Construction of a facsimile data set for large genome sequence analysis.
A test was devised for exploring the question of whether it will be possible to identify genes in large-scale genome studies solely by sequence comparison with current sequence collections. To this end, a facsimile data set was constructed by dividing GenBank Release 56 randomly into two halves, one to serve as a reference set and the other intended to simulate raw data anticipated from large genome sequence projects. All supplementary information and identifying marks were removed from the test set after assignment of random identification numbers to each entry and their encryption. Because noncoding intervening sequences (introns) are underrepresented in GenBank, a program that introduced (simulated) introns into mRNA and prokaryotic sequences was devised. In a further attempt to make the problem of identification more realistic, random base substitutions and single-base deletions were also incorporated. The randomly ordered entries were concatenated, along with random intergenic flanking sequences, into a single long "chromosome" 33 Mb in length and then cut into "cosmids" 50-100 kb long. The chopping process was conducted in such a way that terminal overlaps would allow the order of the entries in the chromosome to be reconstituted. Finally, the sequences of a substantial fraction of the cosmids were converted to their complements. Preliminary searching of 10 test cosmids revealed that more than two-thirds of the entries in the test set should be readily identifiable by type of gene product solely on the basis of comparison with the reference set. These preliminary results suggest that existing computer regimens and sequence collections would be able to identify the majority of eukaryotic genes in any new raw data set, the existence of introns not withstanding. Moreover, the analysis can be conducted in pace with the data collection so that the search results and summary identifications will be instantly available to the research community at large.
Seely
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Center for Molecular Genetics, University of California, San Diego, La Jolla 92093.
Feng
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DF
Smith
D W
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Sulzbach
D
D
Doolittle
R F
RF
D000818:Animals; D003198:Computer Simulation; D003360:Cosmids; D004247:DNA; D001330:Electronic Data Processing; D015723:Gene Library; D015894:Genome, Human; D006801:Humans; D007438:Introns; D008969:Molecular Sequence Data; D011897:Random Allocation; D016415:Sequence Alignment; D014584:User-Computer Interface
D004247:DNA