Bioinformatical Analysis of Alternative Splicing

Splicing is a natural process happening in every living cell. As a fundamental process, all genes undergo splicing before tuning into a functional molecule such as proteins. However, the splicing process is still under active research in order to completely understand how it is regulated. As of now, the splicing machinery is characterized in what we call the spliceosome, but a complete understanding of it is still under active research. The discovery of alternative splicing set a breakthrough in molecular biology. This process allows a simple gene to turn into more than one protein by creating different transcripts or isoforms. The transcriptome is the whole set of known isoforms that have been characterized through research and experimental procedures. Still, many isoforms might remain unknown. Through research, alternative splicing has been shown to be responsible for the development of different pathologies, including cancer. On the other hand, alternative splicing provides a novel mean to characterize potential biomarkers for drug resistance or survival. Due to this, alternative splicing is constantly being studied in order to completely understand its functioning mechanism. With the development of sequencing techniques, it has been possible to develop methods to quantify the different isoforms present in specific samples or conditions. From the method, developed by Frederick Sanger, also known as Sanger sequencing, to the development of new protocols, like third generation sequencers, vast amounts of data have been generated. Even though, sequencing has taken a lead role in the study of alternative splicing, other platforms like junction arrays have been developed to study such phenomenon. Affymetrix recently developed the Clariom microarray, which seems to be the most up to date array to identify splicing events. Most of the available algorithms to identify and quantify alternative splicing events, provide more than one figure of merit per event and does not take into account a coherence in such events. For example, in a cassette exon, not only the skipped exon should show a change in expression, but the flanking junctions should display a similar behavior but in opposite directions. In order to take this into account, a novel method to identify, classify and state statistical significance of splicing events has been developed. EventPointer allows users to identify alternative splicing events and provide the statistical significance of such events. The algorithm can be applied to data from both microarrays or RNA-Seq. Also, EventPointer generates files that can be loaded into genome browsers to ease the interpretation of the results and the desing of primers for standard PCR validations. The performance of EventPointer has been tested in two independent experiments using both platforms. The overall results show a promising validation rate in both technologies. EventPointer, also estimates the percent spliced index for every detected event and not only skipping exons, as most of the available software. The results, obtained through end-point PCR demonstrate that the estimated $\Psi$ values, provided by EventPonter, are highly correlated with the experimental results. EventPointer shows an improved method to identify and quantify alternative splicing events. A comparison between microarrays and RNA-Seq, in their ability to identify alternative splicing events was performed using the same experimental data from three different cell lines treated with a drug that severely affects the splicing machinery. The results show that RNA-Seq is the most flexible and trustable platform for the identification of splicing events, but microarrays are a viable option to analyze alternative splicing due to reasons of cost and convenience. Microarrays can be an alternative when compared to shallow sequencing

Presence of immunogenic alternatively spliced insulin gene product in human pancreatic delta cells

Aims/hypothesis: Transcriptome analyses revealed insulin-gene-derived transcripts in non-beta endocrine islet cells. We studied alternative splicing of human INS mRNA in pancreatic islets. Methods: Alternative splicing of insulin pre-mRNA was determined by PCR analysis performed on human islet RNA and single-cell RNA-seq analysis. Antisera were generated to detect insulin variants in human pancreatic tissue using immunohistochemistry, electron microscopy and single-cell western blot to confirm the expression of insulin variants. Cytotoxic T lymphocyte (CTL) activation was determined by MIP-1β release. Results: We identified an alternatively spliced INS product. This variant encodes the complete insulin signal peptide and B chain and an alternative C-terminus that largely overlaps with a previously identified defective ribosomal product of INS. Immunohistochemical analysis revealed that the translation product of this INS-derived splice transcript was detectable in somatostatin-producing delta cells but not in beta cells; this was confirmed by light and electron microscopy. Expression of this alternatively spliced INS product activated preproinsulin-specific CTLs in vitro. The exclusive presence of this alternatively spliced INS product in delta cells may be explained by its clearance from beta cells by insulin-degrading enzyme capturing its insulin B chain fragment and a lack of insulin-degrading enzyme expression in delta cells. Conclusions/interpretation: Our data demonstrate that delta cells can express an INS product derived from alternative splicing, containing both the diabetogenic insulin signal peptide and B chain, in their secretory granules. We propose that this alternative INS product may play a role in islet autoimmunity and pathology, as well as endocrine or paracrine function or islet development and endocrine destiny, and transdifferentiation between endocrine cells. INS promoter activity is not confined to beta cells and should be used with care when assigning beta cell identity and selectivity. Data availability: The full EM dataset is available via www.nanotomy.org (for review: http://www.nanotomy.org/OA/Tienhoven2021SUB/6126-368/). Single-cell RNA-seq data was made available by Segerstolpe et al [13] and can be found at https://sandberglab.se/pancreas. The RNA and protein sequence of INS-splice was uploaded to GenBank (BankIt2546444 INS-splice OM489474). Graphical abstract: [Figure not available: see fulltext.

Loss of the matrix metalloproteinase-10 causes premature features of aging in satellite cells

Aged muscles accumulate satellite cells with a striking decline response to damage. Although intrinsic defects in satellite cells themselves are the major contributors to aging-associated stem cell dysfunction, increasing evidence suggests that changes in the muscle-stem cell local microenvironment also contribute to aging. Here, we demonstrate that loss of the matrix metalloproteinase-10 (MMP-10) in young mice alters the composition of the muscle extracellular matrix (ECM), and specifically disrupts the extracellular matrix of the satellite cell niche. This situation causes premature features of aging in the satellite cells, contributing to their functional decline and a predisposition to enter senescence under proliferative pressure. Similarly, reduction of MMP-10 levels in young satellite cells from wild type animals induces a senescence response, while addition of the protease delays this program. Significantly, the effect of MMP-10 on satellite cell aging can be extended to another context of muscle wasting, muscular dystrophy. Systemic treatment of mdx dystrophic mice with MMP-10 prevents the muscle deterioration phenotype and reduces cellular damage in the satellite cells, which are normally under replicative pressure. Most importantly, MMP-10 conserves its protective effect in the satellite cell-derived myoblasts isolated from a Duchenne muscular dystrophy patient by decreasing the accumulation of damaged DNA. Hence, MMP-10 provides a previously unrecognized therapeutic opportunity to delay satellite cell aging and overcome satellite cell dysfunction in dystrophic muscles

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize an enriched population of human HSPCs obtained from young and elderly healthy individuals. Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain aging-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks (GRNs) and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRNs regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2, and RUNX1 suggesting a role of these transcription factors (TFs) in the pathogenesis of the disease. In summary, we demonstrate that the combination of single-cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in complex biological systems such as early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with perturbations such as aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patient