Detection of splice junctions from paired-end RNA-seq data by SpliceMap

By Kin Fai Au, Hui Jiang, Lan Lin, Yi Xing, Wing Hung Wong. Nucleic Acids Research, 2010

360 citations recorded by the source corpus.

Alternative splicing is a prevalent post-transcriptional process, which is not only important to normal cellular function but is also involved in human diseases. The newly developed second generation sequencing technique provides high-throughput data (RNA-seq data) to study alternative splicing events in different types of cells. Here, we present a computational method, SpliceMap, to detect splice junctions from RNA-seq data. This method does not depend on any existing annotation of gene structures and is capable of finding novel splice junctions with high sensitivity and specificity. It can handle long reads (50–100 nt) and can exploit paired-read information to improve mapping accuracy. Several parameters are included in the output to indicate the reliability of the predicted junction and help filter out false predictions. We applied SpliceMap to analyze 23 million paired 50-nt reads from human brain tissue. The results show at this depth of sequencing, RNA-seq can support reliable detection of splice junctions except for those that are present at very low level. Compared to current methods, SpliceMap can achieve 12% higher sensitivity without sacrificing specificity.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a95a62316d736c970687f855580feacc7490d76f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Sequence Analysis (2020, neutral): “Once constructed, the graph undergoes a basic simplification procedure (Bankevich et al. 2012, Nurk et al. 2013), which removes only edges with extremely low coverage to prune obvious sequencing errors.”
QuasR: quantification and annotation of short reads in R (2014, methodology): “Contact: michael.stadler@fmi.ch Supplementary information: Supplementary data are available at Bioinformatics online.”
Computational methods for transcriptome annotation and quantification using RNA-seq (2011, methodology): “Exon-first 47–49 methods such as MapSplice 49 , SpliceMap 47 and TopHat 48 use a two-step process.”
From RNA-seq reads to differential expression results (2010, methodology): “Mapping General aligner GMAP/GSNAP [91] BFAST [20] BOWTIE [25] CloudBurst [92] GNUmap [93] MAQ/BWA [23] PerM [19] RazerS [94] Mrfast/mrsfast [22] SOAP/SOAP2 [24,95] SHRiMP [21] De novo annotator QPALMA/GenomeMapper/PALMapper [37] SpliceMap [96] SOAPals [95] G-Mo.”
Improving RNA-Seq expression estimates by correcting for fragment bias (2011, methodology): “We began by comparing the expression estimates on the Microarray Quality Control (MAQC) Human Brain Reference (HBR) dataset, which includes 907 transcripts with uniquely mapping TaqMan qRT-PCR probes [16], with RNA-Seq data from the same sample sequenced by Illumina (SRA012427) [17] (Figure 4).”
Expression of Linear and Novel Circular Forms of an INK4/ARF-Associated Non-Coding RNA Correlates with Atherosclerosis Risk (2010, methodology): “Analysis of RNA-seq data A total of 368,846,235 reads generated on the Illumina platform (study SRP002274) were downloaded from the NCBI Short Read Archive.”
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome (2011, methodology): “Three of the plots generated for the RNA-Seq data set from SRA experiment SRX018974 [25] are shown in Additional file 1.”
MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery (2010, methodology): “SpliceMap is another method that uses splice site ﬂanking bases in locating potential splice sites (22).”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, methodology): “RNA‑seq aligners, such as TopHat 58 , MapSplice 59 , rnaSeqMap 60 , RUM 61 and SpliceMap 62 are capable of aligning a short read to two distinct locations.”
Complexity of the Alternative Splicing Landscape in Plants[C][W][OPEN] (2013, methodology): “An evaluation of all the splice products of 13 alternatively spliced Arabidopsis SR genes in a UPF3 mutant revealed that about half of the 53 variants with a PTC are degraded by NMD (Palusa and Reddy, 2010).”