Personal Websites

Services to the scientific community

* Medicago truncatula biodiversity, geography and genetic resources:

* Medicago truncatula integrated genome viewer (V4.2 annotations, SNPs, genetic maps, RNA-Seq data, …) :

* Medicago truncatula genetic maps :

Laurent Gentzbittel

Full Professor, Head of Digital Agriculture Laboratory
Digital AgroLaboratory

Laurent Gentzbittel received the M.Sc. degree in Genetics and Molecular Biology in 1986 and got his PhD degree in Molecular Genetics from University of Lyon I (France) in 1990.

Laurent Gentzbittel then worked for 7 years in a biotech company as a project leader then as research manager to develop and implement genetic techniques and molecular methods in sunflower.

He then joined the Higher School of Agronomy (Agro-Toulouse), France, as Professor of Quantitative Genetics and Plant Genomics where he has been since 1998.
Laurent Gentzbittel was teaching genomics and statistical genetics at graduate and PhD levels. He has led, leads or participates in several major research projects (French and EU) in plant genomics, and the establishment of genomics facilities in Toulouse. He was also Primary Collaborator in NSF-funded programs. Pr Gentzbittel’s significant research contributions include some pioneering publications including Genome Biol., PNAS, Mol. Biol. Evol. or Nucleic Acid Res.

At Skoltech Dr Gentzbittel will focus on promoting the Agrotechnologies Program into one of the premier research and innovation center in agriculture. The Agrotechnologies Program will integrate knowledge in quantitative genetics, breeding, genomics, molecular biology, statistics and big data to develop and implement new strategies and methods in trait dissection for crop and animal improvement and digital agriculture, to foster innovation.

The development of the Agrotechnologies Program will have three objectives: 1) Collaborate with industry and academics to foster innovation and agro-industrial development in Russia 2) Develop high-level, cutting-edge, basic research programs, towards quick delivering of improved plant varieties or animal breeds, and digital agriculture solutions and 3) Develop teaching and education, including training, retraining and advanced-training of current specialists.

  • Identification and functional validation of genes encoding traits of agronomic and adaptive importance in plants

Based on a strong and solid background in plant genetics (linkage mapping, QTL, GWAS, Genomic Prediction) and genomics (SNPs, transcriptome, proteome, shortRNAome), and using a large portfolio of molecular biology and cellular biology methods (amiRNAs, insertional mutagenesis, KO or over-expression via plant genetic transformation, etc..), we identify and functionally validate genes involved in response to biotic stress. We are currently implementing several genome editing tools in Legumes (soybean, peas, barrel medic, alfalfa) to understand and improve quantitative disease resistances (QDR) and phenology.

  • Whole-genome approaches to efficiently integrate high-throughput genotyping and phenotyping into breeding processes

Most of the adaptive or agronomic important traits (fitness, yield, life expectancy,  resistance or tolerance to abiotic stress, durable resistances to diseases, etc..) are highly influenced by the environment and often determined by a (very) large number of genes. Phenotypic plasticity  also plays an important role in GxE interactions. Using HT, HQ -omics data, we are developing quantitative genetics and statistical models to improve the prediction of these complex phenotypes.  We also implement and test the usability of  these methods in practical breeding programs.

  • Whole-genome approaches to explore crop and natural populations adaption.

Potential of genomic tools for studies of local adaptation and climate change adaptation in crops and natural populations are now clear, in association with experiments such as reciprocal transplants, common gardens, or treatment experiments.  Genomic tools can help to map spatial patterns of adaptive genetic variation and identify genes underlying locally adaptive traits. Using several plant models, including cultivated or native plants, we develop whole-genome based methods and test hypotheses to predict local adaptation and climate change adaptation.

