Alain CHARCOSSET

maize, maize and maize

     
  • Maize diversity
  • Quantitative traits
  • Breeding methods

 INRAE, Directeur de Recherche

 alain.charcosset@inrae.fr —   01 69 33 23 35


 Génétique Quantitative et Méthodologie de la Sélection

Implication de Alain Charcosset dans axe1 20% axe1 Comprendre et éclairer les mécanismes de l'évolution Axe1 Implication de Alain Charcosset dans axe2 10% axe2 Comprendre et prédire les bases génétiques des interactions Axe2 Implication de Alain Charcosset dans axe3 70% axe3 Comprendre et mobiliser la diversitée cultivée pour répondre aux attentes des acteurs Axe3
 Publications    

  • Génétique Quantitative et Évolution - Le Moulon
  • Université Paris-Saclay, INRAE, CNRS, AgroParisTech
  • IDEEV
  • 12 route 128
  • 91190 Gif-sur-Yvette
Alain CHARCOSSET

Education and Positions

  • Senior Researcher (DR1) Institut National de la Recherche Agronomique (INRA)
  • Deputy director of UMR Quantitative Genetics & Evolution - Le Moulon
  • Head of GQMS team (Quantitative Genetics and Selection Methods)
  • 1990: PhD thesis INA-PG
  • 1986: ingénieur Agronome and MS in Plant Breeding INA-PG (present AgroParisTech)

Research interests

My current research aims at

  • understanding how maize genetic European diversity is organized and shaped by past and ongoing selection programs, in order to facilitate the identification of original diversity sources to be used in genetics studies and breeding programs.
  • determining genetic effects involved in the variation of quantitative traits of agronomical interest. To do so, we develop(ed) QTL meta-analysis methods, association mapping panels, and original multiparental QTL mapping populations to rank multiple alleles and address non additive effects.
  • developing marker assisted breeding methods, based on the assembly of favorable alleles at detected QTLs or global genomic prediction, with a specific focus on population optimization.

These research involve dense genotyping of genetic resources or newly created materials and their phenotyping, conducted within our group and by collaborators. I am also involved in the development of informatics tools to facilitate data management / analysis.

Main ongoing / recent external collaborators

  • Brigitte Gouesnard (INRA, AGAP Montpellier) - François Tardieu and Claude Welcker (INRA LEPSE Montpellier) - Catherine Giauffret (INRA Mons), INRA EPGV Evry - J. Laborde, C. Palaffre and colleagues (INRA Saint-Martin de Hinx)
  • Fred van Eeuwijk (WUR, Netherlands) - Chris-Carolyn Schoen (TUM, Germany) - Albrecht Melchinger (Univ. Hohenheim, Germany) - Pedro Revilla (CSIS, Spain) - Jesus Moreno-Gonzalez (CIAM, Spain)
  • CIMMYT - Integrated Breeding Platform Consortium
  • Biogemma - Euralis - Syngenta - RAGT - Limagrain - KWS, Maïsadour - Caussade - Promaïs association.

Main ongoing / recent project responsibilities and community implication

  • Coordinator of Amaizing Project (ANR investment for the Future, 2011- )
  • Coordinator of CornFed Project (2009-2014, Germany, France, Spain), WP leader in UE DROPS project (2011-2015)
  • Coordinator of Promaïs projects related to maize diversity analysis and exploitation
  • Coordinator of INRA Maize Genetics and Breeding program (1994- )
  • Member of the scientific council of INRA “Plant Biology and Improvement” department (2011-2016)
  • Associate editor for Theoretical and Applied Genetics (2004 -) and Genetics (2010- )
  • President of Eucarpia Maize and Sorghum section (2015- ), organization of 2015 section conference
  • Vice-Chair of Maize Steering Committee (2016- )

Awards

  • Prix Jean Dufrenoy (main award of French Agricultural Academy, 2003),
  • Chevalier du Mérite Agricole (national distinction for contribution to French agriculture, 2013)

