Multiplexed single-cell profiling of chromatin states at genomic loci by expansion microscopy

AbstractProper regulation of genome architecture and activity is essential for the development and function of multicellular organisms. Histone modifications, acting in combination, specify these activity states at individual genomic loci. However, the methods used to study these modifications often require either a large number of cells or are limited to targeting one histone mark at a time. Here, we developed a new method called Single Cell Evaluation of Post-TRanslational Epigenetic Encoding (SCEPTRE) that uses Expansion Microscopy (ExM) to visualize and quantify multiple histone modifications at non-repetitive genomic regions in single cells at a spatial resolution of ~75 nm. Using SCEPTRE, we distinguished multiple histone modifications at a single housekeeping gene, quantified histone modification levels at multiple developmentally-regulated genes in individual cells, and identified a relationship between histone H3K4 trimethylation and the loading of paused RNA polymerase II at individual loci. Thus, SCEPTRE enables multiplexed detection of combinatorial chromatin states at single genomic loci in single cells.

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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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ReadZS detects developmentally regulated RNA processing programs in single cell RNA-seq and defines subpopulations independent of gene expression

10.1101/2021.09.29.462469 ◽

2021 ◽

Author(s):

Elisabeth Meyer ◽

Roozbeh Dehghannasiri ◽

Kaitlin Chaung ◽

Julia Salzman

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Processing ◽

Single Cells ◽

Alternative Polyadenylation ◽

Cell Type ◽

Computationally Efficient ◽

Developmentally Regulated ◽

Eukaryotic Gene ◽

Human Spermatogenesis

Post-transcriptional regulation of RNA processing (RNAP), including splicing and alternative polyadenylation (APA), controls eukaryotic gene function. Conservative estimates based on bulk tissue studies conclude that at least 50% of mammalian genes undergo APA. Single-cell RNA sequencing (scRNA-seq) could enable a near complete estimate of the extent, function, and regulation of these and other forms of RNA processing. Yet, statistical methods to detect regulated RNAP are limited in their detection power because they suffer from reliance on (a) incomplete annotations of 3' untranslated regions (3' UTRs), (b) peak calling heuristics, (c) analysis based on measurements collapsed over all cells in a cell type (pseudobulking), or (d) APA-specific detection. Here, we introduce ReadZS, a computationally-efficient, and annotation-free statistical approach to identify regulated RNAP, including but not limited to APA, in single cells. ReadZS rediscovers and substantially extends the scope of known cell type-specific RNAP in the human lung and during human spermatogenesis. The unique single-cell resolution and statistical properties of ReadZS enable discovery of new evolutionarily conserved, developmentally regulated RNAP and subpopulations of lung-resident macrophages, homogenous by gene expression alone.

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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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High-throughput single-cell joint analysis of histone modifications and gene expression by Paired-Tag

10.21203/rs.3.pex-1301/v2 ◽

2021 ◽

Author(s):

Chenxu Zhu ◽

Yanxiao Zhang ◽

Yang Eric Li ◽

Jacinta Lucero ◽

M. Margarita Behrens ◽

...

Keyword(s):

Gene Expression ◽

Molecular Biology ◽

Single Cell ◽

Histone Modifications ◽

High Throughput ◽

Cultured Cells ◽

Single Cells ◽

Joint Analysis ◽

Gene Expressions ◽

Standard Molecular Biology

Abstract We describe here Paired-Tag, a high-throughput multi-omics method for joint profiling of histone modifications and gene expressions in single cells. The assay is based on a combinatorial barcoding indexing strategy that does not require special instruments. It can be performed with nuclei extracted from cultured cells or frozen tissues, in standard molecular biology laboratories.

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Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

10.1101/186940 ◽

2017 ◽

Cited By ~ 2

Author(s):

Tamir Biezuner ◽

Ofir Raz ◽

Shiran Amir ◽

Lilach Milo ◽

Rivka Adar ◽

...

Keyword(s):

Single Cell ◽

Whole Genome Amplification ◽

Single Cells ◽

Targeted Sequencing ◽

Whole Genome ◽

Genome Coverage ◽

Genome Amplification ◽

Cell Experiment ◽

Commercial Kits ◽

Genomic Regions

AbstractAdvances in biochemical technologies have led to a boost in the field of single cell genomics. Observation of the genome at a single cell resolution is currently achieved by pre-amplification using whole genome amplification (WGA) techniques that differ by their biochemical aspects and as a result by biased amplification of the original molecule. Several comparisons between commercially available single cell dedicated WGA kits (scWGA) were performed, however, these comparisons are costly, were only performed on selected scWGA kit and more notably, are limited by the number of analyzed cells, making them limited for reproducibility analysis. We benchmarked an economical assay to compare all commercially available scWGA kits that is based on targeted sequencing of thousands of genomic regions, including highly mutable genomic regions (microsatellites), from a large cohort of human single cells (125 cells in total). Using this approach, we could analyze the genome coverage, the reproducibility of genome coverage and the error rate of each kit. Our experimental design provides an affordable and reliable comparative assay that simulates a real single cell experiment. Results demonstrate the needfor a dedicated kit selection depending on the desired single cell assay.

