Washington: An Indian-origin researcher-led team has for the first time developed a computational tool which it claims can help experts assemble DNA sequences more accurately.
Dr Niranjan Nagarajan and colleagues at the Genome Institute of Singapore says its computational tool comes with a guarantee on its reliability when reconstructing the DNA sequence of organisms, enabling a more streamlined process for analysing genomic sequences.
The genomic study of life (plants and animals alike) is based on computational tools that can first piece together the DNA sequence of these organisms, a process called genome assembly, that is similar to solving a giant puzzle or putting together the words in a book from a shredded copy.
Due to the sheer scale of this challenge, existing approaches for genome assembly rely on heuristics and often result in incorrect reconstructions of the genome. The work represents the first algorithmic solution for genome assembly that provides a quality guarantee and scales to large data.
The assembled genome of an organism forms the basis for a range of downstream biological investigations and serves as a critical resource for the research community.
The draft human genome, for example, was obtained at the expense of billions of dollars, serves as a fundamental resource for biomedical research and is, in fact, still being refined, say the scientists.
"Genetic studies of organisms of interest for human health (such as those causing infectious diseases), agriculture, animal husbandry and other areas of the bio-economy, such as biofuels, are driven by the availability of draft genome sequences," said Dr Nagarajan.
"This research describes a novel computational approach to reconstruct more complete and accurate draft genomes. From an algorithmic perspective, Opera demonstrates the utility of a clear optimisation function and an exact algorithm derived from a parametric complexity analysis in providing a robust solution to a seemingly intractable problem," he added.
The findings have been published in the `Journal of Computational Biology`.