Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries

Despite the ever-increasing output of Illumina sequencing data, loci with extreme base compositions are often under-represented or absent. To evaluate sources of base-composition bias, we traced genomic sequences ranging from 6% to 90% GC through the process by quantitative PCR. We identified PCR du...

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Autores principales: Aird, Daniel, Ross, Michael G, Chen, Wei-Sheng, Danielsson, Maxwell, Fennell, Timothy, Russ, Carsten, Jaffe, David B, Nusbaum, Chad, Gnirke, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3188800/
https://www.ncbi.nlm.nih.gov/pubmed/21338519
http://dx.doi.org/10.1186/gb-2011-12-2-r18
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author Aird, Daniel
Ross, Michael G
Chen, Wei-Sheng
Danielsson, Maxwell
Fennell, Timothy
Russ, Carsten
Jaffe, David B
Nusbaum, Chad
Gnirke, Andreas
author_facet Aird, Daniel
Ross, Michael G
Chen, Wei-Sheng
Danielsson, Maxwell
Fennell, Timothy
Russ, Carsten
Jaffe, David B
Nusbaum, Chad
Gnirke, Andreas
author_sort Aird, Daniel
collection PubMed
description Despite the ever-increasing output of Illumina sequencing data, loci with extreme base compositions are often under-represented or absent. To evaluate sources of base-composition bias, we traced genomic sequences ranging from 6% to 90% GC through the process by quantitative PCR. We identified PCR during library preparation as a principal source of bias and optimized the conditions. Our improved protocol significantly reduces amplification bias and minimizes the previously severe effects of PCR instrument and temperature ramp rate.
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spelling pubmed-31888002011-10-07 Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries Aird, Daniel Ross, Michael G Chen, Wei-Sheng Danielsson, Maxwell Fennell, Timothy Russ, Carsten Jaffe, David B Nusbaum, Chad Gnirke, Andreas Genome Biol Method Despite the ever-increasing output of Illumina sequencing data, loci with extreme base compositions are often under-represented or absent. To evaluate sources of base-composition bias, we traced genomic sequences ranging from 6% to 90% GC through the process by quantitative PCR. We identified PCR during library preparation as a principal source of bias and optimized the conditions. Our improved protocol significantly reduces amplification bias and minimizes the previously severe effects of PCR instrument and temperature ramp rate. BioMed Central 2011 2011-02-21 /pmc/articles/PMC3188800/ /pubmed/21338519 http://dx.doi.org/10.1186/gb-2011-12-2-r18 Text en Copyright ©2011 Aird et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Aird, Daniel
Ross, Michael G
Chen, Wei-Sheng
Danielsson, Maxwell
Fennell, Timothy
Russ, Carsten
Jaffe, David B
Nusbaum, Chad
Gnirke, Andreas
Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title_full Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title_fullStr Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title_full_unstemmed Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title_short Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
title_sort analyzing and minimizing pcr amplification bias in illumina sequencing libraries
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3188800/
https://www.ncbi.nlm.nih.gov/pubmed/21338519
http://dx.doi.org/10.1186/gb-2011-12-2-r18
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