A survey on de novo assembly methods for single-molecular sequencing

Abstract

Background: The single-molecular sequencing (SMS) is under rapid development and generating increasingly long and accurate sequences. De novo assembly of genomes from SMS sequences is a critical step for many genomic studies. To scale well with the developing trends of SMS, many de novo assemblers for SMS have been released. These assembly workflows can be categorized into two different kinds: the correction-and-assembly strategy and the assembly-and-correction strategy, both of which are gaining more and more attentions.

Results: In this article we make a discussion on the characteristics of errors in SMS sequences. We then review the currently widely applied de novo assemblers for SMS sequences. We also describe computational methods relevant to de novo assembly, including the alignment methods and the error correction methods. Benchmarks are provided to analyze their performance on different datasets and to provide use guides on applying the computation methods.

Conclusion: We make a detailed review on the latest development of de novo assembly and some relevant algorithms for SMS, including their rationales, solutions and results. Besides, we provide use guides on the algorithms based on their benchmark results. Finally we conclude the review by giving some developing trends of third generation sequencing (TGS).

Graphical abstract

Keywords

third generation sequencing / single-molecular real-time sequencing / sequence alignment / sequence error correction / de novo assembly

References

[1] Brown, S. D., Nagaraju, S., Utturkar, S., De Tissera, S., Segovia, S., Mitchell, W., Land, M. L., Dassanayake, A. and Köpke, M. (2014) Comparison of single-molecule sequencing and hybrid approaches for finishing the genome of Clostridium autoethanogenum and analysis of CRISPR systems in industrial relevant Clostridia. Biotechnol. Biofuels, 7, 40

[2] Rhoads, A. and Au, K. F. (2015) PacBio sequencing and its applications. Genom. Proteom. Bioinf., 13, 278–289

[3] Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., (2009) Real-time DNA sequencing from single polymerase molecules. Science, 323, 133–138

[4] Detter, J. C., Johnson, S. L., Bishop-Lilly, K. A., Chain, P. S., Gibbons, H. S., Minogue, T. D., Sozhamannan, S., Van Gieson, E.J. and Resnick, I. G. (2014) Nucleic acid sequencing for characterizing infectious and/or novel agents in complex samples. In: Biological Identification, pp. 3–53. Sawston: Woodhead Publishing

[5] Wenger, A. M., Peluso, P., Rowell, W. J., Chang, P. C., Hall, R. J., Concepcion, G. T., Ebler, J., Fungtammasan, A., Kolesnikov, A., Olson, N. D., (2019) Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol., 37, 1155–1162

[6] Chin, C. S., Alexander, D. H., Marks, P., Klammer, A. A., Drake, J., Heiner, C., Clum, A., Copeland, A., Huddleston, J., Eichler, E. E., (2013) Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods, 10, 563–569

[7] Magi, A., Semeraro, R., Mingrino, A., Giusti, B. and D’Aurizio, R. (2018) Nanopore sequencing data analysis: state of the art, applications and challenges. Brief. Bioinformatics, 19, 1256–1272

[8] Jain, M., Koren, S., Miga, K. H., Quick, J., Rand, A. C., Sasani, T. A., Tyson, J. R., Beggs, A. D., Dilthey, A. T., Fiddes, I. T., (2018) Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat. Biotechnol., 36, 338–345

[9] Magi, A., Giusti, B. and Tattini, L. (2017) Characterization of MinION nanopore data for resequencing analyses. Brief. Bioinformatics, 18, 940–953

[10] Rang, F. J., Kloosterman, W. P. and de Ridder, J. (2018) From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol., 19, 90

[11] Loman, N. J., Quick, J. and Simpson, J. T. (2015) A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat. Methods, 12, 733–735

[12] Walker, B. J., Abeel, T., Shea, T., Priest, M., Abouelliel, A., Sakthikumar, S., Cuomo, C. A., Zeng, Q., Wortman, J., Young, S. K., (2014) Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One, 9, e112963

[13] Kingan, S. B., Heaton, H., Cudini, J., Lambert, C. C., Baybayan, P., Galvin, B. D., Durbin, R., Korlach, J. and Lawniczak, M. K. N. (2019) A high-quality de novo genome assembly from a single mosquito using PacBio sequencing. Genes (Basel), 10, 62

[14] Vaser, R., Sović I., Nagarajan, N. and Šikić, M. (2017) Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res., 27, 737–746

[15] Bashir, A., Klammer, A., Robins, W. P., Chin, C. S., Webster, D., Paxinos, E., Hsu, D., Ashby, M., Wang, S., Peluso, P., (2012) A hybrid approach for the automated finishing of bacterial genomes. Nat. Biotechnol., 30, 701–707

[16] Koren, S., Schatz, M. C., Walenz, B. P., Martin, J., Howard, J. T., Ganapathy, G., Wang, Z., Rasko, D. A., McCombie, W. R., Jarvis, E. D., (2012) Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat. Biotechnol., 30, 693–700

[17] Ribeiro, F. J., Przybylski, D., Yin, S., Sharpe, T., Gnerre, S., Abouelleil, A., Berlin, A. M., Montmayeur,A., Shea, T. P., Walker, B. J., (2012) Finished bacterial genomes from shotgun sequence data. Genome Res., 22, 2270–2277

[18] Chin, C. S., Alexander, D. H., Marks, P., Klammer, A. A., Drake, J., Heiner, C., Clum, A., Copeland, A., Huddleston, J., Eichler, E. E., (2013) Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods, 10, 563–569

