Associative expression and systems analysis of complex traits in oilseed rape / canola - ASSYST (PRR-CROPP)

Lead Research Organisation: John Innes Centre
Department Name: Crop Genetics

Abstract

A pilot experiment will evaluate the capabilities of the PBI/NRC 454-NGS platform for SNP discovery. The resulting markers, along with the public genome-wide SNPs from UGI and the public EST-SNPs from the AAFC/DLM project, will become available for the development of a public high throughput SNP genotyping platform during 2008/09. The platform we develop will subsequently be used to screen two DH mapping populations and 450 members of a genotype diversity panel, providing the data for two new high-density SNP maps and for whole-genome association analysis. Global transcriptome data will be obtained from germinated seedlings of 93 DH lines from the mapping population 'Express' x 'V8' plus the two parental genotypes and the F1. Whole-seedling transcript libraries will be sequenced using the next-generation Illumina (Solexa) Genome Analyzer. The quantitative global transcript data will be used to identify polymorphic gene expression markers (GEMs) in the mapping population, and for eQTL analysis. Developing seed will be collected from a population of 250 DH spring type B. napus lines 18 days after flowering and immediately frozen. In addition, mature seed will be collected for analysing seed quality traits. The seedlings and developing seeds will be utilised for hormone profiling and global transcriptome analysis. Alignment of metabolite QTL (mQTL), eQTL and QTLs controlling seed quality traits will identify target regions of the B. napus genome for further characterisation. Quantitative plant hormone metabolite data from all plant populations being analysed in the project will be used for comparison of mQTL with developing seed and seedling trait QTL. Detailed, quantitative hormone profiles from the developing seed and seedling tissue samples will be obtained for 36 compounds. We will adapt and apply computational biology techniques to identify relationships between the transcriptome and a range of developmental, metabolic and performance traits. This will exploit transcriptome datasets developed both prior to this project and during this project, and trait datasets which could include: Seedling biomass traits, quantitative developing seed and seedling hormone measurements, oil content and fatty acid composition, protein and fibre content, seed glucosinolate content, seed weight and seed yield along with mid-parent heterosis for all of the abovementioned traits. We will use appropriate computational platforms for the more detailed analysis of a small number of specific pathways. A B. napus association mapping population of 450 genetically diverse genotypes will be compiled by combining genetic diversity sets from previous studies. These include inbred lines from a core set of 150 rapeseed (B. napus ssp. napus) and 100 swede (B. napus ssp. pabularia) genebank accessions generated in a previous project (RESGEN) by UGI and other European partners, 54 older winter rapeseed varieties and breeding lines from a previous project in Germany (GABI-BRIDGE), 90 genetically diverse modern winter oilseed rape varieties and 180 fixed diversity founder lines. For analysis of the population structure a set of 100 genome-wide SSR markers distributed evenly over all chromosomes will be used. Seedling development of the entire association mapping population will be examined in a greenhouse experiment. The data generated in the greenhouse and field trials will be used for in depth analyses of the correlations between seedling vigour parameters, agronomic traits and seed quality characters, and for detection of marker-phenotype associations with all analysed traits. The B. napus SNP array will be used for high-throughput screening of the association mapping population. This data will be used to identify genome regions contributing to variation in the regulation of genes involved in seedling development.

Technical Summary

The PBI/NRC 454-NGS platform for SNP discovery will be evaluated and resulting markers, along with the public genome-wide SNPs from UGI and the public EST-SNPs from the AAFC/DLM project, will become available for the development of a public high throughput SNP genotyping platform. The platform will be used to provide the data for two new high-density SNP maps and for whole-genome association analysis. Global transcriptome data will be obtained from germinated seedlings of 93 DH lines from the mapping population 'Express' x 'V8' plus the two parental genotypes and the F1. Whole-seedling transcript libraries will be sequenced using the next-generation Illumina (Solexa) Genome Analyzer. The quantitative global transcript data will be used to identify polymorphic gene expression markers (GEMs) in the mapping population, and for eQTL analysis. Seedlings and developing seeds from B. napus lines will be utilised for hormone profiling and global transcriptome analysis. Alignment of metabolite QTL (mQTL), eQTL and QTLs controlling seed quality traits will identify target regions of the B. napus genome for further characterisation. We will adapt and apply computational biology techniques to identify relationships between the transcriptome and a range of developmental, metabolic and performance traits. We will use appropriate computational platforms for the more detailed analysis of a small number of specific pathways. A B. napus association mapping population of 450 genetically diverse genotypes will be compiled and phenotypic data obtained and used to identify genome regions contributing to variation in the regulation of genes involved in seedling development.
 
