Analysis of the Genetic Relationship and Inbreeding Coefficient of the Hetian Qing Donkey through a Simplified Genome Sequencing Technology.

The Hetian Qing donkey is an excellent local donkey breed in Xinjiang. It is of great significance to accelerate breeding and the speed of breeding and rejuvenation, as well as to understand the genetic basis of the strategies and population. This study collected a total of 4 male donkeys and 28 female donkeys. It then obtained genotype data through Simplified Genomic Sequencing (GBS) technology for data analysis. The results detected a total of 55,399 SNP loci, and the genotype detection rate of individuals was ≥90%. A total of 45,557 SNP loci were identified through quality control, of which 95.5% were polymorphic. The average minimum allele frequency was 0.250. The average observed heterozygosity was 0.347. The average expected heterozygosity was 0.340. The average IBS (state homologous) genetic distance was 0.268. ROH: 49 (homozygous fragments), with 73.47% of the length between 1 and 5 Mb. The average per-strip ROH length was 1.75 Mb. The mean inbreeding coefficient was 0.003. The 32 Hetian green donkeys could be divided into six families. The number of individuals in each family is significant. To sum up, the Hetian Qing donkey population has low heterozygosity, few families, and large differences in the number of individuals in each family, which can easily cause a loss of genetic diversity. In the subsequent process of seed protection, seed selection should be conducted according to the divided pedigree to ensure the long-term protection of the genetic resources of Hetian green donkeys.

Stress adaptation in Tibetan cashmere goats is governed by inherent metabolic differences and manifested through variable cashmere phenotypes.

Tibetan cashmere goats are not only served as a valuable model for studying adaptation to hypoxia and high-altitude conditions but also playing a pivotal role in bolstering local economies through the provision of premium quality cashmere yarn. In this study, we performed an integration and network analysis of metabolomic, transcriptomic and proteomic to elucidate the role of differentially expressed genes, important metabolites, and relevant cellular and metabolic pathways between the fine (average 12.04 ± 0.03 µm of mean fiber diameter) and coarse cashmere (average 14.88 ± 0.05 µm of mean fber diameter) producing by Tibetan cashmere goats. We identified a distinction of 56 and 71 differential metabolites (DMs) between the F and C cashmere groups under positive and negative ion modes, respectively. The KEGG pathway enrichment analysis of these DMs highlighted numerous pathways predominantly involved in amino acid and protein metabolism, as indicated by the finding that the most impactful pathway was the mammalian target of rapamycin (mTOR) signalling pathway. In the F group, we identified a distinctive metabolic profile where amino acid metabolites including serine, histidine, asparagine, glutamic acid, arginine, valine, aspartic acid, tyrosine, and methionine were upregulated, while lysine, isoleucine, glutamine, tryptophan, and threonine were downregulated. The regulatory network and gene co-expression network revealed crucial genes, metabolites, and metabolic pathways. The integrative omics analysis revealed a high enrichment of several pathways, notably encompassing protein digestion and absorption, sphingolipid signalling, and the synaptic vesicle cycle. Within the sphere of our integrative analysis, DNMT3B was identified as a paramount gene, intricately associated with significant proteins such as HMCN1, CPB2, GNG12, and LRP1. Our present study delineated the molecular underpinnings governing the variations in cashmere characteristics by conducting comprehensive analyses across metabolomic, transcriptomic, and proteomic dimensions. This research provided newly insights into the mechanisms regulating cashmere traits and facilitated the advancement of selective breeding programs aimed at cultivating high-quality superfine Tibetan cashmere goats.

Regulation of cashmere fineness traits by noncoding RNA in Jiangnan cashmere goats.

BACKGROUND: Cashmere has long been used as the raw material for wool textiles. The diameter of the cashmere fibre determines its quality and economic value. However, the regulatory role of noncoding RNAs (ncRNAs) in cashmere fineness remains unclear, especially regarding the interaction between ncRNAs and coding RNAs. RESULTS: Transcriptome sequencing was used to identify the expression profiles of long noncoding RNAs (lncRNAs), circular RNAs (circRNAs) and microRNAs (miRNAs) in the skin tissues of Jiangnan cashmere goats with different cashmere fineness levels. Integration analysis of ncRNA and coding RNA was performed in combination with previous research results. The results showed that 16,437 lncRNAs, 2234 circRNAs, and 1322 miRNAs were identified in 8 skin samples of cashmere goats. A total of 403 differentially expressed (DE) lncRNAs, 62 DE circRNAs and 30 DE miRNAs were identified in the skin tissues of the fine groups (Fe) and coarse groups (Ce). We predicted the target gene of DE lncRNA, the target gene of DE miRNA and the host gene of DE circRNA. Based on functional annotation and enrichment analysis of target genes, we found that DE lncRNAs could be involved in regulating the fineness traits of cashmere. The most potential lncRNAs were MSTRG.42054.1, MSTRG.18602.3, and MSTRG.2199.13. CONCLUSIONS: The data from this study enriched the cashmere goat noncoding RNA database and helped to supplement the annotation of the goat genome. The results provided a new direction for the breeding of cashmere characters.

