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Aaron New

@aaronmnew.bsky.social
18 followers 55 following 0 posts

quantitative genetics and evolution for useful things - Founder and CEO at Cisgenica

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Reposted by Aaron New
Rishi De-Kayne @rishidekayne.bsky.social · 12/06/2026
🚨 We're hiring computational evolutionary biologists! 🚨 Boosting this - industry evolutionary biology jobs don't come along often, so if you're excited to apply your computational evolutionary biology skills to cutting-edge problems, let's talk! 🧪🧬💻
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Reposted by Aaron New
bioRxiv Synthetic Biology @biorxiv-synthbio.bsky.social · 03/03/2026
High Diversity Gene Libraries Facilitate Machine Learning Guided Exploration of Fluorescent Protein Sequence Space www.biorxiv.org/content/10.64898/20…
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Reposted by Aaron New
Adrian Liston @labliston.bsky.social · 30/01/2026
Our new book "Self-Doubt" is written by scientists for scientists. You might think you are alone when you doubt your ability or suitability for science - you aren't. We all question ourselves and carry doubt with us daily. www.amazon.co.uk/Self-Doubt-A...
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Reposted by Aaron New
Will Ratcliff @wcratcliff.bsky.social · 09/12/2025
1/28 New preprint up, which I think is the best theoretical idea I've ever had. We asked a simple question: what are the costs of investment into non-reproductive somatic cells? Turns out these costs decrease with the *logarithm* of organism size! www.biorxiv.org/content/10.6...
biorxiv.org
The fitness costs of reproductive specialization scale inversely with organismal size
The evolution of reproductive specialization represents a fundamental innovation in multicellular life, yet the conditions favoring its evolution remain poorly understood. Here, we develop a populatio...
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Reposted by Aaron New
Joseph Schacherer @schacherer.bsky.social · 11/12/2025
🚨 New preprint! 🚨@haploteam We built a barcoded collection of 520 natural S. cerevisiae isolates and screened 600+ natural compounds. Six functional response clusters and 100+ GWAS associations reveal how natural variation shapes chemical sensitivity. 🔗 Read the preprint: doi.org/10.64898/202...
doi.org
Population-scale chemical response revealed by a barcoded yeast collection
Natural genetic variation shapes how microbial populations adapt to environmental and chemical challenges, but scalable approaches to map genotype-phenotype relationships across diverse genetic backgr...
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Reposted by Aaron New
Zayna Khayat, PhD @zaynakhayat.bsky.social · 14/11/2025
@oecd-ocde.bsky.social state of health at a glance oe.cd/6gn
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Reposted by Aaron New
Keith Robison @omicsomics.bsky.social · 13/11/2025
A cadre of former colleagues is developing software tools for tracking designed genome edits, propagating annotations to the edited genomes & aligning in a graph-aware manner to assess the success of editing If you are a synthetic biologist, you should check it out bsky.app/profile/hofe...
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Reposted by Aaron New
David Hofer @hofer.bsky.social · 05/11/2025
Some news: Last April, I left Ginkgo Bioworks after 8+ years as a software engineer there. Since then, I’ve been working on starting a new company called GenHub with a couple other ex-Ginkgo people, Bob Van Hove and Chris Mitchell. (1/5)
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Reposted by Aaron New
Joao Ascensao @joaoascensao.bsky.social · 21/08/2025
How common are frequency dependent fitness effects? New preprint out today 👇 doi.org/10.1101/2025...
doi.org
Frequency-dependent fitness effects are ubiquitous
In simple microbial populations, the fitness effects of most selected mutations are generally taken to be constant, independent of genotype frequency. This assumption underpins predictions about evolutionary dynamics, epistatic interactions, and the maintenance of genetic diversity in populations. Here, we systematically test this assumption using beneficial mutations from early generations of the Escherichia coli Long-Term Evolution Experiment (LTEE). Using flow cytometry-based competition assays, we find that frequency-dependent fitness effects are the norm rather than the exception, occurring in approximately 80\% of strain pairs tested. Most competitions exhibit negative frequency-dependence, where fitness advantages decline as mutant frequency increases. Furthermore, we demonstrate that the strength of frequency-dependence is predictable from invasion fitness measurements, with invasion fitness explaining approximately half of the biological variation in frequency-dependent slopes. Additionally, we observe violations of fitness transitivity in several strain combinations, indicating that competitive relationships cannot always be predicted from fitness relative to a single reference strain alone. Through high-resolution measurements of within-growth cycle dynamics, we show that simple resource competition explains a substantial portion of the frequency-dependence: when faster-growing genotypes dominate populations, they deplete shared resources more rapidly, reducing the time available for fitness differences to accumulate. Our results demonstrate that even in a simple model system designed to minimize ecological complexity, subtle ecological interactions between closely related genotypes create frequency-dependent selection that can fundamentally alter evolutionary dynamics. ### Competing Interest Statement The authors have declared no competing interest.
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Reposted by Aaron New
Omaya Dudin 𓂆 ¦🍉¦🦠¦🔬¦ @dudinlab.bsky.social · 31/10/2025
🚨Our collaboration with @centriolelab.bsky.social & @gautamdey.bsky.social is out today in @cp-cell.bsky.social We show that #Expansion #Microscopy is a broad-spectrum modality for Euks, enabling 3D phenotypic maps rooted to phylogeny. #ProtistsOnSky #SciComm #SciSky www.cell.com/cell/fulltex...
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