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An integrated approach for the systematic identification and characterization of heart-enriched genes with unknown functions
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| Zeitschriftentitel: | BMC Genomics |
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| Personen und Körperschaften: | , , , , , , , , |
| In: | BMC Genomics, 10, 2009, 1 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Springer Science and Business Media LLC
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| Schlagwörter: |
| Zusammenfassung: | <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>High throughput techniques have generated a huge set of biological data, which are deposited in various databases. Efficient exploitation of these databases is often hampered by a lack of appropriate tools, which allow easy and reliable identification of genes that miss functional characterization but are correlated with specific biological conditions (e.g. organotypic expression).</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>We have developed a simple algorithm (DGSA = <jats:underline>D</jats:underline> atabase-dependent <jats:underline>G</jats:underline> ene <jats:underline>S</jats:underline> election and <jats:underline>A</jats:underline> nalysis) to identify genes with unknown functions involved in organ development concentrating on the heart. Using our approach, we identified a large number of yet uncharacterized genes, which are expressed during heart development. An initial functional characterization of genes by loss-of-function analysis employing morpholino injections into zebrafish embryos disclosed severe developmental defects indicating a decisive function of selected genes for developmental processes.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion</jats:title> <jats:p>We conclude that DGSA is a versatile tool for database mining allowing efficient selection of uncharacterized genes for functional analysis.</jats:p> </jats:sec> |
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| ISSN: |
1471-2164
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| DOI: | 10.1186/1471-2164-10-100 |