Transcriptome analysis of cattle muscle identifies potential markers for skeletal muscle growth rate and major cell types.

BACKGROUND: This study aimed to identify markers for muscle growth rate and the different cellular contributors to cattle muscle and to link the muscle growth rate markers to specific cell types. RESULTS: The expression of two groups of genes in the longissimus muscle (LM) of 48 Brahman steers of similar age, significantly enriched for "cell cycle" and "ECM (extracellular matrix) organization" Gene Ontology (GO) terms was correlated with average daily gain/kg liveweight (ADG/kg) of the animals. However, expression of the same genes was only partly related to growth rate across a time course of postnatal LM development in two cattle genotypes, Piedmontese x Hereford (high muscling) and Wagyu x Hereford (high marbling). The deposition of intramuscular fat (IMF) altered the relationship between the expression of these genes and growth rate. K-means clustering across the development time course with a large set of genes (5,596) with similar expression profiles to the ECM genes was undertaken. The locations in the clusters of published markers of different cell types in muscle were identified and used to link clusters of genes to the cell type most likely to be expressing them. Overall correspondence between published cell type expression of markers and predicted major cell types of expression in cattle LM was high. However, some exceptions were identified: expression of SOX8 previously attributed to muscle satellite cells was correlated with angiogenesis. Analysis of the clusters and cell types suggested that the "cell cycle" and "ECM" signals were from the fibro/adipogenic lineage. Significant contributions to these signals from the muscle satellite cells, angiogenic cells and adipocytes themselves were not as strongly supported. Based on the clusters and cell type markers, sets of five genes predicted to be representative of fibro/adipogenic precursors (FAPs) and endothelial cells, and/or ECM remodelling and angiogenesis were identified. CONCLUSIONS: Gene sets and gene markers for the analysis of many of the major processes/cell populations contributing to muscle composition and growth have been proposed, enabling a consistent interpretation of gene expression datasets from cattle LM. The same gene sets are likely to be applicable in other cattle muscles and in other species.

Phosphoinositide 3-kinase (PI3K(p110alpha)) directly regulates key components of the Z-disc and cardiac structure.

Maintenance of cardiac structure and Z-disc signaling are key factors responsible for protecting the heart in a setting of stress, but how these processes are regulated is not well defined. We recently demonstrated that PI3K(p110α) protects the heart against myocardial infarction. The aim of this study was to determine whether PI3K(p110α) directly regulates components of the Z-disc and cardiac structure. To address this question, a unique three-dimensional virtual muscle model was applied to gene expression data from transgenic mice with increased or decreased PI3K(p110α) activity under basal conditions (sham) and in a setting of myocardial infarction to display the location of structural proteins. Key findings from this analysis were then validated experimentally. The three-dimensional virtual muscle model visually highlighted reciprocally regulated transcripts associated with PI3K activation that encoded key components of the Z-disc and costamere, including melusin. Studies were performed to assess whether PI3K and melusin interact in the heart. Here, we identify a novel melusin-PI3K interaction that generates lipid kinase activity. The direct impact of PI3K(p110α) on myocyte structure was assessed by treating neonatal rat ventricular myocytes with PI3K(p110α) inhibitors and examining the myofiber morphology of hearts from PI3K transgenic mice. Results demonstrate that PI3K is critical for myofiber maturation and Z-disc alignment. In summary, PI3K regulates the expression of genes essential for cardiac structure and Z-disc signaling, interacts with melusin, and is critical for Z-disc alignment.

Beyond differential expression: the quest for causal mutations and effector molecules.

