CORE
CO
nnecting
RE
positories
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Research partnership
About
About
About us
Our mission
Team
Blog
FAQs
Contact us
Community governance
Governance
Advisory Board
Board of supporters
Research network
Innovations
Our research
Labs
research
A quantitative reference transcriptome for Nematostella vectensis early embryonic development : a pipeline for de novo assembly in emerging model systems
Authors
Derek Aguiar
Sorin Istrail
Joel Smith
Sarah Tulin
Publication date
1 January 2013
Publisher
'Springer Science and Business Media LLC'
Doi
View
on
PubMed
Abstract
© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in EvoDevo 4 (2013): 16, doi:10.1186/2041-9139-4-16.The de novo assembly of transcriptomes from short shotgun sequences raises challenges due to random and non-random sequencing biases and inherent transcript complexity. We sought to define a pipeline for de novo transcriptome assembly to aid researchers working with emerging model systems where well annotated genome assemblies are not available as a reference. To detail this experimental and computational method, we used early embryos of the sea anemone, Nematostella vectensis, an emerging model system for studies of animal body plan evolution. We performed RNA-seq on embryos up to 24 h of development using Illumina HiSeq technology and evaluated independent de novo assembly methods. The resulting reads were assembled using either the Trinity assembler on all quality controlled reads or both the Velvet and Oases assemblers on reads passing a stringent digital normalization filter. A control set of mRNA standards from the National Institute of Standards and Technology (NIST) was included in our experimental pipeline to invest our transcriptome with quantitative information on absolute transcript levels and to provide additional quality control. We generated >200 million paired-end reads from directional cDNA libraries representing well over 20 Gb of sequence. The Trinity assembler pipeline, including preliminary quality control steps, resulted in more than 86% of reads aligning with the reference transcriptome thus generated. Nevertheless, digital normalization combined with assembly by Velvet and Oases required far less computing power and decreased processing time while still mapping 82% of reads. We have made the raw sequencing reads and assembled transcriptome publically available. Nematostella vectensis was chosen for its strategic position in the tree of life for studies into the origins of the animal body plan, however, the challenge of reference-free transcriptome assembly is relevant to all systems for which well annotated gene models and independently verified genome assembly may not be available. To navigate this new territory, we have constructed a pipeline for library preparation and computational analysis for de novo transcriptome assembly. The gene models defined by this reference transcriptome define the set of genes transcribed in early Nematostella development and will provide a valuable dataset for further gene regulatory network investigations
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Springer - Publisher Connector
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 30/04/2017
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
info:doi/10.1186%2F2041-9139-4...
Last time updated on 01/04/2019
Springer - Publisher Connector
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 05/06/2019
Woods Hole Open Access Server
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:darchive.mblwhoilibrary.or...
Last time updated on 07/08/2019