Jeffrey Pullin

Happy to share new manuscript I completed with @ee-reh-neh.bsky.social & @davisjmcc.bsky.social back in Melbourne. The work originally conceived by @ijbeasley.bsky.social focuses on how we can reconcile and meta-analyse eQTL studies across studies cohorts and ancestries. doi.org/10.64898/202...

Very excited to see this work be the first to use the quasar method for eQTL mapping!

Finally, today's offering! www.biorxiv.org/content/10.6...

This began life as a very different project which failed because we couldn't agree on defining eqtl sharing across cohorts. So two young members of the lab dug deeply into this - first @ijbeasley.bsky.social, then @patrickgibbs.bsky.social

Hi yes I will have more to say about this in a few hours but please enjoy this paper. It's been a huge labour of love and effort for the last four years, and a significant part of our research efforts, and I'm so so so thrilled it's finally ready to share.

Tldr: scRNA-seq in Indonesia hard but fun

Delighted to present Latent Interaction Variational Inference (LIVI), a framework for trans-eQTL mapping at single-cell resolution that I developed during my PhD together with colleagues from @steglelab.bsky.social 1/n

Quote from Gosia Trynka, Wellcome Sanger Institute and Biology at Scale committee member: "Linking variants to function at scale requires new tools and new ways of working together. Biology at Scale is designed to connect the communities needed to interpret complex traits. Abstract deadline: 20 April 2026

Share insights on using multimodal biological frameworks at #BiologyAtScale26 🧬

Contribute towards multidisciplinary knowledge exchange, and bridge gaps across genetics, cell biology, and human health.

📅 29 June -1 July 2026
Submit an abstract by 20 April ➡️ bit.ly/4mYud02

#ComplexTraits 🧪

New preprint alert: we use sign errors as a test of how well TWAS works.

Very worryingly we find that TWAS gets the sign wrong around 1/3 of the time (compared to 50% for pure guessing). You can read more about our analysis here, and what we think is going on 👇

High false sign rates in transcriptome-wide association studies Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it r...

How well does TWAS estimate a gene’s direction of effect on a trait? We think of this as an important stress-test for the accuracy of TWAS.

In a new pre-print, we find that TWAS gets the sign wrong around 20-30% of the time!

doi.org/10.64898/202...

1/n

Genome-scale perturb-seq in primary human CD4+ T cells maps context-specific regulators of T cell programs and human immune traits Gene regulatory networks encode the fundamental logic of cellular functions, but systematic network mapping remains challenging, especially in cell states relevant to human biology and disease. Here, ...

Together with @ronghuizhu.bsky.social, we are thrilled to present our new perturb-seq study of 22M primary CD4+ T cells, across donors and timepoints – the result of a decade-long collaboration between the Marson @marsonlab.bsky.social and Pritchard @jkpritch.bsky.social labs 🧵 tinyurl.com/gwt2025

Genome-scale perturb-seq in primary human CD4+ T cells maps context-specific regulators of T cell programs and human immune traits https://www.biorxiv.org/content/10.64898/2025.12.23.696273v1

High false sign rates in transcriptome-wide association studies https://www.biorxiv.org/content/10.64898/2025.12.19.695550v1

Excited to share our new FinnGen single-nucleus multiome preprint! 🧬

We profiled ~10M PBMCs (snRNA-seq + snATAC-seq) from 1,108 Finnish donors to map how genetic variants drive complex disease through chromatin and gene regulation 🧵👇
🔗 Link: www.medrxiv.org/content/10.1...

Design and interpretation of eQTL-GWAS colocalisation studies: lessons from a large-scale evaluation https://www.medrxiv.org/content/10.1101/2025.11.20.25340664v1

Denoising image-based spatial transcriptomics data with DenoIST Image-based spatial transcriptomics (IST) technologies provide unprecedented resolution of gene expression in tissue sections, but suffer from contamination of cells' gene expression profiles due to i...

Great new work led by Aaron Kwok from @davisjmcc.bsky.social’s group. A tool to “denoise” contaminating transcripts from image based spatial data.

www.biorxiv.org/content/10.1...

Estimation and mapping of the missing heritability of human phenotypes - Nature WGS data were used from 347,630 individuals with European ancestry in the UK Biobank to obtain high-precision estimates of coding and non-coding rare variant heritability for 34 co...

First time on Bsky and first big announcement!

I am excited to announce that our new study explaining the missing heritability of many phenotypes using WGS data from ~347,000 UK Biobank participants has just been published in @Nature.

Our manuscript is here: www.nature.com/articles/s41....

