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

Gene regulation could be attributed to TCF3 and other key transcription factors in the muscle of pubertal heifers

Puberty is a whole-body event, driven by the hypothalamic integration of peripheral signals such as leptin or IGF-1. In the process of puberty, reproductive development is simultaneous to growth, including muscle growth. To enhance our understanding of muscle function related to puberty, we performed transcriptome analyses of muscle samples from six pre- and six post-pubertal Brahman heifers (Bos indicus). Our aims were to perform differential expression analyses and co-expression analyses to derive a regulatory gene network associate with puberty. As a result, we identified 431 differentially expressed (DEx) transcripts (genes and non-coding RNAs) when comparing pre- to post-pubertal average gene expression. The DEx transcripts were compared with all expressed transcripts in our samples (over 14,000 transcripts) for functional enrichment analyses. The DEx transcripts were associated with "extracellular region," "inflammatory response" and "hormone activity" (adjusted p < .05). Inflammatory response for muscle regeneration is a necessary aspect of muscle growth, which is accelerated during puberty. The term "hormone activity" may signal genes that respond to progesterone signalling in the muscle, as the presence of this hormone is an important difference between pre- and post-pubertal heifers in our experimental design. The DEx transcript with the highest average expression difference was a mitochondrial gene, ENSBTAG00000043574 that might be another important link between energy metabolism and puberty. In the derived co-expression gene network, we identified six hub genes: CDC5L, MYC, TCF3, RUNX2, ATF2 and CREB1. In the same network, 48 key regulators of DEx transcripts were identified, using a regulatory impact factor metric. The hub gene TCF3 was also a key regulator. The majority of the key regulators (22 genes) are members of the zinc finger family, which has been implicated in bovine puberty in other tissues. In conclusion, we described how puberty may affect muscle gene expression in cattle.

Exploring the longitudinal dynamics of herd BVD antibody test results using model-based clustering

Determining the Bovine Viral Diarrhoea (BVD) infection status of cattle herds is a challenge for control and eradication schemes. Given the changing dynamics of BVD  virus (BVDV) antibody responses in cattle, classifying herds based on longitudinal changes in the results of BVDV antibody tests could offer a novel, complementary approach to categorising herds that is less likely than the present system to result in a herd's status changing from year to year, as it is more likely to capture the true exposure dynamics of the farms. This paper describes the dynamics of BVDV antibody test values (measured as percentage positivity (PP)) obtained from 15,500 bovines between 2007 and 2010 from thirty nine cattle herds located in Scotland and Northern England. It explores approaches of classifying herds based on trend, magnitude and shape of their antibody PP trajectories and investigates the epidemiological similarities between farms within the same cluster. Gaussian mixture models were used for the magnitude and shape clustering. Epidemiologically meaningful clusters were obtained. Farm cluster membership depends on clustering approach used. Moderate concordance was found between the shape and magnitude clusters. These methods hold potential for application to enhance control efforts for BVD and other infectious livestock diseases.

Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post- versus prepubertal Brahman heifers

Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in (Brahman) in age- and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: , , , , and . These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric ( < 0.05). Two of these 5 TF, and , were zinc fingers, belonging to a gene family previously reported to have a central regulatory role in mammalian puberty. The gene belongs to the family of homologues of Drosophila sine oculis () genes implicated in transcriptional regulation of gonadotrope gene expression. Tumor-related genes such as and are known to affect basic cellular processes that are relevant in both cancer and developmental processes. Mutations in were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy.

Meta-analysis of genome-wide association from genomic prediction models

Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.

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

BACKGROUND

This study aimed to identify markers for muscle growth rate and the different cellular contributors to cattle muscle and to link the muscle growth rate markers to specific cell types.

RESULTS

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

CONCLUSIONS

Gene sets and gene markers for the analysis of many of the major processes/cell populations contributing to muscle composition and growth have been proposed, enabling a consistent interpretation of gene expression datasets from cattle LM. The same gene sets are likely to be applicable in other cattle muscles and in other species.

