A systematic comparison of error correction enzymes by next-generation sequencing
Abstract
Gene synthesis, the process of assembling genelength fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.
- Authors:
-
[1];
[1]
- Univ. of California, Los Angeles, CA (United States); UCLA-DOE Inst. for Genomics and Proteomics, Los Angeles, CA (United States)
- Univ. of Pennsylvania, Philadelphia, PA (United States)
- Univ. of California, Los Angeles, CA (United States)
- Brigham and Women's Hospital (Harvard Medical School), Boston, MA (United States); Wyss Inst. for Biologically Inspired Engineering, Boston, MA (United States)
- Publication Date:
- Research Org.:
- Univ. of California, Los Angeles, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1425978
- Grant/Contract Number:
- FC02-02ER63421
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nucleic Acids Research
- Additional Journal Information:
- Journal Volume: 45; Journal Issue: 15; Journal ID: ISSN 0305-1048
- Publisher:
- Oxford University Press
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Lubock, Nathan B., Zhang, Di, Sidore, Angus M., Church, George M., and Kosuri, Sriram. A systematic comparison of error correction enzymes by next-generation sequencing. United States: N. p., 2017.
Web. doi:10.1093/nar/gkx691.
Lubock, Nathan B., Zhang, Di, Sidore, Angus M., Church, George M., & Kosuri, Sriram. A systematic comparison of error correction enzymes by next-generation sequencing. United States. https://doi.org/10.1093/nar/gkx691
Lubock, Nathan B., Zhang, Di, Sidore, Angus M., Church, George M., and Kosuri, Sriram. Tue .
"A systematic comparison of error correction enzymes by next-generation sequencing". United States. https://doi.org/10.1093/nar/gkx691. https://www.osti.gov/servlets/purl/1425978.
@article{osti_1425978,
title = {A systematic comparison of error correction enzymes by next-generation sequencing},
author = {Lubock, Nathan B. and Zhang, Di and Sidore, Angus M. and Church, George M. and Kosuri, Sriram},
abstractNote = {Gene synthesis, the process of assembling genelength fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.},
doi = {10.1093/nar/gkx691},
journal = {Nucleic Acids Research},
number = 15,
volume = 45,
place = {United States},
year = {Tue Aug 01 00:00:00 EDT 2017},
month = {Tue Aug 01 00:00:00 EDT 2017}
}
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Works referencing / citing this record:
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