Ansgar Gruber, Marta Vohnoutová, Cedar McKay, Gabrielle Rocap, Miroslav Oborník
{"title":"ASAFind 2.0:具有复杂质体的硅藻和藻类多类蛋白靶向预测","authors":"Ansgar Gruber, Marta Vohnoutová, Cedar McKay, Gabrielle Rocap, Miroslav Oborník","doi":"10.1111/tpj.70138","DOIUrl":null,"url":null,"abstract":"<p>Plastids of diatoms and related algae with complex plastids of red algal origin are surrounded by four membranes, which also define the periplastidic compartment (PPC), the space between the second and third membranes. Metabolic reactions as well as cell biological processes take place in the PPC; however, genome-wide predictions of the proteins targeted to this compartment were so far based on manual annotation work. Using published experimental protein localizations as reference data, we developed the first automatic prediction method for PPC proteins, which we included as a new feature in an updated version of the plastid protein predictor ASAFind. With our method, at least a subset of the PPC proteins can be predicted with high specificity, with an estimate of at least 81 proteins (0.7% of the predicted proteome) targeted to the PPC in the model diatom <i>Phaeodactylum tricornutum</i>. The proportion of PPC proteins varies, since 180 PPC proteins (1.3% of the predicted proteome) were predicted in the genome of the diatom <i>Thalassiosira pseudonana.</i> The new ASAFind version can also generate a newly designed graphical output that visualizes the contribution of each position in the sequence to the score and accepts the output of the recent versions of SignalP (5.0) and TargetP (2.0) as input data. Furthermore, we release a script to calculate custom scoring matrices that can be used for predictions in a simplified score cut-off mode. This allows for adjustments of the method to other groups of algae.</p>","PeriodicalId":233,"journal":{"name":"The Plant Journal","volume":"122 5","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/tpj.70138","citationCount":"0","resultStr":"{\"title\":\"ASAFind 2.0: multi-class protein targeting prediction for diatoms and algae with complex plastids\",\"authors\":\"Ansgar Gruber, Marta Vohnoutová, Cedar McKay, Gabrielle Rocap, Miroslav Oborník\",\"doi\":\"10.1111/tpj.70138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Plastids of diatoms and related algae with complex plastids of red algal origin are surrounded by four membranes, which also define the periplastidic compartment (PPC), the space between the second and third membranes. Metabolic reactions as well as cell biological processes take place in the PPC; however, genome-wide predictions of the proteins targeted to this compartment were so far based on manual annotation work. Using published experimental protein localizations as reference data, we developed the first automatic prediction method for PPC proteins, which we included as a new feature in an updated version of the plastid protein predictor ASAFind. With our method, at least a subset of the PPC proteins can be predicted with high specificity, with an estimate of at least 81 proteins (0.7% of the predicted proteome) targeted to the PPC in the model diatom <i>Phaeodactylum tricornutum</i>. The proportion of PPC proteins varies, since 180 PPC proteins (1.3% of the predicted proteome) were predicted in the genome of the diatom <i>Thalassiosira pseudonana.</i> The new ASAFind version can also generate a newly designed graphical output that visualizes the contribution of each position in the sequence to the score and accepts the output of the recent versions of SignalP (5.0) and TargetP (2.0) as input data. Furthermore, we release a script to calculate custom scoring matrices that can be used for predictions in a simplified score cut-off mode. 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ASAFind 2.0: multi-class protein targeting prediction for diatoms and algae with complex plastids
Plastids of diatoms and related algae with complex plastids of red algal origin are surrounded by four membranes, which also define the periplastidic compartment (PPC), the space between the second and third membranes. Metabolic reactions as well as cell biological processes take place in the PPC; however, genome-wide predictions of the proteins targeted to this compartment were so far based on manual annotation work. Using published experimental protein localizations as reference data, we developed the first automatic prediction method for PPC proteins, which we included as a new feature in an updated version of the plastid protein predictor ASAFind. With our method, at least a subset of the PPC proteins can be predicted with high specificity, with an estimate of at least 81 proteins (0.7% of the predicted proteome) targeted to the PPC in the model diatom Phaeodactylum tricornutum. The proportion of PPC proteins varies, since 180 PPC proteins (1.3% of the predicted proteome) were predicted in the genome of the diatom Thalassiosira pseudonana. The new ASAFind version can also generate a newly designed graphical output that visualizes the contribution of each position in the sequence to the score and accepts the output of the recent versions of SignalP (5.0) and TargetP (2.0) as input data. Furthermore, we release a script to calculate custom scoring matrices that can be used for predictions in a simplified score cut-off mode. This allows for adjustments of the method to other groups of algae.
期刊介绍:
Publishing the best original research papers in all key areas of modern plant biology from the world"s leading laboratories, The Plant Journal provides a dynamic forum for this ever growing international research community.
Plant science research is now at the forefront of research in the biological sciences, with breakthroughs in our understanding of fundamental processes in plants matching those in other organisms. The impact of molecular genetics and the availability of model and crop species can be seen in all aspects of plant biology. For publication in The Plant Journal the research must provide a highly significant new contribution to our understanding of plants and be of general interest to the plant science community.