Nicholas J. Hudson

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.

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

BackgroundThe 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.ResultsWe 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.ConclusionTaken 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.

Regulatory impact factors

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.

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

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 modules contents, these three gene expression approaches are starting to illuminate the in vivo transcriptional regulation of skeletal muscle development.

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

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

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.

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.

Differences in muscle transcriptome among pigs phenotypically extreme for fatty acid composition

Background Besides having an impact on human health, the porcine muscle fatty acid profile determines meat quality and taste. The RNA-Seq technologies allowed us to explore the pig muscle transcriptome with an unprecedented detail. The aim of this study was to identify differentially-expressed genes between two groups of 6 sows belonging to an Iberian × Landrace backcross with extreme phenotypes according to FA profile. Results We sequenced the muscle transcriptome acquiring 787.5 M of 75 bp paired-end reads. About 85.1% of reads were mapped to the reference genome. Of the total reads, 79.1% were located in exons, 6.0% in introns and 14.9% in intergenic regions, indicating expressed regions not annotated in the reference genome. We identified a 34.5% of the intergenic regions as interspersed repetitive regions. We predicted a total of 2,372 putative proteins. Pathway analysis with 131 differentially-expressed genes revealed that the most statistically-significant metabolic pathways were related with lipid metabolism. Moreover, 18 of the differentially-expressed genes were located in genomic regions associated with IMF composition in an independent GWAS study in the same genetic background. Thus, our results indicate that the lipid metabolism of FAs is differently modulated when the FA composition in muscle differs. For instance, a high content of PUFA may reduce FA and glucose uptake resulting in an inhibition of the lipogenesis. These results are consistent with previous studies of our group analysing the liver and the adipose tissue transcriptomes providing a view of each of the main organs involved in lipid metabolism. Conclusions The results obtained in the muscle transcriptome analysis increase the knowledge of the gene regulation of IMF deposition, FA profile and meat quality, in terms of taste and nutritional value. Besides, our results may be important in terms of human health.

Skeletal muscle atrophy occurs slowly and selectively during prolonged aestivation in Cyclorana alboguttata (Gunther 1867).

SUMMARY We investigated the effect of prolonged immobilisation of six and nine months duration on the morphology and antioxidant biochemistry of skeletal muscles in the amphibian aestivator Cyclorana alboguttata. We hypothesised that, in the event of atrophy occurring during aestivation, larger jumping muscles were more likely to be preserved over smaller non-jumping muscles. Whole muscle mass (g), muscle cross-sectional area (CSA) (μm2), water content (%) and myofibre number (per mm2) remained unchanged in the cruralis muscle after six to nine months of aestivation; however, myofibre area (μm2) was significantly reduced. Whole muscle mass, water content, myofibre number and myofibre CSA remained unchanged in the gastrocnemius muscle after six to nine months of aestivation. However, iliofibularis dry muscle mass, whole muscle CSA and myofibre CSA was significantly reduced during aestivation. Similarly, sartorius dry muscle mass, water content and whole muscle CSA was significantly reduced during aestivation. Endogenous antioxidants were maintained at control levels throughout aestivation in all four muscles. The results suggest changes to muscle morphology during aestivation may occur when lipid reserves have been depleted and protein becomes the primary fuel substrate for preserving basal metabolic processes. Muscle atrophy as a result of this protein catabolism may be correlated with locomotor function, with smaller non-jumping muscles preferentially used as a protein source during fasting over larger jumping muscles. Higher levels of endogenous antioxidants in the jumping muscles may confer a protective advantage against oxidative damage during aestivation; however, it is not clear whether they play a role during aestivation or upon resumption of normal metabolic activity.

Effect of aestivation on long bone mechanical properties in the green-striped burrowing frog, Cyclorana alboguttata

SUMMARY The green-striped burrowing frog, Cyclorana alboguttata, survives extended drought periods by burrowing underground and aestivating. These frogs remain immobile within cocoons of shed skin and mucus during aestivation and emerge from their burrows upon heavy rains to feed and reproduce. Extended periods of immobilisation in mammals typically result in bone remodelling and a decrease in bone strength. We examined the effect of aestivation and, hence, prolonged immobilisation on cross-sectional area, histology and bending strength in the femur and tibiofibula of C. alboguttata. Frogs were aestivated in soil for three and nine months and were compared with control animals that remained active, were fed and had a continual supply of water. Compared with the controls, long bone size, anatomy and bending strength remained unchanged, indicating an absence of disuse osteoporosis. This preservation of bone tissue properties enables C. alboguttata to compress the active portions of their life history into unpredictable windows of opportunity, whenever heavy rains occur.