Revealing myopathy spectrum: integrating transcriptional and clinical features of human skeletal muscles with varying health conditions.

Myopathy refers to a large group of heterogeneous, rare muscle diseases. Bulk RNA-sequencing has been utilized for the diagnosis and research of these diseases for many years. However, the existing valuable sequencing data often lack integration and clinical interpretation. In this study, we integrated bulk RNA-sequencing data from 1221 human skeletal muscles (292 with myopathies, 929 controls) from both databases and our local samples. By applying a method similar to single-cell analysis, we revealed a general spectrum of muscle diseases, ranging from healthy to mild disease, moderate muscle wasting, and severe muscle disease. This spectrum was further partly validated in three specific myopathies (97 muscles) through clinical features including trinucleotide repeat expansion, magnetic resonance imaging fat fraction, pathology, and clinical severity scores. This spectrum helped us identify 234 genuinely healthy muscles as unprecedented controls, providing a new perspective for deciphering the hallmark genes and pathways among different myopathies. The newly identified featured genes of general myopathy, inclusion body myositis, and titinopathy were highly expressed in our local muscles, as validated by quantitative polymerase chain reaction.

Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity.

Background: Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss success. Methods: Within the 8-month multicenter dietary intervention study DiOGenes, we classified a low weight-losers (low-WL) group and a high-WL group based on median weight loss percentage (9.9%) from 281 individuals. Using RNA sequencing, we identified the significantly differentially expressed genes between high-WL and low-WL at baseline and their enriched pathways. We used this information together with support vector machines with linear kernel to build classifier models that predict the weight loss classes. Results: Prediction models based on a selection of genes that are associated with the discovered pathways 'lipid metabolism' (max AUC = 0.74, 95% CI [0.62-0.86]) and 'response to virus' (max AUC = 0.72, 95% CI [0.61-0.83]) predicted the weight-loss classes high-WL/low-WL significantly better than models based on randomly selected genes (P < 0.01). The performance of the models based on 'response to virus' genes is highly dependent on those genes that are also associated with lipid metabolism. Incorporation of baseline clinical factors into these models did not noticeably enhance the model performance in most of the runs. This study demonstrates that baseline adipose tissue gene expression data, together with supervised machine learning, facilitates the characterization of the determinants of successful weight loss.

Molecular pathways behind acquired obesity: Adipose tissue and skeletal muscle multiomics in monozygotic twin pairs discordant for BMI.

Tissue-specific mechanisms prompting obesity-related development complications in humans remain unclear. We apply multiomics analyses of subcutaneous adipose tissue and skeletal muscle to examine the effects of acquired obesity among 49 BMI-discordant monozygotic twin pairs. Overall, adipose tissue appears to be more affected by excess body weight than skeletal muscle. In heavier co-twins, we observe a transcriptional pattern of downregulated mitochondrial pathways in both tissues and upregulated inflammatory pathways in adipose tissue. In adipose tissue, heavier co-twins exhibit lower creatine levels; in skeletal muscle, glycolysis- and redox stress-related protein and metabolite levels remain higher. Furthermore, metabolomics analyses in both tissues reveal that several proinflammatory lipids are higher and six of the same lipid derivatives are lower in acquired obesity. Finally, in adipose tissue, but not in skeletal muscle, mitochondrial downregulation and upregulated inflammation are associated with a fatty liver, insulin resistance, and dyslipidemia, suggesting that adipose tissue dominates in acquired obesity.

Chromosomal instability by mutations in the novel minor spliceosome component CENATAC.

Aneuploidy is the leading cause of miscarriage and congenital birth defects, and a hallmark of cancer. Despite this strong association with human disease, the genetic causes of aneuploidy remain largely unknown. Through exome sequencing of patients with constitutional mosaic aneuploidy, we identified biallelic truncating mutations in CENATAC (CCDC84). We show that CENATAC is a novel component of the minor (U12-dependent) spliceosome that promotes splicing of a specific, rare minor intron subtype. This subtype is characterized by AT-AN splice sites and relatively high basal levels of intron retention. CENATAC depletion or expression of disease mutants resulted in excessive retention of AT-AN minor introns in ˜ 100 genes enriched for nucleocytoplasmic transport and cell cycle regulators, and caused chromosome segregation errors. Our findings reveal selectivity in minor intron splicing and suggest a link between minor spliceosome defects and constitutional aneuploidy in humans.

IntEREst: intron-exon retention estimator.

