Search

Runs of Homozygosity (ROH) are continuous homozygous DNA segments in diploid genomes, which have been used to estimate the genetic diversity, inbreeding levels, and genes associated with specific traits in livestock. In this study, we analyzed the resequencing data from 10 local goat breeds in Yunnan province of China and five additional goat populations obtained from a public database. The ROH analysis revealed 21,029 ROH segments across the 15 populations, with an average length of 1.27 Mb, a pattern of ROH, and the assessment of the inbreeding coefficient indicating genetic diversity and varying levels of inbreeding. iHS (integrated haplotype score) was used to analyze high-frequency Single-Nucleotide Polymorphisms (SNPs) in ROH regions, specific genes related to economic traits such as coat color and weight variation. These candidate genes include OCA2 (OCA2 melanosomal transmembrane protein) and MLPH (melanophilin) associated with coat color, EPHA6 (EPH receptor A6) involved in litter size, CDKAL1 (CDK5 regulatory subunit associated protein 1 like 1) and POMC (proopiomelanocortin) linked to weight variation and some putative genes associated with high-altitude adaptability and immune. This study uncovers genetic diversity and inbreeding levels within local goat breeds in Yunnan province, China. The identification of specific genes associated with economic traits and adaptability provides actionable insights for utilization and conservation efforts. [ABSTRACT FROM AUTHOR]

Simple Summary: In our research, candidate genes related to sheep-milk production were revealed by a genome-resequencing analysis and a genome-signal-selection analysis, and a RT-qPCR experiment was performed to prove the expression levels of these candidate genes, the results showed that the FCGR3A gene's expression level had a significant negative relationship with sheep-milk production. Natural selection and domestication have shaped modern sheep populations into a vast range of phenotypically diverse breeds. Among these breeds, dairy sheep have a smaller population than meat sheep and wool sheep, and less research is performed on them, but the lactation mechanism in dairy sheep is critically important for improving animal-production methods. In this study, whole-genome sequences were generated from 10 sheep breeds, including 57 high-milk-yield sheep and 44 low-milk-yield sheep, to investigate the genetic signatures of milk production in dairy sheep, and 59,864,820 valid SNPs (Single Nucleotide Polymorphisms) were kept after quality control to perform population-genetic-structure analyses, gene-detection analyses, and gene-function-validation analyses. For the population-genetic-structure analyses, we carried out PCA (Principal Component Analysis), as well as neighbor-joining tree and structure analyses to classify different sheep populations. The sheep used in our study were well distributed in ten groups, with the high-milk-yield-group populations close to each other and the low-milk-yield-group populations showing similar classifications. To perform an exact signal-selection analysis, we used three different methods to find SNPs to perform gene-annotation analyses within the 995 common regions derived from the fixation index (FST), nucleotide diversity (Ɵπ), and heterozygosity rate (ZHp) results. In total, we found 553 genes that were located in these regions. These genes mainly participate in the protein-binding pathway and the nucleoplasm-interaction pathway, as revealed by the GO- and KEGG-function-enrichment analyses. After the gene selection and function analyses, we found that FCGR3A, CTSK, CTSS, ARNT, GHR, SLC29A4, ROR1, and TNRC18 were potentially related to sheep-milk-production traits. We chose the strongly selected genes, FCGR3A, CTSK, CTSS, and ARNT during the signal-selection analysis to perform a RT-qPCR (Reale time Quantitative Polymerase Chain Reaction) experiment to validate their expression-level relationship with milk production, and the results showed that FCGR3A has a significant negative relationship with sheep-milk production, while other three genes did not show any positive or negative relations. In this study, it was discovered and proven that the candidate gene FCGR3A potentially contributes to the milk production of dairy sheep and a basis was laid for the further study of the genetic mechanism underlying the strong milk-production traits of sheep. [ABSTRACT FROM AUTHOR]

Tibetan sheep are one of the three major coarse sheep breeds in China, and they possess a long history of formation. However, few studies have been conducted on the identification of Tibetan sheep breeds at the molecular level. In this study, a total of 448 individuals from 24 Tibetan sheep populations in the 5 regions of Tibet, Qinghai, Gansu, Yunnan, and Sichuan were analyzed using the Affymetrix Ovine SNP 600K high-density chip to construct specific single-nucleoside polymorphism (SNP) genetic marker sets of Tibetan sheep breeds. Firstly, the genetic structure analysis showed that Yunnan–Tibetan sheep (NL, Ninglang; JC, Jianchuan), Zuogong (ZG), Heizang (HZ), Gongga (GG,) and Tao sheep (TS) can be clearly distinguished from other Tibetan sheep populations. Next, based on the population differentiation index FST, the PCA and NJ tree results showed that only 60 specific SNPs can successfully separate Tibetan sheep in the Yunnan region from Tibetan sheep in other regions, and the distinguishing effect on Yunnan–Tibetan sheep reached 100%. Using the same method, we found that 4 Tibetan sheep breeds, including Zuogong (ZG, 20 SNPs), Heizang (HZ, 60 SNPs), Gongga (GG, 60 SNPs), and Tao sheep (TS, 30 SNPs), can also be distinguished from other Tibetan sheep populations with only a few SNP loci (20–60), and the distinguishing effect reached 100%. Overall, we successfully obtained a Yunnan region-specific (60 SNPs) genetic marker set and 4 breed-specific SNP genetic marker sets (20–60 SNPs) for the first time for the identification of Tibetan sheep breeds at the molecular level. These made up for the lack of genetic marker sets for the identification of Tibetan sheep breeds, and provided a genomic basis for the scientific classification and accurate identification of livestock and poultry genetic resources on the Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

