Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes1–11, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far12,13. Although single splicing events have been described for ≤200 single cells with statistical confidence14,15, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes16–21, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites6–9,22,23. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms

Targeted, High-Resolution RNA Sequencing of Non-coding Genomic Regions Associated With Neuropsychiatric Functions

The human brain is one of the last frontiers of biomedical research. Genome-wide association studies (GWAS) have succeeded in identifying thousands of haplotype blocks associated with a range of neuropsychiatric traits, including disorders such as schizophrenia, Alzheimer’s and Parkinson’s disease. However, the majority of single nucleotide polymorphisms (SNPs) that mark these haplotype blocks fall within non-coding regions of the genome, hindering their functional validation. While some of these GWAS loci may contain cis-acting regulatory DNA elements such as enhancers, we hypothesized that many are also transcribed into non-coding RNAs that are missing from publicly available transcriptome annotations. Here, we use targeted RNA capture (‘RNA CaptureSeq’) in combination with nanopore long-read cDNA sequencing to transcriptionally profile 1,023 haplotype blocks across the genome containing non-coding GWAS SNPs associated with neuropsychiatric traits, using post-mortem human brain tissue from three neurologically healthy donors. We find that the majority (62%) of targeted haplotype blocks, including 13% of intergenic blocks, are transcribed into novel, multi-exonic RNAs, most of which are not yet recorded in GENCODE annotations. We validated our findings with short-read RNA-seq, providing orthogonal confirmation of novel splice junctions and enabling a quantitative assessment of the long-read assemblies. Many novel transcripts are supported by independent evidence of transcription including cap analysis of gene expression (CAGE) data and epigenetic marks, and some show signs of potential functional roles. We present these transcriptomes as a preliminary atlas of non-coding transcription in human brain that can be used to connect neurological phenotypes with gene expression

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis

Modelling splicing

L’Splicing de les molècules d’ARN és el procés pel qual les seqüències interposades (“introns”) s’eliminen, i les seqüències restants es concatenen per a formar l’ARN madur. La investigació recent mostra que gairebé tots els gens amb splicing es veuen afectats per splicing alternatiu. Aquí, en primer lloc definim la longitud mínima d’un oligomer d’ARN per a funcionar com a lloc d’unió d’un factor d’splicing. A continuació, explorem la capacitat d’aquests oligomers per a predir estructures completes exó-intró. Destaquem els oligomers que són més informatius per a això, i demostrem que la mateixa precisió com en enfocaments anteriors es pot aconseguir amb menys oligomers. L’observació de que aquest enfocament és lluny de predir amb exactitud tota l’estructura exó-intró ens va portar a investigar els factors que juguen un paper en l’splicing co-transcripcional. Demostrem que els nucleosomes es col.loquen preferentment en els exons i plantegem la hipòtesi que juguen un paper en les decisions de l’splicing. A continuació, introduïm el “completed splicing index” i concluem que l’splicing co-transcripcional és molt generalitzat. A més, l’splicing co-transcripcional mostra vincles amb l’organització de la cromatina. A la llum d’aquests resultats, es van supervisar els canvis de la cromatina en exons diferencialment inclosos en dos teixits. Hem descobert una varietat de marques de les histones, però no totes, mostrant un comportament significativament diferent en els exons més inclosos i més exclosos. Las marques més destacades que apareixen són H3K9ac i dos estats de metilació de lisina 4.Splicing of RNA molecules is the process, by which intervening sequences (“introns”) in the primary transcript are excised, and the remaining sequences (“exons”) are concatenated to form the mature RNA. Recent evidence shows that almost all spliced genes are affected by alternative splicing. Here, we define the minimal length of RNA oligomers that can sensibly be called splicing factor binding sites. Then, we explore the capacity of these oligomers to predict complete exon-intron structures. We highlight those oligomers that are most informative for this and show, that equal accuracy as in previous approaches can be achieved with less RNA oligomers. The observation, that this approach falls short of accurately predicting the entire exon-intron structure, led us to investigate determinants linked to co-transcriptional splicing. We show that nucleosomes are preferentially positioned on exons and hypothesize that they play a role in splicing decisions. We then introduce the “completed splicing index” and conclude that co-transcriptional splicing is very wide-spread in humans. Furthermore co-transcriptional splicing exhibits links to chromatin organization. In the light of these results, we go on to monitor chromatin changes on differentially included exons in pair-wise tissue comparisons. We find a variety of histone marks, but not all, showing significantly different behavior on up- and downregulated exons. The most prominently appearing marks are H3K9ac and two lysine 4 methylation states

From chromatin to splicing: RNA-processing as a total artwork

RNA plays a central role in the determination of the phenotype of the cell. The molecular mechanisms involved in primary RNA synthesis and subsequent post-processing are not completely understood, but there is increasing evidence that they are more tightly coupled than previously expected. The analyses by a number of groups of recently published genome wide maps of chromatin structure have further uncovered a role for primary chromatin structure in RNA processing. Indeed, these analyses have revealed that nucleosomes show a characteristic occupancy pattern in exonic regions of metazoan genomes. The pattern is strongly indicative of an implication of nucleosome positioning in exon recognition during pre-mRNA splicing. Characteristic exonic patterns have also been observed for a number of histone modifications, suggesting the possibility that chromatin state plays a direct role in the regulation of splicin

Erratum to: Promoter-like epigenetic signatures in exons displaying cell type-specific splicing

Es tracta d'un erratum de l'article publicat a Promoter-like epigenetic signatures in exons displaying cell type-specific splicing-Genome Biology, 2015, 16, 236. DOI: 10.1186/s13059-015-0797-8After the publication of this work [1] an error was noticed in Fig. 7. The panel‘h’ is missing from Fig. 7. Please see the corrected figure below. The publisher apologises for this error

CLOUDRNASPADES : Isoform assembly using bulk barcoded RNA sequencing data

Motivation: Recent advancements in long-read RNA sequencing have enabled the examination of full-length isoforms, previously uncaptured by short-read sequencing methods. An alternative powerful method for studying isoforms is through the use of barcoded short-read RNA reads, for which a barcode indicates whether two short-reads arise from the same molecule or not. Such techniques included the 10x Genomics linked-read based SParse Isoform Sequencing (SPIso-seq), as well as Loop-Seq, or Tell-Seq. Some applications, such as novel-isoform discovery, require very high coverage. Obtaining high coverage using long reads can be difficult, making barcoded RNA-seq data a valuable alternative for this task. However, most annotation pipelines are not able to work with a set of short reads instead of a single transcript, also not able to work with coverage gaps within a molecule if any. In order to overcome this challenge, we present an RNA-seq assembler that allows the determination of the expressed isoform per barcode. Results: In this article, we present CLOUDRNASPADES, a tool for assembling full-length isoforms from barcoded RNA-seq linked-read data in a reference-free fashion. Evaluating it on simulated and real human data, we found that CLOUDRNASPADES accurately assembles isoforms, even for genes with high isoform diversity.Peer reviewe

Erratum to: Promoter-like epigenetic signatures in exons displaying cell type-specific splicing

After the publication of this work [1] an error was noticed in Fig. 7. The panel‘h’ is missing from Fig. 7. Please see the corrected figure below. The publisher apologises for this error