Dataset Information

Tiling Assembly: a new tool for reference annotation-independent transcript assembly and novel gene identification by RNA-sequencing.

ABSTRACT: Annotation of the rice (Oryza sativa) genome has evolved significantly since release of its draft sequence, but it is far from complete. Several published transcript assembly programmes were tested on RNA-sequencing (RNA-seq) data to determine their effectiveness in identifying novel genes to improve the rice genome annotation. Cufflinks, a popular assembly software, did not identify all transcripts suggested by the RNA-seq data. Other assembly software was CPU intensive, lacked documentation, or lacked software updates. To overcome these shortcomings, a heuristic ab initio transcript assembly algorithm, Tiling Assembly, was developed to identify genes based on short read and junction alignment. Tiling Assembly was compared with Cufflinks to evaluate its gene-finding capabilities. Additionally, a pipeline was developed to eliminate false-positive gene identification due to noise or repetitive regions in the genome. By combining Tiling Assembly and Cufflinks, 767 unannotated genes were identified in the rice genome, demonstrating that combining both programmes proved highly efficient for novel gene identification. We also demonstrated that Tiling Assembly can accurately determine transcription start sites by comparing the Tiling Assembly genes with their corresponding full-length cDNA. We applied our pipeline to additional organisms and identified numerous unannotated genes, demonstrating that Tiling Assembly is an organism-independent tool for genome annotation.

SUBMITTER: Watanabe KA

PROVIDER: S-EPMC4596398 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Tiling Assembly: a new tool for reference annotation-independent transcript assembly and novel gene identification by RNA-sequencing.

Watanabe Kenneth A KA Homayouni Arielle A Tufano Tara T Lopez Jennifer J Ringler Patricia P Rushton Paul P Shen Qingxi J QJ

DNA research : an international journal for rapid publication of reports on genes and genomes 20150903 5

Annotation of the rice (Oryza sativa) genome has evolved significantly since release of its draft sequence, but it is far from complete. Several published transcript assembly programmes were tested on RNA-sequencing (RNA-seq) data to determine their effectiveness in identifying novel genes to improve the rice genome annotation. Cufflinks, a popular assembly software, did not identify all transcripts suggested by the RNA-seq data. Other assembly software was CPU intensive, lacked documentation, o ...[more]

PMID: 26341416

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Project description:BackgroundAn individual's genetics play a role in how RNA transcripts are generated from DNA and consequently in their translation into protein. Transcriptional and translational profiling of patients furnishes the information that a specific marker is present; however, it fails to provide evidence whether the marker correlates with response to a therapeutic agent. A comparative analysis of the frequency of genetic variants, such as single nucleotide polymorphisms (SNPs), in diseased and general populations can identify pathogenic variants in individual patients. This is in part because SNPs have considerable effects on protein function and gene expression when they occur in coding regions and regulatory sequences, respectively. Therefore, a tool that can help users to obtain the allele frequency for a corresponding transcript is the need of the day. Several annotation tools such as SNPnexus and VariED are publicly available; however, none of them can use transcript IDs as input and provide the corresponding genomic positions of variants.ResultsIn this study, we developed an R package, called transcript annotation tool (TransAT), that provides (i) SNP ID and genomic position for a user-provided transcript ID from patients, and (ii) allele frequencies for the SNPs from publicly available global populations. All data elements are extracted, collected, and displayed in an easily downloadable format in two simple command lines. TransAT is available on Windows/Linux/MacOS and is operative for R version 4.0.4 or later. It is available at https://github.com/ShihChingYu/TransAT and can be downloaded and installed using devtools::install_github("ShihChingYu/TransAT", force=T) on the R execution page. Thereafter, all functions can be executed by loading the package into R with library(TransAT).ConclusionsTransAT is a novel tool that seamlessly provides genetic annotations for queried transcripts. Such easily obtainable information would be greatly advantageous for physicians, assisting them to make individualized decisions about specific drug treatments. Moreover, allele frequencies from user-chosen global ethnic populations will highlight the importance of ethnicity and its effect on patient pathogenicity.

Dataset Information

Tiling Assembly: a new tool for reference annotation-independent transcript assembly and novel gene identification by RNA-sequencing.

Publications

Tiling Assembly: a new tool for reference annotation-independent transcript assembly and novel gene identification by RNA-sequencing.

Similar Datasets

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