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Génétique Quantitative et Évolution - Le Moulon

GQMS - Quantitative Genetics and Plant Breeding Methodology

GQMS teams

1. Understand the organization of diversity in Maize

We aim at understanding the effect of historical and modern breeding on the evolution and adaptation of open pollinated and hybrid varieties, in terms of phenotypic variation, global organization of genetic diversity and polymorphism at the genome scale.

2. Decipher quantitative trait architecture

We aim at investigating the genetic determinism of complex traits, in view of direct applications in breeding through marker assisted selection and/or genomic selection but also to gain a better understanding of the type of genetic effects which are involved. Our objective is also to valorize multi-omics data that are now available to get a better insight into agronomical trait variation and regulation.

Specific attention is paid to flowering time, productivity under abiotic environmental constraints (more particularly abiotic stresses), performances stability and hybrid performances in Maize in relationship to global climatic changes and the evolution of agricultural practices (reduction of inputs, agroecology…).

3. Optimize breeding schemes

Our objectives are to optimize the breeding process, from genetic resources to variety development. We investigate more particularly the potential of genomic and phenomic predictions for improving diversity management in breeding schemes, for identifying and introgressing new sources of diversity in elite germplasm and for optimizing hybrid breeding schemes.

This research involves experimental and theoretical approaches, development of statistical methods and decision support tools.

Experimental approaches involve the assembly of diversity panels, the development of original genetic materials in maize, their genotyping in targeted chromosome segments or at the whole genome scale with different marker densities integrating also sequencing approaches and their phenotyping. These experiments are conducted by team members and also benefit to a large extent of the support of INRAE experimental structures and private partners involved in our research projects. Theoretical approaches aim more particularly at developing methods and optimizing experiments for QTL detection (using linkage or association mapping and meta-analysis), marker-assisted selection (with a specific focus on genomic selection) and systems genetics (multi-omics integration). These approaches being generic beyond maize, we collaborate to different projects on other species (flax, cucumber, wheat, tomatoes, legumes, etc).

We more particularly collaborate with the ABI group for the development of:

Beyond our research projects, we provide to researchers and technicians of INRAE working on maize knowledge sharing and we organize the circulation of genetic resources (coordination of the maize group and of the activities of Maize Biological Resources Center).

Most recent projects/network coordinated by team members :


Our teaching activities are focused on our main expertise domains such as population genetics, quantitative genetics, plant breeding, modern breeding methods (from QTL detection to genomic or phenomic selection), statistical modelling, adaptation of plants to abiotic stresses and genomics. We mostly contributed to different specialization of the engineer school AgroparisTech by co-organizing the PISTv specialization and the BIP master degree (M1 and M2) form the Univesity of Paris-Saclay. Researchers of our team also contribute more ponctually to other formations such as AgroCampusOuest, SupAgro Montpellier, the CIHAM in Saragoza (Spain), ENS, Clermont-Auvergne University, Picardie Jules Verne University or the Reims-Champagne Ardennes University.

We also provide teaching to other researchers and breeders through the organization of (i) modules of the doctoral school ABIES (ii) workshops organized in the framework of research projects or INRAE meta-programs (iii) (iii) training establishment such as ASFIS and (iii) training session defined specifically for breeding companies.

GQMS is attached to the LabEx SPS (Sciences des Plantes de Saclay) and to ABIES doctoral school. Members

