Genetic factors underlying host resistance to Rhipicephalus microplus tick infestation in Braford cattle: a systems biology perspective.

Approximately 80% of the world's cattle are raised in regions with a high risk of tick-borne diseases, resulting in significant economic losses due to parasitism by Rhipicephalus (Boophilus) microplus. However, the lack of a systemic biology approach hampers a comprehensive understanding of tick-host interactions that mediate tick resistance phenotypes. Here, we conducted a genome-wide association study (GWAS) of 2933 Braford cattle and found 340 single-nucleotide polymorphisms (SNPs) associated with tick counts. Gene expression analyses were performed on skin samples obtained from previously tick-exposed heifers with extremely high or low estimated breeding values for R. microplus counts. Evaluations were performed both before and after artificial infestation with ticks. Differentially expressed genes were found within 1-Mb windows centered at significant SNPs from GWAS. A total of 330 genes were related to the breakdown of homeostasis that was induced by larval attachment to bovine skin. Enrichment analysis pointed to a key role of proteolysis and signal transduction via JAK/STAT, NFKB and WNT/beta catenin signaling pathways. Integrative analysis on matrixEQTL revealed two cis-eQTLs and four significant SNPs in the genes peptidyl arginine deiminase type IV (PADI4) and LOC11449251. The integration of genomic data from QTL maps and transcriptome analyses has identified a set of twelve key genes that show significant associations with tick loads. These genes could be key candidates to improve the accuracy of genomic predictions for tick resistance in Braford cattle.

Molecular evolution and signatures of selective pressures on Bos, focusing on the Nelore breed (Bos indicus).

Evolutionary history leads to genome changes over time, especially for species that have experienced intense selective pressures over a short period. Here, we investigated the genomic evolution of Bos species by searching for potential selection signatures, focusing on Nelore, an economically relevant cattle breed in Brazil. We assessed the genomic processes determining the molecular evolution across Nelore and thirteen other related taxa by evaluating (i) amino acid sequence conservation, (ii) the dN/dS ratio, and (iii) gene families' turnover rate (λ). Low conserved regions potentially associated with fatty acid metabolism seem to reflect differences in meat fat content in taxa with different evolutionary histories. All Bos species presented genes under positive selection, especially B. indicus and Nelore, which include transport protein cobalamin, glycolipid metabolism, and hormone signaling. These findings could be explained by constant selective pressures to obtain higher immune resistance and efficient metabolism. The gene contraction rate across the Nelore + B. indicus branch was almost nine times higher than that in other lineages (λ = 0.01043 vs. 0.00121), indicating gene losses during the domestication process. Amino acid biosynthesis, reproductive and innate immune system-related pathways were associated with genes recognized within the most frequent rapidly evolving gene families and in genes under positive selection, supporting the substantial relevance of such traits from a domestication perspective. Our data provide new insights into how the genome may respond to intense artificial selection in distinct taxa, and reinforces the presence of selective pressures on traits potentially relevant for future animal breeding investments.

Stool and Ruminal Microbiome Components Associated With Methane Emission and Feed Efficiency in Nelore Beef Cattle.

Background: The impact of extreme changes in weather patterns on the economy and human welfare is one of the biggest challenges our civilization faces. From anthropogenic contributions to climate change, reducing the impact of farming activities is a priority since it is responsible for up to 18% of global greenhouse gas emissions. To this end, we tested whether ruminal and stool microbiome components could be used as biomarkers for methane emission and feed efficiency in bovine by studying 52 Brazilian Nelore bulls belonging to two feed intervention treatment groups, that is, conventional and by-product-based diets. Results: We identified a total of 5,693 amplicon sequence variants (ASVs) in the Nelore bulls' microbiomes. A Differential abundance analysis with the ANCOM approach identified 30 bacterial and 15 archaeal ASVs as differentially abundant (DA) among treatment groups. An association analysis using Maaslin2 software and a linear mixed model indicated that bacterial ASVs are linked to the host's residual methane emission (RCH4) and residual feed intake (RFI) phenotype variation, suggesting their potential as targets for interventions or biomarkers. Conclusion: The feed composition induced significant differences in both abundance and richness of ruminal and stool microbial populations in ruminants of the Nelore breed. The industrial by-product-based dietary treatment applied to our experimental groups influenced the microbiome diversity of bacteria and archaea but not of protozoa. ASVs were associated with RCH4 emission and RFI in ruminal and stool microbiomes. While ruminal ASVs were expected to influence CH4 emission and RFI, the relationship of stool taxa, such as Alistipes and Rikenellaceae (gut group RC9), with these traits was not reported before and might be associated with host health due to their link to anti-inflammatory compounds. Overall, the ASVs associated here have the potential to be used as biomarkers for these complex phenotypes.

