isoformant: A visual toolkit for reference-free long-read isoform analysis at single-read resolution

isoformant is an analytical toolkit for isoform characterization of Oxford Nanopore Technologies (ONT) long-transcript sequencing data (i.e. direct RNA and cDNA). Deployment of these tools using Jupyter Notebook enables interactive analysis of user- defined region-of-interest (ROI), typically a gene. The core module of isoformant clus- ters sequencing reads by k-mer density to generate isoform consensus sequences without the requirement for a reference genome or prior annotations. The inclusion of differential isoform usage hypothesis testing based on read distribution among clusters enables com- parison across multiple samples. Here, as proof-of-principle, we demonstrate the utility of isoformant for analyzing isoform diversity of commercially-available isoform standard mixtures. isoformant is available here: https://github.com/danledinh/isoformant.

Altered cell and RNA isoform diversity in aging Down syndrome brains

Down syndrome (DS), trisomy of human chromosome 21 (HSA21), is characterized by lifelong cognitive impairments and the development of the neuropathological hallmarks of Alzheimer’s disease (AD). The cellular and molecular modifications responsible for these effects are not understood. Here we performed single-nucleus RNA sequencing (snRNA-seq) employing both short- (Illumina) and long-read (Pacific Biosciences) sequencing technologies on a total of 29 DS and non-DS control prefrontal cortex samples. In DS, the ratio of inhibitory-to-excitatory neurons was significantly increased, which was not observed in previous reports examining sporadic AD. DS microglial transcriptomes displayed AD-related aging and activation signatures in advance of AD neuropathology, with increased microglial expression of C1q complement genes (associated with dendritic pruning) and the HSA21 transcription factor gene RUNX1. Long-read sequencing detected vast RNA isoform diversity within and among specific cell types, including numerous sequences that differed between DS and control brains. Notably, over 8,000 genes produced RNAs containing intra-exonic junctions, including amyloid precursor protein (APP) that had previously been associated with somatic gene recombination. These and related results illuminate large-scale cellular and transcriptomic alterations as features of the aging DS brain.

SplicingFactory—splicing diversity analysis for transcriptome data

Motivation Alternative splicing contributes to the diversity of RNA found in biological samples. Current tools investigating patterns of alternative splicing check for coordinated changes in the expression or relative ratio of RNA isoforms where specific isoforms are up- or downregulated in a condition. However, the molecular process of splicing is stochastic and changes in RNA isoform diversity for a gene might arise between samples or conditions. A specific condition can be dominated by a single isoform, while multiple isoforms with similar expression levels can be present in a different condition. These changes might be the result of mutations, drug treatments or differences in the cellular or tissue environment. Here, we present a tool for the characterization and analysis of RNA isoform diversity using isoform level expression measurements. Results We developed an R package called SplicingFactory, to calculate various RNA isoform diversity metrics, and compare them across conditions. Using the package, we tested the effect of RNA-seq quantification tools, quantification uncertainty, gene expression levels, and isoform numbers on the isoform diversity calculation. We analyzed a set of CD34+ hematopoietic stem cells and myelodysplastic syndrome samples and found a set of genes whose isoform diversity change is associated with SF3B1 mutations. Availability and implementation The SplicingFactory package is freely available under the GPL-3.0 license from Bioconductor for the Windows, MacOS and Linux operating systems (https://www.bioconductor.org/packages/release/bioc/html/SplicingFactory.html). Supplementary information Supplementary data are available at Bioinformatics online.

Robust and annotation-free analysis of isoform variation using short-read scRNA-seq data

Although isoform diversity is acknowledged as a fundamental and pervasive aspect of gene expression in higher eukaryotes, it is often omitted from single-cell studies due to quantification challenges inherent to commonly used short-read sequencing technologies. To address this issue, we have developed a suite of computational tools to investigate isoform variation by focusing on splice junction usage patterns, which can often be well characterized in spite of technical difficulties. Our method, which we name scQuint (single-cell quantification of introns), can perform accurate quantification, dimensionality reduction, and differential splicing analysis using short-read, full-length single-cell RNA-seq data. Notably, scQuint does not require transcriptome annotations and is robust to technical artifacts. In applications across diverse mouse tissues from Tabula Muris and the primary motor cortex from the BRAIN Initiative Cell Census Network, we find evidence of strong cell-type-specific isoform variation, complementary to total gene expression, and also identify a large volume of previously unannotated splice junctions. As a community resource, we provide ways to interactively visualize and explore these results, accessible at https://github.com/songlab-cal/scquint-analysis/.