High throughput gene expression technologies are a popular choice for researchers seeking molecular or systems-level explanations of biological phenomena. Nevertheless, there has been a groundswell of opinion that these approaches have not lived up to the hype because the interpretation of the data has lagged behind its generation. In our view a major problem has been an over-reliance on isolated lists of differentially expressed (DE) genes which - by simply comparing genes to themselves - have the pitfall of taking molecular information out of context. Numerous scientists have emphasised the need for better context. This can be achieved through holistic measurements of differential connectivity in addition to, or in replacement, of DE. However, many scientists continue to use isolated lists of DE genes as the major source of input data for common readily available analytical tools. Focussing this opinion article on our own research in skeletal muscle, we outline our resolutions to these problems - particularly a universally powerful way of quantifying differential connectivity. With a well designed experiment, it is now possible to use gene expression to identify causal mutations and the other major effector molecules with whom they cooperate, irrespective of whether they themselves are DE. We explain why, for various reasons, no other currently available experimental techniques or quantitative analyses are capable of reaching these conclusions.

Chronic exposure to anabolic steroids induces the muscle expression of oxytocin and a more than fiftyfold increase in circulating oxytocin in cattle.

Molecular mechanisms in skeletal muscle associated with anabolic steroid treatment of cattle are unclear and we aimed to characterize transcriptional changes. Cattle were chronically exposed (68 ± 20 days) to a steroid hormone implant containing 200 mg trenbolone acetate and 20 mg estradiol (Revalor-H). Biopsy samples from 48 cattle (half treated) from longissimus dorsi (LD) muscle under local anesthesia were collected. Gene expression levels were profiled by microarray, covering 16,944 unique bovine genes: 121 genes were differentially expressed (DE) due to the implant (99.99% posterior probability of not being false positives). Among DE genes, a decrease in expression of a number of fat metabolism-associated genes, likely reflecting the lipid storage activity of intramuscular adipocytes, was observed. The expression of IGF1 and genes related to the extracellular matrix, slow twitch fibers, and cell cycle (including SOX8, a satellite cell marker) was increased in the treated muscle. Unexpectedly, a very large 21- (microarray) to 97 (real time quantitative PCR)-fold higher expression of the mRNA encoding the neuropeptide hormone oxytocin was observed in treated muscle. We also observed an ∼50-fold higher level of circulating oxytocin in the plasma of treated animals at the time of biopsy. Using a coexpression network strategy OXTR was identified as more likely than IGF1R to be a major mediator of the muscle response to Revalor-H. A re-investigation of in vivo cattle LD muscle samples during early to mid-fetal development identified a >128-fold increased expression of OXT, coincident with myofiber differentiation and fusion. We propose that oxytocin may be involved in mediating the anabolic effects of Revalor-H treatment.

Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle.

BACKGROUND: Gene regulation by transcription factors (TF) is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information. RESULTS: We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs). We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs) and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively. CONCLUSION: The pivotal implication of our research is two-fold: (1) there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2) this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

Regulatory impact factors: unraveling the transcriptional regulation of complex traits from expression data.

MOTIVATION: Although transcription factors (TF) play a central regulatory role, their detection from expression data is limited due to their low, and often sparse, expression. In order to fill this gap, we propose a regulatory impact factor (RIF) metric to identify critical TF from gene expression data. RESULTS: To substantiate the generality of RIF, we explore a set of experiments spanning a wide range of scenarios including breast cancer survival, fat, gonads and sex differentiation. We show that the strength of RIF lies in its ability to simultaneously integrate three sources of information into a single measure: (i) the change in correlation existing between the TF and the differentially expressed (DE) genes; (ii) the amount of differential expression of DE genes; and (iii) the abundance of DE genes. As a result, RIF analysis assigns an extreme score to those TF that are consistently most differentially co-expressed with the highly abundant and highly DE genes (RIF1), and to those TF with the most altered ability to predict the abundance of DE genes (RIF2). We show that RIF analysis alone recovers well-known experimentally validated TF for the processes studied. The TF identified confirm the importance of PPAR signaling in adipose development and the importance of transduction of estrogen signals in breast cancer survival and sexual differentiation. We argue that RIF has universal applicability, and advocate its use as a promising hypotheses generating tool for the systematic identification of novel TF not yet documented as critical.

Modes of genetic adaptations underlying functional innovations in the rumen.

