Integrative single-cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer

The recent advance of single-cell copy number variation analysis plays an essential role in addressing intra-tumor heterogeneity, identifying tumor subgroups, and restoring tumor evolving trajectories at single-cell scale. Pleasant visualization of copy number analysis results boosts productive scientific exploration, validation, and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, scSVAS, for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell analysis. Compared with other tools, scSVAS manifests the most comprehensive functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may make scientific discoveries, share interactive visualization, and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing, and publishing single-cell copy number variation profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.

Download Full-text

Copy-scAT: An R package for detection of large-scale and focal copy number alterations in single-cell chromatin accessibility datasets

10.1101/2020.09.21.305516 ◽

2020 ◽

Author(s):

Ana Nikolic ◽

Divya Singhal ◽

Katrina Ellestad ◽

Michael Johnston ◽

Aaron Gillmor ◽

...

Keyword(s):

Single Cell ◽

Copy Number ◽

Large Scale ◽

Malignant Cell ◽

Chromatin Accessibility ◽

Clinical Samples ◽

Cell Populations ◽

Copy Number Alterations ◽

Widespread Application ◽

Organ Systems

ABSTRACTThe single-cell assay for transposase accessible chromatin (scATAC) is an invaluable asset to profile the epigenomic landscape of heterogeneous cells populations in complex tissue and organ systems. However, the lack of tools that enable the use of scATAC data to discriminate between malignant and non-malignant cells has prevented the widespread application of this technique to clinical tumor samples. Here we describe Copy-scAT, a new computational tool that uses scATAC data to infer both large-scale and focal copy number alterations. Copy-scAT can call both clonal and subclonal copy number changes, allowing identification of cancer cells and cell populations that putatively constitute the tumor microenvironment. Copy-scAT therefore enables downstream chromatin accessibility studies that focus on malignant or non-malignant cell populations in clinical samples that are profiled by scATAC.

Download Full-text

Single-cell analysis of chromatin silencing programs in development and tumor progression

10.1101/2020.09.04.282418 ◽

2020 ◽

Author(s):

Steven J. Wu ◽

Scott N. Furlan ◽

Anca B. Mihalas ◽

Hatice S. Kaya-Okur ◽

Abdullah H. Feroze ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Cell Types ◽

Chromatin Accessibility ◽

Polycomb Group ◽

Cell Analysis ◽

Tumor Patient ◽

Primary Sample ◽

Before And After

Single-cell analysis has become a powerful approach for the molecular characterization of complex tissues. Methods for quantifying gene expression1 and chromatin accessibility2 of single cells are now well-established, but analysis of chromatin regions with specific histone modifications has been technically challenging. Here, we adapt the recently published CUT&Tag method3 to scalable single-cell platforms to profile chromatin landscapes in single cells (scCUT&Tag) from complex tissues. We focus on profiling Polycomb Group (PcG) silenced regions marked by H3K27 trimethylation (H3K27me3) in single cells as an orthogonal approach to chromatin accessibility for identifying cell states. We show that scCUT&Tag profiling of H3K27me3 distinguishes cell types in human blood and allows the generation of cell-type-specific PcG landscapes from heterogeneous tissues. Furthermore, we use scCUT&Tag to profile H3K27me3 in a brain tumor patient before and after treatment, identifying cell types in the tumor microenvironment and heterogeneity in PcG activity in the primary sample and after treatment.

Download Full-text

Profiling of transcribed cis-regulatory elements in single cells

10.1101/2021.04.04.438388 ◽

2021 ◽

Author(s):

Jonathan Moody ◽

Tsukasa Kouno ◽

Akari Suzuki ◽

Youtaro Shibayama ◽

Chikashi Terao ◽

...

Keyword(s):

Gene Regulation ◽

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Cell Analysis ◽

Cell Type ◽

Simultaneous Quantification ◽

Promoter Usage

Profiling of cis-regulatory elements (CREs, mostly promoters and enhancers) in single cells allows the interrogation of the cell-type and -state specific contexts of gene regulation and genetic predisposition to diseases. Here we demonstrate single-cell RNA-5′end-sequencing (sc-end5-seq) methods can detect transcribed CREs (tCREs), enabling simultaneous quantification of gene expression and enhancer activities in a single assay with no extra cost. We show enhancer RNAs can be effectively detected using sc-end5-seq methods with either random or oligo(dT) priming. To analyze tCREs in single cells, we developed SCAFE (Single Cell Analysis of Five-prime Ends) to identify genuine tCREs and analyze their activities (https://github.com/chung-lab/scafe). As compared to accessible CRE (aCRE, based on chromatin accessibility), tCREs are more accurate in predicting CRE interactions by co-activity, more sensitive in detecting shifts in alternative promoter usage and more enriched in diseases heritability. Our results highlight additional dimensions within sc-end5-seq data which can be used for interrogating gene regulation and disease heritability.