Systematic comparison of colocalization methods using protein quantitative trait loci Colocalization is frequently performed as a step to triage findings from genetic investigations linking molecular and disease data. However, the reliability and consistency of the various colocalizati...

New pre-print: "Systematic comparison of colocalization methods using protein quantitative trait loci" led by @hwang_seongwon at www.biorxiv.org/content/10.1.... Which method does best? Find out!

Large-scale GWAS meta-analysis of serum antibody levels reveals distinct genetic architectures Antibodies are the principal effector proteins of humoral immunity. Dysregulated antibody production is a feature of a number of heritable immune-mediated diseases, such as the antibody deficiencies a...

New: GWAS of serurm antibody levels. Interesting findings include genetically correlated traits with hard-to-find shared causal variants, and apparently genetically uncorrelated traits sharing causal variants that operate in inconsistent directions www.medrxiv.org/content/10.1...

The worst app I’ve ever used haha

I'm very excited to be attending my first #ASHG25 this week! Come find me at poster board 1090F to talk about flexible and efficient eQTL mapping with quasar!

I'm very excited to be attending my first #ASHG25 this week! Come find me at poster board 1090F to talk about flexible and efficient eQTL mapping with quasar!

Good point! Indeed I just checked and we don't see colocalisation between IFI6 and the GWAS

Makes perfect sense! I think it's super interesting that IFI6 is the regulated gene as it has an antiviral function but is not thought to affect HHV-7

Host control of latent Epstein-Barr virus infection Epstein-Barr virus (EBV) is a herpes virus that infects around 90-95% of the global population, and is associated with numerous autoimmune and neoplastic diseases. EBV persists in B cells as a life-lo...

It's awesome isn't it! There have also been two other recent EBV viral load GWAS: www.medrxiv.org/content/10.1... and www.biorxiv.org/content/10.1...

Great to see this out! Seeing the thumbnail reminded me that SP110 was recently identified as a GWAS hit for HHV7 viral load

Trans-eQTL mapping prioritises USP18 as a negative regulator of interferon response at a lupus risk locus - Nature Communications | Open Targets Out now in Nature Comms: the largest trans-eQTL meta-analysis in a single cell type! An Open Targets team led by Krista Freimann and Kaur Alasoo analysed 3,734 lymphoblastoid cell line samples across...

Out now in Nature Comms: the largest trans-eQTL meta-analysis in a single cell type!

An Open Targets team led by Krista Freimann and @kauralasoo.bsky.social analysed 3,734 lymphoblastoid cell line samples across nine cohorts, identifying four robust loci

www.nature.com/articles/s41...

Clinical and genetic spectrum of Fanconi anemia in Australia and New Zealand Fanconi anemia (FA) is a rare genetic condition that predisposes to progressive bone marrow failure, a specific spectrum of malignancies, including he…

I feel incredibly privileged to share this study on Fanconi anaemia, based on a small but important cohort. This work describes the genetics and clinical outcomes of patients in Australia and New Zealand with a diagnosis of FA.

www.sciencedirect.com/science/arti...

Evaluating multi-ancestry genome-wide association methods: Statistical power, population structure, and practical implications Multi-ancestry GWASs enhance discovery in diverse populations, but optimal methods remain debated. Using theory, simulations, and analyses from the UK Biobank and All of Us, we show that pooled analys...

Multi-ancestry GWAS can increase power and precision, but how should we analyze them? Pooled or stratified? We answer that question in a paper out today in AJHG, led by Julie Dias and Haoyu Zhang. 1/7 www.cell.com/ajhg/fulltex...

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)

Ultra-fast genetic colocalisation across millions of traits Colocalisation is a powerful approach to assess if two genetic association signals are likely to share a causal variant. However, association analyses in large biobanks and molecular quantitative trai...

After 1.5 years of work in @kauralasoo.bsky.social’s lab, we finally published my preprint! We introduce gpu-coloc, a GPU-accelerated implementation of coloc, show comparability to CLPP and aim to provide practical guidelines. Now accessible on BioRxiv: www.biorxiv.org/content/10.1...

Exploiting pleiotropy to enhance variant discovery with functional false discovery rates - Nature Computational Science This study introduces a cost-effective strategy called surrogate functional false discovery rates to increase power in genome-wide association studies by leveraging genetic correlations (or pleiotropy...

Excited to see our (w/ @chr1sw.bsky.social) work published in @natcomputsci.nature.com! We developed a new framework, surrogate functional false discovery rate (sffdr), that integrates summary statistics of related traits to improve power in GWASs.

Paper: www.nature.com/articles/s43...