Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency

Small networks of expressed genes in the whole blood and relationships to profiles in circulating metabolites provide insights in inter-individual variability of feed efficiency in growing pigs

BACKGROUND

Feed efficiency is a research priority to support a sustainable meat production. It is recognized as a complex trait that integrates multiple biological pathways orchestrated in and by various tissues. This study aims to determine networks between biological entities to explain inter-individual variation of feed efficiency in growing pigs.

RESULTS

The feed conversion ratio (FCR), a measure of feed efficiency, and its two component traits, average daily gain and average daily feed intake, were obtained from 47 growing pigs from a divergent selection for residual feed intake and fed high-starch or high-fat high-fiber diets during 58 days. Datasets of transcriptomics (60 k porcine microarray) in the whole blood and metabolomics (1H-NMR analysis and target gas chromatography) in plasma were available for all pigs at the end of the trial. A weighted gene co-expression network was built from the transcriptomics dataset, resulting in 33 modules of co-expressed molecular probes. The eigengenes of eight of these modules were significantly ([Formula: see text]) or tended to be ([Formula: see text]) correlated to FCR. Great homogeneity in the enriched biological pathways was observed in these modules, suggesting co-expressed and co-regulated constitutive genes. They were mainly enriched in genes participating to immune and defense-related processes, and to a lesser extent, to translation, cell development or learning. They were also generally associated with growth rate and percentage of lean mass. In the whole network, only one module composed of genes participating to the response to substances, was significantly associated with daily feed intake and body adiposity. The plasma profiles in circulating metabolites and in fatty acids were summarized by weighted linear combinations using a dimensionality reduction method. Close association was thus found between a module composed of co-expressed genes participating to T cell receptor signaling and cell development process in the whole blood and related to FCR, and the circulating concentrations of polyunsaturated fatty acids in plasma.

CONCLUSION

These systemic approaches have highlighted networks of entities driving key biological processes involved in the phenotypic difference in feed efficiency between animals. Connecting transcriptomics and metabolic levels together had some additional benefits.

Analysis of liver miRNA in Hu sheep with different residual feed intake

Feed efficiency (FE), an important economic trait in sheep production, is indirectly assessed by residual feed intake (RFI). However, RFI in sheep is varied, and the molecular processes that regulate RFI are unclear. It is thus vital to investigate the molecular mechanism of RFI to developing a feed-efficient sheep. The miRNA-sequencing (RNA-Seq) was utilized to investigate miRNAs in liver tissue of 6 out of 137 sheep with extreme RFI phenotypic values. In these animals, as a typical metric of FE, RFI was used to distinguish differentially expressed miRNAs (DE_miRNAs) between animals with high (n = 3) and low (n = 3) phenotypic values. A total of 247 miRNAs were discovered in sheep, with four differentially expressed miRNAs (DE_miRNAs) detected. Among these DE_miRNAs, three were found to be upregulated and one was downregulated in animals with low residual feed intake (Low_RFI) compared to those with high residual feed intake (High_RFI). The target genes of DE_miRNAs were primarily associated with metabolic processes and biosynthetic process regulation. Furthermore, they were also considerably enriched in the FE related to glycolysis, protein synthesis and degradation, and amino acid biosynthesis pathways. Six genes were identified by co-expression analysis of DE_miRNAs target with DE_mRNAs. These results provide a theoretical basis for us to understand the sheep liver miRNAs in RFI molecular regulation.

The mRNA-lncRNA landscape of multiple tissues uncovers key regulators and molecular pathways that underlie heterosis for feed intake and efficiency in laying chickens

BACKGROUND

Heterosis is routinely exploited to improve animal performance. However, heterosis and its underlying molecular mechanism for feed intake and efficiency have been rarely explored in chickens. Feed efficiency continues to be an important breeding goal trait since feed accounts for 60 to 70% of the total production costs in poultry. Here, we profiled the mRNA-lncRNA landscape of 96 samples of the hypothalamus, liver and duodenum mucosa from White Leghorn (WL), Beijing-You chicken (YY), and their reciprocal crosses (WY and YW) to elucidate the regulatory mechanisms of heterosis.

RESULTS

We observed negative heterosis for both feed intake and residual feed intake (RFI) in YW during the laying period from 43 to 46 weeks of age. Analysis of the global expression pattern showed that non-additivity was a major component of the inheritance of gene expression in the three tissues for YW but not for WY. The YW-specific non-additively expressed genes (YWG) and lncRNA (YWL) dominated the total number of non-additively expressed genes and lncRNA in the hypothalamus and duodenum mucosa. Enrichment analysis of YWG showed that mitochondria components and oxidation phosphorylation (OXPHOS) pathways were shared among the three tissues. The OXPHOS pathway was enriched by target genes for YWL with non-additive inheritance of expression in the liver and duodenum mucosa. Weighted gene co-expression network analysis revealed divergent co-expression modules associated with feed intake and RFI in the three tissues from WL, YW, and YY. Among the negatively related modules, the OXPHOS pathway was enriched by hub genes in the three tissues, which supports the critical role of oxidative phosphorylation. Furthermore, protein quantification of ATP5I was highly consistent with ATP5I expression in the liver, which suggests that, in crossbred YW, non-additive gene expression is down-regulated and decreases ATP production through oxidative phosphorylation, resulting in negative heterosis for feed intake and efficiency.

CONCLUSIONS

Our results demonstrate that non-additively expressed genes and lncRNA involved in oxidative phosphorylation in the hypothalamus, liver, and duodenum mucosa are key regulators of the negative heterosis for feed intake and RFI in layer chickens. These findings should facilitate the rational choice of suitable parents for producing crossbred chickens.

Identification of milk-related genes and regulatory networks in Bactrian camel either supplemented or under grazing

Using gene co-expression networks to understand dynamic characterizations in lactating animals becomes a common method. However, there are rarely reporters focusing on milk traits in Bactrian camel by high-throughput sequencing. We used RNA-seq to generate the camel transcriptome from the blood of 16 lactating Alxa Bactrian camel in different feeding groups. In total, we obtained 1185 milk-related genes correlated with milk yield, milk protein, milk fat, and milk lactose across the WGCNA analysis. Moreover, 364 milk-related genes were differentially expressed between supplementation and grazing feeding groups. The differential expression-camel milk-related genes CMRGs (DE-CMRGs) in supplement direct an intensive gene co-expression network to improve milk performance in lactating camels. This study provides a non-invasive method to identify the camel milk-related genes in camel blood for four primary milk traits and valuable theoretical basis and research ideas for the study of the milk performance regulation mechanism of camelid animals.

