Molecular signatures of muscle growth and composition deciphered by the meta-analysis of age-related public transcriptomics data

The lean-to-fat ratio is a major issue in the beef meat industry from both carcass and meat production perspectives. This industrial perspective has motivated meat physiologists to use transcriptomics technologies to decipher mechanisms behind fat deposition within muscle during the time course of muscle growth. However, synthetic biological information from this volume of data remains to be produced to identify mechanisms found in various breeds and rearing practices. We conducted a meta-analysis on 10 transcriptomic data sets stored in public databases, from the longissimus thoracis of five different bovine breeds divergent by age. We updated gene identifiers on the last version of the bovine genome (UCD1.2), and the 715 genes common to the 10 studies were subjected to the meta-analysis. Of the 238 genes differentially expressed (DEG), we identified a transcriptional signature of the dynamic regulation of glycolytic and oxidative metabolisms that agrees with a known shift between those two pathways from the animal puberty. We proposed some master genes of the myogenesis, namely MYOG and MAPK14, as probable regulators of the glycolytic and oxidative metabolisms. We also identified overexpressed genes related to lipid metabolism (APOE, LDLR, MXRA8, and HSP90AA1) that may contribute to the expected enhanced marbling as age increases. Lastly, we proposed a transcriptional signature related to the induction (YBX1) or repression (MAPK14, YWAH, ERBB2) of the commitment of myogenic progenitors into the adipogenic lineage. The relationships between the abundance of the identified mRNA and marbling values remain to be analyzed in a marbling biomarkers discovery perspectives.

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.

Seasonal reorganization of the xylem transcriptome at different tree ages reveals novel insights into wood formation in Pinus radiata

*Seasonal wood development produces earlywood (EW) and latewood (LW) with distinct properties. The molecular mechanisms controlling EW and LW formation at different tree ages are poorly understood. *Seasonal reorganization of the xylem transcriptome was investigated in Pinus radiata at four tree ages using cDNA microarrays. Transcriptome profiles were compared with seasonal wood variation measured by SilviScan (CSIRO, Clayton, Australia). *The xylem transcriptome was considerably reorganized during seasonal change, and this reorganization showed a maturation-related pattern. The greater reorganization occurred at the transition (30%) and juvenile (21%) stages, but it declined with tree maturity (11-13%). However, this pattern does not correlate well with maturation-related patterns of seasonal wood variation. In total, 319 seasonal-responsive xylem candidate genes were identified. Many transcripts involved in primary and secondary wall biosynthesis were preferentially accumulated in EW and LW, respectively. A large proportion (45-81%) of the candidate genes are preferentially regulated at a single age and their transcript abundance may influence maturation-related patterns of seasonal wood variation. *Seasonal reorganization of the xylem transcriptome is significantly affected by tree age. Physiological changes at the transition stage may contribute to its greater seasonal transcriptome reorganization. Identified stage-preferential xylem transcripts could influence seasonal wood variation at different tree ages.

Skeletal muscle specific genes networks in cattle

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

A comprehensive characterisation of the fibre composition and properties of a limb (flexor digitorum superficialis, membri thoraci) and a trunk (psoas major) muscle in cattle

BACKGROUND

The fibre type attributes and the relationships among their properties play an important role in the differences in muscle capabilities and features. Comprehensive characterisation of the skeletal muscles should study the degree of association between them and their involvement in muscle functionality. The purposes of the present study were to characterise the fibre type composition of a trunk (Psoas major, PM) and a limb (Flexor digitorum, membri thoraci, FD) muscle in the bovine species and to study the degree of coordination among contractile, metabolic and histological properties of fibre types. Immunohistochemical, histochemical and histological techniques were used.

