Publications by authors named "Brian P Dalrymple"

46 Publications

Modes of genetic adaptations underlying functional innovations in the rumen.

Sci China Life Sci 2021 01 5;64(1):1-21. Epub 2020 Nov 5.

College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, 210095, China.

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.
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http://dx.doi.org/10.1007/s11427-020-1828-8DOI Listing
January 2021

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.

Front Genet 2018 20;9:330. Epub 2018 Aug 20.

CSIRO Agriculture & Food, Queensland Bioscience Precinct, St Lucia, QLD, Australia.

Ruminants are significant contributors to the livestock generated component of the greenhouse gas, methane (CH). The CH is primarily produced by the rumen microbes. Although the composition of the diet and animal intake amount have the largest effect on CH production and yield (CH production/dry matter intake, DMI), the host also influences CH yield. Shorter rumen feed mean retention time (MRT) is associated with higher dry matter intake and lower CH yield, but the molecular mechanism(s) by which the host affects CH production remain unclear. We integrated rumen wall transcriptome data and CH phenotypes from two independent experiments conducted with sheep in Australia (AUS, = 62) and New Zealand (NZ, = 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 ( < 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 CH production ( < 0.05) and yield ( < 0.01). These genes encode key enzymes in the ketone body synthesis pathway and included members of the poorly characterized aldo-keto reductase 1C () family. Several 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 (synaptopodin, < 0.01) and (nexilin, < 0.05), was associated with lower CH 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 CH yield.
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http://dx.doi.org/10.3389/fgene.2018.00330DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6109778PMC
August 2018

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

Gigascience 2018 03;7(3):1-17

CSIRO Agriculture, 306 Carmody Road, St. Lucia, 4067, QLD, Australia.

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.
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http://dx.doi.org/10.1093/gigascience/gix136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838836PMC
March 2018

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

Sci Rep 2017 10 30;7(1):14301. Epub 2017 Oct 30.

CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd, 4067, Queensland, Australia.

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.
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http://dx.doi.org/10.1038/s41598-017-14772-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662721PMC
October 2017

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

Sci Rep 2016 12 14;6:39022. Epub 2016 Dec 14.

CSIRO Agriculture, Queensland Bioscience Precinct, 306 Carmody Rd, 4067 Queensland, Australia.

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.
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http://dx.doi.org/10.1038/srep39022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5155297PMC
December 2016

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

PeerJ 2016 8;4:e1762. Epub 2016 Mar 8.

CSIRO Agriculture , St. Lucia, QLD , Australia.

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.
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http://dx.doi.org/10.7717/peerj.1762DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4793311PMC
March 2016

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

BMC Genomics 2015 Mar 13;16:177. Epub 2015 Mar 13.

CSIRO Agriculture Flagship, St. Lucia, QLD, 4067, Australia.

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.
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http://dx.doi.org/10.1186/s12864-015-1403-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4364331PMC
March 2015

A gene expression estimator of intramuscular fat percentage for use in both cattle and sheep.

J Anim Sci Biotechnol 2014 16;5(1):35. Epub 2014 Jun 16.

CSIRO Animal, Food and Health Sciences, St. Lucia QLD 4067, Australia.

Background: 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?

Results: The correlation between gene expression (microarray) and IMF% in the longissimus muscle (LM) of twenty sheep was calculated. An integrated analysis of this dataset with an equivalent cattle correlation dataset and a cattle differential expression dataset was undertaken. A total of 30 genes were identified to be strongly correlated with IMF% in both cattle and sheep. The overlap of genes was highly significant, 8 of the 13 genes in the TAG gene set and 8 of the 13 genes in the FA gene set were in the top 100 and 500 genes respectively most correlated with IMF% in sheep, P-value = 0. Of the 30 genes, CIDEA, THRSP, ACSM1, DGAT2 and FABP4 had the highest average rank in both species. Using the data from two small groups of Brahman cattle (control and Hormone growth promotant-treated [known to decrease IMF% in muscle]) and 22 animals in total, the utility of a direct measure and different estimators of IMF% (ultrasound and gene expression) to differentiate between the two groups were examined. Directly measured IMF% and IMF% estimated from ultrasound scanning could not discriminate between the two groups. However, using gene expression to estimate IMF% discriminated between the two groups. Increasing the number of genes used to estimate IMF% from one to five significantly increased the discrimination power; but increasing the number of genes to 15 resulted in little further improvement.

Conclusion: We have demonstrated the utility of a comparative approach to identify robust estimators of IMF% in the LM in cattle and sheep. We have also demonstrated a number of approaches (potentially applicable to much smaller groups of animals than conventional methods) to using gene expression to rank animals for IMF% within a single farm/treatment, or to estimate differences in IMF% between two farms/treatments.
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http://dx.doi.org/10.1186/2049-1891-5-35DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4099020PMC
July 2014

The sheep genome illuminates biology of the rumen and lipid metabolism.