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.

Molecular Mechanism of m6A Methylation Modification Genes METTL3 and FTO in Regulating Heat Stress in Sheep

Heat stress is an important environmental factor affecting livestock production worldwide. Primary hepatocytes and preadipocytes derived from Hu sheep were used to establish a heat stress model. Quantitative reverse transcriptase-PCR (qRT-PCR) analysis showed that heat induction significantly increased the expression levels of heat stress protein (HSP) genes and the N6-methyladenosine (m6A) methylation modification genes: methyltransferase-like protein 3 (METTL3), methyltransferase-like protein 14 (METTL14), and fat mass and obesity associated protein (FTO). Heat stress simultaneously promoted cell apoptosis. Transcriptome sequencing identified 3980 upregulated genes and 2420 downregulated genes related to heat stress. A pathway enrichment analysis of these genes revealed significant enrichment in fatty acid biosynthesis, degradation, and the PI3K-Akt and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Overexpression of METTL3 in primary hepatocytes led to significant downregulation of HSP60, HSP70, and HSP110, and significantly increased mRNA m6A methylation; FTO interference generated the opposite results. Primary adipocytes showed similar results. Transcriptome analysis of cells under METTL3 (or FTO) inference and overexpression revealed differentially expressed genes enriched in the mitogen-activated protein kinase (MAPK) signaling pathways, as well as the PI3K-Akt and Ras signaling pathways. We speculate that METTL3 may increase the level of m6A methylation to inhibit fat deposition and/or inhibit the expression of HSP genes to enhance the body's resistance to heat stress, while the FTO gene generated the opposite molecular mechanism. This study provides a scientific basis and theoretical support for sheep feeding and management practices during heat stress.

Feed efficiency in dairy sheep: An insight from the milk transcriptome

Introduction

As higher feed efficiency in dairy ruminants means a higher capability to transform feed nutrients into milk and milk components, differences in feed efficiency are expected to be partly linked to changes in the physiology of the mammary glands. Therefore, this study aimed to determine the biological functions and key regulatory genes associated with feed efficiency in dairy sheep using the milk somatic cell transcriptome.

Material and methods

RNA-Seq data from high (H-FE, n = 8) and low (L-FE, n = 8) feed efficiency ewes were compared through differential expression analysis (DEA) and sparse Partial Least Square-Discriminant analysis (sPLS-DA).

Results

In the DEA, 79 genes were identified as differentially expressed between both conditions, while the sPLS-DA identified 261 predictive genes [variable importance in projection (VIP) > 2] that discriminated H-FE and L-FE sheep.

Discussion

The DEA between sheep with divergent feed efficiency allowed the identification of genes associated with the immune system and stress in L-FE animals. In addition, the sPLS-DA approach revealed the importance of genes involved in cell division (e.g., KIF4A and PRC1) and cellular lipid metabolic process (e.g., LPL, SCD, GPAM, and ACOX3) for the H-FE sheep in the lactating mammary gland transcriptome. A set of discriminant genes, commonly identified by the two statistical approaches, was also detected, including some involved in cell proliferation (e.g., SESN2, KIF20A, or TOP2A) or encoding heat-shock proteins (HSPB1). These results provide novel insights into the biological basis of feed efficiency in dairy sheep, highlighting the informative potential of the mammary gland transcriptome as a target tissue and revealing the usefulness of combining univariate and multivariate analysis approaches to elucidate the molecular mechanisms controlling complex traits.

Improving gene regulatory network inference and assessment: The importance of using network structure

Gene regulatory networks are graph models representing cellular transcription events. Networks are far from complete due to time and resource consumption for experimental validation and curation of the interactions. Previous assessments have shown the modest performance of the available network inference methods based on gene expression data. Here, we study several caveats on the inference of regulatory networks and methods assessment through the quality of the input data and gold standard, and the assessment approach with a focus on the global structure of the network. We used synthetic and biological data for the predictions and experimentally-validated biological networks as the gold standard (ground truth). Standard performance metrics and graph structural properties suggest that methods inferring co-expression networks should no longer be assessed equally with those inferring regulatory interactions. While methods inferring regulatory interactions perform better in global regulatory network inference than co-expression-based methods, the latter is better suited to infer function-specific regulons and co-regulation networks. When merging expression data, the size increase should outweigh the noise inclusion and graph structure should be considered when integrating the inferences. We conclude with guidelines to take advantage of inference methods and their assessment based on the applications and available expression datasets.

Prune homolog 2 with BCH domain (PRUNE2) gene expression is associated with feed efficiency-related traits in Nelore steers

Animal feeding is a critical factor in increasing producer profitability. Improving feed efficiency can help reduce feeding costs and reduce the environmental impact of beef production. Candidate genes previously identified for this trait in differential gene expression studies (e.g., case-control studies) have not examined continuous gene-phenotype variation, which is a limitation. The aim of this study was to investigate the association between the expression of five candidate genes in the liver, measured by quantitative real-time PCR and feed-related traits. We adopted a linear mixed model to associate liver gene expression from 52 Nelore steers with the following production traits: average daily gain (ADG), body weight (BW), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), Kleiber index (KI), metabolic body weight (MBW), residual feed intake (RFI), and relative growth ratio (RGR). The total expression of the prune homolog 2 (PRUNE2) gene was significantly associated with DMI, FCR, FE, and RFI (P < 0.05). Furthermore, we have identified a new transcript of PRUNE2 (TCONS_00027692, GenBank MZ041267) that was inversely correlated with FCR and FE (P < 0.05), in contrast to the originally identified PRUNE2 transcript. The cytochrome P450 subfamily 2B (CYP2B6), early growth response protein 1 (EGR1), collagen type I alpha 1 chain (COL1A1), and connective tissue growth factor (CTGF) genes were not associated with any feed efficiency-related traits (P > 0.05). The findings reported herein suggest that PRUNE2 expression levels affects feed efficiency-related traits variation in Nelore steers.

