Landscape of multi-tissue global gene expression reveals the regulatory signatures of feed efficiency in beef cattle

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.

Multi-breed host rumen epithelium transcriptome and microbiome associations and their relationship with beef cattle feed efficiency

Understanding host-microbial interactions in the rumen and its influence on desirable production traits may lead to potential microbiota manipulation or genetic selection for improved cattle feed efficiency. This study investigated the host transcriptome and its correlation with the rumen archaea and bacteria differential abundance of two pure beef cattle breeds (Angus and Charolais) and one composite beef hybrid (Kinsella) divergent for residual feed intake (RFI; low-RFI vs. high-RFI). Using RNA-Sequencing of rumen tissue and 16S rRNA gene amplicon sequencing, differentially expressed genes (FDR ≤ 0.05, |log2(Fold-change) >|2) and differentially abundant (p-value < 0.05) archaea and bacteria amplicon sequence variants (ASV) were determined. Significant correlations between gene expression and ASVs (p-value < 0.05) were determine using Spearman correlation. Interesting associations with muscle contraction and the modulation of the immune system were observed for the genes correlated with bacterial ASVs. Potential functional candidate genes for feed efficiency status were identified for Angus (CCL17, CCR3, and CXCL10), Charolais (KCNK9, GGT1 and IL6), and Kinsella breed (ESR2). The results obtained here provide more insights regarding the applicability of target host and rumen microbial traits for the selection and breeding of more feed efficient beef cattle.

Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits

BACKGROUND

Insights into the genetic basis of complex traits and disease in both human and livestock species have been achieved over the past decade through detection of genetic variants in genome-wide association studies (GWAS). A majority of such variants were found located in noncoding genomic regions, and though the involvement of numerous regulatory elements (REs) has been predicted across multiple tissues in domesticated animals, their evolutionary conservation and effects on complex traits have not been fully elucidated, particularly in ruminants. Here, we systematically analyzed 137 epigenomic and transcriptomic datasets of six mammals, including cattle, sheep, goats, pigs, mice, and humans, and then integrated them with large-scale GWAS of complex traits.

RESULTS

Using 40 ChIP-seq datasets of H3K4me3 and H3K27ac, we detected 68,479, 58,562, 63,273, 97,244, 111,881, and 87,049 REs in the liver of cattle, sheep, goats, pigs, humans and mice, respectively. We then systematically characterized the dynamic functional landscapes of these REs by integrating multi-omics datasets, including gene expression, chromatin accessibility, and DNA methylation. We identified a core set (n = 6359) of ruminant-specific REs that are involved in liver development, metabolism, and immune processes. Genes with more complex cis-REs exhibited higher gene expression levels and stronger conservation across species. Furthermore, we integrated expression quantitative trait loci (eQTLs) and GWAS from 44 and 52 complex traits/diseases in cattle and humans, respectively. These results demonstrated that REs with different degrees of evolutionary conservation across species exhibited distinct enrichments for GWAS signals of complex traits.

CONCLUSIONS

We systematically annotated genome-wide functional REs in liver across six mammals and demonstrated the evolution of REs and their associations with transcriptional output and conservation. Detecting lineage-specific REs allows us to decipher the evolutionary and genetic basis of complex phenotypes in livestock and humans, which may benefit the discovery of potential biomedical models for functional variants and genes of specific human diseases.

Selection Signatures in South African Nguni and Bonsmara Cattle Populations Reveal Genes Relating to Environmental Adaptation

Climate change is a major influencing factor in beef production. The greenhouse gases produced from livestock production systems contribute to the overall greenhouse gas emissions. The aim of this study was to identify selection signatures within and between Nguni and Bonsmara cattle in relation to production and adaptation. For this purpose, genomic 150 K single nucleotide polymorphism data from Nguni (n = 231) and Bonsmara (n = 252) cattle in South Africa were used. Extended haplotype homozygosity (EHH) based analysis was executed within each population using integrated haplotype score (iHS). The R package rehh was used for detecting selection signatures across the two populations with cross population EHH (XP-EHH). Total of 121 regions of selection signatures were detected (p < 0.0001) in the Bonsmara and Nguni populations. Several genes relating to DNA methylation, heat stress, feed efficiency and nitrogen metabolism were detected within and between each population. These regions also included QTLs associated with residual feed intake, residual gain, carcass weight, stature and body weight in the Bonsmara, while QTLs associated with conception rate, shear force, tenderness score, juiciness, temperament, heat tolerance, feed efficiency and age at puberty were identified in Nguni. Based on the results of the study it is recommended that the Nguni and Bonsmara be utilized in crossbreeding programs as they have beneficial traits that may allow them to perform better in the presence of climate change. Results of this study coincide with Nguni and Bonsmara breed characteristics and performance, and furthermore support informative crossbreeding programs to enhance livestock productivity in South Africa.

