Reducing Gc-Bias And Improving Coverage Distribution In Illumina Sequencing Using The Kapa Biosystems Library Construction Method

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Next-generation sequencing (NGS) is increasingly used in the laboratory and clinic to identify genomic factors contributing to tumorigenesis, such as somatic mutations, DNA insertions and deletions, transcriptome and epigenetic changes, and chromosomal abnormalities. Because tumor specimen tissues are often quite limited or are from rare and precious samples, it is necessary to prepare sequencing libraries from minimal amounts of DNA. Consequently, limited DNA input necessitates amplification during NGS library preparation. Therefore, it is of great importance to amplify the library in an efficient and uniform manner to achieve reproducible amplification of the library fragments and limit GC content bias. Variable GC-bias among libraries is of particular importance for copy number variant (CNV) detection based on sequence coverage. Here, we compare the TruSeq DNA Sample Preparation Kit (Illumina Inc., San Diego, CA) and the KAPA Library Preparation Kit (Kapa Biosystems, Wilmington, MA) to determine which technique achieves optimal library coverage. The major difference between the methods is the DNA polymerase used for library enrichment. The Kapa HiFi polymerase was engineered to have higher fidelity and increased DNA affinity relative to the Herculase II Fusion DNA Polymerase (Agilent Technologies, Inc., Santa Clara, CA) that we used for library enrichment with the TruSeq kit. Thus, the Kapa HiFi polymerase should more efficiently amplify targets across a larger GC content range and improve sequence coverage uniformity. Relative to TruSeq-prepared libraries, the Kapa-prepared libraries had a larger mean insert size, more uniform coverage distribution, and better coverage of GC-rich regions of the genome. This was observed for DNA extracted from blood, cell lines, and formalin-fixed paraffin embedded (FFPE) tumor samples. More experiments are underway to determine the effect of the improved recovery of high-GC content DNA fragments on CNV detection. Citation Format: Aaron R. Thorner, Ashwini Sunkavalli, Ling Lin, Robert T. Jones, Laura Schubert, Matthew D. Ducar, Ravali Adusumilli, Deniz Nesli Dolcen, Liuda Ziaugra, Jack Lepine, Laura E. MacConaill, William C. Hahn, Matthew Meyerson, Paul Van Hummelen. Reducing GC-bias and improving coverage distribution in Illumina sequencing using the Kapa Biosystems library construction method. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3583. doi:10.1158/1538-7445.AM2014-3583