Efficient QTL detection for nonhost resistance in wild lettuce: backcross inbred lines versus F(2) population

In plants, several population types [F(2), recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as succ...

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Published inTheoretical and applied genetics Vol. 116; no. 6; pp. 845 - 857
Main Authors Jeuken, M J W, Pelgrom, K, Stam, P, Lindhout, P
Format Journal Article
LanguageEnglish
Published Germany 01.04.2008
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Summary:In plants, several population types [F(2), recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as successful as that predicted from theoretical calculations. More practical knowledge of different QTL mapping approaches is needed. In this recent study, we describe the detection and mapping of quantitative resistances to downy mildew in a set of 29 BILs of cultivated lettuce (L. sativa) containing genome segments introgressed from wild lettuce (L. saligna). Introgression regions that are associated with quantitative resistance are considered to harbor a QTL. Furthermore, we compare this with results from an already existing F(2) population derived from the same parents. We identified six QTLs in our BIL approach compared to only three in the F(2) approach, while there were two QTLs in common. We performed a simulation study based on our actual data to help us interpret them. This revealed that two newly detected QTLs in the BILs had gone unnoticed in the F(2), due to a combination of recessiveness of the trait and skewed segregation, causing a deficit of the wild species alleles. This study clearly illustrates the added value of extended genetic studies on two different population types (BILs and F(2)) to dissect complex genetic traits.
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ISSN:0040-5752
DOI:10.1007/s00122-008-0718-2