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NYKRÝNOVÁ, M. BEZDÍČEK, M. LENGEROVÁ, M. ŠKUTKOVÁ, H.
Original Title
Bacterial phenotype prediction based on methylation site profiles
Type
conference paper
Language
English
Original Abstract
Methylated site mapping in the DNA sequences plays a key role in understanding the physiology and pathology of cells and organisms. Thanks to third-generation DNA sequencers, these epigenetic modifications can be detected already when reading genetic information. Therefore, not only genotypic classification but also phenotypic specifications can be determined based on a single sequencing run. However, for phenotyping purposes, there is still a lack of effective standardized tools to design uniform classification schemes for different laboratories. Here, we present a simple tool for comparing DNA methylation site profiles, utilizing sequencing reads mapping to the reference genome similar to core genome analysis in bacterial genotyping. The proposed pipeline maps sequence reads with marked positions of methylated bases to a single representative reference. Thus the output consists of the uniformly aligned methylated site positions in a set of bacterial genomes. This allows for the evaluation of common methylated sites across all genomes, i.e. ,,core methylome”, as well as unique methylated sites in gene and intergenic regions. Thus, determining the sequence type can be further refined by predicting bacterial behaviour such as antibiotic resistance or virulence.
Keywords
methylation; 5mC; phenotype; bacteria; nanopore sequencing
Authors
NYKRÝNOVÁ, M.; BEZDÍČEK, M.; LENGEROVÁ, M.; ŠKUTKOVÁ, H.
Released
29. 8. 2023
Publisher
IEEE
ISBN
979-8-3503-1017-7
Book
2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Pages from
1
Pages to
6
Pages count
URL
https://ieeexplore.ieee.org/document/10264900
BibTex
@inproceedings{BUT184591, author="Markéta {Jakubíčková} and Matěj {Bezdíček} and Martina {Lengerová} and Helena {Vítková}", title="Bacterial phenotype prediction based on methylation site profiles", booktitle="2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)", year="2023", pages="6", publisher="IEEE", doi="10.1109/CIBCB56990.2023.10264900", isbn="979-8-3503-1017-7", url="https://ieeexplore.ieee.org/document/10264900" }