Laurence MOREAU

QTL detection and breeding methods

     
  • Genome-Wide Association Mapping
  • Genomic Selection
  • Marker-Assisted Selection
  • Linkage Analysis
  • Breeding methods

 INRAE, Directrice de Recherche

 laurence.moreau@inrae.fr —   +33 (0)1 69 33 23 37


 Quantitative Genetics and Plant Breeding Methodology

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 Publications    

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

Positions and Education

  • 2020-Present: Head of GQMS team (Quantitative Genetics and Selection Methods)
  • 1999-Present: INRAE Researcher then Senior Scientist (from 2018), GQE-Le Moulon, Gif-sur-Yvette, France
  • 2017: HDR “Methodological and experimental contributions to Marker-Assisted Selection. Application in Maize” Univ. Paris-Sud
  • 2000: Sabbatical in the group of J. Dekkers at the Iowa State University, Ames, USA, in the department of Animal Genetics on the optimization of marker-assisted selection.
  • 1998: PhD “Quantitative Trait Loci (QTL) detection and marker-assisted selection in Maize”, INA-PG (present AgroParisTech), Paris, France
  • 1994: Ingénieur Agronome and MsC in « Genetic Resources and plant breeding », (INA-PG, University of Paris VI and Paris XI).

Research Interests

Plant breeding is currently facing new issues related to global warming and the need to limit environmental impacts of agriculture. Many traits of interest in plant breeding have a complex genetic architecture that is still poorly known. Development of genotyping, then sequencing approaches as well as the access to new other “omics” information make it now possible to better decipher trait architecture and to develop new breeding approaches. My main subjects of research are related to the development of methods and experimental designs for QTL (Quantitative Trait Loci) detection and marker-assisted selection, with a specific focus on multiparental and hybrid designs and applications on Maize. With the advent of high-throughput genotyping approaches, my subjects of research are now more specifically oriented towards:

  • Association mapping and its combination with Linkage Mapping. I am interested in understanding parameters influencing detection power (1) and in the development of methods to better decipher group specific QTL effects (2).

  • Genomic selection. Recent projects deal with the optimization of calibration sets to improve prediction accuracy (3, 4, 5), the impact of group structuration on prediction efficiency (6, 7). I am also studying the potential of genomic predictions to identify interesting sources of favorable alleles in genetic resources and to better manage diversity in breeding programs (8, 9, 10, 11, 12).

  • Hybrid breeding. I contributed to develop an original multiparental design to identify loci involved in the GCA and SCA components of hybrid value for silage related traits and evaluate the possibility of replacing testcross evaluation by genomic predictions calibrated in an incomplete factorial to revisit recurrent reciprocal breeding schemes (13, 14, 15, 16). More generally I am interested in understanding the impact of heterotic group structuration on hybrid performances in order to better understand/predict heterosis.

Most of my research is done in collaboration with private breeding companies mostly on Maize but beyond Maize my objectives are to develop methods and tools applicable to other species, such as “OptiMAS”, a decision tool for implementing marker-assisted selection. Beyond Maize, I am therefore also contributing to projects on different other species (Tomato, Cucumber, Linus, Legumes…).

Main ongoing / recent project responsibilities and community implication

  • Coordinator of the WP4 of the Amaizing Project (ANR investment for the Future, 2011- )
  • Co-coordinator of Promaïs SAMMCR projects (2010- ) related hybrid breeding.
  • Co-coordinator of the INRAE network “R2D2” on the implementation of genomic selection in plant and animal breeding
  • Member of the CTPS, Maize section (2015-2019).
  • Alternate member of the scientific council of INRAE “Plant Biology and Improvement” (present BAP) division (2012-2016)
  • Associate editor for Theoretical and Applied Genetics (2016 -) and Crop Science (2008-2010)
  • Member of the scientific committee of the Eucarpia Biometrics conference (2012-)

Teaching

  • I give lectures on QTL detection, Marker-Assisted Selection and Genomic Selection to different Masters in AgroCampus Ouest, AgroparisTech. I contribute to the Master of plant Breeding of the CIHEAM, Zaragoza, Spain on the interest of Biotechnologies in Maize breeding.
  • I also regularly contribute to courses given for scientists from public institutes or private companies organized by ASFIS, with the framework of projects (Amaizing, Selgen) or organized internally by private breeding companies on QTL detection/GWAS/MAS/GS.

