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A survey of genome sequence assembly techniques and algorithms using high-performance computing

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Abstract

Genome assembly has been an area of active research since the DNA structure was discovered and has gathered more steam after the Human Genome project was launched. A large number of genomes have been assembled and many more are in the pipeline. A number of full-scale assemblers and other special-purpose modules have been reported. Since the volume of data involved in the genome assembly process is extraordinarily large and requires significantly large computational power and processing time, many assemblers have utilized parallel computing to achieve faster and more efficient reconstruction of the DNA. A genome assembler is a multi-step process including different components that may be partly or fully parallelized. Although several assemblers and individual modules that perform various tasks, such as pairwise alignment, multiple sequence alignment, and repeat finding, have been analyzed and documented before, this paper provides a holistic view of the assembly process in the realm of parallel and distributed computing, streamlining all the individual tasks related, but not limited to, the whole genome shotgun sequencing into a sequence of loosely coupled stages where one stage consumes the output of the preceding stage and passes its results to the next one. Many of these tasks are essential to the current and next-generation sequence assemblers. The paper walks through the entire streamlined process while describing, analyzing, and commenting on the algorithms and techniques that have been designed and implemented for each of the stages. Where applicable, the paper suggests improvements that may form the basis of potentially new research work.

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References

  1. Ahmed M, Ahmad I, Khan S (2011) A theoretical analysis of scalability of the parallel genome assembly algorithms. In: Second international conference on bioinformatics models, methods and algorithms. pp 234–237

  2. Ahmed M, Ahmad I, Khan S (2011) A comparative analysis of approaches to parallel genome assembly. J Interdiscipl Sci Comput Life Sci 3:1–7. doi:10.1007/s12539-011-00

    Article  Google Scholar 

  3. Ahmed M, Ahmad M, Ahmad I (2008) A multi-pronged parallel approach to enhance speed and accuracy of sequence assembly. In: Biotechnology and bioinformatics symposium

  4. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    Article  Google Scholar 

  5. Aluru S, Futamura N, Mehrotra K (2003) Parallel biological sequence comparison using prefix computations. J Parallel Distrib Comput 63(3):264–272

    Article  MATH  Google Scholar 

  6. Bao Z, Eddy S (2002) Automated de novo identification of repeat sequence families in sequenced genomes. Genome Res 8:1269–1276

    Article  Google Scholar 

  7. Batzoglou S, Jaffe D, Stanley K, Butler J, Gnerre S, Mauceli E, Berger B, Mesirov J, Lander E (2002) Arachne: a whole-genome shotgun assembler. Genome Res 12(1):177–189

    Article  Google Scholar 

  8. Berger M, Munson P (1991) A novel randomized iterative strategy for aligning multiple protein sequences. CABIOS 7:479–484

    Google Scholar 

  9. Blackshields G, Wallace I, Larkin M, Higgins D (2006) Analysis and comparison of benchmarks for multiple sequence alignment. In Silico Biol 6:321–339

    Google Scholar 

  10. Blazewicz J, Figlerowicz M, Jackowiak P, Janny D, Jarczynski D, Kasprzak M, Nalewaj M, Nowierski B, Styszynski R, Szajkowski L, Widera P (2004) Parallel DNA sequence assembly. In: Proceedings of the fifth Mexican international conference in computer science (ENC ’04). IEEE Computer Society, New York, pp 378–382

  11. Brudno M, Batzoglou S (2004) ProbCons: Probabilistic consistency based multiple alignment of amino acid sequences. In: Proceedings of nineteenth national conference on artificial intelligence. pp 703–708

  12. Chao K, Pearson W, Miller W (1992) Aligning two sequences within a specified diagonal band. Comput Appl Biosci 8:481–487

    Google Scholar 

  13. Cheetham J, Dehne F, Pitre S, Rau-Chaplin A, Taillon P (2003) Parallel CLUSTAL W for PC clusters. In: International conference on computational science and its applications. Lecture notes in computer science, vol 2668. pp 300–309

