Small ruminants are the critical source of livelihood for rural people to the development of sustainable and environmentally sound production systems. They provided a source of meat, milk, skin, and fiber. The several contributions of small ruminants to the economy of millions of rural people are however being challenged by extreme heat stress difficulties. Heat stress is one of the most detrimental factors contributing to reduced growth, production, reproduction performance, milk quantity and quality, as well as natural immunity, making animals more vulnerable to diseases and even death. However, small ruminants have successfully adapted to this extreme environment and possess some unique adaptive traits due to behavioral, morphological, physiological, and largely genetic bases. This review paper, therefore, aims to provide an integrative explanation of small ruminant adaptation to heat stress and address some responsible candidate genes in adapting to thermal-stressed environments.

Detection of selection footprints provides insight into the evolution process and the underlying mechanisms controlling the phenotypic diversity of traits that have been exposed to selection. Selection focused on certain characters, mapping certain genomic regions often shows a loss of genetic diversity with an increased level of homozygosity. Therefore, the runs of homozygosity (ROHs), homozygosity by descent (HBD), and effective population size (Ne) are effective tools for exploring the genetic diversity, understanding the demographic history, foretelling the signature of directional selection, and improving the breeding strategies to use and conserve genetic resources. We characterized the ROH, HBD, Ne, and signature of selection of six Chinese goat populations using single nucleotide polymorphism (SNP) 50K Illumina beadchips. Our results show an inverse relationship between the length and frequency of ROH. A long ROH length, higher level of inbreeding, long HBD segment, and smaller Ne in Guangfeng (GF) goats suggested intensive selection pressure and recent inbreeding in this breed. We identified six reproduction-related genes within the genomic regions with a high ROH frequency, of which two genes overlapped with a putative selection signature. The estimated pair-wise genetic differentiation (FST) among the populations is 9.60% and the inter- and intra-population molecular variations are 9.68% and 89.6%, respectively, indicating low to moderate genetic differentiation. Our selection signatures analysis revealed 54 loci harboring 86 putative candidate genes, with a strong signature of selection. Further analysis showed that several candidate genes, including MARF1, SYCP2, TMEM200C, SF1, ADCY1, and BMP5, are involved in goat fecundity. We identified 11 candidate genes by using cross-population extended haplotype homozygosity (XP-EHH) estimates, of which MARF1 and SF1 are under strong positive selection, as they are differentiated in high and low reproduction groups according to the three approaches used. Gene ontology enrichment analysis revealed that different biological pathways could be involved in the variation of fecundity in female goats. This study provides a new insight into the ROHs patterns for maintenance of within breed diversity and suggests a role of positive selection for genetic variation influencing fecundity in Chinese goat.

Simple Summary: Sheep is one of the most economically important animals used as a source of meat, milk, wool, and fur for human society. These commodities are essential for human being. Body growth, body weight, carcass quality, fat percent, fertility, milk yield, wool, horn type and coat color are essential and useful sheep traits. Understanding the genetic background of these traits is paramount to increase the production and productivity of domestic animals. The availability of genomic data, development of molecular breeding techniques, and genome technologies have come to play a vital role in understanding the genetic background of different animal traits. This is directly or indirectly helpful for the practice of genetic improvement of economically important traits in sheep. The identification of genomic regions, genes associated with phenotypic traits, and description of gene function are some of the applied research activities to understand the genetics of livestock species. The aim of this review is to discuss and summarize different reported research findings on identified genomic regions and candidate genes related with economically important traits as well as gene annotation in sheep.Abstract: Sheep (Ovis aries) is one of the most economically, culturally, and socially important domestic animals. They are reared primarily for meat, milk, wool, and fur production. Sheep were reared using natural selection for a long period of time to offer these traits. In fact, this production system has been slowing the productivity and production potential of the sheep. To improve production efficiency and productivity of this animal through genetic improvement technologies, understanding the genetic background of traits such as body growth, weight, carcass quality, fat percent, fertility, milk yield, wool quality, horn type, and coat color is essential. With the development and utilization of animal genotyping technologies and gene identification methods, many functional genes and genetic variants associated with economically important phenotypic traits have been identified and annotated. This is useful and presented an opportunity to increase the pace of animal genetic gain. Quantitative trait loci and genome wide association study have been playing an important role in identifying candidate genes and animal characterization. This review provides comprehensive information on the identified genomic regions and candidate genes associated with production and reproduction traits, and gene function in sheep.

SummaryInformation about genetic diversity and population structure among goat breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of goat breeds. Here, we measured genetic diversity and population structure in multiple Chinese goat populations, namely, Nanjiang, Qinggeda, Arbas Cashmere, Jining Grey, Luoping Yellow and Guangfeng goats. A total of 193 individuals were genotyped for about 47 401 autosomal single nucleotide polymorphisms (SNPs). We found a high proportion of informative SNPs, ranging from 69.5% in the Luoping Yellow to 93.9% in the Jining Grey goat breeds with an average mean of 84.7%. Diversity, as measured by expected heterozygosity, ranged from 0.371 in Luoping Yellow to 0.405 in Jining Grey goat populations. The average estimated pair‐wise genetic differentiation (FST) among the populations was 8.6%, ranging from 0.2% to 16% and indicating low to moderate genetic differentiation. Principal component analysis, genetic structure and phylogenetic tree analysis revealed a clustering of six Chinese goat populations according to geographic distribution. The results from this study can contribute valuable genetic information and can properly assist with within‐breed diversity, which provides a good opportunity for sustainable utilization of and maintenance of genetic resource improvements in the 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.