Marie-Christine Le Paslier

A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this arrays use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the arrays high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.

Increase in Tomato Locule Number Is Controlled by Two Single-Nucleotide Polymorphisms Located Near WUSCHEL

In tomato (Solanum lycopersicum) fruit, the number of locules (cavities containing seeds that are derived from carpels) varies from two to up to 10 or more. Locule number affects fruit shape and size and is controlled by several quantitative trait loci (QTLs). The large majority of the phenotypic variation is explained by two of these QTLs, fasciated (fas) and locule number (lc), that interact epistatically with one another. FAS has been cloned, and mutations in the gene are described as key factors leading to the increase in fruit size in modern varieties. Here, we report the map-based cloning of lc. The lc QTL includes a 1,600-bp region that is located 1,080 bp from the 3′ end of WUSCHEL, which encodes a homeodomain protein that regulates stem cell fate in plants. The molecular evolution of lc showed a reduction of diversity in cultivated accessions with the exception of two single-nucleotide polymorphisms. These two single-nucleotide polymorphisms were shown to be responsible for the increase in locule number. An evolutionary model of locule number is proposed herein, suggesting that the fas mutation appeared after the mutation in the lc locus to confer the extreme high-locule-number phenotype.

Insertion site‐based polymorphism markers open new perspectives for genome saturation and marker‐assisted selection in wheat

In wheat, the deployment of marker-assisted selection has long been hampered by the lack of markers compatible with high-throughput cost-effective genotyping techniques. Recently, insertion site-based polymorphism (ISBP) markers have appeared as very powerful new tools for genomics and genetic studies in hexaploid wheat. To demonstrate their possible use in wheat breeding programmes, we assessed their potential to meet the five main requirements for utilization in MAS: flexible and high-throughput detection methods, low quantity and quality of DNA required, low cost per assay, tight link to target loci and high level of polymorphism in breeding material. Toward this aim, we developed a programme, IsbpFinder, for the automated design of ISBP markers and adapted three detection methods (melting curve analysis, SNaPshot Multiplex System and Illumina BeadArray technology) for high throughput and flexible detection of ISBP or ISBP-derived SNP markers. We demonstrate that the high level of polymorphism of the ISBPs combined with cost-effective genotyping methods can be used to efficiently saturate genetic maps, discriminate between elite cultivars, and design tightly linked diagnostic markers for virtually all target loci in the wheat genome. All together, our results suggest that ISBP markers have the potential to lead to a breakthrough in wheat marker-assisted selection.

The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution

The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs.

Whole genome resequencing in tomato reveals variation associated with introgression and breeding events

BackgroundOne of the goals of genomics is to identify the genetic loci responsible for variation in phenotypic traits. The completion of the tomato genome sequence and recent advances in DNA sequencing technology allow for in-depth characterization of genetic variation present in the tomato genome. Like many self-pollinated crops, cultivated tomato accessions show a low molecular but high phenotypic diversity. Here we describe the whole-genome resequencing of eight accessions (four cherry-type and four large fruited lines) chosen to represent a large range of intra-specific variability and the identification and annotation of novel polymorphisms.ResultsThe eight genomes were sequenced using the GAII Illumina platform. Comparison of the sequences with the reference genome yielded more than 4 million single nucleotide polymorphisms (SNPs). This number varied from 80,000 to 1.5 million according to the accessions. Almost 128,000 InDels were detected. The distribution of SNPs and InDels across and within chromosomes was highly heterogeneous revealing introgressions from wild species and the mosaic structure of the genomes of the cherry tomato accessions. In-depth annotation of the polymorphisms identified more than 16,000 unique non-synonymous SNPs. In addition 1,686 putative copy-number variations (CNVs) were identified.ConclusionsThis study represents the first whole genome resequencing experiment in cultivated tomato. Substantial genetic differences exist between the sequenced tomato accessions and the reference sequence. The heterogeneous distribution of the polymorphisms may be related to introgressions that occurred during domestication or breeding. The annotated SNPs, InDels and CNVs identified in this resequencing study will serve as useful genetic tools, and as candidate polymorphisms in the search for phenotype-altering DNA variations.

Genome-Wide Association Mapping in Tomato (Solanum lycopersicum) Is Possible Using Genome Admixture of Solanum lycopersicum var. cerasiforme

Genome-wide association mapping is an efficient way to identify quantitative trait loci controlling the variation of phenotypes, but the approach suffers severe limitations when one is studying inbred crops like cultivated tomato (Solanum lycopersicum). Such crops exhibit low rates of molecular polymorphism and high linkage disequilibrium, which reduces mapping resolution. The cherry type tomato (S. lycopersicum var. cerasiforme) genome has been described as an admixture between the cultivated tomato and its wild ancestor, S. pimpinellifolium. We have thus taken advantage of the properties of this admixture to improve the resolution of association mapping in tomato. As a proof of concept, we sequenced 81 DNA fragments distributed on chromosome 2 at different distances in a core collection of 90 tomato accessions, including mostly cherry type tomato accessions. The 81 Sequence Tag Sites revealed 352 SNPs and indels. Molecular diversity was greatest for S. pimpinellifolium accessions, intermediate for S. l. cerasiforme accessions, and lowest for the cultivated group. We assessed the structure of molecular polymorphism and the extent of linkage disequilibrium over genetic and physical distances. Linkage disequilibrium decreased under r2 = 0.3 within 1 cM, and minimal estimated value (r2 = 0.13) was reached within 20 kb over the physical regions studied. Associations between polymorphisms and fruit weight, locule number, and soluble solid content were detected. Several candidate genes and quantitative trait loci previously identified were validated and new associations detected. This study shows the advantages of using a collection of S. l. cerasiforme accessions to overcome the low resolution of association mapping in tomato.

