Title | cloudrnaSPAdes: isoform assembly using bulk barcoded RNA sequencing data. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Meleshko D, Prjbelski AD, Raiko M, Tomescu AI, Tilgner H, Hajirasouliha I |
Journal | Bioinformatics |
Volume | 40 |
Issue | 2 |
Date Published | 2024 Feb 01 |
ISSN | 1367-4811 |
Keywords | Genomics, High-Throughput Nucleotide Sequencing, Humans, Protein Isoforms, RNA, RNA-Seq, Sequence Analysis, RNA, Transcriptome |
Abstract | 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. AVAILABILITY AND IMPLEMENTATION: cloudrnaSPAdes is a feature release of a SPAdes assembler and version used for this article is available at https://github.com/1dayac/cloudrnaSPAdes-release. |
DOI | 10.1093/bioinformatics/btad781 |
Alternate Journal | Bioinformatics |
PubMed ID | 38262343 |
PubMed Central ID | PMC10868327 |
Grant List | R35 GM138152 / GM / NIGMS NIH HHS / United States |