Task 3.1: Exploring variation of maize genome structure and its impact on gene expression
Leader: Johann Joets (INRA UMR GQE). Involved partners: INRA UMR GQE, INRA UMR EPGV, Biogemma. Collaborative partners: INRA IJPB, INRA LEPSE, INRA RDP.

Structural variation originates from transposable element insertion, as well as gene Copy Number (CNV) and Presence/Absence Variation (PAV) and is a major player in maize genome evolution. We investigate the proportion of the different variant types, their molecular origin, their impact on gene regulatory networks, and their history among maize genetic groups.

We have generated whole genome assemblies from 7 maize lines of various geographical origins and phenotypes, and with contrasted genome size. This dataset allows unprecedented genome-wide comparisons and characterization of maize structural variation with high sequence accuracy, thus offering opportunity to evaluate the prevalence of the various molecular mechanisms underlying these variations, and to characterize the features responsible for genome size variation.

The 7 maize lines together with B73 were cultivated in controlled environment, and subjected or not to water deficit. Thirteen different organs harvested at various developmental stages have been used for transcriptome analysis. This massive dataset will be used to evidence the possible role of structural variants in water deficit tolerance as well as the impact of SVs in gene regulation networks.

We collaborate with T3.4 to investigate the extent to which such variants have contributed to maize adaptation to European conditions.

Task 3.2: Exploring variation of chromosome structure from recombination
Leader: M. Falque (INRA UMR GQE). Involved partners: INRA UMR GQE

Structural variation can involve large pieces of chromosomes, thus comprising covariation of several genomic features, such as genes or transposable elements. Using a linkage-based approach, we investigate the extent of such large-scale structural variation, and particularly Copy-Number Variations, from segregation data generated on linkage mapping populations.

We have genotyped using Illumina 15k chip 23 doubled-haploid populations obtained from different maize inbred lines to study the intra-specific variation of recombination rate and crossover interference in maize (Bauer et al., 2013). We are now developing a software to automate the construction of high-density genetic maps and we used it to build the linkage maps corresponding to the 23 populations. We use these data to detect duplications based on apparent heterozygote calls and allele frequency patterns in particular sub-populations.

We collaborate with T3.1 to investigate the overlap between cartography-based and sequence-based variants, and subsequently unravel the molecular origin of large structural variants.

Task 3.3 : Exploring maize methylome variation and plasticity to environmental constraints
Leader: C. Vitte (INRA UMR GQE). Involved partners: INRA UMR GQE, Biogemma

Plant genomes consist in a succession of genes and repeats throughout chromosomes. Allowing genes to be expressed at the right moment, and repeats (mainly transposable elements) to be tamed to avoid too high mutagenesis is critical for proper development. This is achieved through the setting and maintenance of chromatin states, which are regulated at the feature scale (genes, transposable elements). Molecular organization of these chromatin states has been well characterized. But the extent to which maize epigenome varies among individuals, the molecular origin of such variation, and to what extent the chromatin states can be challenged by environmental constraints remain to be fully elucidated.

To investigate the genome/methylome interplay, we have generated whole genome bisulfite sequencing data for several maize lines, and have detected regions with differential methylation levels. We have characterized their genomic location and abundance in the different genomic features, together with their degree of variation in the three cytosine contexts. We have generated the same data from plants grown in standard and cold conditions, thus allowing to analyze the interplay between maize genotype and environmental constraint on the generation of methylome variation.

We collaborate with T3.1 to investigate the interplay between structural and methylome variation, and with T3.4 to investigate the contribution of methylome changes in maize adaptation to European conditions.

Task 3.4: Population genomics of European maize
Leader: M. Tenaillon (INRA UMR GQE). Involved partners: INRA UMR GQE, Biogemma, INRA UMR MIA

Maize was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. The European germplasm derives from the American one, but routes of introduction to Europe are not completely clarified. We investigated maize adaptation to European conditions through the analysis of landrace selection.

We sequenced 67 maize landrace genomes from the Americas and Europe, with an average sequencing depth of 18x, and detected SNPs. We used this dataset to analyze routes of introduction, admixture and selective history of European maize and its American counterparts. By combining differentiation- and diversity-based statistics, we looked for genes and gene networks potentially involved in local adaptation.

We collaborate with T3.1 and T3.3 to investigate the contribution of structural and methylation variants in this process.

Publications:

Sequence analysis of European maize inbred line F2 provides new insights into molecular and chromosomal characteristics of presence/absence variants. 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. BMC Genomics. 2018 Feb 5;19(1):119. doi: 10.1186/s12864-018-4490-7.  EN SAVOIR PLUS

Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. Brandenburg JT, Mary-Huard T, Rigaill G, Hearne SJ, Corti H, Joets J, Vitte C, Charcosset A, Nicolas SD, Tenaillon MI. PLoS Genet. 2017 Mar 16;13(3):e1006666. doi: 10.1371/journal.pgen.1006666. eCollection 2017 Mar.   EN SAVOIR PLUS

Transposable elements, a treasure trove to decipher epigenetic variation: insights from Arabidopsis and crop epigenomes. Mirouze M, Vitte C. J Exp Bot. 2014 Jun;65(10):2801-12. doi: 10.1093/jxb/eru120. Epub 2014 Apr 17. Review.  EN SAVOIR PLUS

Intraspecific variation of recombination rate in maize.  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-González J, Ouzunova M, Revilla P, Charcosset A, Martin OC, Schön CC. Genome Biol. 2013;14(9):R103.  EN SAVOIR PLUS