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ARS Home » Southeast Area » Mississippi State, Mississippi » Crop Science Research Laboratory » Genetics and Sustainable Agriculture Research » Research » Publications at this Location » Publication #174441

Title: MIXED MODEL BASED CONDITIONAL ANALYSIS FOR COMPLEX TRAITS

Author
item WU, JIXIANG
item Jenkins, Johnie
item McCarty, Jack

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/4/2005
Publication Date: 6/1/2005
Citation: Wu, J., Jenkins, J.N., McCarty Jr., J.C. 2005. Mixed model based conditional analysis for complex traits [abstract]. National Cotton Council Beltwide Cotton Conference. p. 1010.

Interpretive Summary:

Technical Abstract: Many cotton complex traits like yield and plant height are determined by several component traits. Usually these traits are measured under a specific experimental design (i.e. RCB design) and a specific genetic model (additive and dominance model). We used the conditional model in conjunction with mixed linear model approaches which is helpful to plant breeders in dissecting the relationships between a complex trait and its component traits. In this presentation, we extended the use of mixed model based conditional analysis to more general cases such as genotype by environment (G×E) interaction models, additive-dominance (AD) models, and additive-dominance and additive × additive (ADAA) models, etc. The software package for this analysis has been developed and is available for use. We will demonstrate the use of the software package in this presentation.