From sequence to phenotype: functional genomics of<i>Phytophthora</i>

Kamoun, Sophien; Dong, Shengli; Hamada, Walid; Huitema, Edgar; Kinney, Douglas; Morgan, William R.; Styer, Allison; Testa, Antonino; Torto, Trudy A.

doi:10.1080/07060660109506963

Cited by 19 publications

(12 citation statements)

References 15 publications

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“…Recent analyses of entire yeast genome databases have included identification of GPI‐anchored proteins in S. cerevisiae (Caro et al , 1997), a comprehensive BLAST analysis of C. albicans homologues of S. cerevisiae sexual cycle genes (Tzung et al , 2001) and a prediction of the subcellular localization of the entire S. cerevisiae proteome (Kumar et al , 2002). Thus, one approach to rapidly analyse an entire genome is to utilize database information and computer‐based algorithms to predict structure and/or function (Tjalsma et al , 2000; Kamoun et al , 2001).…”

Section: Introductionmentioning

confidence: 99%

An analysis of the Candida albicans genome database for soluble secreted proteins using computer‐based prediction algorithms

Lee

Wormsley

Kamoun

et al. 2003

Yeast

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We sought to identify all genes in the Candida albicans genome database whose deduced proteins would likely be soluble secreted proteins (the secretome). While certain C. albicans secretory proteins have been studied in detail, more data on the entire secretome is needed. One approach to rapidly predict the functions of an entire proteome is to utilize genomic database information and prediction algorithms. Thus, we used a set of prediction algorithms to computationally define a potential C. albicans secretome. We first assembled a validation set of 47 C. albicans proteins that are known to be secreted and 47 that are known not to be secreted. The presence or absence of an N-terminal signal peptide was correctly predicted by SignalP version 2.0 in 47 of 47 known secreted proteins and in 47 of 47 known nonsecreted proteins. When all 6165 C. albicans ORFs from CandidaDB were analysed with SignalP, 495 ORFs were predicted to encode proteins with N-terminal signal peptides. In the set of 495 deduced proteins with N-terminal signal peptides, 350 were predicted to have no transmembrane domains (or a single transmembrane domain at the extreme N-terminus) and 300 of these were predicted not to be GPI-anchored. TargetP was used to eliminate proteins with mitochondrial targeting signals, and the final computationally-predicted C. albicans secretome was estimated to consist of up to 283 ORFs. The C. albicans secretome database is available at http://info.med.yale.edu/intmed/infdis/candida/

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Section: Introductionmentioning

confidence: 99%

An analysis of the Candida albicans genome database for soluble secreted proteins using computer‐based prediction algorithms

Lee

Wormsley

Kamoun

et al. 2003

Yeast

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show abstract

“…This includes an algorithm, PexFinder, that identifies genes encoding extracellular proteins from ESTs (T. Torto, A. Styer, and S. Kamoun, submitted for publication; http://www.oardc.ohio-state.edu /phytophthora/pexfinder). Rapid assays for testing Phytophthora genes in planta for virulence function are well established and are being applied to validate candidate genes (40,41,79). A database, the Phytophthora Functional Genomics Database (PFGD), that combines functional assays and expression data with transcript analysis and annotation has recently been funded by the National Science Foundation Plant Genome Program and will be available online at http://www .pfgd.org (M. E. Waugh, personal communication) .…”

Section: Molecular and Genomic Resourcesmentioning

confidence: 99%

“…Structural genomic projects are well under way for P. infestans, P. sojae, and P. brassicae (4,40,42,50,78,99,113) (Table 2). The resources generated through these projects consist mainly of tens of thousands of ESTs from a variety of developmental and infection stages.…”

Section: Molecular and Genomic Resourcesmentioning

confidence: 99%

“…For example, computational tools and algorithms have been developed to mine sequence data sets for genes predicted to function in virulence and host-specificity or to form targets for chemical control (40). This includes an algorithm, PexFinder, that identifies genes encoding extracellular proteins from ESTs (T. Torto, A. Styer, and S. Kamoun, submitted for publication; http://www.oardc.ohio-state.edu /phytophthora/pexfinder).…”

Section: Molecular and Genomic Resourcesmentioning

confidence: 99%

“…With the availability of large EST data sets, the community investigating Phytophthora has embarked on functional genomic analyses (4,40,79). For example, computational tools and algorithms have been developed to mine sequence data sets for genes predicted to function in virulence and host-specificity or to form targets for chemical control (40).…”

Section: Molecular and Genomic Resourcesmentioning

confidence: 99%

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