Former members

Yacine DJABALI, M2 (1/2 PAPPSO)(2020); Alexis Vergne, M1 (2020); Antoine ALLIER, Doctorant (2017-2020); Clément MABIRE (2016-2019), Doctorant ; Simon RIO, Doctorant (2016-2019) ; Adama SEYE, Doctorant (2016-2019) ; Morgane Roth, Post-doc (3 mois en 2019); Romane Guilbaud (2018-2019); Camille Clipet, Ingénieur (2017-2018); Elodie Petitjean, M2(2018); Fabien Laporte, Doctorant (2015-2018); Alban Besnard, M2 (2017); Heloïse Giraud, Doctorante (2012-2016); Marie Gauvin, TR CDD (2017); Cecile Monteil, TR (2013-2017); Philippe Jamin, TR (1993-2017); Sandra Negro, Post-doc (2013-2016); Mariangela Arca, Post-doc (2012-2014); Franck Gauthier, Ingenieur (2011 puis 2013-2014); Fabio Valente, Ingenieur (2009-2013); Magali Joannin, TR (2011-2013); Denis Coubriche, TR ( ); Nicolas Bardol, Doctorant (2010-2013); Xiao Wang, Post-doc (2013); Amandine Larièpe, Doctorante (2008-2012); Ashwin Khobragade, Doctorant (2008-2012); Sophie Bouchet, Post-doc (2009-2012); Marion Trunztler, Doctorante (2008-2011); Yves Roussel, Post-doc (2011); Valerie Loywyck, Post-doc (2008-2010); Tatiana Zerjal, Post-doc (2009); Celine Mir, Post-doc (2006-2009); Yung-Fen Huang, M2 (2008)

GQMS is attached to the LabEx SPS, Sciences des Plantes de Saclay.


  • Cyril Bauland Engineer (INRAE)
  • Aurélien Beugnot PhD student (INRAE)
  • Alain Charcosset Research Director (INRAE)
  • Valérie Combes Assistante Ingénieure (INRAE)
  • Julie Fiévet Associate Professor (AgroParisTech)
  • Margaux Julien Assistant Professor (AgroParisTech)
  • Alizarine Lorenzi PhD student (INRAE)
  • Delphine Madur (INRAE)
  • Tristan Mary-Huard Junior Investigator (INRAE)
  • Laurence Moreau Directrice de Recherche (INRAE)
  • Stéphane Nicolas Junior Investigator (INRAE)
  • Sophie Pin Technician (INRAE)
  • Renaud Rincent Junior Investigator (INRAE)
  • Pauline Robert PhD student (INRAE)
  • Dimitri Sanchez PhD student (INRAE)