Science 2014 Jun;344(6188):1168-1173

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.

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.
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http://dx.doi.org/10.1126/science.1252806DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4157056PMC
June 2014

RNF14 is a regulator of mitochondrial and immune function in muscle.

BMC Syst Biol 2014 Jan 29;8:10. Epub 2014 Jan 29.

CSIRO Animal, Food and Health Sciences, 306 Carmody Road, St, Lucia, Queensland, Australia.

Background: 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.

Results: In this study we have confirmed that the ring finger 14 protein (RNF14), a poorly understood transcriptional regulator, influences the expression of both mitochondrial and immune-related genes. The prediction was based on a combination of network connectivity and differential connectivity in cattle (a non-model organism) and mice data sets, with a focus on skeletal muscle. They assigned similar probability to mammalian RNF14 playing a regulatory role in mitochondrial and immune gene expression. To try and resolve this apparent ambiguity we performed a genome-wide microarray expression analysis on mouse C2C12 myoblasts transiently transfected with two Rnf14 transcript variants that encode 2 naturally occurring but different RNF14 protein isoforms. The effect of both constructs was significantly different to the control samples (untransfected cells and cells transfected with an empty vector). Cluster analyses revealed that transfection with the two Rnf14 constructs yielded discrete expression signatures from each other, but in both cases a substantial set of genes annotated as encoding proteins related to immune function were perturbed. These included cytokines and interferon regulatory factors. Additionally, transfection of the longer transcript variant 1 coordinately increased the expression of 12 (of the total 13) mitochondrial proteins encoded by the mitochondrial genome, 3 of which were significant in isolated pair-wise comparisons (Mt-coxII, Mt-nd2 and mt-nd4l). This apparent additional mitochondrial function may be attributable to the RWD protein domain that is present only in the longer RNF14 isoform.

Conclusions: RNF14 influences the expression of both mitochondrial and immune related genes in a skeletal muscle context, and has likely implications for the inter-relationship between bioenergetic status and inflammation.
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http://dx.doi.org/10.1186/1752-0509-8-10DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3906743PMC
January 2014

A divergent Artiodactyl MYADM-like repeat is associated with erythrocyte traits and weight of lamb weaned in domestic sheep.

PLoS One 2013 30;8(8):e74700. Epub 2013 Aug 30.

Animal Disease Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Pullman, Washington, United States of America ; Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, Washington, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0074700PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3758307PMC
April 2014

Inferring the in vivo cellular program of developing bovine skeletal muscle from expression data.

Gene Expr Patterns 2013 Mar-Apr;13(3-4):109-25. Epub 2013 Feb 16.

Computational and Systems Biology Group, CSIRO Food Futures and CSIRO Animal, Food and Health Sciences, 306 Carmody Road, St. Lucia, QLD 4072, Australia.

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, TGFβ 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.
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http://dx.doi.org/10.1016/j.gep.2013.02.001DOI Listing
September 2013

An Always Correlated gene expression landscape for ovine skeletal muscle, lessons learnt from comparison with an "equivalent" bovine landscape.

BMC Res Notes 2012 Nov 13;5:632. Epub 2012 Nov 13.

Animal Science and Technology College, Yangzhou University, Yangzhou 225009, China.

Background: 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?

Findings: Using gene expression datasets from LM samples from a single postnatal time point for high and low muscling sheep, and from a developmental time course (prenatal to postnatal) for normal sheep and sheep exhibiting the Callipyge muscling phenotype gene expression correlations were calculated across subsets of the data comparable to the bovine analysis. An "Always Correlated" gene expression landscape was constructed by integrating the correlations from the subsets of data and was compared to the equivalent landscape for bovine LM muscle. Whilst at the high level apparently equivalent modules were identified in the two species, at the detailed level overlap between genes in the equivalent modules was limited and generally not significant. Indeed, only 395 genes and 18 edges were in common between the two landscapes.

Conclusions: Since it is unlikely that the equivalent muscles of two closely related species are as different as this analysis suggests, within tissue gene expression correlations appear to be very sensitive to the samples chosen for their construction, compounded by the different platforms used. Thus users need to be very cautious in interpretation of the differences. In future experiments, attention will be required to ensure equivalent experimental designs and use cross-species gene expression platform to enable the identification of true differences between different species.
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http://dx.doi.org/10.1186/1756-0500-5-632DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543716PMC
November 2012

Porcine tissue-specific regulatory networks derived from meta-analysis of the transcriptome.

PLoS One 2012 26;7(9):e46159. Epub 2012 Sep 26.