Identification of KCNJ11 as a functional candidate gene for bovine meat tenderness

The potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene was investigated as a candidate for meat tenderness based on the effects reported on muscle for KCNJ11 gene knockout in rat models and its position in a quantitative trait locus (QTL) for meat tenderness in the bovine genome. Sequence variations in the KCNJ11 gene were described by sequencing six amplified fragments, covering almost the entire gene. We identified single nucleotide polymorphisms (SNP) and validated them by different approaches, taking advantage of simultaneous projects that are being developed with the same Nelore population. By sequencing the KCNJ11 in Nelore steers representing extreme phenotypes for Warner-Bratzler shear force (WBSF), it was possible to identify 22 SNPs. We validated two of the identified markers by genotyping the whole population (n = 460). Analysis of association between genotypes and WBSF values revealed a significant additive effect of a SNP at different meat aging times (P ≤ 0.05). In addition, an association between the expression levels of KCNJ11 and WBSF was found, with lower expression levels of KCNJ11 associated with more tender meat (P ≤ 0.05). The results showed that the KCNJ11 gene is a candidate mapped to a QTL for meat tenderness previously identified on BTA15 and may be useful to identify animals with genetic potential to produce tender meat. The effect of KCNJ11 observed on muscle is potentially due to changes in activity of KATP channels, which in turn influence the flow of potassium in the intracellular space, allowing establishment of the membrane potential necessary for muscle contraction.

Transcription profiling provides insights into gene pathways involved in horn and scurs development in cattle

BACKGROUND

Two types of horns are evident in cattle - fixed horns attached to the skull and a variation called scurs, which refers to small loosely attached horns. Cattle lacking horns are referred to as polled. Although both the Poll and Scurs loci have been mapped to BTA1 and 19 respectively, the underlying genetic basis of these phenotypes is unknown, and so far, no candidate genes regulating these developmental processes have been described. This study is the first reported attempt at transcript profiling to identify genes and pathways contributing to horn and scurs development in Brahman cattle, relative to polled counterparts.

RESULTS

Expression patterns in polled, horned and scurs tissues were obtained using the Agilent 44 k bovine array. The most notable feature when comparing transcriptional profiles of developing horn tissues against polled was the down regulation of genes coding for elements of the cadherin junction as well as those involved in epidermal development. We hypothesize this as a key event involved in keratinocyte migration and subsequent horn development. In the polled-scurs comparison, the most prevalent differentially expressed transcripts code for genes involved in extracellular matrix remodelling, which were up regulated in scurs tissues relative to polled.

CONCLUSION

For this first time we describe networks of genes involved in horn and scurs development. Interestingly, we did not observe differential expression in any of the genes present on the fine mapped region of BTA1 known to contain the Poll locus.

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.

Directed mammalian gene regulatory networks using expression and comparative genomic hybridization microarray data from radiation hybrids

Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches.

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

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

Evolution, development, and cancer are governed by regulatory circuits where the central nodes are transcription factors. Consequently, there is great interest in methods that can identify the causal mutation/perturbation responsible for any circuit rewiring. The most widely available high-throughput technology, the microarray, assays the transcriptome. However, many regulatory perturbations are post-transcriptional. This means that they are overlooked by traditional differential gene expression analysis. We hypothesised that by viewing biological systems as networks one could identify causal mutations and perturbations by examining those regulators whose position in the network changes the most. Using muscular myostatin mutant cattle as a proof-of-concept, we propose an analysis that succeeds based solely on microarray expression data from just 27 animals. Our analysis differs from competing network approaches in that we do not use significance testing to eliminate connections. All connections are contrasted, no matter how weak. Further, the identity of target genes is maintained throughout the analysis. Finally, the analysis is ‘weighted’ such that movement relative to the phenotypically most relevant part of the network is emphasised. By identifying the question to which myostatin is the answer, we present a comparison of network connectivity that is potentially generalisable.

Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis

Background

Transcriptome variability is due to genetic and environmental causes, much like any other complex phenotype. Ascertaining the transcriptome differences between individuals is an important step to understand how selection and genetic drift may affect gene expression. To that end, extant divergent livestock breeds offer an ideal genetic material.

