Rbfox1 is required for myofibril development and maintaining fiber type–specific isoform expression in Drosophila muscles

Protein isoform transitions confer muscle fibers with distinct properties and are regulated by differential transcription and alternative splicing. RNA-binding Fox protein 1 (Rbfox1) can affect both transcript levels and splicing, and is known to contribute to normal muscle development and physiology in vertebrates, although the detailed mechanisms remain obscure. In this study, we report that Rbfox1 contributes to the generation of adult muscle diversity in Drosophila. Rbfox1 is differentially expressed among muscle fiber types, and RNAi knockdown causes a hypercontraction phenotype that leads to behavioral and eclosion defects. Misregulation of fiber type–specific gene and splice isoform expression, notably loss of an indirect flight muscle–specific isoform of Troponin-I that is critical for regulating myosin activity, leads to structural defects. We further show that Rbfox1 directly binds the 3′-UTR of target transcripts, regulates the expression level of myogenic transcription factors myocyte enhancer factor 2 and Salm, and both modulates expression of and genetically interacts with the CELF family RNA-binding protein Bruno1 (Bru1). Rbfox1 and Bru1 co-regulate fiber type–specific alternative splicing of structural genes, indicating that regulatory interactions between FOX and CELF family RNA-binding proteins are conserved in fly muscle. Rbfox1 thus affects muscle development by regulating fiber type–specific splicing and expression dynamics of identity genes and structural proteins.

Long-read isoform sequencing reveals tissue-specific isoform expression between active and hibernating brown bears (Ursus arctos)

Understanding hibernation in brown bears (Ursus arctos) can provide insight into some human diseases. During hibernation, brown bears experience periods of insulin resistance, physical inactivity, extreme bradycardia, obesity, and the absence of urine production. These states closely mimic aspects of human diseases such as type 2 diabetes, muscle atrophy, as well as renal and heart failure. The reversibility of these states from hibernation to active season enables the identification of mediators with possible therapeutic value for humans. Recent studies have identified genes and pathways that are differentially expressed between active and hibernation seasons. However, little is known about the role of differential expression of gene isoforms on hibernation physiology. To identify both distinct and novel mRNA isoforms, full-length RNA-sequencing (Iso-Seq) was performed on adipose, skeletal muscle, and liver from three individuals sampled during both active and hibernation seasons. The existing reference annotation was improved by combining it with the Iso-Seq data. Short-read RNA-sequencing data from six individuals was mapped to the new reference annotation to quantify differential isoform usage between tissues and seasons. We identified differentially expressed isoforms in all three tissues, to varying degrees. Adipose had a high level of differential isoform usage with isoform switching, regardless of whether the genes were differentially expressed. Our analyses revealed that differential isoform usage, even in the absence of differential gene expression, is an important mechanism for modulating genes during hibernation. These findings demonstrate the value of isoform expression studies and will serve as the basis for deeper exploration into hibernation biology.

Maternal methionine supplementation during gestation alters alternative splicing and DNA methylation in bovine skeletal muscle

Background The evaluation of alternative splicing, including differential isoform expression and differential exon usage, can provide some insights on the transcriptional changes that occur in response to environmental perturbations. Maternal nutrition is considered a major intrauterine regulator of fetal developmental programming. The objective of this study was to assess potential changes in splicing events in the longissimus dorsi muscle of beef calves gestated under control or methionine-rich diets. RNA sequencing and whole-genome bisulfite sequencing were used to evaluate muscle transcriptome and methylome, respectively. Results Alternative splicing patterns were significantly altered by maternal methionine supplementation. Most of the altered genes were directly implicated in muscle development, muscle physiology, ATP activities, RNA splicing and DNA methylation, among other functions. Interestingly, there was a significant association between DNA methylation and differential exon usage. Indeed, among the set of genes that showed differential exon usage, significant differences in methylation level were detected between significant and non-significant exons, and between contiguous and non-contiguous introns to significant exons. Conclusions Overall, our findings provide evidence that a prenatal diet rich in methyl donors can significantly alter the offspring transcriptome, including changes in isoform expression and exon usage, and some of these changes are mediated by changes in DNA methylation.

