Received on ,
Accepted on ,

Brief Communications

High-Resolution Melting Curve Analysis of Genomic and Whole-Genome Amplified DNA

¹ Channing Laboratory, Brigham and Women's Hospital, Boston, MA, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, and Harvard Medical School, Boston, MA
² Channing Laboratory, Brigham and Women's Hospital, Boston, MA
³ Channing Laboratory, Brigham and Women's Hospital, Boston, MA, and Harvard Medical School, Boston, MA

^* To whom correspondence should be addressed. E-mail: michael.cho{at}channing.harvard.edu.

BACKGROUND: High-resolution melting curve analysis is an accurate method for mutation detection in genomic DNA. However, performance in whole-genome amplified (WGA) vs genomic DNA has not been directly compared.

METHODS: In 39 paired genomic and WGA samples, 23 amplicons from 9 genes were PCR amplified and analyzed by high-resolution melting curve analysis using the 96-well LightScanner (Idaho Technology). We used genotyping and bidirectional resequencing to verify melting curve results.

RESULTS: Melting patterns were concordant between the genomic and WGA samples in 823 of 863 (95%) analyzed sample pairs. Of the discordant patterns, there was an overrepresentation of alternate melting curve patterns in the WGA samples, suggesting the presence of a mutation (false positives). Targeted resequencing in 135 genomic and 136 WGA samples revealed 43 single nucleotide polymorphisms (SNPs). All SNPs detected in genomic samples were also detected in WGA. Additional genotyping and sequencing allowed the classification of 628 genomic and 614 WGA amplicon samples. Heterozygous variants were identified by non–wild-type melting pattern in 98% of genomic and 97% of WGA samples (P = 0.11). Wild types were correctly classified in 99% of genomic and 91% of WGA samples (P < 0.001).

CONCLUSIONS: In WGA DNA, high-resolution DNA melting curve analysis is a sensitive tool for SNP discovery through detection of heterozygote variants; however, it may misclassify a greater number of wild-type samples.