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  • GENOME SEQUENCE  (2)
  • 1
    Keywords: APOPTOSIS ; CELLS ; GROWTH ; SURVIVAL ; CELL ; GENE ; GENES ; GENOME ; GENOME SEQUENCE ; PROTEIN ; RNA ; CULTURED-CELLS ; SEQUENCE ; SEQUENCES ; CELL-SURVIVAL ; MUTANT ; IDENTIFICATION ; ASSAY ; Drosophila ; NUMBER ; leukemia ; DATABASE ; PHENOTYPE ; acute myeloid leukemia ; CELL-GROWTH ; ALLELE ; CELL-VIABILITY ; ELEGANS ; INTERFERENCE ; SCALE
    Abstract: A crucial aim upon completion of whole genome sequences is the functional analysis of all predicted genes. We have applied a high-throughput RNA-interference (RNAi) screen of 19,470 double-stranded (ds) RNAs in cultured cells to characterize the function of nearly all (91%) predicted Drosophila genes in cell growth and viability. We found 438 dsRNAs that identified essential genes, among which 80% lacked mutant alleles. A quantitative assay of cell number was applied to identify genes of known and uncharacterized functions. In particular, we demonstrate a role for the homolog of a mammalian acute myeloid leukemia gene (AML1) in cell survival. Such a systematic screen for cell phenotypes, such as cell viability, can thus be effective in characterizing functionally related genes on a genome-wide scale
    Type of Publication: Journal article published
    PubMed ID: 14764878
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  • 2
    Keywords: AB-INITIO ; EXPRESSION ; COMBINATION ; evaluation ; Germany ; human ; GENE ; GENES ; GENOME ; GENOME SEQUENCE ; HYBRIDIZATION ; microarray ; PROTEIN ; transcription ; validation ; DNA ; FAMILY ; PROTEIN FAMILIES ; PROTEIN FAMILY ; BIOLOGY ; SEQUENCE ; SEQUENCES ; DISCOVERY ; IDENTIFICATION ; IN-SITU ; DESIGN ; Drosophila ; DROSOPHILA-MELANOGASTER ; MELANOGASTER ; NUMBER ; DATABASE ; HUMAN GENOME ; RT-PCR ; PREDICTION ; MICROARRAY ANALYSIS ; PROJECT ; max ; RESOURCE ; ANOPHELES-GAMBIAE ; SYSTERS
    Abstract: Background: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software.Results: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly.Conclusions: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species
    Type of Publication: Journal article published
    PubMed ID: 14709175
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