Jonathan Pritchard
My lab at Stanford studies human population genetics and complex traits.
- This promises to be a fantastic new meeting at the intersection of human genetics and modern high-throughput functional genomics.
- I'm thrilled to be heading back to the always-wonderful Biology of Genomes conference this year. Hope to see many of you there!
- Reposted by Jonathan PritchardThis paper is a great for teaching phylogenetic trees. "Ancient DNA reveals elephant birds and kiwi are sister taxa and clarifies ratite bird evolution" Clearly written. It discusses hypotheses of relatedness among species via continental drift vs genetic data. 🧪 www.science.org/doi/10.1126/...
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- Reposted by Jonathan PritchardNew preprint on technologies to scale up CRISPR screens. We use them to map 665,856 pairwise genetic perturbations and outline a path to comprehensive interaction mapping in human cells. We also introduce an approach for cloning lentiviral libraries with billions of elements.
- Reposted by Jonathan PritchardRegistration for the 2026 NY Area Population Genetics meeting is now open, at events.simonsfoundation.org/e0mEoL?rt=8k.... Registration is free but required; if you are submitting an abstract, note that the deadline is *January 30th*.
- SAVE THE DATE: the yearly NY Population Genetics meeting will be back on March 9 2026, generously hosted by the @simonsfoundation.org. Details to follow. Please RT.
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- Reposted by Jonathan PritchardClever use of proteomic data to stress-test TWAS and QTL colocalization methods, revealing a high false sign rate. This hypothesis about high-LD and cross-tissue confounding is particularly interesting:
- 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
- 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 👇
- 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
- Reposted by Jonathan PritchardTogether 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
- I'm just delighted to announce our new preprint on genome-scale perturb-seq in CD4+ T cells. We learned both general lessons about the power of perturb-seq, and specific lessons about T cell biology. Led by amazing postdocs Emma Dann and Ronghui Zhu, with my wonderful collaborator Alex Marson.
- 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
- Reposted by Jonathan PritchardDelighted to have our work on 🧬 resilience to 🩸cancer led by @g-agarwal.bsky.social & amazing collaborators, including @kharaslab.bsky.social, published in @science.org: www.science.org/doi/10.1126/... 🧵
- Sunset on 2025. Wishing my Bluesky friends all the very best in the new year.
- Reposted by Jonathan PritchardOne of the most pleasant surprises of the past 20 years was the transformation of Wikipedia into arguably the most reliable general information source freely accessible to the public. It’s not perfect — I’ve certainly seen errors — but it’s kind of shockingly good. One might consider a donation.
- I love this plot illustrating the famous generation-time effect on mutation rates with modern data!
- Reposted by Jonathan PritchardHappy to highlight an essay I wrote together with @marcdemanuel.bsky.social, @natanaels.bsky.social and Anastasia Stolyarova, trying to think through what sets the mutation rate of a cell type in an animal species: www.biorxiv.org/content/10.6... 1/n
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- Reposted by Jonathan PritchardAll right it’s time for the annual “please tell us about one (or a few if you are ambitious) paper from 2025 that really impressed you and why we should all read it“! Go! If you tell us how it changed your view of the world and what makes it so powerful and consequential It would be excellent.
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- Reposted by Jonathan PritchardNow TWO great new papers on why frequencies of disease genes rarely match expectations Here was the first: www.nature.com/articles/s41...
- Our latest preprint revisits the classic model of mutation-selection balance. Do human recessive genes fit Haldane's 100-year old model? This work is by the wonderful @jonj-udd.bsky.social, and co-mentored by @jeffspence.github.io www.biorxiv.org/content/10.6...
- Our latest preprint revisits the classic model of mutation-selection balance. Do human recessive genes fit Haldane's 100-year old model? This work is by the wonderful @jonj-udd.bsky.social, and co-mentored by @jeffspence.github.io www.biorxiv.org/content/10.6...