The rumen is the hallmark organ of ruminants and hosts a diverse ecosystem of microorganisms that facilitates efficient digestion of plant fibers. We analyzed 897 transcriptomes from three Cetartiodactyla lineages: ruminants, camels and cetaceans, as well as data from ruminant comparative genomics and functional assays to explore the genetic basis of rumen functional innovations. We identified genes with relatively high expression in the rumen, of which many appeared to be recruited from other tissues. These genes show functional enrichment in ketone body metabolism, regulation of microbial community, and epithelium absorption, which are the most prominent biological processes involved in rumen innovations. Several modes of genetic change underlying rumen functional innovations were uncovered, including coding mutations, genes newly evolved, and changes of regulatory elements. We validated that the key ketogenesis rate-limiting gene (HMGCS2) with five ruminant-specific mutations was under positive selection and exhibits higher synthesis activity than those of other mammals. Two newly evolved genes (LYZ1 and DEFB1) are resistant to Gram-positive bacteria and thereby may regulate microbial community equilibrium. Furthermore, we confirmed that the changes of regulatory elements accounted for the majority of rumen gene recruitment. These results greatly improve our understanding of rumen evolution and organ evo-devo in general.

Using paired-end sequences to optimise parameters for alignment of sequence reads against related genomes.

BACKGROUND: The advent of cheap high through-put sequencing methods has facilitated low coverage skims of a large number of organisms. To maximise the utility of the sequences, assembly into contigs and then ordering of those contigs is required. Whilst sequences can be assembled into contigs de novo, using assembled genomes of closely related organisms as a framework can considerably aid the process. However, the preferred search programs and parameters that will optimise the sensitivity and specificity of the alignments between the sequence reads and the framework genome(s) are not necessarily obvious. Here we demonstrate a process that uses paired-end sequence reads to choose an optimal program and alignment parameters. RESULTS: Unlike two single fragment reads, in paired-end sequence reads, such as BAC-end sequences, the two sequences in the pair have a known positional relationship in the original genome. This provides an additional level of confidence over match scores and e-values in the accuracy of the positional assignment of the reads in the comparative genome. Three commonly used sequence alignment programs: MegaBLAST, Blastz and PatternHunter were used to align a set of ovine BAC-end sequences against the equine genome assembly. A range of different search parameters, with a particular focus on contiguous and discontiguous seeds, were used for each program. The number of reads with a hit and the number of read pairs with hits for the two end sequences in the tail-to-tail paired-end configuration were plotted relative to the theoretical maximum expected curve. Of the programs tested, MegaBLAST with short contiguous seed lengths (word size 8-11) performed best in this particular task. In addition the data also provides estimates of the false positive and false negative rates, which can be used to determine the appropriate values of additional parameters, such as score cut-off, to balance sensitivity and specificity. To determine whether the approach also worked for the alignment of shorter reads, the first 240 bases of each BAC end sequence were also aligned to the equine genome. Again, contiguous MegaBLAST performed the best in optimising the sensitivity and specificity with which sheep BAC end reads map to the equine and bovine genomes. CONCLUSIONS: Paired-end reads, such as BAC-end sequences, provide an efficient mechanism to optimise sequence alignment parameters, for example for comparative genome assemblies, by providing an objective standard to evaluate performance.

A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation.

Transcription factor (TF) regulation is often post-translational. TF modifications such as reversible phosphorylation and missense mutations, which can act independent of TF expression level, are overlooked by differential expression analysis. Using bovine Piedmontese myostatin mutants as proof-of-concept, we propose a new algorithm that correctly identifies the gene containing the causal mutation from microarray data alone. The myostatin mutation releases the brakes on Piedmontese muscle growth by translating a dysfunctional protein. Compared to a less muscular non-mutant breed we find that myostatin is not differentially expressed at any of ten developmental time points. Despite this challenge, the algorithm identifies the myostatin 'smoking gun' through a coordinated, simultaneous, weighted integration of three sources of microarray information: transcript abundance, differential expression, and differential wiring. By asking the novel question "which regulator is cumulatively most differentially wired to the abundant most differentially expressed genes?" it yields the correct answer, "myostatin". Our new approach identifies causal regulatory changes by globally contrasting co-expression network dynamics. The entirely data-driven 'weighting' procedure emphasises regulatory movement relative to the phenotypically relevant part of the network. In contrast to other published methods that compare co-expression networks, significance testing is not used to eliminate connections.

