Q-RRBS: a quantitative reduced representation bisulfite sequencing method for single-cell methylome analyses

Reduced representation bisulfite sequencing (RRBS) is a powerful method of DNA methylome profiling that can be applied to single cells. However, no previous report has described how PCR-based duplication-induced artifacts affect the accuracy of this method when measuring DNA methylation levels. For quantifying the effects of duplication-induced artifacts on methylome profiling when using ultra-trace amounts of starting material, we developed a novel method, namely quantitative RRBS (Q-RRBS), in which PCR-induced duplication is excluded through the use of unique molecular identifiers (UMIs). By performing Q-RRBS on varying amounts of starting material, we determined that duplication-induced artifacts were more severe when small quantities of the starting material were used. However, through using the UMIs, we successfully eliminated these artifacts. In addition, Q-RRBS could accurately detect allele-specific methylation in absence of allele-specific genetic variants. Our results demonstrate that Q-RRBS is an optimal strategy for DNA methylation profiling of single cells or samples containing ultra-trace amounts of cells.

[1]  Andrew L. Miller,et al.  Ca2+ signaling and early embryonic patterning during the blastula and gastrula periods of zebrafish and Xenopus development. , 2006, Biochimica et biophysica acta.

[2]  Tony Z. Jia,et al.  Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes , 2012, Proceedings of the National Academy of Sciences.

[3]  Lee E. Edsall,et al.  Human DNA methylomes at base resolution show widespread epigenomic differences , 2009, Nature.

[4]  P. Rorsman,et al.  Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. , 2005, Genome research.

[5]  Zachary D. Smith,et al.  Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution , 2010, Nature Methods.

[6]  Felix Krueger,et al.  Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications , 2011, Bioinform..

[7]  Yao-Cheng Lin,et al.  Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations , 2014, Nature Communications.

[8]  T. Ogata,et al.  Imprinting of human GRB10 and its mutations in two patients with Russell-Silver syndrome. , 2000, American journal of human genetics.

[9]  Julie V. Harness,et al.  Genome-wide parent-of-origin DNA methylation analysis reveals the intricacies of human imprinting and suggests a germline methylation-independent mechanism of establishment , 2014, Genome research.

[10]  Francine E. Garrett-Bakelman,et al.  Base-Pair Resolution DNA Methylation Sequencing Reveals Profoundly Divergent Epigenetic Landscapes in Acute Myeloid Leukemia , 2012, PLoS genetics.

[11]  T. Fennell,et al.  Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries , 2011, Genome Biology.

[12]  D. Conrad,et al.  Global variation in copy number in the human genome , 2006, Nature.

[13]  Jialong Liang,et al.  Single-cell sequencing technologies: current and future. , 2014, Journal of genetics and genomics = Yi chuan xue bao.

[14]  O. Stegle,et al.  Single-Cell Genome-Wide Bisulfite Sequencing for Assessing Epigenetic Heterogeneity , 2014, Nature Methods.

[15]  M. Surani,et al.  DNA methylation dynamics during the mammalian life cycle , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[16]  Xiuqing Zhang,et al.  Double restriction-enzyme digestion improves the coverage and accuracy of genome-wide CpG methylation profiling by reduced representation bisulfite sequencing , 2013, BMC Genomics.

[17]  J. Fulka,et al.  DNA methylation pattern in human zygotes and developing embryos. , 2004, Reproduction.

[18]  A. Bird.  DNA methylation patterns and epigenetic memory. , 2002, Genes & development.

[19]  F. Tang,et al.  Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing , 2013, Genome research.

[20]  N. Friedman,et al.  Dynamic and static maintenance of epigenetic memory in pluripotent and somatic cells , 2014, Nature.

[21]  Zachary D. Smith,et al.  Gel-free multiplexed reduced representation bisulfite sequencing for large-scale DNA methylation profiling , 2012, Genome Biology.

[22]  F. Tang,et al.  The DNA methylation landscape of human early embryos , 2014, Nature.

[23]  Alvin C. Powers,et al.  Assessment of Human Pancreatic Islet Architecture and Composition by Laser Scanning Confocal Microscopy , 2005, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[24]  D. Bonthron,et al.  The cell cycle control gene ZAC/PLAGL1 is imprinted--a strong candidate gene for transient neonatal diabetes. , 2000, Human molecular genetics.

[25]  Matthew D Dean,et al.  Genomic landscape of human allele-specific DNA methylation , 2012, Proceedings of the National Academy of Sciences.

[26]  Rudolf Jaenisch,et al.  Role for DNA methylation in genomic imprinting , 1993, Nature.

[27]  S. Linnarsson,et al.  Counting absolute numbers of molecules using unique molecular identifiers , 2011, Nature Methods.

[28]  R. Sandberg,et al.  Full-Length mRNA-Seq from single cell levels of RNA and individual circulating tumor cells , 2012, Nature Biotechnology.

[29]  G. Kelsey,et al.  Genome-wide analysis of DNA methylation in low cell numbers by reduced representation bisulfite sequencing. , 2012, Methods in molecular biology.

[30]  O. Tsutsumi,et al.  Human PEG1/MEST, an imprinted gene on chromosome 7. , 1997, Human molecular genetics.

[31]  Nathan C. Sheffield,et al.  Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics , 2015, Cell reports.

[32]  Zachary D. Smith,et al.  A unique regulatory phase of DNA methylation in the early mammalian embryo , 2012, Nature.

[33]  M. Esteller.  Cancer epigenomics: DNA methylomes and histone-modification maps , 2007, Nature Reviews Genetics.

[34]  Hao Wu,et al.  Early embryos reprogram DNA methylation in two steps. , 2012, Cell stem cell.

[35]  Michael Q. Zhang,et al.  Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications , 2010, Nature Biotechnology.

[36]  L. Weinstein,et al.  Identification of a Methylation Imprint Mark within the Mouse Gnas Locus , 2000, Molecular and Cellular Biology.

[37]  M. Suyama,et al.  Genome-Wide Analysis of DNA Methylation Dynamics during Early Human Development , 2014, PLoS genetics.

[38]  Catalin C. Barbacioru,et al.  mRNA-Seq whole-transcriptome analysis of a single cell , 2009, Nature Methods.

[39]  X. Xie,et al.  Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients , 2013, Proceedings of the National Academy of Sciences.

[40]  Gioele La Manno,et al.  Quantitative single-cell RNA-seq with unique molecular identifiers , 2013, Nature Methods.

[41]  Zohar Mukamel,et al.  Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues , 2012, Nature Genetics.

[42]  Aviv Regev,et al.  DNA methylation dynamics of the human preimplantation embryo , 2014, Nature.

[43]  P. Campbell,et al.  Single-cell mutational profiling and clonal phylogeny in cancer , 2013, Genome research.