A Model Framework for Identifying Genes that Guide the Evolution of Heterochrony

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.

A computational framework for mapping the timing of vegetative phase change

“…By measuring phenotypic values of complex traits repeatedly during a time course, GWAS may produce an important by‐product, that is, the identification of phase change QTLs, by using our reformed functional mapping model. Specifically, these QTLs determine the timing of development from one phase to next, the length of times between developmental landmarks of different phases, and differences in relative growth rate, the time of maximum growth rate, the time of maximum acceleration, the time of maximum deceleration, and the duration of linear growth between different phases (Sun et al ., ). Genetic variants that drive phenotypic variation in phase change are integrated with recent discoveries of regulatory genes and pathways related to this phenomenon (Wu et al ., ; Wang et al ., ; Yang et al ., ), which will certainly lead to a clear understanding of how the organism changes its growth and developmental form to adapt its environment.…”

“…This growth pattern of two phases, separated by flowering, was also found for a dual‐adapted tropical rice variety grown in both flooded and aerobic environments (Clerget et al ., ). The mathematical equations allow the timing and nature of phase change to be estimated precisely, providing a quantitative assessment on how different phases contribute to end‐point growth (Sun et al ., ). Similar mathematical relevance can be true for other plants and organs, although no same pattern of vegetative juvenile–adult phases is held for all cases.…”

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

“…Sun et al . () provided a procedure to test the genetic control of these timing parameters that can be used directly to investigate how the QTL affects MCARI2. Similarly, we can make the above hypothesis tests for the other traits MTCI and NDVI.…”

A computational‐experimental framework for mapping plant coexistence

“…The advantages of systems mapping also include the quantitative investigation of how a QTL regulates the heterochrony of trait development (Sun et al., ). Heterochrony, known as the interspecific difference in the event, timing and rate of development, is thought to affect the evolution of phenotypic traits.…”