Title

Cross chromosomal similarity for DNA sequence compression

Authors

Choi-Ping Paula Wu^{1, *}, Ngai-Fong Law¹ and Wan-Chi Siu¹

Affiliation

¹Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University

Email

paul.a@polyu.edu.hk; * Corresponding author

Article Type

Hypothesis

Date

received May 30, 2008; revised June 27, 2008; accepted July 06, 2008; published July 14, 2008

Abstract

Current DNA compression algorithms work by finding similar repeated regions within the DNA sequence and then encoding these regions together to achieve compression.  Our study on chromosome sequence similarity reveals that the length of similar repeated regions within one chromosome is about 4.5% of the total sequence length. The compression gain is often not high because of these short lengths.  It is well known that similarity exist among different regions of chromosome sequences.  This implies that similar repeated sequences are found among different regions of chromosome sequences. Here, we study cross-chromosomal similarity for DNA sequence compression. The length and location of similar repeated regions among the sixteen chromosomes of S. cerevisiae are studied. It is found that the average percentage of similar subsequences found between two chromosome sequences is about 10% in which 8% comes from cross-chromosomal prediction and 2% from self-chromosomal prediction. The percentage of similar subsequences is about 18% in which only 1.2% comes from self-chromosomal prediction while the rest is from cross-chromosomal prediction among the 16 chromosomes studied.  This suggests the importance of cross-chromosomal similarities in addition to self-chromosomal similarities in DNA sequence compression. An additional 23% of storage space could be reduced on average using self-chromosomal and cross-chromosomal predictions in compressing the 16 chromosomes of S. cerevisiae.

Keywords

DNA; sequence; chromosome; prediction; S. cerevisiae

Citation

Wu et al., Bioinformation 2(9): 412-416 (2008)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.