BINOS4DNA: Bitmap Indexes and NoSQL for Identifying Species with DNA Signatures through Metagenomics Samples

Abstract

The advancement of next generation sequencing (NGS) and shotgun sequencing technologies produced massive amounts of genomics data. Metagenomics, a powerful technique to study genetic material of uncultivable microorganisms received directly from their natural environment, is dealing with high throughput sequencing read data sets. Assembling, binning and alignment of short reads in order to identify microorganisms of a Metagenomics sample are expensive and time- consuming, regardless of other restrictions. DNA signature is a short nucleotide sequence fragment which is used to distinguish species across all other species. It can be a basis for identifying microorganisms both in environmental and clinical samples directly from the short reads, without assembling and alignment processes. In this paper, we propose a scalable method in which we use optimization techniques borrowed from database technology, namely bitmap indexes. They are used to speed up searching and matching of billions of DNA signatures in the short reads of thousands of different microorganisms, using commodity High Performance Computing, such as Hadoop MapReduce, Hive and Hbase.

This work was performed when Ramin Karimi was visiting the LIAS/ISAE-ENSMA Lab. This visit is funded by ERASMUS mobility program. The work was also supported in part by the projects TMOP-4.2.2.C-11/1/KONV-2012-0001, and TMOP 4.2.4. A/2-11-1-2012-0001 supported by the European Union, co-financed by the European Social Fund, and by the OTKA grant NK101680.