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QTL ‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations
Author(s) -
Takagi Hiroki,
Abe Akira,
Yoshida Kentaro,
Kosugi Shunichi,
Natsume Satoshi,
Mitsuoka Chikako,
Uemura Aiko,
Utsushi Hiroe,
Tamiru Muluneh,
Takuno Shohei,
Innan Hideki,
Cano Liliana M.,
Kamoun Sophien,
Terauchi Ryohei
Publication year - 2013
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.12105
Subject(s) - quantitative trait locus , biology , genetics , population , genome , family based qtl mapping , selection (genetic algorithm) , genomics , marker assisted selection , gene , gene mapping , chromosome , demography , artificial intelligence , sociology , computer science
Summary The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTL s). Mapping and isolation of QTL s is important for efficient crop breeding by marker‐assisted selection ( MAS ) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTL s by whole‐genome resequencing of DNA s from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL ‐seq as applied to plant species. We applied QTL ‐seq to rice recombinant inbred lines and F 2 populations and successfully identified QTL s for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL ‐seq is able to detect QTL s over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.