Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.

population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2026-09-01
DOI
https://doi.org/10.1093/nargab/lqag084
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.

Shin‐Han Shiu, Melissa D. Lehti‐Shiu, Paulo Izquierdo, Kenia E Segura Abá et al.
PubMed
Evolution and Genetic Dynamics
article

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.

Shin‐Han Shiu, Melissa D. Lehti‐Shiu, Paulo Izquierdo, Kenia E Segura Abá, Gustavo de Los Campos
article en

Abstract

population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

PubMedVol. 8(3)
New Mexico State University (US), Great Lakes Bioenergy Research Center (US), Michigan State University (US)
Zero hunger
Openalex Percentile: Top 15%
Evolution and Genetic Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.