Systems Biology Reveals NR2F6 and TGFB1 as Key Regulators of Feed Efficiency in Beef Cattle

Insights into the emerging immune checkpoint NR2F6 in cancer immunity

NR2F6 has emerged as a key player in immune regulation, especially in cancer immunity. It has been reported that NR2F6 could suppress the antitumor immune response and has therefore been suggested as a possible target in cancer immunotherapy. In this review, we start by describing the complex structure of the NR2F6 gene and its multifaceted biological functions. Then, we examine its expression in distinct immune cells and cancer cells, elucidating its role in cancer progression. Subsequently, we highlight the predictive significance of NR2F6 for cancer patient outcomes, suggesting its possible use as a prognostic biomarker. Finally, we discuss the emerging potential of NR2F6 as a therapeutic target, presenting novel opportunities for developing effective cancer immunotherapy strategies.

Identification of biological pathways and putative candidate genes for residual feed intake in a tropically adapted beef cattle breed by plasma proteome analysis

This study identified potential biomarkers for feed efficiency by blood plasma proteome analysis of a tropically adapted beef cattle breed. Two experimental groups were selected based on residual feed intake (RFI). The proteome was investigated by LC-MS/MS in a data-dependent acquisition mode. After quality control, 123 differentially abundant proteins (DAPs) were identified between the two experimental groups. Among DAPs with the highest absolute log-fold change values, the PRDM2, KRT5, UGGT1, DENND5B, B2M, SLC44A2, SLC7A2, PTPRC, and FETUB were highlighted as potential biomarkers because of their functions that may contribute to RFI. Furthermore, functional enrichment analysis revealed several biological processes, molecular functions and pathways that contributes to RFI, such as cell signaling, cellular responses to stimuli, immune system, calcium, hormones, metabolism and functions of proteins, lipids and carbohydrates. Protein-protein interaction analysis identified 32 and 11 DAPs as important nodes based on their interactions in the high- and low-RFI groups, respectively. This study represents the first comprehensive profiling of the blood plasma proteome of a tropically adapted beef cattle breed and provides valuable insights into the potential roles of these DAPs in key biological processes and pathways, contributing to our understanding of the mechanisms underlying feed efficiency in tropically adapted beef cattle. SIGNIFICANCE: LC-MS/MS analysis was performed to investigate changes in the blood plasma proteome associated with residual feed intake (RFI) in a tropically adapted beef cattle breed (Bos taurus taurus). Some putative biomarkers were identified to distinguish the high-RFI to low-RFI animals, based on their log-fold change value or on their protein-protein interaction network, which provide helpful sources in developing novel selection strategies for breeding programs. Our findings also revealed valuable insights into the metabolic pathways and biological processes that contribute to RFI in beef cattle, such as those closely linked to cell signaling, cellular responses to stimuli, immune system, calcium, hormones, metabolism and functions of proteins, lipids and carbohydrates.

A high-resolution bovine mitochondrial co-expression network

The mitochondrion is a sophisticated, versatile, and dynamic organelle whose function is incompletely understood. Intending to provide a framework for mitochondrial visualisation and interpretation of genome-wide molecular data, we reverse-engineered a co-expression network whose final structure represented mRNA encoding more than half of the entire mitochondrial proteome. We drew upon 723 RNA-seq data sets representing 91 tissues and cell types from 441 individual cattle. A mitochondrial landscape was formed comprising a main network and many smaller sub-networks. One of the discrete sub-networks contains all 13 mRNA (e.g. MT-ND1, MT -CYTB, MT -COX2, MT -ATP8) plus 15/22 tRNA (e.g. MT-TT) encoded by the mt-genome itself, indicating some independent regulation from the nuclear genome with whom it must cooperate. Intriguingly, this mtDNA sub-network also contains a single nuclear-encoded gene, that of PDHA1. PDHA1 encodes a subunit of the pyruvate dehydrogenase complex that governs the conversion of pyruvate to Acetyl CoA. This enzyme is extremely influential, representing the fundamental cellular connection between the ancient, conserved pathway of glycolysis that occurs exclusively in the cytoplasm, and the TCA cycle that occurs within the mitochondrial matrix. To demonstrate the downstream utility of our approach, we overlaid Longissimus dorsi muscle transcriptome data from differentially feed efficient Charolais and Holstein Friesian cattle. This approach highlighted expression patterns sensitive to both breed and diet in a complex manner. An analytic advantage of this approach is that relatively subtle (<2-fold) but coordinated changes that may be overlooked by conventional gene-by-gene significance testing become readily apparent. Finally, intending to understand the transcriptional regulation of mitochondrial function more thoroughly, we engineered a network built with transcription factors in addition to those mRNA encoding mitochondrial proteins. Here, a set of influential nuclear hormone receptors (e.g. PPARA) are enriched among the most highly and/or well-connected TF.

