Buscamos una/un postdoc entusiasta y motivada para unirse al grupo de Paleogenómica y Biología Evolutiva en @liigh-unam.bsky.social para liderar un proyecto enfocado a muestras humanas prehispánicas. Interesadxs ​por favor enviar CV y ​​carta de intención a [email protected]. Por favor #RT.

(Observation 3) Qualitative trends of portability can depend on the measure of prediction accuracy used. For some traits our measure of group-level prediction accuracy often drops where at the individual level, it increases. (19/27)

Relatedly, some cool recent work from @roshnipatel.bsky.social, Jeffrey Spence, @jkpritch.bsky.social et al. dives deep into expectations, based on models of natural selection, for allele frequency in a group B conditional on allele frequency in group A. academic.oup.com/genetics/art... (16/27)

(Observation 1) Previous work suggested genetic distance from the GWAS sample largely explains variation in PGS performance. However, what we see empirically is that prediction accuracy is extremely noisy at the individual level. (5/27)

Our work on the generalizability of polygenic scores (PGS) from the @arbelharpak.bsky.social Lab is now officially out! We examine the accuracy of PGS predictions at the individual level. We make 3 observations that expose gaps in our understanding of PGS “portability.” rdcu.be/e0LAr (1/27)

The number of people arguing, following the #NeurIPS2025 case, that a bit of systematically bad scholarship and borderline academic misconduct is OK because doing things the right way is tedious and time-consuming is concerning. Yes, doing things well might be boring. But doing them badly is... bad

1/ Our new study, led by Jingwen Ding, examines the role of transcription factors during human neurogenesis to identify gene regulatory networks influencing cell fate, maturation, and subtype specification www.nature.com/articles/s41...

Choice of phenotype scale is critical in biobank-based GxE tests https://www.biorxiv.org/content/10.64898/2026.01.20.694695v1

Balancing selection maintains some remarkable biological diversity, but detecting it from genomic data alone can be tricky. This may bias our view of its true prevalence. We investigated what makes balancing selection more or less detectable in genomic scans. + in thread & preprint!

Pregnancy loss is common in humans, and chromosomal abnormalities are the leading cause. Using genetic data from ~140,000 IVF embryos, we show that maternal variation in meiosis genes influences recombination and aneuploidy risk. First authors: @saracarioscia.bsky.social & @aabiddanda.github.io

General moment closure for the neutral two-locus Wright-Fisher dynamics https://www.biorxiv.org/content/10.64898/2026.01.16.700021v1

We invite you to join our seminar at UCSF Mission Bay campus with @odedrechavi.bsky.social from Tel Aviv University humangenetics.ucsf.edu/ihg-seminar-...

New preprint! and my first single-author paper, so bear with me. www.biorxiv.org/content/10.6... Malaria population genetic studies have found some puzzling patterns: Ne estimates spanning orders of magnitude, genome-wide negative Tajima's D, and over a quarter of genes with πN/πS >1 1/n

But once again, the same trait can show very different sign bias across biobanks. Example: we estimate 72% of rare minor alleles (sign bias of 0.44) increase risk of type 2 diabetes in All of Us, while ~all increase risk in UK Biobank. Why? (11/21)

Excited to share our new preprint from the @arbelharpak.bsky.social Lab! How do recruitment into genetic studies and study characteristics impact what we infer about the genetic bases of traits, and what are the consequences? (1/21) www.biorxiv.org/content/10.6...

We (with Fanny Pouyet and Brian Charlesworth) provide a theoretical perspective on rescaling forward simulations in population genetics, along with some guidelines: arxiv.org/abs/2601.05367

Excited to see this out www.nature.com/articles/s41...! Nonparametric kernel-based tests for spatially variable isoform usage in spatial transcriptomics. So many interesting examples in the CNS and cancer, we're only scratching the surface!

Clever 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:

Happy to share our new preprint from @sashagusevposts.bsky.social and @nmancuso.bsky.social labs! We introduce Mr. PEG, a framework integrating perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits. (1/n) www.medrxiv.org/content/10.6...

“Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex traits” Very nice @medrxivpreprint.bsky.social study by @zeyunlu.bsky.social @sashagusevposts.bsky.social & colleagues 🧪🧬 www.medrxiv.org/content/10.6...

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 👇

Furthermore, Ron explored how perturbation outcomes grouped regulators that act coherently on transcriptional programs. Several known programs emerge, but the real magic is the context specificity: many programs and their regulators change drastically across different stimulation conditions.

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

Interesting to search for works with “Genetics” in the title in Anthropic Works List Lookup to see what was stolen and ingested. #Genetics #AI #Anthropic secure.anthropiccopyrightsettlement.com/lookup

Congrats @jeffgroh.bsky.social et al. Some avocado trees open female-phase flowers in the morning & then male in afternoon. Others show complementary pattern (m->f), to synchronize pollination of two types. Jeff show this to be a >45Mya polymorphism at a transcription factor across 100s of species.

