DISCRIMINATION OF CODING FROM NON-CODING REGIONS IN CATTLE BASED ON METHYLATION AND DEAMINATION PATTERNS

NITIN VARSHNEY¹*, A.K. PAUL², S.D. WAHI^3
1ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, 110012
²ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, 110012
³ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, 110012
* Corresponding Author : jadamprakash@gmail.com

Received : 01-08-2017     Accepted : 06-08-2017     Published : 28-08-2017
Volume : 9     Issue : 8       Pages : 291 - 295
Genetics 9.8 (2017):291-295

Keywords : Coding and noncoding regions, DNA methylation, Epigenetic mechanism, Content sensors
Academic Editor : Prof Ramesh S. Bhat
Conflict of Interest : None declared
Acknowledgements/Funding : This research work was conducted as the Post-Graduation dissertation. All the laboratory facility and software were provided by ICAR-Indian Agricultural Statistical Research Institute, New Delhi, is thankfully acknowledged
Author Contribution : All author equally contributed

Coding regions (CDS) are the part of DNA that helps in protein synthesis and non-coding region (Introns) do not code for proteins. So, discrimination of coding region from the non-coding region is of prime importance for genome annotation. In this study discrimination of Coding and Non-coding regions of cattle genome has been done based on epigenetic mechanism. The features of DNA methylation and spontaneous deamination were used in this approach. Five different indices namely Deviation of nucleotide (NUF), Deviation of dinucleotide (DNF), Intensity of methylation (IME), Triplet avoidance index (TAI), and Tendency of Poly-purine and Poly-pyrimidine (PPI) have been used in this study. These indices were used to encode exon and intron sequences. The proposed method has been compared with the methods based on LDA (Linear Discriminant Analysis) and QDA (Quadratic Discriminant Analysis) based on the area under the ROC (Receiver Operating Characteristic) and the PR (Precision Recall) curves, whereby the proposed method proved to be better as compared to LDA and QDA based methods

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As per corresponding author and all coauthors email request, and NOC by all coauthors - following author names were retracted from article - P.K. MEHER, A.R. RAO