Combining genetical genomics and bulked segregant analysis-based differential expression: an approach to gene localization.

Positional gene isolation in unsequenced species generally requires either a reference genome sequence or an inference of gene content based on conservation of synteny with a genomic model. In the large unsequenced genomes of the Triticeae cereals the latter, i.e. conservation of synteny with the rice and Brachypodium genomes, provides a powerful proxy for establishing local gene content and order. However, efficient exploitation of conservation of synteny requires 'homology bridges' between the model genome and the target region that contains a gene of interest. As effective homology bridges are generally the sequences of genetically mapped genes, increasing the density of these genes around a target locus is an important step in the process. We used bulked segregant analysis (BSA) of transcript abundance data to identify genes located in a specific region of the barley genome. The approach is valuable because only a relatively small proportion of barley genes are currently placed on a genetic map. We analyzed eQTL datasets from the reference Steptoe × Morex doubled haploid population and showed a strong association between differential gene expression and cis-regulation, with 83% of differentially expressed genes co-locating with their eQTL. We then performed BSA by assembling allele-specific pools based on the genotypes of individuals at the partial resistance QTL Rphq11. BSA identified a total of 411 genes as differentially expressed, including HvPHGPx, a gene previously identified as a promising candidate for Rphq11. The genetic location of 276 of these genes could be determined from both eQTL datasets and conservation of synteny, and 254 (92%) of these were located on the target chromosome. We conclude that the identification of differential expression by BSA constitutes a novel method to identify genes located in specific regions of interest. The datasets obtained from such studies provide a robust set of candidate genes for the analysis and serve as valuable resources for targeted marker development and comparative mapping with other grass species.