Detection of chromosomal structural alterations in single cells by SNP arrays: a systematic survey of amplification bias and optimized workflow.

• Main Authors: Kazuya Iwamoto, Miki Bundo, Junko Ueda, Yoko Nakano, Wataru Ukai, Eri Hashimoto, Toshikazu Saito, Tadafumi Kato
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2007-12-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0001306

<h4>Background</h4>In single-cell human genome analysis using whole-genome amplified product, a strong amplification bias involving allele dropout and preferential amplification hampers the quality of results. Using an oligonucleotide single nucleotide polymorphism (SNP) array, we systematically examined the nature of this amplification bias, including frequency, degree, and preference for genomic location, and we assessed the effects of this amplification bias on subsequent genotype and chromosomal copy number analyses.<h4>Methodology/principal findings</h4>We found a large variability in amplification bias among the amplified products obtained by multiple displacement amplification (MDA), and this bias had a severe effect on the genotype and chromosomal copy number analyses. We established optimal experimental conditions for pre-screening for high-quality amplified products, processing array data, and analyzing chromosomal structural alterations. Using this optimized protocol, we successfully detected previously unidentified chromosomal structural alterations in single cells from a lymphoblastoid cell line. These alterations were subsequently confirmed by karyotype analysis. In addition, we successfully obtained reproducible chromosomal copy number profiles of single cells from the cell line with a complex karyotype, indicating the applicability and potential of our optimized workflow.<h4>Conclusions/significance</h4>Our results suggest that the quality of amplification products should be critically assessed before using them for genomic analyses. The method of MDA-based whole-genome amplification followed by SNP array analysis described here will be useful for exploring chromosomal alterations in single cells.