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Title: Defining the maize transcriptome de novo using deep RNA-Seq

Abstract

De novo assembly of the transcriptome is crucial for functional genomics studies in bioenergy research, since many of the organisms lack high quality reference genomes. In a previous study we successfully de novo assembled simple eukaryote transcriptomes exclusively from short Illumina RNA-Seq reads [1]. However, extensive alternative splicing, present in most of the higher eukaryotes, poses a significant challenge for current short read assembly processes. Furthermore, the size of next-generation datasets, often large for plant genomes, presents an informatics challenge. To tackle these challenges we present a combined experimental and informatics strategy for de novo assembly in higher eukaryotes. Using maize as a test case, preliminary results suggest our approach can resolve transcript variants and improve gene annotations.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Genomics Division
OSTI Identifier:
1050662
Report Number(s):
LBNL-4782E-Poster-Pt1
DOE Contract Number:
DE-AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: 6th Annual DOE JGI User Meeting , Walnut Creek, CA, 3/22 - 3/24/2011
Country of Publication:
United States
Language:
English
Subject:
99; 97; de novo assembly, RNA-sequencing, informatics, eukaryotes, transcript variants, gene annotations

Citation Formats

Martin, Jeffrey, Gross, Stephen, Choi, Cindy, Zhang, Tao, Lindquist, Erika, Wei, Chia-Lin, and Wang, Zhong. Defining the maize transcriptome de novo using deep RNA-Seq. United States: N. p., 2011. Web.
Martin, Jeffrey, Gross, Stephen, Choi, Cindy, Zhang, Tao, Lindquist, Erika, Wei, Chia-Lin, & Wang, Zhong. Defining the maize transcriptome de novo using deep RNA-Seq. United States.
Martin, Jeffrey, Gross, Stephen, Choi, Cindy, Zhang, Tao, Lindquist, Erika, Wei, Chia-Lin, and Wang, Zhong. 2011. "Defining the maize transcriptome de novo using deep RNA-Seq". United States. doi:. https://www.osti.gov/servlets/purl/1050662.
@article{osti_1050662,
title = {Defining the maize transcriptome de novo using deep RNA-Seq},
author = {Martin, Jeffrey and Gross, Stephen and Choi, Cindy and Zhang, Tao and Lindquist, Erika and Wei, Chia-Lin and Wang, Zhong},
abstractNote = {De novo assembly of the transcriptome is crucial for functional genomics studies in bioenergy research, since many of the organisms lack high quality reference genomes. In a previous study we successfully de novo assembled simple eukaryote transcriptomes exclusively from short Illumina RNA-Seq reads [1]. However, extensive alternative splicing, present in most of the higher eukaryotes, poses a significant challenge for current short read assembly processes. Furthermore, the size of next-generation datasets, often large for plant genomes, presents an informatics challenge. To tackle these challenges we present a combined experimental and informatics strategy for de novo assembly in higher eukaryotes. Using maize as a test case, preliminary results suggest our approach can resolve transcript variants and improve gene annotations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2011,
month = 6
}

Conference:
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  • De novo assembly of the transcriptome is crucial for functional genomics studies in bioenergy research, since many of the organisms lack high quality reference genomes. In a previous study we successfully de novo assembled simple eukaryote transcriptomes exclusively from short Illumina RNA-Seq reads [1]. However, extensive alternative splicing, present in most of the higher eukaryotes, poses a significant challenge for current short read assembly processes. Furthermore, the size of next-generation datasets, often large for plant genomes, presents an informatics challenge. To tackle these challenges we present a combined experimental and informatics strategy for de novo assembly in higher eukaryotes. Usingmore » maize as a test case, preliminary results suggest our approach can resolve transcript variants and improve gene annotations.« less
  • Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less