Proteome alterations associated with the oleic acid and cis-9, trans-11 conjugated linoleic acid content in bovine skeletal muscle.

Oleic acid (OA) and cis-9, trans-11 conjugated linoleic acid (c9t11-CLA) are fatty acids found in beef with beneficial effects in human health. This study investigated differentially abundant proteins (DAPs) in skeletal muscle of bovines with extreme values of OA, and c9t11-CLA. For each one of the fatty acids, twenty muscle samples were divided into two groups (N = 10_High; N = 10_Low) and analyzed by high definition mass spectrometry. We identified 103 and 133 DAPs between the groups for each fatty acid. We found 64 and 45 up-regulated and 39 and 68 down-regulated proteins for OA and c9t11-CLA, respectively. Comparative analysis between proteomic and transcriptomic data revealed eight and ten genes with a consistent between mRNA expression levels and protein abundance for OA and c9t11-CLA, respectively. Unconventional myosin-Id (MYO1D), mineralocorticoid receptor (NR3C2), geranylgeranyl transferase type-2 subunit-alpha (RABGGTA), and uveal autoantigen with coiled-coil domains and ankyrin repeats (UACA) were found as putative candidate proteins for OA content. Fatty acid synthase (FASN), tubulin alpha-4A chain (TUBA4A), vinculin (VCL), NADH dehydrogenase 1 alpha subcomplex 5 (NDUFA5), and prefoldin subunit 6 (PFDN6) for c9t11-CLA. Our findings contribute to a deeper understanding of the molecular mechanisms behind the regulation of the OA and c9t11-CLA content in cattle skeletal muscle. SIGNIFICANCE: Questions about the association between meat intake and disease incidence in humans has driven animal scientist to pursue a better understanding of the biological processes associated with differences in the intramuscular fat composition. The beneficial effects of oleic acid and conjugated linoleic acid in human health have been demonstrated by improving the immune system and preventing atherosclerosis, different types of cancers, hypertension, and diabetes. Previous genome-wide association and gene expression studies identified genomic regions and differentially expressed genes associated with the fatty acid profile in skeletal muscle. In this work, differences were evaluated at the protein level. The use of a label-free quantitative proteomic approach, compared with muscle transcriptome results obtained by RNA-sequencing, allowed us to earn new insights into the variability in fatty acid deposition in skeletal muscle of farm animals. This study opens new avenues to explore the effect of the fatty acids in the skeletal muscle of livestock animals, which is associated with nutritional values of the meat, and perhaps to understand the mechanisms correlated with metabolic diseases in other species.

Potential Biomarkers for Feed Efficiency-Related Traits in Nelore Cattle Identified by Co-expression Network and Integrative Genomics Analyses.

Feed efficiency helps to reduce environmental impacts from livestock production, improving beef cattle profitability. We identified potential biomarkers (hub genes) for feed efficiency, by applying co-expression analysis in Longissimus thoracis RNA-Seq data from 180 Nelore steers. Six co-expression modules were associated with six feed efficiency-related traits (p-value ≤ 0.05). Within these modules, 391 hub genes were enriched for pathways as protein synthesis, muscle growth, and immune response. Trait-associated transcription factors (TFs) ELF1, ELK3, ETS1, FLI1, and TCF4, were identified with binding sites in at least one hub gene. Gene expression of CCDC80, FBLN5, SERPINF1, and OGN was associated with multiple feed efficiency-related traits (FDR ≤ 0.05) and were previously related to glucose homeostasis, oxidative stress, fat mass, and osteoblastogenesis, respectively. Potential regulatory elements were identified, integrating the hub genes with previous studies from our research group, such as the putative cis-regulatory elements (eQTLs) inferred as affecting the PCDH18 and SPARCL1 hub genes related to immune system and adipogenesis, respectively. Therefore, our analyses contribute to a better understanding of the biological mechanisms underlying feed efficiency in bovine and the hub genes disclosed can be used as biomarkers for feed efficiency-related traits in Nelore cattle.

The structure of microbial populations in Nelore GIT reveals inter-dependency of methanogens in feces and rumen.

