ArticleProceedings of the National Academy of Sciences of the United States of America2012
Dynamic epistasis for different alleles of the same gene.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 26 citations in OpenAlex.
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- SNPeffect: identifying functional roles of SNPs using metabolic networks.The Plant journal : for cell and molecular biology · 2020Article
- Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway.Science advances · 2020Article
- Genomic Variation, Evolvability, and the Paradox of Mental Illness.Frontiers in psychiatry · 2020Article
- Recent insights into the genotype-phenotype relationship from massively parallel genetic assays.Evolutionary applications · 2019Review
- Flux balance analysis with or without molecular crowding fails to predict two thirds of experimentally observed epistasis in yeast.Scientific reports · 2019Article
- Improved discovery of genetic interactions using CRISPRiSeq across multiple environments.Genome research · 2019Article
- Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations.Scientific reports · 2018Article
- Dynamic epistasis under varying environmental perturbations.PloS one · 2015Article
- Abundant local interactions in the 4p16.1 region suggest functional mechanisms underlying SLC2A9 associations with human serum uric acid.Human molecular genetics · 2014Article
- Molecular network analysis enhances understanding of the biology of mental disorders.BioEssays : news and reviews in molecular, cellular and developmental biology · 2014Review
- The strength of genetic interactions scales weakly with mutational effects.Genome biology · 2013Article
- Yeast 5 - an expanded reconstruction of the Saccharomyces cerevisiae metabolic network.BMC systems biology · 2012Article
- Computational approaches for understanding energy metabolism.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Epistasis refers to the phenomenon in which phenotypic consequences caused by mutation of one gene depend on one or more mutations at another gene. Epistasis is critical for understanding many genetic and evolutionary processes, including pathway organization, evolution of sexual reproduction, mutational load, ploidy, genomic complexity, speciation, and the origin of life. Nevertheless, current understandings for the genome-wide distribution of epistasis are mostly inferred from interactions among one mutant type per gene, whereas how epistatic interaction partners change dynamically for different mutant alleles of the same gene is largely unknown. Here we address this issue by combining predictions from flux balance analysis and data from a recently published high-throughput experiment. Our results show that different alleles can epistatically interact with very different gene sets. Furthermore, between two random mutant alleles of the same gene, the chance for the allele with more severe mutational consequence to develop a higher percentage of negative epistasis than the other allele is 50~70% in eukaryotic organisms, but only 20~30% in bacteria and archaea. We developed a population genetics model that predicts that the observed distribution for the sign of epistasis can speed up the process of purging deleterious mutations in eukaryotic organisms. Our results indicate that epistasis among genes can be dynamically rewired at the genome level, and call on future efforts to revisit theories that can integrate epistatic dynamics among genes in biological systems.
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