Postweaning substitution of grazed forage with a high-energy concentrate has variable long-term effects on subcutaneous fat and marbling in Bos taurus genotypes

The objective of this study was to quantify the effects and interactions of stage of growth and genotype on commercial carcass traits and intramuscular fat (IMF) content in 5 muscles of steers ( = 165) and to test the hypothesis that substituting pasture with a high-energy concentrate during the immediate postweaning period increases IMF. Cattle of 3 genotypes (Angus, Hereford, and Wagyu × Angus; = 55/genotype) were selected at weaning from commercial herds, targeting genotypic differences in marbling and subcutaneous fatness. Following weaning, steers were fed for 168 d within 2 different improved, temperate pasture-based nutritional systems: a forage-only system (FS) and forage with high-energy supplemented system (SS), with 2 replicates per system. The supplement was fed at a level of 1% of average BW adjusted every 2 wk to provide an estimated 50% of energy requirements for 168 d from weaning. Pasture on offer in both systems was managed to match the BW of the FS and SS steers during the postweaning treatment period to avoid confounding due to differences in growth rate during this period. Steers were then regrouped into 2 replicates and backgrounded on improved, temperate pasture for 158 d and then grain fed within 1 group for 105 d (short fed) or 259 d (long fed). Groups were slaughtered at commencement (d 0) and end of postweaning nutritional treatments (d 168), end of backgrounding (d 326), and after short (d 431) or long feedlotting (d 585). Serial slaughter stage had an effect on all traits assessed ( < 0.01). The FS steers had more rib fat ( < 0.01) and higher Meat Standards Australia marbling score ( < 0.05) and a tendency ( < 0.10) to have greater eye muscle area than the SS steers throughout the study. Genotypic differences were evident ( < 0.05) for all traits assessed except HCW, dressing percentage, rib fat depth, ossification score, ultimate pH, and IMF in the semitendinosus muscle. The results for marbling and IMF do not support the use of a high-energy feed as a substitute for an equivalent amount of energy from pasture during the immediate postweaning period to enhance development of marbling.

Characterization of the longissimus lumborum transcriptome response to adding propionate to the diet of growing Angus beef steers

Development of management paradigms that enhance the rate of gain and qualitative characteristics of beef carcass development has the potential to impact production and nutrient use efficiency but also mitigate losses to the environment. We used eight Black Angus beef steers (272.5 ± 17.6 kg initial body wt) fed a forage-based pelleted diet alone (n = 4) or supplemented with sodium propionate included (n = 4) for 42 days. High-quality RNA was extracted from the longissimus lumborum and subjected to transcriptome sequencing using RNA-seq technology. Trimmed reads were aligned to the bovine reference genome (Btau4.0, release 63) and uniquely mapped reads from control and propionate treatment groups were subject to further analysis using edgeR. Candidates were filtered to account for multiple testing and differentially expressed genes (153 at a false discovery rate of <5%) were analyzed using Gene Ontology (GO) analysis (GOseq) to select terms where enrichment had occurred. Significant GO terms included regulation of cholesterol transport, regulation of sterol transport, and cellular modified amino acid metabolic process. Furthermore, the top four identified gene networks included lipid metabolism, small molecule biochemistry, carbohydrate metabolism, and molecular transport-related categories. Notably, changes in lipid metabolism specific genes reflect both increased oxidative and lipid synthetic capacities. Metabolism-related gene changes are reflective of expected enhancements in lean tissue accretion patterns exhibited in steers where high ruminal propionate relative to other short chain fatty acids is observed. Propionate feeding induced increased N retention in rapidly growing Angus cattle, and the observed alterations in LL tissue lipid metabolism-related gene networks are consistent with enhanced cell formation and function (protein synthesis, and lipogenic vs. lipolytic activities).