BACKGROUND: The success of different species of ruminants in the colonization of a diverse range of environments is due to their ability to digest and absorb nutrients from cellulose, a complex polysaccharide found in leaves and grass. Ruminants rely on a complex and diverse microbial community, or microbiota, in a unique compartment known as the rumen to break down this polysaccharide. Changes in microbial populations of the rumen can affect the host's development, health, and productivity. However, accessing the rumen is stressful for the animal. Therefore, the development and use of alternative sampling methods are needed if this technique is to be routinely used in cattle breeding. To this end, we tested if the fecal microbiome could be used as a proxy for the rumen microbiome due to its accessibility. We investigated the taxonomic composition, diversity and inter-relations of two different GIT compartments, rumen and feces, of 26 Nelore (Bos indicus) bulls, using Next Generation Sequencing (NGS) metabarcoding of bacteria, archaea and ciliate protozoa. RESULTS: We identified 4265 Amplicon Sequence Variants (ASVs) from bacteria, 571 from archaea, and 107 from protozoa, of which 143 (96 bacteria and 47 archaea) were found common between both microbiomes. The most prominent bacterial phyla identified were Bacteroidetes (41.48%) and Firmicutes (56.86%) in the ruminal and fecal microbiomes, respectively, with Prevotella and Ruminococcaceae UCG-005 the most relatively abundant genera identified in each microbiome. The most abundant archaeal phylum identified was Euryarchaeota, of which Methanobrevibacter gottschalkii, a methanogen, was the prevalent archaeal species identified in both microbiomes. Protozoa were found exclusively identified in the rumen with Bozasella/Triplumaria being the most frequent genus identified. Co-occurrence among ruminal and fecal ASVs reinforces the relationship of microorganisms within a biological niche. Furthermore, the co-occurrence of shared archaeal ASVs between microbiomes indicates a dependency of the predominant fecal methanogen population on the rumen population. CONCLUSIONS: Co-occurring microorganisms were identified within the rumen and fecal microbiomes, which revealed a strong association and inter-dependency between bacterial, archaeal and protozoan populations of the same microbiome. The archaeal ASVs identified as co-occurring between GIT compartments corresponded to the methanogenic genera Methanobrevibacter and Methanosphaera and represented 26.34% of the overall archaeal sequencesdiversity in the rumen and 42.73% in feces. Considering that these archaeal ASVs corresponded to a significant part of the overall diversity of both microbiomes, which is much higher if one includes the interactions of these co-occurring with other rumen archaea ASVs, we suggest that fecal methanogens could be used as a proxy of ruminal methanogens.

Network analysis uncovers putative genes affecting resistance to tick infestation in Braford cattle skin.

BACKGROUND: Genetic resistance in cattle is considered a suitable way to control tick burden and its consequent losses for livestock production. Exploring tick-resistant (R) and tick-susceptible (S) hosts, we investigated the genetic mechanisms underlying the variation of Braford resistance to tick infestation. Skin biopsies from four-times-artificially infested R (n = 20) and S (n = 19) hosts, obtained before the first and 24 h after the fourth tick infestation were submitted to RNA-Sequencing. Differential gene expression, functional enrichment, and network analysis were performed to identify genetic pathways and transcription factors (TFs) affecting host resistance. RESULTS: Intergroup comparisons of hosts before (Rpre vs. Spre) and after (Rpost vs. Spost) tick infestation found 51 differentially expressed genes (DEGs), of which almost all presented high variation (TopDEGs), and 38 were redundant genes. Gene expression was consistently different between R and S hosts, suggesting the existence of specific anti-tick mechanisms. In the intragroup comparisons, Rpost vs. Rpre and Spost vs. Spre, we found more than two thousand DEGs in response to tick infestation in both resistance groups. Redundant and non-redundant TopDEGs with potential anti-tick functions suggested a role in the development of different levels of resistance within the same breed. Leukocyte chemotaxis was over-represented in both hosts, whereas skin degradation and remodeling were only found in TopDEGs from R hosts. Also, these genes indicated the participation of cytokines, such as IL6 and IL22, and the activation of Wingless (WNT)-signaling pathway. A central gene of this pathway, WNT7A, was consistently modulated when hosts were compared. Moreover, the findings based on a genome-wide association study (GWAS) corroborate the prediction of the WNT-signaling pathway as a candidate mechanism of resistance. The regulation of immune response was the most relevant pathway predicted for S hosts. Members of Ap1 and NF-kB families were the most relevant TFs predicted for R and S, respectively. CONCLUSION: This work provides indications of genetic mechanisms presented by Braford cattle with different levels of resistance in response to tick infestation, contributing to the search of candidate genes for tick resistance in bovine.