A multiway analysis for identifying high integrity bovine BACs.

BACKGROUND: In large genomics projects involving many different types of analyses of bacterial artificial chromosomes (BACs), such as fingerprinting, end sequencing (BES) and full BAC sequencing there are many opportunities for the identities of BACs to become confused. However, by comparing the results from the different analyses, inconsistencies can be identified and a set of high integrity BACs preferred for future research can be defined. RESULTS: The location of each bovine BAC in the BAC fingerprint-based genome map and in the genome assembly were compared based on the reported BESs, and for a smaller number of BACs the full sequence. BACs with consistent positions in all three datasets, or if the full sequence was not available, for both the fingerprint map and BES-based alignments, were deemed to be correctly positioned. BACs with consistent BES-based and fingerprint-based locations, but with conflicting locations based on the fully sequenced BAC, appeared to have been misidentified during sequencing, and included a number of apparently swapped BACs. Inconsistencies between BES-based and fingerprint map positions identified thirty one plates from the CHORI-240 library that appear to have suffered substantial systematic problems during the end-sequencing of the BACs. No systematic problems were identified in the fingerprinting of the BACs. Analysis of BACs overlapping in the assembly identified a small overrepresentation of clones with substantial overlap in the library and a substantial enrichment of highly overlapping BACs on the same plate in the CHORI-240 library. More than half of these BACs appear to have been present as duplicates on the original BAC-library plates and thus should be avoided in subsequent projects. CONCLUSION: Our analysis shows that approximately 95% of the bovine CHORI-240 library clones with both a BAC fingerprint and two BESs mapping to the genome in the expected orientations (approximately 27% of all BACs) have consistent locations in the BAC fingerprint map and the genome assembly. We have developed a broadly applicable methodology for checking the integrity of BAC-based datasets even where only incomplete and partially assembled genomic sequence is available.

Analysis of the complement and molecular evolution of tRNA genes in cow.

BACKGROUND: Detailed information regarding the number and organization of transfer RNA (tRNA) genes at the genome level is becoming readily available with the increase of DNA sequencing of whole genomes. However the identification of functional tRNA genes is challenging for species that have large numbers of repetitive elements containing tRNA derived sequences, such as Bos taurus. Reliable identification and annotation of entire sets of tRNA genes allows the evolution of tRNA genes to be understood on a genomic scale. RESULTS: In this study, we explored the B. taurus genome using bioinformatics and comparative genomics approaches to catalogue and analyze cow tRNA genes. The initial analysis of the cow genome using tRNAscan-SE identified 31,868 putative tRNA genes and 189,183 pseudogenes, where 28,830 of the 31,868 predicted tRNA genes were classified as repetitive elements by the RepeatMasker program. We then used comparative genomics to further discriminate between functional tRNA genes and tRNA-derived sequences for the remaining set of 3,038 putative tRNA genes. For our analysis, we used the human, chimpanzee, mouse, rat, horse, dog, chicken and fugu genomes to predict that the number of active tRNA genes in cow lies in the vicinity of 439. Of this set, 150 tRNA genes were 100% identical in their sequences across all nine vertebrate genomes studied. Using clustering analyses, we identified a new tRNA-GlyCCC subfamily present in all analyzed mammalian genomes. We suggest that this subfamily originated from an ancestral tRNA-GlyGCC gene via a point mutation prior to the radiation of the mammalian lineages. Lastly, in a separate analysis we created phylogenetic profiles for each putative cow tRNA gene using a representative set of genomes to gain an overview of common evolutionary histories of tRNA genes. CONCLUSION: The use of a combination of bioinformatics and comparative genomics approaches has allowed the confident identification of a set of cow tRNA genes that will facilitate further studies in understanding the molecular evolution of cow tRNA genes.

