Dataset Information

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

ABSTRACT: BACKGROUND: Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies. RESULTS: We have developed a web-based software resource, called CROPPER that uses the latest genomic information concerning different data identifiers and orthologous genes from the Ensembl database. CROPPER can be used to combine genomic data from different heterogeneous sources, allowing researchers to perform cross-platform/cross-species compendium studies without the need for complex computational tools or the requirement of setting up one's own in-house database. We also present an example of a simple cross-platform/cross-species compendium study based on publicly available Parkinson's disease data derived from different sources. CONCLUSION: CROPPER is a user-friendly and freely available web-based software resource that can be successfully used for cross-species/cross-platform compendium studies.

SUBMITTER: Paananen J

PROVIDER: S-EPMC1592126 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

Paananen Jussi J Storvik Markus M Wong Garry G

BMC bioinformatics 20060922

<h4>Background</h4>Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our ai ...[more]

PMID: 16995941

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Project description:BACKGROUND: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models (e.g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles. RESULTS: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model. CONCLUSION: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Project description:Cotton is cultivated worldwide for its white fiber, of which around 90% is tetraploid upland cotton (Gossypium hirsutum L.) carrying both A and D genome. Since centuries, yield increasing efforts for the cotton crop by conventional breeding approaches have caused an extensive erosion of natural genetic variability. Mutation based improvement strategies provide an effective way of creating new allelic variations. Targeting Induced Local Lesions IN Genomes (TILLING) provides a mutation based reverse genetic strategy to create and evaluate induced genetic variability at DNA level. Here, we report development and testing of TILLING populations of allotetraploid cotton (G. hirsutum) for functional genomic studies and mutation based enrichment of cotton genetic resources. Seed of two cotton cultivars "PB-899 and PB-900" were mutagenized with 0.3 and 0.2% (v/v) ethyl methanesulfonate, respectively. The phenotyping of M1 and M2 populations presented numerous mutants regarding the branching pattern, leaf morphology, disease resistance, photosynthetic lesions and flower sterility. Molecular screening for point mutations was performed by TILLING PCR aided CEL1 mismatch cleavage. To estimate the mutation frequency in the mutant genomes, five gene classes were TILLed in 8000 M2 plants of each var. "PB-899" and "PB-900." These include actin (GhACT), Pectin Methyl Esterase (GhPME), sucrose synthase (GhSUS), resistance gene analog, and defense response gene (DRGs). The var. PB-899 was harboring 47% higher mutation induction rate than PB-900. The highest rate of mutation frequency was identified for NAC-TF5 (EU706348) of DRGs class, ranging from 1/58 kb in PB-899 to 1/105 kb in PB-900. The mutation screening assay revealed the presence of significant proportion of induced mutations in cotton TILLING populations such as 1/153 kb and 1/326 kb in var. "PB-899" and "PB-900," respectively. The establishment of a cotton TILLING platform (COTIP) and data obtained from the resource TILLING population suggest its effectiveness in widening the genetic bases of cotton for improvement and utilizing it for subsequent reverse genetic studies of various genes.

Dataset Information

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

Publications

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

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