Abstract
Methods to assemble sequence reads into larger pieces are described. In many cases, the raw data of sequencing machines are pictures, which are translated in a subsequent analysis step (base calling) into sequence reads. Each position of a sequence read receives a quality score, indicating the probability of a sequencing error. After quality filtering and trimming of adapter regions or barcoding indices, these reads can be assembled de novo into larger pieces. Basically three different types of assembly strategies are in use: greedy algorithms, overlap-layout-consensus assemblers and methods relying on k-mer graphs. Overlapping reads producing contiguous sequences are named contigs. Positional information from paired-end reads or mate pairs can be used to order contigs into scaffolds. In the ideal case of genome sequencing, the number of scaffolds would equal the number of expected chromosomes. Several statistics can be used to describe or compare different sequence assemblies. Generally, a diversity of programs and chosen parameters should be explored to find the best assembly. Different strategies are used for genome, transcriptome and metagenome assemblies, and all of them greatly benefit from the inclusion of long reads. Assembly methods are becoming an increasingly important tool for everybody working with sequence data, since the vast majority of published sequence data in NCBI GenBank is deposited as short reads in the sequence read archive (► http://www.ncbi.nlm.nih.gov/sra/). This data is usually not directly searchable by methods like BLAST and needs to be assembled for subsequent analysis.
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References
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477
Bankevich A, Pevzner PA (2016) TruSPAdes: barcode assembly of TruSeq synthetic long reads. Nat Methods 13:248–250
Batzoglou S, Jaffe DB, Stanley K, Butler J, Gnerre S, Mauceli E, Berger B, Mesirov JP, Lander ES (2002) ARACHNE: a whole-genome shotgun assembler. Genome Res 12:177–189
Boetzer M, Henkel CV, Jansen HJ, Butler D, Pirovano W (2011) Scaffolding pre-assembled contigs using SSPACE. Bioinformatics 27:578–579
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120
Bradnam K, Fass J, Alexandrov A, Baranay P, Bechner M, Birol I, Boisvert S, Chapman J, Chapuis G, Chikhi R, Chitsaz H, Chou W-C, Corbeil J, Del Fabbro C, Docking T, Durbin R, Earl D, Emrich S, Fedotov P, Fonseca N, Ganapathy G, Gibbs R, Gnerre S, Godzaridis E, Goldstein S, Haimel M, Hall G, Haussler D, Hiatt J, Ho I, Howard J, Hunt M, Jackman S, Jaffe D, Jarvis E, Jiang H, Kazakov S, Kersey P, Kitzman J, Knight J, Koren S, Lam T-W, Lavenier D, Laviolette F, Li Y, Li Z, Liu B, Liu Y, Luo R, MacCallum I, MacManes M, Maillet N, Melnikov S, Naquin D, Ning Z, Otto T, Paten B, Paulo O, Phillippy A, Pina-Martins F, Place M, Przybylski D, Qin X, Qu C, Ribeiro F, Richards S, Rokhsar D, Ruby J, Scalabrin S, Schatz M, Schwartz D, Sergushichev A, Sharpe T, Shaw T, Shendure J, Shi Y, Simpson J, Song H, Tsarev F, Vezzi F, Vicedomini R, Vieira B, Wang J, Worley K, Yin S, Yiu S-M, Yuan J, Zhang G, Zhang H, Zhou S, Korf I (2013) Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species. GigaScience 2:10
Chang Z, Wang Z, Li G (2014) The impacts of read length and transcriptome complexity for De Novo assembly: a simulation study. PLoS One 9:e94825
Chevreux B, Pfisterer T, Drescher B, Driesel AJ, Müller WEG, Wetter T, Suhai S (2004) Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs. Genome Res 14:1147–1159
Chikhi R, Medvedev P (2014) Informed and automated k-mer size selection for genome assembly. Bioinformatics 30:31–37
Chin C-S, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, Clum A, Copeland A, Huddleston J, Eichler EE, Turner SW, Korlach J (2013) Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods 10:563–569