  14. Darling A, Carey L, Feng W (2003) The design, implementation, and evaluation of mpiBLAST. In: Fourth international conference on Linux clusters: the HPC revolution 2003 in conjunction with The ClusterWorld Conference & Expo

  15. Deng X, Li E, Shan J, Chen W (2006) Parallel implementation and performance characterization of MUSCLE. In: Parallel and distributed processing symposium

  16. Dovichi N, Zhang J (2000) How capillary electrophoresis sequenced the human genome. Angew Chemie Int Edition 39:4463–4468

    Article  Google Scholar 

  17. Du Z, Lin F (2006) pNJTree: a parallel program for reconstruction of neighbor-joining tree and its application in ClustalW. J Parallel Comput 32:5–6

    Article  Google Scholar 

  18. Ebedes J, Datta A (2004) Multiple sequence alignment in parallel on a workstation cluster. Bioinformatics 20(7):1193–1195

  19. Edgar R (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797

    Article  Google Scholar 

  20. Edgar R, Myers E (2005) PILER: identification and classification of genomic repeats. Bioinformatics 1 21(Supplement 1):i152–i158

  21. Essoussi N, Boujenfa K, Limam M (2008) A comparison of MSA tools. Bioinformatics 2:452–455

  22. Ewing B, Hillier L, Wendl M, Green P (1998) Base-calling of automated sequencer traces using Phred. I. Accuracy assessment. Genome Res 8(3):175–185

    Article  Google Scholar 

  23. Felsenfeld A, Peterson J, Schloss J, Guyer M (1999) Assessing the quality of the DNA sequence from the human genome project. Genome Res 9:1–4

    Google Scholar 

  24. Grama A, Gupta A, Kumar V (1993) Isoefficiency: measuring the scalability of parallel algorithms and architectures. IEEE Parallel Distrib Technol 1(3):12–21

    Article  Google Scholar 

  25. Green P (1996) http://bozeman.mbt.washington.edu/phrap.docs/phrap.html. Accessed 19 Sep 2014

  26. Gordon D, Abajian C, Green P (1998) Consed: a graphical tool for sequence finishing. Genome Res 8:195–202

    Article  Google Scholar 

  27. Gusfield D (1997) Algorithms on strings, trees and sequences. Cambridge University Press, Cambridge, pp 9–10

  28. Higgins D, Sharp P (1988) CLUSTAL: a package for performing multiple sequence alignment on a microcomputer. Gene 73(1):237–44

    Article  Google Scholar 

  29. Higgins D (1994) CLUSTAL V: multiple alignment of dna and protein sequences. Methods Mol Biol 25:307–318

    Google Scholar 

  30. Hirosawa M, Totoki Y, Hoshida M, Ishikawa M (1995) Comprehensive study on iterative algorithms of multiple sequence alignment. Comput Appl Biosci 11:13–18

    Google Scholar 

  31. Huang X, Wang J, Aluru S, Yang S, Hillier L (2003) PCAP: a whole-genome assembly program. Genome Res 13:2164–2170

    Article  Google Scholar 

  32. Huang X, Madan A (1999) CAP3: a DNA sequence assembly program. Genome Res 9(9):868–877

    Article  Google Scholar 

  33. Isokawa M, Wayama M, Shimizu T (1996) Multiple sequence alignment using a genetic algorithm. Genome Inform 7:176–177

    Google Scholar 

  34. Jeanmougin F, Thompson J, Gouy M, Higgins D, Gibson T (1998) Multiple sequence alignment with clustal X. Trends Biochem Sci 23:403–405

    Article  Google Scholar 

  35. Johnson D, Metaxas P (1997) Connected components in O(log3/2n) parallel time for the CREW PRAM. J Comput Syst Sci 54(2):227–242

  36. Kalyanaraman A, Kothari S, Brendel V, Aluru S (2003) Efficient clustering of large EST data sets on parallel computers. Nucleic Acids Res 31(11):2963–2964