Single-Step Genome-Wide Association Study of Factors for Evaluated and Linearly Scored Traits in Swedish Warmblood Horses

Swedish Warmblood horses (SWB) are bred for show jumping and/or dressage with young horse test scores as indicator traits. This study aimed to investigate possible candidate genes and regions of importance for evaluated and linearly scored young horse test traits. A single-step genome-wide association study (ssGWAS) was done using the BLUPF90 suite of programs for factors scores from factor analysis of traits assessed at young horse tests together with height at withers. The ssGWAS included 20,814 SWB with factors scores for four factors for evaluated traits. A total of 6436 of these horses also had factor scores for 13 factors for linearly scored traits. Genotypes from a 670K SNP array were available for 380 of the horses in this study. All genotyped horses had factor scores for evaluated traits, and 379 also had factors scores for linearly scored traits. Significant SNPs associated with three factors related to size were located on ECA3 within or nearby a well-known region, including the genes ligand dependent nuclear receptor corepressor like (LCORL), non-SMC condensin I complex subunit G (NCAPG), DDB1 and CUL4 Associated Factor 16 (DCAF16), and the Family with Sequence Similarity 184 Member B (FAM184B). Significant SNPs were also detected for two factors for evaluated traits representing conformation and jumping, and four factors for linearly scored traits related to body length, neck conformation, walk and trot (hindleg position and activity), respectively. Among nearby genes, calcium/calmodulin-dependent protein kinase type 1D (CAMK1D) for the factor for linearly scored traits related to neck conformation and GLI Family Zinc Finger 2 (GLI2) for the factor for evaluated jumping traits, were most promising. For these, top associated SNPs were detected within the genes, and the known gene functions seems to be related to the phenotypes. In conclusion, ssGWAS is beneficial to detect plausible candidate genes/regions for desired traits in warmblood horses.

Unraveling Ruminant Feed Efficiency Through Metabolomics: A Systematic Review

BACKGROUND

Advancements in metabolomic technologies have revolutionized our understanding of feed efficiency (FE) in livestock, offering new pathways to enhance both profitability and sustainability in ruminant production.

METHODS

This review offers a critical and systematic evaluation of the metabolomics methods used to measure and assess FE in ruminants. We conducted a comprehensive search of PubMed, Web of Science, and Scopus databases, covering publications from 1971 to 2023. This review synthesizes findings from 71 studies that applied metabolomic approaches to uncover the biological mechanisms driving interindividual variations in FE across cattle, sheep, goats, and buffaloes.

RESULTS

Most studies focused on cattle and employed targeted metabolomics to identify key biomarkers, including amino acids, fatty acids, and other metabolites linked to critical pathways such as energy metabolism, nitrogen utilization, and muscle development. Despite promising insights, challenges remain, including small sample sizes, methodological inconsistencies, and a lack of validation studies, particularly for non-cattle species.

CONCLUSIONS

By leveraging state-of-the-art metabolomic methods, this review highlights the potential of metabolomics to provide cost-effective, non-invasive molecular markers for FE evaluation, paving the way for more efficient and sustainable livestock management. Future research should prioritize larger, species-specific studies with standardized methods to validate identified biomarkers and enhance practical applications in livestock production systems.

Relationship between the rumen microbiome and liver transcriptome in beef cattle divergent for feed efficiency

BACKGROUND

Feed costs account for a high proportion of the variable cost of beef production, ultimately impacting overall profitability. Thus, improving feed efficiency of beef cattle, by way of determining the underlying genomic control and selecting for feed efficient cattle provides a method through which feed input costs may be reduced whilst also contributing to the environmental sustainability of beef production. The rumen microbiome dictates the feed degradation capacity and consequent nutrient supply in ruminants, thus potentially impacted by feed efficiency phenotype. Equally, liver tissue has been shown to be responsive to feed efficiency phenotype as well as dietary intake. However, although both the rumen microbiome and liver transcriptome have been shown to be impacted by host feed efficiency phenotype, knowledge of the interaction between the rumen microbiome and other peripheral tissues within the body, including the liver is lacking. Thus, the objective of this study was to compare two contrasting breed types (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI) over contrasting dietary phases (zero-grazed grass and high-concentrate), based on gene co-expression network analysis of liver transcriptome data and microbe co-abundance network of rumen microbiome data. Traits including RFI, dry matter intake (DMI) and growth rate (ADG), as well as rumen concentrations of volatile fatty acids were also included within the network analysis.