Origin, evolution, and biological role of miRNA cluster in DLK-DIO3 genomic region in placental mammals.

MicroRNAs (miRNAs) are a rapidly growing family of small regulatory RNAs modulating gene expression in plants and animals. In animals, most of the miRNAs discovered in early studies were found to be evolutionarily conserved across the whole kingdom. More recent studies, however, have identified many miRNAs that are specific to a particular group of organisms or even a single species. These present a question about evolution of the individual miRNAs and their role in establishing and maintaining lineage-specific functions and characteristics. In this study, we describe a detailed analysis of the miRNA cluster (hereafter mir-379/mir-656 cluster) located within the imprinted DLK-DIO3 region on human chromosome 14. We show that orthologous miRNA clusters are present in all sequenced genomes of the placental (eutherian) mammals but not in the marsupial (metatherian), monotreme (prototherian), or any other vertebrate genomes. We provide evidence that the locus encompassing this cluster emerged in an early eutherian ancestor prior to the radiation of modern placental mammals by tandem duplication of the ancient precursor sequence. The original amplified cluster may have contained in excess of 250 miRNA precursor sequences, most of which now appear to be inactive. Examination of the eutherian genomes showed that the cluster has been maintained in evolution for approximately 100 Myr. Analysis of genes that contain predicted evolutionarily conserved targets for miRNAs from this cluster revealed significant overrepresentation of the Gene Ontology terms associated with biological processes such as neurogenesis, embryonic development, transcriptional regulation, and RNA metabolism. Consistent with these findings, a survey of the miRNA expression data within the cluster demonstrates a strong bias toward brain and placenta samples from adult organisms and some embryonic tissues. Our results suggest that emergence of the mir-379/mir-656 miRNA cluster was one of the factors that facilitated evolution of the placental mammals. Overrepresentation of genes involved in regulation of neurogenesis among predicted miRNAs targets indicates an important role of the mir-379/mir-656 cluster in this biological process in the placental mammals.

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data.

Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers, and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits and identifying potential genome editing targets.

Across-Experiment Transcriptomics of Sheep Rumen Identifies Expression of Lipid/Oxo-Acid Metabolism and Muscle Cell Junction Genes Associated With Variation in Methane-Related Phenotypes.

Ruminants are significant contributors to the livestock generated component of the greenhouse gas, methane (CH4). The CH4 is primarily produced by the rumen microbes. Although the composition of the diet and animal intake amount have the largest effect on CH4 production and yield (CH4 production/dry matter intake, DMI), the host also influences CH4 yield. Shorter rumen feed mean retention time (MRT) is associated with higher dry matter intake and lower CH4 yield, but the molecular mechanism(s) by which the host affects CH4 production remain unclear. We integrated rumen wall transcriptome data and CH4 phenotypes from two independent experiments conducted with sheep in Australia (AUS, n = 62) and New Zealand (NZ, n = 24). The inclusion of the AUS data validated the previously identified clusters and gene sets representing rumen epithelial, metabolic and muscular functions. In addition, the expression of the cell cycle genes as a group was consistently positively correlated with acetate and butyrate concentrations (p < 0.05, based on AUS and NZ data together). The expression of a group of metabolic genes showed positive correlations in both AUS and NZ datasets with CH4 production (p < 0.05) and yield (p < 0.01). These genes encode key enzymes in the ketone body synthesis pathway and included members of the poorly characterized aldo-keto reductase 1C (AKR1C) family. Several AKR1C family genes appear to have ruminant specific evolution patterns, supporting their specialized roles in the ruminants. Combining differential gene expression in the rumen wall muscle of the shortest and longest MRT AUS animals (no data available for the NZ animals) with correlation and network analysis, we identified a set of rumen muscle genes involved in cell junctions as potential regulators of MRT, presumably by influencing contraction rates of the smooth muscle component of the rumen wall. Higher rumen expression of these genes, including SYNPO (synaptopodin, p < 0.01) and NEXN (nexilin, p < 0.05), was associated with lower CH4 yield in both AUS and NZ datasets. Unlike the metabolic genes, the variations in the expression of which may reflect the availability of rumen metabolites, the muscle genes are currently our best candidates for causal genes that influence CH4 yield.

