The SpliZ generalizes 'percent spliced in' to reveal regulated splicing at single-cell resolution

Regulation of endocrine cell alternative splicing revealed by single-cell RNA sequencing in type 2 diabetes pathogenesis

The prevalent RNA alternative splicing (AS) contributes to molecular diversity, which has been demonstrated in cellular function regulation and disease pathogenesis. However, the contribution of AS in pancreatic islets during diabetes progression remains unclear. Here, we reanalyze the full-length single-cell RNA sequencing data from the deposited database to investigate AS regulation across human pancreatic endocrine cell types in non-diabetic (ND) and type 2 diabetic (T2D) individuals. Our analysis demonstrates the significant association between transcriptomic AS profiles and cell-type-specificity, which could be applied to distinguish the clustering of major endocrine cell types. Moreover, AS profiles are enabled to clearly define the mature subset of β-cells in healthy controls, which is completely lost in T2D. Further analysis reveals that RNA-binding proteins (RBPs), heterogeneous nuclear ribonucleoproteins (hnRNPs) and FXR1 family proteins are predicted to induce the functional impairment of β-cells through regulating AS profiles. Finally, trajectory analysis of endocrine cells suggests the β-cell identity shift through dedifferentiation and transdifferentiation of β-cells during the progression of T2D. Together, our study provides a mechanism for regulating β-cell functions and suggests the significant contribution of AS program during diabetes pathogenesis.

Quantifying transcriptome diversity: a review

Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.

Interrogations of single-cell RNA splicing landscapes with SCASL define new cell identities with physiological relevance

RNA splicing shapes the gene regulatory programs that underlie various physiological and disease processes. Here, we present the SCASL (single-cell clustering based on alternative splicing landscapes) method for interrogating the heterogeneity of RNA splicing with single-cell RNA-seq data. SCASL resolves the issue of biased and sparse data coverage on single-cell RNA splicing and provides a new scheme for classifications of cell identities. With previously published datasets as examples, SCASL identifies new cell clusters indicating potentially precancerous and early-tumor stages in triple-negative breast cancer, illustrates cell lineages of embryonic liver development, and provides fine clusters of highly heterogeneous tumor-associated CD4 and CD8 T cells with functional and physiological relevance. Most of these findings are not readily available via conventional cell clustering based on single-cell gene expression data. Our study shows the potential of SCASL in revealing the intrinsic RNA splicing heterogeneity and generating biological insights into the dynamic and functional cell landscapes in complex tissues.

Opportunities and tradeoffs in single-cell transcriptomic technologies

Recent technological and algorithmic advances enable single-cell transcriptomic analysis with remarkable depth and breadth. Nonetheless, a persistent challenge is the compromise between the ability to profile high numbers of cells and the achievement of full-length transcript coverage. Currently, the field is progressing and developing new and creative solutions that improve cellular throughput, gene detection sensitivity and full-length transcript capture. Furthermore, long-read sequencing approaches for single-cell transcripts are breaking frontiers that have previously blocked full transcriptome characterization. We here present a comprehensive overview of available options for single-cell transcriptome profiling, highlighting the key advantages and disadvantages of each approach.

Analyzing alternative splicing in Alzheimer's disease postmortem brain: a cell-level perspective

Alzheimer's disease (AD) is a neurodegenerative disease with no effective cure that attacks the brain's cells resulting in memory loss and changes in behavior and language skills. Alternative splicing is a highly regulated process influenced by specific cell types and has been implicated in age-related disorders such as neurodegenerative diseases. A comprehensive detection of alternative splicing events (ASEs) at the cellular level in postmortem brain tissue can provide valuable insights into AD pathology. Here, we provided cell-level ASEs in postmortem brain tissue by employing bioinformatics pipelines on a bulk RNA sequencing study sorted by cell types and two single-cell RNA sequencing studies from the prefrontal cortex. This comprehensive analysis revealed previously overlooked splicing and expression changes in AD patient brains. Among the observed alterations were changed in the splicing and expression of transcripts associated with chaperones, including CLU in astrocytes and excitatory neurons, PTGDS in astrocytes and endothelial cells, and HSP90AA1 in microglia and tauopathy-afflicted neurons, which were associated with differential expression of the splicing factor DDX5. In addition, novel, unknown transcripts were altered, and structural changes were observed in lncRNAs such as MEG3 in neurons. This work provides a novel strategy to identify the notable ASEs at the cell level in neurodegeneration, which revealed cell type-specific splicing changes in AD. This finding may contribute to interpreting associations between splicing and neurodegenerative disease outcomes.