Residual Feed Intake in Beef Cattle Is Associated With Differences in Hepatic mRNA Expression of Fatty Acid, Amino Acid, and Mitochondrial Energy Metabolism Genes

We evaluated the mRNA expression of genes involved in hepatic fatty acid, amino acid, and mitochondrial energy metabolism in crossbred beef steers with divergent low and high residual feed intake (RFI). Low-RFI beef steers (n = 8; RFI = - 1.93 kg/d) and high-RFI beef steers (n = 8; RFI = + 2.01kg/d) were selected from a group of 56 growing crossbred beef steers (average BW = 261 ± 18.5 kg) fed a high-forage total mixed ration after a 49-d performance testing period. At the end of the 49-d performance testing period, liver biopsies were collected from the low-RFI and high-RFI beef steers for RNA extraction and cDNA synthesis. The mRNA expression of 84 genes each related to fatty acid metabolism, amino acid metabolism, and mitochondrial energy metabolism were analyzed using pathway-focused PCR-based arrays. The mRNA expression of 8 genes (CRAT, SLC27A5, SLC27A2, ACSBG2, ACADL, ACADSB, ACAA1, and ACAA2) involved fatty acid transport and β-oxidation were upregulated (FC ≥ 2.0, FDR ≤ 0.05) in low-RFI, compared to high-RFI steers. Among those involved in amino acid metabolism, hepatic mRNA expression of a gene encoding for aminoadipate aminotransferase, an enzyme related to lysine degradation, was downregulated (FC = -5.45, FDR = 0.01) in low-RFI steers, whereas those of methionine adenosyltransferase I and aspartate aminotransferase 2, which both link amino acid and lipid metabolism, were upregulated (FC ≥ 2.0, FDR ≤ 0.05). Two mitochondrial energy metabolism genes (UQCRC1 and ATP5G1) involved in ATP synthesis via oxidative phosphorylation were upregulated (FC ≥ 2.0, FDR ≤ 0.05) in low-RFI beef steers, compared to high-RFI beef steers. The results of this study demonstrated that low-RFI beef steers exhibit upregulation of molecular mechanisms related to fatty acid transport, fatty acid β-oxidation, and mitochondrial ATP synthesis, which suggest that low-RFI beef steers have enhanced metabolic capacity to maximize capture of energy and nutrients from feeds consumed.

Identifying key genes in milk fat metabolism by weighted gene co-expression network analysis

Milk fat is the most important and energy-rich substance in milk, and its content and composition are important reference elements in the evaluation of milk quality. However, the current identification of valuable candidate genes affecting milk fat is limited. IlluminaPE150 was used to sequence bovine mammary epithelial cells (BMECs) with high and low milk fat rates (MFP), the weighted gene co-expression network (WGCNA) was used to analyze mRNA expression profile data in this study. As a result, a total of 10,310 genes were used to construct WGCNA, and the genes were classified into 18 modules. Among them, violet (r = 0.74), yellow (r = 0.75) and darkolivegreen (r =  − 0.79) modules were significantly associated with MFP, and 39, 181, 75 hub genes were identified, respectively. Combining enrichment analysis and differential genes (DEs), we screened five key candidate DEs related to lipid metabolism, namely PI4K2A, SLC16A1, ATP8A2, VEGFD and ID1, respectively. Relative to the small intestine, liver, kidney, heart, ovary and uterus, the gene expression of PI4K2A is the highest in mammary gland, and is significantly enriched in GO terms and pathways related to milk fat metabolism, such as monocarboxylic acid transport, phospholipid transport, phosphatidylinositol signaling system, inositol phosphate metabolism and MAPK signaling pathway. This study uses WGCNA to form an overall view of MFP, providing a theoretical basis for identifying potential pathways and hub genes that may be involved in milk fat synthesis.

Identification of key genes and functional enrichment pathways involved in fat deposition in Xinyang buffalo by WGCNA

The Xinyang buffalo is a valuable and endangered domestic heritage resource in the Dabie Mountain region in China. With the increasing mechanization of agriculture, the Xinyang buffalo, mainly used for labor, faces unprecedented challenges. One of the feasible approaches to conserve and expand the species is to transfer Xinyang buffalo from service-use to meat-use, but the main hindrance to this transformation is the inferior meat quality of Xinyang buffalo, which is not popular with consumers. Based on the above, this study was conducted to evaluate the growth performance (n = 120) and slaughter performance (n = 3) of Xinyang buffalo and to measure the amino acid levels of the eye muscle (EM), and assess the meat quality. Later, transcriptome sequencing was performed on the subcutaneous fat of the back at six (n = 3) and 30 months of age (n = 3), together with the excavation of candidate genes associated with fat deposition using the weighted co-expression network analysis (WGCNA) method. The results showed that the slaughter rate of Xinyang buffalo was 43.09%, net meat percentage was 33.04%, the ocular area was 59.16 ± 7.58, the backfat thickness was 1.03 ± 0.16, and meat bone ratio was 3.29. The total amino acid contents were 0.63 g per gram of beef, which contained 0.05 g of essential amino acids, and the three most abundant amino acids were Ser (447.17 mg/g), Asp (29.8 mg/g), and Pro (27.24 mg/g). The WGCNA results showed that six phenotypes measured were significantly correlated with the turquoise module (r > 0.97, P < 0.001), and the genes in these modules were significantly enriched in the pathways related to substance metabolism and energy metabolisms, such as metabolic pathways, citrate cycle, and fatty acid metabolism. Meanwhile, six key candidate genes (FH, MECR, GPI, PANK3, ATP6V1A, PHYH) were identified, which were associated with growth and development, fat deposition, and intra-muscular amino acid levels (P < 0.05). In short, this study provides another feasible way to preserve buffalo and enriches the theory of its molecular genetic breeding.

