Gene co-expression and alternative splicing analysis of key metabolic tissues to unravel the regulatory signatures of fatty acid composition in cattle

A comprehensive study on the longissius dorsi muscle of Ashdan yaks under different feeding regimes based on transcriptomic and metabolomic analyses

Yak is an important dominant livestock species at high altitude, and the growth performance of yak has obvious differences under different feeding methods. This experiment was conducted to compare the effects of different feeding practices on growth performance and meat quality of yaks through combined transcriptomic and metabolomic analyses. In terms of yak growth performance, compared with traditional grazing, in-house feeding can significantly improve the average daily weight gain, carcass weight and net meat weight of yaks; in terms of yak meat quality, in-house feeding can effectively improve the quality of yak meat. A combined transcriptomic and metabolomic analysis revealed 31 co-enriched pathways, among which arginine metabolism, proline metabolism and glycerophospholipid metabolism may be involved in the development of the longissimus dorsi muscle of yak and the regulation of meat quality-related traits. The experimental results increased our understanding of yak meat quality and provided data materials for subsequent deep excavation of the mechanism of yak meat quality.

Assessment of different enrichment methods revealed the optimal approach to identify bovine circRnas

Although circular RNAs (circRNAs) play important roles in regulating gene expression, the understanding of circRNAs in livestock animals is scarce due to the significant challenge to characterize them from a biological sample. In this study, we assessed the outcomes of bovine circRNA identification using six enrichment approaches with the combination of ribosomal RNAs removal (Ribo); linear RNAs degradation (R); linear RNAs and RNAs with structured 3' ends degradation (RTP); ribosomal RNAs coupled with linear RNAs elimination (Ribo-R); ribosomal RNA, linear RNAs and RNAs with poly (A) tailing elimination (Ribo-RP); and ribosomal RNA, linear RNAs and RNAs with structured 3' ends elimination (Ribo-RTP), respectively. RNA-sequencing analysis revealed that different approaches led to varied ratio of uniquely mapped reads, false-positive rate of identifying circRNAs, and the number of circRNAs per million clean reads (Padj <0.05). Out of 2,285 and 2,939 highly confident circRNAs identified in liver and rumen tissues, respectively, 308 and 260 were commonly identified from five methods, with Ribo-RTP method identified the highest number of circRNAs. Besides, 507 of 4,051 identified bovine highly confident circRNAs had shared splicing sites with human circRNAs. The findings from this work provide optimized methods to identify bovine circRNAs from cattle tissues for downstream research of their biological roles in cattle.

Muscle transcriptome analysis reveal candidate genes and pathways related to fat and lipid metabolism in Yunling cattle

Yunling cattle (YL) is a recently developed beef breed harboring a quarter of Yunnan ancestral cattle genome, spanning over past 30 years. Compared with Diqing cattle (DQ), a Yunnan native cattle breed, YL presents various advantages, including rapid growth and exquisite meat quality. However, the molecular mechanisms underlying these phenotypic differences are not clearly understood. To further identify the candidate genes responsible for the quality of the meat in the muscle, longissimus dorsi (LD) muscle was used for RNA-Seq analysis. A total of 508 differentially expressed genes (DEGs) were identified in YL (adjusted p-value <0.01 and log2FoldChange >1), of which 243 were up-regulated and 265 were down-regulated. Functional association analysis showed that the identified DEGs mainly enriched the lipid and fat metabolism pathways. Moreover, it was also observed that several fat-related genes were differentially expressed in both cattle breeds, including three up-regulated genes (MOGAT1, ACSM3, PLPP2) and two down-regulated genes (ADIG, GPAT3). In addition, alternative splice analysis was also performed revealing an important 9-11 exon skipping variation of GPAM gene (crucial for beef marbling) in YL, which is three times higher than that in DQ, suggesting that this variation might have played the central role in the 'snow beef' effect in YL. We believe that our results will help in understanding the mechanism of muscle development and promote the further breeding programs in YL cattle.

