Hybrid error correction and de novo assembly of single-molecule sequencing reads

By Sergey Koren, Michael C. Schatz, Brian Walenz, Jeffrey Martin, Jason T. Howard, Ganeshkumar Ganapathy, Zhong Wang, David A. Rasko, W. Richard McCombie, Erich D. Jarvis and 2 more. Nature Biotechnology, 2012

1,002 citations recorded by the source corpus.

Single-molecule sequencing instruments can generate multikilobase sequences with the potential to greatly improve genome and transcriptome assembly. However, the error rates of single-molecule reads are high, which has limited their use thus far to resequencing bacteria. To address this limitation, we introduce a correction algorithm and assembly strategy that uses short, high-fidelity sequences to correct the error in single-molecule sequences. We demonstrate the utility of this approach on reads generated by a PacBio RS instrument from phage, prokaryotic and eukaryotic whole genomes, including the previously unsequenced genome of the parrot Melopsittacus undulatus, as well as for RNA-Seq reads of the corn (Zea mays) transcriptome. Our long-read correction achieves >99.9% base-call accuracy, leading to substantially better assemblies than current sequencing strategies: in the best example, the median contig size was quintupled relative to high-coverage, second-generation assemblies. Greater gains are predicted if read lengths continue to increase, including the prospect of single-contig bacterial chromosome assembly.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/e123f2b9e196e43584e416499b79e8d73114dde2

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Citations in the corpus

Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation (2016, methodology): “Thisstrategywasfirstintro-duced by PBcR for the hierarchical correction and assembly of single-molecule reads (Korenet al. 2012).”
Sequence assembly demystified (2013, methodology): “…1,2 , the development of new de novo assembly strategies for data derived from metagenomic 3–5 , single-cell 6,7 or transcriptome experiments 8,9 and the effective use of complementary information derived from multiple sequencing technologies 10,11 and/or paired-end data or mate-pair data 12,13 .”
PacBio Sequencing and Its Applications (2015, methodology): “Koren et al. developed the PacBio corrected Reads (PBcR) approach for using short reads to correct the errors in long reads [34].”
hybridSPAdes: an algorithm for hybrid assembly of short and long reads (2016, methodology): “For ECOLI200 dataset, both Cerulean and hybridPBcR generated inferior assemblies.”
Improving PacBio Long Read Accuracy by Short Read Alignment (2012, methodology): “Comparing with PacBioToCA , LSC has significantly higher sensitivity as it output a several - fold higher number of ecLRs in every bin of read length ( Figure 5 ) .”
Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions (2016, positive): “In addition, reference genomes based on short-read technologies can be greatly improved by including some data from longer-read platforms to generate a hybrid genome assembly (English et al. 2012; Koren et al. 2012).”
Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads (2016, background): “Alternatively, they may first use short reads to correct errors in long reads, followed by assembly of the corrected long reads[6,7].”
Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis (2017, neutral): “28 – 34).”
SNP Discovery through Next-Generation Sequencing and Its Applications (2012, background): “However, their long reads o ﬀ er a deﬁnite advantage to ﬁll gaps in genomic sequences and, at least in bacterial genomes, NGS reads have proven capable of “correcting” the base call errors of this TGS technology [33–36].”