Chemical Group-Based Metabolome Analysis Identifies Candidate Plasma Biomarkers Associated With Residual Feed Intake in Beef Steers

We applied chemical group-based metabolomics to identify blood metabolic signatures associated with residual feed intake in beef cattle. A group of 56 crossbred growing beef steers (average BW = 261.3 ± 18.5 kg) were adapted to a high-forage total mixed ration in a confinement dry lot equipped with GrowSafe intake nodes for period of 49 d to determine their residual feed intake classification (RFI). After RFI determination, weekly blood samples were collected three times from beef steers with the lowest RFI [most efficient (HFE); n = 8] and highest RFI and least-efficient [least efficient (LFE); n = 8]. Plasma was prepared by centrifugation and composited for each steer. Metabolome analysis was conducted using a chemical isotope labeling (CIL)/liquid chromatography–mass spectrometry, which permitted the analysis of metabolites containing amine/phenol-, carboxylic acid-, and carbonyl-chemical groups, which are metabolites associated with metabolisms of amino acids, fatty acids, and carbohydrates, respectively. A total number of 495 amine/phenol-containing metabolites were detected and identified; pathway analysis of all these metabolites showed that arginine biosynthesis and histidine metabolism were enriched (P &lt; 0.10) in HFE, relative to LFE steers. Biomarker analyses of the amine/phenol-metabolites identified methionine, 5-aminopentanoic acid, 2-aminohexanedioic acid, and 4-chlorolysine as candidate biomarkers of RFI [false discovery rate ≤ 0.05; Area Under the Curve (AUC) &gt; 0.90]. A total of 118 and 330 metabolites containing carbonyl- and carboxylic acid-chemical groups, respectively were detected and identified; no metabolic pathways associated with these metabolites were altered and only one candidate biomarker (methionine sulfoxide) was identified. These results identified five candidate metabolite biomarkers of RFI in beef cattle which are mostly associated with amino acid metabolism. Further validation using a larger cohort of beef cattle of different genetic pedigree is required to confirm these findings.

Transcriptome sequencing reveals Gastrodia elata Blume could increase the cell viability of eNPCs under hypoxic condition by improving DNA damage repair ability

ETHNOPHARMACOLOGICAL RELEVANCE

Gastrodia elata Blume (GEB), known as Tianma in China, is a traditional medicinal herb that has been reported to have various pharmacological effects and neuroprotection, has long been used for treating dizziness, epilepsy, stroke. However, explanation of its underlying mechanisms remains a great challenge.

AIM OF THE STUDY

The neuroprotective mechanism of GEB on hypoxia-induced neuronal injury in cultured mouse embryonic neural progenitor cells (eNPCs) was investigated, with emphasis on the eNPCs proliferation and DNA damage repair.

MATERIALS AND METHODS

In this study, hypoxia was focused, which may be caused by stroke or acute cerebral ischemia and is considered as one of the important factors contributing to the Central Nervous System diseases. CoCl₂ was adopted to construct a hypoxic/ischemic condition in eNPCs. eNPCs proliferation analysis validated GEB neuroprotective effect under hypoxic/ischemic condition. Transcriptome and weighted gene co-expression network analysis (WGCNA) screened the special gene-network module correlated with what appeared to have significant positive correlation with GEB. Then, Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to explore the biological functions of selected genes in the modules that had high correlation with GEB.

RESULTS

GEB has neuroprotective effect and could rescue eNPCs proliferation under hypoxic/ischemic condition induced by CoCl₂. Transcriptome and WGCNA unveil the neuroprotective mechanism of GEB on improving DNA damage repair ability by increasing the expression of genes associated with DNA repair and replication. Western blotting and qPCR showed that GEB could improve DNA damage repair ability by increasing the expression of Mcm2, Mcm6, Pold2, Pole, Pole2, Rfc1, Pole4, Dna2 and Rpa2, which were associated with DNA damage and replication.

CONCLUSION

Through transcriptome and WGCNA, this study unveiled Gastrodia elata Blume could increase the cell viability of eNPCs under hypoxic condition by improving DNA damage repair ability.

Identifying the key genes and functional enrichment pathways associated with feed efficiency in cattle

Residual feed intake (RFI) is a measurement of feed efficiency, and is inversely correlated with feed efficiency. The differentially expressed genes (DEGs) associated with RFI vary substantially among studies, posing great challenges in finding the RFI-related marker genes. This study attempted to resolve this issue by integrating and comparing the multiple transcriptome sequencing data associated with RFI in the cattle liver, using differential, functional enrichment, protein-protein interaction (PPI) network, weighted co-expression network (WGCNA), and gene set enrichment analyses (GSEA) to identify the candidate genes and functional enrichment pathways that are closely associated with RFI. Four candidate genes namely SHC1, GPX4, ACADL, and IGF1 were identified and validated as the marker genes for RFI. Four functional enrichment pathways, namely the fatty acid metabolism, sugar metabolism, energy metabolism, and protein ubiquitination were also found to be closely related to RFI. This study identified several genes and signaling pathways with shared characteristics, which will provide new insights into the molecular mechanisms related to the regulation of feed efficiency, and provide basis for molecular markers related to feed efficiency in beef cattle.

Comparative transcriptome analysis of winter yaks in plateau and plain

The yak is an important source for the people living and ecological environment in the Qinghai-Tibet Plateau. In every winter, many domestic yaks will lose bodyweight or dead under cold and food scarcity. Moving the plateau yaks to farm in the plain is a useful approach to reduce their environmental stress and gain more production. In this study, we measured growth, slaughter and beef quality traits every month and sequenced mRNA expression levels of muscles of two groups yaks living in plateau and plain respectively. We found there is significant difference (p-value <0.01) in the third (60 days), fourth (90 days), fifth (120 days) and sixth (150 days) weights between subpopulations in the plateau and plain. We identified 540 different expressed genes (DEGs) including 123 known genes and 417 unknown genes. Using the weighted correlation network analysis (WGCNA) to build a co-express network, the modules were strong relative to weight traits. The findings highlighted the underlying way and a relative network to yield a new view about gene expression between the yaks living plateau and plain.

Integrated Network Analysis to Identify Key Modules and Potential Hub Genes Involved in Bovine Respiratory Disease: A Systems Biology Approach