Characterization of feed efficiency-related key signatures molecular in different cattle breeds

Feed efficiency is a major constraint in the beef industry and has a significant negative correlation with residual feed intake (RFI). RFI is widely used as a measure of feed efficiency in beef cattle and is independent of economic traits such as body weight and average daily gain. However, key traits with commonality or specificity among beef cattle breeds at the same level of RFI have not been reported. Accordingly, the present study hypothesized that signatures associated with feed efficiency would have commonality or specificity in the liver of cattle breeds at the same RFI level. By comparing and integrating liver transcriptome data, we investigated the critical signatures closely associated with RFI in beef cattle using weighted co-expression network analysis, consensus module analysis, functional enrichment analysis and protein network interaction analysis. The results showed that the consensus modules in Angus and Charolais cattle were negatively correlated, and four (turquoise, red, tan, yellow) were significantly positively correlated in Angus liver, while (turquoise, red) were significantly negatively correlated in Charolais liver. These consensus modules were found to be primarily involved in biological processes such as substance metabolism, energy metabolism and gene transcription, which may be one of the possible explanations for the difference in feed efficiency between the two beef breeds. This research also identified five key candidate genes, PLA2G12B, LCAT, MTTP, LCAT, ABCA1 and FADS1, which are closely associated with hepatic lipid metabolism. The present study has identified some modules, genes and pathways that may be the major contributors to the variation in feed efficiency among different cattle breeds, providing a new perspective on the molecular mechanisms of feed efficiency in beef cattle and a research basis for investigating molecular markers associated with feed efficiency in beef cattle.

Identification of key genes in bovine muscle development by co-expression analysis

Background

Skeletal muscle is not only an important tissue involved in exercise and metabolism, but also an important part of livestock and poultry meat products. Its growth and development determines the output and quality of meat to a certain extent, and has an important impact on the economic benefits of animal husbandry. Skeletal muscle development is a complex regulatory network process, and its molecular mechanism needs to be further studied.

Method

We used a weighted co-expression network (WGCNA) and single gene set enrichment analysis (GSEA) to study the RNA-seq data set of bovine tissue differential expression analysis, and the core genes and functional enrichment pathways closely related to muscle tissue development were screened. Finally, the accuracy of the analysis results was verified by tissue expression profile detection and bovine skeletal muscle satellite cell differentiation model in vitro (BSMSCs).

Results

In this study, Atp2a1, Tmod4, Lmod3, Ryr1 and Mybpc2 were identified as marker genes in muscle tissue, which are mainly involved in glycolysis/gluconeogenesis, AMPK pathway and insulin pathway. The assay results showed that these five genes were highly expressed in muscle tissue and positively correlated with the differentiation of bovine BSMSCs.

Conclusions

In this study, several muscle tissue characteristic genes were excavated, which may play an important role in muscle development and provide new insights for bovine molecular genetic breeding.

Multi-transcriptomics reveals RLMF axis-mediated signaling molecules associated with bovine feed efficiency

The regulatory axis plays a vital role in interpreting the information exchange and interactions among mammal organs. In this study on feed efficiency, it was hypothesized that a rumen-liver-muscle-fat (RLMF) regulatory axis exists and scrutinized the flow of energy along the RLMF axis employing consensus network analysis from a spatial transcriptomic standpoint. Based on enrichment analysis and protein-protein interaction analysis of the consensus network and tissue-specific genes, it was discovered that carbohydrate metabolism, energy metabolism, immune and inflammatory responses were likely to be the biological processes that contribute most to feed efficiency variation on the RLMF regulatory axis. In addition, clusters of genes related to the electron respiratory chain, including ND (2,3,4,4L,5,6), NDUF (A13, A7, S6, B3, B6), COX (1,3), CYTB, UQCR11, ATP (6,8), clusters of genes related to fatty acid metabolism including APO (A1, A2, A4, B, C3), ALB, FG (A, G), as well as clusters of the ribosomal-related gene including RPL (8,18A,18,15,13, P1), the RPS (23,27A,3A,4X), and the PSM (A1-A7, B6, C1, C3, D2-D4, D8 D9, E1) could be the primary effector genes responsible for feed efficiency variation. The findings demonstrate that high feed efficiency cattle, through the synergistic action of the regulatory axis RLMF, may improve the efficiency of biological processes (carbohydrate metabolism, protein ubiquitination, and energy metabolism). Meanwhile, high feed efficiency cattle might enhance the ability to respond to immunity and inflammation, allowing nutrients to be efficiently distributed across these organs associated with digestion and absorption, energy-producing, and energy-storing organs. Elucidating the distribution of nutrients on the RLMF regulatory axis could facilitate an understanding of feed efficiency variation and achieve the study on its molecular regulation.