RESULTS

Overall, DMI had the greatest number of connections followed by RFI, with ADG displaying the fewest number of significant connections. Hepatic genes related to lipid metabolism were correlated to both RFI and DMI phenotypes, whilst genes related to immune response were correlated to DMI. Despite the known relationship between RFI and DMI, the same microbes were not directly connected to these phenotypes, the Succiniclasticum genus was however, negatively connected to both RFI and ADG. Additionally, a stepwise regression analysis revealed significant roles for both Succiniclasticum genus and Roseburia.faecis sp. in predicting RFI, DMI and ADG.

CONCLUSIONS

Results from this study highlight the interactive relationships between rumen microbiome and hepatic transcriptome data of cattle divergent for RFI, whilst also increasing our understanding of the underlying biology of both DMI and ADG in beef cattle.

Effect of breed and dietary composition on the miRNA profile of beef steers divergent for feed efficiency

Identifying and breeding cattle that are more feed efficient is of great benefit to beef production. Additionally, it is crucial that genes contributing to feed efficiency are robust across varying management settings including dietary source as well as being relevant across contrasting breeds of cattle. The aim of this study was to determine miRNAs that are contributing to the expression of residual feed intake (RFI) across two breeds and dietary sources. miRNA profiling was undertaken in Longissimus dorsi tissue of Charolais and Holstein-Friesian steers divergent for RFI phenotype following two contrasting consecutive diets (high-forage and high-concentrate). Ten miRNA were identified as differentially expressed (adj. P < 0.1) across the breed and diet contrasts examined. Of particular interest was the differential expression of miR-2419-5p and miR-2415-3p, both of which were up-regulated in the Low-RFI Charolais steers across each dietary phase. Pathway analysis of target mRNA genes of differentially expressed miRNA revealed enrichment (P < 0.05) for pathways including metabolic related pathways, insulin receptor signalling, adipogenesis as well as pathways related to skeletal muscle growth. These results provide insight into the skeletal muscle miRNAome of beef cattle and their potential molecular regulatory mechanisms relating to feed efficiency in beef cattle.

Genes involved in the cholecystokinin receptor signaling map were differentially expressed in the jejunum of steers with variation in residual feed intake

The jejunum is a critical site for nutrient digestion and absorption, and variation in its ability to take up nutrients within the jejunum is likely to affect feed efficiency. The purpose of this study was to determine differences in gene expression in the jejunum of beef steers divergent for residual feed intake (RFI) in one cohort of steers (Year 1), and to validate those genes in animals from a second study (Year 2). Steers from Year 1 (n = 16) were selected for high and low RFI. Jejunum mucosal tissue was obtained for RNA-seq. Thirty-two genes were differentially expressed (PFDR≤0.15), and five were over-represented in pathways including inflammatory mediator, cholecystokinin receptor (CCKR) signaling, and p38 MAPK pathways. Several differentially expressed genes (ALOX12, ALPI, FABP6, FABP7, FLT1, GSTA2, MEF2B, PDK4, SPP1, and TTF2) have been previously associated with RFI in other studies. Real-time qPCR was used to validate nine differentially expressed genes in the Year 1 steers used for RNA-seq, and in the Year 2 validation cohort. Six genes were validated as differentially expressed (P < 0.1) using RT-qPCR in the Year 1 population. In the Year 2 population, five genes displayed the same direction of expression as the Year 1 population and 3 were differentially expressed (P < 0.1). The CCKR pathway is involved in digestion, appetite control, and regulation of body weight making it a compelling candidate for feed efficiency in cattle, and the validation of these genes in a second population of cattle is suggestive of a role in feed efficiency.

An across breed, diet and tissue analysis reveals the transcription factor NR1H3 as a key mediator of residual feed intake in beef cattle

BACKGROUND

Provision of feed is a major determinant of overall profitability in beef production systems, accounting for up to 75% of the variable costs. Thus, improving cattle feed efficiency, by way of determining the underlying genomic control and subsequently selecting for feed efficient cattle, provides a method through which feed input costs may be reduced. The objective of this study was to undertake gene co-expression network analysis using RNA-Sequence data generated from Longissimus dorsi and liver tissue samples collected from steers of two contrasting breeds (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI), across two consecutive distinct dietary phases (zero-grazed grass and high-concentrate). Categories including differentially expressed genes (DEGs) based on the contrasts of RFI phenotype, breed and dietary source, as well as key transcription factors and proteins secreted in plasma were utilised as nodes of the gene co-expression network.

RESULTS

Of the 2,929 DEGs within the network analysis, 1,604 were reported to have statistically significant correlations (≥ 0.80), resulting in a total of 43,876 significant connections between genes. Pathway analysis of clusters of co-expressed genes revealed enrichment of processes related to lipid metabolism (fatty acid biosynthesis, fatty acid β-oxidation, cholesterol biosynthesis), immune function, (complement cascade, coagulation system, acute phase response signalling), and energy production (oxidative phosphorylation, mitochondrial L-carnitine shuttle pathway) based on genes related to RFI, breed and dietary source contrasts.

