Thesis defense: Helena Martins

on the September 26, 2018

September 26, 2018 at 2:00 pm
Helena Martins from TIMC – BCM will defend her thesis “Statistical Methods to Identify Local Adaptation in Continuous and Admixed Populations”. Her thesis is directed by Olivier François (co-director: Michael Blum).
Statistical Methods to Identify Local Adaptation in Continuous and Admixed Populations
 

Abstract

Finding genetic signatures of local adaptation is of great interest for many population genetic studies. Conventional approaches to sorting selective loci from their genomic
background focus on the extreme values of the fixation index, FST, across loci. However, the computation of the fixation index becomes challenging when the
population is genetically continuous, when predefining subpopulations is a difficult task, and in the presence of admixed individuals in the sample. In this thesis, we
present a new method to identify loci under selection based on an extension of the FST statistic to samples with admixed individuals. Considering statistical methods to
identify local adaptation in admixed population, we included spatial data to compute ancestry coefficients and allele frequencies. To extend our work, we investigated the effects of linkage disequilibrium and LD-pruning methods in genome scans for selection. In conclusion, this PhD work, makes possible the application of genome scans for selection in presence of admixed individuals and, open new spaces for numerous and varied biological analyses.

Key-words

population genetics, genome scans for selection, admixed populations, population differentiation tests, linkage disequilibrium, biostatistics.

Jury members

Mathieu GAUTIER, Researcher, INRA, Rapporteur
Stéphanie MANEL, Study director, CEFE/CNRS, Rapporteur
Laurence DESPRES, Professor, UGA, Examiner
Yves VIGOUROUX, Research director, IRD, Examiner
Michael BLUM, Research director, CNRS, Co-director of the thesis
Olivier FRANÇOIS, Professor, Grenoble INP, Director of the thesis

Published on September 11, 2018

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