Open AccessAccurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands
Author(s) -
Dong Xing,
Longzhi Tan,
Chi-Han Chang,
Heng Li,
Xiaohui Xie
Publication year - 2021
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2013106118
Subject(s) - false positive paradox , computational biology , biology , genome , transposable element , single cell analysis , multiple displacement amplification , dna sequencing , false positives and false negatives , dna , genetics , sequencing by hybridization , single cell sequencing , polymerase chain reaction , cell , dna sequencer , computer science , gene , dna extraction , mutation , exome sequencing , machine learning
Single-nucleotide variants (SNVs), pertinent to aging and disease, occur sporadically in the human genome, hence necessitating single-cell measurements. However, detection of single-cell SNVs suffers from false positives (FPs) due to intracellular single-stranded DNA damage and the process of whole-genome amplification (WGA). Here, we report a single-cell WGA method termed multiplexed end-tagging amplification of complementary strands (META-CS), which eliminates nearly all FPs by virtue of DNA complementarity, and achieved the highest accuracy thus far. We validated META-CS by sequencing kindred cells and human sperm, and applied it to other human tissues. Investigation of mature single human neurons revealed increasing SNVs with age and potentially unrepaired strand-specific oxidative guanine damage. We determined SNV frequencies along the genome in differentiated single human blood cells, and identified cell type-dependent mutational patterns for major types of lymphocytes.