CONCLUSIONS

Although similar biological processes were evident across the three factors examined, no one gene node was evident across RFI, breed and diet contrasts in both liver and muscle tissues. However within the liver tissue, the IRX4, NR1H3, HOXA13 and ZNF648 gene nodes, which all encode transcription factors displayed significant connections across the RFI, diet and breed comparisons, indicating a role for these transcription factors towards the RFI phenotype irrespective of diet and breed. Moreover, the NR1H3 gene encodes a protein secreted into plasma from the hepatocytes of the liver, highlighting the potential for this gene to be explored as a robust biomarker for the RFI trait in beef cattle.

A network-based approach to understanding gene-biological processes affecting economically important traits of Nelore cattle

This study aimed to build gene-biological process networks with differentially expressed genes associated with economically important traits of Nelore cattle from 17 previous studies. The genes were clustered into three groups by evaluated traits: group 1, production traits; group 2, carcass traits; and group 3, meat quality traits. For each group, a gene-biological process network analysis was performed with the differentially expressed genes in common. For production traits, 37 genes were found in common, of which 13 genes were enriched for six Gene Ontology (GO) terms; these terms were not functionally grouped. However, the enriched GO terms were related to homeostasis, the development of muscles and the immune system. For carcass traits, four genes were found in common. Thus, it was not possible to functionally group these genes into a network. For meat quality traits, the analysis revealed 222 genes in common. CSRP3 was the only gene differentially expressed in all three groups. Non-redundant biological terms for clusters of genes were functionally grouped networks, reflecting the cross-talk between all biological processes and genes involved. Many biological processes and pathways related to muscles, the immune system and lipid metabolism were enriched, such as striated muscle cell development and triglyceride metabolic processes. This study provides insights into the genetic mechanisms of production, carcass and meat quality traits of Nelore cattle. This information is fundamental for a better understanding of the complex traits and could help in planning strategies for the production and selection systems of Nelore cattle.

Gene co-expression in response to Staphylococcus aureus infection reveals networks of genes with specific functions during bovine subclinical mastitis

Staphylococcus aureus is one of the most prevalent contagious bacterial pathogen of bovine mastitis. The subclinical mastitis it causes has long-term economic implications and it is difficult to control. To further understanding of the genetic basis of mammary gland defense against S. aureus infection, the transcriptomes of milk somatic cells from 15 cows with persistent natural S. aureus infection (S. aureus-positive, SAP) and 10 healthy control cows (HC) were studied by deep RNA-sequencing technology. Comparing the transcriptomes of SAP to HC group revealed 4,077 differentially expressed genes (DEG; 1,616 up- and 2,461 downregulated). Functional annotation indicated enrichment of DEG in 94 Gene Ontology (GO) and 47 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Terms related to the immune response and disease processes were mostly enriched for by upregulated DEG, whereas biological process terms related to cell adhesion, cell movement and localization, and tissue development were mostly enriched for by downregulated DEG. Weighted gene co-expression network analysis grouped DEG into 7 modules, the most important module (colored turquoise by software and here referred to as Turquoise module) was positively significantly correlated with S. aureus subclinical mastitis. The 1,546 genes in the Turquoise module were significantly enriched in 48 GO terms and 72 KEGG pathways, with 80% of them being disease- and immune-related terms [e.g., immune system process (GO:0002376), cytokine-cytokine receptor interaction (bta04060) and S. aureus infection (bta05150)]. Some DEG such as IFNG, IL18, IL1B, NFKB1, CXCL8, and IL12B were enriched in immune and disease pathways suggesting their possible involvement in the regulation of the host response to S. aureus infection. Four modules (Yellow, Brown, Blue, and Red) were negatively correlated (significantly) with S. aureus subclinical mastitis, and were enriched in functional annotations involved in the regulation of cell migration, cell communication, metabolic process, and blood circulatory system development, respectively. Application of sparse partial least squares discriminant analysis to genes of the Turquoise module identified 5 genes (NR2F6, PDLIM5, RAB11FIP5, ACOT4, and TMEM53) capable of explaining the majority of the differences in the expression patterns between SAP and HC cows. In conclusion, this study has furthered understanding of the genetic changes in the mammary gland and the molecular mechanisms underlying S. aureus mastitis, as well as revealed a list of candidate discriminant genes with potential regulatory roles in response to S. aureus infection.

