Ansgar GruberBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Cedar McKaySchool of Oceanography, University of Washington, Gabrielle RocapSchool of Oceanography, University of Washington, Miroslav OborníkBiology Centre, Institute of Parasitology, Czech Academy of SciencesUniversity of South Bohemia
{"title":"不同版本的SignalP和TargetP在硅藻质体蛋白预测中的ASAFind比较","authors":"Ansgar GruberBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Cedar McKaySchool of Oceanography, University of Washington, Gabrielle RocapSchool of Oceanography, University of Washington, Miroslav OborníkBiology Centre, Institute of Parasitology, Czech Academy of SciencesUniversity of South Bohemia","doi":"arxiv-2303.02509","DOIUrl":null,"url":null,"abstract":"Plastid targeted proteins of diatoms and related algae can be predicted with\nhigh sensitivity and specificity using the ASAFind method published in 2015.\nASAFind predictions rely on SignalP predictions of endoplasmic reticulum (ER)\ntargeting signal peptides. Recently (in 2019), a new version of SignalP was\nreleased, SignalP 5.0. We tested the ability of SignalP 5.0 to recognize signal\npeptides of nucleus-encoded, plastid-targeted diatom pre-proteins, and to\nidentify the signal peptide cleavage site. The results were compared to manual\npredictions of the characteristic cleavage site motif, and to previous versions\nof SignalP. SignalP 5.0 is less sensitive than the previous versions of SignalP\nin this specific task, and also in the detection of signal peptides of\nnon-plastid proteins in diatoms. However, in combination with ASAFind, the\nresulting prediction performance for plastid proteins is high. In addition, we\ntested the multi-location prediction tool TargetP for its suitability to\nprovide signal peptide information to ASAFind. The newest version, TargetP 2.0,\nhad the highest prediction performances for diatom signal peptides and\nmitochondrial transit peptides compared to other versions of SignalP and\nTargetP, thus it provides a good basis for ASAFind predictions.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"22 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of different versions of SignalP and TargetP for diatom plastid protein predictions with ASAFind\",\"authors\":\"Ansgar GruberBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Cedar McKaySchool of Oceanography, University of Washington, Gabrielle RocapSchool of Oceanography, University of Washington, Miroslav OborníkBiology Centre, Institute of Parasitology, Czech Academy of SciencesUniversity of South Bohemia\",\"doi\":\"arxiv-2303.02509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plastid targeted proteins of diatoms and related algae can be predicted with\\nhigh sensitivity and specificity using the ASAFind method published in 2015.\\nASAFind predictions rely on SignalP predictions of endoplasmic reticulum (ER)\\ntargeting signal peptides. Recently (in 2019), a new version of SignalP was\\nreleased, SignalP 5.0. We tested the ability of SignalP 5.0 to recognize signal\\npeptides of nucleus-encoded, plastid-targeted diatom pre-proteins, and to\\nidentify the signal peptide cleavage site. The results were compared to manual\\npredictions of the characteristic cleavage site motif, and to previous versions\\nof SignalP. SignalP 5.0 is less sensitive than the previous versions of SignalP\\nin this specific task, and also in the detection of signal peptides of\\nnon-plastid proteins in diatoms. However, in combination with ASAFind, the\\nresulting prediction performance for plastid proteins is high. In addition, we\\ntested the multi-location prediction tool TargetP for its suitability to\\nprovide signal peptide information to ASAFind. The newest version, TargetP 2.0,\\nhad the highest prediction performances for diatom signal peptides and\\nmitochondrial transit peptides compared to other versions of SignalP and\\nTargetP, thus it provides a good basis for ASAFind predictions.\",\"PeriodicalId\":501170,\"journal\":{\"name\":\"arXiv - QuanBio - Subcellular Processes\",\"volume\":\"22 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Subcellular Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2303.02509\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Subcellular Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2303.02509","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of different versions of SignalP and TargetP for diatom plastid protein predictions with ASAFind
Plastid targeted proteins of diatoms and related algae can be predicted with
high sensitivity and specificity using the ASAFind method published in 2015.
ASAFind predictions rely on SignalP predictions of endoplasmic reticulum (ER)
targeting signal peptides. Recently (in 2019), a new version of SignalP was
released, SignalP 5.0. We tested the ability of SignalP 5.0 to recognize signal
peptides of nucleus-encoded, plastid-targeted diatom pre-proteins, and to
identify the signal peptide cleavage site. The results were compared to manual
predictions of the characteristic cleavage site motif, and to previous versions
of SignalP. SignalP 5.0 is less sensitive than the previous versions of SignalP
in this specific task, and also in the detection of signal peptides of
non-plastid proteins in diatoms. However, in combination with ASAFind, the
resulting prediction performance for plastid proteins is high. In addition, we
tested the multi-location prediction tool TargetP for its suitability to
provide signal peptide information to ASAFind. The newest version, TargetP 2.0,
had the highest prediction performances for diatom signal peptides and
mitochondrial transit peptides compared to other versions of SignalP and
TargetP, thus it provides a good basis for ASAFind predictions.