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

被引:120
作者
Cooper, Mark [1 ]
van Eeuwijk, Fred A. [2 ,3 ]
Hammer, Graeme L. [4 ]
Podlich, Dean W. [1 ]
Messina, Carlos [1 ]
机构
[1] Pioneer HiBred Int Inc, Johnston, IA 50131 USA
[2] Wageningen UR, Biometris, NL-6700 AC Wageningen, Netherlands
[3] Ctr BioSyst Genom, NL-6700 AB Wageningen, Netherlands
[4] Univ Queensland, Sch Land Crop & Food Sci, APSRU, Brisbane, Qld 4072, Australia
关键词
ROOT ARCHITECTURAL TRAITS; MIXED-MODEL; GENETIC ARCHITECTURE; LEAF GROWTH; WATER-DEFICIT; LOCI; NETWORK; RESPONSES; TIME; ILLUSTRATION;
D O I
10.1016/j.pbi.2009.01.006
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
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-OTL 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.
引用
收藏
页码:231 / 240
页数:10
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