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Unraveling the DNA methylation landscape in dog blood across breeds

Authors :
Miyuki Nakamura
Yuki Matsumoto
Keiji Yasuda
Masatoshi Nagata
Ryo Nakaki
Masahiro Okumura
Jumpei Yamazaki
Source :
BMC Genomics, Vol 25, Iss 1, Pp 1-15 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background DNA methylation is a covalent bond modification that is observed mainly at cytosine bases in the context of CG pairs. DNA methylation patterns reflect the status of individual tissues, such as cell composition, age, and the local environment, in mammals. Genetic factors also impact DNA methylation, and the genetic diversity among various dog breeds provides a valuable platform for exploring this topic. Compared to those in the human genome, studies on the profiling of methylation in the dog genome have been less comprehensive. Results Our study provides extensive profiling of DNA methylation in the whole blood of three dog breeds using whole-genome bisulfite sequencing. The difference in DNA methylation between breeds was moderate after removing CpGs overlapping with potential genetic variation. However, variance in methylation between individuals was common and often occurred in promoters and CpG islands (CGIs). Moreover, we adopted contextual awareness methodology to characterize DNA primary sequences using natural language processing (NLP). This method could be used to effectively separate unmethylated CGIs from highly methylated CGIs in the sequences that are identified by the conventional criteria. Conclusions This study presents a comprehensive DNA methylation landscape in the dog blood. Our observations reveal the similar methylation patterns across dog breeds, while CGI regions showed high variations in DNA methylation level between individuals. Our study also highlights the potential of NLP approach for analyzing low-complexity DNA sequences, such as CGIs.

Details

Language :
English
ISSN :
14712164 and 04149289
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.9b22f832d04149289f0f267cf2297dd5
Document Type :
article
Full Text :
https://doi.org/10.1186/s12864-024-10963-2