Skeletal muscle specific genes networks in cattle

While physiological differences across skeletal muscles have been described, the differential gene expression underlying them and the discovery of how they interact to perform specific biological processes are largely to be elucidated. The purpose of the present study was, firstly, to profile by cDNA microarrays the differential gene expression between two skeletal muscle types, Psoas major (PM) and Flexor digitorum (FD), in beef cattle and then to interpret the results in the context of a bovine gene coexpression network, detecting possible changes in connectivity across the skeletal muscle system. Eighty four genes were differentially expressed (DE) between muscles. Approximately 54% encoded metabolic enzymes and structural-contractile proteins. DE genes were involved in similar processes and functions, but the proportion of genes in each category varied within each muscle. A correlation matrix was obtained for 61 out of the 84 DE genes from a gene coexpression network. Different groups of coexpression were observed, the largest one having 28 metabolic and contractile genes, up-regulated in PM, and mainly encoding fast-glycolytic fibre structural components and glycolytic enzymes. In FD, genes related to cell support seemed to constitute its identity feature and did not positively correlate to the rest of DE genes in FD. Moreover, changes in connectivity for some DE genes were observed in the different gene ontologies. Our results confirm the existence of a muscle dependent transcription and coexpression pattern and suggest the necessity of integrating different muscle types to perform comprehensive networks for the transcriptional landscape of bovine skeletal muscle.

Genetic and environmental effects on meat quality

In order for livestock industries to consistently produce high quality meat, there must be an understanding of the factors that cause quality to vary, as well as the contribution of genetics. A brief overview of meat tenderness is presented to understand how genotype and environment may interact to influence this trait. Essentially, meat tenderness is determined from the contribution of connective tissue, sarcomere length determined pre-rigor and rate of proteolysis during ageing, as well as contributions from intramuscular fat and post-mortem energy metabolism. The influence of mutations in myostatin, the callipyge gene, the Carwell or rib eye muscle gene as well as the calpain system on meat tenderness is presented. Specific examples of interactions between the production or processing environment and genetics are presented for both sheep and cattle. The day-to-day variation in tenderness is evident across experiments and this variation needs to be controlled in order to consistently produce tender meat.

Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks

MOTIVATION

We present PCIT, an algorithm for the reconstruction of gene co-expression networks (GCN) that combines the concept partial correlation coefficient with information theory to identify significant gene to gene associations defining edges in the reconstruction of GCN. The properties of PCIT are examined in the context of the topology of the reconstructed network including connectivity structure, clustering coefficient and sensitivity.

RESULTS

We apply PCIT to a series of simulated datasets with varying levels of complexity in terms of number of genes and experimental conditions, as well as to three real datasets. Results show that, as opposed to the constant cutoff approach commonly used in the literature, the PCIT algorithm can identify and allow for more moderate, yet not less significant, estimates of correlation (r) to still establish a connection in the GCN. We show that PCIT is more sensitive than established methods and capable of detecting functionally validated gene-gene interactions coming from absolute r values as low as 0.3. These bona fide associations, which often relate to genes with low variation in expression patterns, are beyond the detection limits of conventional fixed-threshold methods, and would be overlooked by studies relying on those methods.

AVAILABILITY

FORTRAN 90 source code to perform the PCIT algorithm is available as Supplementary File 1.

Application of gene expression studies in livestock production systems: a European perspective

In the context of sustainable agriculture and animal husbandry, understanding animal physiology remains a major challenge in the breeding and production of livestock, especially to develop animal farming systems that respond to the new and diversified consumer demand. Physiological processes depend on the expression of many genes acting in concert. Considerable effort has been expended in recent years on examining the mechanisms controlling gene expression and their regulation by biological and external factors (e.g. genetic determinants, nutritional factors, and animal management). Two main strategies have been developed to identify important genes. The first one has focussed on the expression of candidate genes for key physiological pathways at the level of both the transcripts and proteins. An original strategy has emerged with the advent of genomics that addresses the same issues through the examination of the molecular signatures of all genes and proteins using high-throughput techniques (e.g. transcriptomics and proteomics). In this review, the application of the gene expression studies in livestock production systems is discussed. Some practical examples of genomics applied to livestock production systems (e.g. to optimise animal nutrition, meat quality or animal management) are presented, and their outcomes are considered. In the future, integration of the knowledge gained from these studies will finally result in optimising livestock production systems through detection of desirable animals and their integration into accurate breeding programs or innovative management systems.

