TY - JOUR
T1 - Expression quantitative trait loci analysis in plants
AU - Druka, Arnis
AU - Potokina, Elena
AU - Luo, Zewei
AU - Jiang, Ning
AU - Chen, Xinwei
AU - Kearsey, Mike
AU - Waugh, Robbie
PY - 2010/1
Y1 - 2010/1
N2 - An expression Quantitative Trait Locus or eQTL is a chromosomal region that accounts for a proportion of the variation in abundance of a mRNA transcript observed between individuals in a genetic mapping population. A single gene can have one or multiple eQTLs. Large scale mRNA profiling technologies advanced genome-wide eQTL mapping in a diverse range of organisms allowing thousands of eQTLs to be detected in a single experiment. When combined with classical or trait QTLs, correlation analyses can directly suggest candidates for genes underlying these traits. Furthermore, eQTL mapping data enables genetic regulatory networks to be modelled and potentially provide a better understanding of the underlying phenotypic variation. The mRNA profiling data sets can also be used to infer the chromosomal positions of thousands of genes, an outcome that is particularly valuable for species with unsequenced genomes where the chromosomal location of the majority of genes remains unknown. In this review we focus on eQTL studies in plants, addressing conceptual and technical aspects that include experimental design, genetic polymorphism prediction and candidate gene identification.
AB - An expression Quantitative Trait Locus or eQTL is a chromosomal region that accounts for a proportion of the variation in abundance of a mRNA transcript observed between individuals in a genetic mapping population. A single gene can have one or multiple eQTLs. Large scale mRNA profiling technologies advanced genome-wide eQTL mapping in a diverse range of organisms allowing thousands of eQTLs to be detected in a single experiment. When combined with classical or trait QTLs, correlation analyses can directly suggest candidates for genes underlying these traits. Furthermore, eQTL mapping data enables genetic regulatory networks to be modelled and potentially provide a better understanding of the underlying phenotypic variation. The mRNA profiling data sets can also be used to infer the chromosomal positions of thousands of genes, an outcome that is particularly valuable for species with unsequenced genomes where the chromosomal location of the majority of genes remains unknown. In this review we focus on eQTL studies in plants, addressing conceptual and technical aspects that include experimental design, genetic polymorphism prediction and candidate gene identification.
KW - Expression quantitative trait loci
KW - Genetical genomics
KW - Transcript-derived markers
KW - Transcript-level variation
UR - http://www.scopus.com/inward/record.url?scp=71949112678&partnerID=8YFLogxK
U2 - 10.1111/j.1467-7652.2009.00460.x
DO - 10.1111/j.1467-7652.2009.00460.x
M3 - Article
C2 - 20055957
AN - SCOPUS:71949112678
VL - 8
SP - 10
EP - 27
JO - Plant Biotechnology Journal
JF - Plant Biotechnology Journal
SN - 1467-7644
IS - 1
ER -