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Sequence assembly demystified

Nature Reviews Genetics volume 14, pages 157–167 (2013)Cite this article

Subjects

This article has been updated

Key Points

  • Advances in sequencing technologies and increased access to sequencing have led to recent renewed interest in sequence assembly algorithms and tools.

  • Assembly continues to be a computationally challenging problem in which engineering 'details' play a more important part than the choice of a specific assembly paradigm in defining the performance and accuracy of assemblers.

  • Modern sequence assemblers continue to explore new ways to capture and to analyse graph structures to carry out assembly in a time- and memory-efficient manner.

  • Most assembly programs are based on heuristics and ad hoc techniques and provide no guarantees on the correctness of the reconstructed sequence. Recent tools have sought to address this need by focusing on assembly tasks in which exact algorithms are feasible.

  • The availability of multiple sequencing technologies and library preparation protocols has brought into focus the importance of experimental design in sequence assembly.

  • Coupling of experimental design with the development of assembly algorithms may be key to optimizing assembly results in the future.

  • A combination of in silico assessment and validation using independent experimental data is currently used to assess the reliability of sequence assembly, although computational tools for assembly validation are still limited in number.

  • Sequence assembly is increasingly used for applications other than the traditional role of assembling genomes, including transcriptome analysis, reconstruction of microbial communities (metagenomics) and the discovery of genomic variants.

  • Application-specific assemblers, which exploit characteristics of the sequences to be reconstructed, have emerged as an important area of focus for assembly research.

Abstract

Advances in sequencing technologies and increased access to sequencing services have led to renewed interest in sequence and genome assembly. Concurrently, new applications for sequencing have emerged, including gene expression analysis, discovery of genomic variants and metagenomics, and each of these has different needs and challenges in terms of assembly. We survey the theoretical foundations that underlie modern assembly and highlight the options and practical trade-offs that need to be considered, focusing on how individual features address the needs of specific applications. We also review key software and the interplay between experimental design and efficacy of assembly.

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Figure 1: Methods for assembly validation.
Figure 2: Comparison of isolate genome, single-cell and metagenomic assembly.

Change history

  • 05 February 2013

    In the above article, the paper cited as reference 89 was incorrect. The correct reference has now been added in its place.

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Acknowledgements

N.N. was supported by the Agency for Science, Technology and Research (A*STAR), Singapore. M.P. was supported in part by the US National Science Foundation (grants IIS-1117247 and IIS-0844494) and by the Bill and Melinda Gates Foundation.

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Authors and Affiliations

  1. Computational and Systems Biology, Genome Institute of Singapore, 138672, Singapore

    Niranjan Nagarajan

  2. Department of Computer Science, University of Maryland, College Park, 20742, Maryland, USA

    Mihai Pop

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Correspondence to Mihai Pop.

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Supplementary information

Supplementary information S1 (table)

Other assembly programs. (PDF 143 kb)

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FURTHER INFORMATION

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The Assemblathon

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Glossary

Paired-end data

Data from a pair of reads sequenced from ends of the same DNA fragment. The genomic distance between the reads is approximately known and is used to constrain assembly solutions. See also 'mate-pair read'.

Mate-pair data

Data from a pair of reads sequenced from the same circularized DNA fragment. The circularization step allows for larger fragments sizes to be used. They provide the same information as paired-end reads to the assembler.

Contiguous sequence

(Contig). A sequence reconstructed by assembling together multiple reads.

Read

The sequence generated by a sequencing machine from a DNA fragment.

Overlap

The relationship between two reads, the ends of which have highly similar sequences. The minimum length allowed for the corresponding sequence is an important parameter in assembly.

Scaffolds

An ordered collection of contiguous sequences (contigs), the relative placement of which is typically inferred from mate-pair reads and other information. The sequence within the gaps between the contigs is usually not known.

Library

A collection of paired-end or mate-pair reads derived from DNA fragments with a tightly controlled size range.

Depth of coverage

The average number of reads covering a particular base in the sequence being assembled.

N50

A statistic used for assessing the contiguity of a genome assembly. The contigs in an assembly are sorted by size and added, starting with the largest. The size of the contig is reported that makes the total greater than or equal to 50% of the genome size.

Isolate genome

The genome of a single organism isolated through culture, for which a substantial quantity of DNA can be obtained.

k-mers

Strings of k consecutive letters extracted from a longer sequence, such as a read or a reference assembly.

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Nagarajan, N., Pop, M. Sequence assembly demystified. Nat Rev Genet 14, 157–167 (2013). https://doi.org/10.1038/nrg3367

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