Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloning identified several QTLs. However linkage mapping is limited to the analysis of traits differing between two lines and the impact of the genetic background on QTL effect has been underlined. Genome-wide association studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shown that GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impact of population structure. Nevertheless, GWAs success might be limited due to the low decay of linkage disequilibrium, which varies along the genome in this species. Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC population by crossing eight tomato lines whose genomes were resequenced. We showed the potential of the MAGIC population when coupled with whole genome sequencing to detect candidate single nucleotide polymorphisms (SNPs) underlying the QTLs. QTLs for fruit quality traits were mapped and related to the variations detected at the genome sequence and expression levels. The advantages and limitations of the three types of population, in the context of the available genome sequence and resequencing facilities, are discussed.This work was supported by CEA-IG/CNG, by performing the DNA QC and providing access to INRA-EPGV to their Illumina Sequencing Platform. We acknowledge groups of Anne Boland (DNA and Cell Bank service) and Marie-Thérèse Bihoreau (Illumina HT Sequencing). The ANR MAGIC-Tom SNP project 09-GENM-109G and the European Solanaceae Integrated Project EUSOL (Food-CT-2006-016214) supported this work. LP was supported by a postdoctoral INRA fellowship, EA by an INRA PhD fellowship and JD by a grant from the Embassy of France in Thailand in Junior Research Fellowship Program 2014.Peer reviewe

Comparison of metabolomic, proteomic and genomic variability in tomato fruit

International audienc

Deciphering the genetic control of quantitative traits with magic

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Deciphering the genetic control of tomato fruit quality in the resequencing era

Identifying the genes controlling the variation of quantitative traits is a key goal for breeders. Genetic variations underlying quantitative traits (QTL) have been mapped by traditional linkage mapping for years and positional cloning identified several QTLs.[br/] However linkage mapping is limited to the analysis of traits differing between two lines and the impact of genetic background on QTL effect has been underlined. Thanks to the increase in molecular markers, genome-wide association studies were then proposed to circumvent QTL limitations. ln tomato, a self-pollinated crop, we have shown that association studies are possible, using the admixed nature of cherry tomato genomes that limits the impact of population structure in such an approach.[br/] Nevertheless, the results might be limited by linkage disequilibrium, which varies greatly along the genome. Multi-allelic Advanced Generation Inter-Cross (MAGIC) populations allow a wide range of variability to be analyzed and avoid dealing with population structure

Genetic diversity, inheritance and integration of multi-level omic data in tomato fruit

Tomato fruit quality is an important trait for tomato breeders, but complex by the number of components and by their polygenic nature. In order to decipher the genetic diversity and the inheritance of fruit quality components at a global level, we conducted a large multi-level omic experiment. A set of 8 contrasted lines and 4 of their F1 hybrids were phenotyped for fruit development traits. Fruits were harvested and pericarp samples analysed at 2 stages (celle expansion and orange) and different scales: (1) primary and secondary metabolome profiles, (2) activities of 28 enzymes involved in primary metabolism, (3) proteome profiles revealed by 2D-PAGE and sequencing of 470 spots showing quantitative variations and (4) gene expression analysis by Digital Gene Expression. In parallel, the 8 lines were resequenced and more than 3 millions SNPs identified when aligned on the reference tomato genome. This experiment allowed us to address several questions: the range of variability for the metabolic traits and expression data. Correlation networks can be constructed within and between levels of analysis to identify regulatory networks. Diversity of chosen candidate genes can be analysed, relating the polymorphisms at the sequence levels with their expression. Some examples will be presente

Genetic diversity, inheritance and integration of multi-level omic data in tomato fruit

Tomato fruit quality is an important trait for tomato breeders, but complex by the number of components and by their polygenic nature. In order to decipher the genetic diversity and the inheritance of fruit quality components at a global level, we conducted a large multi-level omic experiment. A set of 8 contrasted lines and 4 of their F1 hybrids were phenotyped for fruit development traits. Fruits were harvested and pericarp samples analysed at 2 stages (celle expansion and orange) and different scales: (1) primary and secondary metabolome profiles, (2) activities of 28 enzymes involved in primary metabolism, (3) proteome profiles revealed by 2D-PAGE and sequencing of 470 spots showing quantitative variations and (4) gene expression analysis by Digital Gene Expression. In parallel, the 8 lines were resequenced and more than 3 millions SNPs identified when aligned on the reference tomato genome. This experiment allowed us to address several questions: the range of variability for the metabolic traits and expression data. Correlation networks can be constructed within and between levels of analysis to identify regulatory networks. Diversity of chosen candidate genes can be analysed, relating the polymorphisms at the sequence levels with their expression. Some examples will be presente

Genetic diversity, inheritance and integration of multi-level omic data in tomato fruit

International audienceTomato fruit quality is an important trait for tomato breeders, but complex by the number of components and by their polygenic nature. In order to decipher the genetic diversity and the inheritance of fruit quality components at a global level, we conducted a large multi-level omic experiment. A set of 8 contrasted lines and 4 of their F1 hybrids were phenotyped for fruit development traits. Fruits were harvested and pericarp samples analysed at 2 stages (celle expansion and orange) and different scales: (1) primary and secondary metabolome profiles, (2) activities of 28 enzymes involved in primary metabolism, (3) proteome profiles revealed by 2D-PAGE and sequencing of 470 spots showing quantitative variations and (4) gene expression analysis by Digital Gene Expression. In parallel, the 8 lines were resequenced and more than 3 millions SNPs identified when aligned on the reference tomato genome. This experiment allowed us to address several questions: the range of variability for the metabolic traits and expression data. Correlation networks can be constructed within and between levels of analysis to identify regulatory networks. Diversity of chosen candidate genes can be analysed, relating the polymorphisms at the sequence levels with their expression. Some examples will be presente

Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era

Open Access.Identification of the polymorphisms controlling quantitative traits remains a challenge for plant geneticists. Multiparent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping. Here, we present the first tomato MAGIC population and highlight its potential for the valorization of intraspecific variation, QTL mapping and causal polymorphism identification. The population was developed by crossing eight founder lines, selected to include a wide range of genetic diversity, whose genomes have been previously resequenced. We selected 1536 SNPs among the 4 million available to enhance haplotype prediction and recombination detection in the population. The linkage map obtained showed an 87% increase in recombination frequencies compared to biparental populations. The prediction of the haplotype origin was possible for 89% of the MAGIC line genomes, allowing QTL detection at the haplotype level. We grew the population in two greenhouse trials and detected QTLs for fruit weight. We mapped three stable QTLs and six specific of a location. Finally, we showed the potential of the MAGIC population when coupled with whole genome sequencing of founder lines to detect candidate SNPs underlying the QTLs. For a previously cloned QTL on chromosome 3, we used the predicted allelic effect of each founder and their genome sequences to select putative causal polymorphisms in the supporting interval. The number of candidate polymorphisms was reduced from 12 284 (in 800 genes) to 96 (in 54 genes), including the actual causal polymorphism. This population represents a new permanent resource for the tomato genetics community.This work was supported by the ANR MAGIC-Tom SNP project 09-GENM-109G. LP was supported by a postdoctoral INRA fellowship.Peer reviewe