Performance comparisons of methylation and structural variants from low-input whole-genome methylation sequencing

Author:

Sun Zhifu1ORCID,Behati Saurabh1,Wang Panwen1,Bhagwate Aditya1,McDonough Samantha2,Wang Vivian2,Taylor William3,Cunningham Julie2,Kisiel John3

Affiliation:

1. Division of Computational Biology, Mayo Clinic, Rochester, MN 55905, USA

2. Medical Genome Facility, Mayo Clinic, Rochester, MN 55905, USA

3. Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, MN 55905, USA

Abstract

Aim: Whole-genome methylation sequencing carries both DNA methylation and structural variant information (single nucleotide variant [SNV]; copy number variant [CNV]); however, limited data is available on the reliability of obtaining this information simultaneously from low-input DNA using various library preparation and sequencing protocols. Methods: A HapMap NA12878 sample was sequenced with three protocols (EM-sequencing, QIA-sequencing and Swift-sequencing) and their performance was compared on CpG methylation measurement and SNV and CNV detection. Results: At low DNA input (10–25 ng), EM-sequencing was superior in almost all metrics except CNV detection where all protocols were similar. EM-sequencing captured the highest number of CpGs and true SNVs. Conclusion: EM-sequencing is suitable to detect methylation, SNVs and CNVs from single sequencing with low-input DNA.

Funder

Exact Sciences

Mayo Clinic Center for Individualized Medicine

NIH

Publisher

Future Medicine Ltd

Subject

Cancer Research,Genetics

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