In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 17, No. 7 ( 2021-7-15), p. e1009157-
Abstract:
The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map. Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccharomyces cerevisiae and S. uvarum . The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes. Results highlighted that the negative correlation between production traits such as population carrying capacity ( K ) and traits associated with growth and fermentation rates ( J max ) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high J max was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results. This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1009157
DOI:
10.1371/journal.pcbi.1009157.g001
DOI:
10.1371/journal.pcbi.1009157.g002
DOI:
10.1371/journal.pcbi.1009157.g003
DOI:
10.1371/journal.pcbi.1009157.g004
DOI:
10.1371/journal.pcbi.1009157.g005
DOI:
10.1371/journal.pcbi.1009157.t001
DOI:
10.1371/journal.pcbi.1009157.t002
DOI:
10.1371/journal.pcbi.1009157.s001
DOI:
10.1371/journal.pcbi.1009157.s002
DOI:
10.1371/journal.pcbi.1009157.s003
DOI:
10.1371/journal.pcbi.1009157.s004
DOI:
10.1371/journal.pcbi.1009157.s005
DOI:
10.1371/journal.pcbi.1009157.s006
DOI:
10.1371/journal.pcbi.1009157.s007
DOI:
10.1371/journal.pcbi.1009157.s008
DOI:
10.1371/journal.pcbi.1009157.s009
DOI:
10.1371/journal.pcbi.1009157.s010
DOI:
10.1371/journal.pcbi.1009157.r001
DOI:
10.1371/journal.pcbi.1009157.r002
DOI:
10.1371/journal.pcbi.1009157.r003
DOI:
10.1371/journal.pcbi.1009157.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2193340-6
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