The secreted protein discovery initiative (SPDI), a large-scale effort to identify novel human secreted and transmembrane proteins: a bioinformatics assessment.

Hilary F Clark, Austin L Gurney, Evangeline Abaya, Kevin Baker, Daryl Baldwin, Jennifer Brush, Jian Chen, Bernard Chow, Clarissa Chui, Craig Crowley, Bridget Currell, Bethanne Deuel, Patrick Dowd, Dan Eaton, Jessica Foster, Christopher Grimaldi, Qimin Gu, Philip E Hass, Sherry Heldens, Arthur Huang, Hok Seon Kim, Laura Klimowski, Yisheng Jin, Stephanie Johnson, James Lee, Lhney Lewis, Dongzhou Liao, Melanie Mark, Edward Robbie, Celina Sanchez, Jill Schoenfeld, Somasekar Seshagiri, Laura Simmons, Jennifer Singh, Victoria Smith, Jeremy Stinson, Alicia Vagts, Richard Vandlen, Colin Watanabe, David Wieand, Kathryn Woods, Ming-Hong Xie, Daniel Yansura, Sothy Yi, Guoying Yu, Jean Yuan, Min Zhang, Zemin Zhang, Audrey Goddard, William I Wood, Paul Godowski, Alane Gray

Index: Genome Res. 13(10) , 2265-70, (2003)

Full Text: HTML

Abstract

A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.