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A dissection model for mapping complex traits
Author(s) -
Sang Mengmeng,
Shi Hexin,
Wei Kun,
Ye Meixia,
Jiang Libo,
Sun Lidan,
Wu Rongling
Publication year - 2019
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.14185
Subject(s) - quantitative trait locus , biology , trait , evolutionary biology , genetics , gene , computer science , programming language
Summary Many quantitative traits are composites of other traits that contribute differentially to genetic variation. Quantitative trait locus ( QTL) mapping of these composite traits can benefit by incorporating the mechanistic process of how their formation is mediated by the underlying components. We propose a dissection model by which to map these interconnected components traits under a joint likelihood setting. The model can test how a composite trait is determined by pleiotropic QTL s for its component traits or jointly by different sets of QTL s each responsible for a different component. The model can visualize the pattern of time‐varying genetic effects for individual components and their impacts on composite traits. The dissection model was used to map two composite traits, stemwood volume growth decomposed into its stem height, stem diameter and stem form components for Euramerican poplar adult trees, and total lateral root length constituted by its average lateral root length and lateral root number components for Euphrates poplar seedlings. We found the pattern of how QTL s for different components contribute to phenotypic variation in composite traits. The detailed understanding of the genetic machineries of composite traits will not only help in the design of molecular breeding in plants and animals, but also shed light on the evolutionary processes of quantitative traits under natural selection.