Simultaneous identification of differential gene expression and connectivity in inflammation, adipogenesis and cancer.

MOTIVATION: Biological differences between classes are reflected in transcriptional changes which in turn affect the levels by which essential genes are individually expressed and collectively connected. The purpose of this communication is to introduce an analytical procedure to simultaneously identify genes that are differentially expressed (DE) as well as differentially connected (DC) in two or more classes of interest. RESULTS: Our procedure is based on a two-step approach: First, mixed-model equations are applied to obtain the normalized expression levels of each gene in each class treatment. These normalized expressions form the basis to compute a measure of (possible) DE as well as the correlation structure existing among genes. Second, a two-component mixture of bi-variate distributions is fitted to identify the component that encapsulates those genes that are DE and/or DC. We demonstrate our approach using three distinct datasets including a human systemic inflammation oligonucleotide data; a spotted cDNA data dealing with bovine in vitro adipogenesis and SAGE database on cancerous and normal tissue samples.

A comparison of transcriptomic patterns measured in the skin of Chinese fine and coarse wool sheep breeds.

We characterised wool traits, and skin gene expression profiles of fine wool Super Merino (SM) and coarse wool Small Tail Han (STH) sheep. SM sheep had a significantly higher total density of wool follicles, heavier fleeces, finer fibre diameter, and increased crimp frequency, staple length and wool grease (lanolin) production. We found 435 genes were expressed at significantly different levels in the skin of the two breeds (127 genes more highly in SM and 308 genes more highly in STH sheep). Classification of the genes more highly expressed in SM sheep revealed numerous lipid metabolic genes as well as genes encoding keratins, keratin-associated proteins, and wool follicle stem cell markers. In contrast, mammalian epidermal development complex genes and other genes associated with skin cornification and muscle function were more highly expressed in STH sheep. Genes identified in this study may be further evaluated for inclusion in breeding programs, or as targets for therapeutic or genetic interventions, aimed at altering wool quality or yield. Expression of the lipid metabolic genes in the skin of sheep may be used as a novel trait with the potential to alter the content or properties of lanolin or the fleece.

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.

Epithelial, metabolic and innate immunity transcriptomic signatures differentiating the rumen from other sheep and mammalian gastrointestinal tract tissues.