Candidate Genes and Gene Networks Change with Age in Japanese Black Cattle by Blood Transcriptome Analysis

Age is an important physiological factor that affects the metabolism and immune function of beef cattle. While there have been many studies using the blood transcriptome to study the effects of age on gene expression, few have been reported on beef cattle. To this end, we used the blood transcriptomes of Japanese black cattle at different ages as the study subjects and screened 1055, 345, and 1058 differential expressed genes (DEGs) in the calf vs. adult, adult vs. old, and calf vs. old comparison groups, respectively. The weighted co-expression network consisted of 1731 genes. Finally, blue, brown, and yellow age-specific modules were obtained, in which genes were enriched in signaling pathways related to growth and development and immune metabolic dysfunction, respectively. Protein-protein interaction (PPI) analysis showed gene interactions in each specific module, and 20 of the highest connectivity genes were chosen as potential hub genes. Finally, we identified 495, 244, and 1007 genes by exon-wide selection signature (EWSS) analysis of different comparison groups. Combining the results of hub genes, we found that VWF, PARVB, PRKCA, and TGFB1I1 could be used as candidate genes for growth and development stages of beef cattle. CORO2B and SDK1 could be used as candidate marker genes associated with aging. In conclusion, by comparing the blood transcriptome of calves, adult cattle, and old cattle, the candidate genes related to immunity and metabolism affected by age were identified, and the gene co-expression network of different age stages was constructed. It provides a data basis for exploring the growth, development, and aging of beef cattle.

Multi-breed genomic predictions and functional variants for fertility of tropical bulls

Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.

Network analysis reveals different hub genes and molecular pathways for pig in vitro fertilized early embryos and parthenogenotes

Maternal-to-zygotic transition (MZT) occurs when maternal transcripts decay and zygotic genome is activated gradually at early stage of embryo development. Previously, single cell RNA-seq (scRNA-seq) has helped us to uncover the MZT-associated mRNA dynamics of in vitro produced pig early embryos. Here, to further investigate functional modules and hub genes associated with MZT process, the weighted gene-coexpression network analysis (WGCNA) was performed on our previously generated 45 scRNA-seq datasets. For the in vitro fertilized embryo (IVF) group, 5 significant modules were identified (midnightblue/black/red and blue/brown modules, positively correlated with 1-cell (IVF1) and 8-cell (IVF8), respectively), containing genes mainly enriched in signaling pathways such as Wnt, regulation of RNA transcription, fatty acid metabolic process, poly(A) RNA binding and lysosome. For the parthenogenetically activated embryo (PA) group, 9 significant modules were identified (black/purple/red, brown/turquoise/yellow, and magenta/blue/green modules, positively correlated with MII oocytes, 1-cell (PA1), and 8-cell (PA8), respectively), mainly enriched in extracellular exosome, poly(A) RNA binding, mitochondrion, transcription factor activity. Moreover, some of identified hub genes within 3 IVF and 9 PA significant modules, including ADCY2, DHX34, KDM4A, GDF10, ABCC10, PAFAH2, HEXIM2, COQ9, DCAF11, SGK1, ESRRB etc., have been reported to play vital roles in different biological processes. Our findings provide information and resources for subsequent in-depth study on the regulation and function of MZT in pig embryos.

Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits

Background

Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population).

Results

The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle.

Conclusions

Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08671-w.

Leveraging transcriptome and epigenome landscapes to infer regulatory networks during the onset of sexual maturation

Background

Despite sexual development being ubiquitous to vertebrates, the molecular mechanisms underpinning this fundamental transition remain largely undocumented in many organisms. We designed a time course experiment that successfully sampled the period when Atlantic salmon commence their trajectory towards sexual maturation.

Results

Through deep RNA sequencing, we discovered key genes and pathways associated with maturation in the pituitary-ovarian axis. Analyzing DNA methylomes revealed a bias towards hypermethylation in ovary that implicated maturation-related genes. Co-analysis of DNA methylome and gene expression changes revealed chromatin remodeling genes and key transcription factors were both significantly hypermethylated and upregulated in the ovary during the onset of maturation. We also observed changes in chromatin state landscapes that were strongly correlated with fundamental remodeling of gene expression in liver. Finally, a multiomic integrated analysis revealed regulatory networks and identified hub genes including TRIM25 gene (encoding the estrogen-responsive finger protein) as a putative key regulator in the pituitary that underwent a 60-fold change in connectivity during the transition to maturation.

Conclusion

The study successfully documented transcriptome and epigenome changes that involved key genes and pathways acting in the pituitary – ovarian axis. Using a Systems Biology approach, we identified hub genes and their associated networks deemed crucial for onset of maturation. The results provide a comprehensive view of the spatiotemporal changes involved in a complex trait and opens the door to future efforts aiming to manipulate puberty in an economically important aquaculture species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08514-8.