see also Google Scholar

1. Grigoreva E., Ulianich P., Ben C., Gentzbittel L.*, Potokina E.* (2019) First insights into the guar (Cyamopsis tetragonoloba (L.) Taub.) genome of the ‘Vavilovskij 130’ accession, using second and third-generation sequencing technologies. Russian J. Genet. 55(11):1406-1416 doi:10.1134/S102279541911005X * co-corresponding authors
2. Gentzbittel L., Ben C., Mazurier M., Shin M-G., Todd L., Rickauer M., Marjoram P., Nuzhdin S., Tatarinova T.V. (2019) WhoGEM: an admixture- based prediction machine accurately predicts quantitative functional traits in plants. Genome Biol. doi: 10.1186/s13059-019-1697-0 (2017 IF : 16.49)
3. Yamchi A., Ben C., Rossignol M., Zareie S.R., Mirlohi A., Sayed-Tabatabaei B.E., Pichereaux C., Sarrafi A., Rickauer M., Gentzbittel L. (2018) Proteomics analysis of Medicago truncatula response to infection by the phytopathogenic bacterium Ralstonia solanacearum points to jasmonate and salicylate defence pathways. Cellular Microbiol. 20:e12796 doi:10.1111/cmi.12796 (2016 IF : 4.55)
4. Garmier M., Gentzbittel L., Wen J.Q., Mysore K.S., Ratet P. (2017) Genetic and genomic resources for the study of Medicago truncatula. Curr. Protocol. Plant Biol. 2:4 doi:10.1002/cppb.20058
5. Kadri A., Julier B., Laouar M., Ben C., Badri M., Chedded J., Mouhouche B., Gentzbittel L., Abdelguerfi A. (2017) Genetic determinism of fitness traits under drought stress in the model legume Medicago truncatula. Acta Physiol. Plant. 39:227 doi:10.1007/s11738-017-2527-1 (2016 IF : 1.68)
6. Cai F., Watson B.S., Meek D., Huhman D.V., Wherritt D.J., Ben C., Gentzbittel L., Driscoll B.T., Sumner L.W., Bede J. (2017) Medicago truncatula oleanolic-derived saponins are correlated with caterpillar deterrence. J. Chem Ecol. 43:712-724. doi:10.1007/s10886-017-0863-7(2015 IF : 3.15)
7. Rahoui S., Martinez Y., Sakouhi L., Ben C., Rickauer M., El Ferjani E., Gentzbittel L., Chaoui A. (2017) Cadmium-induced changes in antioxidative systems and differentiation in roots of contrasted Medicago truncatula lines. Protoplasma 254(1):473-489 doi:10.1007/s00709-016-0968-9 (2016 IF : 2.66)
8. Toueni M., Ben C., Leru A., Gentzbittel L.*, Rickauer M.* (2016) Quantitative resistance to Verticillium wilt in Medicago truncatula involves eradication of the fungus from roots and is associated with transcriptional responses related to innate immunity. Front. Plant Sci. 7:1431. doi:10.3389/fpls.2016.01431 * co-corresponding authors (2016 IF : 4.68)
9. Gentzbittel L., Ben C., Rickauer M., Andersen S.U., Stougaard J., Young N.D. (2015) Naturally occuring diversity helps to reveal genes of adaptive importance in Legumes. Frontier Plant Sci.6:269. doi:10.3389/fpls.2015.00269 (2016 IF : 4.68)
10. Rahoui S., Chaoui A., Ben C., Rickauer M., Gentzbittel L., El Ferjani E. (2015) Effect of cadmium pollution on mobilization of embryo reserves in seedlings of six contrasted Medicago truncatula lines. Phytochemistry 111:98-106 doi:10.1016/j.phytochem.2014.12.002 (2016 IF :3.35)
11. Rubiales D., Singh K.B., Higgins T.J.V., Fondevilla S., Gentzbittel L., Lichtenzveig J., Chen W., Rispail N. (2015) Achievements and challenges in Legume breeding for pest and disease resistance. Crit. Rev. Plant Sci. 34(1-3):195-236. (2015 IF : 5.98)
12. Formey D., Sallet E., Lelandais-Brie`re C., Ben C., Bustos-Sanmamed P., Niebel A., Frugier F., Combier JP., Hartmann C., Wincker P., Roux C., Gentzbittel L.*, Gouzy J., Crespi M.* (2014) The small RNA diversity from Medicago truncatula roots under biotic interactions evidences the environmental plasticity of the miRNome. Genome Biol. 15(9):457 (2014 IF : 13.48) *co-corresponding authors.
13. Foroozanfar M, Exbrayat S, Gentzbittel L, Bertoni G, Maury P, Naghavie M, Peyghambari A, Badri M, Ben C, Debelle´ F, Sarrafi A. (2014) Genetic variability and identification of QTL affecting plant growth and chlorophyll fluorescence parameters in the model legume Medicago truncatula under control and salt conditions. Functional Plant Biol. 41:983-1001 (2014 IF : 3.38)
