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- W2973303153 abstract "The general framework of this thesis is the issue of the genotype-phenotype relationship, through the analysis of the heterosis phenomenon in yeast, in an approach combining biology, mathematics and statistics. Prior to this work, a very large set of heterogeneous data, corresponding to different levels of organization (proteomics, fermentation and life history traits), had been collected on a semi-diallel design involving 11 strains belonging to two species. This type of data is ideally suited for multi-scale modelling and for testing models for predicting the variation of integrated phenotypes from protein and metabolic (flux) traits, taking into account dependence patterns between variables and between observations. I first decomposed, for each trait, the total genetic variance into variances of additive, inbreeding and heterosis effects, and showed that the distribution of these components made it possible to define well-defined groups of proteins in which most of the characters of fermentation and life history traits took place. Within these groups, the correlations between the variances of heterosis and inbreeding effects could be positive, negative or null, which was the first experimental demonstration of a possible decoupling between the two phenomena. The second part of the thesis consisted of interfacing quantitative proteomic data with the yeast genome-scale metabolic model using a constraint-based modelling approach. Using a recent algorithm, I looked, in the space of possible solutions, for the one that minimized the distance between the flux vector and the vector of the observed abundances of proteins. I was able to predict unobserved fluxes, and to compare correlation patterns at different integration levels. Data allowed to distinguish between two major types of fermentation or life history traits whose biochemical interpretation is consistent in terms of trade-off, and which had not been highlighted from quantitative proteomic data alone. Altogether, my thesis work allows a better understanding of the evolution of the genotype-phenotype map." @default.
- W2973303153 created "2019-09-26" @default.
- W2973303153 creator A5044847011 @default.
- W2973303153 date "2019-07-08" @default.
- W2973303153 modified "2023-09-24" @default.
- W2973303153 title "Mathematical modelling and integration of complex biological data : analysis of the heterosis phenomenon in yeast" @default.
- W2973303153 hasPublicationYear "2019" @default.
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