  • Arca M., Mary-Huard T. , Gouesnard B., Bérard A., Bauland C. , Combes V. , Madur D. , Charcosset A. , Nicolas S. . (2021) Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array. Front. Plant Sci., (11) 568699
  • Diaw Y., Tollon-Cordet C., Charcosset A. , Nicolas S. , Madur D. , Ronfort J., David J., Gouesnard B., Chiang TY.. (2021) Genetic diversity of maize landraces from the South-West of France. PLoS ONE, 2 (16) e0238334
  • Gonzàlez-Diéguez D., Legarra A., Charcosset A. , Moreau L. , Lehermeier C., Teyssèdre S., Vitezica ZG.. (2021) Genomic Prediction of Hybrid Crops Allows Disentangling Dominance and Epistasis. Genetics, iyab026
  • Rio S., Moreau L. , Charcosset A. , Mary-Huard T. . (2020) Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize. Genetics, 1 (216) 27-41
  • Allier A., 20 janvier 2020, Contributions to genetic diversity management in maize breeding programs using genomic selection
  • Allier A., Teyssèdre S., Lehermeier C., Charcosset A. , Moreau L. . (2020) Genomic prediction with a maize collaborative panel: identification of genetic resources to enrich elite breeding programs. Theor Appl Genet, 1 (133) 201-215
  • Allier A., Teyssèdre S., Lehermeier C., Moreau L. , Charcosset A. . (2020) Optimized breeding strategies to harness genetic resources with different performance levels. BMC Genomics, 1 (21) 349
  • Benoist R., Capdevielle‐Dulac C., Chantre C., Jeannette R., Calatayud PA., Drezen JM., Dupas S., Le Rouzic A., Le Ru B., Moreau L. , Van Dijk E., Kaiser L., Mougel F.. (2020) Quantitative Trait Loci involved in the reproductive success of a parasitoid wasp. Mol Ecol, mec.15567
  • Blein-Nicolas M., Negro SS., Balliau T., Welcker C., Cabrera-Bosquet L., Nicolas S. , Charcosset A. , Zivy M.. (2020) A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize. Genome Res., 11 (30) 1593-1604
  • Castelletti S., Coupel-Ledru A., Granato I., Palaffre C., Cabrera-Bosquet L., Tonelli C., Nicolas S. , Tardieu F., Welcker C., Conti L., de Meaux J.. (2020) Maize adaptation across temperate climates was obtained via expression of two florigen genes. PLoS Genet, 7 (16) e1008882
  • Diouf I., Derivot L., Koussevitzky S., Carretero Y., Bitton F., Moreau L. , Causse M., Rebetzke G.. (2020) Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population. Journal of Experimental Botany, eraa265
  • Rio S., Mary-Huard T. , Moreau L. , Bauland C. , Palaffre C., Madur D. , Combes V. , Charcosset A. , Springer NM.. (2020) Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering. PLoS Genet, 3 (16) e1008241
  • Seye AI., Bauland C. , Charcosset A. , Moreau L. . (2020) Revisiting hybrid breeding designs using genomic predictions: simulations highlight the superiority of incomplete factorials between segregating families over topcross designs. Theor Appl Genet, 6 (133) 1995-2010
  • de Vienne D., Fiévet J. . (2020) The Pitfalls of Heterosis Coefficients. Plants, 7 (9) 875
  • Allier A., Teyssèdre S., Lehermeier C., Claustres B., Maltese S., Melkior S., Moreau L. , Charcosset A. . (2019) Assessment of breeding programs sustainability: application of phenotypic and genomic indicators to a North European grain maize program. Theor Appl Genet, 5 (132) 1321-1334
  • Allier A., Lehermeier C., Charcosset A. , Moreau L. , Teyssèdre S.. (2019) Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection. Front. Genet., (10) 1006
  • Allier A., Moreau L. , Charcosset A. , Teyssèdre S., Lehermeier C.. (2019) Usefulness Criterion and Post-selection Parental Contributions in Multi-parental Crosses: Application to Polygenic Trait Introgression. G3: Genes, Genomes, Genetics, 5 (9) 1469-1479
  • Boussardon C., Martin-Magniette ML., Godin B., Benamar A., Vittrant B., Citerne S., Mary-Huard T. , Macherel D., Rajjou L., Budar F.. (2019) Novel Cytonuclear Combinations Modify Arabidopsis thaliana Seed Physiology and Vigor. Front Plant Sci, (10) 32