Background. Ruminants are successful herbivorous mammals, in part due to their specialized forestomachs, the rumen complex, which facilitates the conversion of feed to soluble nutrients by micro-organisms. Is the rumen complex a modified stomach expressing new epithelial (cornification) and metabolic programs, or a specialised stratified epithelium that has acquired new metabolic activities, potentially similar to those of the colon? How has the presence of the rumen affected other sections of the gastrointestinal tract (GIT) of ruminants compared to non-ruminants? Methods. Transcriptome data from 11 tissues covering the sheep GIT, two stratified epithelial and two control tissues, was analysed using principal components to cluster tissues based on gene expression profile similarity. Expression profiles of genes along the sheep GIT were used to generate a network to identify genes enriched for expression in different compartments of the GIT. The data from sheep was compared to similar data sets from two non-ruminants, pigs (closely related) and humans (more distantly related). Results. The rumen transcriptome clustered with the skin and tonsil, but not the GIT transcriptomes, driven by genes from the epidermal differentiation complex, and genes encoding stratified epithelium keratins and innate immunity proteins. By analysing all of the gene expression profiles across tissues together 16 major clusters were identified. The strongest of these, and consistent with the high turnover rate of the GIT, showed a marked enrichment of cell cycle process genes (P = 1.4 E-46), across the whole GIT, relative to liver and muscle, with highest expression in the caecum followed by colon and rumen. The expression patterns of several membrane transporters (chloride, zinc, nucleosides, amino acids, fatty acids, cholesterol and bile acids) along the GIT was very similar in sheep, pig and humans. In contrast, short chain fatty acid uptake and metabolism appeared to be different between the species and different between the rumen and colon in sheep. The importance of nitrogen and iodine recycling in sheep was highlighted by the highly preferential expression of SLC14A1-urea (rumen), RHBG-ammonia (intestines) and SLC5A5-iodine (abomasum). The gene encoding a poorly characterized member of the maltase-glucoamylase family (MGAM2), predicted to play a role in the degradation of starch or glycogen, was highly expressed in the small and large intestines. Discussion. The rumen appears to be a specialised stratified cornified epithelium, probably derived from the oesophagus, which has gained some liver-like and other specialized metabolic functions, but probably not by expression of pre-existing colon metabolic programs. Changes in gene transcription downstream of the rumen also appear have occurred as a consequence of the evolution of the rumen and its effect on nutrient composition flowing down the GIT.

Gene network analysis identifies rumen epithelial cell proliferation, differentiation and metabolic pathways perturbed by diet and correlated with methane production.

Ruminants obtain nutrients from microbial fermentation of plant material, primarily in their rumen, a multilayered forestomach. How the different layers of the rumen wall respond to diet and influence microbial fermentation, and how these process are regulated, is not well understood. Gene expression correlation networks were constructed from full thickness rumen wall transcriptomes of 24 sheep fed two different amounts and qualities of a forage and measured for methane production. The network contained two major negatively correlated gene sub-networks predominantly representing the epithelial and muscle layers of the rumen wall. Within the epithelium sub-network gene clusters representing lipid/oxo-acid metabolism, general metabolism and proliferating and differentiating cells were identified. The expression of cell cycle and metabolic genes was positively correlated with dry matter intake, ruminal short chain fatty acid concentrations and methane production. A weak correlation between lipid/oxo-acid metabolism genes and methane yield was observed. Feed consumption level explained the majority of gene expression variation, particularly for the cell cycle genes. Many known stratified epithelium transcription factors had significantly enriched targets in the epithelial gene clusters. The expression patterns of the transcription factors and their targets in proliferating and differentiating skin is mirrored in the rumen, suggesting conservation of regulatory systems.

Characterisation and application of a bovine U6 promoter for expression of short hairpin RNAs.

BACKGROUND: The use of small interfering RNA (siRNA) molecules in animals to achieve double-stranded RNA-mediated interference (RNAi) has recently emerged as a powerful method of sequence-specific gene knockdown. As DNA-based expression of short hairpin RNA (shRNA) for RNAi may offer some advantages over chemical and in vitro synthesised siRNA, a number of vectors for expression of shRNA have been developed. These often feature polymerase III (pol. III) promoters of either mouse or human origin. RESULTS: To develop a shRNA expression vector specifically for bovine RNAi applications, we identified and characterised a novel bovine U6 small nuclear RNA (snRNA) promoter from bovine sequence data. This promoter is the putative bovine homologue of the human U6-8 snRNA promoter, and features a number of functional sequence elements that are characteristic of these types of pol. III promoters. A PCR based cloning strategy was used to incorporate this promoter sequence into plasmid vectors along with shRNA sequences for RNAi. The promoter was then used to express shRNAs, which resulted in the efficient knockdown of an exogenous reporter gene and an endogenous bovine gene. CONCLUSION: We have mined data from the bovine genome sequencing project to identify a functional bovine U6 promoter and used the promoter sequence to construct a shRNA expression vector. The use of this native bovine promoter in shRNA expression is an important component of our future development of RNAi therapeutic and transgenic applications in bovine species.