Cock PJA, Fields CJ, Goto N, Heuer ML, Rice PM (2010) The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 38:1767–1771
Coughlan L, Cotter P, Hill C, Alvarez-Ordóñez A (2015) Biotechnological applications of functional metagenomics in the food and pharmaceutical industries. Front Microbiol 6:672
David M, Dursi LJ, Yao D, Boutros PC, Simpson JT (2017) Nanocall: an open source basecaller for Oxford nanopore sequencing data. Bioinformatics 33:49–55
Dohmen E, Kremer LPM, Bornberg-Bauer E, Kemena C (2016) DOGMA: domain-based transcriptome and proteome quality assessment. Bioinformatics 32:2577–2581
Donmez N, Brudno M (2013) SCARPA: scaffolding reads with practical algorithms. Bioinformatics 29:428–434
Earl D, Bradnam K, St John J, Darling A, Lin D, Fass J, Hung On Ken Y, Buffalo V, Zerbino DR, Diekhans M, Ngan N, Ariyaratne PN, Sung W-K, Ning Z, Haimel M, Simpson JT, Fonseca NA, Birol I, Docking TR, Ho IY, Rokhsar DS, Chikhi R, Lavenier D, Chapuis G, Naquin D, Maillet N, Schatz MC, Kelley DR, Phillippy AM, Koren S, Yang S-P, Wu W, Chou W-C, Srivastava A, Shaw TI, Ruby JG, Skewes-Cox P, Betegon M, Dimon MT, Solovyev V, Seledtsov I, Kosarev P, Vorobyev D, Ramirez-Gonzalez R, Leggett R, MacLean D, Xia F, Luo R, Li Z, Xie Y, Liu B, Gnerre S, MacCallum I, Przybylski D, Ribeiro FJ, Yin S, Sharpe T, Hall G, Kersey PJ, Durbin R, Jackman SD, Chapman JA, Huang X, DeRisi JL, Caccamo M, Li Y, Jaffe DB, Green RE, Haussler D, Korf I, Paten B (2011) Assemblathon 1: a competitive assessment of de novo short read assembly methods. Genome Res 21:2224–2241
Ewing B, Green P (1998) Base-calling of automated sequencer traces using Phred. II. Error probabilities. Genome Res 8:186–194
Gao S, Sung W-K, Nagarajan N (2011) Opera: reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. J Comput Biol 18:1681–1691
Goodwin S, Gurtowski J, Ethe-Sayers S, Deshpande P, Schatz MC, McCombie WR (2015) Oxford nanopore sequencing, hybrid error correction, and de novo assembly of a eukaryotic genome. Genome Res 25:1750–1756
Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A (2011) Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat Biotechnol 29:644–U130
Gurevich A, Saveliev V, Vyahhi N, Tesler G (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–1075
Hackl T, Hedrich R, Schultz J, Förster F (2014) proovread: large-scale high-accuracy PacBio correction through iterative short read consensus. Bioinformatics 30:3004–3011
Hernandez D, François P, Farinelli L, Østerås M, Schrenzel J (2008) De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer. Genome Res 18:802–809
Howison M, Zapata F, Dunn CW (2013) Toward a statistically explicit understanding of de novo sequence assembly. Bioinformatics 29:2959–2963
Howison M, Zapata F, Edwards EJ, Dunn CW (2014) Bayesian genome assembly and assessment by Markov chain Monte Carlo sampling. PLoS One 9:e99497
Huang X, Madan A (1999) CAP3: a DNA sequence assembly program. Genome Res 9:868–877
Hunt M, Newbold C, Berriman M, Otto T (2014) A comprehensive evaluation of assembly scaffolding tools. Genome Biol 15:R42
Kelley D, Schatz M, Salzberg S (2010) Quake: quality-aware detection and correction of sequencing errors. Genome Biol 11:R116
Kircher M, Heyn P, Kelso J (2011) Addressing challenges in the production and analysis of Illumina sequencing data. BMC Genomics 12:382
Kircher M, Stenzel U, Kelso J (2009) Improved base calling for the Illumina genome analyzer using machine learning strategies. Genome Biol 10:R83
Koren S, Schatz M, Walenz B, Martin J, Howard J, Ganapathy G, Wang Z, Rasko D, McCombie W, Jarvis E, Phillippy A (2012) Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat Biotechnol 30:693–700
Koren S, Walenz BP, Berlin K, Miller JR, Phillippy AM (2016) Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. bioRxiv. doi.org/10.1101/071282.
