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Molecular Plant Breeding 2010, Vol.1 No.5
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Research Article Open Access
Association mapping of six agronomic traits on chromosome 4A of wheat
(Triticum aestivum L.)
Lihua Liu
1,2
, Lixin Wang
1
, Ji Yao
2
, Yonglian Zheng
2
, Changping Zhao
1
1 Beijing Engineering and Technique Research Center of Hybrid Wheat, Beijing Academy of Agricultural and Forestry Sciences, Beijing, 100097
2 National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070
3 5 &KLQD
Corresponding author email:
cp_zhao@vip.sohu.com; zhyl@mail.hzau.edu.cn;
Authors
Molecular Plant Breeding 2010, Vol 1 No 5 DOI: 10.5376/mpb.2010.01.0005
Received: Jul., 26, 2010
Accepted: Oct., 20, 2010
Published: Oct., 30, 2010
This is an Open Access article distributed under the terms of th
which permits unrestricted use, distribution, and
reproduction in anymedium, provided the original work is properly cited.
Preferred citation for this article:
Liu et al 2010, Association mapping of six agronomic traits on chromosome 4A of wheat (Triticum aestivum L.), Molecular Plant Breeding Vol 1 No 5 (doi:
10.5376/mpb.2010.01.0005)
Abstract
Association mapping is a powerful approach to identify associations between traits of interest and genetic markers. In this
study, 103 wheat germplasm accessions from China were genotyped using 76 SSR markers and 40 EST-SSR markers. The
phenotyping of plant height, spike length, spikelets per spike, spikelets density, grains per spike and thousand-kernel weight were
carried out in three locations for three years. Six subpopulations were identified among these accessions by population structure
analysis based on 49 SSR and 40 EST-SSR markers. Linkage disequilibrium (LD) on chromosome 4A extended up to ~3 cM with
r
2
=0.054. Based on the mixed linear model considering population structure and relative kinship, a total of 10 SSR markers (
p
<0.01)
on chromosome 4A were significantly associated with six agronomic traits, and six of them were associated with multiple traits.
Some of the associated markers were in agreement with previous quantitative trait loci (QTL) analysis. This study demonstrated that
association mapping can be successfully applied in wheat breeding context for detection of marker-traits associations. Furthermore,
association mapping can enhance previous QTL information and provide additional QTL information for marker-assisted selection.
Keywords
Association mapping; Population structure; Linkage disequilibrium; Mixed linear model
Background
For molecular breeders the goal of plant genetics
research is to identify genes or genomic regions that
are responsible for the phenotypes (Weigel and
Nordborg, 2005), and most traits of agricultural or
evolutionary importance are controlled by multiple
quantitative trait loci (QTLs). In the past several
decades, QTLs studies in wheat and many other crop
species were mainly carried out by linkage analysis in
F
2
-, DH (double haploid)- or RIL (recombinant inbred
lines)- derived mapping populations based on genetic
recombination. However, with the development of
molecular biology and biometrics, association
mapping as a new and powerful tool has been
demonstrated that it could complement and enhance
previous QTL information identified by linkage
analyses for marker-assisted selection in wheat
(
Breseghello
and Sorrells, 2006). Association
mapping is a method to detect correlations between
genotypes and phenotypes in a collection of
germplasm based on linkage disequilibrium (LD). A
major advantage of this approach over classical
linkage analysis in breeding germplasm is that it does
not require the time-consuming and expensive
generation
of
specific
genetic
populations
(Flint-Garcia et al. 2005). Furthermore, this approach
can detect larger number of alleles and increase
mapping resolution (Yu and Buckler 2006).
Association mapping has been first successfully used
for genetic studies on some complex human diseases,
and it has also been used successfully in various plant
species to identify markers associated with a variety of
phenotypes in recent years. Significant associations
have been identified between SNPs (single nucleotide
polymorphisms), RFLP (restriction fragment length
polymorphism), AFLP (amplified fragment length
polymorphism), SSR (single sequence repeat) markers
and varied agronomical or morphological traits in
maize (Thornsberry et al. 2001;
Beló
et al. 2008;
Harjes et al. 2008), rice (
Agrama
et al., 2007; Wen et