RESULTS

The fibre type composition was delineated immunohistochemically in calf muscle samples, identifying three pure (I, IIA, and IIX) and two hybrid type fibres (I+IIA, and IIAX). Most of the fibres in FD were types I and IIA, while pure IIX were absent. All fibre types were found in PM, the IIX type being the most frequent. Compared to other species, small populations of hybrid fibres were detected. The five fibre types, previously identified, were ascribed to three different acid and alkaline mATPase activity patterns. Type I fibres had the highest oxidative capacity and the lowest glycolytic capacity. The reverse was true for the IIX fibres, whereas the type IIA fibres showed intermediate properties. Regarding the histological properties, type I fibres tended to be more capillarised than the II types. Correlations among contractile, metabolic and histological features on individual fibres were significantly different from zero (r values varied between -0.31 and 0.78). Hybrid fibre values were positioned between their corresponding pure types, and their positions were different regarding their metabolic and contractile properties.

CONCLUSION

Coordination among the contractile, metabolic and histological properties of fibres has been observed. However, the magnitude of the correlation among them is always below 0.8, suggesting that the properties of muscles are not fully explained by the fibre composition. These results support the concept that, to some extent, muscle plasticity can be explained by the fibre type composition, and by the properties derived from their metabolic and histological profiles.

Gene expression patterns during intramuscular fat development in cattle

Deposition of intramuscular fat, or "marbling," in beef cattle contributes significantly to meat quality variables, including juiciness, flavor, and tenderness. The accumulation of intramuscular fat is largely influenced by the genetic background of cattle, as well as their age and nutrition. To identify genes that can be used as early biomarkers for the prediction of marbling capacity, we studied the muscle transcriptome of 2 cattle crossbreeds with contrasting intramuscular fat content. The transcriptomes of marbling LM tissue of heifers from Wagyu x Hereford (WxH; n = 6) and Piedmontese x Hereford (PxH; n = 7) crosses were profiled by using a combination of complementary DNA microarray and quantitative reverse transcription-PCR. Five biopsies of LM were taken from each animal at approximately 3, 7, 12, 20, and 25 mo from birth. Tissue was also collected from the LM of each animal at slaughter (approximately 30 mo). Microarray experiments, conducted on the first 3 biopsies of 2 animals from each crossbreed, identified 97 differentially expressed genes. The gene expression results indicated that the LM transcriptome of animals with high marbling potential (WxH) could be reliably distinguished from less marbled animals (PxH) when the animals were as young as 7 mo of age. At this early age, one cannot reliably determine meaningful differences in intramuscular fat deposition. We observed greater expression of a set of adipogenesis- and lipogenesis-related genes in the LM of young WxH animals compared with their PxH contemporaries. In contrast, genes highly expressed in PxH animals were associated with mitochondrial oxidative activity. Further quantitative reverse transcription-PCR experiments revealed that the messenger RNA of 6 of the lipogenesis-related genes also peaked at the age of 20 to 25 mo in WxH animals. The messenger RNA expression of ADIPOQ, SCD, and THRSP was highly correlated with intramuscular fat content of an individual in WxH animals. Our study provides clear evidence of early molecular changes associated with marbling and also identifies specific time frames when intramuscular fat development in cattle muscle can be detected by using gene expression. This information could be used by animal scientists to design optimal nutrition for high marbling potential. In addition, the genes found to be highly expressed during development of marbling could be used to develop genetic markers or biomarkers to assist with beef production strategies.

Gene expression profiling of muscle tissue in Brahman steers during nutritional restriction

Expression profiling using microarrays allows for the detailed characterization of the gene networks that regulate an animal's response to environmental stresses. During nutritional restriction, processes such as protein turnover, connective tissue remodeling, and muscle atrophy take place in the skeletal muscle of the animal. These processes and their regulation are of interest in the context of managing livestock for optimal production efficiency and product quality. Here we expand on recent research applying complementary DNA (cDNA) microarray technology to the study of the effect of nutritional restriction on bovine skeletal muscle. Using a custom cDNA microarray of 9,274 probes from cattle muscle and s.c. fat libraries, we examined the differential gene expression profile of the LM from 10 Brahman steers under three different dietary treatments. The statistical approach was based on mixed-model ANOVA and model-based clustering of the BLUP solutions for the gene x diet interaction effect. From the results, we defined a transcript profile of 156 differentially expressed array elements between the weight loss and weight gain diet substrates. After sequence and annotation analyses, the 57 upregulated elements represented 29 unique genes, and the 99 downregulated elements represented 28 unique genes. Most of these co-regulated genes cluster into groups with distinct biological function related to protein turnover and cytoskeletal metabolism and contribute to our mechanistic understanding of the processes associated with remodeling of muscle tissue in response to nutritional stress.

Gene expression profiling of porcine peripheral blood leukocytes after infection with Actinobacillus pleuropneumoniae

The gene expression profile of peripheral blood leukocytes (PBL) from extreme performing pigs after infection with Actinobacillus pleuropneumoniae was analysed using a custom complementary DNA (cDNA) microarray and quantitative reverse transcription-PCR (qRT-PCR). Four high performing animals with low disease-score (HP), three low performing animals with high disease-score (LP) and one medium performing animal with medium disease-score (MP) were selected for microarray profiling. PBL RNA from these eight pigs collected before and at 24h after APP infection, was examined. The study identified 92 genes that were up-regulated and four genes that were down-regulated in PBL RNA from HP pigs compared to LP pigs. The majority of differentially expressed (DE) genes were identified by virtue of their elevated expression in the HP animals at 24h post-infection. A large number of annotated DE genes are involved in innate immune response pathways. The gene expression profile of 10 DE candidate genes was further explored across the entire pig population in the same infection trial using qRT-PCR. Considerable animal-to-animal variation in PBL gene expression was observed, especially in the LP group. The qRT-PCR analysis suggested that only one true LP pig might be present in this study, which contributes significantly to the differential expression profile of the selected genes in HP animals following APP infection. This study has therefore identified a set of genes which could serve as molecular indicators for an effective immune response to APP in pigs and which could also serve as source for gene marker development in molecular genetics studies of heritable immune traits.

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

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

The effect of genetic variation of the retinoic acid receptor-related orphan receptor C gene on fatness in cattle

Genotypes at the retinoic acid receptor-related orphan receptor C (RORC) gene were associated with fatness in 1750 cattle. Ten SNPs were genotyped in RORC and the adjacent gene leucine-rich repeat neuronal 6D (LRRN6D) to map the QTL, 7 of which are in a 4.2-kb sequence around the ligand-binding domain of the RORC gene. Of the 29 inferred haplotypes for these SNPs, 2 have a combined frequency of 54.6% while the top 5 haplotypes have a combined frequency of 85.3%. The average D' value of linkage disequilibrium was 0.92 although the average r2 was a low 0.18. The RORC:g.3290T>G SNP had the strongest association with marbling. The inferred haplotypes were significantly associated with marbling and the difference between the most divergent haplotypes was 0.35 sigma(p) of marbling and 0.28 sigma(p) of rump fat, explaining the previously reported QTL effect. cDNA for RORC were sequenced and 2 new alternative transcripts were found. Fetal tissue shows 40 times greater transcription of RORC than adult tissue. The highest expression in fetal tissue was found in liver and kidney, but in adults the longissimus muscle had the greatest expression of the tissues tested.

Gene expression profiling of bovine skeletal muscle in response to and during recovery from chronic and severe undernutrition1