Chromatin accessibility and regulatory vocabulary across indicine cattle tissues

BACKGROUND

Spatiotemporal changes in the chromatin accessibility landscape are essential to cell differentiation, development, health, and disease. The quest of identifying regulatory elements in open chromatin regions across different tissues and developmental stages is led by large international collaborative efforts mostly focusing on model organisms, such as ENCODE. Recently, the Functional Annotation of Animal Genomes (FAANG) has been established to unravel the regulatory elements in non-model organisms, including cattle. Now, we can transition from prediction to validation by experimentally identifying the regulatory elements in tropical indicine cattle. The identification of regulatory elements, their annotation and comparison with the taurine counterpart, holds high promise to link regulatory regions to adaptability traits and improve animal productivity and welfare.

RESULTS

We generate open chromatin profiles for liver, muscle, and hypothalamus of indicine cattle through ATAC-seq. Using robust methods for motif discovery, motif enrichment and transcription factor binding sites, we identify potential master regulators of the epigenomic profile in these three tissues, namely HNF4, MEF2, and SOX factors, respectively. Integration with transcriptomic data allows us to confirm some of their target genes. Finally, by comparing our results with Bos taurus data we identify potential indicine-specific open chromatin regions and overlaps with indicine selective sweeps.

CONCLUSIONS

Our findings provide insights into the identification and analysis of regulatory elements in non-model organisms, the evolution of regulatory elements within two cattle subspecies as well as having an immediate impact on the animal genetics community in particular for a relevant productive species such as tropical cattle.

Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data

Machine learning (ML) methods have shown promising results in identifying genes when applied to large transcriptome datasets. However, no attempt has been made to compare the performance of combining different ML methods together in the prediction of high feed efficiency (HFE) and low feed efficiency (LFE) animals. In this study, using RNA sequencing data of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle, and pituitary) from nine HFE and nine LFE Nellore bulls, we evaluated the prediction accuracies of five analytical methods in classifying FE animals. These included two conventional methods for differential gene expression (DGE) analysis (t-test and edgeR) as benchmarks, and three ML methods: Random Forests (RFs), Extreme Gradient Boosting (XGBoost), and combination of both RF and XGBoost (RX). Utility of a subset of candidate genes selected from each method for classification of FE animals was assessed by support vector machine (SVM). Among all methods, the smallest subsets of genes (117) identified by RX outperformed those chosen by t-test, edgeR, RF, or XGBoost in classification accuracy of animals. Gene co-expression network analysis confirmed the interactivity existing among these genes and their relevance within the network related to their prediction ranking based on ML. The results demonstrate a great potential for applying a combination of ML methods to large transcriptome datasets to identify biologically important genes for accurately classifying FE animals.

Cerebrum, liver, and muscle regulatory networks uncover maternal nutrition effects in developmental programming of beef cattle during early pregnancy

The molecular basis underlying fetal programming in response to maternal nutrition remains unclear. Herein, we investigated the regulatory relationships between genes in fetal cerebrum, liver, and muscle tissues to shed light on the putative mechanisms that underlie the effects of early maternal nutrient restriction on bovine developmental programming. To this end, cerebrum, liver, and muscle gene expression were measured with RNA-Seq in 14 fetuses collected on day 50 of gestation from dams fed a diet initiated at breeding to either achieve 60% (RES, n = 7) or 100% (CON, n = 7) of energy requirements. To build a tissue-to-tissue gene network, we prioritized tissue-specific genes, transcription factors, and differentially expressed genes. Furthermore, we built condition-specific networks to identify differentially co-expressed or connected genes. Nutrient restriction led to differential tissue regulation between the treatments. Myogenic factors differentially regulated by ZBTB33 and ZNF131 may negatively affect myogenesis. Additionally, nutrient-sensing pathways, such as mTOR and PI3K/Akt, were affected by gene expression changes in response to nutrient restriction. By unveiling the network properties, we identified major regulators driving gene expression. However, further research is still needed to determine the impact of early maternal nutrition and strategic supplementation on pre- and post-natal performance.

Upstream Regulator Analysis of Wooden Breast Myopathy Proteomics in Commercial Broilers and Comparison to Feed Efficiency Proteomics in Pedigree Male Broilers

