logo umr
Génétique Quantitative et Évolution - Le Moulon

Matthieu FALQUE

Matthieu FALQUE

Research Engineer, INRAE

Meiotic recombination

  • plant genetics,
  • molecular markers,
  • linkage mapping,
  • meiosis and recombination,
  • modeling

matthieu.falque@inrae.fr

+33 (0)1 69 33 23 64

orcid.org/0000-0002-6444-858X

Publications

  • Génétique Quantitative et Évolution - Le Moulon
  • Université Paris-Saclay, INRAE, CNRS, AgroParisTech
  • Ferme du Moulon
  • F-91190 Gif-sur-Yvette

Education and Positions

  • Currently Member of the BASE team, affiliated with the Labex Saclay Plant Sciences
  • HDR (ability to supervise PhD students) 2015, University of Orsay, France
  • Currently Head of the ACEP team (Atelier Cartographie Expression Polymorphisme)
  • Since 1998: Ingénieur de Recherche (INRA) at UMR GQE - Le Moulon, Gif-sur-Yvette, France
  • Postdoc in Plant Population Genetics (1997-1998) CNRS, Lille France
  • Postdoc in Plant Population Genetics (1995-1997) NIOO-CTO, Heteren-Wageningen, The Netherlands
  • Postdoc in Plant Molecular Genetics (1994-1995) CIRAD, Montpellier, France
  • Ph.D. in Plant Biology (1994), Univ Toulouse, France

Research interests

My research in the BASE team

2 pathways for crossover formation

2 pathways for crossover formation

Starting from linkage mapping for plant breeding applications, my research now mostly focuses on crossover number and distribution. In particular, I have been developing with Olivier Martin mathematical models to simulate crossover interference. These models take into account the two different pathways of crossover formation which have been discovered in several organisms. Using these modeling approaches, we have unveiled the existence of these two distinct pathways of crossover formation in Maize, and investigated quantitative properties of crossover formation mechanisms in different species. In particular, we have demonstrated in Tomato that crossovers produced by two different pathways still can interfere with each other out to distances of about 6 microns.

Fluorescent markers FACS-based method for high-throughput measurement of recombination rate and crossover interference in the budding yeast

FACS recombination phenotyping (simple case of 2 markers)

More recently, with my PhD student Xavier Raffoux , we have developed experimental approaches using the budding yeast as a model species to investigate the genetics underlying quantitative variability of recombination rate and landscape along chromosomes.
First, we have developed a method to measure recombination rate and crossover interference at high-throughput by using fluorescent markers. We have developed 8 tester strains spanning entirely chromosomes VI and XI, and parly chromosome I. In each tester, 3 linked fluorescent markers have been inserted at about 30cM from each other, thus delimiting 2 consecutive intervals from which crossover interference can be measured with a very high accurracy (Ref).
Then we have applied this method to characterize the intra-specific diversity of recombination rate and interference in the species S. cerevisiae. In the different intervals analyzed, recombination showed up to 9-fold variation across strains but global recombination landscapes along chromosomes varied less. We also measured recombination rates in one region in 10 different crosses involving five parental strains. Our overall results indicate that recombination rate is increasingly positively correlated with sequence similarity between homologs. We also estimated that cis and trans effects explained respectively 38% and 17% of the variance of recombination rate(Ref).
Our main research interest now is about evolutionary aspects of meiotic recombination. Using our FACS-based method, we will implement experimental evolution under recurrent selection for modified increased or dereased rate, and use the evolved populations to investigate the role of recombination in adaptation to stress.

My research in the ACEP group

The ACEP group is an internal platform of services in the fields of genetic map construction and analyses of DNA polymorphism and gene expression. We provide DNA analysis service and keep a technological witch in molecular marker technologies. I also develop software tools for automated genetic mapping with large numbers of markers, and I have constructed high-density genetic maps in several plant species.

Current Projects

  1. Experimental evolution under recurrent selection for meiotic recombination rate
  2. Automatic construction of high-resolution linkage maps from data sets with high numbers of markers.
  3. Quantifying across successive generations how linkage slows down genetic progress and how to best use new technologies that enhance recombination rates.

Teaching activities

Occasional teaching for students and professionals from breeding companies on molecular markers, genetic mapping, and plant genomics for breeding.