BACKGROUND: In-depth study of the intron retention levels of transcripts provide insights on the mechanisms regulating pre-mRNA splicing efficiency. Additionally, detailed analysis of retained introns can link these introns to post-transcriptional regulation or identify aberrant splicing events in human diseases. RESULTS: We present IntEREst, Intron-Exon Retention Estimator, an R package that supports rigorous analysis of non-annotated intron retention events (in addition to the ones annotated by RefSeq or similar databases), and support intra-sample in addition to inter-sample comparisons. It accepts binary sequence alignment/map (.bam) files as input and determines genome-wide estimates of intron retention or exon-exon junction levels. Moreover, it includes functions for comparing subsets of user-defined introns (e.g. U12-type vs U2-type) and its plotting functions allow visualization of the distribution of the retention levels of the introns. Statistical methods are adapted from the DESeq2, edgeR and DEXSeq R packages to extract the significantly more or less retained introns. Analyses can be performed either sequentially (on single core) or in parallel (on multiple cores). We used IntEREst to investigate the U12- and U2-type intron retention in human and plant RNAseq dataset with defects in the U12-dependent spliceosome due to mutations in the ZRSR2 component of this spliceosome. Additionally, we compared the retained introns discovered by IntEREst with that of other methods and studies. CONCLUSION: IntEREst is an R package for Intron retention and exon-exon junction levels analysis of RNA-seq data. Both the human and plant analyses show that the U12-type introns are retained at higher level compared to the U2-type introns already in the control samples, but the retention is exacerbated in patient or plant samples carrying a mutated ZRSR2 gene. Intron retention events caused by ZRSR2 mutation that we discovered using IntEREst (DESeq2 based function) show considerable overlap with the retained introns discovered by other methods (e.g. IRFinder and edgeR based function of IntEREst). Our results indicate that increase in both the number of biological replicates and the depth of sequencing library promote the discovery of retained introns, but the effect of library size gradually decreases with more than 35 million reads mapped to the introns.

Multiple Isoforms of ANRIL in Melanoma Cells: Structural Complexity Suggests Variations in Processing.

The long non-coding RNA ANRIL, antisense to the CDKN2B locus, is transcribed from a gene that encompasses multiple disease-associated polymorphisms. Despite the identification of multiple isoforms of ANRIL, expression of certain transcripts has been found to be tissue-specific and the characterisation of ANRIL transcripts remains incomplete. Several functions have been associated with ANRIL. In our judgement, studies on ANRIL functionality are premature pending a more complete appreciation of the profusion of isoforms. We found differential expression of ANRIL exons, which indicates that multiple isoforms exist in melanoma cells. In addition to linear isoforms, we identified circular forms of ANRIL (circANRIL). Further characterisation of circANRIL in two patient-derived metastatic melanoma cell lines (NZM7 and NZM37) revealed the existence of a rich assortment of circular isoforms. Moreover, in the two melanoma cell lines investigated, the complements of circANRIL isoforms were almost completely different. Novel exons were also discovered. We also found the family of linear ANRIL was enriched in the nucleus, whilst the circular isoforms were enriched in the cytoplasm and they differed markedly in stability. With respect to the variable processing of circANRIL species, bioinformatic analysis indicated that intronic Arthrobacter luteus (Alu) restriction endonuclease inverted repeats and exon skipping were not involved in selection of back-spliced exon junctions. Based on our findings, we hypothesise that "ANRIL" has wholly distinct dual sets of functions in melanoma. This reveals the dynamic nature of the locus and constitutes a basis for investigating the functions of ANRIL in melanoma.

Global analysis of the nuclear processing of transcripts with unspliced U12-type introns by the exosome.

U12-type introns are a rare class of introns in the genomes of diverse eukaryotes. In the human genome, they number over 700. A subset of these introns has been shown to be spliced at a slower rate compared to the major U2-type introns. This suggests a rate-limiting regulatory function for the minor spliceosome in the processing of transcripts containing U12-type introns. However, both the generality of slower splicing and the subsequent fate of partially processed pre-mRNAs remained unknown. Here, we present a global analysis of the nuclear retention of transcripts containing U12-type introns and provide evidence for the nuclear decay of such transcripts in human cells. Using SOLiD RNA sequencing technology, we find that, in normal cells, U12-type introns are on average 2-fold more retained than the surrounding U2-type introns. Furthermore, we find that knockdown of RRP41 and DIS3 subunits of the exosome stabilizes an overlapping set of U12-type introns. RRP41 knockdown leads to slower decay kinetics of U12-type introns and globally upregulates the retention of U12-type, but not U2-type, introns. Our results indicate that U12-type introns are spliced less efficiently and are targeted by the exosome. These characteristics support their role in the regulation of cellular mRNA levels.

Biclustering methods: biological relevance and application in gene expression analysis.

DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering) methods where genes (or respectively samples) are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes). An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical) methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1) we examine how well the considered (bi)clustering methods differentiate various sample types; (2) we evaluate how well the groups of genes discovered by the (bi)clustering methods are annotated with similar Gene Ontology categories; (3) we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4) we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

Defective minor spliceosome mRNA processing results in isolated familial growth hormone deficiency.

The molecular basis of a significant number of cases of isolated growth hormone deficiency remains unknown. We describe three sisters affected with severe isolated growth hormone deficiency and pituitary hypoplasia caused by biallelic mutations in the RNPC3 gene, which codes for a minor spliceosome protein required for U11/U12 small nuclear ribonucleoprotein (snRNP) formation and splicing of U12-type introns. We found anomalies in U11/U12 di-snRNP formation and in splicing of multiple U12-type introns in patient cells. Defective transcripts include preprohormone convertases SPCS2 and SPCS3 and actin-related ARPC5L genes, which are candidates for the somatotroph-restricted dysfunction. The reported novel mechanism for familial growth hormone deficiency demonstrates that general mRNA processing defects of the minor spliceosome can lead to very narrow tissue-specific consequences.