Awards

2019: Prix Limagrain of the French Academy of Agriculture

Bibliography

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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

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
  • 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
  • Beugnot A., 07/02/2023, Hybrid performance in maize: from study of complementary between heterotic groups to genomic prediction, PhD, Université Paris-Saclay
  • Bouidghaghen J., Moreau L. , Beauchêne K., Chapuis R., Mangel N., Cabrera‐Bosquet L., Welcker C., Bogard M., Tardieu F.. (2023) Robotized indoor phenotyping allows genomic prediction of adaptive traits in the field. Nat Commun, 1 (14) 6603
  • Lorenzi A., 08/11/2023, Optimization of genomic selection for hybrids in a reciprocal selection program: Experimental evaluation in maize and simulations, PhD, Université Paris-Saclay
  • Raffo MA., Cuyabano BCD., Rincent R., Sarup P., Moreau L. , Mary-Huard T., Jensen J.. (2023) Genomic prediction for grain yield and micro-environmental sensitivity in winter wheat. Front. Plant Sci., (13) 1075077
  • 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
  • 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
  • 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,
  • Monnot S., Cantet M., Mary-Huard T., Moreau L. , Lowdon R., Van Haesendonck M., Ricard A., Boissot N.. (2022) Unravelling cucumber resistance to several viruses via genome-wide association studies highlighted resistance hotspots and new QTLs. Horticulture Research, uhac184
  • 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
  • Speck A., Trouvé JP., Enjalbert J., Geffroy V., Joets J., Moreau L. . (2022) Genetic Architecture of Powdery Mildew Resistance Revealed by a Genome-Wide Association Study of a Worldwide Collection of Flax (Linum usitatissimum L.). Front. Plant Sci., (13) 871633
  • 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
  • Monnot S., Desaint H., Mary-Huard T., Moreau L. , Schurdi-Levraud V., Boissot N.. (2021) Deciphering the Genetic Architecture of Plant Virus Resistance by GWAS, State of the Art and Potential Advances. Cells, 11 (10) 3080
  • 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
  • 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., 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Moreau L. , 2017-06-13 13/06/17, Utilisation des marqueurs en sélection : des QTL à la Sélection Génomique, HDR, Université Paris Sud
  • 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
  • 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)
  • Moreau L. , Charmet G., Charcosset A., Le Gouis J., Deretz S.. (2016) Quelle place pour la selection génomique chez les espèces de grande culture ?. ,
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Charcosset A., Moreau L. , Ricroch A., Dattée Y., Fellous M.. (2011) Cartographie de QTL, génétique d’association et application en sélection. , 112-125
  • Manicacci D., Moreau L. , Charcosset A., Prioul JL., Thévenot C., Molnar T., Mike Burrel .. (2011) QTL cartography, meta-analysis and association genetics. , 37-66
  • Moreau L. , Charcosset A., Prioul JL., Thévenot C., Molnar T., Mike Burrel .. (2011) Marker-assisted selection in maize. , 411-434
  • Capelle V., Remoue C., Moreau L. , Reyss A., Mahe A., Massonneau A., Falque M., Charcosset A., Thevenot C., Rogowsky P., Coursol S., Prioul JL.. (2010) QTLs and candidate genes for desiccation and abscisic acid content in maize kernels. BMC plant biology, (10) 2
  • Cassan L., Moreau L. , Segouin S., Bellamy A., Falque M., Limami AM.. (2010) Genetic map construction and quantitative trait loci (QTL) mapping for nitrogen use efficiency and its relationship with productivity and quality of the biennial crop Belgian endive (Cichorium intybus L.). Journal of plant physiology, 15 (167) 1253-63
  • Huang YF., Madur D., Combes V., Ky CL., Coubriche D., Jamin P., Jouanne S., Dumas F., Bouty E., Bertin P., Charcosset A., Moreau L. . (2010) The genetic architecture of grain yield and related traits in Zea maize L. revealed by comparing intermated and conventional populations. Genetics, 1 (186) 395-404
  • Truntzler M., Barrière Y., Sawkins MC., Lespinasse D., Betran J., Charcosset A., Moreau L. . (2010) Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes. TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 8 (121) 1465-82
  • Barre P., Moreau L. , Mi F., Turner L., Gastal F., Julier B., Ghesquière M.. (2009) Quantitative trait loci for leaf length in perennial ryegrass (Lolium perenne L.). Grass & Forage Sci, 3 (64) 310-321
  • Ducrocq S., Giauffret C., Madur D., Combes V., Dumas F., Jouanne S., Coubriche D., Jamin P., Moreau L. , Charcosset A.. (2009) Fine mapping and haplotype structure analysis of a major flowering time quantitative trait locus on maize chromosome 10. Genetics, 4 (183) 1555-63
  • Jannink JL., Moreau L. , Charmet G., Charcosset A.. (2009) Overview of QTL detection in plants and tests for synergistic epistatic interactions. Genetica, 2 (136) 225-36
  • Blanc G., Charcosset A., Veyrieras JB., Gallais A., Moreau L. . (2008) Marker-assisted selection efficiency in multiple connected populations: a simulation study based on the results of a QTL detection experiment in maize. Euphytica, 1-2 (161) 71-84