14. Tang H.B., Krishnakumar V., Bidwell S., Rosen B., Chan A., Zhou S.G., Gentzbittel L., Childs KL., Yandell M., Gundlach H., Mayer K.F.X., Schwartz D.C., Town C.D. (2014) An improved genome release (version Mt4.0) for the model legume Medicago truncatula. BMC Genomics 15:312 (2014 IF : 4.36)
15. Rahoui S., Ben C., Chaoui A., Martinez Y., Yamchi A., Rickauer M., Gentzbittel L., El Ferjani E. (2014) Oxidative injury and antioxidant genes regulation in cadmium-exposed radicles of six contrasted Medicago truncatula genotypes. Environ. Sci. Pollut. R. 21(13):8070-8083 (2014 IF : 2.92)
16. Mouttet R., Escobar-Gutie´rrez A., Esquibet M., Gentzbittel L., Mugnie´ry D., Reignault P.,Sarniguet C., Castagnone-Sereno P. (2014) Banning of methyl bromide for seed treatment: Could Ditylenchus dipsaci become again a major threat for alfalfa production in Europe? Pest Manag. Sci. 70(7):1017-1022 (2014 IF : 2.86)
17. Madrid E., Barilli E., Gil J., Huguet T., Gentzbittel L., Rubiales D. (2014) Detection of partial resistance QTL against Didymella pinodes in Medicago truncatula. Mol. Breeding 33:589-599 (2014 IF : 2.57)
18. Negahi, A., Ben, C., Gentzbittel, L., Maury, P., Nabipour, A., Ebrahimi, A., Sarrafi, A., Rickauer, M. (2014) Quantitative trait loci associated with resistance to a potato isolate of Verticillium albo-atrum in Medicago truncatula. Plant Pathol. 63(2):308-315 (2014 IF : 2.57)
19. Ben, C., Debelle´, F., Berges, H., Bellec, A., Jardinaud, M.-F., Anson, P., Huguet, T., Gentzbittel, L., Vailleau, F. (2013). MtQRRS1, an R-locus required for Medicago truncatula quantitative resistance to Ralstonia solanacearum. New Phytol. 199:758-772 (2014 IF : 7.84)
20. Ben, C., Toueni, M., Montanari, S., Tardin, M.-C., Fervel, M., Negahi, A., Saint-Pierre, L., Mathieu, G., Gras, M.-C., Noe¨ l, D., Prospe´ri, J.-M., Pilet-Nayel, M.-L., Baranger, A., Huguet, T., Julier, B., Rickauer, M., Gentzbittel, L. (2013). Natural diversity in the model legume Medicago truncatula allows identifying distinct genetic mechanisms conferring partial resistance to Verticillium wilt. J. Exp. Bot. 64: 317–332. (2014 IF : 6.31)
21. Huang, X., Fabre, F., Sarrafi, A., Liu, Z., Gentzbittel, L. (2013). Analysis of somatic embryogenesis QTL and marker-assisted selection in sunflower (Helianthus annuus L.). Chinese Journal of Oils Crop Sciences 35: 524–532.
22. Saeidi G, Rickauer M, Gentzbittel L. (2012). Tolerance for cadmium pollution in a core-collection of the model legume, Medicago truncatula L. at seedling stage. Aust J Crop Sci. 6:641-648 (2011 IF : 1.68)
23. Branca A, Paape TD, Zhou P, Briskine R, Farmer AD, Mudge J, Bharti AK, Woodward JE, May GD, Gentzbittel L, Ben C, Denny R, Sadowsky MJ, Ronfort J, Bataillon T, Young ND, Tiffin P. (2011). Whole-genome nucleotide diversity, recombination, and linkage disequilibrium in the model legume Medicago truncatula. Proc Natl Acad Sci U S A. 108(42): E864-870 (2014 IF : 9.67)
24. Turner, M., Jauneau, A., Genin, S., Tavella, M.-J., Vailleau, F., Gentzbittel, L., Jardinaud, M.-F (2009). Dissection of bacterial Wilt on Medicago truncatula revealed two type III secretion system effectors acting on root infection process and disease development. Plant Physiol. 50:1713-1722. (2014 IF : 8.03)
25. Stewart S., Hodge S., Mansfield J., Prosperi J.M., Huguet T., Ben C., Gentzbittel L., Powell G. (2009). The RAP1 gene confers extreme resistance to the pea aphid in Medicago truncatula without engaging the hypersensitive reaction. Mol Plant Microb Interact. 22(12):1645- 1655. (2014 IF : 4.41)
26. Buti M, Giordani T, Vukich M, Gentzbittel L, Pistelli L, Cattonaro F, Morgante M, Cavallini A, Natali L. (2009). HACRE1, a recently inserted copia-like retrotransposon of sunflower (Helianthus annuus L.). Genome 52:904-911