Publications

Carrillo-Perdomo E, Vidal A, Kreplak J, Duborjal H, Leveugle M, Duarte J, Desmetz C, Deulvot C, Raffiot B, Marget P, Tayeh N, Pichon JP, Falque M, Martin OC, Burstin J, Aubert G. (2020) Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene-based SNP markers and the construction of a high-density consensus map. Sci Rep, 1 (10) 6790
Falque M, Jebreen K, Paux E, Knaak C, Mezmouk S, Martin OC. (2020) CNVmap: A Method and Software To Detect and Map Copy Number Variants from Segregation Data. Genetics, 3 (214) 561-576
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
Kreplak J, Madoui MA, Cápal P, Novák P, Labadie K, Aubert G, Bayer PE, Gali KK, Syme RA, Main D, Klein A, Bérard A, Vrbová I, Fournier C, d’Agata L, Belser C, Berrabah W, Toegelová H, Milec Z, Vrána J, Lee HT, Kougbeadjo A, Térézol M, Huneau C, Turo CJ, Mohellibi N, Neumann P, Falque M, Gallardo K, McGee R, Tar’an B, Bendahmane A, Aury JM, Batley J, Le Paslier MC, Ellis N, Warkentin TD, Coyne CJ, Salse J, Edwards D, Lichtenzveig J, Macas J, Doležel J, Wincker P, Burstin J. (2019) A reference genome for pea provides insight into legume genome evolution. Nat Genet, 9 (51) 1411-1422
Martinez Palacios P, Jacquemot MP, Tapie M, Rousselet A, Diop M, Remoué C, Falque M, Lloyd A, Jenczewski E, Lassalle G, Chévre AM, Lelandais C, Crespi M, Brabant P, Joets J, Alix K. (2019) Assessing the Response of Small RNA Populations to Allopolyploidy Using Resynthesized Brassica napus Allotetraploids. Mol Biol Evol, 4 (36) 709-726
Termolino P, Falque M, Aiese Cigliano R, Cremona G, Paparo R, Ederveen A, Martin OC, Consiglio FM, Conicella C. (2019) Recombination suppression in heterozygotes for a pericentric inversion induces the interchromosomal effect on crossovers in Arabidopsis. Plant J, 6 (100) 1163-1175
Tourrette E, 25 novembre 2019, Unleashing genetic diversity in breeding by increasing recombination: an in silico study
Tourrette E, Bernardo R, Falque M, Martin OC. (2019) Assessing by Modeling the Consequences of Increased Recombination in Recurrent Selection of Oryza sativa and Brassica rapa. G3, 12 (9) 4169-4181
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
Raffoux X, 2018-06-11 06/11/18, Diversité et déterminisme génétique de la recombinaison méiotique chez Saccharomyces cerevisiae
Raffoux X, Bourge M, Dumas F, Martin OC, Falque M. (2018) High-throughput measurement of recombination rates and genetic interference in Saccharomyces cerevisiae. Yeast, 6 (35) 431-442
Raffoux X, Bourge M, Dumas F, Martin OC, Falque M. (2018) Role of Cis, Trans, and Inbreeding Effects on Meiotic Recombination in Saccharomyces cerevisiae. Genetics, 4 (210) 1213-1226
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
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
Pelé A, Falque M, Trotoux G, Eber F, Nègre S, Gilet M, Huteau V, Lodé M, Jousseaume T, Dechaumet S, Morice J, Poncet C, Coriton O, Martin OC, Rousseau-Gueutin M, Chèvre AM. (2017) Amplifying recombination genome-wide and reshaping crossover landscapes in Brassicas. PLoS Genet, 5 (13)
Falque M, 2015-10-15 15/10/15, Sur les traces de la recombinaison méiotique, source de biodiversité et outil génétique
Sidhu GK, Fang C, Olson MA, Falque M, Martin OC, Pawlowski WP. (2015) Recombination patterns in maize reveal limits to crossover homeostasis. PNAS, 52 (112) 15982-15987
Ganal MW, Durstewitz G, Polley A, Bérard A, Buckler ES, Charcosset A, Clarke JD, Graner EM, Hansen M, Joets J, Le Paslier MC, McMullen MD, Montalent P, Rose M, Schön CC, Sun Q, Walter H, Martin OC, Falque M, Lukens L. (2011) A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome. PLoS ONE, 12 (6) e28334
Gauthier F, Martin O, Falque M. (2011) CODA (crossover distribution analyzer): quantitative characterization of crossover position patterns along chromosomes. BMC Bioinformatics, 1 (12) 27