A dissection model for mapping complex traits

Mengmeng Sang, Hexin Shi, Kun Wei, Meixia Ye, Libo Jiang, Lidan Sun, Rongling Wu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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 QTLs for its component traits or jointly by different sets of QTLs 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 QTLs 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.

Original languageEnglish (US)
Pages (from-to)1168-1182
Number of pages15
JournalPlant Journal
Volume97
Issue number6
DOIs
StatePublished - Mar 2019

All Science Journal Classification (ASJC) codes

  • Genetics
  • Plant Science
  • Cell Biology

Fingerprint

Dive into the research topics of 'A dissection model for mapping complex traits'. Together they form a unique fingerprint.

Cite this