Since the famous discovery of the structure of the DNA double helix, referred to as the canonical, right-handed B-form DNA by Watson and Crick, experimental evidence has revealed the existence of more than a dozen alternative (or non-B) DNA secondary structures. These include, among others, stem-loops (also known as cruciforms or hairpins), triplexes or H-DNA, quadruplexes or G4 DNA, A-DNA, and Z-DNA
The important role of DNA secondary structures in various genomic processes is documented experimentally in genomes of many organisms from bacteria to humans. It was shown that stem-loop structures can function as terminators, attenuators, promoter and recognition elements, while cruciform structures play roles in DNA replication, and genetic instability. Triplexes (H-DNA) have been shown to play roles in transcriptional repression, recombination, and genetic instability. Quadruplexes can regulate DNA replication, gene expression, and telomere maintenance. A-DNA can play an essential role in DNA packaging, and Z-DNA has been found to participate in DNA supercoiling, gene transcription, and genetic instability.
Experiments to confirm functional roles based on the actual formation of a particular structure are quite laborious and have not yet reached the level of high throughput technology. Thus, computational prediction remains the major tool to reveal genomic DNA regions with the potential to adopt non-B DNA structures. Here we launch a project with the aim to map DNA secondary structures in various genomes from bacteria to human, and assign them a potential probabilistic function based on the methods of comparative genomics, statistics, and machine learning. The computationally predicted DNA secondary structure maps could serve as a roadmap for experimentalists to target specific genomic regions while testing their hypotheses. The project will require both development of bioinformatic algorithms and experimental techniques to facilitate progress in this field.
Since the famous discovery of the structure of the DNA double helix, referred to as the canonical, right-handed B-form DNA by Watson and Crick, experimental evidence has revealed the existence of more than a dozen alternative (or non-B) DNA secondary structures. These include, among others, stem-loops (also known as cruciforms or hairpins), triplexes or H-DNA, quadruplexes or G4 DNA, A-DNA, and Z-DNA
The important role of DNA secondary structures in various genomic processes is documented experimentally in genomes of many organisms from bacteria to humans. It was shown that stem-loop structures can function as terminators, attenuators, promoter and recognition elements, while cruciform structures play roles in DNA replication, and genetic instability. Triplexes (H-DNA) have been shown to play roles in transcriptional repression, recombination, and genetic instability. Quadruplexes can regulate DNA replication, gene expression, and telomere maintenance. A-DNA can play an essential role in DNA packaging, and Z-DNA has been found to participate in DNA supercoiling, gene transcription, and genetic instability.
Experiments to confirm functional roles based on the actual formation of a particular structure are quite laborious and have not yet reached the level of high throughput technology. Thus, computational prediction remains the major tool to reveal genomic DNA regions with the potential to adopt non-B DNA structures. Here we launch a project with the aim to map DNA secondary structures in various genomes from bacteria to human, and assign them a potential probabilistic function based on the methods of comparative genomics, statistics, and machine learning. The computationally predicted DNA secondary structure maps could serve as a roadmap for experimentalists to target specific genomic regions while testing their hypotheses. The project will require both development of bioinformatic algorithms and experimental techniques to facilitate progress in this field.