Development of two major resources for pea genomics: the GenoPea 13.2K SNP Array and a high‐density, high‐resolution consensus genetic map

Single nucleotide polymorphism (SNP) arrays represent important genotyping tools for innovative strategies in both basic research and applied breeding. Pea is an important food, feed and sustainable crop with a large (about 4.45 Gbp) but not yet available genome sequence. In the present study, 12 pea recombinant inbred line populations were genotyped using the newly developed GenoPea 13.2K SNP Array. Individual and consensus genetic maps were built providing insights into the structure and organization of the pea genome. Largely collinear genetic maps of 3918-8503 SNPs were obtained from all mapping populations, and only two of these exhibited putative chromosomal rearrangement signatures. Similar distortion patterns in different populations were noted. A total of 12 802 transcript-derived SNP markers placed on a 15 079-marker high-density, high-resolution consensus map allowed the identification of ohnologue-rich regions within the pea genome and the localization of local duplicates. Dense syntenic networks with sequenced legume genomes were further established, paving the way for the identification of the molecular bases of important agronomic traits segregating in the mapping populations. The information gained on the structure and organization of the genome from this research will undoubtedly contribute to the understanding of the evolution of the pea genome and to its assembly. The GenoPea 13.2K SNP Array and individual and consensus genetic maps are valuable genomic tools for plant scientists to strengthen pea as a model for genetics and physiology and enhance breeding.

Transcriptomic analysis of the interaction between Helianthus annuus and its obligate parasite Plasmopara halstedii shows single nucleotide polymorphisms in CRN sequences

BackgroundDowny mildew in sunflowers (Helianthus annuus L.) is caused by the oomycete Plasmopara halstedii (Farl.) Berlese et de Toni. Despite efforts by the international community to breed mildew-resistant varieties, downy mildew remains a major threat to the sunflower crop. Very few genomic, genetic and molecular resources are currently available to study this pathogen. Using a 454 sequencing method, expressed sequence tags (EST) during the interaction between H. annuus and P. halstedii have been generated and a search was performed for sites in putative effectors to show polymorphisms between the different races of P. halstedii.ResultsA 454 pyrosequencing run of two infected sunflower samples (inbred lines XRQ and PSC8 infected with race 710 of P. halstedii, which exhibit incompatible and compatible interactions, respectively) generated 113,720 and 172,107 useable reads. From these reads, 44,948 contigs and singletons have been produced. A bioinformatic portal, HP, was specifically created for in-depth analysis of these clusters. Using in silico filtering, 405 clusters were defined as being specific to oomycetes, and 172 were defined as non-specific oomycete clusters. A subset of these two categories was checked using PCR amplification, and 86% of the tested clusters were validated. Twenty putative RXLR and CRN effectors were detected using PSI-BLAST. Using corresponding sequences from four races (100, 304, 703 and 710), 22 SNPs were detected, providing new information on pathogen polymorphisms.ConclusionsThis study identified a large number of genes that are expressed during H. annuus/P. halstedii compatible or incompatible interactions. It also reveals, for the first time, that an infection mechanism exists in P. halstedii similar to that in other oomycetes associated with the presence of putative RXLR and CRN effectors. SNPs discovered in CRN effector sequences were used to determine the genetic distances between the four races of P. halstedii. This work therefore provides valuable tools for further discoveries regarding the H. annuus/P. halstedii pathosystem.

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.

Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy

Pea is an important food and feed crop and a valuable component of low-input farming systems. Improving resistance to biotic and abiotic stresses is a major breeding target to enhance yield potential and regularity. Genomic selection (GS) has lately emerged as a promising technique to increase the accuracy and gain of marker-based selection. It uses genome-wide molecular marker data to predict the breeding values of candidate lines to selection. A collection of 339 genetic resource accessions (CRB339) was subjected to high-density genotyping using the GenoPea 13.2K SNP Array. Genomic prediction accuracy was evaluated for thousand seed weight (TSW), the number of seeds per plant (NSeed), and the date of flowering (BegFlo). Mean cross-environment prediction accuracies reached 0.83 for TSW, 0.68 for NSeed, and 0.65 for BegFlo. For each trait, the statistical method, the marker density, and/or the training population size and composition used for prediction were varied to investigate their effects on prediction accuracy: the effect was large for the size and composition of the training population but limited for the statistical method and marker density. Maximizing the relatedness between individuals in the training and test sets, through the CDmean-based method, significantly improved prediction accuracies. A cross-population cross-validation experiment was further conducted using the CRB339 collection as a training population set and nine recombinant inbred lines populations as test set. Prediction quality was high with mean Q2 of 0.44 for TSW and 0.59 for BegFlo. Results are discussed in the light of current efforts to develop GS strategies in pea.