  • Courret C., Gérard PR., Ogereau D., Falque M., Moreau L. , Montchamp-Moreau C.. (2019) X-chromosome meiotic drive in Drosophila simulans: a QTL approach reveals the complex polygenic determinism of Paris drive suppression. Heredity, 6 (122) 906-915
  • Forst E., Enjalbert J., Allard V., Ambroise C., Krissaane I., Mary-Huard T. , Robin S., Goldringer I.. (2019) A generalized statistical framework to assess mixing ability from incomplete mixing designs using binary or higher order variety mixtures and application to wheat. Field Crops Research, (242) 107571
  • Fustier MA., Martínez-Ainsworth NE., Aguirre-Liguori JA., Venon A., Corti H., Rousselet A., Dumas F., Dittberner H., Camarena MG., Grimanelli D., Ovaskainen O., Falque M., Moreau L. , Meaux J., Montes-Hernández S., Eguiarte LE., Vigouroux Y., Manicacci D., Tenaillon MI.. (2019) Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude. PLOS Genetics, 12 (15) e1008512
  • Mabire C., 2019-04-23 23/04/19, Contribution des variations structurales de type insertions/délétions à l'adaptation, la variation des caractères et les performances hybrides chez le maïs
  • Mabire C., Duarte J., Darracq A., Pirani A., Rimbert H., Madur D. , Combes V. , Vitte C., Praud S., Rivière N., Joets J., Pichon JP., Nicolas S. . (2019) High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix® axiom® array. BMC Genomics, 1 (20) 848
  • Mangin B., Rincent R. , Rabier CE., Moreau L. , Goudemand-Dugue E.. (2019) Training set optimization of genomic prediction by means of EthAcc. PLOS ONE, 2 (14) e0205629
  • Millet EJ., Kruijer W., Coupel-Ledru A., Prado SA., Cabrera-Bosquet L., Lacube S., Charcosset A. , Welcker C., Eeuwijk F., Tardieu F.. (2019) Genomic prediction of maize yield across European environmental conditions. Nat Genet, 6 (51) 952-956
  • Negro SS., Millet EJ., Madur D. , Bauland C. , Combes V. , Welcker C., Tardieu F., Charcosset A. , Nicolas S. . (2019) Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies. BMC Plant Biol., 1 (19) 318
  • Rio S., 2019-04-26 26/04/19, Contributions to genomic selection and association mapping in structured and admixed populations : application to maize
  • Rio S., Mary-Huard T. , Moreau L. , Charcosset A. . (2019) Genomic selection efficiency and a priori estimation of accuracy in a structured dent maize panel. Theor Appl Genet, 1 (132) 81-96
  • Seye A., 2019-03-21 21/03/19, Prédiction assistée par marqueurs de la performance hybride dans un schéma de sélection réciproque : simulations et évaluation expérimentale pour le maïs ensilage
  • Seye AI., Bauland C. , Giraud H., Mechin V., Reymond M., Charcosset A. , Moreau L. . (2019) Quantitative trait loci mapping in hybrids between Dent and Flint maize multiparental populations reveals group-specific QTL for silage quality traits with variable pleiotropic effects on yield. Theor Appl Genet, 5 (132) 1523-1542
  • Virlouvet L., El Hage F., Griveau Y., Jacquemot MP., Gineau E., Baldy A., Legay S., Horlow C., Combes V. , Bauland C. , Palafre C., Falque M., Moreau L. , Coursol S., Méchin V., Reymond M.. (2019) Water Deficit-Responsive QTLs for Cell Wall Degradability and Composition in Maize at Silage Stage. Front. Plant Sci., (10) 488
  • Darracq A., Vitte C., Nicolas S. , Duarte J., Pichon JP., Mary-Huard T. , Chevalier C., Bérard A., Le Paslier MC., Rogowsky P., Charcosset A. , Joets J.. (2018) Sequence analysis of European maize inbred line F2 provides new insights into molecular and chromosomal characteristics of presence/absence variants. BMC Genomics, 1 (19) 119
  • Fiévet J. , Nidelet T., Dillmann C., de Vienne D.. (2018) Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations. Front. Genet., (9)
