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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Casboundary: automated definition of integral Cas cassettes

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Author(s):
Padilha, Victor A. [1] ; Alkhnbashi, Omer S. [2] ; Tran, Van Dinh [2] ; Shah, Shiraz A. [3] ; Carvalho, Andre C. P. L. F. [1] ; Backofen, Rolf [2, 4, 5]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Freiburg, Dept Comp Sci, Bioinformat Grp, D-79110 Freiburg - Germany
[3] Copenhagen Univ Hosp Herlev & Gentofte, COPSAC, DK-2820 Gentofte - Denmark
[4] Univ Freiburg, Signalling Res Ctr BIOSS, D-79104 Freiburg - Germany
[5] Univ Freiburg, CIBSS, D-79104 Freiburg - Germany
Total Affiliations: 5
Document type: Journal article
Source: Bioinformatics; v. 37, n. 10, p. 1352-1359, MAY 15 2021.
Web of Science Citations: 1
Abstract

Motivation: CRISPR-Cas are important systems found in most archaeal and many bacterial genomes, providing adaptive immunity against mobile genetic elements in prokaryotes. The CRISPR-Cas systems are encoded by a set of consecutive cas genes, here termed cassette. The identification of cassette boundaries is key for finding cassettes in CRISPR research field. This is often carried out by using Hidden Markov Models and manual annotation. In this article, we propose the first method able to automatically define the cassette boundaries. In addition, we present a Cas-type predictive model used by the method to assign each gene located in the region defined by a cassette's boundaries a Cas label from a set of pre-defined Cas types. Furthermore, the proposed method can detect potentially new cas genes and decompose a cassette into its modules. Results: We evaluate the predictive performance of our proposed method on data collected from the two most recent CRISPR classification studies. In our experiments, we obtain an average similarity of 0.86 between the predicted and expected cassettes. Besides, we achieve F-scores above 0.9 for the classification of cas genes of known types and 0.73 for the unknown ones. Finally, we conduct two additional study cases, where we investigate the occurrence of potentially new cas genes and the occurrence of module exchange between different genomes. (AU)

FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 19/21300-9 - Machine learning tools for bioinformatics problems
Grantee:Victor Alexandre Padilha
Support Opportunities: Scholarships in Brazil - Doctorate