iiinova — where your digital self keeps evolving

Finally, thanks to all my collaborators & to the reviewers for their kind feedback that improved our manuscript!

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At the same time, rapid growth under pesticide implies that dominance cannot be too low when alleles confer a fitness advantage. These observations are consistent with contextual dominance: alleles appear recessive when deleterious but dominant when beneficial.

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These two independent measurements allowed us to estimate both the cost and dominance of pesticide resistance: decline in exposed cages after pesticide removal requires a fitness cost, while persistence at low frequency in unexposed cages suggests low dominance.

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Simultaneously inferring both parameters is generally difficult, especially for deleterious alleles. In our experiment, however, costly resistant alleles remained low in unexposed cages; in exposed cages, they rose in frequency with pesticide application and began to decline once it was removed.

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Georgii "Yegor" Bazykin @gbazykin.bsky.social · 18/09/2025

How is functional variation at large-effect loci maintained in natural populations, even as environments change? In a paper led by @mkarag.bsky.social, we tracked known pesticide resistant alleles in outdoor 𝘋. 𝘮𝘦𝘭𝘢𝘯𝘰𝘨𝘢𝘴𝘵𝘦𝘳 cages & inferred selection and dominance from temporal sequencing data.

Glass beads of all sorts balancing on wavy threads.

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Reposted by Nastia Lyulina

Now hiring a computational postdoc (evolutionary genomics, molecular evolution) in my lab at Emory University. If you’re interested in population genetics, fitness landscapes, and viral evolution — get in touch. faculty-emory.icims.com/jobs/151181/...

faculty-emory.icims.com

Careers | Emory University | Atlanta GA

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Nastia Lyulina @alyulina.github.io · 06/08/2025

So excited for you and your group! Congrats!

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Reposted by Nastia Lyulina

Jonathan Pritchard @jkpritch.bsky.social · 07/07/2025

Staff scientist position (computational): I am looking for a computational scientist to join my genomics lab at Stanford. They should have an outstanding skillset in ML/statistical methods for genomic applications, postdoc experience and a strong publication record. #sciencejobs

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Nastia Lyulina @alyulina.github.io · 21/06/2025

Unfortunately not, but happy to chat offline!

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Nastia Lyulina @alyulina.github.io · 20/06/2025

Looking forward to #evolution2025! I will be talking about how time-varying demography and selection shape the site frequency spectrum — Saturday at 4:15 pm, Population Genetics Theory IV. Come say hi if you are around!

A schematic illustrating the allele frequency trajectories that contribute to a slice of the site frequency spectrum.

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Reposted by Nastia Lyulina

Jeff Spence @jeffspence.github.io · 02/06/2025

I'm excited to announce that I'll be starting a lab at UCSF in the @ihgatucsf.bsky.social and @ucsf-epibiostat.bsky.social in July. We'll work at the intersection of statistical genetics, population genetics, and machine learning.

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Karl Jacoby @karl-jacoby.bsky.social · 20/03/2025

Letter signed by members of the Columbia History Department urging resistance to the Trump Administration's efforts to dictate university policy. "Should this control be realized, here or elsewhere, it would make any real historical scholarship, teaching, and intellectual community impossible."

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Reposted by Nastia Lyulina

Fernando Rossine @fernpizza.bsky.social · 21/02/2025

Here we show that within-cell competition is key to plasmid evolution. Look at this photo of plasmids competing inside cells in a colony!!!

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Reposted by Nastia Lyulina

Aylwyn Scally @aylwyn-scally.bsky.social · 21/02/2025

We are excited to announce a new faculty position here in Cambridge, for researchers in computational and/or theoretical biology, based jointly in Genetics and Mathematics. Come and join us! Happy to answer questions about research, teaching and working here. www.jobs.cam.ac.uk/job/50414/

jobs.cam.ac.uk

Assistant/Associate Professor in Computational Biology - Job Opportunities - University of Cambridge

Assistant/Associate Professor in Computational Biology in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge.

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Grant Kinsler @grantkinsler.bsky.social · 17/02/2025

This allowed us to visualize the pattern of clones in the tumor! 10/16

A section of a tumor where each region of the tumor is colored by a distinct color which represents clonal growth in the tumor.

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Reposted by Nastia Lyulina

Amy Goldberg @amygoldberg.bsky.social · 16/02/2025

Project scientist in computational population genetics (post PhD/postdoc experience usually expected). recruit.apo.ucla.edu/JPF10171

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Nastia Lyulina @alyulina.github.io · 22/01/2025

Happy to have been part of this story!

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Reposted by Nastia Lyulina

Michael Baym @baym.lol · 17/01/2025

This paper has been a long time coming: We looked at the genomes of historical bacterial samples over a century to look for trends of antibiotic resistance genes, finding multiple instances of them in infections before the age of antibiotics, but an increase in both frequency and mobility after

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Nikhil Milind @nikhilmilind.dev · 12/11/2024

For many traits there is a correlation between the number of duplications or loss-of-function (LoF) mutations someone carries, and their phenotype. Curiously, for most traits, these effects are aligned in the SAME direction. Why?

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Nastia Lyulina @alyulina.github.io · 06/11/2024

I am glad to see this work in print & on the cover! Read more at academic.oup.com/genetics/article/228/3/iyae145/7747749

Artist's depiction of mutant lineages rising and falling in frequency, influenced by selection, recombination, and genetic drift. In this issue, Lyulina et al. develop a mathematical framework for quantifying the statistical associations between these variants. Image courtesy of Anastasia Lyulina.

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Moving forward, we hope that our theoretical framework can be a starting point for understanding frequency-resolved linkage more broadly. We would love to hear your thoughts!

Our analytical results lead to several empirically relevant findings, e.g. that the dependence of homoplasy on the frequencies of the alleles can distinguish the effects of recombination from the confounding effects of recurrent mutation and epistasis.

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We derive how these homoplasy measures depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles.

In this work, we analyze an alternative class of two-locus statistics that quantify the homoplasy produced by recombination. These measures vanish in the absence of recombination and recurrent mutation and approach one in the limit of linkage equilibrium.

Interpreting these decay curves is notoriously difficult since the magnitude of these correlations is shaped by phenomena like epistasis and demography in addition to recombination (e.g. from @nanditagarud.bsky.social et al. – can recombination be behind the fast decay at short distances?).

While a large body of population genetics theory has been devoted to this topic, much of our existing understanding has focused on pairwise correlations, and how they decay with the distance between loci.

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