- One of the most basic theories in popgen predicts the equilibrium frequency of genetic diseases when there is balance between new mutations and removal by selection A key prediction is that recessive mutations are much more common than (co)dominant mutations as they are only selected in homozygotes
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- GWAS has been an incredible discovery tool for human genetics: it regularly identifies *causal* links from 1000s of SNPs to any given trait. But mechanistic interpretation is usually difficult. Our latest work on causal models for this is out yesterday: www.nature.com/articles/s41... A short🧵:
- My mental model for why GWAS interpretation is hard is that genes are connected through *unknown* gene regulatory networks in relevant cell types, and many/most hits come from dispersed effects. We wrote about this idea in our "Omnigenic Model" papers in 2017/19
- Reposted by Jonathan PritchardAfter time in the Bay Area, I’ve started a new role as Lecturer in the Department of Allergy and Rheumatology at the University of Tokyo. We’re the group of clinicians who see patients with autoimmune diseases, while researching new treatments and patient stratification. (continued)
- Reposted by Jonathan PritchardOur latest collaboration with @jkpritch.bsky.social – led by joint post-doc Mineto Ota – is in @nature.com today: www.nature.com/articles/s41...
- Reposted by Jonathan PritchardOur new ancient DNA paper has just been published! We present 28 new genomes from southern Africa - several of them high-coverage whole genomes. Exciting to be moving towards population-level representation of ancient southern African genetic diversity! www.nature.com/articles/s41...
- Reposted by Jonathan PritchardCongratulations to Richard Durbin on being awarded our Genetics Society Medal!
- Reposted by Jonathan PritchardIt was a total pleasure to work with @roshnipatel.bsky.social on this, who really led the charge in all respects. Anyone interested in learning about the intersection of population genetics and statistical genetics should check out her new lab in Oregon!
- Excited to share work from my postdoc with @docedge.bsky.social and collaborators Matt Pennell and @jgschraiber.bsky.social, newly out over the weekend: www.biorxiv.org/content/10.1... (1/6)
- Reposted by Jonathan PritchardGrateful to Isabella Alves & @cterminiphd.bsky.social for writing this fantastic N&V in @natcellbio.nature.com: www.nature.com/articles/s41... Nicely covers our 📰 led by della Volpe & co: www.nature.com/articles/s41...
- Reposted by Jonathan PritchardThe last work of my PhD is finally out: www.pnas.org/doi/10.1073/...! This work is about accurately estimating branch length in the Ancestral Recombination Graph (ARG), which is achieved by a really simple framework with minimal assumptions. (1/n)
- Reposted by Jonathan PritchardSuper excited about our schedule for BAPG at stanford on Dec 6. bapg2025.github.io/bapg2025stan... Amazing talks, a fabulous keynote, a lively poster session. A brilliant and interactive community. What’s not to love? 1/2 @sophiejwalton.bsky.social
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- Reposted by Jonathan PritchardAn empirical approach to evaluating the prevalence of long-lived balancing selection in humans--and important limitations. Work by @hannahmm.bsky.social
- Revisiting the evidence for long-lived balancing selection in humans. biorxiv.org/content/10.1101/202…
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- Excited to share our latest work on the factors that determine what genes we find (and don't find!) in GWAS and burden tests. We describe a critical concept that we call *specificity*. Led by Jeff Spence and Hakhamanesh Mostafavi:
- How do GWAS and rare variant burden tests rank gene signals? In new work @nature.com with @hakha.bsky.social, @jkpritch.bsky.social, and our wonderful coauthors we find that the key factors are what we call Specificity, Length, and Luck! 🧬🧪🧵 www.nature.com/articles/s41...
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- Reposted by Jonathan PritchardProud of the latest edition of my free intro biostats book. gitrepo: github.com/ybrandvain/b... book: ybrandvain.github.io/biostats/ Not complete but at a good point to take a break, and I think its quite usable dm me with comments , ideas etc
- Reposted by Jonathan PritchardFor population genetics and evolutionary biology folks in the Bay Area: the next BAPG will be hosted by Stanford CEHG and the Petrov lab at Stanford on 12/6. Registration is free but required. The deadline for talk submission is Nov. 16. Hope to see you soon! Pls RT! docs.google.com/forms/d/e/1F...
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- I want to try something again at #ASHG25 this year: I'll block some time on Thursday and Friday afternoons to meet with trainees who would be interested to chat on any topic. I did this last year and it was great to meet a whole bunch of new people, at all career stages!