Description The ERANET ASSYST project has generated a large, genetically and geographically diverse collection of Brassica napus inbred lines as a public resource for genetic association studies in this important crop species. This population was subjected to extensive phenotypic analyses in multi-location field trials and growth-chamber experiments. In the first phase of the ASSYST project we also generated quantitative gene expression data from seeds and seedlings of segregating B. napus doubled-haploid populations using microarray and digital gene expression platforms and performed a comprehensive analysis of seed and seedling growth hormone profiles in these populations by HPLC-MS/MS. A subset of the ASSYST diversity set was subjected to whole-transcriptome analysis via mRNA deep sequencing.

The segregating transcriptome data is now being integrated with the quantitative metabolite, hormone and phenotype data using a systems-genetics approach that combines an analysis of gene co-expression networks with expression QTL (eQTL) approaches. Weighted gene co-expression network analysis (WGCNA) was investigated for its potential to find key regulatory genes involved in relevant pathways and traits in B. napus. Preliminary eQTL and network analysis revealed important regulatory expression networks controlling biosynthesis of important nutritional and antinutritional seed compounds. A high-density B. napus 6000-SNP array has been designed and will be used to screen the diversity collection for association analyses with seed quality, seedling developmental and other phenotype data. High-density SNP maps of the segregating populations, also generated with this SNP array, will facilitate a more precise identification of potential regulatory candidate genes underlying important cis-eQTL. The expression of genes (i) for which eQTL hotspots are observed in the linkage mapping populations, and (ii) which are identified as candidates by systems genetics approaches based on global gene expression and hormone profiles, will be examined in the genotype diversity set by quantitative real-time PCR. This data will then be used for associative expression mapping.
Exploitation Route The methods and resources developed in the project will allow others to conduct their own projects in Brassica napus and other species both in collaboration and independently.
Sectors Agriculture, Food and Drink
 
Description A total of five German oilseed rape breeding companies agreed to collaborate with MPIZ (B. Stich) and JLU (R. Snowdon) on phenotyping work with the ASSYST B. napus diversity set (at their own cost) in 2009 and 2010. In addition a number of new academic cooperation partners also obtained seed samples from the ASSYST diversity collection and the ExV8-DH mapping population, and in turn agreed to provide phenotype data from field evaluations in diverse environments. These populations are currently being grown in additional field trials in Chile (CGNA, Temuco, Dr. Federico Iniguez-Luy), Romania (University of Iasi) and China (Southwest University, Chongqing). A further cooperation is planned with the New South Wales Department of Primary Industries, Australia, who have expressed an interest in screening the ASSYST diversity collection under Australian conditions for flowering time and other traits. These additional field trials at extremely diverse locations represent a considerable broadening of the phenotypic data basis that will be available for the planned genome-wide association and network analyses. In development of the SNP resources for Brassica, Isobel Parkin (AAFC) and Andrew Sharpe (NRC-PBI) have also developed a collaboration with Federico Iniguez-Luy at CGNA, Chile. This has provided additional data for SNP discovery and a number of Chilean scientists have visited Canada for training, predominantly in bioinformatics. The computational methods developed at JIC for the allocation of transcript abundance to A and C genome homoeologues have been used in additional project, underpinning the further development of collaborations. This included the UK Oilseed Rape Genetic Improvement Network (which involves academic institutions RRes and U. Warwick as well as the UK rapeseed breeders) and a consortium funded under BBSRC's Integrated Biorefining Research and Technology Club (which involves the academic institution IFR and the rapeseed breeder KWS-UK). The approach developed at JIC of applying Associative Transcriptomics to identify the genetic basis of trait variation, using the ASSYST panel, has enabled a research consortium to be assembled in the UK that aims to address the improvement of co-products of oilseed rape crops and the nutrient use efficiency of the crop. The consortium, led by Ian Bancroft and involving Rod Snowdon on its Science Advisory Board, includes both academic members (Universities of York, Nottingham and Cologne, TGAC, IFR and RRes) and industry members (ADAS, Elsoms, Monsanto, Limagrain, Biogemma, Cargill, CaseIH and HGCA). The program has recently been funded via a BBSRC strategic Longer and Larger grant award (~GBP 4M). The computational methods developed at JIC for the allocation of transcript abundance to A and C genome homoeologues has enabled a European research consortium to be assembled that aims to understand better the mechanisms involved in genome evolution in B. napus and relate structural variation to trait variation. The consortium, led by Ian Bancroft and involving Rod Snowdon, includes academic partners in UK, Germany and France. The program has recently been funded via ERA-CAPS (~€1.4M).
Sector Agriculture, Food and Drink
Impact Types Societal,Economic