Publications

  • Ali B., Huguenin-Bizot B., Laurent M., Chaumont F., Maistriaux LC., Nicolas S., Duborjal H., Welcker C., Tardieu F., Mary-Huard T., Moreau L., Charcosset A. , Runcie D., Rincent R.. (2024) High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions. Theor Appl Genet, 7 (137) 175
  • Balconi C., Galaretto A., Malvar RA., Nicolas SD., Redaelli R., Andjelkovic V., Revilla P., Bauland C., Gouesnard B., Butron A., Torri A., Barata AM., Kravic N., Combes V., Mendes-Moreira P., Murariu D., Šarčević H., Schierscher-Viret B., Vincent M., Zanetto A., Kessel B., Madur D., Mary-Huard T., Pereira A., Placinta DD., Strigens A., Charcosset A. , Goritschnig S.. (2024) Genetic and Phenotypic Evaluation of European Maize Landraces as a Tool for Conservation and Valorization of Agrobiodiversity. Biology, 6 (13) 454
  • De Walsche A., Gauthier F., Charcosset A. , Mary-Huard T.. (2024) Large-scale composite hypothesis testing for omics analyses. ,
  • Lorenzi A., Bauland C., Pin S., Madur D., Combes V., Palaffre C., Guillaume C., Touzy G., Mary-Huard T., Charcosset A. , Moreau L.. (2024) Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles. Theor Appl Genet, 3 (137) 75
  • Maistriaux LC., Laurent MJ., Jeanguenin L., Prado SA., Nader J., Welcker C., Charcosset A. , Tardieu F., Nicolas SD., Chaumont F.. (2024) Genetic variability of aquaporin expression in maize: From eQTLs to a MITE insertion regulating PIP2;5 expression. Plant Physiology, kiae326
  • Arca M., Gouesnard B., Mary‐Huard T., Le Paslier MC., Bauland C., Combes V., Madur D., Charcosset A. , Nicolas SD.. (2023) Genotyping of DNA pools identifies untapped landraces and genomic regions to develop next‐generation varieties. Plant Biotechnology Journal, 6 (21) 1123-1139
  • Beugnot A., 07/02/2023, Hybrid performance in maize: from study of complementary between heterotic groups to genomic prediction, PhD, Université Paris-Saclay
  • De Walsche A., Vergne A., Rincent R., Roux F., Nicolas S., Welcker C., Mezmouk S., Charcosset A. , Mary-Huard T.. (2023) metaGE: Investigating Genotype × Environment interactions through meta-analysis. ,
  • Galić V., Anđelković V., Kravić N., Grčić N., Ledenčan T., Jambrović A., Zdunić Z., Nicolas S., Charcosset A. , Šatović Z., Šimić D.. (2023) Genetic diversity and selection signatures in a gene bank panel of maize inbred lines from Southeast Europe compared with two West European panels. BMC Plant Biol, 1 (23) 315
  • Legarra A., Gonzalez-Dieguez DO., Charcosset A. , Vitezica ZG.. (2023) Impact of interpopulation distance on dominance variance and average heterosis in hybrid populations within species. GENETICS, 2 (224)
  • Revilla P., Butrón A., Rodriguez VM., Rincent R., Charcosset A. , Giauffret C., Melchinger AE., Schön CC., Bauer E., Altmann T., Brunel D., Moreno-González J., Campo L., Ouzunova M., Álvarez Ángel., Ruíz de Galarreta JI., Laborde J., Malvar RA.. (2023) Genetic Variation for Cold Tolerance in Two Nested Association Mapping Populations. Agronomy, 1 (13) 195
  • Rio S., Charcosset A. , Moreau L., Mary-Huard T., Endelman J.. (2023) Detecting directional and non-directional epistasis in bi-parental populations using genomic data. GENETICS, 3 (224) iyad089
  • Sanchez D., Sadoun SB., Mary-Huard T., Allier A., Moreau L., Charcosset A. . (2023) Improving the use of plant genetic resources to sustain breeding programs’ efficiency. Proc. Natl. Acad. Sci. U.S.A., 14 (120) e2205780119
  • Sanchez D., 29/09/2023, Incorporation of genetic resources in breeding programs: theoretical analysis and experimental evaluation of a pre-breeding multiparental maize population, PhD, Université Paris-Saclay
  • Ahmadi N., Bartholomé J., Rio S., Charcosset A. , Mary-Huard T., Moreau L., Rincent R.. (2022) Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches. DOI.org (Crossref), (2467) 77-112
  • Laporte F., Charcosset A. , Mary-Huard T.. (2022) Efficient ReML inference in variance component mixed models using a Min-Max algorithm. PLoS Comput Biol, 1 (18) e1009659
  • Lorenzi A., Bauland C., Mary-Huard T., Pin S., Palaffre C., Guillaume C., Lehermeier C., Charcosset A. , Moreau L.. (2022) Genomic prediction of hybrid performance: comparison of the efficiency of factorial and tester designs used as training sets in a multiparental connected reciprocal design for maize silage. Theor Appl Genet,
  • Roth M., Beugnot A., Mary-Huard T., Moreau L., Charcosset A. , Fievet JB.. (2022) Improving genomic predictions with inbreeding and non-additive effects in two admixed maize hybrid populations in single and multi-environment contexts. Genetics, iyac018
  • Welcker C., Spencer NA., Turc O., Granato I., Chapuis R., Madur D., Beauchene K., Gouesnard B., Draye X., Palaffre C., Lorgeou J., Melkior S., Guillaume C., Presterl T., Murigneux A., Wisser RJ., Millet EJ., van Eeuwijk F., Charcosset A. , Tardieu F.. (2022) Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions. Nat Commun, 1 (13) 3225
  • Arca M., Mary-Huard T., Gouesnard B., Bérard A., Bauland C., Combes V., Madur D., Charcosset A. , Nicolas SD.. (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 SD., 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