Cross talk between mineral metabolism and meat quality: a systems biology overview.

Meat quality has an inherent complexity because of the multiple interrelated causative factors and layers of feedback regulation. Understanding the key factors and their interactions has been challenging, despite the availability of remarkable high-throughput tools and techniques that have provided insights on muscle metabolism and the genetic basis of meat quality. Likewise, we have deepened our knowledge about mineral metabolism and its role in cell functioning. Regardless of these facts, complex traits like mineral content and meat quality have been studied under reductionist approaches. However, as these phenotypes arise from complex interactions among different biological layers (genome, transcriptome, proteome, epigenome, etc.), along with environmental effects, a holistic view and systemic-level understanding of the genetic basis of complex phenotypes are in demand. Based on the state of the art, we addressed some of the questions regarding the interdependence of meat quality traits and mineral content. Furthermore, we sought to highlight potential regulatory mechanisms arising from the genes, miRNAs, and mineral interactions, as well as the pathways modulated by this interplay affecting muscle, mineral metabolism, and meat quality. By answering these questions, we did not intend to give an exhaustive review but to identify the key biological points, the challenges, and benefits of integrative genomic approaches.

Co-Expression Networks Reveal Potential Regulatory Roles of miRNAs in Fatty Acid Composition of Nelore Cattle.

Fatty acid (FA) content affects the sensorial and nutritional value of meat and plays a significant role in biological processes such as adipogenesis and immune response. It is well known that, in beef, the main FAs associated with these biological processes are oleic acid (C18:1 cis9, OA) and conjugated linoleic acid (CLA-c9t11), which may have beneficial effects on metabolic diseases such as type 2 diabetes and obesity. Here, we performed differential expression and co-expression analyses, weighted gene co-expression network analysis (WGCNA) and partial correlation with information theory (PCIT), to uncover the complex interactions between miRNAs and mRNAs expressed in skeletal muscle associated with FA content. miRNA and mRNA expression data were obtained from skeletal muscle of Nelore cattle that had extreme genomic breeding values for OA and CLA. Insulin and MAPK signaling pathways were identified by WGCNA as central pathways associated with both of these fatty acids. Co-expression network analysis identified bta-miR-33a/b, bta-miR-100, bta-miR-204, bta-miR-365-5p, bta-miR-660, bta-miR-411a, bta-miR-136, bta-miR-30-5p, bta-miR-146b, bta-let-7a-5p, bta-let-7f, bta-let-7, bta-miR 339, bta-miR-10b, bta-miR 486, and the genes ACTA1 and ALDOA as potential regulators of fatty acid synthesis. This study provides evidence and insights into the molecular mechanisms and potential target genes involved in fatty acid content differences in Nelore beef cattle, revealing new candidate pathways of phenotype modulation that could positively benefit beef production and human consumption.

Detection of Co-expressed Pathway Modules Associated With Mineral Concentration and Meat Quality in Nelore Cattle.

Meat quality is a complex trait that is influenced by genetic and environmental factors, which includes mineral concentration. However, the association between mineral concentration and meat quality, and the specific molecular pathways underlying this association, are not well explored. We therefore analyzed gene expression as measured with RNA-seq in Longissimus thoracis muscle of 194 Nelore steers for association with three meat quality traits (intramuscular fat, meat pH, and tenderness) and the concentration of 13 minerals (Ca, Cr, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, and Zn). We identified seven sets of co-expressed genes (modules) associated with at least two traits, which indicates that common pathways influence these traits. From pathway analysis of module hub genes, we further found an over-representation for energy and protein metabolism (AMPK and mTOR signaling pathways) in addition to muscle growth, and protein turnover pathways. Among the identified hub genes FASN, ELOV5, and PDE3B are involved with lipid metabolism and were affected by previously identified eQTLs associated to fat deposition. The reported hub genes and over-represented pathways provide evidence of interplay among gene expression, mineral concentration, and meat quality traits. Future studies investigating the effect of different levels of mineral supplementation in the gene expression and meat quality traits could help us to elucidate the regulatory mechanism by which the genes/pathways are affected.