Boring, field-specific answer. This SMART-PTA technology, which allows genotype + phenotype in hundreds of somatic cells, will lead to an expansion of population genetics for somatic cells as a field. www.biorxiv.org/content/10.1...

This is a really cool paper

In the December issue of #GENETICS, @jeremyjberg.bsky.social et al. introduce an evolutionary model of complex disease susceptibility, identifying how diseases are shaped by selection acting on other pleiotropically related traits. buff.ly/QTZPpYQ

How much better is an ancestral recombination graph (ARG) than a site frequency spectrum (SFS)? For recovering mutation rate history, we can answer fairly precisely because both ARG and SFS are linear transforms of mutation rate history. This blog post uses spectral analysis to clarify the picture.

In fact, they appear to be eerily similar. The per generation mutation rate seems to lay between 10-9 and 10-8 per bp in all animal taxa surveyed to date–despite vast differences in environments, life histories, and three orders of magnitude variation in the generation time: 4/n

Happy 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

No contest. Just read the first two sentences of the abstract. www.nature.com/articles/s41...

This paper by Celentano et al. on scalable simulation under the birth death is one of my favourites for the year! It introduces some elegant thinning that has been sorely needed. Fantastic to pave the way forward for future simulation-heavy inference, including neural Bayes! doi.org/10.1073/pnas...

I guess the preprint came out in 2024 but it was published this year so I'll say this paper from @jeffspence.github.io and @hakha.bsky.social which is probably the paper that pleiotropy-pilled me the most. Really got me to think about what GWAS means www.nature.com/articles/s41...

All 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.

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

But if each gene is doing multiple jobs, then every phenotypical trait is controlled by multiple genes. Even homozygous deleterious mutations are doing something else when in heterozygous form: doi.org/10.64898/202... Complexity is the norm, more complexity than what fits in the human imagination

This is a good time to talk about the TRUE genetics revolution brought in by sequencing the human genome: The genetic underpinning of traits is not simple, will never be simple. Complex gene-gene interactions are the rule, not the exception 🧵 www.nature.com/articles/d41...

Published online on Jan 2, 2025 and just appeared in the December 2025 issue!

A heads up for people using scipy.sparse.linalg.expm_multiply to solve linear ODEs -- the function appears to have some randomness that is not documented, but appears to be fixable by setting numpy.random.seed beforehand. github.com/scipy/scipy/issues/24188

Happy to share my work with my advisor Zachary Szpiech! Why are associations between ROH & complex traits inconsistent across studies? We use realistic simulations to show how demographic history and genetic architecture interact to shape the phenotypic impact of ROH. www.biorxiv.org/content/10.6...

While stories of singular DNA changes that drove evolution of human brain/behaviour remain seductive, advances across multiple fields of biology cast doubt on such simplistic narratives of our origins. A new paper from my lab shows how biobanks may speak to this fundamental question.🧪 Explainer🧵👇1/n

Grateful to share our paper on gene-specific selective sweeps in human gut microbiomes, now out in Nature! It has been a joy to work with @rwolff.bsky.social, whose insights and hard work made this possible. www.nature.com/articles/s41...

Have you ever wondered: just how strong *is* the evidence for Muller's ratchet on mtDNA? Well, wonder no more! (Project led by Yu Mo, with @smishra677.bsky.social and @yadirapga.bsky.social) "No molecular evidence for Muller's ratchet in mitochondrial genomes" www.biorxiv.org/content/10.6...

I'm hiring a postdoc with a flexible start date (any time in 2026). Come work with us on topics at the interface of machine learning, biophysics, a nonequilibrium statistical mechanics. If interested, send me a CV and a short summary of why you think you'd be a good fit. statmech.stanford.edu

"Together, these results suggest that most selection experienced by pathogenic mutations in recessive disease genes may be due to stabilizing selection in heterozygotes [due to pleiotropy]. We conclude that very few human genes follow the classic model of recessive mutation-selection balance."

Well well. The standard model for how frequencies of recessive disease genes are established doesn't work. And that seems to be because recessive variants are visible to selection due to pleiotropy. (But still we teach Mendelian genetics...) www.biorxiv.org/content/10.6...

Preprint online right before the holidays! Excited to share the first piece of work from the Zhang Lab, led by my absolutely stellar postdoc Michelle Kim! In this work, we ask how admixture, selection and demography shape complex trait genetics and GWAS performance www.biorxiv.org/content/10.6...

Congratulations to the winners of the 2025 Genomic History Inference Strategies Tournament challenges! Among the 9 challenges, we had five winners: @alwaysrong.bsky.social, @adaigle.bsky.social, @andrewhvaughn.bsky.social, @thymelicus.bsky.social, @rgollnisch.bsky.social