[19] Smith, T. F. and Waterman, M. S. (1981) Identification of common molecular subsequences. J. Mol. Biol., 147, 195–197

[20] Altschul, S. F., Madden, T. L., Schäffer, A. A., Zhang, J., Zhang, Z., Miller, W. and Lipman, D. J. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res., 25, 3389–3402

[21] Chaisson, M. J. and Tesler, G. (2012) Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics, 13, 238

[22] Ferragina, P. and Manzini, G. (2000) Opportunistic data structures with applications In: Proceedings the 41st Annual Symposium on Foundations of Computer Science, pp. 390–398. IEEE

[23] Li, H. and Durbin, R. (2010) Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics, 26, 589–595

[24] Ben, L. and Salzberg, S. L. (2012) Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359

[25] Chen, Y., Ye, W., Zhang, Y. and Xu, Y. (2015) High speed BLASTN: an accelerated MegaBLAST search tool. Nucleic Acids Res., 43, 7762–7768

[26] Lam, T. W., Sung, W. K., Tam, S. L., Wong, C. K. and Yiu, S. M. (2008) Compressed indexing and local alignment of DNA. Bioinformatics, 24, 791–797

[27] Abouelhoda, M. I. and Ohlebusch, E. A. (2003) Local chaining algorithm and its applications in comparative genomics. In: International Workshop on Algorithms in Bioinformatics, pp. 1–16. Berlin: Springer

[28] Eppstein, D., Galil, Z., Giancarlo, R. and Italiano, G. F. (1992) Sparse dynamic programming I: linear cost functions. J. Assoc. Comput. Mach., 39, 519–545

[29] Myers, G. (2014) Efficient local alignment discovery amongst noisy long reads In: International Workshop on Algorithms in Bioinformatics, pp. 52–67. Berlin: Springer

[30] Cormen, T. H., Leiserson,C. E., Rivest, R. L. and Stein, C. (2009) Introduction to Algorithms (3rd. edition), pp.197–204. Cambridge: MIT Press

[31] Myers, E. W. (1986) AnO (ND) difference algorithm and its variations. Algorithmica, 1, 251–266

[32] Roberts, M., Hayes, W., Hunt, B. R., Mount, S. M. and Yorke, J. A. (2004) Reducing storage requirements for biological sequence comparison. Bioinformatics, 20, 3363–3369

[33] Li, H. (2016) Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics, 32, 2103–2110

[34] Li, H. (2018) Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics, 34, 3094–3100

[35] Gotoh, O. (1990) Optimal sequence alignment allowing for long gaps. Bull. Math. Biol., 52, 359–373

[36] Suzuki, H. and Kasahara, M. (2018) Introducing difference recurrence relations for faster semi-global alignment of long sequences. BMC Bioinformatics, 19, 45

[37] Šošic, M. and Šikic, M. (2017) Edlib: a C/C ++ library for fast, exact sequence alignment using edit distance. Bioinformatics, 33, 1394–1395

[38] Myers, G. (1999) A fast bit-vector algorithm for approximate string matching based on dynamic programming. J. Assoc. Comput. Mach., 46, 395–415

[39] Hirschberg, D. S. (1975) A linear space algorithm for computing maximal common subsequences. Commun. ACM, 18, 341–343

[40] Lee, C., Grasso, C. and Sharlow, M. F. (2002) Multiple sequence alignment using partial order graphs. Bioinformatics, 18, 452–464

[41] Chin, C. S., Peluso, P., Sedlazeck, F. J., Nattestad, M., Concepcion,G. T., Clum, A., Dunn, C., O’Malley, R., Figueroa-Balderas, R., Morales-Cruz, A., (2016) Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods, 13, 1050–1054

[42] Myers, E. W. (2005) The fragment assembly string graph. Bioinformatics, 21(suppl_2), ii79–ii85

[43] Berlin, K., Koren, S., Chin, C. S., Drake, J. P., Landolin, J. M. and Phillippy, A. M. (2015) Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat. Biotechnol., 33, 623–630

[44] Koren, S., Walenz, B. P., Berlin, K., Miller, J. R., Bergman, N. H. and Phillippy, A. M. (2017) Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res., 27, 722–736

[45] Miller, J. R., Delcher, A. L., Koren, S., Venter, E., Walenz, B. P., Brownley, A., Johnson, J., Li, K., Mobarry, C. and Sutton, G. (2008) Aggressive assembly of pyrosequencing reads with mates. Bioinformatics, 24, 2818–2824

[46] Xiao, C. L., Chen, Y., Xie, S. Q., Chen,K.-N., Wang, Y., Han, Y., Luo F., Xie , Z. (2017) MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads. Nat. Methods, 14, 1072–1074

[47] Kolmogorov, M., Yuan, J., Lin, Y. and Pevzner, P. A. (2019) Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol., 37, 540–546

[48] Ruan, J. and Li, H. (2020) Fast and accurate long-read assembly with wtdbg2. Nat. Methods, 17, 155–158

[49] Chen, Y., Nie, F., Xie, S.-Q. and Zheng, Y.-F. (2020) Fast and accurate assembly of Nanopore reads via progressive error correction and adaptive read selection. bioRxiv, 930107

COMPLIANCE WITH ETHICS GUIDELINES

The authors Ying Chen and Chuan-Le Xiao declare that they have no conflict of interests.

This article is a review article and does not contain any studies with human or animal subjects performed by any of the authors.

RIGHTS & PERMISSIONS

2020 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature