A new computational tool developed by researchers at the Genome Institute of Singapore (GIS) could provide a significant boost to genome study.
The tool could enable a more streamlined process for reconstructing and studying genomic sequences.
The work, lead by Dr Niranjan Nagarajan, Assistant Director of Computational and Mathematical Biology at the GIS, was reported in the November 2011 issue of the Journal of Computational Biology
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 reported here represents the first algorithmic solution for genome assembly that provides a quality guarantee and scales to large datasets.
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. Improved assembly tools thus serve to generate the most complete and accurate draft genomes that can be reconstructed from the data, avoiding mis-assembly related dead-ends for downstream research as well as minimizing the painstaking effort needed to refine and correct a draft assembly.
"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 optimization function and an exact algorithm derived from a parametric complexity analysis in providing a robust solution to a seemingly intractable problem."
Mihai Pop, Associate Prof, Department of Computer Science; and Interim Director, Center for Bioinformatics and Computational Biology at the University of Maryland said: "Opera is an important advance in genome assembly algorithms - currently it is the best stand-alone genome scaffolder available in the community. In Opera, Dr Nagarajan's team has introduced a rigorous theoretical framework for genome scaffolding as well as a practical implementation that achieves remarkable performance. These results are impressive given the substantial research in the field over the past 30 years, as well as the numerous developments spurred in recent years by advances in sequencing technologies."