Abstract
The accurate mapping of quantitative trait loci (QTL) depends notably on the number of recombination events occurring in the segregating population. The cost of phenotyping often limits the sample size used in QTL mapping. To get round this problem, we assessed a selective phenotyping method, called qtlRec sampling. In order to improve the accuracy of QTL mapping, a subset of individuals was selected to maximize the number of recombination events at putative QTL positions; the usefulness of this subset was compared to a selected sample built to maximize the recombination rate over the whole genome. We assessed this method on the quantitative oil content trait in Brassica napus. We showed that the qtlRec strategy could allow increasing accuracy (both support interval and position) of QTL location while it maintained a similar power of detection. We then applied this approach to the B. napus—Leptosphaeria maculans pathosystem for which resistance QTL with minor effect were previously identified. This allowed the validation of the QTL in six genomic regions. The qtlRec method is an attractive strategy for validating QTL in multiple year and/or location trials for a trait which requires costly and time-consuming phenotyping.
Highlights
Many traits in plants as well as animals and humans are complex and controlled by quantitative trait loci (QTL)
We present the assessment of a new sampling strategy, referred to as qtlRec
It is based on the selection of individuals which maximize the recombinetion at targeted QTL regions in order to improve the accuracy of QTL location in comparison to a MapPop sample of the same size
Summary
Many traits in plants as well as animals and humans are complex and controlled by quantitative trait loci (QTL). The genetic analysis of these complex traits showed that most reported QTL correspond to large genomic regions covering 10 to 30 centiMorgans (cM), which usually include several hundred genes [1,2]. These large support intervals are a major limitation to the use of QTL in breeding programs through marker-assisted selection (MAS). The type and restricted size of populations (F2, doubled haploids...) commonly used to detect and map QTL in plants limit these events. One solution is to use populations with much larger numbers of individuals but it is time consuming and costly, both financially and in terms of human means, to genotype markers and/or phenotype traits and this can limit this approach
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