Comprehensive transcriptome analysis of the highly complex Pisum sativum genome using next generation sequencing

Publication Overview
TitleComprehensive transcriptome analysis of the highly complex Pisum sativum genome using next generation sequencing
AuthorsFranssen SU, Shrestha RP, Bräutigam A, Bornberg-Bauer E, Weber AP
TypeJournal Article
Journal NameBMC genomics
Volume12
Year2011
Page(s)227
CitationFranssen SU, Shrestha RP, Bräutigam A, Bornberg-Bauer E, Weber AP. Comprehensive transcriptome analysis of the highly complex Pisum sativum genome using next generation sequencing. BMC genomics. 2011; 12:227.

Abstract

BACKGROUND
The garden pea, Pisum sativum, is among the best-investigated legume plants and of significant agro-commercial relevance. Pisum sativum has a large and complex genome and accordingly few comprehensive genomic resources exist.

RESULTS
We analyzed the pea transcriptome at the highest possible amount of accuracy by current technology. We used next generation sequencing with the Roche/454 platform and evaluated and compared a variety of approaches, including diverse tissue libraries, normalization, alternative sequencing technologies, saturation estimation and diverse assembly strategies. We generated libraries from flowers, leaves, cotyledons, epi- and hypocotyl, and etiolated and light treated etiolated seedlings, comprising a total of 450 megabases. Libraries were assembled into 324,428 unigenes in a first pass assembly.A second pass assembly reduced the amount to 81,449 unigenes but caused a significant number of chimeras. Analyses of the assemblies identified the assembly step as a major possibility for improvement. By recording frequencies of Arabidopsis orthologs hit by randomly drawn reads and fitting parameters of the saturation curve we concluded that sequencing was exhaustive. For leaf libraries we found normalization allows partial recovery of expression strength aside the desired effect of increased coverage. Based on theoretical and biological considerations we concluded that the sequence reads in the database tagged the vast majority of transcripts in the aerial tissues. A pathway representation analysis showed the merits of sampling multiple aerial tissues to increase the number of tagged genes. All results have been made available as a fully annotated database in fasta format.

CONCLUSIONS
We conclude that the approach taken resulted in a high quality - dataset which serves well as a first comprehensive reference set for the model legume pea. We suggest future deep sequencing transcriptome projects of species lacking a genomics backbone will need to concentrate mainly on resolving the issues of redundancy and paralogy during transcriptome assembly.

Features
This publication contains information about 84,267 features:
Feature NameUniquenameType
JI954522JI954522.1region
JI954521JI954521.1region
JI954520JI954520.1region
JI954519JI954519.1region
JI954518JI954518.1region
JI954517JI954517.1region
JI954516JI954516.1region
JI954515JI954515.1region
JI954514JI954514.1region
JI954513JI954513.1region
JI954512JI954512.1region
JI954511JI954511.1region
JI954510JI954510.1region
JI954509JI954509.1region
JI954508JI954508.1region
JI954507JI954507.1region
JI954506JI954506.1region
JI954505JI954505.1region
JI954504JI954504.1region
JI954503JI954503.1region
JI954502JI954502.1region
JI954501JI954501.1region
JI954500JI954500.1region
JI954499JI954499.1region
JI954498JI954498.1region

Pages

Properties
Additional details for this publication include:
Property NameValue
Publication Date2011
Journal AbbreviationBMC Genomics
DOI10.1186/1471-2164-12-227
Elocation10.1186/1471-2164-12-227
Journal CountryEngland
Publication ModelElectronic
ISSN1471-2164
eISSN1471-2164
LanguageEnglish
Language Abbreng
Publication TypeJournal Article
Publication TypeResearch Support, Non-U.S. Gov't