Gene expression profiles of LM from beef cattle that underwent significant postweaning undernutrition were studied using complementary DNA (cDNA) microarrays. After 114 d of undernutrition, the RNA from LM showed 2- to 6-fold less expression of many genes from the classes of muscle structural proteins, muscle metabolic enzymes, and extracellular matrix compared with animals on a rapid growth diet. The expression levels of these genes had mostly returned to pretreatment levels after 84 d of realimentation. The gene expression changes associated with undernutrition and BW loss showed an emphasis on downregulation of gene expression specific to fast-twitch fibers, typical of starving mammals, with a preferential atrophy of glycolytic fast-twitch fibers. We also identified a small group of genes that showed 2- to 5-fold elevated expression in LM after 114 d of undernutrition. Putative roles for these genes in atrophying skeletal muscle are regulation of myogenic differentiation (CSRP3), maintenance of mesenchymal stem cells (CYR61), modulation of membrane function (TM4SF2), prevention of oxidative damage (SESN1), and regulation of muscle protein degradation (SQSTM1). A significant increase in stearoyl-CoA desaturase (SCD) gene expression was observed in atrophying muscle, suggesting either that increased fatty acid synthesis is part of the tissue response to caloric restriction, or that SCD plays another role in energy metabolism in the mixed cellular environment of bovine skeletal muscle.

Joint analysis of multiple cDNA microarray studies via multivariate mixed models applied to genetic improvement of beef cattle

In functional genomic laboratories, it is common to use the same microarray slide across studies, each investigating a unique biological question, and each analyzed separately due to computational limitations and/or because there is no hybridization of samples from different studies on one slide. However, the question of analyzing data from multiple studies is a major current issue in microarray data analysis because there are gains to be made in the accuracy of estimated effects by exploiting a covariance structure between gene expression data across studies. We propose an approach for combining multiple studies using multivariate mixed models, with the assumption of a nonzero correlation among genes across experiments, while imposing a null residual covariance. We applied this method to jointly analyze three experiments in genetics of cattle with a total of 54 arrays, each with 19,200 spots and 7,638 elements. The resulting seven-variate model contains 752,476 equations and 56 covariances. To identify differentially expressed genes, we applied model-based clustering to a linear combination of the random gene x variety interaction effect. We enhanced the biological interpretation of the results by applying an iterative algorithm to identify the gene ontology classes that significantly changed in each experiment. We found 118 elements with coordinate expression that clustered into distinct biological functions such as adipogenesis and protein turnover. These results contribute to our understanding of the mechanistic processes involved in adipogenesis and nutrient partitioning.

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.

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.

Gene expression profiling of bovine in vitro adipogenesis using a cDNA microarray

The gene expression profile of bovine bone marrow stromal cells undergoing adipogenesis was established using a custom cDNA microarray. Cells that were treated with adipogenic stimulants and those that were not were collected at each of the six time points, and gene expression differences between the treated and untreated samples within each time point were compared using a microarray. Statistical analyses revealed that 158 genes showed a minimum fold change of 2 in at least one of the five post-differentiation time points. These genes are involved in various cellular pathways and functions, including lipogenesis, glycolysis, cytoskeleton remodelling, extracellular matrix, transcription as well as various signalling pathways such as insulin, calcium and wingless signalling. The experiment also identified 17 differentially expressed (DE) microarray elements with no assigned function. Quantitative real-time PCR was employed to validate eight DE genes, and the PCR data were found to reproduce the microarray data for these eight genes. Subsequent gene ontology annotation was able to provide a global overview of the molecular function of DE genes during adipogenesis. This analysis was able to indicate the importance of different gene categories at various stages of adipogenic conversion, thereby providing further insights into the molecular changes during bovine adipogenesis.

Gene expression-based approaches to beef quality research

Advances in mammalian genomics have permitted the application of gene expression profiling approaches to gene discovery for meat quality traits in cattle. The first custom cDNA microarray based on the transcriptome of bovine muscle and fat tissue was developed and applied to animal experimentation and cell culture experimentation between 1999 and 2005. Complementary DNA microarray tools for beef quality research were developed in parallel with bioinformatics tools that permit the analysis of microarray data obtained from complex experimental designs commonly encountered in large animal research. In addition, tools were designed to link gene expression data with gene function in the bovine, such as in vitro models of bovine adipogenesis and bioinformatics tools to map gene networks from expression data. The application of these genomics tools to the study of beef quality has yielded novel knowledge of genes and molecules involved in the processes of intramuscular adipogenesis and protein turnover. This review summarises the current state of knowledge and important lessons derived from bovine genomics initiatives in Australia and around the world.