Computational and Systems Biology, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Animal, Food and Health Sciences, Queensland Bioscience Precinct, St. Lucia, Brisbane, Queensland, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0046159PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458843PMC
April 2013

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

BMC Genomics 2012 Jul 31;13:356. Epub 2012 Jul 31.

Computational and Systems BiologyCSIRO Livestock Industries, 306 Carmody Road St, Lucia, Brisbane, QLD 4067, Australia.

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.
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http://dx.doi.org/10.1186/1471-2164-13-356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444927PMC
July 2012

Eukaryotic evolutionary transitions are associated with extreme codon bias in functionally-related proteins.

PLoS One 2011 23;6(9):e25457. Epub 2011 Sep 23.

Computational and Systems Biology, CSIRO Livestock Industries, Queensland Bioscience Precinct, St. Lucia, Brisbane, Queensland, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0025457PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3179510PMC
February 2012

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

J Biol Chem 2011 Sep 11;286(35):30837-30846. Epub 2011 Jul 11.

Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, 8008, Australia. Electronic address:

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.
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http://dx.doi.org/10.1074/jbc.M111.271684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3162444PMC
September 2011

Binding inhibitors of the bacterial sliding clamp by design.

J Med Chem 2011 Jul 7;54(13):4831-8. Epub 2011 Jun 7.

CSIRO Livestock Industries, St. Lucia, Queensland 4067, Australia.

The bacterial replisome is a target for the development of new antibiotics to combat drug resistant strains. The β(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 β(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 α-β(2) interaction at low micromolar concentrations. We report the crystal structure of the complex containing one of these inhibitors, a biphenyl oxime, bound to β(2), as a starting point for further inhibitor design.
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http://dx.doi.org/10.1021/jm2004333DOI Listing
July 2011

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

Physiol Genomics 2011 May 15;43(9):467-78. Epub 2011 Feb 15.

Australian Cooperative Research Centre for Beef Genetic Technologies, University of New England, Armidale, New South Wales.

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.
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http://dx.doi.org/10.1152/physiolgenomics.00226.2010DOI Listing
May 2011

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

BMC Genomics 2011 Jan 12;12:23. Epub 2011 Jan 12.

Computational and Systems Biology, CSIRO Food Futures Flagship and CSIRO Livestock Industries, 306 Carmody Rd, St. Lucia, Brisbane, Queensland 4067, Australia.

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.
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http://dx.doi.org/10.1186/1471-2164-12-23DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3025955PMC
January 2011

Quality control of the sheep bacterial artificial chromosome library, CHORI-243.

BMC Res Notes 2010 Dec 13;3:334. Epub 2010 Dec 13.

CSIRO Livestock Industries, 306 Carmody Road, St, Lucia, QLD 4067, Australia.

Background: 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.

Findings: A series of analyses were undertaken based on the mapping the sheep BAC-end sequences (BESs) to the virtual sheep genome. Overall, very few plate specific biases were identified, with only three of the 528 plates in the library significantly affected. The analysis of the number of tail-to-tail (concordant) BACs on the plates identified a number of plates with lower than average numbers of such BACs. For plates 198 and 213 a partial swap of the BESs determined with one of the two primers appear to have occurred. A third plate, 341, also with a significant deficit in tail-to-tail BACs, appeared to contain a substantial number of sequences determined from contaminating eubacterial 16 S rRNA DNA. Additionally a small number of eubacterial 16 S rRNA DNA sequences were present on two other plates, 111 and 338, in the library.

Conclusions: The comparative genomic approach can be used to assess BAC library integrity in the absence of fingerprinting. The sequences of the sheep CHORI-243 library BACs have high integrity, especially with the corrections detailed above. The library represents a high quality resource for use by the sheep genomics community.
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http://dx.doi.org/10.1186/1756-0500-3-334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3020178PMC
December 2010

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

BMC Genomics 2010 Aug 3;11:458. Epub 2010 Aug 3.

CSIRO Livestock Industries, 306 Carmody Road, St, Lucia, QLD 4067, Australia.

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.
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http://dx.doi.org/10.1186/1471-2164-11-458DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091654PMC
August 2010

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

Bioinformatics 2010 Apr 9;26(7):896-904. Epub 2010 Feb 9.

Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, Brisbane, Queensland 4067, Australia.

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.
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http://dx.doi.org/10.1093/bioinformatics/btq051DOI Listing
April 2010

Inferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks.

PLoS One 2009 Oct 1;4(10):e7249. Epub 2009 Oct 1.

Food Futures Flagship and Livestock Industries, Commonwealth Scientific and Industrial Research Organisation, Queensland Bioscience Precinct, St. Lucia, Brisbane, Queensland, Australia.

Background: 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.

