Signal Sequence and Keyword Trap in silico for Selection of Full-Length Human cDNAs Encoding Secretion or Membrane Proteins from Oligo-Capped cDNA Libraries

We have developed an in silico method of selection of humanfull-length cDNAs encoding secretion or membrane proteins fromoligo-capped cDNA libraries. Fullness rates were increased toabout 80% by combination of the oligo-capping method and ATGpr,software for prediction of translation start point and the codingpotential. Then, using 5'-end single-pass sequences, cDNAs havingthe signal sequence were selected by PSORT (‘signal sequencetrap’). We also applied ‘secretion or membrane protein-relatedkeyword trap’ based on the result of BLAST search againstthe SWISS-PROT database for the cDNAs which could not be selectedby PSORT. Using the above procedures, 789 cDNAs were primarilyselected and subjected to full-length sequencing, and 334 ofthese cDNAs were finally selected as novel. Most of the cDNAs(295 cDNAs: 88.3%) were predicted to encode secretion or membraneproteins. In particular, 165(80.5%) of the 205 cDNAs selectedby PSORT were predicted to have signal sequences, while 70 (54.2%)of the 129 cDNAs selected by ‘keyword trap’ preservedthe secretion or membrane protein-related keywords. Many importantcDNAs were obtained, including transporters, receptors, andligands, involved in significant cellular functions. Thus, anefficient method of selecting secretion or membrane protein-encodingcDNAs was developed by combining the above four procedures.