Genome-Wide Linkage Disequilibrium and the Extent of Effective Population Sizes in Six Chinese Goat Populations Using a 50K Single Nucleotide Polymorphism Panel.

Haile Berihulay,Yuehui Ma,Rabiul Islam,Lin Jiang

doi:10.3390/ani9060350

Abstract

Simple SummaryInformation on linkage disequilibrium (LD) and the extent of effective population size (Ne) has important implications for exploring the degree of biological diversity, for predicting underlying selection pressure, and for designing animal breeding programs. In this study, we assessed LD, Ne, and the distribution of minor allele frequency in six goat populations. Accordingly, the results of LD and Ne using a single nucleotide polymorphism (SNP) panel (Caprine SNP 50K BeadChip, Lincoln, NE, USA) are helpful for the sustainable conservation, proper management, and utilization of Chinese goat populations.Genome-wide linkage disequilibrium is a useful parameter to study quantitative trait locus (QTL) mapping and genetic selection. In many genomic methodologies, effective population size is an important genetic parameter because of its relationship to the loss of genetic variation, increases in inbreeding, the accumulation of mutations, and the effectiveness of selection. In this study, a total of 193 individuals were genotyped to assess the extent of LD and Ne in six Chinese goat populations using the SNP 50K BeadChip. Across the determined autosomal chromosomes, we found an average of 0.02 and 0.23 for r2 and D’ values, respectively. The average r2 between all the populations varied little and ranged from 0.055 r2 for the Jining Grey to 0.128 r2 for the Guangfeng, with an overall mean of 0.083. Across the 29 autosomal chromosomes, minor allele frequency (MAF) was highest on chromosome 1 (0.321) and lowest on chromosome 25 (0.309), with an average MAF of 0.317, and showing the lowest (25.5% for Louping) and highest (28.8% for Qingeda) SNP proportions at MAF values > 0.3. The inbreeding coefficient ranged from 0.064 to 0.085, with a mean of 0.075 for all the autosomes. The Jining Grey and Qingeda populations showed higher Ne estimates, highlighting that these animals could have been influenced by artificial selection. Furthermore, a declining recent Ne was distinguished for the Arbas Cashmere and Guangfeng populations, and their estimated values were closer to 64 and 95, respectively, 13 generations ago, which indicates that these breeds were exposed to strong selection. This study provides an insight into valuable genetic information and will open up the opportunity for further genomic selection analysis of Chinese goat populations.

Highlights

Goats (Capra hircus) are animals that are highly adaptable to diverse environmental conditions, are raised all over the world for meat, milk, skin, fibre, and manure production, and are the sole sourceAnimals 2019, 9, 350; doi:10.3390/ani9060350 www.mdpi.com/journal/animalsAnimals 2019, 9, 350 of livelihood for many rural people and landless laborers [1,2]
The commercial application of genomic selection implies that relatively large numbers of important breeding animals are genotyped using dense marker covering [3], which opens up the possibility of performing quantitative trait loci (QTL) mapping studies with greater power and precision
In most whole genome marker data sets, the causal variants are usually not included but the effects of quantitative loci are reflected by markers that are in linkage disequilibrium (LD) with the causal loci [4]

Summary

Introduction

Animals 2019, 9, 350 of livelihood for many rural people and landless laborers [1,2] They present reasonable reproductive and productive performance, it is necessary to improve their production efficiency to become more competitive with other livestock industries. In this regard, genetic selection plays a vital role and substantial genetic gain has been achieved using traditional breeding methods. The commercial application of genomic selection implies that relatively large numbers of important breeding animals are genotyped using dense marker covering [3], which opens up the possibility of performing quantitative trait loci (QTL) mapping studies with greater power and precision. LD could be the most widely important measurement of connectedness between allele pairs and haplotype block structures across a given population [7]

Objectives

Methods

Results

Discussion

Conclusion