Sheep (Ovis aries) are a major source of meat, milk, and fiber in the form of wool and represent a distinct class of animals that have a specialized digestive organ, the rumen, that carries out the initial digestion of plant material. We have developed and analyzed a high-quality reference sheep genome and transcriptomes from 40 different tissues. We identified highly expressed genes encoding keratin cross-linking proteins associated with rumen evolution. We also identified genes involved in lipid metabolism that had been amplified and/or had altered tissue expression patterns. This may be in response to changes in the barrier lipids of the skin, an interaction between lipid metabolism and wool synthesis, and an increased role of volatile fatty acids in ruminants compared with nonruminant animals.
Muscle development and remodelling, mitochondrial physiology and inflammation are thought to be inter-related and to have implications for metabolism in both health and disease. However, our understanding of their molecular control is incomplete.
Delta relaxation enhanced magnetic resonance (dreMR) imaging requires an auxiliary B0 electromagnet capable of shifting the main magnetic field within a clinical 1.5 Tesla (T) MR system. In this work, the main causes of interaction between an actively shielded, insertable resistive B0 electromagnet and a 1.5T superconducting system are systematically identified and mitigated.
The expression of genes encoding proteins involved in triacyglyceride and fatty acid synthesis and storage in cattle muscle are correlated with intramuscular fat (IMF)%. Are the same genes also correlated with IMF% in sheep muscle, and can the same set of genes be used to estimate IMF% in both species?
We outline an in vivo cellular program of bovine longissimus muscle development inferred from expression data from 60 days post conception to 3months postnatal. Analytic challenges included changes in cellular composition, ambiguous diagnostic markers of cell type and contrasts between cattle human and mouse myogenesis. Nevertheless, the expression profiles of the myosin isoforms support slow and fast muscle fibres emanating from primary and secondary myogenesis respectively, while expression of the prenatal myosin subunits is down regulated prior to birth. Of the canonical pro-myogenic transcription factors (TF), MYF6 and MYF5 are negatively co-expressed, with MYF6 displaying higher expression in the post-natal samples and MYF5, MYOG, HES6 and PAX7 displaying higher expression in early development. A set of TFs (SIX1, EYA2 and DACH2) considered important in undifferentiated murine cells were equally abundant in differentiated bovine cells. An examination of mammalian regulators of fibre composition, muscle mass and muscle metabolism, underscored the roles of PPARGC1A, TGF? signalling and the NHR4 Nuclear Hormone Receptors on bovine muscle development. Enriched among the most variably expressed genes from the entire data set were molecules regulating mitochondrial metabolism of carbohydrate (PDK4), fat (UCP3), protein (AGXT2L1) and high energy phosphate (CKMT2). The dramatic increase in the expression of these transcripts, which may enable the peri-natal transition to metabolic independence critical for new-born herbivores, provides surprising evidence for substantial developmental remodelling of muscle mitochondria and reflects changes in nutrient availability. Overall, despite differences in size, metabolism and physiology, the muscle structural subunit expression program appears very similar in ruminants, rodents and humans.
A genome-wide association study (GWAS) was performed to investigate seven red blood cell (RBC) phenotypes in over 500 domestic sheep (Ovis aries) from three breeds (Columbia, Polypay, and Rambouillet). A single nucleotide polymorphism (SNP) showed genome-wide significant association with increased mean corpuscular hemoglobin concentration (MCHC, P?=?6.2×10(-14)) and genome-wide suggestive association with decreased mean corpuscular volume (MCV, P?=?2.5×10(-6)). The ovine HapMap project found the same genomic region and the same peak SNP has been under extreme historical selective pressure, demonstrating the importance of this region for survival, reproduction, and/or artificially selected traits. We observed a large (>50 kb) variant haplotype sequence containing a full-length divergent artiodactyl MYADM-like repeat in strong linkage disequilibrium with the associated SNP. MYADM gene family members play roles in membrane organization and formation in myeloid cells. However, to our knowledge, no member of the MYADM gene family has been identified in development of morphologically variant RBCs. The specific RBC differences may be indicative of alterations in morphology. Additionally, erythrocytes with altered morphological structure often exhibit increased structural fragility, leading to increased RBC turnover and energy expenditure. The divergent artiodactyl MYADM-like repeat was also associated with increased ewe lifetime kilograms of lamb weaned (P?=?2×10(-4)). This suggests selection for normal RBCs might increase lamb weights, although further validation is required before implementation in marker-assisted selection. These results provide clues to explain the strong selection on the artiodactyl MYADM-like repeat locus in sheep, and suggest MYADM family members may be important for RBC morphology in other mammals.
