Supreet Saini

This study shows that asexual adaptation in yeast leads to dynamic, environment-dependent changes in mating efficiency that are often reversible and do not lead to stable reproductive isolation.

The paper examines genomic variation in membrane and cytoplasmic proteins across E. coli and S. cerevisiae, finding higher non-synonymous variation and lower synonymous variation in membrane proteins.

This study shows that copy number variations (CNVs) dominate genome evolution in yeast adapting to glucose or galactose, with opposing CNV dynamics in each environment.

This study shows that adaptation to similar environments leads to unpredictable adaptive responses but predictable pleiotropic effects based on ancestral fitness.

The paper shows that facultative cheating and hybrid vigor resolve cooperator-cheater conflict in a yeast public goods system by enabling phenotypic flexibility through hybridization.

This study shows that subtle environmental changes in sugar presentation alter genetic and phenotypic adaptation in yeast, with predictable pleiotropic effects.

The paper shows that metabolic constraints influence global epistasis, making fitness effects less predictable as genetic divergence increases.

This study provides empirical evidence of resource-dependent changes in payoff matrices of Saccharomyces cerevisiae populations, showing three distinct evolutionary outcomes based on carbon source and genotypes.

This study shows that synonymous and single nucleotide mutations can alter protein localization and fitness in a horizontally transferred gene.

The paper analyzes epistasis in an E. coli gene's fitness landscape, showing that pairwise epistasis is fluid and binary, with most mutations lacking strong global patterns.

The paper presents a stochastic gene expression model of cell growth that explains the growth advantage of metabolic exchange and auxotrophy in microbial communities.

The paper models optimal lysogenic propensity for viruses in stressed environments, finding it depends on MoI and stress intensity.

The paper develops a stochastic model to study actin treadmill regulation in Plasmodium, focusing on maintaining filament size and understanding regulator interactions.