MiRNAs differentially expressed in skeletal muscle of animals with divergent estimated breeding values for beef tenderness.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs of approximately 22 nucleotides, highly conserved among species, which modulate gene expression by cleaving messenger RNA target or inhibiting translation. MiRNAs are involved in the regulation of many processes including cell proliferation, differentiation, neurogenesis, angiogenesis, and apoptosis. Beef tenderness is an organoleptic characteristic of great influence in the acceptance of meat by consumers. Previous studies have shown that collagen level, marbling, apoptosis and proteolysis are among the many factors that affect beef tenderness. Considering that miRNAs can modulate gene expression, this study was designed to identify differentially expressed miRNAs that could be modulating biological processes involved with beef tenderness. RESULTS: Deep sequence analysis of miRNA libraries from longissimus thoracis muscle allowed the identification of 42 novel and 308 known miRNAs. Among the known miRNAs, seven were specifically expressed in skeletal muscle. Differential expression analysis between animals with high (H) and low (L) estimated breeding values for shear force (EBVSF) revealed bta-mir-182 and bta-mir-183 are up-regulated (q value < 0.05) in animals with L EBVSF, and bta-mir-338 is up-regulated in animals with H EBVSF. The number of bovine predicted targets for bta-mir-182, bta-mir-183 and bta-mir-338 were 811, 281 and 222, respectively, which correspond to 1204 unique target genes. Among these, four of them, MEF2C, MAP3K2, MTDH and TNRC6B were common targets of the three differentially expressed miRNAs. The functional analysis identified important pathways related to tenderness such as apoptosis and the calpain-calpastatin system. CONCLUSION: The results obtained indicate the importance of miRNAs in the regulatory mechanisms that influence muscle proteolysis and meat tenderness and contribute to our better understanding of the role of miRNAs in biological processes associated with beef tenderness.

Gene co-expression networks associated with carcass traits reveal new pathways for muscle and fat deposition in Nelore cattle.

BACKGROUND: Positively correlated with carcass weight and animal growth, the ribeye area (REA) and the backfat thickness (BFT) are economic important carcass traits, which impact directly on producer's payment. The selection of these traits has not been satisfactory since they are expressed later in the animal's life and multigene regulated. So, next-generation technologies have been applied in this area to improve animal's selection and better understand the molecular mechanisms involved in the development of these traits. Correlation network analysis, performed by tools like WGCNA (Weighted Correlation Network Analysis), has been used to explore gene-gene interactions and gene-phenotype correlations. Thus, this study aimed to identify putative candidate genes and metabolic pathways that regulate REA and BFT by constructing a gene co-expression network using WGCNA and RNA sequencing data, to better understand genetic and molecular variations behind these complex traits in Nelore cattle. RESULTS: The gene co-expression network analysis, using WGCNA, were built using RNA-sequencing data normalized by transcript per million (TPM) from 43 Nelore steers. Forty-six gene clusters were constructed, between them, three were positively correlated (p-value< 0.1) to the BFT (Green Yellow, Ivory, and Light Yellow modules) and, one cluster was negatively correlated (p-value< 0.1) with REA (Salmon module). The enrichment analysis performed by DAVID and WebGestalt (FDR 5%) identified eight Gene Ontology (GO) terms and three KEGG pathways in the Green Yellow module, mostly associated with immune response and inflammatory mechanisms. The enrichment of the Salmon module demonstrated 19 GO terms and 21 KEGG pathways, related to muscle energy metabolism, lipid metabolism, muscle degradation, and oxidative stress diseases. The Ivory and Light yellow modules have not shown significant results in the enrichment analysis. CONCLUSION: With this study, we verified that inflammation and immune response pathways modulate the BFT trait. Energy and lipid metabolism pathways, highlighting fatty acid metabolism, were the central pathways associated with REA. Some genes, as RSAD2, EIF2AK2, ACAT1, and ACSL1 were considered as putative candidate related to these traits. Altogether these results allow us to a better comprehension of the molecular mechanisms that lead to muscle and fat deposition in bovine.

An integrative transcriptome analysis indicates regulatory mRNA-miRNA networks for residual feed intake in Nelore cattle.

