Evidence map›Paper›PMID 28143409›Full record

ArticleBMC genomics2017

Improved annotation with de novo transcriptome assembly in four social amoeba species.

Reema Singh, Hajara M Lawal, Christina Schilde, Gernot Glöckner, Geoffrey J Barton, Pauline Schaap, Christian Cole

Abstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Reema SinghComputational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK.
Hajara M LawalCell and Development Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK.
Christina SchildeCell and Development Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK.
Gernot GlöcknerInstitute of Biochemistry I, Medical Faculty, University of Cologne, D-50931, Cologne, Germany.
Geoffrey J BartonComputational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK.
Pauline SchaapCell and Development Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK.
Christian ColeComputational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, UK. c.cole@dundee.ac.uk.ORCID 0000-0002-2560-2484

Funding

Biotechnology and Biological Sciences Research Council BB/K000799/1Wellcome Trust 098439/Z/12/ZWellcome Trust 100293/Z/12/Z
6 · The paper itself

Abstract

backgroundAnnotation of gene models and transcripts is a fundamental step in genome sequencing projects. Often this is performed with automated prediction pipelines, which can miss complex and atypical genes or transcripts. RNA sequencing (RNA-seq) data can aid the annotation with empirical data. Here we present de novo transcriptome assemblies generated from RNA-seq data in four Dictyostelid species: D. discoideum, P. pallidum, D. fasciculatum and D. lacteum. The assemblies were incorporated with existing gene models to determine corrections and improvement on a whole-genome scale. This is the first time this has been performed in these eukaryotic species.

resultsAn initial de novo transcriptome assembly was generated by Trinity for each species and then refined with Program to Assemble Spliced Alignments (PASA). The completeness and quality were assessed with the Benchmarking Universal Single-Copy Orthologs (BUSCO) and Transrate tools at each stage of the assemblies. The final datasets of 11,315-12,849 transcripts contained 5,610-7,712 updates and corrections to >50% of existing gene models including changes to hundreds or thousands of protein products. Putative novel genes are also identified and alternative splice isoforms were observed for the first time in P. pallidum, D. lacteum and D. fasciculatum.

conclusionsIn taking a whole transcriptome approach to genome annotation with empirical data we have been able to enrich the annotations of four existing genome sequencing projects. In doing so we have identified updates to the majority of the gene annotations across all four species under study and found putative novel genes and transcripts which could be worthy for follow-up. The new transcriptome data we present here will be a valuable resource for genome curators in the Dictyostelia and we propose this effective methodology for use in other genome annotation projects.

Indexed as

Gene Expression ProfilingMolecular Sequence AnnotationTranscriptomeAmoebaCloning, MolecularComputational BiologyGenomeGenomicsHigh-Throughput Nucleotide SequencingReproducibility of ResultsDe novoDictyosteliaRNA-seqSocial amoebaTranscriptome assembly

Identifiers

PMID28143409
PMCPMC5282741

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