Frontiers in Bioengineering and Biotechnology (May 2016)

Efficient synergistic single-cell genome assembly

  • Narjes S. Movahedi,
  • Mallory eEmbree,
  • Harish eNagarajan,
  • Karsten eZengler,
  • Hamidreza eChitsaz

DOI
https://doi.org/10.3389/fbioe.2016.00042
Journal volume & issue
Vol. 4

Abstract

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As the vast majority of all microbes are unculturable, single-cell sequencing has become a significant method to gain insight into microbial physiology. Single-cell sequencing methods, currently powered by multiple displacement genome amplification (MDA), have passed important milestones such as finishing and closing the genome of a prokaryote. However, the quality and reliability of genome assemblies from single cells are still unsatisfactory due to uneven coverage depth and the absence of scattered chunks of the genome in the final collection of reads caused by MDA bias. In this work, our new algorithm Hybrid De novo Assembler (HyDA) demonstrates the power of co-assembly of multiple single-cell genomic data sets through significant improvement of the assembly quality in terms of predicted functional elements and length statistics. Co-assemblies contain significantly more base pairs and protein coding genes, cover more subsystems, and consist of longer contigs compared to individual assemblies by the same algorithm as well as state-of-the-art single-cell assemblers SPAdes and IDBA-UD. Hybrid emph{De novo} Assembler (HyDA) is also able to avoid chimeric assemblies by detecting and separating shared and exclusive pieces of sequence for input data sets. By replacing one deep single-cell sequencing experiment with a few single-cell sequencing experiments of lower depth, the co-assembly method can hedge against the risk of failure and loss of the sample, without significantly increasing sequencing cost. Application of the single-cell co-assembler HyDA to the study of three uncultured members of an alkane-degrading methanogenic community validated the usefulness of the co-assembly concept. HyDA is open source and publicly available at http://chitsazlab.org/software.html and the raw reads are available at http://chitsazlab.org/research.html.

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