  • Joets J., Vitte C., Charcosset A. , Bennetzen J., Flint-Garcia S., Hirsch C., Tuberosa R.. (2018) Draft assembly of the F2 European maize genome sequence and its comparison to the B73 genome sequence: a characterization of genotype-specific regions.. , In Press
  • Laporte F., 2018-03-13 13/03/18, Développement de méthodes statistiques pour l’identification de gènes d’intérêt en présence d’apparentement et de dominance, application à la génétique du maïs
  • Bedoya CA., Dreisigacker S., Hearne S., Franco J., Mir C., Prasanna BM., Taba S., Charcosset A. , Warburton ML.. (2017) Genetic diversity and population structure of native maize populations in Latin America and the Caribbean. PLoS One, 4 (12)
  • Bouchet S., Bertin P., Presterl T., Jamin P., Coubriche D., Gouesnard B., Laborde J., Charcosset A. . (2017) Association mapping for phenology and plant architecture in maize shows higher power for developmental traits compared with growth influenced traits. Heredity (Edinb), 3 (118) 249-259
  • Brandenburg JT., Mary-Huard T. , Rigaill G., Hearne SJ., Corti H., Joets J., Vitte C., Charcosset A. , Nicolas S. , Tenaillon MI.. (2017) Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLOS Genetics, 3 (13) e1006666
  • Cañas RA., Yesbergenova-Cuny Z., Simons M., Chardon F., Armengaud P., Quilleré I., Cukier C., Gibon Y., Limami AM., Nicolas S. , Brulé L., Lea PJ., Maranas CD., Hirel B.. (2017) Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modeling Approach to Link Leaf Physiology to Kernel Yield. The Plant Cell, 5 (29) 919-943
  • Giraud H., Bauland C. , Falque M., Madur D. , Combes V. , Jamin P., Monteil C., Laborde J., Palaffre C., Gaillard A., Blanchard P., Charcosset A. , Moreau L. . (2017) Linkage Analysis and Association Mapping QTL Detection Models for Hybrids Between Multiparental Populations from Two Heterotic Groups: Application to Biomass Production in Maize (Zea mays L.). G3: Genes, Genomes, Genetics, g3.300121.2017
  • Giraud H., Bauland C. , Falque M., Madur D. , Combes V. , Jamin P., Monteil C., Laborde J., Palaffre C., Gaillard A., Blanchard P., Charcosset A. , Moreau L. . (2017) Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize (Zea mays L.) Heterotic Groups. Genetics, 3 (207) 1167-1180
  • Gouesnard B., Negro S., Laffray A., Glaubitz J., Melchinger A., Revilla P., Moreno-Gonzalez J., Madur D. , Combes V. , Tollon-Cordet C., Laborde J., Kermarrec D., Bauland C. , Moreau L. , Charcosset A. , Nicolas S. . (2017) Genotyping-by-sequencing highlights original diversity patterns within a European collection of 1191 maize flint lines, as compared to the maize USDA genebank. Theor Appl Genet, 10 (130) 2165-2189
  • Laporte F., Charcosset A. , Mary‐Huard T.. (2017) Estimation of the relatedness coefficients from biallelic markers, application in plant mating designs. Biometrics, 3 (73) 885-894
  • Larièpe A., Moreau L. , Laborde J., Bauland C. , Mezmouk S., Décousset L., Mary-Huard T. , Fiévet J. , Gallais A., Dubreuil P., Charcosset A. . (2017) General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents. Theor. Appl. Genet., 2 (130) 403-417
  • Mary-Huard T. , 2017-06-12 06/12/17, Some contributions to statistical modeling and model selection with applications to genomics and quantitative genetics
  • Moreau L. , 2017-06-13 13/06/17, Utilisation des marqueurs en sélection : des QTL à la Sélection Génomique
  • Rincent R. , Charcosset A. , Moreau L. . (2017) Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations. Theor Appl Genet, 11 (130) 2231-2247
  • Fernandez O., Urrutia M., Bernillon S., Giauffret C., Tardieu F., Le Gouis J., Langlade N., Charcosset A. , Moing A., Gibon Y.. (2016) Fortune telling: metabolic markers of plant performance. Metabolomics, 10 (12) 158
  • Giraud H., 2016-01-22 22/01/16, Genetic analysis of hybrid value for silage maize in multiparental designs : QTL detection and genomic selection
