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Identifying the best PCR enzyme for library amplification in NGS

Authors :
Michael A Quail
Craig Corton
James Uphill
Jacqueline Keane
Yong Gu
Publication Year :
2022
Publisher :
Cold Spring Harbor Laboratory, 2022.

Abstract

BackgroundPCR amplification is a necessary step in many next generation sequencing (NGS) library preparation methods[1] [2]. Whilst many PCR enzymes are developed to amplify single targets efficiently, accurately and with specificity, few are developed to meet the challenges imposed by NGS PCR, namely unbiased amplification of a wide range of different sizes and GC content. As a result PCR amplification during NGS library prep often results in bias toward GC neutral and smaller fragments. As NGS has matured, optimised NGS library prep kits and polymerase formulations have emerged and in this study we have tested a wide selection of available enzymes for both short read Illumina library preparation and long fragment amplification ahead of long-read sequencing.ResultsWe tested over 20 different Hi-fidelity PCR enzymes/NGS amplification mixes on a range of Illumina library templates of varying GC content and composition, and find that both yield and genome coverage uniformity characteristics of the commercially available enzymes varied dramatically. Three enzymes Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) “Equinox” and Takara Ex Premier were found to give a consistent performance, over all genomes, that mirrored closely that observed for PCR free datasets. We also test a range of enzymes for long read sequencing by amplifying size fractionated S. cerevisiae DNA of average size 21.6 and 13.4kb respectively.ConclusionThe enzymes of choice for short read (Illumina) library fragment amplification are Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) “Equinox” and Takara Ex Premier, with RepliQa also being the best performing enzyme from the enzymes tested for long fragment amplification prior to long read sequencing.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....5dba9ee5f3ef26a9849bce05cea4832f
Full Text :
https://doi.org/10.1101/2022.10.31.514486