Higher RET Gene Expression Levels Do Not Represent anAlternative RET Activation Mechanism in Medullary Thyroid Carcinoma

This study was designed to investigate whether RET (rearranged during transfection) mRNA over-expression could be considered an alternative driver event for the development of medullary thyroid carcinoma (MTC), and if different RET isoforms could play a role in MTC tumorigenesis. Eighty-three MTC patients, whose mutational profile was previously identified by next-generation sequencing (NGS) IONS5, were included in this study. Expression analysis was performed by the quantitative reverse transcription-polymerase chain reaction technique. RET expression levels were found to be significantly higher in cases with RET somatic mutations than in cases that were negative for RET somatic mutations (p = 0.003) as well as in cases with a somatic mutation, either in RET or RAS than in cases negative for both these mutations (p = 0.01). All cases were positive for the RET51 isoform expression while only 72/83 (86.7%) were positive for RET9 isoform expression. A statistically significant higher expression of the RET51 isoform was found in cases positive for RET somatic mutation than in cases either positive for RAS mutation (p = 0.0006) or negative for both mutations (p = 0.001). According to our data, RET gene over-expression does not play a role in MTC tumorigenesis, neither as an entire gene or as an isoform. At variance, the RET gene, and in particular the RET51 isoform, is expressed higher in RET mutated cases. On the basis of these results we can hypothesize that the overexpression of RET, and in particular of RET51, could potentiate the transforming activity of mutated RET, making these cases more aggressive.

Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq

The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. However, its application to single-cell RNA-seq has been limited by throughput and expense. Here we develop and characterize long-read Split-seq (LR-Split-seq), which uses combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells.

Combining Multiple RNA-Seq Data Analysis Algorithms Using Machine Learning Improves Differential Isoform Expression Analysis

RNA sequencing has become the standard technique for high resolution genome-wide monitoring of gene expression. As such, it often comprises the first step towards understanding complex molecular mechanisms driving various phenotypes, spanning organ development to disease genesis, monitoring and progression. An advantage of RNA sequencing is its ability to capture complex transcriptomic events such as alternative splicing which results in alternate isoform abundance. At the same time, this advantage remains algorithmically and computationally challenging, especially with the emergence of even higher resolution technologies such as single-cell RNA sequencing. Although several algorithms have been proposed for the effective detection of differential isoform expression from RNA-Seq data, no widely accepted golden standards have been established. This fact is further compounded by the significant differences in the output of different algorithms when applied on the same data. In addition, many of the proposed algorithms remain scarce and poorly maintained. Driven by these challenges, we developed a novel integrative approach that effectively combines the most widely used algorithms for differential transcript and isoform analysis using state-of-the-art machine learning techniques. We demonstrate its usability by applying it on simulated data based on several organisms, and using several performance metrics; we conclude that our strategy outperforms the application of the individual algorithms. Finally, our approach is implemented as an R Shiny application, with the underlying data analysis pipelines also available as docker containers.

Micro-dissection and integration of long and short reads to create a robust catalog of kidney compartment-specific isoforms

Studying isoform expression at the microscopic level has always been a challenging task. A classical example is kidney, where glomerular and tubulo-insterstitial compartments carry out drastically different physiological functions and thus presumably their isoform expression also differs. We aim at developing an experimental and computational pipeline for identifying isoforms at microscopic structure-level. We microdissed glomerular and tubulo-interstitial compartments from healthy human kidney tissues from two cohorts. The two compartments were separately sequenced with the PacBio RS II platform. These transcripts were then validated using transcripts of the same samples by the traditional Illumina RNA-Seq protocol, distinct Illumina RNA-Seq short reads from European Renal cDNA Bank (ERCB) samples, and annotated GENCODE transcript list, thus identifying novel transcripts. We identified 14,739 and 14,259 annotated transcripts, and 17,268 and 13,118 potentially novel transcripts in the glomerular and tubulo-interstitial compartments, respectively. Of note, relying solely on either short or long reads would have resulted in many erroneous identifications. We identified distinct pathways involved in glomerular and tubulointerstitial compartments at the isoform level.We demonstrated the possibility of micro-dissecting a tissue, incorporating both long- and short-read sequencing to identify isoforms for each compartment.