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep.

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992-2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h2 values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

Genome-wide identification and characterization of long non-coding RNAs expressed during sheep fetal and postnatal hair follicle development.

Long non-coding RNAs (lncRNAs), >200 nt in length, are transcribed from mammalian genomes. They play important regulatory roles in various biological processes; However, the function and expression profile of lncRNAs involved in the development of hair follicles in the fetus, have been relatively under-explored area. To investigate the specific role of lncRNAs and mRNAs that regulate hair follicle development, we herein performed a comprehensive study on the lncRNA and mRNA expression profiles of sheep at multiple embryonic days (E65, E85, E105, and E135) and six lambs aged one week (D7) and one month (D30) using RNA-seq technology. The number of genes (471 lncRNAs and 12,812 mRNAs) differentially expressed and potential targets of differentially expressed lncRNAs were predicted. Differentially expressed lncRNAs were grouped into 10 clusters based on their expression pattern by K-means clustering. Moreover, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that some differentially expressed mRNAs, such as DKK1, DSG4, FOXE1, Hoxc13, SFRP1, SFRP2, and Wnt10A overlapped with lncRNAs targets, and enriched in important hair follicle developmental pathways, including Wnt, TNF, and MAPK signaling pathways. In addition, 9 differentially expressed lncRNAs and 4 differentially expressed mRNAs were validated using quantitative real-time PCR (qRT-PCR). This study helps enrich the Ovis lncRNA databases and provides a comprehensive lncRNA transcriptome profile of fetal and postnatal skin of sheep. Additionally, it provides a foundation for further experiments on the role of lncRNAs in the regulation of hair growth in sheep.

Association analysis of polymorphisms in six keratin genes with wool traits in sheep.

OBJECTIVE: The purpose of this study was to investigate the genetic effects of six keratin (KRT) genes on the wool traits of 418 Chinese Merino (Xinjiang type) (CMXT) individuals. METHODS: To explore the effects and association of six KRT genes on sheep wool traits, The polymerase chain reaction-based single-strand conformation polymorphism (PCR-SSCP), DNA sequencing, and the gene pyramiding effect methods were used. RESULTS: We report 20 mutation sites (single-nucleotide polymorphisms) within the six KRT genes, in which twelve induced silent mutations; five induced missense mutations and resulted in Ile→Thr, Glu→Asp, Gly→Ala, Ala→Ser, Se→His; two were nonsense mutations and one was a same-sense mutation. Association analysis showed that two genotypes of the KRT31 gene were significantly associated with fiber diameter (p<0.05); three genotypes of the KRT36 gene were significantly associated with wool fineness score and fiber diameter (p<0.05), three genotypes of the KRT38 gene were significantly associated with the number of crimps (p< 0.05); and three genotypes of the KRT85 gene were significantly associated with wool crimps score, body size, and fiber diameter (p<0.05). Analysis of the gene pyramiding effect between the different genotypes of the gene loci KRT36, KRT38, and KRT85, each genotype in a gene locus was combined with all the genotypes of another two gene loci and formed the different three loci combinations, indicated a total of 26 types of possible combined genotypes in the analyzed population. Compared with the other combined genotypes, the combinations CC-GG-II, CC-HH-IJ, CC-HH-JJ, DD-HH-JJ, CC-GH-IJ, and CC-GH-JJ at gene loci KRT36, KRT38, and KRT85, respectively, had a greater effect on wool traits (p<0.05). CONCLUSION: Our results indicate that the mutation loci of KRT31, KRT36, KRT38, and KRT85 genes, as well as the combinations at gene loci KRT36, KRT38, and KRT85 in CMXT have significant effects on wool traits, suggesting that these genes are important candidate genes for wool traits, which will contribute to sheep breeding and provide a molecular basis for improved wool quality in sheep.