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Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in 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&ndash, 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.

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

This study was conducted to estimate variance components and genetic parameters for 305 days mature equivalent milk yields (MEM) and calving interval (CAI) of registered Xinjiang Brown cattle. The total records were 3940 including 2579 for 305-day MEM and 1970 for CAI, which were collected from Xinjiang Urumqi Cattle Breeding farm in China with calving records from 1990 to 2008. Genetic parameters were obtained by multiple trait derivative-free restricted maximum likelihood (MTDFREML) using animal model. The model included year, season, parity and calving interval of calving for 305 days MEM, and year, season and parity of birth for CAI as fixed effects. Heritability for 305 days MEM was moderate (0.39) and in the same range of parameters estimated in management systems with medium production levels. Heritability of calving interval was small (0.02) as fertility traits for Xinjiang Brown cattle. Estimates of genetic and environmental correlations between 305 days MEM and CAI were 0.47 and 0.37, respectively. Estimates of genetic variation and heritability indicated that selection would result in genetic improvement of production traits. Estimates of both heritability and genetic variation for CAI were small, which indicates that genetic improvement would be difficult.

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.