Methodology/principal Findings: Here we report a simple algorithm that asks "which transcriptional regulator has the highest average absolute co-expression correlation to the genes in a co-expression module?" It correctly infers a number of known causal regulators of fundamental biological processes, including cell cycle activity (E2F1), glycolysis (HLF), mitochondrial transcription (TFB2M), adipogenesis (PIAS1), neuronal development (TLX3), immune function (IRF1) and vasculogenesis (SOX17), within a skeletal muscle context. However, none of the canonical pro-myogenic transcription factors (MYOD1, MYOG, MYF5, MYF6 and MEF2C) were linked to muscle structural gene expression modules. Co-expression values were computed using developing bovine muscle from 60 days post conception (early foetal) to 30 months post natal (adulthood) for two breeds of cattle, in addition to a nutritional comparison with a third breed. A number of transcriptional landscapes were constructed and integrated into an always correlated landscape. One notable feature was a 'metabolic axis' formed from glycolysis genes at one end, nuclear-encoded mitochondrial protein genes at the other, and centrally tethered by mitochondrially-encoded mitochondrial protein genes.

Conclusions/significance: The new module-to-regulator algorithm complements our recently described Regulatory Impact Factor analysis. Together with a simple examination of a co-expression module's contents, these three gene expression approaches are starting to illuminate the in vivo transcriptional regulation of skeletal muscle development.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0007249PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2749936PMC
October 2009

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

PLoS Comput Biol 2009 May 1;5(5):e1000382. Epub 2009 May 1.

Food Futures Flagship and Livestock Industries, Commonwealth Scientific and Industrial Research Organisation, Queensland Bioscience Precinct, St Lucia Brisbane, Queensland, Australia.

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.
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http://dx.doi.org/10.1371/journal.pcbi.1000382DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2671163PMC
May 2009

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

BMC Genomics 2009 Apr 24;10:188. Epub 2009 Apr 24.

CSIRO Livestock Industries, Queensland Biosciences Precinct, St Lucia, QLD, Australia.

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.
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http://dx.doi.org/10.1186/1471-2164-10-188DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680898PMC
April 2009

A genome wide survey of SNP variation reveals the genetic structure of sheep breeds.

PLoS One 2009 3;4(3):e4668. Epub 2009 Mar 3.

CSIRO Livestock Industries, St Lucia, Brisbane, Queensland, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0004668PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652362PMC
May 2009

A multiway analysis for identifying high integrity bovine BACs.

BMC Genomics 2009 Jan 23;10:46. Epub 2009 Jan 23.

CSIRO Livestock Industries, 306 Carmody Road, St. Lucia, QLD 4067, Australia.

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.
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http://dx.doi.org/10.1186/1471-2164-10-46DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2660975PMC
January 2009

Using a 3D virtual muscle model to link gene expression changes during myogenesis to protein spatial location in muscle.

BMC Syst Biol 2008 Oct 22;2:88. Epub 2008 Oct 22.

CSIRO, Food Futures Flagship, Queensland Bioscience Precinct, 306 Carmody Road, St, Lucia, QLD 4067, Australia.

Background: Myogenesis is an ordered process whereby mononucleated muscle precursor cells (myoblasts) fuse into multinucleated myotubes that eventually differentiate into myofibres, involving substantial changes in gene expression and the organisation of structural components of the cells. To gain further insight into the orchestration of these structural changes we have overlaid the spatial organisation of the protein components of a muscle cell with their gene expression changes during differentiation using a new 3D visualisation tool: the Virtual Muscle 3D (VMus3D).

Results: Sets of generic striated muscle costamere, Z-disk and filament proteins were constructed from the literature and protein-interaction databases. Expression profiles of the genes encoding these proteins were obtained from mouse C2C12 cells undergoing myogenesis in vitro, as well as a mouse tissue survey dataset. Visualisation of the expression data in VMus3D yielded novel observations with significant relationships between the spatial location and the temporal expression profiles of the structural protein products of these genes. A muscle specificity index was calculated based on muscle expression relative to the median expression in all tissues and, as expected, genes with the highest muscle specificity were also expressed most dynamically during differentiation. Interestingly, most genes encoding costamere as well as some Z-disk proteins appeared to be broadly expressed across most tissues and showed little change in expression during muscle differentiation, in line with the broader cellular role described for some of these proteins.

Conclusion: By studying gene expression patterns from a structural perspective we have demonstrated that not all genes encoding proteins that are part of muscle specific structures are simply up-regulated during muscle cell differentiation. Indeed, a group of genes whose expression program appears to be minimally affected by the differentiation process, code for proteins participating in vital skeletal muscle structures. Expression alone is a poor metric of gene behaviour. Instead, the "connectivity model of muscle development" is proposed as a mechanism for muscle development: whereby the closer to the myofibril core of muscle cells, the greater the gene expression changes during muscle differentiation and the greater the muscle specificity.
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http://dx.doi.org/10.1186/1752-0509-2-88DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2596796PMC
October 2008
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