Residual Feed Intake (RFI) is an economically relevant trait in beef cattle. Among the molecular regulatory mechanisms, microRNAs (miRNAs) are an important dimension in post-transcriptional regulation and have been associated with different biological pathways. Here, we performed differential miRNAs expression and weighted gene co-expression network analyses (WGCNA) to better understand the complex interactions between miRNAs and mRNAs expressed in bovine skeletal muscle and liver. MiRNA and mRNA expression data were obtained from Nelore steers that were genetically divergent for RFI (N = 10 [low RFI or feed efficient]; N = 10 [high RFI or feed inefficient]). Differentially expressed and hub miRNAs such as bta-miR-486, bta-miR-7, bta-miR15a, bta-miR-21, bta-miR 29, bta- miR-30b, bta-miR-106b, bta-miR-199a-3p, bta-miR-204, and bta-miR 296 may have a potential role in variation of RFI. Functional enrichment analysis of differentially expressed (DE) miRNA's target genes and miRNA-mRNA correlated modules revealed that insulin, lipid, immune system, oxidative stress and muscle development signaling pathways might potentially be involved in RFI in this population. Our study identified DE miRNAs, miRNA - mRNA regulatory networks and hub miRNAs related to RFI. These findings suggest a possible role of miRNAs in regulation of RFI, providing new insights into the potential molecular mechanisms that control feed efficiency in Nelore cattle.

A comprehensive manually-curated compendium of bovine transcription factors.

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

Data from proteomic analysis of bovine Longissimus dorsi muscle associated with intramuscular fat content.

The proteomic data presented in this article are associated with the research article entitled "Longissimus dorsi muscle label-free quantitative proteomic reveals biological mechanisms associated with intramuscular fat deposition" published in Journal of Proteomics [1]. In this article, we characterized the proteomic profile of bovine Longissimus dorsi muscle from Nelore steers and identified differentially abundant proteins associated with the intramuscular fat (IMF) content. An integrated transcriptome-assisted label-free quantitative proteomic approach by High Definition Mass Spectrometry (HDMSE) was employed to identify and quantify the proteins. A functional enrichment analysis using the differentially abundant proteins list was performed to understand the biological processes involved in IMF deposition. Moreover, to explore and clarify the biological mechanisms that influence IMF content, the mRNA data for the same trait from Cesar and collaborators [2] obtained by RNA-sequencing technology was compared with proteomic data. The mRNA data is deposited in the European Nucleotide Archive (ENA) repository (EMBL-EBI), under accession PRJEB13188.

Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.

BACKGROUND: Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. RESULTS: We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism. CONCLUSION: This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.

Longissimus dorsi muscle label-free quantitative proteomic reveals biological mechanisms associated with intramuscular fat deposition.

The pathways involved in intramuscular fat (IMF) deposition in Longissimus dorsi muscle were investigated using an integrated transcriptome-assisted label-free quantitative proteomic approach by High Definition Mass Spectrometry. We quantified 1582 proteins, of which 164 were differentially abundant proteins (DAPs, p < 0.05) between animals with high (H) and low (L) genomic estimated breeding values (GEBV) for IMF content. Ingenuity pathway analysis (IPA) revealed that these DAPs were mainly involved in glycolysis metabolism, actin cytoskeleton signaling, cell-cell adherens junction and pathways for MAPK and insulin. A comparative study between transcriptomic (mRNA) and proteomic data showed 17 differentially expressed genes corresponding to DAPs, of which three genes/proteins did not agree on the direction of the fold change between groups. Moreover, we investigated microRNAs data to explain these differences in fold change direction, being able to unravel two of the three unexpected mRNA/protein relationships. Results demonstrated that changes in protein/mRNA levels of sarcomere organization, intracellular signal transduction and regulation of actin cytoskeleton, are involved in IMF deposition. These findings provide a deeper understanding of the highly complex regulatory mechanisms involved in IMF deposition in cattle and indicate target pathways for future studies. SIGNIFICANCE: Intramuscular fat is the amount of fat deposited inside muscle and plays an important role in human health and meat quality attributes, influencing energy metabolism of skeletal muscle, as well as, tenderness, flavor, and juiciness of beef. We performed for the first time the utilization of integrated transcriptome-assisted label-free quantitative proteomic approach using High Definition Mass Spectrometry for characterization of the changes in the proteomic profile of the Longissimus dorsi muscle associated with intramuscular fat deposition in cattle. Furthermore, we compared the muscle proteome with the muscle transcriptome (mRNA and microRNAs), obtained by RNA-sequencing, to better understand the relationship between expression of mRNAs and proteins and to unravel essential biological mechanisms involved in bovine skeletal muscle IMF deposition.