Characterization of peripheral white blood cells transcriptome to unravel the regulatory signatures of bovine subclinical mastitis resistance

Subclinical bovine mastitis is a pathogenic infection of the breast characterized by a marked decrease in milk production and quality. As it has no obvious clinical symptoms, diagnosis and treatment are challenging. Therefore, searching for biomarkers in cows’ peripheral white blood cells is valuable for preventing and treating subclinical mastitis. Thus, in this study, the transcriptome of peripheral blood from healthy and subclinical mastitis cows was characterized to find the regulatory signatures of bovine subclinical mastitis using RNA-seq. A total of 287 differentially expressed genes (DEGs) and 70 differentially expressed lncRNAs (DELs) were detected, and 37 DELs were documented near known Quantitative Trait Loci (QTL) associated with the mastitis of cows. Bioinformatic analysis indicated that lncRNAs MSTRG25101.2, MSTRG.56327.1, and MSTRG.18968.1, which are adjacent to the SCS QTL and SCC QTL, may be candidate lncRNAs that influence the pathogenesis of mastitis in cows by up-regulating the expression of genes TLR4, NOD2, CXCL8, and OAS2. Moreover, the alternative splicing (AS) pattern of transcriptional sequence differences between healthy cows and subclinical mastitis cows suggested a molecular mechanism of mastitis resistance and susceptibility. A total of 2,212 differential alternative splicing (DAS) events, corresponding to 1,621 unique DAS genes, were identified in both groups and significantly enriched in immune and inflammatory pathways. Of these, 29 DAS genes were subject to regulation by 32 alternative splicing SNPs, showing diverse and specific splicing patterns and events. It is hypothesized that the PIK3C2B and PPRPF8 splice variants associated with AS SNPs (rs42705933 and rs133847062) may be risk factors for susceptibility to bovine subclinical mastitis. Altogether, these key blood markers associated with resistance to subclinical mastitis and SNPs associated with alternative splicing of genes provide the basis for genetic breeding for resistance to subclinical mastitis in cows.

Over-Expression of Two Different Isoforms of Cattle TUSC5 Showed Opposite Effects on Adipogenesis

(1) Background: Adipogenesis is an important issue in human health and livestock meat quality that has received widespread attention and extensive study. However, alternative splicing events may generate multiple isoforms with different functions. This will lead to known knowledge being far more complex than before. (2) Methods: We studied the effects of two different TUSC5 isoforms (TUSC5A and TUSC5B) in cattle on adipogenesis by constructing over-expression cell models and RNA-sequencing methods. (3) Results: We discovered that over-expression of TUSC5A promotes the process of adipogenesis while over-expression of TUSC5B suppresses it. Eight important genes (PPARG, ACC1, FASN, SCD1, LPL, FABP4, GPDH, and GLUT4) during adipogenesis were significantly promoted (student’s t-test, p < 0.05) by TUSC5A and suppressed by TUSC5B both before and after cell differentiation. By performing a comprehensive analysis using a RNA-seq strategy, we found that both up-regulated differentially expressed genes (DEGs, |log2FoldChange| ≥ 1, p ≤ 0.05) of TUSC5A and down-regulated DEGs of TUSC5B were significantly enriched in the adipogenesis related GO terms, and the PPAR signaling pathway may play important role in those differences. (4) Conclusions: Our study proved that over-expression of two TUSC5 isoforms would regulate adipogenesis in the opposite direction. It is important to understand the function of the TUSC5 gene correctly.

Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Central Genes Associated With Bovine Subcutaneous Adipose Tissue

Background

Fat deposition is an important economic trait in livestock and poultry production. However, the relationship between various genes and signal pathways of fat deposition is still unclear to a large extent. The purpose of this study is to analyze the potential molecular targets and related molecular pathways in bovine subcutaneous adipose tissue.

Results

We downloaded the GSE116775 microarray dataset from Gene Expression Omnibus (GEO). The weighted gene co-expression network (WGCNA) was used to analyze the gene expression profile, and the key gene modules with the highest correlation with subcutaneous adipose tissue were identified, and the functional enrichment of the key modules was analyzed. Then, the “real” Hub gene was screened by in-module analysis and protein–protein interaction network (PPI), and its expression level in tissue samples and adipocytes was verified. The study showed that a total of nine co-expression modules were identified, and the number of genes in these modules ranged from 101 to 1,509. Among them, the blue module is most closely related to subcutaneous adipose tissue, containing 1,387 genes. These genes were significantly enriched in 10 gene ontologies including extracellular matrix organization, biological adhesion, and collagen metabolic process, and were mainly involved in pathways including ECM-receptor interaction, focal adhesion, cAMP signaling pathway, PI3K-AKT signaling pathway, and regulation of lipolysis in adipocytes. In the PPI network and coexpression network, five genes (CAV1, ITGA5, COL5A1, ABL1, and HSPG2) were identified as “real” Hub genes. Analysis of Hub gene expression by dataset revealed that the expression of these Hub genes was significantly higher in subcutaneous adipose tissue than in other tissues. In addition, real-time fluorescence quantitative PCR (qRT-PCR) analysis based on tissue samples and adipocytes also confirmed the above results.