Construction and validation of a Bovine Innate Immune Microarray

BACKGROUND

Microarray transcript profiling has the potential to illuminate the molecular processes that are involved in the responses of cattle to disease challenges. This knowledge may allow the development of strategies that exploit these genes to enhance resistance to disease in an individual or animal population.

RESULTS

The Bovine Innate Immune Microarray developed in this study consists of 1480 characterised genes identified by literature searches, 31 positive and negative control elements and 5376 cDNAs derived from subtracted and normalised libraries. The cDNA libraries were produced from 'challenged' bovine epithelial and leukocyte cells. The microarray was found to have a limit of detection of 1 pg/microg of total RNA and a mean slide-to-slide correlation co-efficient of 0.88. The profiles of differentially expressed genes from Concanavalin A (ConA) stimulated bovine peripheral blood lymphocytes were determined. Three distinct profiles highlighted 19 genes that were rapidly up-regulated within 30 minutes and returned to basal levels by 24 h; 76 genes that were up-regulated between 2-8 hours and sustained high levels of expression until 24 h and 10 genes that were down-regulated. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray analysis. The results indicate that there is a dynamic process involving gene activation and regulatory mechanisms re-establishing homeostasis in the ConA activated lymphocytes. The Bovine Innate Immune Microarray was also used to determine the cross-species hybridisation capabilities of an ovine PBL sample.

CONCLUSION

The Bovine Innate Immune Microarray has been developed which contains a set of well-characterised genes and anonymous cDNAs from a number of different bovine cell types. The microarray can be used to determine the gene expression profiles underlying innate immune responses in cattle and sheep.

Transcriptional profiling of skeletal muscle tissue from two breeds of cattle

We used a 9.6 K cattle muscle/fat cDNA microarray to study gene expression differences between the longuissimus dorsi (LD) muscle of Japanese Black (JB) and Holstein (HOL) cattle. JB cattle exhibit an unusual ability to accumulate intramuscular adipose tissue with fat melting points lower than that in other breeds. The LD biopsies from three JB (Tajima strain) and three HOL animals were used in this breed comparison. Seventeen genes were identified as preferentially expressed in LD samples from JB and seven genes were found to be expressed more highly in HOL. The expression of six selected differentially expressed genes was confirmed by quantitative real-time PCR. The genes more highly expressed in JB are associated with unsaturated fatty acid synthesis, fat deposition, and the thyroid hormone pathway. These results are consistent with the increased amounts and proportions of monounsaturated fatty acids observed in the muscle of JB animals. By discovering as yet uncharacterized genes that are differentially regulated in this comparison, the work may lead us to a better understanding of the regulatory pathways involved in the development of intramuscular adipose tissue.

Transcriptional profiling of muscle tissue in growing Japanese Black cattle to identify genes involved with the development of intramuscular fat

Japanese Black cattle are characterised by a unique ability to deposit intramuscular fat with lower melting temperature. In this study, 3 consecutive biopsies from Longissimus muscle tissue were taken and RNA isolated from 3 Japanese Black (Tajima strain) and 3 Holstein animals at age 11–20 months. The gene expression changes in these samples were analysed using a bovine fat/muscle cDNA microarray. A mixed-ANOVA model was fitted to the intensity signals. A total of 335 (4.8%) array elements were identified as differentially expressed genes in this breed × time comparison study. Genes preferentially expressed in Japanese Black are associated with mono-unsaturated fatty acid synthesis, fat deposition, adipogenesis development and muscle regulation, while examples of genes preferentially expressed in Holstein come from functional classes involved in connective tissue and skeletal muscle development. The gene expression differences detected between the Longissimus muscle of the 2 breeds give important clues to the molecular basis for the unique features of the Japanese Black breed, such as the onset and rate of adipose tissue development, metabolic differences, and signalling pathways involved in converting carbohydrate to lipid during lipogenesis. These findings will impact on industry management strategies designed to manipulate intramuscular adipose development at different development stages to gain maximum return for beef products.