Results

We have analyzed with microarrays five tissues from the endocrine axis (hypothalamus, adenohypophysis, thyroid gland, gonads and fat tissue) of 16 pigs from both sexes pertaining to four extreme breeds (Duroc, Large White, Iberian and a cross with SinoEuropean hybrid line). Using a Bayesian linear model approach, we observed that the largest breed variability corresponded to the male gonads, and was larger than at the remaining tissues, including ovaries. Measurement of sex hormones in peripheral blood at slaughter did not detect any breed-related differences. Not unexpectedly, the gonads were the tissue with the largest number of sex biased genes. There was a strong correlation between sex and breed bias expression, although the most breed biased genes were not the most sex biased genes. A combined analysis of connectivity and differential expression suggested three biological processes as being primarily different between breeds: spermatogenesis, muscle differentiation and several metabolic processes.

Conclusion

These results suggest that differences across breeds in gene expression of the male gonads are larger than in other endocrine tissues in the pig. Nevertheless, the strong presence of breed biased genes in the male gonads cannot be explained solely by changes in spermatogenesis nor by differences in the reproductive tract development.

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

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.

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.

Gastrointestinal nematode challenge induces some conserved gene expression changes in the gut mucosa of genetically resistant sheep

Sheep have a varying ability to resist infection with gastrointestinal nematodes. This ability is due in part to genetic differences that exist between individuals. In order to define these differences we have used real-time PCR to quantify gene expression responses in the gut mucosal surface of genetically resistant and susceptible sheep, following a nematode challenge. Expression profiles were determined in response to two different nematode species, Haemonchus contortus and Trichostrongylus colubriformis, and in divergent sheep originating from two different genetic backgrounds. Results show that the response generated differs between resistant and susceptible animals and is further impacted by the origin of the sheep and nematode species used for challenge. However, some conserved features of a response mounted by a resistant or a susceptible animal were identified. Genes found to be more abundantly expressed in resistant animals include markers of an early inflammatory response, several Toll-like receptors (TLR2, 4, 9) and free radical producing genes (DUOX1 and NOS2A). Conversely, genes differentiating susceptible animals indicate a prolonged response and development of a chronic inflammatory state, characterised by elevated expression of members of the NF-kappabeta signalling pathway (IKBKB and NFKBIA) together with delayed expression of regulatory markers such as IL2RA (CD25), IL10 and TGFbeta2. While multiple nematode response pathways were identified, the identification of conserved aspects of the response which associate with resistance provides evidence that alternative nematode control strategies, such as breeding for resistant animals, may be feasible.

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.

Stress-induced gene expression profiling in the black tiger shrimp Penaeus monodon

Cultured shrimp are continuously exposed to variable environmental conditions that have been associated with stress and subsequent outbreaks of disease. To investigate the effect of environmental stress on Penaeus monodon gene expression, a 3,853 random cDNA microarray chip was generated with clones originating from six stress-enriched hemocyte libraries generated by suppression subtractive hybridization and a normal hemocyte cDNA library. Changes in temporal gene expression were analyzed from shrimp exposed to hypoxic, hyperthermic, and hypoosmotic conditions; 3.1% of the cDNAs were differentially expressed in response to at least one of the environmental stressors, and 72% of the differentially expressed clones had no significant sequence similarity to previously known genes. Among those genes with high identity to known sequences, the most common functional groups were immune-related genes and non-long terminal repeat retrotransposons. Hierarchical clustering revealed a set of cDNAs with temporal and stress-specific gene expression profiles as well as a set of cDNAs indicating a common stress response between stressors. Hypoxic and hyperthermic stressors induced the most severe short-term response in terms of gene regulation, and the osmotic stress had the least variation in expression profiles relative to the control. These expression data agree with observed differences in shrimp physical appearance and behavior following exposure to stress conditions.

Gene expression studies of developing bovine longissimus muscle from two different beef cattle breeds

BACKGROUND

The muscle fiber number and fiber composition of muscle is largely determined during prenatal development. In order to discover genes that are involved in determining adult muscle phenotypes, we studied the gene expression profile of developing fetal bovine longissimus muscle from animals with two different genetic backgrounds using a bovine cDNA microarray. Fetal longissimus muscle was sampled at 4 stages of myogenesis and muscle maturation: primary myogenesis (d 60), secondary myogenesis (d 135), as well as beginning (d 195) and final stages (birth) of functional differentiation of muscle fibers. All fetuses and newborns (total n = 24) were from Hereford dams and crossed with either Wagyu (high intramuscular fat) or Piedmontese (GDF8 mutant) sires, genotypes that vary markedly in muscle and compositional characteristics later in postnatal life.

