PhyEffector, the First Algorithm That Identifies Classical and Non-Classical Effectors in Phytoplasmas
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Published:2023-11-17
Issue:7
Volume:8
Page:550
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ISSN:2313-7673
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Container-title:Biomimetics
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language:en
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Short-container-title:Biomimetics
Author:
Carreón-Anguiano Karla Gisel1ORCID, Vila-Luna Sara Elena1, Sáenz-Carbonell Luis1, Canto-Canche Blondy1ORCID
Affiliation:
1. Unidad de Biotecnología, Centro de Investigación Científica de Yucatán, A.C., Calle 43 No. 130 x 32 y 34, Colonia Chuburná de Hidalgo, Mérida C.P. 97205, Yucatán, Mexico
Abstract
Phytoplasmas are the causal agents of more than 100 plant diseases in economically important crops. Eleven genomes have been fully sequenced and have allowed us to gain a better understanding of the biology and evolution of phytoplasmas. Effectors are key players in pathogenicity and virulence, and their identification and description are becoming an essential practice in the description of phytoplasma genomes. This is of particular importance because effectors are possible candidates for the development of new strategies for the control of plant diseases. To date, the prediction of effectors in phytoplasmas has been a great challenge; the reliable comparison of effectoromes has been hindered because research teams have used the combination of different programs in their predictions. This is not trivial since significant differences in the results can arise, depending on the predictive pipeline used. Here, we tested different predictive pipelines to create the PhyEffector algorithm; the average value of the F1 score for PhyEffector was 0.9761 when applied to different databases or genomes, demonstrating its robustness as a predictive tool. PhyEffector can recover both classical and non-classical phytoplasma effectors, making it an invaluable tool to accelerate effectoromics in phytoplasmas.
Funder
Consejo Nacional de Humanidades, Ciencias y Tecnologías
Subject
Molecular Medicine,Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biotechnology
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