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GenomeRNAi: a database for cell-based RNAi phenotypes.

Thomas Horn1, Zeynep Arziman, Juerg Berger

  • 1German Cancer Research Center, Boveri-Group Signaling and Functional Genomics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany.

Nucleic Acids Research
|December 1, 2006
PubMed
Summary
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RNA interference (RNAi) screens enable systematic genetic studies by analyzing loss-of-function phenotypes across genomes. The GenomeRNAi database integrates these RNAi data for enhanced functional annotation and discovery.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • RNA interference (RNAi) is a key technology for generating gene loss-of-function phenotypes.
  • Annotated genomes facilitate systematic genetic screens for nearly all genes.
  • Large datasets of RNAi-induced phenotypes present challenges in systematic integration and functional annotation.

Purpose of the Study:

  • To present the GenomeRNAi database as a resource for accessing and integrating published RNAi phenotypes.
  • To facilitate functional annotation by mapping RNAi phenotypes to genomic loci.
  • To provide access to RNAi probe sequences used in various screens.

Main Methods:

  • Genome-wide RNAi screens were performed in Caenorhabditis elegans and Drosophila.
  • Data integration involved mapping phenotypes to genomic loci and identifying potential non-specific regions.

Related Experiment Videos

  • The GenomeRNAi database was developed for searching by phenotype, gene, RNAi probe, or sequence.

    • Main Results:

    • The GenomeRNAi database consolidates RNAi phenotypes from cell-based screens.
    • Phenotypes are mapped to genomic locations, including non-specific regions.
    • Sequence information for RNAi probes is accessible.

    Conclusions:

    • The GenomeRNAi database serves as a valuable resource for functional genomics research.
    • It enables systematic integration and annotation of RNAi-derived functional information.
    • Facilitates cross-species functional annotation and discovery through comprehensive RNAi data.