AGORA: Assembly Guided by Optical Restriction Alignment
1 Center for Bioinformatics and Computational Biology, University of Maryland-College Park, College Park, MD, USA
2 Laboratory for Molecular and Computational Genomics, University of Wisconsin-Madison, Madison, WI, USA
3 Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA
4 Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
5 Applied Mathematics and Scientific Computation Program, University of Maryland-College Park, College Park, MD, USA
6 Department of Computer Science, and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
Citation and License
BMC Bioinformatics 2012, 13:189 doi:10.1186/1471-2105-13-189Published: 2 August 2012
Genome assembly is difficult due to repeated sequences within the genome, which create ambiguities and cause the final assembly to be broken up into many separate sequences (contigs). Long range linking information, such as mate-pairs or mapping data, is necessary to help assembly software resolve repeats, thereby leading to a more complete reconstruction of genomes. Prior work has used optical maps for validating assemblies and scaffolding contigs, after an initial assembly has been produced. However, optical maps have not previously been used within the genome assembly process. Here, we use optical map information within the popular de Bruijn graph assembly paradigm to eliminate paths in the de Bruijn graph which are not consistent with the optical map and help determine the correct reconstruction of the genome.
We developed a new algorithm called AGORA: Assembly Guided by Optical Restriction Alignment. AGORA is the first algorithm to use optical map information directly within the de Bruijn graph framework to help produce an accurate assembly of a genome that is consistent with the optical map information provided. Our simulations on bacterial genomes show that AGORA is effective at producing assemblies closely matching the reference sequences.
Additionally, we show that noise in the optical map can have a strong impact on the final assembly quality for some complex genomes, and we also measure how various characteristics of the starting de Bruijn graph may impact the quality of the final assembly. Lastly, we show that a proper choice of restriction enzyme for the optical map may substantially improve the quality of the final assembly.
Our work shows that optical maps can be used effectively to assemble genomes within the de Bruijn graph assembly framework. Our experiments also provide insights into the characteristics of the mapping data that most affect the performance of our algorithm, indicating the potential benefit of more accurate optical mapping technologies, such as nano-coding.