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.

Characterization and Duodenal Transcriptome Analysis of Chinese Beef Cattle With Divergent Feed Efficiency Using RNA-Seq

Residual feed intake (RFI) is an important measure of feed efficiency for agricultural animals. Factors associated with cattle RFI include physiology, dietary factors, and the environment. However, a precise genetic mechanism underlying cattle RFI variations in duodenal tissue is currently unavailable. The present study aimed to identify the key genes and functional pathways contributing to variance in cattle RFI phenotypes using RNA sequencing (RNA-seq). Six bulls with extremely high or low RFIs were selected for detecting differentially expressed genes (DEGs) by RNA-seq, followed by conducting GO, KEGG enrichment, protein-protein interaction (PPI), and co-expression network (WGCNA, n = 10) analysis. A total of 380 differentially expressed genes was obtained from high and low RFI groups, including genes related to energy metabolism (ALDOA, HADHB, INPPL1), mitochondrial function (NDUFS1, RFN4, CUL1), and feed intake behavior (CCK). Two key sub-networks and 26 key genes were detected using GO analysis of DEGs and PPI analysis, such as TPM1 and TPM2, which are involved in mitochondrial pathways and protein synthesis. Through WGCNA, a gene network was built, and genes were sorted into 27 modules, among which the blue (r = 0.72, p = 0.03) and salmon modules (r = -0.87, p = 0.002) were most closely related with RFI. DEGs and genes from the main sub-networks and closely related modules were largely involved in metabolism; oxidative phosphorylation; glucagon, ribosome, and N-glycan biosynthesis, and the MAPK and PI3K-Akt signaling pathways. Through WGCNA, five key genes, including FN1 and TPM2, associated with the biological regulation of oxidative processes and skeletal muscle development were identified. Taken together, our data suggest that the duodenum has specific biological functions in regulating feed intake. Our findings provide broad-scale perspectives for identifying potential pathways and key genes involved in the regulation of feed efficiency in beef cattle.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Transcriptome Atlas of 16 Donkey Tissues

Donkeys (Equus asinus) are important livestock with great economic value in meat, skin, and milk production. However, a lack of knowledge of the transcriptome landscape across a wide range of donkey tissues limits genetic selective breeding and conservation. Here we used transcriptomics to describe the transcriptome landscape, classify the tissue-specific gene expression across all primary donkey tissues, and present supplementary analyses on the protein level of additional donkey milk samples. Overall, 16,013 protein-coding genes and 21,983 transcripts were mapped to the reference genome, including 6,778 ubiquitously expressed genes and 2,601 tissue-enriched genes. Functional analysis revealed that the function of the tissue-enriched genes was highly tissue specific. Tissue-elevated genes that could be associated with unique phenotypes in donkey were analyzed. The results showed that, compared with those in human and other livestock, the lysozyme gene in donkey breast was specifically and highly expressed. The calcium-binding lysozyme, encoded by the lysozyme gene, was also detected in high amounts in donkey milk. Given those intact lysozyme genes that predict potentially functional calcium-binding lysozyme found in only a few species (e.g., donkey and horse), the high expression of the lysozyme gene in donkey breast may contribute to the high lysozyme content in donkey milk. Furthermore, 71% of the proteins in donkey milk overlapped with human milk protein, higher than the overlapping rates of bovine, sheep, and swine with humans. The donkey transcriptomic resource contributes to the available genomic resources to interpret the molecular mechanisms underlying phenotype traits.

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.

