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Anne-Céline Thuillet

Researcher at Institut de recherche pour le développement

Publications -  21
Citations -  2310

Anne-Céline Thuillet is an academic researcher from Institut de recherche pour le développement. The author has contributed to research in topics: Domestication & Gene. The author has an hindex of 17, co-authored 21 publications receiving 2040 citations. Previous affiliations of Anne-Céline Thuillet include University of Wisconsin-Madison & Institut national de la recherche agronomique.

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Maize association population: a high-resolution platform for quantitative trait locus dissection.

TL;DR: In this paper, the authors describe the population structure of the 302 lines, and investigate the relationship between population structure and various measures of phenotypic and breeding value, finding that on average, their estimates of population structure account for 9.3% of phenotype variation, roughly equivalent to a major quantitative trait locus (QTL).
Journal ArticleDOI

Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations

TL;DR: In this paper, the authors provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection, and investigate the power and robustness of eight methods to identify loci potentially under selection.

Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations : [W633]

TL;DR: In this article, the authors provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection, and investigate the power and robustness of eight methods to identify loci potentially under selection.
Journal ArticleDOI

Estimation of Long Term Effective Population Sizes through the History of Durum Wheat using Microsatellite Data

TL;DR: It is demonstrated from simulations that the unbiased estimator of θ based on Nei's heterozygosity is the most appropriate for estimating Ne because of a small variance and a relative robustness to variations in the mutation model compared to other estimators.