CoBATCH for high-throughput single-cell epigenomic profiling

ABSTRACTAn efficient, generalizable method for genome-wide mapping of single-cell histone modifications or chromatin-binding proteins is so far lacking. Here we develop CoBATCH, combinatorial barcoding and targeted chromatin release, for single-cell profiling of genomic distribution of chromatin-binding proteins in cell culture and tissue. Protein A in fusion to Tn5 transposase is enriched through specific antibodies to genomic regions and Tn5 generates indexed chromatin fragments ready for the library preparation and sequencing. Importantly, through a combinatorial barcoding strategy, we are able to measure epigenomic features up to tens of thousands single cells per experiment. CoBATCH produces not only high signal-to-noise features, but also ~10,000 reads per cells, allowing for efficiently deciphering epigenetic heterogeneity of cell populations and subtypes and inferring developmental histories. Thus, obviating specialized device, CoBATCH is easily deployable for any laboratories in life science and medicine.

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Antibody-guided Chromatin Tagmentation (ACT-seq)

10.21203/rs.2.1708/v1 ◽

2019 ◽

Author(s):

Benjamin Carter ◽

Keji Zhao ◽

Wai Lim Ku ◽

Jee Youn Kang ◽

Qingsong Tang

Keyword(s):

Single Cell ◽

Specific Antibody ◽

Binding Proteins ◽

Single Cells ◽

Protein A ◽

Histone Variants ◽

Chromatin Binding ◽

Histone Tail ◽

Genome Wide ◽

Tn5 Transposase

Abstract ACT-seq is a streamlined method for mapping genome-wide distributions of histone tail modifications, histone variants, and chromatin-binding proteins in a small number of or single cells. ACT-seq utilizes a fusion of Tn5 transposase to Protein A that is targeted to chromatin by a specific antibody, allowing chromatin fragmentation and sequence tag insertion specifically at genomic sites presenting the relevant antigen. The Tn5 transposase enables the use of an index multiplexing strategy (iACT-seq), which enables construction of thousands of single-cell libraries in one day by a single researcher without the need for drop-based fluidics or visual sorting. The protocol described here is intended for use with bulk-cell samples. The single-cell iACT-seq protocol is separate.

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Mapping Histone Modifications in Low Cell Number and Single Cells Using Antibody-guided Chromatin Tagmentation (ACT-seq)

10.1101/571208 ◽

2019 ◽

Cited By ~ 1

Author(s):

Benjamin Carter ◽

Wai Lim Ku ◽

Qingsong Tang ◽

Jee Youn Kang ◽

Keji Zhao

Keyword(s):

Single Cells ◽

Protein A ◽

Histone Variants ◽

Cell Number ◽

Attractive Alternative ◽

Chromatin Binding ◽

Epigenetic Marks ◽

Genome Wide ◽

Tn5 Transposase ◽

Intensive Procedures

ABSTRACTModern next-generation sequencing-based methods have empowered researchers to assay the epigenetic states of individual cells. Existing techniques for profiling epigenetic marks in single cells often require the use and optimization of time-intensive procedures such as drop fluidics, chromatin fragmentation, and end repair. Here we describe ACT-seq, a novel and streamlined method for mapping genome-wide distributions of histone tail modifications, histone variants, and chromatin-binding proteins in a small number of or single cells. ACT-seq utilizes a fusion of Tn5 transposase to Protein A that is targeted to chromatin by a specific antibody, allowing chromatin fragmentation and sequence tag insertion specifically at genomic sites presenting the relevant antigen. The Tn5 transposase enables the use of an index multiplexing strategy (iACT-seq), which enables construction of thousands of single-cell libraries in one day by a single researcher without the need for drop-based fluidics or visual sorting. We conclude that ACT-seq present an attractive alternative to existing techniques for mapping epigenetic marks in single cells.

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Rapid and Low-Input Profiling of Histone Marks in Plants Using Nucleus CUT&Tag

Frontiers in Plant Science ◽

10.3389/fpls.2021.634679 ◽

2021 ◽

Vol 12 ◽

Author(s):

Weizhi Ouyang ◽

Xiwen Zhang ◽

Yong Peng ◽

Qing Zhang ◽

Zhilin Cao ◽

...

Keyword(s):

Histone Modifications ◽

Chromatin Immunoprecipitation ◽

Binding Sites ◽

Protein A ◽

Transcriptional Factor ◽

Experimental Procedure ◽

Histone Marks ◽

Genome Wide ◽

Efficient Alternative ◽

Tn5 Transposase

Characterizing genome-wide histone posttranscriptional modifications and transcriptional factor occupancy is crucial for deciphering their biological functions. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a powerful method for genome-wide profiling of histone modifications and transcriptional factor-binding sites. However, the current ChIP-seq experimental procedure in plants requires significant material and several days for completion. CUT&Tag is an alternative method of ChIP-seq for low-sample and single-cell epigenomic profiling using protein A-Tn5 transposase fusion proteins (PAT). In this study, we developed a nucleus CUT&Tag (nCUT&Tag) protocol based on the live-cell CUT&Tag technology. Our results indicate that nCUT&Tag could be used for histone modifications profiling in both monocot rice and dicot rapeseed using crosslinked or fresh tissues. In addition, both active and repressive histone marks such as H3K4me3 and H3K9me2 can be identified using our nCUT&Tag. More importantly, all the steps in nCUT&Tag can be finished in only 1 day, and the assay can be performed with as little as 0.01 g of plant tissue as starting materials. Therefore, our results demonstrate that nCUT&Tag is an efficient alternative strategy for plant epigenomic studies.

