Dataset Information

Alternative Splicing in Next Generation Sequencing Data of Saccharomyces cerevisiae.

ABSTRACT: mRNA splicing is required in about 4% of protein coding genes in Saccharomyces cerevisiae. The gene structure of those genes is simple, generally comprising two exons and one intron. In order to characterize the impact of alternative splicing on the S. cerevisiae transcriptome, we perform a systematic analysis of mRNA sequencing data. We find evidence of a pervasive use of alternative splice sites and detect several novel introns both within and outside protein coding regions. We also find a predominance of alternative splicing on the 3' side of introns, a finding which is consistent with existing knowledge on conservation of exon-intron boundaries in S. cerevisiae. Some of the alternatively spliced transcripts allow for a translation into different protein products.

SUBMITTER: Schreiber K

PROVIDER: S-EPMC4607428 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Alternative Splicing in Next Generation Sequencing Data of Saccharomyces cerevisiae.

Schreiber Konrad K Csaba Gergely G Haslbeck Martin M Zimmer Ralf R

PloS one 20151015 10

mRNA splicing is required in about 4% of protein coding genes in Saccharomyces cerevisiae. The gene structure of those genes is simple, generally comprising two exons and one intron. In order to characterize the impact of alternative splicing on the S. cerevisiae transcriptome, we perform a systematic analysis of mRNA sequencing data. We find evidence of a pervasive use of alternative splice sites and detect several novel introns both within and outside protein coding regions. We also find a pre ...[more]

PMID: 26469855

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Project description:Motivation. Alternative splicing events (ASEs) are prevalent in the transcriptome of eukaryotic species and are known to influence many biological phenomena. The identification and quantification of these events are crucial for a better understanding of biological processes. Next-generation DNA sequencing technologies have allowed deep characterization of transcriptomes and made it possible to address these issues. ASEs analysis, however, represents a challenging task especially when many different samples need to be compared. Some popular tools for the analysis of ASEs are known to report thousands of events without annotations and/or graphical representations. A new tool for the identification and visualization of ASEs is here described, which can be used by biologists without a solid bioinformatics background. Results. A software suite named Splicing Express was created to perform ASEs analysis from transcriptome sequencing data derived from next-generation DNA sequencing platforms. Its major goal is to serve the needs of biomedical researchers who do not have bioinformatics skills. Splicing Express performs automatic annotation of transcriptome data (GTF files) using gene coordinates available from the UCSC genome browser and allows the analysis of data from all available species. The identification of ASEs is done by a known algorithm previously implemented in another tool named Splooce. As a final result, Splicing Express creates a set of HTML files composed of graphics and tables designed to describe the expression profile of ASEs among all analyzed samples. By using RNA-Seq data from the Illumina Human Body Map and the Rat Body Map, we show that Splicing Express is able to perform all tasks in a straightforward way, identifying well-known specific events. Availability and Implementation. Splicing Express is written in Perl and is suitable to run only in UNIX-like systems. More details can be found at: http://www.bioinformatics-brazil.org/splicingexpress.

Project description:Full-length human immunodeficiency virus type 1 (HIV-1) RNA serves as the genome or as an mRNA, or this RNA undergoes splicing using four donors and 10 acceptors to create over 50 physiologically relevant transcripts in two size classes (1.8 kb and 4 kb). We developed an assay using Primer ID-tagged deep sequencing to quantify HIV-1 splicing. Using the lab strain NL4-3, we found that A5 (env/nef) is the most commonly used acceptor (about 50%) and A3 (tat) the least used (about 3%). Two small exons are made when a splice to acceptor A1 or A2 is followed by activation of donor D2 or D3, and the high-level use of D2 and D3 dramatically reduces the amount of vif and vpr transcripts. We observed distinct patterns of temperature sensitivity of splicing to acceptors A1 and A2. In addition, disruption of a conserved structure proximal to A1 caused a 10-fold reduction in all transcripts that utilized A1. Analysis of a panel of subtype B transmitted/founder viruses showed that splicing patterns are conserved, but with surprising variability of usage. A subtype C isolate was similar, while a simian immunodeficiency virus (SIV) isolate showed significant differences. We also observed transsplicing from a downstream donor on one transcript to an upstream acceptor on a different transcript, which we detected in 0.3% of 1.8-kb RNA reads. There were several examples of splicing suppression when the env intron was retained in the 4-kb size class. These results demonstrate the utility of this assay and identify new examples of HIV-1 splicing regulation. IMPORTANCE During HIV-1 replication, over 50 conserved spliced RNA variants are generated. The splicing assay described here uses new developments in deep-sequencing technology combined with Primer ID-tagged cDNA primers to efficiently quantify HIV-1 splicing at a depth that allows even low-frequency splice variants to be monitored. We have used this assay to examine several features of HIV-1 splicing and to identify new examples of different mechanisms of regulation of these splicing patterns. This splicing assay can be used to explore in detail how HIV-1 splicing is regulated and, with moderate throughput, could be used to screen for structural elements, small molecules, and host factors that alter these relatively conserved splicing patterns.

Dataset Information

Alternative Splicing in Next Generation Sequencing Data of Saccharomyces cerevisiae.

Publications

Alternative Splicing in Next Generation Sequencing Data of Saccharomyces cerevisiae.

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