Biology subjects

Entizne, J. C.

Publications and source records attributed to Entizne, J. C..

5 recordsLinked to original sources

bioRxiv2021

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

Accurate characterization of splice junctions as well as transcription start and end sites in reference transcriptomes allows precise quantification of transcripts from RNA-seq data and enable 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 (RTD) from the European 2-row spring barley cultivar Barke (BaRTv2.18). Stringent and thorough filtering was carried out to maintain the quality and accuracy of the splice junctions and transcript start and end sites. BaRTv2.18 shows increased transcript diversity and completeness compared to an earlier version, BaRTv1.0. The accuracy of transcript level quantification, splice junctions and transcript start and end sites has been validated extensively using parallel technologies and analysis, including high resolution RT PCR and 5 RACE. BaRTv2.18 contains 39,434 genes and 148,260 transcripts, representing the most comprehensive and resolved reference transcriptome in barley to date. It provides an important and high-quality resource for advanced transcriptomic analyses, including both transcriptional and post-transcriptional regulation, with exceptional resolution and precision.

plant biology↗

bioRxiv2021

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

BackgroundAccurate 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. ResultsWe present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 160k transcripts - twice that of the best current Arabidopsis transcriptome and including over 1,500 novel genes. 79% of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We developed novel methods to determine splice junctions and transcription start and end sites accurately. Mis- match profiles around splice junctions provided a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identified high confidence transcription start/end sites and removed fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provided higher resolution of transcript expression profiling and identified cold- and light-induced differential transcription start and polyadenylation site usage. ConclusionsAtRTD3 is the most comprehensive Arabidopsis transcriptome currently available. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single molecule sequencing analysis from any species.

plant biology↗

bioRxiv2020

TranSuite: a software suite for accurate translation and characterization of transcripts

Protein translation programs often select the longest open reading frame (ORF) in a transcript leading to numerous inaccurate and mis-annotated ORFs in databases. Unproductive transcript isoforms containing premature termination codons (PTCs) are potential substrates for nonsense-mediated decay (NMD). These transcripts often contain truncated ORFs but are incorrectly annotated due to selection of a long ORF beginning at an AUG downstream of the PTC despite the transcript containing the authentic translation start AUG. In gene expression and alternative splicing analyses, it is important to identify transcript isoforms which code for different protein variants and to distinguish these from potential NMD substrates. Here, we present TranSuite, a pipeline of bioinformatics tools that address these challenges by performing accurate translations, characterizing alternative ORFs and identifying NMD and other features of transcripts in newly assembled and existing transcriptomes. Directly comparing ORFs defined by TranSuite and TransDecoder for the Arabidopsis transcriptome AtRTD2 identified ORF mis-calling in over 16k (27%) of transcripts by TransDecoder.

bioinformatics↗

bioRxiv2018

Rapid and dynamic alternative splicing impacts the Arabidopsis cold response transcriptome

BackgroundPlants have adapted to tolerate and survive constantly changing environmental conditions by re-programming gene expression. The scale of the contribution of alternative splicing (AS) to stress responses has been underestimated due to limitations in RNA-seq analysis programs and poor representation of AS transcripts in plant databases. Significantly, the dynamics of the AS response have not been investigated but this is now possible with accurate transcript quantification programs and AtRTD2, a new, comprehensive transcriptome for Arabidopsis.\n\nResultsUsing ultra-deep RNA-sequencing of a time-course of Arabidopsis thaliana plants exposed to cold treatment, we identified 8,949 genes with altered expression of which 2,442 showed significant differential alternative splicing (DAS) and 1,647 genes were regulated only at the level of AS (DAS-only). The high temporal resolution demonstrated the rapid induction of both transcription and AS resulting in coincident waves of differential expression (transcription) and differential alternative splicing in the first 6-9 hours of cold. The differentially expressed and DAS gene sets were largely non-overlapping, each comprising thousands of genes. The dynamic analysis of AS identified genes with rapid and sensitive AS within 3 h of transfer to the cold (early AS genes), which were enriched for splicing and transcription factors. A detailed investigation of the novel cold-response DAS-only gene, U2B\"-LIKE, suggested that it regulates AS and is required for tolerance to freezing.\n\nConclusionsOur data indicate that transcription and AS are the major regulators of transcriptome reprogramming that together govern the physiological and survival responses of plants to low temperature.

genomics↗

bioRxiv2016

Fast and accurate differential splicing analysis across multiple conditions with replicates

Multiple approaches have been proposed to study differential splicing from RNA sequencing (RNA-seq) data1, including the analysis of transcript isoforms2,3, clusters of splice-junctions4,5, alternative splicing events6-8 and exonic regions9. However, many challenges remain unsolved, including the limitation in speed, the computing capacity and storage requirements, the constraints in the number of reads needed to achieve sufficient accuracy, and the lack of robust methods to account for variability between replicates and for analyses across multiple conditions. We present here a significant extension of SUPPA8 to enable streamlined analysis of differential splicing across multiple conditions, taking into account biological variability. We show that SUPPA differential splicing analysis achieves high accuracy using extensive experimental and simulated data compared to other methods; and shows higher accuracy at low sequencing depth, with short read lengths, and using replicas with unbalanced depth, which has important implications for the cost-effective use of RNA-seq data for splicing analysis. We also validate the analysis of multiple conditions with SUPPA by studying differential splicing during iPS-cell to neuron differentiation and during erythroblast differentiation, providing support for the applicability of SUPPA for the robust analysis of differential splicing beyond binary comparisons.

bioinformatics↗