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      De novo assembly and characterization of the root transcriptome of Aegilops variabilis during an interaction with the cereal cyst nematode

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          Abstract

          Background

          Aegilops variabilis No.1 is highly resistant to cereal cyst nematode (CCN). However, a lack of genomic information has restricted studies on CCN resistance genes in Ae. variabilis and has limited genetic applications in wheat breeding.

          Results

          Using RNA-Seq technology, we generated a root transcriptome at a sequencing depth of 4.69 gigabases of Ae. variabilis No. 1 from a pooled RNA sample. The sample contained equal amounts of RNA extracted from CCN-infected and untreated control plants at three time-points. Using the Trinity method, nearly 52,081,238 high-quality trimmed reads were assembled into a non-redundant set of 118,064 unigenes with an average length of 500 bp and an N50 of 599 bp. The total assembly was 59.09 Mb of unique transcriptome sequences with average read-depth coverage of 33.25×. In BLAST searches of our database against public databases, 66.46% (78,467) of the unigenes were annotated with gene descriptions, conserved protein domains, or gene ontology terms. Functional categorization further revealed 7,408 individual unigenes and three pathways related to plant stress resistance.

          Conclusions

          We conducted high-resolution transcriptome profiling related to root development and the response to CCN infection in Ae. variabilis No.1. This research facilitates further studies on gene discovery and on the molecular mechanisms related to CCN resistance.

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          Most cited references 42

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          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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            KEGG: kyoto encyclopedia of genes and genomes.

             M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

              Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2012
                11 April 2012
                : 13
                : 133
                Affiliations
                [1 ]Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, Sichuan, China
                [2 ]Graduate University of the Chinese Academy of Sciences, Beijing, China
                1471-2164-13-133
                10.1186/1471-2164-13-133
                3439707
                22494814
                Copyright ©2012 Xu et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Genetics

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