    Article  Google Scholar 

  37. Kalyanaraman A, Aluru S, Brendel V, Kothari S (2003) Space and time efficient parallel algorithms and software for EST clustering. IEEE Trans Parallel Distrib Syst 14:1209–1221

    Article  Google Scholar 

  38. Karl JA, Wiseman RW, O’Connor DH (2009) Cost-effective sequence-based nonhuman primate MHC class I genotyping from RNA. Methods 49(1):11–17. doi:10.1016/j.ymeth.2009.05.002

  39. Larkin M, Blackshields G, Brown N, Chenna R, McGettigan P, McWilliam H, Valentin F, Wallace A, Wilm R, Lopez R, Thompson J, Gibson T, Higgins D (2007) Clustal W and clustal X version 2.0. Bioinformatics 23:2947–2948

    Article  Google Scholar 

  40. Lee Z, Su S, Chuang C, Liu K (2008) Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment. Appl Soft Comput 8:55–78

    Article  Google Scholar 

  41. Li K (2003) ClustalW-MPI: ClustalW analysis using distributed and parallel computing. Bioinformatics 19(12) :1585–1586

  42. Li R, Zhu H, Ruan J, Qian W, Li S, Yang H, Wang J (2010) De novo assembly of human genomes with massively parallel short read sequencing. Genome Res 20(2):265–272

    Article  Google Scholar 

  43. Lipman D, Altschul S, Kececioglu D (1989) A tool for multiple sequence alignment. Proc Natl Acad Sci 86:4412–4415

    Article  Google Scholar 

  44. Liu X, Pande P, Meyerhenke H, Bader D (2013) PASQUAL: parallel techniques for next generation genome sequence assembly. IEEE Trans Parallel Distrib Syst 24(5):977–986

    Article  Google Scholar 

  45. Luo J, Ahmad I, Ahmed M (2005) Parallel multiple sequence alignment using dynamic scheduling. In: International conference on information technology: coding and computing, vol 1. pp 8–13

  46. Mardis E (2008) Next-generation DNA sequencing methods. Ann Rev Genomics Hum Genet 9:387–402

    Article  Google Scholar 

  47. Martins W, Cuvillo J, Francisco B, Theobald J, Gao G (2001) A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison. In: Proceedings of the Pacific symposium on biocomputing. pp 311–332

  48. Miller P, Nadkarni P, Carriero N (1991) Parallel computation and FASTA: confronting the problem of parallel database search for a fast sequence comparison algorithm. Comput Appl Biosci 7(1):71–78

    Google Scholar 

  49. Mullikin J, Ning Z (2003) The Phusion assembler. Genome Res 1:81–90

    Article  Google Scholar 

  50. Myers E, Sutton G, Smith H, Adams M, Venter J (2002) On the sequencing and assembly of the human genome. Proc Natl Acad Sci 99(7):4145–4146

    Article  Google Scholar 

  51. Needleman S, Wunsch C (1970) A general method applicable to the search for similarities in the amino acid sequence of two sequences. J Mol Biol 48:443–453

    Article  Google Scholar 

  52. Notredame C, Higgins D, Heringa J (2000) T-Coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 302:205–217

    Article  Google Scholar 

  53. Ogden T, Rosenberg M (2006) Multiple sequence alignment accuracy and phylogenetic inference. Syst Biol 56(2):314–328

    Article  Google Scholar 

  54. Pevzner P, Tang H, Waterman S (2001) An Eulerian path approach to DNA fragment assembly. Proc Natl Acad Sci USA 98(17):9748–9753

    Article  MathSciNet  MATH  Google Scholar 

  55. Pevzner P, Tang H, Tesler G (2004) De novo repeat classification and fragment assembly. Genome Res 14(9):1786–1796

    Article  Google Scholar 

  56. Porreca G (2010) Genome sequencing on nanoballs. Nat Biotechnol 28(1):43–44

    Article  Google Scholar 

  57. Prism ABIABI (1996) DNA sequencing analysis software. In: User’s manual, PE Applied Biosystems, Foster City

  58. Ralston A (1982) De Bruijn sequences—a model example of the interaction of discrete mathematics and computer science. Math Magaz 55:131–143

