R
Renaud Rincent
Researcher at Institut national de la recherche agronomique
Publications - 37
Citations - 1314
Renaud Rincent is an academic researcher from Institut national de la recherche agronomique. The author has contributed to research in topics: Selection (genetic algorithm) & Population. The author has an hindex of 15, co-authored 25 publications receiving 927 citations. Previous affiliations of Renaud Rincent include Blaise Pascal University & University of Auvergne.
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Journal ArticleDOI
Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds ( Zea mays L.)
Renaud Rincent,Denis Laloë,Stéphane Nicolas,Thomas Altmann,Dominique Brunel,Pedro Revilla,Víctor M. Rodríguez,Jesús Moreno-González,Albrecht E. Melchinger,Eva Bauer,C-C. Schoen,Nina Meyer,Catherine Giauffret,Cyril Bauland,Philippe Jamin,Jacques Laborde,Hervé Monod,Pascal Flament,Alain Charcosset,Laurence Moreau +19 more
TL;DR: In this article, different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix (RA-BLUP) were used to select the reference individuals.
Journal ArticleDOI
Intraspecific variation of recombination rate in maize
Eva Bauer,Matthieu Falque,Hildrun Walter,Cyril Bauland,Christian Camisan,Laura Campo,Nina Meyer,Nicolas Ranc,Renaud Rincent,Wolfgang Schipprack,Thomas Altmann,Pascal Flament,Albrecht E. Melchinger,Monica A. Menz,Jesús Moreno-González,Milena Ouzunova,Pedro Revilla,Alain Charcosset,Olivier C. Martin,Chris-Carolin Schön +19 more
TL;DR: The present work provides the most comprehensive study on intraspecific variation of recombination rates and crossover interference strength in eukaryotes and should pave the way for precise identification of genes controlling recombinations rates in maize and other organisms.
Journal ArticleDOI
Phenomic Selection Is a Low-Cost and High-Throughput Method Based on Indirect Predictions: Proof of Concept on Wheat and Poplar.
Renaud Rincent,Jean-Paul Charpentier,Patricia Faivre-Rampant,Etienne Paux,Jacques Le Gouis,Catherine Bastien,Vincent Segura +6 more
TL;DR: This work proposed using near-infrared spectroscopy as a high-throughput, low cost and non-destructive tool to indirectly capture endophenotypic variants and compute relationship matrices for predicting complex traits, and coined this new approach ”phenomic selection” (PS).
Journal ArticleDOI
Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium
Renaud Rincent,Laurence Moreau,Hervé Monod,Estelle Kuhn,Albrecht E. Melchinger,Rosa Ana Malvar,Jesús Moreno-González,Stéphane Nicolas,Delphine Madur,Valérie Combes,Fabrice Dumas,Thomas Altmann,Dominique Brunel,Milena Ouzunova,Pascal Flament,Pierre Dubreuil,Alain Charcosset,Tristan Mary-Huard +17 more
TL;DR: Two alternative approaches to estimating the kinship matrix to recover power in regions of high LD were considered and were efficient to control false positives and were more powerful than classical models.
Journal ArticleDOI
Association mapping for cold tolerance in two large maize inbred panels
Pedro Revilla,Víctor M. Rodríguez,Amando Ordás,Renaud Rincent,Alain Charcosset,Catherine Giauffret,Albrecht E. Melchinger,Chris-Carolin Schön,Eva Bauer,Thomas Altmann,Dominique Brunel,Jesús Moreno-González,Laura Campo,Milena Ouzunova,A. Alvarez,Jose Ignacio Ruiz de Galarreta,Jacques Laborde,Rosa Ana Malvar +17 more
TL;DR: These results open new possibilities to genetically improve cold tolerance either with genome-wide selection or with marker assisted selection.