reposted by Ferhat Ay

Problems in splicing, due to SF3 complex dispersal, cause changes in gene expression, but only a small set of exons-introns are sensitive to speckles loss. These genes have introns with short & GC-rich architecture and are found in GC-rich isochores.

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Reposted by Ferhat Ay

Differential gene expression analysis upon speckles loss reveals only genes within high GC chromatin domains are susceptible. The distance of the chromosomes 18 (lowest GC content) and 19 (highest GC content) from the speckles also indicate their speckle dependency.

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Reposted by Ferhat Ay

Speckles take a large space in the human cell nucleus and form viscoelastic boundaries that restrict random chromatin movements. Upon speckles loss, the chromatin mobility increases and active(A) and inactive(B) chromatin compartments mix as shown by the Pore-C analysis by @ferhatay.bsky.social lab

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Reposted by Ferhat Ay

Nuclear speckles are protein and RNA rich condensates that are proximal to GC-rich regions of the human genome. We dissolved speckles by rapidly depleting the 2 core proteins; SON & SRRM2 and investigated the role of speckles in: 1. 3D genome folding 2. transcription & splicing.

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Reposted by Ferhat Ay

Sushmita Roy @sroyyors.bsky.social · 27/01/2026

Our most recent work on the “function and evolution” of #nuclear-speckles is now online at Cell @cp-cell.bsky.social doi.org/10.1016/j.ce... Read the thread👇 for the highlights of our findings.

doi.org

Redirecting

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Reposted by Ferhat Ay

Thanks to @ferhatay.bsky.social and Aly Khan, we’re excited to announce a new chapter for RECOMB-RSG 2026. After years with ISCB/DREAM, we are transitioning to an official RECOMB satellite meeting (May 25 in Thessaloniki). recomb-rsg.github.io

recomb-rsg.github.io

RECOMB-RSG 2026 | Regulatory Genomics Satellite

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Reposted by Ferhat Ay

JCI insight @insight.jci.org · 14/01/2026

From RIME to reason In this Research Letter by Hal M. Hoffman @ferhatay.bsky.social & team, scRNA-seq analysis before & after treatment of recurrent infectious mucocutaneous eruption (RIME) reveals dysregulation of TNF/IFN signaling & classical monocytes: doi.org/10.1172/jci....

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Ferhat Ay @ferhatay.bsky.social · 08/01/2026

It did fly! Happy new year Jiao, thank you!

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Ferhat Ay @ferhatay.bsky.social · 06/01/2026

10th year anniversary of Ay lab at LJI! What a journey so far! Thank you to all lab members, collaborators, LJI family, who made this enjoyable and exciting. Here is a photo that summarizes how my lab sees me now 😂😂😢😢

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Ferhat Ay @ferhatay.bsky.social · 25/11/2025

Happy to see this out @insight.jci.org The first paper of hopefully many with Reid Oldenburg, Croker lab and others at UCSD utilizing BD Rhapsody platform for single-cell profiling of patient samples for severe conditions such as RIME.

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Our source code, utility scripts and links to processed data and results are all available on our lab's GitHub: lnkd.in/g7EdGYuu Hope you enjoy reading it and reach out if you have any questions or feedback! Big thanks to Cell Reports Methods and their editorial team for the efficient review

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Our results highlight the importance of distance stratification in capturing differences in long-range loops, differences in sensitivity across different statistical models and provides overall best practices for differential HiChIP analysis.

good collaborator Katia Georgopoulos in annotation of the results, we implemented a unified framework with all different approaches to date, developed performance metrics and systematically evaluated tools/tests utilized by us and others on multiple different HiChIP datasets.

We and others have worked on this problem but realized the variability in effectiveness of different approaches across different data sets. In this work, led by Sourya Bhattacharyya (now at Empirico) and Daniela Salgado Figueroa (UCSD Bioinformatics PhD student) in my lab and with help from our

Anders Sejr Hansen @andersshansen.bsky.social · 20/08/2025

Our latest paper on comparative analysis of HiChIP data is now online! HiChIP is one of the most useful/practical assays to profile 3D genome organization and chromatin loops but has its challenges in the data analysis especially when it comes to comparative analysis.

