Hardware Accelerated Sequence Alignment with Traceback

Biological sequence alignment is an essential tool used in molecular biology and biomedical applications. The growing volume of genetic data and the complexity of sequence alignment present a challenge in obtaining alignment results in a timely manner. Knownmethods to accelerate alignment on reconfigurable hardware only address sequence comparison, limit the sequence length, or exhibit memory and I/O bottlenecks. A space-efficient, global sequence alignment algorithm and architecture is presented that accelerates the forward scan and traceback in hardware without memory and I/O limitations. With 256 processing elements in FPGA technology, a performance gain over 300 times that of a desktop computer is demonstrated on sequence lengths of 16000. For greater performance, the architecture is scalable to more processing elements.

[1]  J Goodman,et al.  The value of a database in surveillance and vaccine selection , 2001 .

[2]  Yvan Saeys,et al.  Scalable hardware accelerator for comparing DNA and protein sequences , 2006, InfoScale '06.

[3]  Martin C. Herbordt,et al.  Families of FPGA-based accelerators for approximate string matching , 2007, Microprocess. Microsystems.

[4]  J. Thompson,et al.  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. , 1994, Nucleic acids research.

[5]  O. Gotoh An improved algorithm for matching biological sequences. , 1982, Journal of molecular biology.

[6]  Jasmin Ajanovic PCI Express , 2011, Encyclopedia of Parallel Computing.

[7]  Srinivas Aluru,et al.  Space and time optimal parallel sequence alignments , 2004, IEEE Transactions on Parallel and Distributed Systems.

[8]  E. C. Uberbacher,et al.  A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space , 1994 .

[9]  Quinn Snell,et al.  Qnet: A Modular Architecture for Reconfigurable Computing , 2008, ERSA.

[10]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[11]  Heitor Silvério Lopes,et al.  Implementation of a Parallel Algorithm for Protein Pairwise Alignment Using Reconfigurable Computing , 2006, 2006 IEEE International Conference on Reconfigurable Computing and FPGA's (ReConFig 2006).

[12]  Shea N. Gardner,et al.  Sequencing Needs for Viral Diagnostics , 2004, Journal of Clinical Microbiology.

[13]  Adam Zemla,et al.  Comparative Genomics Tools Applied to Bioterrorism Defence , 2003, Briefings Bioinform..

[14]  Eugene W. Myers,et al.  Optimal alignments in linear space , 1988, Comput. Appl. Biosci..

[15]  Enno Ohlebusch,et al.  An Applications-focused Review of Comparative Genomics Tools: Capabilities, Limitations and Future Challenges , 2003, Briefings Bioinform..

[16]  T. Ramdas,et al.  A Survey of FPGAs for Acceleration of High Performance Computing and their Application to Computational Molecular Biology , 2005, TENCON 2005 - 2005 IEEE Region 10 Conference.

[17]  Daniel P. Lopresti,et al.  FPGA Implementation of Systolic Sequence Alignment , 1992, FPL.

[18]  Akihiko Konagaya,et al.  High Speed Homology Search with FPGAs , 2001, Pacific Symposium on Biocomputing.

[19]  Ying Liu,et al.  A Highly Parameterized and Efficient FPGA-Based Skeleton for Pairwise Biological Sequence Alignment , 2009, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[20]  F. Delsuc,et al.  Phylogenomics and the reconstruction of the tree of life , 2005, Nature Reviews Genetics.

[21]  Christus,et al.  A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins , 2022 .

[22]  D. Higgins,et al.  T-Coffee: A novel method for fast and accurate multiple sequence alignment. , 2000, Journal of molecular biology.

[23]  Joel H. Saltz,et al.  Parallel processing of biological sequence comparison algorithms , 1988, International Journal of Parallel Programming.