Anna Cuomo

I'm excited to be heading to #FOGLondon tomorrow and give a talk on the TenK10K phase 1 project!

Find me on the single-cell stage tomorrow Jan 28th at 3:10pm :)

festivalofgenomics.com/london

#FOGLondon #genomics #biodata

You are welcome to explore other TenK10K studies for different biological questions:
tinyurl.com/tenk10k-flag... led by
@annasecuomo.bsky.social
tinyurl.com/tenk10k-repeat led by
@htanudisastro.bsky.social
tinyurl.com/tenk10k-causal led by
@alberthenry.bsky.social & Anne Senabouth (14/n)

Genetic regulation of cell type-specific chromatin accessibility shapes immune function and disease risk Understanding how genetic variation influences gene regulation at the single-cell level is crucial for elucidating the mechanisms underlying complex diseases. However, limited large-scale single-cell multi-omics data have constrained our understanding of the regulatory pathways that link variants to cell type-specific gene expression. Here we present chromatin accessibility profiles from 3.5 million peripheral blood mononuclear cells (PBMCs) across 1,042 donors, generated using single-cell ATAC-seq and multiome (RNA+ATAC) sequencing, with matched whole-genome sequencing, generated as part of the TenK10K program. We characterized 440,996 chromatin peaks across 28 immune cell types and mapped 243,273 chromatin accessibility quantitative trait loci (caQTLs), 60% of which are cell type-specific. Integration with TenK10K scRNA-seq data (5.4 million PBMCs) identified 31,688 candidate cis-regulatory elements colocalized with eQTLs; over half (52.5%) show evidence of causal effects mediated via chromatin accessibility. Integrating caQTLs with GWAS summary statistics for 16 diseases and 44 blood traits uncovered 9.8% - 30.0% more colocalized signals compared with using eQTLs alone, many of which have not been reported in prior studies. We demonstrate cell type-specific mechanisms, such as a regulatory effect on IRGM acting through altered promoter chromatin accessibility in CD8 effector memory T cells but not in naive cells. Using a graph neural network, we inferred peak-to-gene relationships from unpaired multiome data by incorporating caQTL and eQTL signals, achieving up to 80% higher accuracy compared to using paired multiome data without QTL information. This improvement further enhanced gene regulatory network inference, leading to the identification of 128 additional transcription factor (TF)-target gene pairs (a 22% increase). These findings provide an unprecedented single-cell map of chromatin accessibility and genetic variation in human circulating immune cells, establishing a powerful resource for dissecting cell type-specific regulation and advancing our understanding of genetic risk for complex diseases. ### Competing Interest Statement L.C., E.B.D., and K.K.H.F. are employed at Illumina Inc. D.G.M. is a paid advisor to Insitro and GSK, and receives research funding from Google and Microsoft, unrelated to the work described in this manuscript. G.A.F reports grants from National Health and Medical Research Council (Australia), grants from Abbott Diagnostic, Sanofi, Janssen Pharmaceuticals, and NSW Health. G.A.F reports honorarium from CSL, CPC Clinical Research, Sanofi, Boehringer-Ingelheim, Heart Foundation, and Abbott. G.A.F serves as Board Director for the Australian Cardiovascular Alliance (past President), Executive Committee Member for CPC Clinical Research, Founding Director and CMO for Prokardia and Kardiomics, and Executive Committee member for the CAD Frontiers A2D2 Consortium. In addition, G.A.F serves as CMO for the non-profit, CAD Frontiers, with industry partners including, Novartis, Amgen, Siemens Healthineers, ELUCID, Foresite Labs LLC, HeartFlow, Canon, Cleerly, Caristo, Genentech, Artyra, and Bitterroot Bio, Novo Nordisk and Allelica. In addition, G.A.F has the following patents: "Patent Biomarkers and Oxidative Stress" awarded USA May 2017 (US9638699B2) issued to Northern Sydney Local Health District, "Use of P2X7R antagonists in cardiovascular disease" PCT/AU2018/050905 licensed to Prokardia, "Methods for treatment and prevention of vascular disease" PCT/AU2015/000548 issued to The University of Sydney/Northern Sydney Local Health District, "Methods for predicting coronary artery disease" AU202290266 issued to The University of Sydney, and the patent "Novel P2X7 Receptor Antagonists" PCT/AU2022/051400 (23.11.2022), International App No: WO/2023/092175 (01.06.2023), issued to The University of Sydney. ### Funding Statement A.X. is supported by NHMRC Investigator grant 2033018. J.E.P. is supported by NHMRC Investigator grant 2034556, and a Fok Family Fellowship; D.G.M. is supported by an NHMRC investigator grant (2009982). G.A.F. and the BioHEART Study have been supported by NHMRC Investigator Grant, NSW Health Office of Health and Medical Research, and the NSW Health Statewide Biobank scheme. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Human Research Ethics Committee of St Vincent's Hospital gave ethical approval for this work. The National Statement on Ethical Conduct in Human Research of the National Health and Medical Research Council gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Raw caQTL summary statistics will be available at Zenodo website prior to acceptance. [https://github.com/powellgenomicslab/tenk10k\_phase1\_multiome][1] [1]: https://github.com/powellgenomicslab/tenk10k_phase1_multiome

New preprint alert: tinyurl.com/tenk10k-multiome. Excited to share our analysis on the impact of genetic variants on single-cell chromatin accessibility in blood, using scATAC-seq and WGS from over 1,000 donors and 3.5M nuclei as part of TenK10K phase 1 🧬
🧵👇 (1/n)

Another preprint from the TenK10K program! This work, led by @alberthenry.bsky.social and Anne Senabouth, leverages the unprecedented power of this WGS/single cell RNA-seq cohort to explore causal influences of blood gene expression on immune diseases and traits. Thread:

So excited about more TenK10K papers coming out 😍 congratulations to the whole team!!!

