Dataset Information

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data.

ABSTRACT:

Background

One-dimensional (1-D) electrophoretic data obtained using the cDNA-AFLP method have attracted great interest for the identification of differentially expressed transcript-derived fragments (TDFs). However, high-throughput analysis of the cDNA-AFLP data is currently limited by the need for labor-intensive visual evaluation of multiple electropherograms. We would like to have high-throughput ways of identifying such TDFs.

Results

We describe a method, GOGOT, which automatically detects the differentially expressed TDFs in a set of time-course electropherograms. Analysis by GOGOT is conducted as follows: correction of fragment lengths of TDFs, alignment of identical TDFs across different electropherograms, normalization of peak heights, and identification of differentially expressed TDFs using a special statistic. The output of the analysis is a highly reduced list of differentially expressed TDFs. Visual evaluation confirmed that the peak alignment was performed perfectly for the TDFs by virtue of the correction of peak fragment lengths before alignment in step 1. The validity of the automated ranking of TDFs by the special statistic was confirmed by the visual evaluation of a third party.

Conclusion

GOGOT is useful for the automated detection of differentially expressed TDFs from cDNA-AFLP temporal electrophoretic data. The current algorithm may be applied to other electrophoretic data and temporal microarray data.

SUBMITTER: Kadota K

PROVIDER: S-EPMC1904450 | biostudies-literature | 2007 May

REPOSITORIES: biostudies-literature

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Publications

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data.

Kadota Koji K Araki Ryoko R Nakai Yuji Y Abe Masumi M

Algorithms for molecular biology : AMB 20070530

<h4>Background</h4>One-dimensional (1-D) electrophoretic data obtained using the cDNA-AFLP method have attracted great interest for the identification of differentially expressed transcript-derived fragments (TDFs). However, high-throughput analysis of the cDNA-AFLP data is currently limited by the need for labor-intensive visual evaluation of multiple electropherograms. We would like to have high-throughput ways of identifying such TDFs.<h4>Results</h4>We describe a method, GOGOT, which automat ...[more]

PMID: 17535446

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Project description:BackgroundThe oomycete Plasmopara viticola (Berk. and Curt.) Berl. and de Toni causes downy mildew in grapevine (Vitis vinifera L.). This pathogen is strictly biotrophic, thus completely dependent on living host cells for its survival. The molecular basis of compatibility and disease development in this system is poorly understood. We have carried out a large-scale cDNA-AFLP analysis to identify grapevine and P. viticola genes associated with the infection process.ResultsWe carried out cDNA-AFLP analysis on artificially infected leaves of the susceptible cultivar Riesling at the oil spot stage, on water-treated leaves and on a sample of pure sporangia as controls. Selective amplifications with 128 primer combinations allowed the visualization of about 7000 transcript-derived fragments (TDFs) in infected leaves, 1196 of which (17%) were differentially expressed. We sequenced 984 fragments, 804 of which were identified as grapevine transcripts after homology searching, while 96 were homologous to sequences in Phytophthora spp. databases and were attributed to P. viticola. There were 82 orphan TDFs. Many grapevine genes spanning almost all functional categories were downregulated during infection, especially genes involved in photosynthesis. Grapevine genes homologous to known resistance genes also tended to be repressed, as were several resistance gene analogs and carbonic anhydrase (recently implicated in pathogen resistance). In contrast, genes encoding cytoskeletal components, enzymes of the phenylpropanoid and beta-oxidation pathways, and pathogenesis related proteins were primarily upregulated during infection. The majority of P. viticola transcripts expressed in planta showed homology to genes of unknown function or to genomic Phytophthora sequences, but genes related to metabolism, energy production, transport and signal transduction were also identified.ConclusionThis study provides the first global catalogue of grapevine and P. viticola genes expressed during infection, together with their functional annotations. This will help to elucidate the molecular basis of the infection process and identify genes and chemicals that could help to inhibit the pathogen.

Project description:BackgroundcDNA-AFLP is a transcriptomics technique which does not require prior sequence information and can therefore be used as a gene discovery tool. The method is based on selective amplification of cDNA fragments generated by restriction endonucleases, electrophoretic separation of the products and comparison of the band patterns between treated samples and controls. Unequal distribution of restriction sites used to generate cDNA fragments negatively affects the performance of cDNA-AFLP. Some transcripts are represented by more than one fragment while other escape detection, causing redundancy and reducing the coverage of the analysis, respectively.ResultsWith the goal of improving the coverage of cDNA-AFLP without increasing its redundancy, we designed a modified cDNA-AFLP protocol. Immobilized cDNA is sequentially digested with several restriction endonucleases and the released DNA fragments are collected in mutually exclusive pools. To investigate the performance of the protocol, software tool MECS (Multiple Enzyme cDNA-AFLP Simulation) was written in Perl. cDNA-AFLP protocols described in the literature and the new sequential digestion protocol were simulated on sets of cDNA sequences from mouse, human and Arabidopsis thaliana. The redundancy and coverage, the total number of PCR reactions, and the average fragment length were calculated for each protocol and cDNA set.ConclusionSimulation revealed that sequential digestion of immobilized cDNA followed by the partitioning of released fragments into mutually exclusive pools outperformed other cDNA-AFLP protocols in terms of coverage, redundancy, fragment length, and the total number of PCRs. Primers generating 30 to 70 amplicons per PCR provided the highest fraction of electrophoretically distinguishable fragments suitable for normalization. For A. thaliana, human and mice transcriptome, the use of two marking enzymes and three sequentially applied releasing enzymes for each of the marking enzymes is recommended.

Dataset Information

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data.

Background

Results

Conclusion

Publications

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data.

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