Great collaboration between @genomedatalab.bsky.social
at @irbbarcelona.org / @bric-ucph.bsky.social
and the @benlehner.bsky.social group at @crg.eu
/ @sangerinstitute.bsky.social
👉Read our NMDetective-AI study www.biorxiv.org/content/10.6...
Posts by Fran Supek
Cells can destroy mRNAs with premature🛑stop, frameshift or splice #mutations via NMD pathway. But whether a given variant is silenced ✂️is often predicted using a few hand-crafted NMD rules. We asked: can this be modeled quantitatively, across human genes, w/both #AI and experiment?
AI-generated cartoon of a computational biologist and wet-lab biologist collaborating on a research project
✂️🧬preprint!
"Quantitative prediction of nonsense-mediated #mRNA decay across human genes by #genomic language #model & large-scale mutational scanning"
Fantastic teamwork by @IgnasiToledano 👨🔬and @MarcellVeiner👨💻. We combine massive experiment and sequence AI to elucidate NMD👇
Figure 1: Data modalities of genomic language models. From review article "The DNA dialect: a comprehensive guide to pretrained genomic language models" by Veiner and Supek.
On the heels of the release of #AlphaGenome, we have written up a review on 🧬genomic language models for DNA/RNA, out in EMBO @molsystbiol.org journal
🔖"The DNA dialect: a comprehensive guide to pretrained genomic language models" by Marcell Veiner👏 & yours truly👇
link.springer.com/article/10.1...
We also have a PhD student position open. Application deadline 10.2. 👇
candidate.hr-manager.net/ApplicationI...
Ideal positions for recent bioinformatics/genomics/compbiol PhDs looking to pivot towards AI 🖥️ 🧠 & to do impactful science. Also great for computer science people looking to get into genomics. 🧬
1️⃣ candidate.hr-manager.net/ApplicationI...
2️⃣ candidate.hr-manager.net/ApplicationI...
We're recruiting 2 postdocs👩💻👨🏫 on the "A-SOuRCCE" project:
1️⃣AI for Knowledge Graphs in Regulatory Genomics (auto extraction, organization and querying of knowledge)
2️⃣Agentic AI for Scientific Discovery in Genomics (LLMs for hypothesis generation and assessment)
Apply below! 👇 Deadline soon: 10.2.
AI-generated cartoon illustrating a team of researchers working on A-SOuRCCE
Big thanks to my awesome lab members 💯 @genomedatalab.bsky.social, and to present & past host institutions who helped shape this vision @bric-ucph.bsky.social 🥳 @irbbarcelona.org 🙌 @crg.eu 🎉@institutrb.bsky.social🙏
Now let’s get to work!🔬🤖 Will be recruiting PhDs/postdocs soon, watch this space...
By integrating AI agents with knowledge graphs grounded in biological fact, our discovery engine will:
- auto-generate mechanistic hypotheses 🧬
- assess their novelty 💫 and plausibility 🧠
- validate against population genetics (GWAS) data 📊
This will accelerate pathway: data -> mechanism -> target
AI-generated cartoon to illustrate the central idea of the A-SOuRCCE project
Delighted to share that our project on agentic AI for genomic science has been funded!🌟 We secured 1.7M € from @novo-nordisk.bsky.social in “Data Science Investigator: Distinguished” - v grateful!🙏
A-SOuRCCE stands for "AI for Single-cell Omics and Reproducible Cardiometabolic & Cancer Exploration"
Overall: human DNA replication origins usage isn't a roll of the dice 🎲 it’s genetic potential gated by epigenetic context
👏Huge congrats to lead authors Marcell Veiner
& Marina Salvadores - bravo for excellent teamwork!
Read the full study here...👇
www.biorxiv.org/content/10.6...
2) the "software"
🩸🫁DNA is same in every cell - why do colon/lung/... cells copy differently?
🦀We tracked "fossil" mutations in cancer genomes to decode tissue-specificity
🧬Local chromatin environment acts as a switch, turning the hard-coded sites ON or OFF in each tissue
1) the "hardware"
💻🧠 We trained a deep learning model (ORIFormer), revealing replication initation is "hard-coded" in DNA by specific sequence motifs, like ZNF770 sites
🧬 The genome has a built-in map of potential start sites, w/ complex "grammar" that was previously elusive
AI-generated graphical summary of the DNA replication origins study
📢new study @genomedatalab.bsky.social
When a cell divides, it copies 3 billion DNA letters. How does it know where to begin?
