chris macdonald

@ccmm.bsky.social

Postdoc @fraserlab @willowcoyote at UCSF, messing around with proteins. Sentimental empiricist.

Happy to share the final version of @oliviamghosh.bsky.social's paper on inferring low dimensional phenotype-fitness maps from high-throughput fitness measurements across environments. Fun collaboration with @oliviamghosh.bsky.social, @grantkinsler.bsky.social, & @petrovadmitri.bsky.social

PLOS Biology@plosbiology.org · 4mo ago

Predicting the effect of a #mutation on #fitness is hard. @oliviamghosh.bsky.social @petrovadmitri.bsky.social &co use fitness effects of adaptive yeast mutants to show that underlying genotype-phenotype-fitness maps are low-dimensional but context-dependent @plosbiology.org 🧪 plos.io/4dLy2Ez

Two models for the nature of pleiotropy in adaptation. Left: Schematic of the environmental structure in this study. Environments can be mapped onto a multidimensional environment space characterized by chemical and physical compositions. The large green circle represents an environment where adaptive mutants evolved, and the large pink circle is a distant environment. Around each base, a set of identical environmental perturbations (arrows) is applied, generating clusters of similar environments around distinct base environments. Top right: Schematic of fitnotype map for adaptive mutants near their home base environment. By measuring fitness in each of the green environments, one can infer how many fitnotypes matter for this set of mutants in their home environment. Here, only four of the possible 8 fitnotypes matter. Bottom right: When the mutants are moved to the distant base environment, and their fitness is measured in all pink environments (base and perturbations), there are two possibilities. Either more fitnotypes become important and the space appears higher-dimensional (left, pleiotropic expansion), or the set of fitnotypes that matters remains low-dimensional, but shifts (right, pleiotropic shift).

The data is in: the NIH goalposts have shifted. What were once almost certain fundable scores have become coin flips and what used to be likely grants have become aspirational, leading to fewer awards. Another manifestation of how HHS policies have led to fewer awards and less science.

Graph of award probability of R35 and R01 from NIH factbook as a function of review rank percentile. As is apparent, 2025 is a significant departure, with lower award probabilities at all scores <40 and significant departures from norm, where even being in the top 10% is no longer a nearly certain indicator of success.

Data source: https://report.nih.gov/nihdatabook/report/302