Background: Bovine respiratory disease (BRD) is the most common disease in the beef and dairy cattle industry. BRD is a multifactorial disease resulting from the interaction between environmental stressors and infectious agents. However, the molecular mechanisms underlying BRD are not fully understood yet. Therefore, this study aimed to use a systems biology approach to systematically evaluate this disorder to better understand the molecular mechanisms responsible for BRD. Methods: Previously published RNA-seq data from whole blood of 18 healthy and 25 BRD samples were downloaded from the Gene Expression Omnibus (GEO) and then analyzed. Next, two distinct methods of weighted gene coexpression network analysis (WGCNA), i.e., module-trait relationships (MTRs) and module preservation (MP) analysis were used to identify significant highly correlated modules with clinical traits of BRD and non-preserved modules between healthy and BRD samples, respectively. After identifying respective modules by the two mentioned methods of WGCNA, functional enrichment analysis was performed to extract the modules that are biologically related to BRD. Gene coexpression networks based on the hub genes from the candidate modules were then integrated with protein-protein interaction (PPI) networks to identify hub-hub genes and potential transcription factors (TFs). Results: Four significant highly correlated modules with clinical traits of BRD as well as 29 non-preserved modules were identified by MTRs and MP methods, respectively. Among them, two significant highly correlated modules (identified by MTRs) and six nonpreserved modules (identified by MP) were biologically associated with immune response, pulmonary inflammation, and pathogenesis of BRD. After aggregation of gene coexpression networks based on the hub genes with PPI networks, a total of 307 hub-hub genes were identified in the eight candidate modules. Interestingly, most of these hub-hub genes were reported to play an important role in the immune response and BRD pathogenesis. Among the eight candidate modules, the turquoise (identified by MTRs) and purple (identified by MP) modules were highly biologically enriched in BRD. Moreover, STAT1, STAT2, STAT3, IRF7, and IRF9 TFs were suggested to play an important role in the immune system during BRD by regulating the coexpressed genes of these modules. Additionally, a gene set containing several hub-hub genes was identified in the eight candidate modules, such as TLR2, TLR4, IL10, SOCS3, GZMB, ANXA1, ANXA5, PTEN, SGK1, IFI6, ISG15, MX1, MX2, OAS2, IFIH1, DDX58, DHX58, RSAD2, IFI44, IFI44L, EIF2AK2, ISG20, IFIT5, IFITM3, OAS1Y, HERC5, and PRF1, which are potentially critical during infection with agents of bovine respiratory disease complex (BRDC). Conclusion: This study not only helps us to better understand the molecular mechanisms responsible for BRD but also suggested eight candidate modules along with several promising hub-hub genes as diagnosis biomarkers and therapeutic targets for BRD.

Novel functional sequences uncovered through a bovine multiassembly graph

Many genomic analyses start by aligning sequencing reads to a linear reference genome. However, linear reference genomes are imperfect, lacking millions of bases of unknown relevance and are unable to reflect the genetic diversity of populations. This makes reference-guided methods susceptible to reference-allele bias. To overcome such limitations, we build a pangenome from six reference-quality assemblies from taurine and indicine cattle as well as yak. The pangenome contains an additional 70,329,827 bases compared to the Bos taurus reference genome. Our multiassembly approach reveals 30 and 10.1 million bases private to yak and indicine cattle, respectively, and between 3.3 and 4.4 million bases unique to each taurine assembly. Utilizing transcriptomes from 56 cattle, we show that these nonreference sequences encode transcripts that hitherto remained undetected from the B. taurus reference genome. We uncover genes, primarily encoding proteins contributing to immune response and pathogen-mediated immunomodulation, differentially expressed between Mycobacterium bovis-infected and noninfected cattle that are also undetectable in the B. taurus reference genome. Using whole-genome sequencing data of cattle from five breeds, we show that reads which were previously misaligned against the Bos taurus reference genome now align accurately to the pangenome sequences. This enables us to discover 83,250 polymorphic sites that segregate within and between breeds of cattle and capture genetic differentiation across breeds. Our work makes a so-far unused source of variation amenable to genetic investigations and provides methods and a framework for establishing and exploiting a more diverse reference genome.

Nitrogen metabolism and mammary gland amino acid utilization in lactating dairy cows with different residual feed intake

OBJECTIVE

This study was conducted to enhance our understanding of nitrogen (N) metabolism and mammary amino acid (AA) utilization in lactating cows with divergent phenotypes of residual feed intake (RFI).

METHODS

Fifty-three multiparous mid-lactation Holstein dairy cows were selected for RFI measurements over a 50-d experimental period. The 26 cows with the most extreme RFI values were classified into the high RFI (n = 13) and low RFI (n = 13) groups, respectively, for analysis of N metabolism and AA utilization.

RESULTS

Compared with the high RFI cows, the low RFI animals had lower dry matter intake (p<0.01) with no difference observed in milk yield between the two groups (p> 0.10). However, higher ratios of milk yield to dry matter intake (p<0.01) were found in the low RFI cows than in the high RFI cows. The low RFI cows had significant greater ratios of milk protein to metabolizable protein (p = 0.02) and milk protein to crude protein intake than the high RFI cows (p = 0.01). The arterial concentration and mammary uptake of essential AA (p<0.10), branched-chain AA (p<0.10), and total AA (p<0.10) tended to be lower in the low RFI cows. Additionally, the low RFI cows tended to have a lower ratio of AA uptake to milk output for essential AA (p = 0.08), branched-chain AA (p = 0.07) and total AA (p = 0.09) than the high RFI cows.

CONCLUSION

In summary, both utilization of metabolizable protein for milk protein and mammary AA utilization are more efficient in cows with lower RFI than in the high RFI cows. Our results provide new insight into the protein metabolic processes (related to N and AA) involved in feed efficiency.

Weighted gene co-expression network analysis identifies modules and functionally enriched pathways in the lactation process

The exponential growth in knowledge has resulted in a better understanding of the lactation process in a wide variety of animals. However, the underlying genetic mechanisms are not yet clearly known. In order to identify the mechanisms involved in the lactation process, various mehods, including meta-analysis, weighted gene co-express network analysis (WGCNA), hub genes identification, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment at before peak (BP), peak (P), and after peak (AP) stages of the lactation processes have been employed. A total of 104, 85, and 26 differentially expressed genes were identified based on PB vs. P, BP vs. AP, and P vs. AP comparisons, respectively. GO and KEGG pathway enrichment analysis revealed that DEGs were significantly enriched in the "ubiquitin-dependent ERAD" and the "chaperone cofactor-dependent protein refolding" in BP vs. P and P vs. P, respectively. WGCNA identified five significant functional modules related to the lactation process. Moreover, GJA1, AP2A2, and NPAS3 were defined as hub genes in the identified modules, highlighting the importance of their regulatory impacts on the lactation process. The findings of this study provide new insights into the complex regulatory networks of the lactation process at three distinct stages, while suggesting several candidate genes that may be useful for future animal breeding programs. Furthermore, this study supports the notion that in combination with a meta-analysis, the WGCNA represents an opportunity to achieve a higher resolution analysis that can better predict the most important functional genes that might provide a more robust bio-signature for phenotypic traits, thus providing more suitable biomarker candidates for future studies.