Single-cell genetics identifies cell type-specific causal mechanisms in complex traits and diseases Genome-wide association studies (GWAS) have been instrumental in uncovering the genetic basis of complex traits. When integrated with expression quantitative trait loci (eQTL) mapping, they can elucid...

1. 🚨New preprint: tinyurl.com/tenk10k-causal.
We explored causal effects of gene expression in immune cell types on complex traits and diseases by combining single-cell expression quantitative trait loci (sc-eQTL) mapping in 5M+ cells from 1,925 donors in TenK10K study and GWAS. 🧵

Impact of Rare and Common Genetic Variation on Cell Type-Specific Gene Expression Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expre...

For more detail check out the preprint at medrxiv.org/content/10.1..., or get in touch! (12/12)

As always, teamwork makes the dream work, huge thanks to everyone involved: supervisors Joseph Powell and @dgmacarthur.bsky.social, ‪@htanudisastro.bsky.social‬, Ellie Spenceley, @blakebowen.bsky.social, @alberthenry.bsky.social, Hao Lawrence Huang, @anglixue.bsky.social and many others! 👏(11/n)

Other work covering different aspects of this dataset is coming, so stay tuned! Starting with @htanudisastro.bsky.social on the role of tandem repeats in the regulation of single-cell expression :) read more at bsky.app/profile/htan... (updated version coming soon!)(10/n)

In summary, deeply sequenced scRNA-seq from ~2,000 individuals and >5m cells and matched WGS, combined with a powerful sc-eQTL mapping tool allow us to decipher how genetic variants shape the immune landscape at unprecedented resolution 🚀(9/n)

Impact of Rare and Common Genetic Variation on Cell Type-Specific Gene Expression Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expre...

Check out the preprint to read more about how we define a framework to quantify cell type specificity, identify eQTLs that vary dynamically along biologically-informed cell states, and map cell state abundance QTLs! ‼️ medrxiv.org/content/10.1... (8/n)

For example, we found distinct eQTLs OSM in different cell types, with the NK cells-specific effect (only 👀) colocalizing with a risk locus for IBD (7/n)

We found over 30,000 colocalization events between our eQTLs and GWAS loci from 14 disease phenotypes and 44 blood traits, displaying remarkable cell type specificity (43% disease loci colocalize with an eQTL in only one cell type!) 🤩 (6/n)

These samples were sequenced deeply, with ~3,000 cells per individual across 28 cell types, giving us power to find common eQTLs for 83% of genes and rare variant signal for 47%, with variants often beautifully overlapping with functional annotation + in-house scATAC-seq 😍(5/n)

We leverage WGS to call common *and rare* variants, and use SAIGE-QTL to model single-cell counts, to identify >150,000 common eQTLs and >30,000 rare variant gene-level effects (via Burden + SKAT tests) (4/n)

Efficient and accurate mixed model association tool for single-cell eQTL analysis Understanding the genetic basis of gene expression can help us understand the molecular underpinnings of human traits and disease. Expression quantitative trait locus (eQTL) mapping can help in studyi...

Yet, most single-cell eQTL maps only test for the effect of common variants and use “pseudo-bulk” individual-level aggregated expression, rather than modelling single-cell profiles directly. Both are addressed by our recently introduced, SAIGE-QTL www.medrxiv.org/content/10.1... (3/n)

Single-cell genomics meets human genetics - Nature Reviews Genetics In this Review, the authors describe the emerging field of single-cell genetics, which lies at the intersection of single-cell genomics and human genetics. They review the first single-cell expression...

Population-scale single-cell studies, where matched scRNA-seq and genotype data are available for hundreds (now thousands!) of individuals can transform our understanding of the cell contexts underpinning key processes in human biology and disease www.nature.com/articles/s41... (2/n)

📢 new preprint alert: So so excited to share our analysis on the impact of common and rare variants on single-cell gene expression in blood, using WGS and scRNA-seq data from nearly 2,000 individuals and 5.4m cells as part of TenK10K phase 1 🧬 www.medrxiv.org/content/10.1...
🧵👇 (1/n)

Bluesky now has over 20M people!! 🎉

We've been adding over a million users per day for the last few days. To celebrate, here are 20 fun facts about Bluesky:

This work was driven by brilliant PhD student @htanudisastro.bsky.social as a close collaboration with Joseph Powell’s team, especially postdoc @annasecuomo.bsky.social. Both Anna and Hope will be presenting at #ASHG2024 on Wednesday - we’d welcome comments as we prep the final dataset of over 2K!

give us a couple more weeks!

Sad to be missing #ASHG23, but check out the talk by the brilliant Wei Zhou talk on Saturday on our new scalable & efficient method for single-cell eQTL mapping!

I'm delighted to release the first half of my new textbook in human genetics:
web.stanford.edu/group/pritch...

"An Owner's Guide to the Human Genome: an introduction to human population genetics, variation and disease"

BlueSky for Scientists BlueSky for Scientists Authors: Steve Haroz and Mark RubinURL: http://blueskyscience.steveharoz.com Features you may miss from Twitter or Mastodon As BlueSky is in beta, some features are not impleme...

A guide to BlueSky for Scientists
* Common questions
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Please share with scientists on BlueSky!

Written by me and @markrubin.bsky.social

🧪 #stats #PsychSciSky #neuroscience