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
JI953322JI953322.1region
JI953321JI953321.1region
JI953320JI953320.1region
JI953319JI953319.1region
JI953318JI953318.1region
JI953317JI953317.1region
JI953316JI953316.1region
JI953315JI953315.1region
JI953314JI953314.1region
JI953313JI953313.1region
JI953312JI953312.1region
JI953311JI953311.1region
JI953310JI953310.1region
JI953309JI953309.1region
JI953308JI953308.1region
JI953307JI953307.1region
JI953306JI953306.1region
JI953305JI953305.1region
JI953304JI953304.1region
JI953303JI953303.1region
JI953302JI953302.1region
JI953301JI953301.1region
JI953300JI953300.1region
JI953299JI953299.1region
JI953298JI953298.1region

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