RESULTS

We obtained expression profiles of three individuals for each time point and genotype to allow comparisons across time and between sire breeds. Quantitative reverse transcription-PCR analysis of RNA from developing longissimus muscle was able to validate the differential expression patterns observed for a selection of differentially expressed genes, with one exception. We detected large-scale changes in temporal gene expression between the four developmental stages in genes coding for extracellular matrix and for muscle fiber structural and metabolic proteins. FSTL1 and IGFBP5 were two genes implicated in growth and differentiation that showed developmentally regulated expression levels in fetal muscle. An abundantly expressed gene with no functional annotation was found to be developmentally regulated in the same manner as muscle structural proteins. We also observed differences in gene expression profiles between the two different sire breeds. Wagyu-sired calves showed higher expression of fatty acid binding protein 5 (FABP5) RNA at birth. The developing longissimus muscle of fetuses carrying the Piedmontese mutation shows an emphasis on glycolytic muscle biochemistry and a large-scale up-regulation of the translational machinery at birth. We also document evidence for timing differences in differentiation events between the two breeds.

CONCLUSION

Taken together, these findings provide a detailed description of molecular events accompanying skeletal muscle differentiation in the bovine, as well as gene expression differences that may underpin the phenotype differences between the two breeds. In addition, this study has highlighted a non-coding RNA, which is abundantly expressed and developmentally regulated in bovine fetal muscle.

Identification of a gene network contributing to hypertrophy in callipyge skeletal muscle

The callipyge mutation in sheep results in postnatal skeletal muscle hypertrophy in the pelvic limbs and loins with little or no effect on anterior skeletal muscles. Associated with the phenotype are changes in the expression of a number of imprinted genes flanking the site of the mutation, which lies in an intergenic region at the telomeric end of ovine chromosome 18. The manner in which these local changes in gene expression are translated into muscle hypertrophy is not known. Microarray-based transcriptional profiling was used to identify differentially expressed genes in longissimus dorsi skeletal muscle samples taken at birth and 12 wk of age from callipyge and wild-type sheep. The phenotype was only expressed at the latter developmental time and associated with decreased type 1 fibers (slow oxidative) and a shift toward type IIx and IIb fibers (fast-twitch glycolytic). We have identified 131 genes in the samples taken at 12 wk of age that were differentially expressed as a function of genotype but not due to the fiber type changes. The gene expression changes occurring as a function of genotype in the samples taken at birth indicated that the transcriptional framework underpinning the phenotype was emerging prior to expression of the phenotype. Eight genes were differentially expressed as a function of genotype at both developmental times. A model is proposed describing a core network of genes and histone epigenetic modifications that is likely to underpin the fiber type changes and muscle hypertrophy characteristic of callipyge sheep.

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

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

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.

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.

Differential gene expression of wheat progeny with contrasting levels of transpiration efficiency

High water use efficiency or transpiration efficiency (TE) in wheat is a desirable physiological trait for increasing grain yield under water-limited environments. The identification of genes associated with this trait would facilitate the selection for genotypes with higher TE using molecular markers. We performed an expression profiling (microarray) analysis of approximately 16,000 unique wheat ESTs to identify genes that were differentially expressed between wheat progeny lines with contrasting TE levels from a cross between Quarrion (high TE) and Genaro 81 (low TE). We also conducted a second microarray analysis to identify genes responsive to drought stress in wheat leaves. Ninety-three genes that were differentially expressed between high and low TE progeny lines were identified. One fifth of these genes were markedly responsive to drought stress. Several potential growth-related regulatory genes, which were down-regulated by drought, were expressed at a higher level in the high TE lines than the low TE lines and are potentially associated with a biomass production component of the Quarrion-derived high TE trait. Eighteen of the TE differentially expressed genes were further analysed using quantitative RT-PCR on a separate set of plant samples from those used for microarray analysis. The expression levels of 11 of the 18 genes were positively correlated with the high TE trait, measured as carbon isotope discrimination (Delta(13)C). These data indicate that some of these TE differentially expressed genes are candidates for investigating processes that underlie the high TE trait or for use as expression quantitative trait loci (eQTLs) for TE.

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.

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.