  • Mary-Huard T., Das S., Mukhopadhyay I., Robin S., Birol I.. (2021) Querying multiple sets of P -values through composed hypothesis testing. Bioinformatics, 1 (38) 141-148
  • Allier A., 2020-01, Contributions to Genetic Diversity Management in Maize Breeding Programs using Genomic Selection, Theses, Université Paris-Saclay
  • 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
  • Arca M., Gouesnard B., Mary-Huard T., Le Paslier MC., Bauland C., Combes V., Madur D., Charcosset A. , Nicolas SD.. (2020) Genome-wide SNP genotyping of DNA pools identifies untapped landraces and genomic regions that could enrich the maize breeding pool. DOI.org (Crossref),
  • Blein-Nicolas M., Negro SS., Balliau T., Welcker C., Cabrera-Bosquet L., Nicolas SD., 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
  • 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
  • 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
  • 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
  • Mabire C., 2019-04, Contribution des variations structurales de type insertions/délétions à l'adaptation, la variation des caractères et les performances hybrides chez le maïs, Theses, Université Paris Saclay (COmUE)
  • 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 SD.. (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, Contributions to genomic selection and association mapping in structured and admixed populations : application to maize, Theses, Université Paris Saclay (COmUE)
  • 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 AI., 2019-03, Prédiction assistée par marqueurs de la performance hybride dans un schéma de sélection réciproque : simulations et évaluation expérimentale pour le maïs ensilage, Theses, Université Paris Saclay (COmUE)
  • 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
  • Bennetzen J., Flint-Garcia S., Hirsch C., Tuberosa R., Joets J., Vitte C., Charcosset A. . (2018) Draft Assembly of the F2 European Maize Genome Sequence and Its Comparison to the B73 Genome Sequence: A Characterization of Genotype-Specific Regions. DOI.org (Crossref), 3-12
  • 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
  • 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, PhD thesis, Université Paris-Saclay
  • 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 SD., Tenaillon MI.. (2017) Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLOS Genetics, 3 (13) e1006666
  • 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 JB., 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
  • 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, Genetic analysis of hybrid value for silage maize in multiparental designs : QTL detection and genomic selection, Theses, Université Paris Saclay (COmUE)
  • 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 ?. ,
  • 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
  • Rousselle Y., Jones E., Charcosset A. , Moreau P., 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., 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.), PhD thesis, AgroParisTech
  • 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
  • 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
  • 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, PhD thesis, AgroParisTech
  • Larièpe A., Mangin B., Jasson S., Combes V., Dumas F., Jamin P., Lariagon C., Jolivot D., Madur D., Fiévet J., Gallais A., Dubreuil P., Charcosset A. , Moreau L.. (2012) The Genetic Basis of Heterosis: Multiparental Quantitative Trait Loci Mapping Reveals Contrasted Levels of Apparent Overdominance Among Traits of Agronomical Interest in Maize ( Zea mays L.). Genetics, 2 (190) 795-811
  • Rincent R., Laloe D., Nicolas S., Altmann T., Brunel D., Revilla P., Rodriguez VM., Moreno-Gonzalez J., Melchinger A., Bauer E., Schoen CC., Meyer N., Giauffret C., Bauland C., Jamin P., Laborde J., Monod H., Flament P., Charcosset A. , Moreau L.. (2012) 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.). Genetics, 2 (192) 715-28
  • Sosnowski O., Charcosset A. , Joets J.. (2012) BioMercator V3: an upgrade of genetic map compilation and quantitative trait loci meta-analysis algorithms. Bioinformatics, 15 (28) 2082-3
  • Truntzler M., Ranc N., Sawkins MC., Nicolas S., Manicacci D., Lespinasse D., Ribiere V., Galaup P., Servant F., Muller C., Madur D., Betran J., Charcosset A. , Moreau L.. (2012) Diversity and linkage disequilibrium features in a composite public/private dent maize panel: consequences for association genetics as evaluated from a case study using flowering time. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 4 (125) 731-47
  • Zerjal T., Rousselet A., Mhiri C., Combes V., Madur D., Grandbastien MA., Charcosset A. , Tenaillon MI.. (2012) Maize genetic diversity and association mapping using transposable element insertion polymorphisms. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 8 (124) 1521-37
  • Charcosset A. , Moreau L., Ricroch A., Dattée Y., Fellous M.. (2011) Cartographie de QTL, génétique d’association et application en sélection. , 112-125
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