The identification of genome-wide selection signatures can provide insights on the mechanisms of natural and/or artificial selection and uncover genes related to biological functions and/or phenotypes. Tibetan sheep are an important livestock in Tibet, providing meat and wool for Tibetans who are renown for breeding livestock that adapt well to high altitudes. Using whole-genome sequences with an effective sequencing depth of 5×, we investigated the genomic diversity and structure and, identified selection signatures of White Tibetan, Oula and Poll Dorset sheep. We obtained 30,163,679 Single Nucleotide Polymorphisms (SNPs) and 5,388,372 indels benchmarked against the ovine Oar_v4.0 genome assembly. Next, using FST, ZHp and XP-EHH approaches, we identified selection signatures spanning a set of candidate genes, including HIF1A, CAPN3, PRKAA1, RXFP2, TRHR and HOXA10 that are associated with pathways and GO categories putatively related to hypoxia responses, meat traits and disease resistance. Candidate genes and GO terms associated with coat color were also identified. Finally, quantification of blood physiological parameters, revealed higher levels of mean corpuscular hemoglobin measurement and mean corpuscular hemoglobin concentration in Tibetan sheep compared with Poll Dorset, suggesting a greater oxygen-carrying capacity in the Tibetan sheep and thus better adaptation to high-altitude hypoxia. In conclusion, this study provides a greater understanding of genome diversity and variations associated with adaptive and production traits in sheep. [ABSTRACT FROM AUTHOR]

Copy number variation ( CNV), an essential form of genetic variation, has been increasingly recognized as one promising genetic marker in the analysis of animal genomes. Here, we used the Equine 70K single nucleotide polymorphism genotyping array for the genome-wide detection of CNVs in 96 horses from three diverse Chinese breeds: Debao pony ( DB), Mongolian horse ( MG) and Yili horse ( YL). A total of 287 CNVs were determined and merged into 122 CNV regions ( CNVRs) ranging from 199 bp to 2344 kb in size and distributed in a heterogeneous manner on chromosomes. These CNVRs were integrated with seven existing reports to generate a composite genome-wide dataset of 1558 equine CNVRs, revealing 69 (56.6%) novel CNVRs. The majority (69.7%) of the 122 CNVRs overlapped with 438 genes, whereas 30.3% were located in intergenic regions. Most of these genes were associated with common CNVRs, which were shared by divergent horse breeds. As many as 60, 42 and 91 genes overlapping with the breed-specific ss were identified in DB, MG and YL respectively. Among these genes, FGF11, SPEM1, PPARG, CIDEB, HIVEP1 and GALR may have potential relevance to breed-specific traits. These findings provide valuable information for understanding the equine genome and facilitating association studies of economically important traits with equine CNVRs in the future. [ABSTRACT FROM AUTHOR]

A label-free electrochemical DNA sensor was fabricated by deposition of polyaniline and pristine graphene nanosheet (P/Gratios) composites in different mass ratios, DNA probe and bovine serum albumin (BSA) layer by layer on the surface of a glassy carbon electrode (GCE). Electrochemical impedance spectroscopy (EIS) was employed to monitor every step of fabrication of P/Gratio-based DNA sensors and to evaluate the detection results in terms of the hybridization of complementary DNA, mutant DNA and non-complementary DNA. The results illustrate that the P/Gratio-based DNA sensor could highly efficiently detect complementary DNA from 0.01 pm to 1 μm and discriminate single-nucleotide polymorphisms (SNPs). In the process of detection, double-stranded DNA (dsDNA), resulting from hybridization of a DNA probe, escaping from or remaining on the sensor surface, was monitored by changing the ratio of polyaniline (PANI) to graphene, which was decided by the competition between the electrostatic interaction and Brownian motion. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article presents the study of Chinese sheep breed polycerate phenotype and genotyped them with the Illumina OvineSNP50 BeadChip array. It adds that GWAS was performed by the use of EMMAX software and all polycerate phenotypes revealed same genome-wide significant Single-nucleotide polymorphism (SNP) marker.

Simple Summary: Information 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. [ABSTRACT FROM AUTHOR]