Reducing assembly complexity of microbial genomes with single-molecule sequencing

Genome Biol. 2013;14(9):R101. doi: 10.1186/gb-2013-14-9-r101.

Abstract

Background: The short reads output by first- and second-generation DNA sequencing instruments cannot completely reconstruct microbial chromosomes. Therefore, most genomes have been left unfinished due to the significant resources required to manually close gaps in draft assemblies. Third-generation, single-molecule sequencing addresses this problem by greatly increasing sequencing read length, which simplifies the assembly problem.

Results: To measure the benefit of single-molecule sequencing on microbial genome assembly, we sequenced and assembled the genomes of six bacteria and analyzed the repeat complexity of 2,267 complete bacteria and archaea. Our results indicate that the majority of known bacterial and archaeal genomes can be assembled without gaps, at finished-grade quality, using a single PacBio RS sequencing library. These single-library assemblies are also more accurate than typical short-read assemblies and hybrid assemblies of short and long reads.

Conclusions: Automated assembly of long, single-molecule sequencing data reduces the cost of microbial finishing to $1,000 for most genomes, and future advances in this technology are expected to drive the cost lower. This is expected to increase the number of completed genomes, improve the quality of microbial genome databases, and enable high-fidelity, population-scale studies of pan-genomes and chromosomal organization.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Base Sequence
  • Contig Mapping / methods*
  • Contig Mapping / statistics & numerical data
  • Escherichia coli / genetics
  • Francisella tularensis / genetics
  • Genome Size
  • Genome, Archaeal*
  • Genome, Bacterial*
  • Genomic Library
  • Mannheimia haemolytica / genetics
  • Molecular Sequence Data
  • Salmonella enterica / genetics
  • Sequence Analysis, DNA / economics
  • Sequence Analysis, DNA / methods*
  • Sequence Analysis, DNA / statistics & numerical data
  • Software*