The level of fat deposition in carcass is a crucial factor influencing meat quality. Guangling Large-Tailed (GLT) and Small-Tailed Han (STH) sheep are important local Chinese fat-tailed breeds that show distinct patterns of fat depots. To gain a better understanding of fat deposition, transcriptome profiles were determined by RNA-sequencing of perirenal, subcutaneous, and tail fat tissues from both the sheep breeds. The common highly expressed genes (co-genes) in all the six tissues, and the genes that were differentially expressed (DE genes) between these two breeds in the corresponding tissues were analyzed. Approximately 47 million clean reads were obtained for each sample, and a total of 17,267 genes were annotated. Of the 47 highly expressed co-genes, FABP4, ADIPOQ, FABP5, and CD36 were the four most highly transcribed genes among all the known genes related to adipose deposition. FHC, FHC-pseudogene, and ZC3H10 were also highly expressed genes and could, thus, have roles in fat deposition. A total of 2091, 4233, and 4131 DE genes were identified in the perirenal, subcutaneous, and tail fat tissues between the GLT and STH breeds, respectively. Gene Ontology (GO) analysis showed that some DE genes were associated with adipose metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that PPAR signaling pathway and ECM-receptor interaction were specifically enriched. Four genes, namely LOC101102230, PLTP, C1QTNF7, and OLR1 were up-regulated and two genes, SCD and UCP-1, were down-regulated in all the tested tissues of STH. Among the genes involved in ECM–receptor interaction, the genes encoding collagens, laminins, and integrins were quite different depending on the depots or the breeds. In STH, genes such as LAMB3, RELN, TNXB, and ITGA8, were identified to be up regulated and LAMB4 was observed to be down regulated. This study unravels the complex transcriptome profiles in sheep fat tissues, highlighting the candidate genes involved in fat deposition. Further studies are needed to investigate the roles of the candidate genes in fat deposition and in determining the meat quality of sheep.

Domestic goats are commonly reared for meat and milk production in several regions of the world. However, the genetic mechanism underlying muscle development and meat quality of goats is limited. Therefore, the aim of this study was to identify known and novel genes regulating muscle development and meat quality of goats using second- and third-generation sequencing technologies. To achieve this, the meat quality and transcriptomes of longissimus dorsi (LD) and biceps femoris (BF) muscle tissues of Lingqiu Greyback goats were examined and compared. Differentially expressed genes (DEGs) and isoforms (DEIs) were functionally annotated. Results showed that 45,574 full-length transcripts covering 18,491 loci were characterized, and 12,566 genes were co-expressed in all samples. Differential expression analysis identified 231 DEGs, including 45 novel genes in the LD and BF muscles of the goats. Additionally, 1173 DEIs were found, in which 642 novel isoforms were identified in this study. Functional annotation and pathway analysis of the DEGs and DEIs revealed that some of them were associated with muscle growth and lipid metabolism. Overall, the findings of this study contribute to the understanding of the transcriptomic diversity underlying meat quality and muscle development of goat.

Adipose tissues represent an important energy storage organ in animals and are the largest endocrine organ. It plays an important regulatory role in the pathogenesis of insulin resistance, cardiovascular disease, and metabolic syndrome. Adipose development is a complex biological process involving multiple key genes, signaling pathways, and non-coding RNAs, including microRNAs and circular RNAs. In this study, we characterized circITGB1 and named its host gene ITGB1, which is differentially expressed in sheep of different months based on sequencing data. We collated and analyzed the sequencing data to select miRNA-23a with strong binding to ARRB1. We found that miRNA-23a regulates the development and differentiation of sheep adipocytes by targeting ARRB1. As a competing endogenous RNA, circITGB1 overexpression effectively alleviated the inhibitory effect of miR-23a on ARRB1. Conclusively, we provide evidence that circITGB1 regulates the proliferation and differentiation of sheep adipocytes via the miR-23a/ARRB1 pathway. This study provides a scientific basis for further studies on adipose tissue development at the circRNA level.

