Modeling QTL for complex traits: detection and context for plant breeding

Cooper, Mark, van Eeuwijk, Fred A., Hammer, Graeme L., Podlich, Dean W. and Messina, Carlos (2009) Modeling QTL for complex traits: detection and context for plant breeding. Current Opinion In Plant Biology, 12 2: 231-240. doi:10.1016/j.pbi.2009.01.006


Author Cooper, Mark
van Eeuwijk, Fred A.
Hammer, Graeme L.
Podlich, Dean W.
Messina, Carlos
Title Modeling QTL for complex traits: detection and context for plant breeding
Journal name Current Opinion In Plant Biology   Check publisher's open access policy
ISSN 1369-5266
1879-0356
Publication date 2009-04
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1016/j.pbi.2009.01.006
Volume 12
Issue 2
Start page 231
End page 240
Total pages 10
Place of publication London, United Kingdom
Publisher Elsevier
Language eng
Abstract The genetic architecture of a trait is defined by the set of genes contributing to genetic variation within a reference population of genotypes together with information on their location in the genome and the effects of their alleles on traits, including intra-locus and inter-locus interactions, environmental dependencies, and pleiotropy. Accumulated evidence from trait mapping studies emphasizes that plant breeders work within a trait genetic complexity continuum. Some traits show a relatively simple genetic architecture while others, such as grain yield, have a complex architecture. An important advance is that we now have empirical genetic models of trait genetic architecture obtained from mapping studies (multi-QTL models including various genetic effects that may vary in relation to environmental factors) to ground theoretical investigations on the merits of alternative breeding strategies. Such theoretical studies indicate that as the genetic complexity of traits increases the opportunities for realizing benefits from molecular enhanced breeding strategies increase. To realize these potential benefits and enable the plant breeder to increase rate of genetic gain for complex traits it is anticipated that the empirical genetic models of trait genetic architecture used for predicting trait variation will need to incorporate the effects of genetic interactions and be interpreted within a genotype–environment–management framework for the target agricultural production system.
Keyword Root architectural traits
Gene regulatory networks
Mixed-model
Water-deficit
Leaf growth
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collection: School of Agriculture and Food Sciences
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 53 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 68 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Mon, 07 Mar 2011, 15:30:33 EST