Integrative analysis of microRNAs and mRNAs revealed regulation of composition and metabolism in Nelore cattle.

BACKGROUND: The amount of intramuscular fat can influence the sensory characteristics and nutritional value of beef, thus the selection of animals with adequate fat deposition is important to the consumer. There is growing knowledge about the genes and pathways that control the biological processes involved in fat deposition in muscle. MicroRNAs (miRNAs) belong to a well-conserved class of non-coding small RNAs that modulate gene expression across a range of biological functions in animal development and physiology. The aim of this study was to identify differentially expressed (DE) miRNAs, regulatory candidate genes and co-expression networks related to intramuscular fat (IMF) deposition. To achieve this, we used mRNA and miRNA expression data from the Longissimus dorsi muscle of 30 Nelore steers with high (H) and low (L) genomic estimated breeding values (GEBV) for IMF deposition. RESULTS: Differential miRNA expression analysis between animals with extreme GEBV values for IMF identified six DE miRNAs (FDR 10%). Functional annotation of the target genes for these microRNAs indicated that the PPARs signaling pathway is involved with IMF deposition. Candidate regulatory genes such as SDHAF4, FBXO17, ALDOA and PKM were identified by partial correlation with information theory (PCIT), phenotypic impact factor (PIF) and regulatory impact factor (RIF) co-expression approaches from integrated miRNA-mRNA expression data. Two DE miRNAs (FDR 10%), bta-miR-143 and bta-miR-146b, which were upregulated in the Low IMF group, were correlated with regulatory candidate genes, which were functionally enriched for fatty acid oxidation GO terms. Co-expression patterns obtained by weighted correlation network analysis (WGCNA), which showed possible interaction and regulation between mRNAs and miRNAs, identified several modules related to immune system function, protein metabolism, energy metabolism and glucose catabolism according to in silico analysis performed herein. CONCLUSION: In this study, several genes and miRNAs were identified as candidate regulators of IMF by analyzing DE miRNAs using two different miRNA-mRNA co-expression network methods. This study contributes to the understanding of potential regulatory mechanisms of gene signaling networks involved in fat deposition processes measured in muscle. Glucose metabolism and inflammation processes were the main pathways found in silico to influence intramuscular fat deposition in beef cattle in the integrative mRNA-miRNA co-expression analysis.

Comparative muscle transcriptome associated with carcass traits of Nellore cattle.

BACKGROUND: Commercial cuts yield is an important trait for beef production, which affects the final value of the products, but its direct determination is a challenging procedure to be implemented in practice. The measurement of ribeye area (REA) and backfat thickness (BFT) can be used as indirect measures of meat yield. REA and BFT are important traits studied in beef cattle due to their strong implication in technological (carcass yield) and nutritional characteristics of meat products, like the degree of muscularity and total body fat. Thus, the aim of this work was to study the Longissimus dorsi muscle transcriptome of Nellore cattle, associated with REA and BFT, to find differentially expressed (DE) genes, metabolic pathways, and biological processes that may regulate these traits. RESULTS: By comparing the gene expression level between groups with extreme genomic estimated breeding values (GEBV), 101 DE genes for REA and 18 for BFT (false discovery rate, FDR 10%) were identified. Functional enrichment analysis for REA identified two KEGG pathways, MAPK (Mitogen-Activated Protein Kinase) signaling pathway and endocytosis pathway, and three biological processes, response to endoplasmic reticulum stress, cellular protein modification process, and macromolecule modification. The MAPK pathway is responsible for fundamental cellular processes, such as growth, differentiation, and hypertrophy. For BFT, 18 biological processes were found to be altered and grouped into 8 clusters of semantically similar terms. The DE genes identified in the biological processes for BFT were ACHE, SRD5A1, RSAD2 and RSPO3. RSAD2 has been previously shown to be associated with lipid droplet content and lipid biosynthesis. CONCLUSION: In this study, we identified genes, metabolic pathways, and biological processes, involved in differentiation, proliferation, protein turnover, hypertrophy, as well as adipogenesis and lipid biosynthesis related to REA and BFT. These results enlighten some of the molecular processes involved in muscle and fat deposition, which are economically important carcass traits for beef production.

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle.

Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS) could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV) for average daily weight gain (ADG) in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP), BayesA, and BayesCπ] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively)]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44) and sample size (568 animals in the training population). Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.