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SCELLECTOR: ranking amplification bias in single cells using shallow sequencing

BMC Bioinformatics ◽

10.1186/s12859-020-03858-y ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Vivekananda Sarangi ◽

Alexandre Jourdon ◽

Taejeong Bae ◽

Arijit Panda ◽

Flora Vaccarino ◽

...

Keyword(s):

Single Cell ◽

Multiple Displacement Amplification ◽

Single Cells ◽

Sequencing Data ◽

High Coverage ◽

Amplification Bias ◽

Single Cell Profiling ◽

High Concordance ◽

Human Neuronal Cells

Abstract Background The study of mosaic mutation is important since it has been linked to cancer and various disorders. Single cell sequencing has become a powerful tool to study the genome of individual cells for the detection of mosaic mutations. The amount of DNA in a single cell needs to be amplified before sequencing and multiple displacement amplification (MDA) is widely used owing to its low error rate and long fragment length of amplified DNA. However, the phi29 polymerase used in MDA is sensitive to template fragmentation and presence of sites with DNA damage that can lead to biases such as allelic imbalance, uneven coverage and over representation of C to T mutations. It is therefore important to select cells with uniform amplification to decrease false positives and increase sensitivity for mosaic mutation detection. Results We propose a method, Scellector (single cell selector), which uses haplotype information to detect amplification quality in shallow coverage sequencing data. We tested Scellector on single human neuronal cells, obtained in vitro and amplified by MDA. Qualities were estimated from shallow sequencing with coverage as low as 0.3× per cell and then confirmed using 30× deep coverage sequencing. The high concordance between shallow and high coverage data validated the method. Conclusion Scellector can potentially be used to rank amplifications obtained from single cell platforms relying on a MDA-like amplification step, such as Chromium Single Cell profiling solution.

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SHERRY2: A method for rapid and sensitive single cell RNA-seq

10.1101/2021.12.25.474161 ◽

2021 ◽

Author(s):

Lin Di ◽

Bo Liu ◽

Yuzhu Lyu ◽

Shihui Zhao ◽

Yuhong Pang ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Dynamic Range ◽

Single Cells ◽

Rna Seq ◽

Wide Dynamic Range ◽

Uniform Coverage ◽

Optimized Protocol ◽

Tn5 Transposase ◽

Higher Sensitivity

Many single cell RNA-seq applications aim to probe a wide dynamic range of gene expression, but most of them are still challenging to accurately quantify low-aboundance transcripts. Based on our previous finding that Tn5 transposase can directly cut-and-tag DNA/RNA hetero-duplexes, we present SHERRY2, an optimized protocol for sequencing transcriptomes of single cells or single nuclei. SHERRY2 is robust and scalable, and it has higher sensitivity and more uniform coverage in comparison with prevalent scRNA-seq methods. With throughput of a few thousand cells per batch, SHERRY2 can reveal the subtle transcriptomic differences between cells and facilitate important biological discoveries.

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Antibody-guided Chromatin Tagmentation for Two or More Factors (ACT2-seq)

10.21203/rs.3.pex-1695/v1 ◽

2021 ◽

Author(s):

Benjamin Carter ◽

Wai Lim Ku ◽

Keji Zhao

Keyword(s):

Single Cell ◽

Magnetic Beads ◽

Protein A ◽

Epigenetic Marks ◽

Tn5 Transposase

Abstract This protocol details the reagents and steps required to perform antibody-guided chromatin tagmentation for two or more factors (ACT2-seq, ACT2). Like its predecessor ACT-seq, ACT2 uses a fusion of protein A and Tn5 transposase to bind and profile epigenetic marks across the genome. ACT2 builds on the capabilities of ACT-seq by directly and concurrently profiling co-occupancy of epigenetic marks, which previously required laborious, expensive, and technically challenging approaches involving fluorescence, magnetic beads, or single-cell methods. ACT2 requires only standard pipetting and centrifugation techniques and can be completed in less than a single day of bench work.