In an effort to understand the apparent trade-off between the continual push for growth performance and the recent emergence of muscle pathologies, shotgun proteomics was conducted on breast muscle obtained at ~8 weeks from commercial broilers with wooden breast (WB) myopathy and compared with that in pedigree male (PedM) broilers exhibiting high feed efficiency (FE). Comparison of the two proteomic datasets was facilitated using the overlay function of Ingenuity Pathway Analysis (IPA) (Qiagen, CA, USA). We focused on upstream regulator analysis and disease-function analysis that provides predictions of activation or inhibition of molecules based on (a) expression of downstream target molecules, (b) the IPA scientific citation database. Angiopoeitin 2 (ANGPT2) exhibited the highest predicted activation Z-score of all molecules in the WB dataset, suggesting that the proteomic landscape of WB myopathy would promote vascularization. Overlaying the FE proteomics data on the WB ANGPT2 upstream regulator network presented no commonality of protein expression and no prediction of ANGPT2 activation. Peroxisome proliferator coactivator 1 alpha (PGC1α) was predicted to be inhibited, suggesting that mitochondrial biogenesis was suppressed in WB. PGC1α was predicted to be activated in high FE pedigree male broilers. Whereas RICTOR (rapamycin independent companion of mammalian target of rapamycin) was predicted to be inhibited in both WB and FE datasets, the predictions were based on different downstream molecules. Other transcription factors predicted to be activated in WB muscle included epidermal growth factor (EGFR), X box binding protein (XBP1), transforming growth factor beta 1 (TGFB1) and nuclear factor (erythroid-derived 2)-like 2 (NFE2L2). Inhibitions of aryl hydrocarbon receptor (AHR), AHR nuclear translocator (ARNT) and estrogen related receptor gamma (ESRRG) were also predicted in the WB muscle. These findings indicate that there are considerable differences in upstream regulators based on downstream protein expression observed in WB myopathy and in high FE PedM broilers that may provide additional insight into the etiology of WB myopathy.

Brain Transcriptome Analysis Reveals Potential Transcription Factors and Biological Pathways Associated with Feed Efficiency in Commercial DLY Pigs

Feed efficiency (FE) is one of the most important economic traits in the porcine industry. In this study, high-throughput RNA sequencing (RNA-seq) was first utilized for brain tissue transcriptome analysis in pigs to indicate the potential genes and biological pathways related to FE in pigs. A total of 8 pigs with either extremely high-FE group (HE-group) or low-FE group (LE-group) were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs for transcriptomic analysis. RNA-seq analysis was performed to determine differentially expressed genes (DEGs) between the HE- and LE-group, and 430 DEGs were identified in brain tissues of pigs (|log₂(FoldChange)| > 1; adjusted p-values <0.05). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEGs were mainly enriched in synaptic signaling or transmission, and hormone secretion pathways, in which insulin secretion, and oxytocin signaling pathways were closely associated with FE by regulating feeding behavior and energy metabolism (adjusted p-values <0.05). Further, the transcription factors (TFs) analysis and gene co-expression network analysis indicated three hub differentially expressed TFs (NR2F2, TFAP2D, and HNF1B) that affected FE by mainly regulating feeding behavior, insulin sensitivity, or energy metabolism. Our findings suggest several potential TFs and biological pathways for further investigations of FE in pigs.

Whole Transcriptome Analysis Identifies the Taxonomic Status of a New Chinese Native Cattle Breed and Reveals Genes Related to Body Size

Wandong (WD) cattle has recently been identified as a new Chinese native cattle breed by the National Commission for Livestock and Poultry Genetic Resources. The population size of this breed is less than 10,000. WD cattle and Dabieshan (DB) cattle are sympatric but are raised in different ecological environments, on mountains and plains, respectively, and the body sizes of these two breeds are markedly different. Blood samples were obtained from 8 adult female WD cattle and 7 adult female DB cattle (24 months old). The total RNA was extracted from leukocyte cells, and sequencing experiments were conducted on the Illumina HiSeq^TM 4000 platform. After the removal of one outlier sample from the WD cattle breed as determined by principal component analysis (PCA), phylogenetic and population structure analyses indicated that WD and DB cattle formed a distinct Central China cattle group and showed evidence of hybridization between Bos. taurus and Bos. indicus. The immune-regulator CD48 (P = 1.3E-6) was associated with breed-specific traits according to loss-of-function variant enrichment analysis. In addition, 113 differentially expressed genes were identified between the two breeds, many of which are associated with the regulation of body growth, which is the major difference between the two breeds. This study showed that WD cattle belong to the group of hybrids between Bos. Taurus and Bos. indicus, and one novel gene associated with breed traits and multiple differentially expressed genes between these two closely related breeds was identified. The results provide insights into the genetic mechanisms that underlie economically important traits, such as body size, in cattle.

Genome-Wide Co-Expression Distributions as a Metric to Prioritize Genes of Functional Importance

Genome-wide gene expression analysis are routinely used to gain a systems-level understanding of complex processes, including network connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we developed a computational pipeline to assign to every gene its pair-wise genome-wide co-expression distribution to one of 8 template distributions shapes varying between unimodal, bimodal, skewed, or symmetrical, representing different proportions of positive and negative correlations. We then used a hypergeometric test to determine if specific genes (regulators versus non-regulators) and properties (differentially expressed or not) are associated with a particular distribution shape. We applied our methodology to five publicly available RNA sequencing (RNA-seq) datasets from four organisms in different physiological conditions and tissues. Our results suggest that genes can be assigned consistently to pre-defined distribution shapes, regarding the enrichment of differential expression and regulatory genes, in situations involving contrasting phenotypes, time-series, or physiological baseline data. There is indeed a striking additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Our method can be applied to extract further information from transcriptomic data and help uncover the molecular mechanisms involved in the regulation of complex biological process and phenotypes.

