Biology subjects

Ha, N.-T.

Publications and source records attributed to Ha, N.-T..

3 recordsLinked to original sources

bioRxiv2020

Ghat: An R package for identifying adaptive polygenic traits

Identifying selection on polygenic complex traits in crops and livestock is important for understanding evolution and helps prioritize important characteristics for breeding. The QTL that contribute to polygenic trait variation often exhibit small or infinitesimal effects. This hinders the ability to detect QTL controlling polygenic traits because enormously high statistical power is needed for their detection. Recently, we circumvented this challenge by introducing a method to identify selection on complex traits by evaluating the relationship between genome-wide changes in allele frequency and estimates of effect-size. The approach involves calculating a composite-statistic across all markers that captures this relationship, followed by implementing a linkage disequilibrium-aware permutation test to evaluate if the observed pattern differs from that expected due to drift during evolution and population stratification. In this manuscript, we describe "Ghat", an R package developed to implement this method to test for selection on polygenic traits. We demonstrate the package by applying it to test for polygenic selection on 15 published European wheat traits including yield, biomass, quality, morphological characteristics, and disease resistance traits. Moreover, we applied Ghat to different simulated populations with different breeding history and genetic architecture. The results highlight the power of Ghat to identify selection on complex traits. The Ghat package is accessible on CRAN, the Comprehensive R Archival Network, and on GitHub.

genomics↗

bioRxiv2020

Multiple loci linked to inversions are associated with eye size variation in species of the Drosophila virilis phylad

The size and shape of organs is tightly controlled to achieve optimal function. Natural morphological variations often represent functional adaptations to an ever-changing environment. For instance, variation in head morphology is pervasive in insects and the underlying molecular basis is starting to be revealed in the Drosophila genus for species of the melanogaster group. However, it remains unclear whether similar diversifications are governed by similar or different molecular mechanisms over longer timescales. To address this issue, we used species of the virilis phylad because they have been diverging from D. melanogaster for at least 40 million years. Our comprehensive morphological survey revealed remarkable differences in eye size and head shape among these species with D. novamexicana having the smallest eyes and southern D. americana populations having the largest eyes. We show that the genetic architecture underlying eye size variation is complex with multiple associated genetic variants located on most chromosomes. Our genome wide association study (GWAS) strongly suggests that some of the putative causative variants are associated with the presence of inversions. Indeed, northern populations of D. americana share derived inversions with D. novamexicana and they show smaller eyes compared to southern ones. Intriguingly, we observed a significant enrichment of genes involved in eye development on the 4th chromosome after intersecting chromosomal regions associated with phenotypic differences with those showing high differentiation among D. americana populations. We propose that variants associated with chromosomal inversions contribute to both intra- and inter-specific variation in eye size among species of the virilis phylad.

evolutionary biology↗

bioRxiv2017

A simple test identifies selection on complex traits in breeding and experimentally-evolved populations

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome wide association studies and selection mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique utilizes additive effects estimates from all available markers, and relates these estimates to allele frequency change over time. Using this information, we generate a composite statistic, denoted[G] , which can be used to test for significant evidence of selection on a trait. Our test requires pre- and post-selection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that[G] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.

evolutionary biology↗