27. Roche, J., Hewezi, T., Bouniols, A., Gentzbittel, L. (2009). Real-time PCR monitoring of signal transduction related genes involved in water stress tolerance mechanism of sunflower. Plant Physiol. Biochem. 47:139–145.
28. Darvishzadeh, R., Hewezi, T., Gentzbittel, L., Sarrafi, A. (2008). Differential expression of defence-related genes between compatible and partially compatible sunflower–Phoma macdonaldii interactions. Crop Protection 27:740–746.
29. Hewezi T, Léger M, Gentzbittel L. (2008). A comprehensive analysis of the combined effects of high light and high temperature stresses on gene expression in sunflower. Ann Bot(Lond) 102:127-40.
30. Vailleau F., Sartorel E., Jardinaud M.F., Chardon F., Génin S., Huguet T., Gentzbittel L., Petitprez M. (2007). Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula. Mol Plant Microb Interact. 20(2):159-167.
31. Poormohammad Kiani S., Grieu P., Maury P., Hewezi T., Gentzbittel L., Sarrafi A. (2007). Genetic variability for physiological traits under drought conditions and differential expression of water stress-associated genes in sunflower (Helianthus annuus L.). Theor Appl Genet 114:193-207.
32. Roche J., Hewezi T., Bouniols A., Gentzbittel L. (2007). Transcriptional profiles of primary metabolism and signal transduction-related genes in response to water stress in field-grown sunflower genotypes using a thematic cDNA microarray. Planta 226:601-17
33. Huang XQ., Nabipour A., Gentzbittel L., Sarrafi A. (2007) Somatic embryogenesis from thin epidermal layers in sunflower and chromosomal regions controlling the response. Plant Sci 173:247-252
34. Abou Alfadil T., Poormohammad Kiani S., Dechamp-Guillaume G., Gentzbittel L., Sarrafi A. (2007). QTL mapping of partial resistance to Phoma basal stem and root necrosis in sunflower (Helianthus annuus L.) Plant Sci 172:815-823
35. Darvishzadeh. R, Kiani S.P., Dechamp-Guillaume G., Gentzbittel L., Sarrafi A. (2007) Quantitative trait loci associated with isolate specific and isolate nonspecific partial resistance to Phoma macdonaldii in sunflower. Plant Pathol. 56:855-861.
36. Kiani S.P., Talia P., Maury P., Grieu P., Heinz R., Perrault A., Nishinakamasu V., Hopp E., Gentzbittel L., Paniego N., Sarrafi A. (2007). Genetic analysis of plant water status and osmotic adjustment in recombinant inbred lines of sunflower under two water treatments. Plant Sci 172:773-787
37. Angot A., Peeters N., Lechner E., Vailleau F., Gentzbittel L., Sartorel E., Genschik P., Boucher C., Genin S. (2006). Ralstonia solanacearum requires F-box-like domain-containing type III effectors to promote disease on several host plants. Proc Natl Acad Sci USA. 103(39):14620-14625.
38. Hewezi T., Léger M., El Kayal W., Gentzbittel L. (2006). Transcriptional profiling of sunflower plant growing under low temperatures reveals an extensive downregulation of gene expression associated with chilling sensitivity. J Exp. Bot. 57:3109-3122.
39. Alignan M., Hewezi T., Petitprez M., Dechamp-Guillaume G., Gentzbittel L. (2006). A cDNA microarray approach to decipher sunflower (Helianthus annuus) responses to the necrotrophic fungus Phoma macdonaldii. New Phytol. 170:523-536.
40. Hewezi T., Petitprez M., Gentzbittel L. (2006). Primary metabolic pathways and signal transduction in sunflower (Helianthus annuus L. ) : Comparison of transcriptional profiling in leaves and immature embryos using cDNA microarrays. Planta 223:948-964
41. Petitprez M., Sarrafi A., Flores-Berrios E., XuHan X., Brière C., Gentzbittel L. (2005). Somatic embryogenesis by liquid culture of epidermal layers in sunflower: from genetic control to cell development. Plant Cell, Tissue and Organ Culture 81:331-337.
42. Al-Chaarani G., Gentzbittel L., Wedzony M., Sarrafi A. (2005). Identification of QTLs for germination and seedling development in sunflower (Helianthus annuus L.). Plant Sci 169: 221-227.
