Universität zu Köln

Cook, David E., Valle-Inclan, Jose Espejo, Pajoro, Alice, Rovenich, Hanna, Thomma, Bart P. H. J. ORCID: 0000-0003-4125-4181 and Faino, Luigi ORCID: 0000-0002-6807-4191 (2019). Long-Read Annotation: Automated Eukaryotic Genome Annotation Based on Long-Read cDNA Sequencing. Plant Physiol., 179 (1). S. 38 - 55. ROCKVILLE: AMER SOC PLANT BIOLOGISTS. ISSN 1532-2548

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Abstract

Single-molecule full-length complementary DNA (cDNA) sequencing can aid genome annotation by revealing transcript structure and alternative splice forms, yet current annotation pipelines do not incorporate such information. Here we present long-read annotation (LoReAn) software, an automated annotation pipeline utilizing short-and long-read cDNA sequencing, protein evidence, and ab initio prediction to generate accurate genome annotations. Based on annotations of two fungal genomes (Verticillium dahliae and Plicaturopsis crispa) and two plant genomes (Arabidopsis [Arabidopsis thaliana] and Oryza sativa), we show that LoReAn outperforms popular annotation pipelines by integrating single-molecule cDNA-sequencing data generated from either the Pacific Biosciences or MinION sequencing platforms, correctly predicting gene structure, and capturing genes missed by other annotation pipelines.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Cook, David E. UNSPECIFIED UNSPECIFIED UNSPECIFIED Valle-Inclan, Jose Espejo UNSPECIFIED UNSPECIFIED UNSPECIFIED Pajoro, Alice UNSPECIFIED UNSPECIFIED UNSPECIFIED Rovenich, Hanna UNSPECIFIED UNSPECIFIED UNSPECIFIED Thomma, Bart P. H. J. UNSPECIFIED orcid.org/0000-0003-4125-4181 UNSPECIFIED Faino, Luigi UNSPECIFIED orcid.org/0000-0002-6807-4191 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-140430
DOI:	10.1104/pp.18.00848
Journal or Publication Title:	Plant Physiol.
Volume:	179
Number:	1
Page Range:	S. 38 - 55
Date:	2019
Publisher:	AMER SOC PLANT BIOLOGISTS
Place of Publication:	ROCKVILLE
ISSN:	1532-2548
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Biology > Botanical Institute
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language ARABIDOPSIS INFORMATION RESOURCE; RNA-SEQ; PROVIDES INSIGHTS; GENE PREDICTION; TRANSCRIPTOME; CHROMOSOME; EVOLUTION; ORTHOMCL; TOOL Multiple languages Plant Sciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14043