  • Millet E., Welcker C., Kruijer W., Negro S., Nicolas S. , Coupel-Ledru A., Bauland C. , Praud S., Ranc N., Presterl T., Tuberosa R., Bedo Z., Draye X., Usadel B., Charcosset A. , van Eeuwijk F., Tardieu F.. (2016) Genome-wide analysis of yield in Europe: allelic effects as functions of drought and heat scenarios. Plant physiology, 2 (172) 749-764
  • Moreau L. , Charmet G., Charcosset A. , Le Gouis J., Deretz S.. (2016) Quelle place pour la selection génomique chez les espèces de grande culture ?. ,
  • Nicolas S. , Peros JP., Lacombe T., Launay A., Le Paslier MC., Berard A., Mangin B., Valiere S., Martins F., Le Cunff L., Laucou V., Bacilieri R., Dereeper A., Chatelet P., This P., Doligez A.. (2016) Genetic diversity, linkage disequilibrium and power of a large grapevine (Vitis vinifera L) diversity panel newly designed for association studies. BMC plant biology, 1 (16) 74
  • Revilla P., Rodriguez VM., Ordas A., Rincent R. , Charcosset A. , Giauffret C., Melchinger AE., Schon CC., Bauer E., Altmann T., Brunel D., Moreno-Gonzalez J., Campo L., Ouzunova M., Alvarez A., Ruiz de Galarreta JI., Laborde J., Malvar RA.. (2016) Association mapping for cold tolerance in two large maize inbred panels. BMC plant biology, 1 (16) 127
  • Tenaillon MI., Manicacci D., Nicolas S. , Tardieu F., Welcker C.. (2016) Testing the link between genome size and growth rate in maize. PeerJ, (4) e2408
  • Bel L., Daudin JJ., Etienne M., Lebarbier E., Mary-Huard T. , Robin S., Vuillet C., Daudin JJ.. (2015) Modèle mixte, modélisation de la variance. , 162-189
  • Bel L., Daudin JJ., Etienne M., Lebarbier E., Mary-Huard T. , Robin S., Vuillet C., Daudin JJ.. (2015) Plans d’expérience. , 218-246
  • Gallais A., Editions Quae .. (2015) Pour comprendre l'amélioration des plantes. Enjeux, méthodes, objectifs et critères de sélection. ,
  • Rousselle Y., Jones E., Charcosset A. , Moreau L. , Robbins K., Stich B., Knaak C., Flament P., Karaman Z., Martinant JP., Fourneau M., Taillardat A., Romestant M., Tabel C., Bertran J., Ranc N., Lespinasse D., Blanchard P., Kahler A., Chen J., Kahler J., Dobrin S., Warner T., Ferris R., Smith S.. (2015) Study on Essential Derivation in Maize: III. Selection and Evaluation of a Panel of Single Nucleotide Polymorphism Loci for Use in European and North American Germplasm. Crop Science, 3 (55) 1170-1180
  • Berthet E., Charcosset A. , Lemarié S., Moreau L. , Segrestin B., Debaeke P., Quilot-Turion B.. (2014) Nouvelles questions pour la conception.. ,
  • Giraud H., Lehermeier C., Bauer E., Falque M., Segura V., Bauland C. , Camisan C., Campo L., Meyer N., Ranc N., Schipprack W., Flament P., Melchinger AE., Menz M., Moreno-Gonzalez J., Ouzunova M., Charcosset A. , Schon CC., Moreau L. . (2014) Linkage disequilibrium with linkage analysis of multiline crosses reveals different multiallelic QTL for hybrid performance in the flint and dent heterotic groups of maize. Genetics, 4 (198) 1717-34
  • Lehermeier C., Kramer N., Bauer E., Bauland C. , Camisan C., Campo L., Flament P., Melchinger AE., Menz M., Meyer N., Moreau L. , Moreno-Gonzalez J., Ouzunova M., Pausch H., Ranc N., Schipprack W., Schonleben M., Walter H., Charcosset A. , Schon CC.. (2014) Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction. Genetics, 1 (198) 3-16
  • Revilla P., Rodriguez VM., Ordas A., Rincent R. , Charcosset A. , Giauffret C., Melchinger AE., Schon CC., Bauer E., Altmann T., Brunel D., Moreno-Gonzalez J., Campo L., Ouzunova M., Laborde J., Alvarez A., de Galarreta JIR., Malvar RA.. (2014) Cold Tolerance in Two Large Maize Inbred Panels Adapted to European Climates. Crop Sci., 5 (54) 1981-1991
  • Rincent R. , Nicolas S. , Bouchet S., Altmann T., Brunel D., Revilla P., Malvar RA., Moreno-Gonzalez J., Campo L., Melchinger AE., Schipprack W., Bauer E., Schoen CC., Meyer N., Ouzunova M., Dubreuil P., Giauffret C., Madur D. , Combes V. , Dumas F., Bauland C. , Jamin P., Laborde J., Flament P., Moreau L. , Charcosset A. . (2014) Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production. Theor Appl Genet, 11 (127) 2313-31
