Universität zu Köln

Singh, Reema ORCID: 0000-0001-7049-5473, Lawal, Hajara M., Schilde, Christina, Gloeckner, Gernot, Barton, Geoffrey J., Schaap, Pauline ORCID: 0000-0003-4500-2555 and Cole, Christian ORCID: 0000-0002-2560-2484 (2017). Improved annotation with de novo transcriptome assembly in four social amoeba species. BMC Genomics, 18. LONDON: BMC. ISSN 1471-2164

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Abstract

Background: Annotation 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. Results: An 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. Conclusions: In 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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Singh, Reema UNSPECIFIED orcid.org/0000-0001-7049-5473 UNSPECIFIED Lawal, Hajara M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schilde, Christina UNSPECIFIED UNSPECIFIED UNSPECIFIED Gloeckner, Gernot UNSPECIFIED UNSPECIFIED UNSPECIFIED Barton, Geoffrey J. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schaap, Pauline UNSPECIFIED orcid.org/0000-0003-4500-2555 UNSPECIFIED Cole, Christian UNSPECIFIED orcid.org/0000-0002-2560-2484 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-242039
DOI:	10.1186/s12864-017-3505-0
Journal or Publication Title:	BMC Genomics
Volume:	18
Date:	2017
Publisher:	BMC
Place of Publication:	LONDON
ISSN:	1471-2164
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language MULTIPLE SEQUENCE ALIGNMENT; GENOME ANNOTATION; MESSENGER-RNA; IDENTIFICATION; PREDICTION; DATABASE; RECONSTRUCTION; SMART Multiple languages Biotechnology & Applied Microbiology; Genetics & Heredity Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/24203