Download Full-text

Alleloscope: Integrative single cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer

10.1101/2020.10.23.349407 ◽

2020 ◽

Author(s):

Chi-Yun Wu ◽

Billy T. Lau ◽

Heonseok Kim ◽

Anuja Sathe ◽

Susan M. Grimes ◽

...

Keyword(s):

Single Cell ◽

Chromatin Remodeling ◽

Copy Number ◽

Gastric Cancer Cell Line ◽

Chromatin Accessibility ◽

Intratumor Heterogeneity ◽

Tumor Evolution ◽

Copy Number Aberrations ◽

Allele Specific ◽

Allelic Copy Number

AbstractCancer progression is driven by both somatic copy number aberrations (CNAs) and chromatin remodeling, yet little is known about the interplay between these two classes of events in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single cell DNA and ATAC sequencing data, either separately or in combination. This approach allows for integrative multi-omic analysis of allele-specific copy number and chromatin accessibility on the same cell. On scDNA-seq data from gastric, colorectal, and breast cancer samples, with extensive validation using matched linked-read sequencing, Alleloscope finds pervasive occurrence of highly complex, multi-allelic copy number aberrations, where cells that carry varying allelic configurations adding to the same total copy number co-evolve within a tumor. The contributions of such allele-specific events to intratumor heterogeneity have been under-reported and under-studied due to the lack of methods for their detection. On scATAC-seq from two basal cell carcinoma samples and a gastric cancer cell line, Alleloscope detects multi-allelic copy number events and copy neutral loss-of-heterozygosity, enabling the dissection of the contributions of chromosomal instability and chromatin remodeling in tumor evolution.

Download Full-text

Alleloscope: Integrative single cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer

10.21203/rs.3.rs-98536/v1 ◽

2020 ◽

Author(s):

Chi-Yun Wu ◽

Billy Lau ◽

Heonseok Kim ◽

Anuja Sathe ◽

Susan M Grimes ◽

...

Keyword(s):

Single Cell ◽

Chromatin Remodeling ◽

Copy Number ◽

Gastric Cancer Cell Line ◽

Chromatin Accessibility ◽

Intratumor Heterogeneity ◽

Tumor Evolution ◽

Copy Number Aberrations ◽

Allele Specific ◽

Allelic Copy Number

Abstract Cancer progression is driven by both somatic copy number aberrations (CNAs) and chromatin remodeling, yet little is known about the interplay between these two classes of events in shaping the clonal diversity of cancers. We present Alleloscope, a method for allele-specific copy number estimation that can be applied to single cell DNA and ATAC sequencing data, either separately or in combination. This approach allows for integrative multi-omic analysis of allele-specific copy number and chromatin accessibility on the same cell. On scDNA-seq data from gastric, colorectal, and breast cancer samples, with extensive validation using matched linked-read sequencing, Alleloscope finds pervasive occurrence of highly complex, multi-allelic copy number aberrations, where cells that carry varying allelic configurations adding to the same total copy number co-evolve within a tumor. The contributions of such allele-specific events to intratumor heterogeneity have been under-reported and under-studied due to the lack of methods for their detection. On scATAC-seq from two basal cell carcinoma samples and a gastric cancer cell line, Alleloscope detects multi-allelic copy number events and copy neutral loss-of-heterozygosity, enabling the dissection of the contributions of chromosomal instability and chromatin remodeling in tumor evolution.

Download Full-text

ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis

Nature Genetics ◽

10.1038/s41588-021-00790-6 ◽

2021 ◽

Vol 53 (3) ◽

pp. 403-411 ◽

Cited By ~ 1

Author(s):

Jeffrey M. Granja ◽

M. Ryan Corces ◽

Sarah E. Pierce ◽

S. Tansu Bagdatli ◽

Hani Choudhry ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Chromatin Accessibility ◽

Cell Analysis ◽

Software Suite ◽

Cell Clustering ◽

Gene Regulatory ◽

Regulatory Landscapes ◽

Scalable Software

AbstractThe advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells.

Download Full-text