Exploring the Regulatory Potential of Long Non-Coding RNA in Feed Efficiency of Indicine Cattle

Long non-coding RNA (lncRNA) can regulate several aspects of gene expression, being associated with complex phenotypes in humans and livestock species. In taurine beef cattle, recent evidence points to the involvement of lncRNA in feed efficiency (FE), a proxy for increased productivity and sustainability. Here, we hypothesized specific regulatory roles of lncRNA in FE of indicine cattle. Using RNA-Seq data from the liver, muscle, hypothalamus, pituitary gland and adrenal gland from Nellore bulls with divergent FE, we submitted new transcripts to a series of filters to confidently predict lncRNA. Then, we identified lncRNA that were differentially expressed (DE) and/or key regulators of FE. Finally, we explored lncRNA genomic location and interactions with miRNA and mRNA to infer potential function. We were able to identify 126 relevant lncRNA for FE in Bos indicus, some with high homology to previously identified lncRNA in Bos taurus and some possible specific regulators of FE in indicine cattle. Moreover, lncRNA identified here were linked to previously described mechanisms related to FE in hypothalamus-pituitary-adrenal axis and are expected to help elucidate this complex phenotype. This study contributes to expanding the catalogue of lncRNA, particularly in indicine cattle, and identifies candidates for further studies in animal selection and management.

Regulating appetite in broilers for improving body and muscle development - A review

Appetite is the desire for feed and water and the voluntary intake of feed and is an important regulator of livestock productivity and animal health. Economic traits such as growth rate and muscle development (meat deposition) in broilers are directly correlated to appetite. Factors that may influence appetite include environmental factors, such as stress and temperature variation, and animal‐specific factors, such as learning period, eating capacity and preferences. Feed preferences have been reported to be determined in early life, and this period is important in broilers due to their fast growth and relatively short growth trajectories. This may be of importance when contemplating the use of more circular and sustainable feeds and the optimization of appetite for these feeds. The objective of this review was to review the biological mechanisms underlying appetite using data from human, animal and bird models and to consider the option for modulating appetite particularly as it relates to broiler chickens.

Common Gene Modules Identified for Chicken Adiposity by Network Construction and Comparison

Excessive fat deposition can cause chicken health problem, and affect production efficiency by causing great economic losses to the industry. However, the molecular underpinnings of the complex adiposity trait remain elusive. In the current study, we constructed and compared the gene co-expression networks on four transcriptome profiling datasets, from two chicken lines under divergent selection for abdominal fat contents, in an attempt to dissect network compositions underlying adipose tissue growth and development. After functional enrichment analysis, nine network modules important to adipogenesis were discovered to be involved in lipid metabolism, PPAR and insulin signaling pathways, and contained hub genes related to adipogenesis, cell cycle, inflammation, and protein synthesis. Moreover, after additional functional annotation and network module comparisons, common sub-modules of similar functionality for chicken fat deposition were identified for different chicken lines, apart from modules specific to each chicken line. We further validated the lysosome pathway, and found TFEB and its downstream target genes showed similar expression patterns along with chicken preadipocyte differentiation. Our findings could provide novel insights into the genetic basis of complex adiposity traits, as well as human obesity and related metabolic diseases.

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.

Enhanced identification of significant regulators of gene expression

Background

Diseases like cancer will lead to changes in gene expression, and it is relevant to identify key regulatory genes that can be linked directly to these changes. This can be done by computing a Regulatory Impact Factor (RIF) score for relevant regulators. However, this computation is based on estimating correlated patterns of gene expression, often Pearson correlation, and an assumption about a set of specific regulators, normally transcription factors. This study explores alternative measures of correlation, using the Fisher and Sobolev metrics, and an extended set of regulators, including epigenetic regulators and long non-coding RNAs (lncRNAs). Data on prostate cancer have been used to explore the effect of these modifications.

Results

A tool for computation of RIF scores with alternative correlation measures and extended sets of regulators was developed and tested on gene expression data for prostate cancer. The study showed that the Fisher and Sobolev metrics lead to improved identification of well-documented regulators of gene expression in prostate cancer, and the sets of identified key regulators showed improved overlap with previously defined gene sets of relevance to cancer. The extended set of regulators lead to identification of several interesting candidates for further studies, including lncRNAs. Several key processes were identified as important, including spindle assembly and the epithelial-mesenchymal transition (EMT).

Conclusions

The study has shown that using alternative metrics of correlation can improve the performance of tools based on correlation of gene expression in genomic data. The Fisher and Sobolev metrics should be considered also in other correlation-based applications.

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.