COMPUTER GENE-MAPPING BY EAGI-BASED STSS

The rapid pace at which the human genome project has proceeded has gre atly benefited from two classes of short sequence tags, genomic (STS) and transcribed (EST), which are listed in two separate databases. Usu ally, STSs are random genomic sequences derived only for mapping purpo ses, while ESTs represent transcribed sequences that have to be mapped one by one. Here, we propose a way of establishing links between thes e two sets of sequences, allowing the automatic mapping of EST sequenc es by simple comparison with relatively nonrandom STSs. We suggest tha t EagI-based STSs derived by selected genomic portions organized in YA C contigs can automatically finely map a relevant portion of the ESTs, partially bridging the gap between the two sets of sequences and savi ng a great amount of time in mapping efforts. To test this principle, we have selected 330 high-quality STSs derived from the Xq24-qter regi on and used them for transcript searches by comparing them to the EST as well as to the nonredundant database. This search detected four kno wn genes and two additional EST clones. In contrast, when the same dat abases were searched with a set of 53 sequences derived from the same chromosomal region around EagI sites, 7 known genes and 6 additional E STs were found. These findings, together with data obtained from simul ation analysis on long sequences in the same chromosomal region, sugge st that EagI-based STSs can partially bridge the gap between STSs and ESTs. (C) 1996 Academic Press, Inc.