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(p110?) protects the heart against myocardial infarction. The aim of this study was to determine whether PI3K(p110?) 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(p110?) 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(p110?) on myocyte structure was assessed by treating neonatal rat ventricular myocytes with PI3K(p110?) 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.
The bacterial replisome is a target for the development of new antibiotics to combat drug resistant strains. The ?(2) sliding clamp is an essential component of the replicative machinery, providing a platform for recruitment and function of other replisomal components and ensuring polymerase processivity during DNA replication and repair. A single binding region of the clamp is utilized by its binding partners, which all contain conserved binding motifs. The C-terminal Leu and Phe residues of these motifs are integral to the binding interaction. We acquired three-dimensional structural information on the binding site in ?(2) by a study of the binding of modified peptides. Development of a three-dimensional pharmacophore based on the C-terminal dipeptide of the motif enabled identification of compounds that on further development inhibited ?-?(2) interaction at low micromolar concentrations. We report the crystal structure of the complex containing one of these inhibitors, a biphenyl oxime, bound to ?(2), as a starting point for further inhibitor design.
Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins--perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair--a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function--which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins--perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor--which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation.
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.
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.
The sheep CHORI-243 bacterial artificial chromosome (BAC) library is being used in the construction of the virtual sheep genome, the sequencing and construction of the actual sheep genome assembly and as a source of DNA for regions of the genome of biological interest. The objective of our study is to assess the integrity of the clones and plates which make up the CHORI-243 library using the virtual sheep genome.
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.
Two types of horns are evident in cattle - fixed horns attached to the skull and a variation called scurs, which refers to small loosely attached horns. Cattle lacking horns are referred to as polled. Although both the Poll and Scurs loci have been mapped to BTA1 and 19 respectively, the underlying genetic basis of these phenotypes is unknown, and so far, no candidate genes regulating these developmental processes have been described. This study is the first reported attempt at transcript profiling to identify genes and pathways contributing to horn and scurs development in Brahman cattle, relative to polled counterparts.
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.
Despite modern technologies and novel computational approaches, decoding causal transcriptional regulation remains challenging. This is particularly true for less well studied organisms and when only gene expression data is available. In muscle a small number of well characterised transcription factors are proposed to regulate development. Therefore, muscle appears to be a tractable system for proposing new computational approaches.
To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
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.
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.
The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability.
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.
We have recently described a method for the construction of an informative gene expression correlation landscape for a single tissue, longissimus muscle (LM) of cattle, using a small number (less than a hundred) of diverse samples. Does this approach facilitate interspecies comparison of networks?
The processes that drive tissue identity and differentiation remain unclear for most tissue types. So are the gene networks and transcription factors (TF) responsible for the differential structure and function of each particular tissue, and this is particularly true for non model species with incomplete genomic resources. To better understand the regulation of genes responsible for tissue identity in pigs, we have inferred regulatory networks from a meta-analysis of 20 gene expression studies spanning 480 Porcine Affymetrix chips for 134 experimental conditions on 27 distinct tissues. We developed a mixed-model normalization approach with a covariance structure that accommodated the disparity in the origin of the individual studies, and obtained the normalized expression of 12,320 genes across the 27 tissues. Using this resource, we constructed a network, based on the co-expression patterns of 1,072 TF and 1,232 tissue specific genes. The resulting network is consistent with the known biology of tissue development. Within the network, genes clustered by tissue and tissues clustered by site of embryonic origin. These clusters were significantly enriched for genes annotated in key relevant biological processes and confirm gene functions and interactions from the literature. We implemented a Regulatory Impact Factor (RIF) metric to identify the key regulators in skeletal muscle and tissues from the central nervous systems. The normalization of the meta-analysis, the inference of the gene co-expression network and the RIF metric, operated synergistically towards a successful search for tissue-specific regulators. Novel among these findings are evidence suggesting a novel key role of ERCC3 as a muscle regulator. Together, our results recapitulate the known biology behind tissue specificity and provide new valuable insights in a less studied but valuable model species.
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.
Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.
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