    Article  MathSciNet  MATH  Google Scholar 

  59. Ronaghi M, Uhlen M, Nyren P (1998) A sequencing method based on real-time pyrophosphate. Science 281(5375):363

    Article  Google Scholar 

  60. Rusk N (2011) Torrents of sequence. Nat Methods 8(1):44–44

    Google Scholar 

  61. Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol 4:406–425

    Google Scholar 

  62. Sanger F, Nicklen S, Coulson A (1977) DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci 74:5463–7

    Article  Google Scholar 

  63. Simpson J, Wong K, Jackman S, Schein J, Jones S, Birol I (2009) ABySS: a parallel assembler for short read sequence data. Genome Res 19:1117–1123

    Article  Google Scholar 

  64. Shi W, Zhou W (2005) A parallel Euler approach for large-scale biological sequence assembly. In: Proceedings of the third international conference on information technology and applications

  65. Smit A, Hubley R, Green P (1996–2010) RepeatMasker Open-3.0. http://www.repeatmasker.org. Accessed 20 Sep 2014

  66. Smith T, Waterman M (1981) Identification of common molecular subsequences. J Mol Biol 147:195–197

    Article  Google Scholar 

  67. Southern E (1975) Detection of specific sequences among DNA fragments separated by gel electrophoresis. J Mol Biol 98:503–517

    Article  Google Scholar 

  68. Sutton G, White O, Adams M, Kerlavage A (1995) TIGR assembler: a new tool for assembling large shotgun sequencing projects. Genome Sci Technol 1(1):9–19

    Article  Google Scholar 

  69. Thompson J, Plewniak F, Poch O (1999) A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Res 27(13):12682–2690

    Article  Google Scholar 

  70. Valouev A, Ichikawa J, Tonthat T, Stuart J, Ranade S, Peckham H, Zeng K, Malek J, Costa G, McKernan K, Sidow A, Fire A, Johnson S (2008) A high-resolution nucleosome position map of C. Elegans reveals a lack of universal sequence-dictated positioning. Genome Res 18(7):1051–1063

    Article  Google Scholar 

  71. Venter J, Adams M, Myers E (2001) The sequence of the human genome. Science 16(291):1304–1351

    Article  Google Scholar 

  72. Volfovsky N, Haas B, Salzberg S (2001) A clustering method for repeat analysis in DNA sequences. Genome Biol 2(8)

  73. Watson J, Crick F (1953) Molecular structure of nucleic acids: a structure for deoxyribose nucleic acid. Nature 171:737–738

    Article  Google Scholar 

  74. Yap T, Munson P, Frieder O, Martino R (1995) Parallel multiple sequence alignment using speculative computation. In: Proceedings of the international conference on parallel processing

  75. Yap T, Frieder O, Martino R (1998) Parallel computation in biological sequence analysis. IEEE Trans Parallel Distrib Syst 9(3) :283–294

  76. Zhang C, Wong A (1997) A genetic algorithm for multiple molecular sequence alignment. Comput Appl Biosci 13(6):565–581

    Google Scholar 

  77. Zhao F, Li T, Bryant D (2008) A new pheromone trail-based genetic algorithm for comparative genome assembly. Nucleic Acids Res 36(10):3455–3462

    Article  Google Scholar 

  78. Zola J, Yang X, Rospondek S, Aluru S (2007) Parallel T-Coffee: a parallel multiple sequence aligner. In: Proceedings of international society for computers and their applications, parallel and distributed computing systems. pp 248–253

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  1. University of Texas at Arlington, Arlington, USA

    Munib Ahmed, Ishfaq Ahmad & Mohammad Saad Ahmad

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  1. Munib Ahmed
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  2. Ishfaq Ahmad
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Ahmed, M., Ahmad, I. & Ahmad, M.S. A survey of genome sequence assembly techniques and algorithms using high-performance computing. J Supercomput 71, 293–339 (2015). https://doi.org/10.1007/s11227-014-1297-4

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