From words to complete phrases: insight into single-cell isoforms using short and long reads

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.

Analysis of RNA processing directly from spatial transcriptomics data reveals previously unknown regulation

Technical advances have led to an explosion in the amount of biological data available in recent years, especially in the field of RNA sequencing. Specifically, spatial transcriptomics (ST) datasets, which allow each RNA molecule to be mapped to the 2D location it originated from within a tissue, have become readily available. Due to computational challenges, ST data has rarely been used to study RNA processing such as splicing or differential UTR usage. We apply the ReadZS and the SpliZ, methods developed to analyze RNA process in scRNA-seq data, to analyze spatial localization of RNA processing directly from ST data for the first time. Using Moran's I metric for spatial autocorrelation, we identify genes with spatially regulated RNA processing in the mouse brain and kidney, re-discovering known spatial regulation in Myl6 and identifying previously-unknown spatial regulation in genes such as Rps24, Gng13, Slc8a1, Gpm6a, Gpx3, ActB, Rps8, and S100A9. The rich set of discoveries made here from commonly used reference datasets provides a small taste of what can be learned by applying this technique more broadly to the large quantity of Visium data currently being created.

Alternative splicing in shaping the molecular landscape of the cochlea

The cochlea is a complex organ comprising diverse cell types with highly specialized morphology and function. Until now, the molecular underpinnings of its specializations have mostly been studied from a transcriptional perspective, but accumulating evidence points to post-transcriptional regulation as a major source of molecular diversity. Alternative splicing is one of the most prevalent and well-characterized post-transcriptional regulatory mechanisms. Many molecules important for hearing, such as cadherin 23 or harmonin, undergo alternative splicing to produce functionally distinct isoforms. Some isoforms are expressed specifically in the cochlea, while some show differential expression across the various cochlear cell types and anatomical regions. Clinical phenotypes that arise from mutations affecting specific splice variants testify to the functional relevance of these isoforms. All these clues point to an essential role for alternative splicing in shaping the unique molecular landscape of the cochlea. Although the regulatory mechanisms controlling alternative splicing in the cochlea are poorly characterized, there are animal models with defective splicing regulators that demonstrate the importance of RNA-binding proteins in maintaining cochlear function and cell survival. Recent technological breakthroughs offer exciting prospects for overcoming some of the long-standing hurdles that have complicated the analysis of alternative splicing in the cochlea. Efforts toward this end will help clarify how the remarkable diversity of the cochlear transcriptome is both established and maintained.

ReadZS detects cell type-specific and developmentally regulated RNA processing programs in single-cell RNA-seq

RNA processing, including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNA processing from single-cell RNA sequencing data are limited by reliance on pre-existing annotations, peak calling heuristics, and collapsing measurements by cell type. We introduce ReadZS, an annotation-free statistical approach to identify regulated RNA processing in single cells. ReadZS discovers cell type-specific RNA processing in human lung and conserved, developmentally regulated RNA processing in mammalian spermatogenesis-including global 3' UTR shortening in human spermatogenesis. ReadZS also discovers global 3' UTR lengthening in Arabidopsis development, highlighting the usefulness of this method in under-annotated transcriptomes.

CHD8 haploinsufficiency links autism to transient alterations in excitatory and inhibitory trajectories

Mutations in the chromodomain helicase DNA-binding 8 (CHD8) gene are a frequent cause of autism spectrum disorder (ASD). While its phenotypic spectrum often encompasses macrocephaly, implicating cortical abnormalities, how CHD8 haploinsufficiency affects neurodevelopmental is unclear. Here, employing human cerebral organoids, we find that CHD8 haploinsufficiency disrupted neurodevelopmental trajectories with an accelerated and delayed generation of, respectively, inhibitory and excitatory neurons that yields, at days 60 and 120, symmetrically opposite expansions in their proportions. This imbalance is consistent with an enlargement of cerebral organoids as an in vitro correlate of patients' macrocephaly. Through an isogenic design of patient-specific mutations and mosaic organoids, we define genotype-phenotype relationships and uncover their cell-autonomous nature. Our results define cell-type-specific CHD8-dependent molecular defects related to an abnormal program of proliferation and alternative splicing. By identifying cell-type-specific effects of CHD8 mutations, our study uncovers reproducible developmental alterations that may be employed for neurodevelopmental disease modeling.