Laver T, Harrison J, O’Neill PA, Moore K, Farbos A, Paszkiewicz K, Studholme DJ (2015) Assessing the performance of the Oxford nanopore technologies MinION. Biomol Detect Quantif 3:1–8
Li D, Luo R, Liu C-M, Leung C-M, Ting H-F, Sadakane K, Yamashita H, Lam T-W (2016) MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102:3–11
Li H (2016) Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32:2103–2110
Li R, Fan W, Tian G, Zhu H, He L, Cai J, Huang Q, Cai Q, Li B, Bai Y, Zhang Z, Zhang Y, Wang W, Li J, Wei F, Li H, Jian M, Nielsen R, Li D, Gu W, Yang Z, Xuan Z, Ryder O, Leung F-C, Zhou Y, Cao J, Sun X, Fu Y (2010) The sequence and de novo assembly of the giant panda genome. Nature 463:311–317
Lin Y, Yuan J, Kolmogorov M, Shen MW, Pevzner PA (2016) Assembly of long error-prone reads using de Bruijn graphs. Proc Natl Acad Sci USA 113:E8396-E8405 (In press)
Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y (2012) SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience 1:18
MacCallum I, Przybylski D, Gnerre S, Burton J, Shlyakhter I, Gnirke A, Malek J, McKernan K, Ranade S, Shea TP, Williams L, Young S, Nusbaum C, Jaffe DB (2009) ALLPATHS 2: small genomes assembled accurately and with high continuity from short paired reads. Genome Biol 10:R103
Marçais G, Kingsford C (2011) A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27:764–770
Martin JA, Wang Z (2011) Next-generation transcriptome assembly. Nat Rev Genet 12:671–682
Miller J, Koren S, Sutton G (2010) Assembly algorithms for next-generation sequencing data. Genomics 95:315
Myers EW, Sutton GG, Delcher AL, Dew IM, Fasulo DP, Flanigan MJ, Kravitz SA, Mobarry CM, Reinert KHJ, Remington KA, Anson EL, Bolanos RA, Chou H-H, Jordan CM, Halpern AL, Lonardi S, Beasley EM, Brandon RC, Chen L, Dunn PJ, Lai Z, Liang Y, Nusskern DR, Zhan M, Zhang Q, Zheng X, Rubin GM, Adams MD, Venter JC (2000) A whole-genome assembly of Drosophila. Science 287:2196–2204
Nagarajan N, Pop M (2013) Sequence assembly demystified. Nat Rev Genet 14:157–167
Nakamura K, Oshima T, Morimoto T, Ikeda S, Yoshikawa H, Shiwa Y, Ishikawa S, Linak MC, Hirai A, Takahashi H, Altaf-Ul-Amin M, Ogasawara N, Kanaya S (2011) Sequence-specific error profile of Illumina sequencers. Nucleic Acids Res 39:e90
Namiki T, Hachiya T, Tanaka H, Sakakibara Y (2012) MetaVelvet: an extension of velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 40:e155
Peng Y, Leung HCM, Yiu S-M, Chin FYL (2010) IDBA—a practical iterative de Bruijn graph de novo assembler. In: Berger B (ed) Research in computational molecular biology, vol 6044. Springer, Berlin, pp 426–440
Peng Y, Leung HCM, Yiu S-M, Lv M-J, Zhu X-G, Chin FYL (2013) IDBA-Tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels. Bioinformatics 29:326–334
Peng Y, Leung HCM, Yiu SM, Chin FYL (2011) Meta-IDBA: a de Novo assembler for metagenomic data. Bioinformatics 27:i94–i101
Pevzner P, Tang H, Waterman M (2001) An Eulerian path approach to DNA fragment assembly. Proc Natl Acad Sci 98:9748–9753
Renaud G, Kircher M, Stenzel U, Kelso J (2013) freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencers. Bioinformatics 29:1208–1209
Robertson G, Schein J, Chiu R, Corbett R, Field M, Jackman SD, Mungall K, Lee S, Okada HM, Qian JQ, Griffith M, Raymond A, Thiessen N, Cezard T, Butterfield YS, Newsome R, Chan SK, She R, Varhol R, Kamoh B, Prabhu A-L, Tam A, Zhao Y, Moore RA, Hirst M, Marra MA, Jones SJM, Hoodless PA, Birol I (2010) De novo assembly and analysis of RNA-seq data. Nat Methods 7:909–912
Salmela L, Rivals E (2014) LoRDEC: accurate and efficient long read error correction. Bioinformatics 30:3506–3514
Salzberg S, Phillippy A, Zimin A, Puiu D, Magoc T, Koren S, Treangen T, Schatz M, Delcher A, Roberts M, Marcais G, Pop M, Yorke J (2012) GAGE: a critical evaluation of genome assemblies and assembly algorithms. Genome Res 22:557–567
Schatz MC, Delcher AL, Salzberg SL (2010) Assembly of large genomes using second-generation sequencing. Genome Res 20:1165–1173
Schulz MH, Zerbino DR, Vingron M, Birney E (2012) Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels. Bioinformatics 28:1086–1092
Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM (2015) BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31:3210–3212
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
Smeds L, Kunstner A (2011) CONDETRI - A content dependent read trimmer for Illumina data. PLoS One 6:e26314
Smith-Unna R, Boursnell C, Patro R, Hibberd J, Kelly S (2016) TransRate: reference free quality assessment of de novo transcriptome assemblies. Genome Res 26:1134–1144
Sović I, Križanović K, Skala K, Šikić M (2016) Evaluation of hybrid and non-hybrid methods for de novo assembly of nanopore reads. Bioinformatics 32:2582–2589
Wang Z, Gerstein M, Snyder M (2009) RNA-seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63
Zerbino D, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821–829
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Bleidorn, C. (2017). Assembly and Data Quality. In: Phylogenomics. Springer, Cham. https://doi.org/10.1007/978-3-319-54064-1_5
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DOI: https://doi.org/10.1007/978-3-319-54064-1_5
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