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Single-cell ATAC-seq Signal Extraction and Enhancement with SCATE

10.1101/795609 ◽

2019 ◽

Cited By ~ 1

Author(s):

Zhicheng Ji ◽

Weiqiang Zhou ◽

Hongkai Ji

Keyword(s):

Single Cell ◽

State Of The Art ◽

Single Cells ◽

Regulatory Elements ◽

Single Cell Sequencing ◽

Statistical Framework ◽

Genome Wide ◽

Cell Subpopulations ◽

Accessible Chromatin ◽

Regulatory Landscape

AbstractSingle-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is the state-of-the-art technology for analyzing genome-wide regulatory landscape in single cells. Single-cell ATAC-seq data are sparse and noisy. Analyzing such data is challenging. Existing computational methods cannot accurately reconstruct activities of individual cis-regulatory elements (CREs) in individual cells or rare cell subpopulations. We present a new statistical framework, SCATE, that adaptively integrates information from co-activated CREs, similar cells, and publicly available regulome data to substantially increase the accuracy for estimating activities of individual CREs. We show that using SCATE, one can better reconstruct the regulatory landscape of a heterogeneous sample.

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Reconstructing mutational lineages in breast cancer by multi-patient-targeted single cell DNA sequencing

10.1101/2021.11.16.468877 ◽

2021 ◽

Author(s):

Nicholas Navin ◽

Jake Leighton ◽

Min Hu ◽

Emi Sei ◽

Funda Meric-Bernstam

Keyword(s):

Breast Cancer ◽

Dna Sequencing ◽

Single Cell ◽

Copy Number ◽

Somatic Mutations ◽

Single Cells ◽

Tumor Evolution ◽

Sequencing Method ◽

Genomic Regions ◽

Microfluidics Platform

Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells, however most genomic regions characterized in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq sequencing method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this data, we reconstructed mutational lineages and identified early mutational and copy number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggests that MPT can overcome technical obstacles for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.

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SNV identification from single-cell RNA sequencing data

Human Molecular Genetics ◽

10.1093/hmg/ddz207 ◽

2019 ◽

Vol 28 (21) ◽

pp. 3569-3583 ◽

Cited By ~ 3

Author(s):

Patricia M Schnepp ◽

Mengjie Chen ◽

Evan T Keller ◽

Xiang Zhou

Keyword(s):

Dna Sequencing ◽

Single Cell ◽

Rna Sequencing ◽

Single Cells ◽

Specific Gene ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Single Cell Rna Sequencing ◽

Sequencing Studies ◽

Genomic Regions

Abstract Integrating single-cell RNA sequencing (scRNA-seq) data with genotypes obtained from DNA sequencing studies facilitates the detection of functional genetic variants underlying cell type-specific gene expression variation. Unfortunately, most existing scRNA-seq studies do not come with DNA sequencing data; thus, being able to call single nucleotide variants (SNVs) from scRNA-seq data alone can provide crucial and complementary information, detection of functional SNVs, maximizing the potential of existing scRNA-seq studies. Here, we perform extensive analyses to evaluate the utility of two SNV calling pipelines (GATK and Monovar), originally designed for SNV calling in either bulk or single-cell DNA sequencing data. In both pipelines, we examined various parameter settings to determine the accuracy of the final SNV call set and provide practical recommendations for applied analysts. We found that combining all reads from the single cells and following GATK Best Practices resulted in the highest number of SNVs identified with a high concordance. In individual single cells, Monovar resulted in better quality SNVs even though none of the pipelines analyzed is capable of calling a reasonable number of SNVs with high accuracy. In addition, we found that SNV calling quality varies across different functional genomic regions. Our results open doors for novel ways to leverage the use of scRNA-seq for the future investigation of SNV function.

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CUT&Tag for efficient epigenomic profiling of small samples and single cells

Nature Communications ◽

10.1038/s41467-019-09982-5 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 120

Author(s):

Hatice S. Kaya-Okur ◽

Steven J. Wu ◽

Christine A. Codomo ◽

Erica S. Pledger ◽

Terri D. Bryson ◽

...

Keyword(s):

High Resolution ◽

Rna Polymerase Ii ◽

Single Cells ◽

Protein A ◽

Small Samples ◽

Live Cells ◽

Protein Activation ◽

Tn5 Transposase ◽

Fragment Libraries

Abstract Many chromatin features play critical roles in regulating gene expression. A complete understanding of gene regulation will require the mapping of specific chromatin features in small samples of cells at high resolution. Here we describe Cleavage Under Targets and Tagmentation (CUT&Tag), an enzyme-tethering strategy that provides efficient high-resolution sequencing libraries for profiling diverse chromatin components. In CUT&Tag, a chromatin protein is bound in situ by a specific antibody, which then tethers a protein A-Tn5 transposase fusion protein. Activation of the transposase efficiently generates fragment libraries with high resolution and exceptionally low background. All steps from live cells to sequencing-ready libraries can be performed in a single tube on the benchtop or a microwell in a high-throughput pipeline, and the entire procedure can be performed in one day. We demonstrate the utility of CUT&Tag by profiling histone modifications, RNA Polymerase II and transcription factors on low cell numbers and single cells.

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