⁉️For years, the field debated if replication initiation was random or strict
📜Our preprint uses AI + mutation signatures to show it’s a precise, two-part system
👉Read the study by Zadra, Orsolic et al.
"Dual inhibition of the nonsense mediated mRNA decay enhances tumour immunogenicity, drives immunoediting, and potentiates checkpoint blockade"
as a biorxiv preprint, fresh from the oven:
www.biorxiv.org/content/10.6...
AI-generated cartoon displaying simplified concept
➡️ We trained protein language model on these datasets of mutations from tumors treated by NMDi. A fine-tuned 💻AI model successfully learned to identify immunogenic neopeptides, capturing features that go beyond standard MHC-binding predictions.
AI-generated cartoon displaying simplified concept
➡️ Our mRNA data adds to the mounting literature that abberant splicing in cancer (esp intron retention) could contribute to making tumors immune-hot. 💊NMD inhibiton is extremely helpful in exposing these tumor splicing errors.
AI-generated cartoon displaying simplified concept
➡️ Using WGS, we tracked the evolutionary footprint of treatment. We observed strong "immunoediting" -- a negative selective pressure against immunogenic mutations -- thus NMD inhibition makes tumors highly visible to the immune system.
Our team's contribution @irbbarcelona.org (led by the mighty postdoc 🤓 Davor Orsolic) and yours truly at Biotech Research & Innovation Centre (BRIC), UCPH_Research dived into the 🧬 tumor genomics and computational modeling.
www.biorxiv.org/content/10.6...
read more!👇
In a synergy with the @TheAnaJanic lab @UPFBarcelona, who led the study spearheaded by Ivan Zadra 👏, we investigated how inhibiting the cellular quality-control mechanism known as NMD can force lung tumors in 🐁 to reveal their hidden mutations to the immune system.
Figure summarizing NMD from a review article Supek, Lehner and Lindeboom (2021) Trends in Genetics.
Excited to share our latest collaborative study of a frontier approach in cancer immunotherapy, targeting the Nonsense-Mediated mRNA Decay (NMD) pathway.
Read more in a short 🧵+ link to preprint is below:
📣 Attention postdocs in the life sciences! Are you ready to take the big leap?
Start your lab at the Biotech Research and Innovation Centre in Copenhagen! 🇩🇰 @bric-ucph.bsky.social
Collegial atmosphere, cutting-edge science, core funding.
(+the weather is wonderful, relative to Siberia😁)
Apply!👇
Congrats to colleagues from IRB!
Check out the full story here:
"Variable efficiency of nonsense-mediated mRNA decay across human tissues, tumors and individuals"
genomebiology.biomedcentral.com/articles/10....
👏👏to Guille for marvelous work!
Why care? Our prior work (Lindeboom et al., reviewed in www.cell.com/trends/genet... ) + Guille paper supports that NMD
🛑modulates selection on somatic nonsense "driver" mutations
🛑associates w/cancer (immuno)therapy💊response (neoantigens!)
🛑linked w/ severity of inherited genetic disease
👇
Interestingly, genetic variants can change global NMD efficiency in an individual🤔
🧬 inherited variants - SNVs in KDM6B chromatin modifier gene
🧬 somatic variants - copy number alterations at chromosome 1q (SMG5, SMG7...)
Nice IRB writeup here 👇
www.irbbarcelona.org/en/news/scie...
🛑Guille's @guillepalou.bsky.social no-nonsense 😉 paper is out in @springernature.com Genome Biology!
We report variable activity of the NMD pathway (mRNA QC) across tissues & individuals:
🧠less active in the nervous system & in reproductive tissues
🩸more active in digestive tract, muscle, blood
Fantastic to be in such great company!🤩
👏Congrats to 19 colleagues from my institutions (🇩🇰BRIC @UCPH_health and 🇪🇸@IRBBarcelona) in this year's Elsevier/Stanford top 2% most cited researchers list