Full-Length Transcriptome and Gene Expression Analysis of Different Ovis aries Adipose Tissues Reveals Transcript Variants Involved in Lipid Biosynthesis.

Sheep have historically been bred globally as a vital food source. To explore the transcriptome of adipose tissue and investigate key genes regulating adipose metabolism in sheep, adipose tissue samples were obtained from F1 Dorper × Hu sheep. High-throughput sequencing libraries for second- and third-generation sequencing were constructed using extracted total RNA. Functional annotation of differentially expressed genes and isoforms facilitated the identification of key regulatory genes and isoforms associated with sheep fat metabolism. SMRT-seq generated 919,259 high-accuracy cDNA sequences after filtering. Full-length sequences were corrected using RNA-seq sequences, and 699,680 high-quality full-length non-chimeric (FLNC) reads were obtained. Upon evaluating the ratio of total lengths based on FLNC sequencing, it was determined that 36,909 out of 56,316 multiple-exon isoforms met the criteria for full-length status. This indicates the identification of 330,375 full-length FLNC transcripts among the 370,114 multiple-exon FLNC transcripts. By comparing the reference genomes, 60,276 loci and 111,302 isoforms were identified. In addition, 43,423 new genes and 44,563 new isoforms were identified. The results identified 185 (3198), 394 (3592), and 83 (3286) differentially expressed genes (transcripts) between tail and subcutaneous, tail and visceral, and subcutaneous and visceral adipose tissues, respectively. Functional annotation and pathway analysis revealed the following observations. (1) Among the differentially expressed genes (DEGs) of TF and SF tissues, the downregulation of ACADL, ACSL6, and NC_056060.1.2536 was observed in SF, while FFAR4 exhibited upregulation. (2) Among the DEGs of TF and VF tissues, expressions of ACADL, ACSL6, COL1A1, COL1A2, and SCD were downregulated in VF, with upregulation of FFAR4. (3) Among SF and VF expressions of COL1A1, COL1A2, and NC_056060.1.2536 were downregulated in VF. Specific differentially expressed genes (ACADL, ACSL6, COL1A1, COL1A2, FFAR4, NC_056060.1.2536, and SCD) and transcripts (NC_056066.1.1866.16 and NC_056066.1.1866.22) were identified as relevant to fat metabolism. These results provide a dataset for further verification of the regulatory pathway associated with fat metabolism in sheep.

Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits.

Genomic best linear-unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify causal variants effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (G). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to optimize the performance of weighted GBLUP and compare them with other available methods using simulated and real data sets. First, two types of methods (marker effects with local shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted G matrices were constructed based on the marker information from the first step: (1) the genomic-feature-weighted G, (2) the estimated marker-variance-weighted G, and (3) the absolute value of the estimated marker-effect-weighted G. Following the above process, six different weighted GBLUP methods (local shrinkage/normal-prior GF/EV/AEWGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy was trait dependant, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of a large effect. Normal-prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (explain 25-50% genetic variance) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.

Transcriptome analysis of adipose tissues from two fat-tailed sheep breeds reveals key genes involved in fat deposition.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

miR-124-3p affects the formation of intramuscular fat through alterations in branched chain amino acid consumption in sheep.

Intramuscular fat is used to determine meat quality in animals; however, factors affecting branched chain amino acid (BCAA) catabolism, which fuels adipogenesis and lipogenesis, remain unclear. To better understand the post-transcriptional influence on BCAA catabolism during adipogenesis, we investigated the role of miR-124-3p. Stromal vascular fraction (SVF) cells were isolated from skeletal muscle of sheep, and induced to differentiate. We determined the roles of miR-124-3p and its predicted target, branched chain keto acid dehydrogenase E1, alpha polypeptide (BCKDHA), in adipogenic differentiation and lipogenesis of SVFs after overexpressing or inhibiting miR-124-3p or BCKDHA, respectively. miR-124-3p altered the luciferase activity of constructs containing 3'-UTR of BCKDHA and the formation of lipid droplets, along with the adipogenic markers and BCAA consumption. Besides, the adipogenic performance and BCAA consumption in BCKDHA-overexpressing or knocked-down SVFs and the expression of adipogenic marker genes were altered. We demonstrate that miR-124-3p is an important factor for adipogenesis and provide insights into the formation of intramuscular fat in animals.

Coordinated microRNA and messenger RNA expression profiles for understanding sexual dimorphism of gonads and the potential roles of microRNA in the steroidogenesis pathway in Nile tilapia (Oreochromis niloticus).

Sexual dimorphism is a widespread phenomenon in animals. However, the potential role of microRNAs (miRNAs) in regulating this dimorphism is not fully understood. In our study, we used an integrated approach to identify functional targets of miRNA by combining the paired expression profiles of miRNAs and messenger RNAs (mRNAs) in ovaries and testes of young Nile tilapia, Oreochromis niloticus. The results revealed that 67 upregulated and nine downregulated miRNAs and 2299 upregulated and 3260 downregulated genes were identified in the ovary compared with those in the testis (P < 0.01). The target genes of differentially expressed miRNAs were predicted and overlapped with the differentially expressed mRNAs. Furthermore, Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted in these coincident genes. By correlating miRNA-mRNA and predicting computational target, two types of negatively regulatory miRNA-mRNA correlations (upregulated or downregulated miRNA and downregulated or upregulated mRNA) were obtained. Seven functional miRNA-target gene pairs, miR-17-5p/DMRT1, miR-20a/DMRT1, miR-138/CYP17A2, miR-338/CYP17A2, miR-200a/CYP17A2, miR-456/AMH, and miR-138/AMH, were predicted at the sequence level and further detected by real-time polymerase chain reaction on the basis of the significantly negative relationships. Our results suggest that the integrated analysis of miRNA and mRNA expression profiling can provide novel insights into the molecular mechanism of sexual dimorphism.