43. Alejo-Jaimes A., Jardinaud M. F., Maury P., Alibert G., Gentzbittel L., Sarrafi A., Grieu P., Petitprez M. (2004). Genetic variation for germination and physiological traits in sunflower mutants induced by gamma rays. J Genet Breed 58:285-294.
44. Ben C., Hewezi T., Jardinaud M.F., Béna F., Ladouce N., Moretti S., Tamborindeguy C., Liboz T., Petitprez M., Gentzbittel L. (2004) Comparative analysis of early embryonic sunflower cDNA libraries. Plant Mol Biol. 57:255-270
45. Müller C., Denis M., Gentzbittel L., Faraut T. (2004) The ICCARE Web server: an attempt to merge sequence and mapping information for plant and animal species. Nucleic Acid Res 32: W429-W434.
46. Tamborindeguy C., Ben C., Liboz T., Gentzbittel L. (2004) Sequence evaluation of four cDNA libraries for sunflower developmental genomics. Mol Genet Genomics 271:367-375
47. Tamborindeguy C., Ben C., Jardinaud F., Gentzbittel L., Liboz T. (2004) Study of embryogenesis in sunflower : mass-cloning of differential and non-differential transcript-derived-fragments (TDF) from cDNA-AFLP experiments. Plant Mol Biol Rep 22:1-7
48. El-Sharkawy I., Jones B., Gentzbittel L., Lelièvre J-M., Pech J.C., Latché A. (2004) Differential regulation of ACC synthase genes in cold-dependent and -independent ripening in pear fruit. Plant Cell Environ 27:1197-1210
49. Al-Chaarani G., Gentzbittel L., Barrault G., Lenoble S., Sarrafi A. (2004). The effects of gamma rays and genotypes on sunflower organogenesis traits. J Genet Breed 58:
50. Rachid Al-Chaarani G., Gentzbittel L., Huang X.Q., Sarrafi A. (2004) Genotypic variation and identification of QTLs for agronomic traits, using AFLP and SSR markers in RILs of sunflower (Helianthus annuus). Theor Appl Genet 109:1353-1360
51. Langar K., Lorieux M., Desmarais E., Griveau Y., Gentzbittel L., Berville A. (2003) Combined mapping of DALP and AFLP markers in cultivated sunflower using F9 recombinant inbred lines. Theor Appl Genet 106:1068-1074.
52. Huang XQ, Gentzbittel L., Petitprez M., Sarrafi A. (2002) Genetic control for protoplast division in recombinant inbred lines of sunflower (Helianthus annuus L.). J Genet Breed 56:365-370.
53. Mokrani L., Gentzbittel L., Azanza F., Fitamant L., Al-Chaarani G., Sarrafi A. (2002) Mapping and analysis of quantitative trait loci for grain oil content and agronomic traits using AFLP and SSR in sunflower (Helianthus annuus L.).Theor Appl Genet 106:149-156.
54. Gentzbittel L., Abbott A., Galaud JP., Georgi L., Fabre F., Liboz T., Alibert G. (2002) A bacterial artificial chromosome (BAC) library for sunflower, and identification of clones containing genes for putative transmembrane receptors. Mol Genet Genomics 266:979-987.
55. Rachid Al-Chaarani G., Roustaee A., Gentzbittel L., Mokrani L., Barrault G., Dechamp-Guillaume G., Sarrafi A. (2002) A QTL analysis of sunflower partial resistance to downy mildew (Plasmopara halstedii) and black stem (Phoma macdonaldii) by the use of recombinant inbred lines (RILs). Theor Appl Genet 104:490-496.
56. Hervé, D., Fabre F., Flores Berrios E., Leroux N., Al Chaarani G., Planchon C., Sarrafi A., Gentzbittel L. (2001) QTL analysis of photosynthesis and water status traits in sunflower (Helianthus annuus L.) under greenhouse conditions. J Exp Bot 52:1857-1864.
57. Flores Berrios E., Gentzbittel L., Alibert G., Sarrafi A. (2000) . Genotypic variation and chromosomal location of QTLs for somatic embryogenesis revealed by epidermic layers culture of recombinant inbred lines in the sunflower (Helianthus annuus L.). Theor Appl Genet 101:1307-1312.
58. Flores Berrios E., Gentzbittel L., Kayyal H., Alibert G., Sarrafi A. (2000) AFLP mapping of QTLs for in vitro organogenesis traits using recombinant inbred lines in sunflower (Helianthus annuus L.). Theor Appl Genet 101:1299-1306.