Genetic parameters for performance, feed efficiency, and carcass traits in Senepol heifers

Improving feed efficiency is a key breeding goal in the beef cattle industry. In this study, we estimated the genetic parameters for feed efficiency and carcass traits in Senepol cattle raised in tropical regions. Various indicators of feed efficiency [gain to feed ratio (G:F), feed conversion ratio (FCR), residual weight gain (RG), residual intake and body weight gain (RIG), and residual feed intake (RFI)] as well as growth [final BW, average daily gain (ADG), and DM intake (DMI)], and carcass [rib-eye area (REA), backfat thickness (BF), intramuscular fat score, and carcass conformation score] traits were included in the study. After data editing, records from 1 393 heifers obtained between 2009 and 2018 were used for the analyses. We fitted an animal model that included contemporary group (animals from the same farm that were evaluated in the same test season) as the fixed effect, and a linear effect of animal age at the beginning of the test as a covariate; in addition to random direct additive genetic and residual effects. The (co)variance components were estimated by Bayesian inference in uni- and bivariate analyses. Our results showed that feed efficiency indicators derived from residual variables such as RG, RIG, and RFI can be improved through genetic selection (h² = 0.14 ± 0.06, 0.13 ± 0.06, and 0.20 ± 0.08, respectively). Variables calculated as ratios such as G:F and FCR were more influenced by environmental factors (h² = 0.08 ± 0.05 and 0.09 ± 0.05), and were, therefore, less suitable for use in breeding programs. The traits with the greatest and impact on genetic progress in feed efficiency were ADG, REA, and BF. The traits with the greatest and least impact on growth and carcass traits were RG and RFI, respectively. Selection for feed efficiency will result in distinct overall effects on the growth and carcass traits of Senepol heifers. Direct selection for lower RFI may reduce DMI and increase carcass fatness at the finishing stage, but it might also result in reduced growth and muscle deposition. Residual BW gain is associated with the highest weight gain and zero impact on REA and BF, however, it is linked to higher feed consumption. Thus, the most suitable feed efficiency indicator was RIG, as it promoted the greatest decrease in feed intake concomitant with faster growth, with a similar impact on carcass traits when compared to the other feed efficiency indicators.

Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows

MOTIVATION

Enhancing the utilization of human-inedible crop by-products by ruminants to produce high-quality milk for human consumption is an emerging global task. We performed a multi-omics-based study to decipher the regulatory biological processes of milk production when cows fed low-quality crop by-products with the aim to improve their utilization.

RESULTS

Seven types of different high-throughput omics data were generated across three central organs [rumen, liver and mammary gland (MG)] and biofluids (rumen fluid and blood) that involved in milk production. The integrated multi-omics analysis including metabolomics, metagenomics and transcriptomics showed altered microbiome at compositional and functional levels, microbial metabolites in the rumen, down-regulated genes and associated functions in liver and MG. These changes simultaneously contributed to down-regulated three key metabolic nodes (propionate, glucose and amino acid) across these organs and biofluids that led to lowered milk yield and quality when cows consumed corn stover (CS). Hippuric acid was identified as a biomarker that led to low milk production in CS-fed cows, suggesting a future evaluation parameter related to the metabolic mechanism of low-quality forage utilization. This study unveils the milk production-related biological mechanism across different biofluids and tissues under a low-quality forage diet, which provides a novel understanding and potential improvement strategies for future crop by-products utilization and sustainable ruminant production.

AVAILABILITY AND IMPLEMENTATION

The raw files of metagenomics, metabolomics, and transcriptomics data can be accessed at NCBI SRA (No. SRR5028206), EMBI-EBI (No. MTBLS411), and GEO (NO. GSE78524) databases respectively.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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

Increasing the healthy/unhealthy fatty acid (FA) ratio in meat is one of the urgent tasks required to address consumer concerns. However, the regulatory mechanisms ultimately resulting in FA profiles vary among animals and remain largely unknown. In this study, using ~1.2 Tb high-quality RNA-Seq-based transcriptomic data of 188 samples from four key metabolic tissues (rumen, liver, muscle, and backfat) together with the contents of 49 FAs in backfat, the molecular regulatory mechanisms of these tissues contributing to FA formation in cattle were explored. Using this large dataset, the alternative splicing (AS) events, one of the transcriptional regulatory mechanisms in four tissues were identified. The highly conserved and absent AS events were detected in rumen tissue, which may contribute to its functional differences compared with the other three tissues. In addition, the healthy/unhealthy FA ratio related AS events, differential expressed (DE) genes, co-expressed genes, and their functions in four tissues were analysed. Eight key genes were identified from the integrated analysis of DE, co-expressed, and AS genes between animals with high and low healthy/unhealthy FA ratios. This study provides an applicable pipeline for AS events based on comprehensive RNA-Seq analysis and improves our understanding of the regulatory mechanism of FAs in beef cattle.

Biological Network Approach for the Identification of Regulatory Long Non-Coding RNAs Associated With Metabolic Efficiency in Cattle

Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle. Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F₂-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set. Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.