New indicators of beef sensory quality revealed by expression of specific genes

To identify new molecular markers of beef sensory quality, the transcriptomes of Longissimus thoracis muscle from 25 Charolais bull calves were analyzed using microarrays and compared between high and low meat quality groups; 215 genes were differentially expressed according to tenderness, juiciness, and/or flavor. Among these, 23 were up-regulated in the tenderest, juiciest, and tastiest meats, and 18 were highly correlated with both flavor and juiciness (e.g., PRKAG1), explaining up to 60% of their variability. Nine were down-regulated in the same meats, but only DNAJA1 [the results relating to DNAJA1 and its relationship with tenderness have been patented (Genomic marker for meat tenderness; Patent EP06300943.5, September 12, 2006)], which encodes a heat shock protein, showed a strong negative correlation with tenderness that alone explained 63% of its variability. This protein, known for its anti-apoptotic role, could be involved in meat aging. Thus, DNAJA1 could constitute a new marker of beef sensory quality.

Gene expression profiling of Hereford Shorthorn cattle following challenge with Boophilus microplus tick larvae

The ability of cattle to resist tick infestations is partly genetically determined. In order to better define the nature of Bos taurus resistance to the cattle tick Boophilus microplus, skin gene expression was studied using a cattle skin derived cDNA microarray. Expression profiles were determined in skin biopsies sampled from three highly tick resistant animals (HR) and two animals with lower tick resistance (LR) at time 0, immediately before challenge, and again 24 h after challenge. The analysis of the resulting expression data addressed two biological questions: first, for any animal exposed to ticks, which genes are differentially expressed in the 24 h following challenge; and second, which genes are differentially expressed between animals of high and low resistance at 24 h after challenge? In total, 214 genes were found to be differentially expressed in response to larval challenge across all the animals. Seventy-two genes were upregulated and 76 were downregulated at 24 h after challenge. Genes with significantly altered gene expression levels following tick infestation were predominantly keratin genes or mitochondrial genes, as well as odorant binding protein (OBP) and Bos taurus major allergen BDA20. In addition, we identified 66 genes with differential expression between HR and LR animals at 24 h. Of these, genes representing the extracellular matrix and immunoglobulin gene expression pathways were overrepresented. Three differentially expressed genes, OBP, Bos taurus major allergen BDA20 and dendritic cell protein HFL-B5 were further analysed by quantitative reverse transcription PCR (qRT-PCR). The qRT-PCR assay results closely mirrored the expression profiles found in the microarray experiment.

A gene coexpression network for bovine skeletal muscle inferred from microarray data

We present the application of large-scale multivariate mixed-model equations to the joint analysis of nine gene expression experiments in beef cattle muscle and fat tissues with a total of 147 hybridizations, and we explore 47 experimental conditions or treatments. Using a correlation-based method, we constructed a gene network for 822 genes. Modules of muscle structural proteins and enzymes, extracellular matrix, fat metabolism, and protein synthesis were clearly evident. Detailed analysis of the network identified groupings of proteins on the basis of physical association. For example, expression of three components of the z-disk, MYOZ1, TCAP, and PDLIM3, was significantly correlated. In contrast, expression of these z-disk proteins was not highly correlated with the expression of a cluster of thick (myosins) and thin (actin and tropomyosins) filament proteins or of titin, the third major filament system. However, expression of titin was itself not significantly correlated with the cluster of thick and thin filament proteins and enzymes. Correlation in expression of many fast-twitch muscle structural proteins and enzymes was observed, but slow-twitch-specific proteins were not correlated with the fast-twitch proteins or with each other. In addition, a number of significant associations between genes and transcription factors were also identified. Our results not only recapitulate the known biology of muscle but have also started to reveal some of the underlying associations between and within the structural components of skeletal muscle.