No abstract

Although commonplace in human disease genetics, genome-wide association (GWA) studies have only relatively recently been applied to plants. Using 32 phenotypes in the inbreeding crop barley, we report GWA mapping of 15 morphological traits across ∼500 cultivars genotyped with 1,536 SNPs. In contrast to the majority of human GWA studies, we observe high levels of linkage disequilibrium within and between chromosomes. Despite this, GWA analysis readily detected common alleles of high penetrance. To investigate the potential of combining GWA mapping with comparative analysis to resolve traits to candidate polymorphism level in unsequenced genomes, we fine-mapped a selected phenotype (anthocyanin pigmentation) within a 140-kb interval containing three genes. Of these, resequencing the putative anthocyanin pathway gene HvbHLH1 identified a deletion resulting in a premature stop codon upstream of the basic helix-loop-helix domain, which was diagnostic for lack of anthocyanin in our association and biparental mapping populations. The methodology described here is transferable to species with limited genomic resources, providing a paradigm for reducing the threshold of map-based cloning in unsequenced crops.genetic variation | small grain cereals | colinearity

SummaryTranscript abundance from cRNA hybridizations to Affymetrix microarrays can be used for simultaneous marker development and genome-wide gene expression quantitative trait locus (eQTL) analysis of crops. We have previously shown that it is easily possible to use Affymetrix expression arrays to profile individuals from a segregating population to accurately identify robust polymorphic molecular genetic markers. We applied the method to identify more than 2000 genetic polymorphisms (transcript derived markers, TDMs) from an experiment involving two commercial varieties of barley (Hordeum vulgare; Steptoe and Morex) and their doubled-haploid progeny. With this set of TDMs, we constructed a genetic map and used it for the genomewide eQTL analysis of about 16 000 genes in a relatively large population (n = 139). We identified 23 738 significant eQTLs at a genome-wide significance (P £ 0.05), affecting the expression of 12 987 genes. Over a third of these genes with expression variation have only one identified eQTL while the rest have two to six. A large proportion of the quantitatively controlled transcripts appear to be regulated by both cis and trans effects. More than half of the quantitatively controlled transcripts appear to be primarily regulated by cis eQTLs in this population. We show that although there appear to be eQTL hotspots many of these are in chromosomal regions of low recombination, such as genetic centromeres, and so have a high gene density per centimorgan. Some chromosomal regions have a significant excess of eQTL over the number expected from gene density, and many of these are biased towards eQTL for which the allele from one particular parent increases the expression level.

The recent development of Affymetrix chips designed from assembled EST sequences has spawned considerable interest in identifying single-feature polymorphisms (SFPs) from transcriptome data. SFPs are valuable genetic markers that potentially offer a physical link to the structural genes themselves. However, most current SFP prediction methodologies were developed for sequenced species although SFPs are particularly valuable for species with complex and unsequenced genomes. To establish the sensitivity and specificity of prediction, we explored four methods for identifying SFPs from experiments involving two tissues in two commercial barleys and their doubled-haploid progeny. The methods were compared in terms of numbers of SFPs predicted and their ability to identify known sequence polymorphisms in the features, to confirm existing SNP genotypes and to match existing maps and individual haplotypes. We identified .4000 separate SFPs that accurately predicted the SNP genotype of .98% of the doubled-haploid (DH) lines. They were highly enriched for features containing sequence polymorphisms but all methods uniformly identified a majority of SFPs ($64%) in features for which there was no sequence polymorphism while 5% mapped to different locations, indicating that ''SFPs'' mainly represent polymorphism in cis-acting regulators. All methods are efficient and robust at predicting markers for gene mapping.