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Reposted by Ferhat Ay

I have NIGMS R35, impact score 12 NIHGRI R21, 4th percentile NHGRI R01, 7th percentile (co-I) and it seems like none will be funded. 0/3. PO (who has been very helpful) said "Unfortunately, I do not expect this application will be selected for funding in FY25." 😭

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Ferhat Ay @ferhatay.bsky.social · 21/08/2025

Oh my god 😱😱 good luck Anders. These are amazing scores..We have multiple single digit %ile grants with collaborators.. one is a resubmission after multiple submissions finally making “the cut” just to have the goal post moved 😥 fingers crossed for some last minute miracle for all of us

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Reposted by Ferhat Ay

Alejandra Medina-Rivera @alemedinarivera.bsky.social · 24/07/2025

RegSys Day 2! Starting the day with a keynote by Roser Vento-Tormo on the cellular components of the placenta and uterus interaction #ismbeccb2025

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Reposted by Ferhat Ay

Anthony Mathelier @amathelier.bsky.social · 23/07/2025

Today marks the start of the #RegSys @iscb-regsys.bsky.social track at ##ISMBECCB2025! Very much looking forward to listening to the exciting science that will be presented. Join us in room 11BC today and tomorrow.

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Reposted by Ferhat Ay

Marcel Schulz @themarcelschulz.bsky.social · 23/07/2025

#RegSys is starting with the keynote from @verapancaldi.bsky.social who talks about the changes of chromatin structure and the epigenome in cancer patients #ismbeccb2025

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Reposted by Ferhat Ay

Marcel Schulz @themarcelschulz.bsky.social · 23/07/2025

Laura Hinojosa talks about TFs that regulate replication timing #RegSys #ismbeccb2025 @ferhatay.bsky.social

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Loop Catalog: a comprehensive HiChIP database of human and mouse samples - Genome Biology

over 1000 distinct human and mouse HiChIP samples from 152 studies plus 44 high-resolution Hi-C samples. In the paper, we demonstrate its utility for interpreting GWAS and eQTL variants through SNP-to-gene linking, identifying enriched sequence motifs and motif pairs. tinyurl.com/LoopCatalog

tinyurl.com

HiChIP enables cost-effective and high-resolution profiling of chromatin loops. To leverage the increasing number of HiChIP datasets, we develop Loop Catalog ( https://loopcatalog.lji.org ), a web-bas...

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3 years ago we decided to compile these datasets in one place. We were fortunate to get NIH support for this, which transformed it from a local resource for our lab to a comprehensive data resource. What we named Loop Catalog is now a web-based database featuring loop calls from

The third one is work led by Joaquin Reyna (former UCSD Bioinformatics PhD student) and Kyra Fetter (former UCSD undergraduate student) with help from multiple members of our lab. Seeing the increase in the number and quality of HiChIP datasets and having developed tools for its analysis,

This highlighted master transcription factor binding sites (Oct4, Sox2, Nanog for ES cells) with contributions from transcription start sites (TSS), and a combinatorial regulation by these core elements, as the basis of RT control.

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Here Jesse Turner (FSU and now at NIH) and Laura Hinojosa (UCSD Bioinformatics PhD student) with help from other co-authors dissected the previously characterized ERCEs of multiple kilobases in size down to hundreds of base pairs to map out the core parts which retain control of early replication.

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The second one is a follow up of our earlier collaboration with Gilbert lab (SDBRI) where we have discovered ERCEs, regulatory elements that control early replication of DNA.

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Soffritto: a deep learning model for predicting high-resolution replication timing

This enabled us to understand the contribution of different features to high-resolution RT both locally and globally. Our comparison with not-so-deep learning methods showed that they readily provide a pretty good baseline suggestion non-linear effects may be minimal. tinyurl.com/Soffritto

tinyurl.com

AbstractMotivation. Replication timing (RT) refers to the order in which DNA loci are replicated during S phase. RT is cell-type specific and implicated in

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One of these is more expensive than the other, you can guess. And accordingly, there is (much) more available data from one than the other. Dante developed a deep learning framework that utilizes 2-fraction RT data with histone modifications to predict 16-fraction data with pretty good accuracy.

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