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Combining genetical genomics and bulked segregant analysis-based diverential expression: An approach to gene localization

Theoretical and Applied Genetics, ISSN: 0040-5752, Vol: 122, Issue: 7, Page: 1375-1383
2011
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Article Description

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, eYcient exploitation of conservation of synteny requires 'homology bridges' between the model genome and the target region that contains a gene of interest. As eVective 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 speciWc 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 diVerential gene expression and cis-regulation, with 83% of diVerentially expressed genes co-locating with their eQTL. We then performed BSA by assembling allele-speciWc pools based on the genotypes of individuals at the partial resistance QTL Rphq11. BSA identiWed a total of 411 genes as diVerentially expressed, including HvPHGPx, a gene previously identiWed 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 identiWcation of diVerential expression by BSA constitutes a novel method to identify genes located in speciWc 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. © The Author(s) 2011.

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