Genetic mechanisms underlying feed utilization and implementation of genomic selection for improved feed efficiency in dairy cattle

The economic importance of genetically improving feed efficiency has been recognized by cattle producers worldwide. It has the potential to considerably reduce costs, minimize environmental impact, optimize land and resource use efficiency, and improve the overall cattle industry’s profitability. Feed efficiency is a genetically complex trait that can be described as units of product output (e.g., milk yield) per unit of feed input. The main objective of this review paper is to present an overview of the main genetic and physiological mechanisms underlying feed utilization in ruminants and the process towards implementation of genomic selection for feed efficiency in dairy cattle. In summary, feed efficiency can be improved via numerous metabolic pathways and biological mechanisms through genetic selection. Various studies have indicated that feed efficiency is heritable, and genomic selection can be successfully implemented in dairy cattle with a large enough training population. In this context, some organizations have worked collaboratively to do research and develop training populations for successful implementation of joint international genomic evaluations. The integration of “-omics” technologies, further investments in high-throughput phenotyping, and identification of novel indicator traits will also be paramount in maximizing the rates of genetic progress for feed efficiency in dairy cattle worldwide.

HpeNet: Co-expression Network Database for de novo Transcriptome Assembly of Paeonia lactiflora Pall

The herbaceous peony (Paeonia lactiflora Pall.) is a well-known ornamental flowering and pharmaceutical plant found in China. Its high medicinal value has long been recognized by traditional Chinese medicine (as Radix paeoniae Alba and Radix paeoniae Rubra), and it has become economically valued for its oilseed in recent years; like other Paeonia species, it has been identified as a novel resource for the α-linolenic acid used in seed oil production. However, its genome has not yet been sequenced, and little transcriptome data on Paeonia lactiflora are available. To obtain a comprehensive transcriptome for Paeonia lactiflora, RNAs from 10 tissues of the Paeonia lactiflora Pall. cv Shaoyou17C were used for de novo assembly, and 416,062 unigenes were obtained. Using a homology search, it was found that 236,222 (approximately 57%) unigenes had at least one BLAST hit in one or more public data resources. The construction of co-expression networks is a feasible means for improving unigene annotation. Using in-house transcriptome data, we obtained a co-expression network covering 95.13% of the unigenes. Then we integrated co-expression network analyses and lipid-related pathway genes to study lipid metabolism in Paeonia lactiflora cultivars. Finally, we constructed the online database HpeNet (http://bioinformatics.cau.edu.cn/HpeNet) to integrate transcriptome data, gene information, the co-expression network, and so forth. The database can also be searched for gene details, gene functions, orthologous matches, and other data. Our online database may help the research community identify functional genes and perform research on Paeonia lactiflora more conveniently. We hope that de novo transcriptome assembly, combined with co-expression networks, can provide a feasible means to predict the gene function of species that do not have a reference genome.

Mitochondrial protein gene expression and the oxidative phosphorylation pathway associated with feed efficiency and energy balance in dairy cattle

Feed efficiency and energy balance are important traits underpinning profitability and environmental sustainability in animal production. They are complex traits, and our understanding of their underlying biology is currently limited. One measure of feed efficiency is residual feed intake (RFI), which is the difference between actual and predicted intake. Variation in RFI among individuals is attributable to the metabolic efficiency of energy utilization. High RFI (H_RFI) animals require more energy per unit of weight gain or milk produced compared with low RFI (L_RFI) animals. Energy balance (EB) is a closely related trait calculated very similarly to RFI. Cellular energy metabolism in mitochondria involves mitochondrial protein (MiP) encoded by both nuclear (NuMiP) and mitochondrial (MtMiP) genomes. We hypothesized that MiP genes are differentially expressed (DE) between H_RFI and L_RFI animal groups and similarly between negative and positive EB groups. Our study aimed to characterize MiP gene expression in white blood cells of H_RFI and L_RFI cows using RNA sequencing to identify genes and biological pathways associated with feed efficiency in dairy cattle. We used the top and bottom 14 cows ranked for RFI and EB out of 109 animals as H_RFI and L_RFI, and positive and negative EB groups, respectively. The gene expression counts across all nuclear and mitochondrial genes for animals in each group were used for differential gene expression analyses, weighted gene correlation network analysis, functional enrichment, and identification of hub genes. Out of 244 DE genes between RFI groups, 38 were MiP genes. The DE genes were enriched for the oxidative phosphorylation (OXPHOS) and ribosome pathways. The DE MiP genes were underexpressed in L_RFI (and negative EB) compared with the H_RFI (and positive EB) groups, suggestive of reduced mitochondrial activity in the L_RFI group. None of the MtMiP genes were among the DE MiP genes between the groups, which suggests a non-rate limiting role of MtMiP genes in feed efficiency and warrants further investigation. The role of MiP, particularly the NuMiP and OXPHOS pathways in RFI, was also supported by our gene correlation network analysis and the hub gene identification. We validated the findings in an independent data set. Overall, our study suggested that differences in feed efficiency in dairy cows may be linked to differences in cellular energy demand. This study broadens our knowledge of the biology of feed efficiency in dairy cattle.

Detection and integrated analysis of lncRNA and mRNA relevant to plateau adaptation of Yak

Known as the ‘ship of the plateau’, through thousands of years evolution and cruelty environments selection containing low oxygen and strong ultraviolet radiation, yaks have adapted plateau environments and supplied important goods and materials for the people in the Qinghai‐Tibet Plateau. This study aimed to identify differentially expressed (DE) genes and novel long non‐coding RNAs (lncRNAs) of yaks for the Plateau adaptation and their underlying co‐expression and regulatory network. We carried out RNA‐seq analysis for cerebral and cerebellar tissue specimens of Bos taurus, Bos grunniens × Bos Taurus and B. grunniens. Furthermore, 12,072 pseudo lncRNAs were predicted using three software. In total, 4,257 significant DE transcripts were identified using the Ballgown R package (p < .01), of which 1,021 were protein‐coding genes, 14 were known lncRNAs, and 661 were novel lncRNAs. Using WGCNA, a co‐expression network of DE mRNAs and lncRNAs comprising 5 modules was generated to determine functional associations clusters. This study reveals a valuable sub‐network comprising 8 hub genes, one known lncRNA and 5 novel lncRNAs in the major module. These hub genes are associated with blood pressure regulation, generation of reactive oxygen species and metabolism. The analysis of co‐expressed genes thus provides a basis for the regulatory mechanisms in PA in Yaks and for the detection of additional genes between cross‐breed and parent populations.

Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits

Most traits of agricultural importance are quantitative traits controlled by numerous genes. However, it remains unclear about the molecular mechanisms underpinning quantitative traits. Here, we report the molecular characteristics of the genes controlling three quantitative traits randomly selected from three diverse plant species, including ginsenoside biosynthesis in ginseng (Panax ginseng C.A. Meyer), fiber length in cotton (Gossypium hirsutum L. and G. barbadense L.) and grain yield in maize (Zea mays L.). We found that a vast majority of the genes controlling a quantitative trait were significantly more likely spliced into multiple transcripts while they expressed. Nevertheless, only one to four, but not all, of the transcripts spliced from each of the genes were significantly correlated with the phenotype of the trait. The genes controlling a quantitative trait were multiple times more likely to form a co-expression network than other genes expressed in an organ. The network varied substantially among genotypes of a species and was associated with their phenotypes. These findings indicate that the genes controlling a quantitative trait are more likely pleiotropic and functionally correlated, thus providing new insights into the molecular basis underpinning quantitative traits and knowledge necessary to develop technologies for efficient manipulation of quantitative traits.

Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency in Bos taurus Bulls

Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.

Identification of genetic loci associated with growth traits at weaning in yak through a genome-wide association study

A multilocus GWAS was performed to explore the genetic architecture of four growth traits in yak. In total, 354 female yaks for which measurements of body weight (BW), withers height (WH), body length (BL) and chest girth (CG) at weaning were available underwent genotyping with the Illumina BovineHD BeadChip (770K). After quality control, we retained 98 688 SNPs and 354 animals for GWAS analysis. We identified seven, 18, seven and nine SNPs (corresponding to seven, 17, seven and eight candidate genes) associated with BW, WH, BL and CG at weaning respectively. Interestingly, most of these candidate genes were reported to be involved in growth-related processes such as muscle formation, lipid deposition, feed efficiency, carcass composition and development of the central and peripheral nervous system. Our results offer novel insight into the molecular architecture underpinning yak growth traits. Further functional analyses are thus warranted to explore the molecular mechanisms whereby these genes affect these traits of interest.

Whole blood transcriptome analysis in ewes fed with hemp seed supplemented diet

The hemp plant (Cannabis sativa L.) has a long tradition of being used for many different purposes such as industry, medicine and nutrition. In particular, because hemp seed (HS) is rich in oil protein and considerable amounts of dietary fiber, vitamins and minerals that are particularly suitable also for animal nutrition. Different studies have evaluated HS on qualitative and quantitative properties of livestock products but as of today, nobody has investigated the molecular pathway behind HS supplementation in farm animals. Thus, in this study, we will report the first RNA sequencing of the whole-blood transcriptome of ewes fed either with a controlled diet (CTR, n = 5) or with a diet supplemented with 5% of hemp seed (HSG, n = 5). Applying a false discovery rate (FDR) <0.05 and a log₂FC either higher than 0.5 or lower than −0.5, we identified 314 differentially regulated genes in the HS-supplemented group compared to the CTR group. Several genes encoding for different subunits belonging to the complex I, II, III, IV and ATP-synthase were up-regulated making oxidative phosphorylation (FDR: 3.05e-19) and thermogenesis (FDR: 2.17e-16) the highest up-regulated pathways in our study. Moreover, we found up-regulation in different genes involved in lactose biosyntheses such as GALK1 and PGM1 and, as a result, we observed a statistically higher lactose percentage in the HSG group (p < 0.05). These results indicate that HS supplementation positively affects the energy production pathway in lactating ewes conferring them also more resistance to adverse climatic conditions such as low temperature. Finally, the higher milk lactose content makes the derived dairy products more profitable.

Whole blood transcriptome analysis in ewes fed with hemp seed supplemented diet

The hemp plant (Cannabis sativa L.) has a long tradition of being used for many different purposes such as industry, medicine and nutrition. In particular, because hemp seed (HS) is rich in oil protein and considerable amounts of dietary fiber, vitamins and minerals that are particularly suitable also for animal nutrition. Different studies have evaluated HS on qualitative and quantitative properties of livestock products but as of today, nobody has investigated the molecular pathway behind HS supplementation in farm animals. Thus, in this study, we will report the first RNA sequencing of the whole-blood transcriptome of ewes fed either with a controlled diet (CTR, n = 5) or with a diet supplemented with 5% of hemp seed (HSG, n = 5). Applying a false discovery rate (FDR) <0.05 and a log₂FC either higher than 0.5 or lower than -0.5, we identified 314 differentially regulated genes in the HS-supplemented group compared to the CTR group. Several genes encoding for different subunits belonging to the complex I, II, III, IV and ATP-synthase were up-regulated making oxidative phosphorylation (FDR: 3.05e-19) and thermogenesis (FDR: 2.17e-16) the highest up-regulated pathways in our study. Moreover, we found up-regulation in different genes involved in lactose biosyntheses such as GALK1 and PGM1 and, as a result, we observed a statistically higher lactose percentage in the HSG group (p < 0.05). These results indicate that HS supplementation positively affects the energy production pathway in lactating ewes conferring them also more resistance to adverse climatic conditions such as low temperature. Finally, the higher milk lactose content makes the derived dairy products more profitable.

Gene co-expression network analysis reveals key potential gene modules in utero-vaginal junction associated with duration of fertility trait of breeder hens

The number of days (DN) when hens lay fertile eggs as well as the number of fertile eggs (FN) were produced after a single artificial insemination (AI), including the two duration of fertility (DF) traits. Indeed, they are the key production performance that associates with the production cost of hatching egg when its determination the interval between successive artificial inseminations. However, the relevant genes response for regulating the DF has not been uncovered yet. Therefore, we performed a weighted gene co-expression network analysis (WGCNA) to investigate the insight into co-expression gene modules on DF process in hens. The total mRNA was extracted from the utero-vaginal junction (UVJ, with the sperm storage function in hen’s oviduct which is the biological basis for DF) of 20 hens with several levels of DF traits, and performed transcriptome sequences of mRNA. As a result, three co-expression gene modules were identified to be highly correlated with DF traits. Moreover, the expression changes of top 5 hub genes in each module with DF traits were further confirmed in other 20 hens by RT-PCR. These findings highlighted the co-expression modules and their affiliated genes as playing important roles in the regulation of DF traits.