Genomic selection (GS) is a genetic breeding method that uses genome-wide marker information to improve the accuracy of the prediction of complex traits. The single-step GBLUP (ssGBLUP) model, which integrates pedigree, phenotypic, and genomic data, has improved genomic prediction. However, ssGBLUP assumes that all markers contribute equally to genetic variance, which can limit its predictive accuracy, especially for traits controlled by major genes. To overcome this limitation, we integrate results from genome-wide association studies (GWAS) into an enhanced ssGBLUP framework, termed single-step genome-wide association assisted BLUP (ssGWABLUP). Our approach assigns differential weights to markers on the basis of their GWAS results, thereby increasing the contribution of effective markers while diminishing the influence of ineffective ones during the construction of the genomic relationship matrix. By incorporating pseudo quantitative trait nucleotides (pQTNs) as covariates, we aim to capture the effects of markers closely associated with major causal variants, leading to the development of the ssGWABLUP_pQTNs. Compared with weighted ssGBLUP (WssGBLUP), the ssGWABLUP model demonstrated superior accuracy and dispersion across different genetic architectures. We then compared the performance of our proposed ssGWABLUP_pQTNs model against both ssGBLUP and ssGWABLUP across various genetic scenarios. Our results demonstrate that ssGWABLUP_pQTNs outperforms other models in terms of prediction accuracy, particularly in scenarios with simpler genetic architectures. Additionally, evaluation using pig dataset confirmed the effectiveness of ssGWABLUP_pQTNs, highlighting its potential for practical breeding applications. The incorporation of pQTNs and a weighted genomic relationship matrix presents a promising and potentially scalable approach to further enhance genomic prediction, with potential implications for improving the accuracy of genomic selection in breeding programs.

Intrauterine growth restriction (IUGR) is a common perinatal complication in animal reproduction, with long-lasting negative effects on neonates and postnatal animals, which seriously negatively affects livestock production. In this study, we aimed to identify potential genes associated with the diagnosis of IUGR through bioinformatics analysis. Based on the 73 differentially expressed related genes obtained by differential analysis and weighted gene co-expression network analysis, we used three machine learning algorithms to identify 4 IUGR-related hub genes (IUGR-HGs), namely, ADAM9, CRYL1, NDP52, and SERPINA7, whose ROC curves showed that they are a good diagnostic target for IUGR. Next, we identified two molecular subtypes of IUGR through consensus clustering analysis and constructed a gene scoring system based on the IUGR-HGs. The results showed that the IUGR score was positively correlated with the risk of IUGR. The AUC value of IUGR scoring accuracy was 0.970. Finally, we constructed a new artificial neural network model based on the four IUGR-HGs to diagnose sheep IUGR, and its accuracy reached 0.956. In conclusion, the IUGR-HGs we identified provide new potential molecular markers and models for the diagnosis of IUGR in sheep; they can better diagnose whether sheep have IUGR. The present findings provide new perspectives on the diagnosis of IUGR.

The Guangling Large-Tailed sheep is renowned for its unique tail fat deposition, with a significant proportion of its total body fat being localized in the tail region. Fat deposition is a complex biological process regulated by various molecular mechanisms. Our previous studies have identified a large number of differentially expressed circular RNAs (circRNAs) in the tail adipose tissue of the Guangling Large-Tailed sheep. These circRNAs may play a pivotal role in the process of fat deposition. Given the potential regulatory functions of circRNAs in adipose metabolism, investigating their roles in tail fat deposition is of significant scientific importance. In this study, we identified novel circARID1A. Using various experimental methods, including lentivirus infection, RNase R treatment, actinomycin D assay, qPCR, western blotting, and dual-luciferase reporter assays, we determined that circARID1A inhibits the expression of miR-493-3p through competitive binding, thereby regulating adipocyte differentiation. Further research revealed that miR-493-3p promotes adipocyte differentiation by targeting YTH domain family 2 (YTHDF2), and this regulatory effect is also influenced by circARID1A. In conclusion, our findings suggest that circARID1A inhibits tail fat cell differentiation in the Guangling Large-Tailed sheep through the circARID1A/miR-493-3p/YTHDF2 axis, providing theoretical support for improving meat quality and fat deposition in sheep.