Identification, deployment, and transferability of quantitative trait loci from genome-wide association studies in plants
2020
Mohsen Mohammadi | Alencar Xavier | Travis Beckett | Savannah Beyer | Liyang Chen | Habte Chikssa | Valerie Cross | Fabiana Freitas Moreira | Elizabeth French | Rupesh Gaire | Stefanie Griebel | Miguel Angel Lopez | Samuel Prather | Blake Russell | Weidong Wang
Over the past decade, the use of genome-wide association studies (GWAS) in plant breeding for discovery and validation of quantitative trait loci (QTL) has vastly increased. Successful deployment and transferability of these findings, however, have been limited. To increase the value of GWAS for plant breeding, experimental and methodological aspects must be addressed and refined. Population designs and statistical techniques are necessary to properly account for the effect of long-range linkage disequilibrium. Success of current methods has been restricted to the detection of common-variants with moderate additive effects; discovery of rare variants or QTL that depart from additivity has been elusive. Pleiotropy casts doubt on the cause-effect relationships between markers and multiple traits. Major criticisms of association studies center on reproducibility of results and the lack of transferability to other environments and populations. We also discuss population structure, phenotypic plasticity, epistasis, and genotype-by-environment interactions as they apply to GWAS. Perspectives are given for environment-dependent QTL, experimental settings, use of next-generation populations, and deployment of GWAS results for breeding applications and strategic exploitation of genotype-by-environment interactions. In summary, we present an overview of contemporary issues in identification and deployment of marker-trait associations and suggest future avenues of research towards new methods and new sources of data.
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