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High-throughput single-cell epigenomic profiling by targeted insertion of promoters (TIP-seq)

The Journal of Cell Biology ◽

10.1083/jcb.202103078 ◽

2021 ◽

Vol 220 (12) ◽

Author(s):

Daniel A. Bartlett ◽

Vishnu Dileep ◽

Tetsuya Handa ◽

Yasuyuki Ohkawa ◽

Hiroshi Kimura ◽

...

Keyword(s):

Rna Polymerase ◽

Single Cell ◽

Rna Polymerase Ii ◽

High Throughput ◽

Single Cells ◽

Mapping Method ◽

Ctcf Binding ◽

Linear Amplification ◽

Site Mapping ◽

Chromatin Profiling

Chromatin profiling in single cells has been extremely challenging and almost exclusively limited to histone proteins. In cases where single-cell methods have shown promise, many require highly specialized equipment or cell type–specific protocols and are relatively low throughput. Here, we combine the advantages of tagmentation, linear amplification, and combinatorial indexing to produce a high-throughput single-cell DNA binding site mapping method that is simple, inexpensive, and capable of multiplexing several independent samples per experiment. Targeted insertion of promoters sequencing (TIP-seq) uses Tn5 fused to proteinA to insert a T7 RNA polymerase promoter adjacent to a chromatin protein of interest. Linear amplification of flanking DNA with T7 polymerase before sequencing library preparation provides ∼10-fold higher unique reads per single cell compared with other methods. We applied TIP-seq to map histone modifications, RNA polymerase II (RNAPII), and transcription factor CTCF binding sites in single human and mouse cells.

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Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis

Communications Biology ◽

10.1038/s42003-020-0896-2 ◽

2020 ◽

Vol 3 (1) ◽

Cited By ~ 2

Author(s):

Maeve O’Huallachain ◽

Felice-Alessio Bava ◽

Mary Shen ◽

Carolina Dallett ◽

Sri Paladugu ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Single Cell Analysis ◽

Single Cells ◽

Model Systems ◽

Cellular Heterogeneity ◽

Human Model ◽

Targeted Analysis ◽

Technological Advances ◽

And Function

AbstractSingle-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

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High-throughput single-cell joint analysis of histone modifications and gene expression by Paired-Tag

10.21203/rs.3.pex-1301/v1 ◽

2021 ◽

Cited By ~ 1

Author(s):

Chenxu Zhu ◽

Yanxiao Zhang ◽

Yang Eric Li ◽

Jacinta Lucero ◽

M. Margarita Behrens ◽

...

Keyword(s):

Gene Expression ◽

Molecular Biology ◽

Single Cell ◽

Histone Modifications ◽

High Throughput ◽

Cultured Cells ◽

Single Cells ◽

Joint Analysis ◽

Gene Expressions ◽

Standard Molecular Biology

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CoBATCH for high-throughput single-cell epigenomic profiling

10.1101/590661 ◽

2019 ◽

Author(s):

Qianhao Wang ◽

Haiqing Xiong ◽

Shanshan Ai ◽

Xianhong Yu ◽

Yaxi Liu ◽

...

Keyword(s):

Single Cell ◽

Binding Proteins ◽

Single Cells ◽

Protein A ◽

High Signal ◽

Chromatin Binding ◽

Genome Wide ◽

Single Cell Profiling ◽

Genomic Regions ◽

Tn5 Transposase

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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RNA labelling in live plants reveals single cell transcriptional dynamics: application to phosphate signaling

10.1101/2021.04.12.439441 ◽

2021 ◽

Author(s):

Sahar Hani ◽

Laura Cuyas Carrera ◽

Pascale David ◽

David Secco ◽

James Whelan ◽

...

Keyword(s):

Single Cell ◽

Rna Polymerase Ii ◽

Transcriptional Repression ◽

Transcription Initiation ◽

Imaging System ◽

Single Cells ◽

Intrinsic Noise ◽

Transcriptional Responses ◽

Fast Kinetics ◽

Allelic Differences

Plants are sessile organisms constantly adapting to ambient fluctuations through spatial and temporal transcriptional responses. Here, we implemented the latest generation of RNA imaging system and combined it with microfluidics to visualize transcriptional regulation in living Arabidopsis plants. This enabled quantitative measurements of the transcriptional activity of single loci in single cells, real time and changing environmental conditions. Using phosphate responsive genes as model, we found that active genes displayed high transcription initiation rates (~3s) and frequently clustered together in endoreplicated cells. We observed gene bursting and large allelic differences in single cells, revealing that at steady-state, intrinsic noise dominated extrinsic variations. Moreover, we established that transcriptional repression triggered in roots by phosphate, a crucial macronutrient limiting plant development, occurred with unexpected fast kinetics (~minutes) and striking heterogeneity between neighboring cells. Access to single cell RNA polymerase II dynamics within live plants will benefit future studies of signaling processes.

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