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      De novo characterization of a whitefly transcriptome and analysis of its gene expression during development

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          Abstract

          Background

          Whitefly ( Bemisia tabaci) causes extensive crop damage throughout the world by feeding directly on plants and by vectoring hundreds of species of begomoviruses. Yet little is understood about its genes involved in development, insecticide resistance, host range plasticity and virus transmission.

          Results

          To facilitate research on whitefly, we present a method for de novo assembly of whitefly transcriptome using short read sequencing technology (Illumina). In a single run, we produced more than 43 million sequencing reads. These reads were assembled into 168,900 unique sequences (mean size = 266 bp) which represent more than 10-fold of all the whitefly sequences deposited in the GenBank (as of March 2010). Based on similarity search with known proteins, these analyses identified 27,290 sequences with a cut-off E-value above 10 -5. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcriptome changes during whitefly development using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 2.5 million tags per sample and identified a large number of genes associated with specific developmental stages and insecticide resistance.

          Conclusion

          Our data provides the most comprehensive sequence resource available for whitefly study and demonstrates that the Illumina sequencing allows de novo transcriptome assembly and gene expression analysis in a species lacking genome information. We anticipate that next generation sequencing technologies hold great potential for the study of the transcriptome in other non-model organisms.

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          Most cited references25

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          TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

          TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.
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            Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms

            The hippocampal expression profiles of wild-type mice and mice transgenic for δC-doublecortin-like kinase were compared with Solexa/Illumina deep sequencing technology and five different microarray platforms. With Illumina's digital gene expression assay, we obtained ∼2.4 million sequence tags per sample, their abundance spanning four orders of magnitude. Results were highly reproducible, even across laboratories. With a dedicated Bayesian model, we found differential expression of 3179 transcripts with an estimated false-discovery rate of 8.5%. This is a much higher figure than found for microarrays. The overlap in differentially expressed transcripts found with deep sequencing and microarrays was most significant for Affymetrix. The changes in expression observed by deep sequencing were larger than observed by microarrays or quantitative PCR. Relevant processes such as calmodulin-dependent protein kinase activity and vesicle transport along microtubules were found affected by deep sequencing but not by microarrays. While undetectable by microarrays, antisense transcription was found for 51% of all genes and alternative polyadenylation for 47%. We conclude that deep sequencing provides a major advance in robustness, comparability and richness of expression profiling data and is expected to boost collaborative, comparative and integrative genomics studies.
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              Asymmetric mating interactions drive widespread invasion and displacement in a whitefly.

              The role of behavioral mechanisms in animal invasions is poorly understood. We show that asymmetric mating interactions between closely related but previously allopatric genetic groups of the whitefly Bemisia tabaci, a haplodiploid species, have been a driving force contributing to widespread invasion and displacement by alien populations. We conducted long-term field surveys, caged population experiments, and detailed behavioral observations in Zhejiang, China, and Queensland, Australia, to investigate the invasion process and its underlying behavioral mechanisms. During invasion and displacement, we found increased frequency of copulation leading to increased production of female progeny among the invader, as well as reduced copulation and female production in the indigenous genetic groups. Such asymmetric mating interactions may be critical to determining the capacity of a haplodiploid invader and the consequences for its closely related indigenous organisms.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2010
                24 June 2010
                : 11
                : 400
                Affiliations
                [1 ]Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou 310029, China
                Article
                1471-2164-11-400
                10.1186/1471-2164-11-400
                2898760
                20573269
                fcd535e0-02fa-4a5c-b25f-c0d8c064064a
                Copyright ©2010 Wang 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.

                History
                : 10 December 2009
                : 24 June 2010
                Categories
                Research Article

                Genetics
                Genetics

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