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Human skeletal muscle health is important for quality of life and several chronic diseases, including type II diabetes, heart disease, and cancer. Skeletal muscle is a tissue widely used to study mechanisms behind different diseases and adaptive effects of controlled interventions. For such mechanistic studies, knowledge about the gene expression profiles in different states is essential. Since the baseline transcriptome has not been analyzed systematically, the purpose of this study was to provide a deep reference profile of female and male skeletal muscle. RNA sequencing data were analyzed from a large set of 45 resting human muscle biopsies. We provide extensive information on the skeletal muscle transcriptome, including 5 previously unannotated protein-coding transcripts. Global transcriptional tissue homogeneity was strikingly high, within both a specific muscle and the contralateral leg. We identified23,000 known isoforms and found5000 isoforms that differ between the sexes. The female and male transcriptome was enriched for genes associated with oxidative metabolism and protein catabolic processes, respectively. The data demonstrate remarkably high tissue homogeneity and provide a deep and extensive baseline reference for the human skeletal muscle transcriptome, with regard to alternative splicing, novel transcripts, and sex differences in functional ontology.transcriptome: sex differences, alternative splicing, and tissue homogeneity assessed with RNA sequencing.

Regularly performed endurance training has many beneficial effects on health and skeletal muscle function, and can be used to prevent and treat common diseases e.g. cardiovascular disease, type II diabetes and obesity. The molecular adaptation mechanisms regulating these effects are incompletely understood. To date, global transcriptome changes in skeletal muscles have been studied at the gene level only. Therefore, global isoform expression changes following exercise training in humans are unknown. Also, the effects of repeated interventions on transcriptional memory or training response have not been studied before. In this study, 23 individuals trained one leg for three months. Nine months later, 12 of the same subjects trained both legs in a second training period. Skeletal muscle biopsies were obtained from both legs before and after both training periods. RNA sequencing analysis of all 119 skeletal muscle biopsies showed that training altered the expression of 3,404 gene isoforms, mainly associated with oxidative ATP production. Fifty-four genes had isoforms that changed in opposite directions. Training altered expression of 34 novel transcripts, all with protein-coding potential. After nine months of detraining, no training-induced transcriptome differences were detected between the previously trained and untrained legs. Although there were several differences in the physiological and transcriptional responses to repeated training, no coherent evidence of an endurance training induced transcriptional skeletal muscle memory was found. This human lifestyle intervention induced differential expression of thousands of isoforms and several transcripts from unannotated regions of the genome. It is likely that the observed isoform expression changes reflect adaptational mechanisms and processes that provide the functional and health benefits of regular physical activity., Author Summary Skeletal muscle is the most abundant tissue of the healthy human body. It is also highly adaptable to different environmental stimuli, e.g. regular exercise. Exercise training improves overall health and muscle function, and can be used to prevent and treat several common diseases e.g. cardiovascular disease and type II diabetes. Therefore, it is of great importance to understand the molecular mechanisms behind adaptation processes in human skeletal muscle. In this study, we show that different expression variants from the same gene can be regulated in different directions with training, implicating alternative protein functions from one single gene. Such findings are emblematic of the complex mechanisms regulating the effects of training. We also find that training changes the activity of functionally unknown parts of the genome, with the potential for new proteins involved in the health-enhancing effects of exercise. Additionally, our results challenge the belief of a skeletal muscle memory, where previous training can affect the response to a subsequent training period. Overall, we provide understanding of the skeletal muscle biology and novel insights into the mechanisms behind the massive benefits of regular exercise on the human skeletal muscle transcriptome, inspiring further studies for deeper investigation.

International audience; It has been unclear whether ischemic stroke induces neurogenesis or neuronal DNA rearrangements in the human neocortex. Using immunohistochemistry; transcriptome, genome and ploidy analyses; and determination of nuclear bomb test-derived (14)C concentration in neuronal DNA, we found neither to be the case. A large proportion of cortical neurons displayed DNA fragmentation and DNA repair a short time after stroke, whereas neurons at chronic stages after stroke showed DNA integrity, demonstrating the relevance of an intact genome for survival.

Background The majority of published gene-expression studies have used RNA isolated from whole cells, overlooking the potential impact of including nuclear transcriptome in the analyses. In this study, mRNA fractions from the cytoplasm and from whole cells (total RNA) were prepared from three human cell lines and sequenced using massive parallel sequencing. Results For all three cell lines, of about 15000 detected genes approximately 400 to 1400 genes were detected in different amounts in the cytoplasmic and total RNA fractions. Transcripts detected at higher levels in the total RNA fraction had longer coding sequences and higher number of miRNA target sites. Transcripts detected at higher levels in the cytoplasmic fraction were shorter or contained shorter untranslated regions. Nuclear retention of transcripts and mRNA degradation via miRNA pathway might contribute to this differential detection of genes. The consequence of the differential detection was further investigated by comparison to proteomics data. Interestingly, the expression profiles of cytoplasmic and total RNA correlated equally well with protein abundance levels indicating regulation at a higher level. Conclusions We conclude that expression levels derived from the total RNA fraction be regarded as an appropriate estimate of the amount of mRNAs present in a given cell population, independent of the coding sequence length or UTRs.

We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.

BACKGROUND: The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity. METHODOLOGY: In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation. CONCLUSION/SIGNIFICANCE: The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.