59. Flores Berrios E., Gentzbittel L., Mokrani L., Alibert G., Sarrafi A. (2000) Genetic control of early events in protoplast division and regeneration pathways in sunflower. Theor Appl Genet 101:606-612.
60. Bolandi A.R., Branchard M., Alibert G., Gentzbittel L., Berville A., Sarrafi A. (2000) Combining-ability analysis of somatic embryogenesis from epidermal layers in the sunflower (Helianthus annuus L.). Theor Appl Genet 100:621-624.
61. Flores Berrios E, Gentzbittel L, Serieys H, Alibert G, Sarrafi A. (1999) Influence of genotype and gelling agents on in vitro regeneration by organogenesis in sunflower (Helianthus annuus L.). Plant, Cell, Tissue and Org. Cult. 59:65-69.
62. Berrios EF, Gentzbittel L, Alibert G, Griveau Y, Berville A, Sarrafi A. (1999) Genetic control of in vitro-organogenesis in recombinant inbred lines of sunflower (Helianthus annuus L.). Plant Breed 118:359-361.
63. Gentzbittel L, Mestries E, Mouzeyar S, Mazeyrat F, Badaoui S, Vear F, Tourvieille de Labrouhe D, Nicolas P (1999) A composite map of expressed sequences and phenotypic traits of the sunflower (Helianthus annuus L.) genome. Theor Appl Genet 99:218-234.
64. Gentzbittel L, Mouzeyar S, Badaoui S, Mestries E, Vear F, Tourvieille de Labrouhe D, Nicolas P (1998) Cloning of molecular markers for disease resistance in sunflower, Helianthus annuus L. Theor Appl Genet 96:519-525.
65. Mestries E, Gentzbittel L, Tourvieille de Labrouhe D, Nicolas P, Vear F (1998) Analysis of quantitative trait loci associated with resistance to Sclerotinia sclerotiorum in sunflowers (Helianthus annuus L.) using molecular markers. Mol Breeding 4:215-226.
66. Courbou I, Badaoui S, Mouzeyar S, Gentzbittel L, Nicolas P (1997) RT-PCR cloning of a sunflower calmodulin (accession U79736) complete cds. (PGR97-072). Plant Physiol 114:395.
67. Vear F, Gentzbittel L, Philippon J, Mouzeyar S, Mestries E, Roeckel-Drevet P, Tourvieille de Labrouhe D, Nicolas P (1997) The genetics of resistance to five races of downy mildew (Plasmopara halstedii) in sunflower (Helianthus annuus L.). Theor Appl Genet 95:584-589.
68. Roeckel-Drevet P, Gagne G, Mouzeyar S, Gentzbittel L, Philippon J, Nicolas P, Tourvieille de Labrouhe D, Vear F (1996) Colocation of downy mildew (Plasmopara halstedii) resistance genes in sunflower (Helianthus annuus L.). Euphytica 91:225-228.
69. Mouzeyar S, Roeckel-Drevet P, Gentzbittel L, Philippon J, Tourvieille de Labrouhe D, Vear F, Nicolas P (1995) RFLP and RAPD mapping of the sunflower Pl1 locus for resistance to Plasmopara halstedii race 1. Theor Appl Genet 91:733-737.
70. Gentzbittel L, Vear F, Zhang Y-X, Bervillé A, Nicolas P (1995) Development of a consensus linkage RFLP map of cultivated sunflower (Helianthus annuus L.). Theor Appl Genet 90:1079-1086.
71. Zhang Y-X, Gentzbittel L, Vear F, Nicolas P (1995) Assessment of inter- and intra- inbred line variability in sunflower (Helianthus annuus L.) by RFLPs. Genome 38:1040-1048.
72. Gentzbittel L, Zhang X-Y, Vear F, Griveau B, Nicolas P (1994) RFLP studies of genetic relationships among inbred lines of the cultivated sunflower, Helianthus annuus L.: evidence for distinct restorer and maintainer germplasm pools. Theor Appl Genet 89:419-425.
73. Gentzbittel L, Perrault A, Nicolas P (1992) Molecular phylogeny of the Helianthus genus, based on nuclear restriction-fragment-length polymorphism (RFLP). Mol Biol Evol 9:872-892.
74. Gentzbittel L, Nicolas P (1990) Improvement of “A BASIC program to construct evolutionary trees from restriction endonucleases data” with the use of PASCAL language. J Hered 81:491-492.
75. Crouzillat D, Gentzbittel L, de la Canal L, Vaury C, Perrault A, Nicolas P, Ledoigt G (1989) Properties and nucleotide sequence of a mitochondrial plasmid from sunflower. Curr Genet 15:283-289.
76. Gentzbittel L, Nicolas P (1989) A BASIC program to construct evolutionary trees from restriction endonucleases data. J Hered 80:254.

