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Genomics. 2008 Nov;92(5):344-52. doi: 10.1016/j.ygeno.2008.07.002. Epub 2008 Sep 18.

A bioinformatic and transcriptomic approach to identifying positional candidate genes without fine mapping: an example using rice root-growth QTLs.

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Department of Plant and Soil Science, Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK.


Fine mapping can accurately identify positional candidate genes for quantitative trait loci (QTLs) but can be time consuming, costly, and, for small-effect QTLs with low heritability, difficult in practice. We propose an alternative approach, which uses meta-analysis of original mapping data to produce a relatively small confidence interval for target QTLs, lists the underlying positional candidates, and then eliminates them using whole-genome transcriptomics. Finally, sequencing is conducted on the remaining candidate genes allowing identification of allelic variation in either expression or protein sequence. We demonstrate the approach using root-growth QTLs on chromosomes 2, 5, and 9 of the Bala x Azucena rice mapping population. Confidence intervals of 10.5, 9.6, and 5.4 cM containing 189, 322, and 81 genes, respectively, were produced. Transcriptomics eliminated 40% of candidate genes and identified nine expression polymorphisms. Sequencing of 30 genes revealed that 57% of the predicted proteins were polymorphic. The limitations of this approach are discussed.

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