Construction of gene interaction and regulatory networks in bovine skeletal muscle from expression data

We propose a data-driven reverse engineering approach to isolate the components of a gene interaction and regulatory network. We apply this method to the construction of a network for bovine skeletal muscle. Key nodes in the network include muscle-specific genes and transcription factors. muscle-specific genes are identified from data mining the USA National Cancer Institute, Cancer Genome Anatomy Project database, while transcription factors are predicted by accurate function annotation. A total of 5 microarray studies spanning 78 hybridisations and 23 different experimental conditions provided raw expression data. A recently-reported analytical method based on multivariate mixed-model equations is used to compute gene co-expression measures across 624 genes. The resulting network included 102 genes (of which 40 were muscle-specific genes and 7 were transcription factors) that clustered in 7 distinct modules with clear biological interpretation.

Gene expression profiling of ovine skin and wool follicle development using a combined ovine - bovine skin cDNA microarray

Low fibre diameter and high fleece weight are important determinants of the economic value of the Merino fleece. The combination of these traits is found in Merino sheep with high follicle densities resulting from a high secondary to primary follicle ratio. Morphological stages in the development of primary and secondary follicles of fetal sheep skin have been well described. We have used gene expression profiling of fetal skin to identify genes that may be important in controlling these follicle developmental processes. A combined ovine (2.3 K) and bovine (6.14 K) cDNA microarray of 2 fetal and 1 adult stage skin tissues was constructed to compare gene expression levels between fetal day 82, day 105, day 120 and adult sheep skin developmental stages. The transcript profile resulted in 238 differentially expressed array elements relative to the adult expression, which represented 132 unique genes. These clustered into 50 up- and 82 down-regulated genes and distinct gene ontologies including structural constituents, phosphate transport, signal transduction and organogenesis. Northern blot analysis of 2 selected genes, S100A7LI and TAGLN, validated the microarray results. This list of genes contains candidates of interest for further investigation into the molecular control of wool follicle development.

Genetics research in the Cooperative Research Centre for Cattle and Beef Quality

In its first 7-year term, the Cooperative Research Centre (CRC) for the Cattle and Beef Industry (Meat Quality) identified the genetic and non-genetic factors that impacted on beef eating quality. Following this, the CRC for Cattle and Beef Quality was established in 1999 to identify the consequences of improving beef eating quality and feed efficiency by genetic and non-genetic means on traits other than carcass and beef quality. The new CRC also had the responsibility to incorporate results from the first Beef CRC in national schemes such as BREEDPLAN (Australia’s beef genetic evaluation scheme) and Meat Standards Australia (Australia’s unique meat grading scheme that guarantees the eating quality of beef). This paper describes the integrated research programs and their results involving molecular and quantitative genetics, meat science, growth and nutrition and industry economics in the Beef CRC’s second phase (1999–2006) and the rationale for the individual genetics programs established. It summarises the planned scientific and beef industry outcomes from each of these programs and also describes the development and/or refinement by CRC scientists of novel technologies targeting increased genetic gains through enhanced measurement and recording in beef industry herds, thereby ensuring industry use of CRC results.

Validation of alternative methods of data normalization in gene co-expression studies

MOTIVATION

Clusters of genes encoding proteins with related functions, or in the same regulatory network, often exhibit expression patterns that are correlated over a large number of conditions. Protein associations and gene regulatory networks can be modelled from expression data. We address the question of which of several normalization methods is optimal prior to computing the correlation of the expression profiles between every pair of genes.

RESULTS

We use gene expression data from five experiments with a total of 78 hybridizations and 23 diverse conditions. Nine methods of data normalization are explored based on all possible combinations of normalization techniques according to between and within gene and experiment variation. We compare the resulting empirical distribution of gene x gene correlations with the expectations and apply cross-validation to test the performance of each method in predicting accurate functional annotation. We conclude that normalization methods based on mixed-model equations are optimal.