Accelerated microRNA-Precursor Detection Using the Smith-Waterman Algorithm on FPGAs

During the last few years more and more functionalities of RNA have been discovered that were previously thought of being carried out by proteins alone. One of the most striking discoveries was the detection of microRNAs, a class of noncoding RNAs that play an important role in post-transcriptional gene regulation. Large-scale analyses are needed for the still increasingly growing amount of sequence data derived from new experimental technologies. In this paper we present a framework for the detection of the distinctive precursor structure of microRNAS that is based on the well-known Smith-Waterman algorithm. By conducting the computation of the local alignment on a FPGA, we are able to gain a substantial speedup compared to a pure software implementation bringing together supercomputer performance and bioinformatics research. We conducted experiments on real genomic data and we found several new putative hits for microRNA precursor structures