  • Rincent R. , 2014-11-04 11/04/14, Optimization of association genetics and genomic selection strategies for populations of different diversity levels. Application in maize (Zea mays L.)
  • Rincent R. , Moreau L. , Monod H., Kuhn E., Melchinger AE., Malvar RA., Moreno-Gonzalez J., Nicolas S. , Madur D. , Combes V. , Dumas F., Altmann T., Brunel D., Ouzunova M., Flament P., Dubreuil P., Charcosset A. , Mary-Huard T. . (2014) Recovering power in association mapping panels with variable levels of linkage disequilibrium. Genetics, 1 (197) 375-87
  • Valente F., Gauthier F., Bardol N., Blanc G., Joets J., Charcosset A. , Moreau L. , Fleury D., Whitford R.. (2014) OptiMAS: A Decision Support Tool to Conduct Marker-Assisted Selection Programs. , (1145) 97-116
  • Bardol N., Ventelon M., Mangin B., Jasson S., Loywick V., Couton F., Derue C., Blanchard P., Charcosset A. , Moreau L. . (2013) Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 11 (126) 2717-36
  • Bardol N., 2013-08-03 08/03/13, Interest of dense genotyping for selection in multi-parental designs. Comparison of two marker-assisted selection approaches: Genomewide selection and QTL-LDLA based selection. Application in maize (Zea mays L.)
  • Bauer E., Falque M., Walter H., Bauland C. , Camisan C., Campo L., Meyer N., Ranc N., Rincent R. , Schipprack W., Altmann T., Flament P., Melchinger AE., Menz M., Moreno-Gonzalez J., Ouzunova M., Revilla P., Charcosset A. , Martin OC., Schon CC.. (2013) Intraspecific variation of recombination rate in maize. Genome biology, 9 (14) R103
  • Bouchet S., Servin B., Bertin P., Madur D. , Combes V. , Dumas F., Brunel D., Laborde J., Charcosset A. , Nicolas S. . (2013) Adaptation of maize to temperate climates: mid-density genome-wide association genetics and diversity patterns reveal key genomic regions, with a major contribution of the Vgt2 (ZCN8) locus. PloS one, 8 (8) e71377
  • Gallais A.. (2013) De la domestication à la transgénèse, évolution des outils pour l’amélioration des plantes. ,
  • Houel C., Martin-Magniette ML., Nicolas S. , Lacombe T., Le Cunff L., Franck D., Torregrosa L., Conéjéro G., Lalet S., This P., Adam-Blondon AF.. (2013) Genetic diversity of berry size in grapevine (Vitis vinifera L.). Aus J Grape and Wine R, 2 (19) 208-220
  • Mir C., Zerjal T., Combes V. , Dumas F., Madur D. , Bedoya C., Dreisigacker S., Franco J., Grudloyma P., Hao PX., Hearne S., Jampatong C., Laloe D., Muthamia Z., Nguyen T., Prasanna BM., Taba S., Xie CX., Yunus M., Zhang S., Warburton ML., Charcosset A. . (2013) Out of America: tracing the genetic footprints of the global diffusion of maize. Theor Appl Genet, 11 (126) 2671-82
  • Valente F., Gauthier F., Bardol N., Blanc G., Joets J., Charcosset A. , Moreau L. . (2013) OptiMAS: a decision support tool for marker-assisted assembly of diverse alleles. The Journal of heredity, 4 (104) 586-90
  • Canas RA., Quillere I., Gallais A., Hirel B.. (2012) Can genetic variability for nitrogen metabolism in the developing ear of maize be exploited to improve yield?. The New phytologist, 2 (194) 440-52
  • Durand E., Bouchet S., Bertin P., Ressayre A., Jamin P., Charcosset A. , Dillmann C., Tenaillon MI.. (2012) Flowering time in maize: linkage and epistasis at a major effect locus. Genetics, 4 (190) 1547-62
  • Khobragade A., 2012-03-23 23/03/12, Combining linkage analysis and association genetics to finely map loci involved in maize grain production and maturation -- Cartographie fine de locus impliqués dans la production et la maturation du grain chez le maïs par une approche conjointe de linkage et de génétique d’association
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