Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis.

Background: Meta-analysis of QTLs combines the results of several QTL detection studies and provides narrow confidence intervals for meta-QTLs, permitting easier positional candidate gene identification. It is usually applied to multiple mapping populations, but can be applied to one. Here, a meta-analysis of drought related QTLs in the Bala x Azucena mapping population compiles data from 13 experiments and 25 independent screens providing 1,650 individual QTLs separated into 5 trait categories; drought avoidance, plant height, plant biomass, leaf morphology and root traits.

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

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.