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
JI959447JI959447.1region
JI959446JI959446.1region
JI959445JI959445.1region
JI959444JI959444.1region
JI959443JI959443.1region
JI959442JI959442.1region
JI959441JI959441.1region
JI959440JI959440.1region
JI959439JI959439.1region
JI959438JI959438.1region
JI959437JI959437.1region
JI959436JI959436.1region
JI959435JI959435.1region
JI959434JI959434.1region
JI959433JI959433.1region
JI959432JI959432.1region
JI959431JI959431.1region
JI959430JI959430.1region
JI959429JI959429.1region
JI959428JI959428.1region
JI959427JI959427.1region
JI959426JI959426.1region
JI959425JI959425.1region
JI959424JI959424.1region
JI959423JI959423.1region

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