Conclusion

In this study, five key genes related to subcutaneous adipose tissue were discovered, which laid a foundation for further study of the molecular regulation mechanism of subcutaneous adipose tissue development and adipose deposition.

Breed dependent regulatory mechanisms of beneficial and non-beneficial fatty acid profiles in subcutaneous adipose tissue in cattle with divergent feed efficiency

The current study aimed to determine whether breed and feed efficiency affect the molecular mechanisms regulating beneficial and non-beneficial fatty acid profiles in subcutaneous adipose tissue of beef steers. Fatty acid profiling and RNA-Seq based transcriptome analysis were performed on subcutaneous adipose tissues collected from beef steers with three divergent breeds (Angus, ANG, n = 47; Charolais, CHAR, n = 48; Kinsella Composite, KC, n = 48) and different residual feed intake (RFI, a measure of feed efficiency). The comparison of fatty acid profiles showed that KC had higher beneficial FAs compared to the other two breeds. Distinct FA profiles between H-RFIfat and L-RFIfat steers was more obvious for KC steers, where H-RFIfat steers tended to have higher proportion of healthy FAs and lower proportion of the unhealthy FAs. A higher number of differentially expressed (DE) genes were observed for KC steers, whereas ANG and CHAR steers had a lower number of DE genes between H- and L-RFIfat steers. The association analyses of the gene expressions and FA profiles showed that 10 FA metabolism-associated genes together with the one upstream regulator (SREBF1) were associated with the proportion of C18:2n-6, total n-6, PUFA and PUFA/SFA for KC steers but not the other two breeds. Subcutaneous adipose tissue FA profiles and healthy FA index differed in cattle with divergent feed efficiency and such variation was unique for the three examined cattle breeds. Key FA metabolism-associated genes together with SREBF1 which is the upstream regulator of a set of genes involved in lipid metabolism may be of importance for genetic selection of meat with higher healthy FA index in beef cattle.

Identifying Key Genes and Functionally Enriched Pathways of Diverse Adipose Tissue Types in Cattle

Background: Fat is a tissue that not just stores energy and plays a protective role; it is also a vital endocrine organ that generates and integrates signals to influence metabolism. Meanwhile, the excessive accumulation of lipids in adipose tissue can lead to metabolic disturbance and diseases. To date, the complicated molecular mechanisms of bovine adipose tissue are still unknown. This study aimed to identify key genes and functionally enriched pathways in various adipose tissue types.

Results: The RNAseq data of 264 samples were downloaded from Gene Expression Omnibus (GEO) and analyzed by weighted gene co-expression network analysis (WGCNA). We identified 19 modules that significantly associated with at least one adipose tissue type. The brown module from GSE39618 was most closely associated with intramuscular fat tissue, which contained 550 genes. These genes were significantly enriched in pathways that related to inflammation and disease, such as TNF signaling pathway, IL-17 signaling pathway, and NF-kappa B signaling pathway. The pink module (GSE39618) that contained 58 genes was most closely associated with omental fat tissue. The turquoise (GSE39618), blue (GSE116775), and yellow (GSE65125) module were most closely associated with subcutaneous fat tissue. Genes in these modules were significantly enriched in pathways related to fat metabolism, such as the PPAR signaling pathway, fatty acid metabolism and PI3K-Akt signaling pathway. At last, key genes for intramuscular fat (PTGS2 and IL6), omental fat (ARHGEF5 and WT1), and subcutaneous fat (KIT, QR6Q1, PKD2L1, etc.) were obtained and verified. In addition, it was found that IL10 and VCAM1 might be potential genes to distinguish adipose and muscle.

Conclusion: The study applied WGCNA to generate a landscape of adipose tissue and provide a basis for identifying potential pathways and hub genes of different adipose tissue types.

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from -0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.