Targeted Nanopore Sequencing with Cas9 for studies of methylation, structural variants, and mutations

Nanopore sequencing technology can rapidly and directly interrogate native DNA molecules. Often we are interested only in interrogating specific areas at high depth, but conventional enrichment methods have thus far proved unsuitable for long reads1. Existing strategies are currently limited by high input DNA requirements, low yield, short (<5kb) reads, time-intensive protocols, and/or amplification or cloning (losing base modification information). In this paper, we describe a technique utilizing the ability of Cas9 to introduce cuts at specific locations and ligating nanopore sequencing adaptors directly to those sites, a method we term ‘nanopore Cas9 Targeted-Sequencing’ (nCATS). We have demonstrated this using an Oxford Nanopore MinION flow cell (Capacity >10Gb+) to generate a median 165X coverage at 10 genomic loci with a median length of 18kb, representing a several hundred-fold improvement over the 2-3X coverage achieved without enrichment. We performed a pilot run on the smaller Flongle flow cell (Capacity ~1Gb), generating a median coverage of 30X at 11 genomic loci with a median length of 18kb. Using panels of guide RNAs, we show that the high coverage data from this method enables us to (1) profile DNA methylation patterns at cancer driver genes, (2) detect structural variations at known hot spots, and (3) survey for the presence of single nucleotide mutations. Together, this provides a low-cost method that can be applied even in low resource settings to directly examine cellular DNA. This technique has extensive clinical applications for assessing medically relevant genes and has the versatility to be a rapid and comprehensive diagnostic tool. We demonstrate applications of this technique by examining the well-characterized GM12878 cell line as well as three breast cell lines (MCF-10A, MCF-7, MDA-MB-231) with varying tumorigenic potential as a model for cancer. Contributions TG and WT constructed the study. TG performed the experiments. TG, IL, and FS analyzed the data. TG, JG, ER, RB and AH and developed the method. TG and WT wrote the paper

[1]  A. Mechelli,et al.  Clustering analysis , 2020, Machine Learning.

[2]  Bernhard M. Schuldt,et al.  Analysis of short tandem repeat expansions and their methylation state with nanopore sequencing , 2019, Nature Biotechnology.

[3]  Christos Proukakis,et al.  Evaluation of the detection of GBA missense mutations and other variants using the Oxford Nanopore MinION , 2019, Molecular genetics & genomic medicine.

[4]  Evan E. Eichler,et al.  Characterizing the Major Structural Variant Alleles of the Human Genome , 2019, Cell.

[5]  J. Simpson,et al.  Simultaneous profiling of chromatin accessibility and methylation on human cell lines with nanopore sequencing , 2018, bioRxiv.

[6]  Xuchen Cao,et al.  KRT19 and CEACAM5 mRNA-marked circulated tumor cells indicate unfavorable prognosis of breast cancer patients , 2018, Breast Cancer Research and Treatment.

[7]  Bernhard M. Schuldt,et al.  Repeat expansion and methylation state analysis with nanopore sequencing , 2018, bioRxiv.

[8]  William Stafford Noble,et al.  Integrative detection and analysis of structural variation in cancer genomes , 2018, Nature Genetics.

[9]  Mark T. W. Ebbert,et al.  Long-read sequencing across the C9orf72 ‘GGGGCC’ repeat expansion: implications for clinical use and genetic discovery efforts in human disease , 2018, Molecular Neurodegeneration.

[10]  Heng Li,et al.  Minimap2: pairwise alignment for nucleotide sequences , 2017, Bioinform..

[11]  Gkikas Magiorkinis,et al.  Multiplexed Targeted Sequencing for Oxford Nanopore MinION: A Detailed Library Preparation Procedure. , 2018, Methods in molecular biology.

[12]  Ryan L. Collins,et al.  Multi-platform discovery of haplotype-resolved structural variation in human genomes , 2017, bioRxiv.

[13]  Michael C. Schatz,et al.  Accurate detection of complex structural variations using single molecule sequencing , 2017, Nature Methods.

[14]  Vineet Bafna,et al.  HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies , 2017, Genome research.

[15]  Winston Timp,et al.  Detecting DNA cytosine methylation using nanopore sequencing , 2017, Nature Methods.

[16]  Y. Ebenstein,et al.  Cas9-Assisted Targeting of CHromosome segments (CATCH) for targeted nanopore sequencing and optical genome mapping , 2017, bioRxiv.

[17]  Anshul Kundaje,et al.  Umap and Bismap: quantifying genome and methylome mappability , 2016, bioRxiv.

[18]  Mingming Jia,et al.  COSMIC: somatic cancer genetics at high-resolution , 2016, Nucleic Acids Res..

[19]  F. Balloux,et al.  Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast , 2016, Nature Communications.

[20]  D. Calistri,et al.  GSTP1 Methylation and Protein Expression in Prostate Cancer: Diagnostic Implications , 2016, Disease markers.

[21]  G. McVean,et al.  A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree , 2016, bioRxiv.

[22]  G. Stein,et al.  Histone H3 lysine 4 acetylation and methylation dynamics define breast cancer subtypes , 2016, Oncotarget.

[23]  Gillian,et al.  Histone H 3 lysine 4 acetylation and methylation dynamics define breast cancer subtypes , 2016 .

[24]  Alexa B. R. McIntyre,et al.  Extensive sequencing of seven human genomes to characterize benchmark reference materials , 2015, Scientific Data.

[25]  L. Rönnstrand,et al.  Keratin 19 expression correlates with poor prognosis in breast cancer , 2014, Molecular Biology Reports.

[26]  Jennifer A. Doudna,et al.  DNA interrogation by the CRISPR RNA-guided endonuclease Cas9 , 2014, Nature.

[27]  Cristina Botta,et al.  Differences and homologies of chromosomal alterations within and between breast cancer cell lines: a clustering analysis , 2014, Molecular Cytogenetics.

[28]  Andrew P. Feinberg,et al.  Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host , 2013, Nature Reviews Cancer.

[29]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[30]  P. Deininger.  Alu elements: know the SINEs , 2011, Genome Biology.

[31]  Heng Li,et al.  A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data , 2011, Bioinform..

[32]  C. Cole,et al.  COSMIC: the catalogue of somatic mutations in cancer , 2011, Genome Biology.

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

[34]  M. King,et al.  BRCA1 and BRCA2 and the genetics of breast and ovarian cancer. , 2001, Human molecular genetics.

[35]  T. Hsu,et al.  Cytogenetic analysis on eight human breast tumor cell lines: high frequencies of 1q, 11q and HeLa-like marker chromosomes. , 1981, Cancer genetics and cytogenetics.