NanoSINC-seq dissects the isoform diversity in subcellular compartments of single cells

Alternative mRNA isoforms play a key role in generating diverse protein isoforms. To dissect isoform usage in the subcellular compartments of single cells, we introduced an novel approach, nanopore sequencing coupled with single-cell integrated nuclear and cytoplasmic RNA sequencing, that couples microfluidic fractionation, which separates cytoplasmic RNA from nuclear RNA, with full-length complementary DNA (cDNA) sequencing using a nanopore sequencer. Leveraging full-length cDNA reads, we found that the nuclear transcripts are notably more diverse than cytoplasmic transcripts. Our findings also indicated that transcriptional noise emanating from the nucleus is regulated across the nuclear membrane and then either attenuated or amplified in the cytoplasm depending on the function involved. Overall, our results provide the landscape that shows how the transcriptional noise arising from the nucleus propagates to the cytoplasm.

Deconvolution of Expression for Nascent RNA Sequencing Data (DENR) Highlights Pre-RNA Isoform Diversity in Human Cells

Quantification of mature-RNA isoform abundance from RNA-seq data has been extensively studied, but much less attention has been devoted to quantifying the abundance of distinct precursor RNAs based on nascent RNA sequencing data. Here we address this problem with a new computational method called Deconvolution of Expression for Nascent RNA sequencing data (DENR). DENR models the nascent RNA read counts at each locus as a mixture of user-provided isoforms. The performance of the baseline algorithm is enhanced by the use of machine-learning predictions of transcription start sites (TSSs) and an adjustment for the typical “shape profile” of read counts along a transcription unit. We show using simulated data that DENR clearly outperforms simple read-count-based methods for estimating the abundances of both whole genes and isoforms. By applying DENR to previously published PRO-seq data from K562 and CD4+ T cells, we find that transcription of multiple isoforms per gene is widespread, and the dominant isoform frequently makes use of an internal TSS. We also identify > 200 genes whose dominant isoforms make use of different TSSs in these two cell types. Finally, we apply DENR and StringTie to newly generated PRO-seq and RNA-seq data, respectively, for human CD4+ T cells and CD14+ monocytes, and show that entropy at the pre-RNA level makes a disproportionate contribution to overall isoform diversity, especially across cell types. Altogether, DENR is the first computational tool to enable abundance quantification of pre-RNA isoforms based on nascent RNA sequencing data, and it reveals high levels of pre-RNA isoform diversity in human cells.

Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility

The rhesus macaque (Macaca mulatta) is the most widely studied nonhuman primate (NHP) in biomedical research. We present an updated reference genome assembly (Mmul_10, contig N50 = 46 Mbp) that increases the sequence contiguity 120-fold and annotate it using 6.5 million full-length transcripts, thus improving our understanding of gene content, isoform diversity, and repeat organization. With the improved assembly of segmental duplications, we discovered new lineage-specific genes and expanded gene families that are potentially informative in studies of evolution and disease susceptibility. Whole-genome sequencing (WGS) data from 853 rhesus macaques identified 85.7 million single-nucleotide variants (SNVs) and 10.5 million indel variants, including potentially damaging variants in genes associated with human autism and developmental delay, providing a framework for developing noninvasive NHP models of human disease.

Perspective in Alternative Splicing Coupled to Nonsense-Mediated mRNA Decay

Alternative splicing (AS) of precursor mRNA (pre-mRNA) is a cellular post-transcriptional process that generates protein isoform diversity. Nonsense-mediated RNA decay (NMD) is an mRNA surveillance pathway that recognizes and selectively degrades transcripts containing premature translation-termination codons (PTCs), thereby preventing the production of truncated proteins. Nevertheless, NMD also fine-tunes the gene expression of physiological mRNAs encoding full-length proteins. Interestingly, around one third of all AS events results in PTC-containing transcripts that undergo NMD. Numerous studies have reported a coordinated action between AS and NMD, in order to regulate the expression of several genes, especially those coding for RNA-binding proteins (RBPs). This coupling of AS to NMD (AS-NMD) is considered a gene expression tool that controls the ratio of productive to unproductive mRNA isoforms, ultimately degrading PTC-containing non-functional mRNAs. In this review, we focus on the mechanisms underlying AS-NMD, and how this regulatory process is able to control the homeostatic expression of numerous RBPs, including splicing factors, through auto- and cross-regulatory feedback loops. Furthermore, we discuss the importance of AS-NMD in the regulation of biological processes, such as cell differentiation. Finally, we analyze interesting recent data on the relevance of AS-NMD to human health, covering its potential roles in cancer and other disorders.