A model framework for identifying genes that guide the evolution of heterochrony

Lidan Sun, Meixia Ye, Han Hao, Ningtao Wang, Yaqun Wang, Tangren Cheng, Qixiang Zhang, Rongling Wu

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Heterochrony, the phylogenic change in the time of developmental events or rate of development, has been thought to play an important role in producing phenotypic novelty during evolution. Increasing evidence suggests that specific genes are implicated in heterochrony, guiding the process of developmental divergence, but no quantitative models have been instrumented to map such heterochrony genes. Here, we present a computational framework for genetic mapping by which to characterize and locate quantitative trait loci (QTLs) that govern heterochrony described by four parameters, the timing of the inflection point, the timing of maximum acceleration of growth, the timing of maximum deceleration of growth, and the length of linear growth. The framework was developed from functional mapping, a dynamic model derived to map QTLs for the overall process and pattern of development. By integrating an optimality algorithm, the framework allows the so-called heterochrony QTLs (hQTLs) to be tested and quantified. Specific pipelines are given for testing how hQTLs control the onset and offset of developmental events, the rate of development, and duration of a particular developmental stage. Computer simulation was performed to examine the statistical properties of the model and demonstrate its utility to characterize the effect of hQTLs on population diversification due to heterochrony. By analyzing a genetic mapping data in rice, the framework identified an hQTL that controls the timing of maximum growth rate and duration of linear growth stage in plant height growth. The framework provides a tool to study how genetic variation translates into phenotypic innovation, leading a lineage to evolve, through heterochrony.

Original languageEnglish (US)
Pages (from-to)2238-2247
Number of pages10
JournalMolecular biology and evolution
Volume31
Issue number8
DOIs
StatePublished - Aug 2014

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics

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