Extra pay for ’Scientific Excellence and Ph.D Supervision’ since 2000, without interruptions (promotion based on national ranking of the best 15% candidates)

Cecile Ben
Principal Research Scientist
Elena Martynova
Research Scientist
Pavel Mazin
Research Scientist
Stepan Boldyrev
  • Modern Plant Breeding: from Genetic Resources to Marker Assisted Selection and Genomic Prediction.
    Plant breeding is one of the most important science and technology developed by humankind.
    In a context where reductions on chemical inputs are required by societal demand and national and international regulations, but where the demand for raw materials continues to increase to cope with demographic change, the genetic improvement of plants contributes to answer these major challenges, while integrating them into a sustainable development policy. This module trains executives specialized in plant breeding and creation of plant varieties.
  • Experimental designs and Advanced BioStatistics.
    Given the wealth of raw genomics data, the challenge is now to get the most of observations and to decipher the phenotypes – genotypes relationships, including the Genotype x Environment component.  Reliable phenotypic data (at the ‘macro’ level such as breading quality or plant’s fitness, ‘micro’ level such as cellular response or pathogen colonization, or ‘molecular’ level such as gene expression levels or metabolite profiling) are thus a must for good genetic studies thanks to high-throughput high-quality phenotyping methods.
    Reliable high-quality phenotypic data rely on proven and accurate experimental designs, and make use of covariates. Genetic relationships among individuals ought also to be included in the models.  The matrix form of the Linear Mixed  Model allows an unprecedented and successful jump into this task, due to its extraordinary flexibility and the improvement of computational resources.