Structural representations of DNA regulatory substrates can enhance sequence-based algorithms by associating functional sequence variants
Paper in proceeding, 2020

The nucleotide sequence representation of DNA can be inadequate for resolving protein-DNA binding sites and regulatory substrates, such as those involved in gene expression and horizontal gene transfer. Considering that sequence-like representations are algorithmically very useful, here we fused over 60 currently available DNA physicochemical and conformational variables into compact structural representations that can encode single DNA binding sites to whole regulatory regions. We find that the main structural components reflect key properties of protein-DNA interactions and can be condensed to the amount of information found in a single nucleotide position. The most accurate structural representations compress functional DNA sequence variants by 30% to 50%, as each instance encodes from tens to thousands of sequences. We show that a structural distance function discriminates among groups of DNA substrates more accurately than nucleotide sequence-based metrics. As this opens up a variety of implementation possibilities, we develop and test a distance-based alignment algorithm, demonstrating the potential of using the structural representations to enhance sequence-based algorithms. Due to the bias of most current bioinformatic methods to nucleotide sequence representations, it is possible that considerable performance increases might still be achievable with such solutions.

Bio-Algorithms

DNA structural properties

Regulatory genomics

Author

Jan Zrimec

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2020

Vol. 21 September 2020
9781450379649 (ISBN)

11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2020
Virtual; online, USA,

Subject Categories

Biochemistry and Molecular Biology

Biophysics

Bioinformatics and Systems Biology

DOI

10.1145/3388440.3412482

More information

Latest update

1/5/2021 2