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
JI957272JI957272.1region
JI957271JI957271.1region
JI957270JI957270.1region
JI957269JI957269.1region
JI957268JI957268.1region
JI957267JI957267.1region
JI957266JI957266.1region
JI957265JI957265.1region
JI957264JI957264.1region
JI957263JI957263.1region
JI957262JI957262.1region
JI957261JI957261.1region
JI957260JI957260.1region
JI957259JI957259.1region
JI957258JI957258.1region
JI957257JI957257.1region
JI957256JI957256.1region
JI957255JI957255.1region
JI957254JI957254.1region
JI957253JI957253.1region
JI957252JI957252.1region
JI957251JI957251.1region
JI957250JI957250.1region
JI957249JI957249.1region
JI957248JI957248.1region

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