A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis.

Background: Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis.

BaRTv2: a highly resolved barley reference transcriptome for accurate transcript-specific RNA-seq quantification.

Accurate characterisation of splice junctions (SJs) as well as transcription start and end sites in reference transcriptomes allows precise quantification of transcripts from RNA-seq data, and enables detailed investigations of transcriptional and post-transcriptional regulation. Using novel computational methods and a combination of PacBio Iso-seq and Illumina short-read sequences from 20 diverse tissues and conditions, we generated a comprehensive and highly resolved barley reference transcript dataset from the European 2-row spring barley cultivar Barke (BaRTv2.18).

Rapid and Dynamic Alternative Splicing Impacts the Arabidopsis Cold Response Transcriptome.

Plants have adapted to tolerate and survive constantly changing environmental conditions by reprogramming gene expression The dynamics of the contribution of alternative splicing (AS) to stress responses are unknown. RNA-sequencing of a time-series of plants exposed to cold determines the timing of significant AS changes. This shows a massive and rapid AS response with coincident waves of transcriptional and AS activity occurring in the first few hours of temperature reduction and further AS throughout the cold.

SUPPA2: fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions.

Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length.

A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing.

Alternative splicing generates multiple transcript and protein isoforms from the same gene and thus is important in gene expression regulation. To date, RNA-sequencing (RNA-seq) is the standard method for quantifying changes in alternative splicing on a genome-wide scale. Understanding the current limitations of RNA-seq is crucial for reliable analysis and the lack of high quality, comprehensive transcriptomes for most species, including model organisms such as Arabidopsis, is a major constraint in accurate quantification of transcript isoforms.