Investigation of muscle transcriptomes using gradient boosting machine learning identifies molecular predictors of feed efficiency in growing pigs

Background

Improving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors.

Results

Microarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI was estimated (RFI-BV), and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R² = 0.63–0.65), FCR (R² = 0.61–0.70) and FCRe (R² = 0.49–0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R² = 0.73, FRC: R² = 0.76; FCRe: R² = 0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV.

Conclusion

It was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6010-9) contains supplementary material, which is available to authorized users.

A Gene Expression Atlas of the Domestic Water Buffalo (Bubalus bubalis)

The domestic water buffalo (Bubalus bubalis) makes a major contribution to the global agricultural economy in the form of milk, meat, hides, and draught power. The global water buffalo population is predominantly found in Asia, and per head of population more people depend upon the buffalo than on any other livestock species. Despite its agricultural importance, there are comparatively fewer genomic and transcriptomic resources available for buffalo than for other livestock species. We have generated a large-scale gene expression atlas covering multiple tissue and cell types from all major organ systems collected from three breeds of riverine water buffalo (Mediterranean, Pandharpuri and Bhadawari) and used the network analysis tool Graphia Professional to identify clusters of genes with similar expression profiles. Alongside similar data, we and others have generated for ruminants as part of the Functional Annotation of Animal Genomes Consortium; this comprehensive transcriptome supports functional annotation and comparative analysis of the water buffalo genome.

Metabolomics Analyses in High-Low Feed Efficient Dairy Cows Reveal Novel Biochemical Mechanisms and Predictive Biomarkers

Residual feed intake (RFI) is designed to estimate net efficiency of feed use, so low RFI animals are considered for selection to reduce feeding costs. However, metabolic profiling of cows and availability of predictive metabolic biomarkers for RFI are scarce. Therefore, this study aims to generate a better understanding of metabolic mechanisms behind low and high RFI in Jerseys and Holsteins and identify potential predictive metabolic biomarkers. Each metabolite was analyzed to reveal their associations with two RFIs in two breeds by a linear regression model. An integrative analysis of metabolomics and transcriptomics was performed to explore interactions between functionally related metabolites and genes in the created metabolite networks. We found that three main clusters were detected in the heat map and all identified fatty acids (palmitoleic, hexadecanoic, octadecanoic, heptadecanoic, and tetradecanoic acid) were grouped in a cluster. The lower cluster were all from fatty acids, including palmitoleic acid, hexadecanoic acid, octadecanoic acid, heptadecanoic acid, and tetradecanoic acid. The first component of the partial least squares-discriminant analysis (PLS-DA) explained a majority (61.5%) of variations of all metabolites. A good division between two breeds was also observed. Significant differences between low and high RFIs existed in the fatty acid group (P < 0.001). Statistical results revealed clearly significant differences between breeds; however, the association of individual metabolites (leucine, ornithine, pentadecanoic acid, and valine) with the RFI status was only marginally significant or not significant due to a lower sample size. The integrated gene-metabolite pathway analysis showed that pathway impact values were higher than those of a single metabolic pathway. Both types of pathway analyses revealed three important pathways, which were aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate metabolism, and the citrate cycle (TCA cycle). Finally, one gene (2-hydroxyacyl-CoA lyase 1 (+HACL1)) associated with two metabolites (-α-ketoglutarate and succinic acid) were identified in the gene-metabolite interaction network. This study provided novel metabolic pathways and integrated metabolic-gene expression networks in high and low RFI Holstein and Jersey cattle, thereby providing a better understanding of novel biochemical mechanisms underlying variation in feed efficiency.

Transcriptomic Analysis Provides Novel Insights into Heat Stress Responses in Sheep

Simple Summary

The general increase in global temperatures has meant that heat stress has become an increasingly significant problem for sheep. This has both direct and indirect impact on their physiological functions, productivity, and health of sheep. Sheep generally live in high-temperature environments; however, the genes and pathways that play regulatory roles in the heat stress responses of sheep remain unclear. In this study, we applied RNA-Seq technology to analyze liver tissues of sheep from heat-stressed and control groups, and screened genes and pathways related to sheep heat stress. This work provides a theoretical foundation for the breeding and production of heat-resistant sheep.

Abstract

With the intensified and large-scale development of sheep husbandry and global warming, sheep heat stress has become an increasingly important issue. However, little is known about the molecular mechanisms related to sheep responses to heat stress. In this study, transcriptomic analysis of liver tissues of sheep in the presence and absence of heat stress was conducted, with the goal of identifying genes and pathways related to regulation when under such stress. After a comparison with the sheep reference genome, 440,226,436 clean reads were obtained from eight libraries. A p-value ≤ 0.05 and fold change ≥ 2 were taken as thresholds for categorizing differentially expressed genes, of which 1137 were identified. The accuracy and reliability of the RNA-Seq results were confirmed by qRT-PCR. The identified differentially expressed genes were significantly associated with 419 GO terms and 51 KEGG pathways, which suggested their participation in biological processes such as response to stress, immunoreaction, and fat metabolism. This study’s results provide a comprehensive overview of sheep heat stress-induced transcriptional expression patterns, laying a foundation for further analysis of the molecular mechanisms of sheep heat stress.

Gene co-expression networks contributing to the expression of compensatory growth in metabolically active tissues in cattle

Compensatory growth (CG) is an accelerated growth phenomenon which occurs in animals upon re-alimentation following a period of dietary restriction. The objective of this study was to perform gene co-expression analysis on metabolic tissues of animals undergoing CG, in order to elucidate the molecular control governing this phenomenon. Thirty Holstein Friesian bulls were fed a restricted diet for 125 days, after which they received feed ad libitum. Following 55 days of ad libitum feeding all animals were slaughtered. RNAseq and gene co-expression analyses were performed on tissue samples collected at slaughter including liver, rumen papillae and jejunum epithelium tissues. A period of CG resulted in 15 networks of co-expressed genes. One network of genes, involved in proteasome core complex, signal transduction and protein synthesis was found to be similar across liver and jejunum tissue datasets (r = 0.68, P = 0.04). Results from this study also showed that a large portion of co-expressed genes had not previously been implicated in the expression of CG, thus this study identifies novel genes involved in controlling CG across tissues, with hub genes holding potential for use as biomarkers for the selection of animals with a greater propensity to display CG.