From association to prediction: statistical methods for the dissection and selection of complex traits in plants.

Abstract:

:Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic interactions. Selecting optimal models enables accurate evaluation of associations between marker loci and numerous phenotypes including gene expression. Significant improvements in QTL discovery via association mapping and acceleration of breeding cycles through genomic selection are two successful applications of models using genome-wide markers. Given recent advances in genotyping and phenotyping technologies, further refinement of these approaches is needed to model genetic architecture more accurately and run analyses in a computationally efficient manner, all while accounting for false positives and maximizing statistical power.

journal_name

Curr Opin Plant Biol

authors

Lipka AE,Kandianis CB,Hudson ME,Yu J,Drnevich J,Bradbury PJ,Gore MA

doi

10.1016/j.pbi.2015.02.010

subject

Has Abstract

pub_date

2015-04-01 00:00:00

pages

110-8

eissn

1369-5266

issn

1879-0356

pii

S1369-5266(15)00030-8

journal_volume

24

pub_type

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