We thank Linda Orzolek from the Johns Hopkins Transcriptomics and Deep Sequencing Core for help in sequencing the produced libraries and Lizhi Jiang for performing the ex vivo retinal explants.

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Nothing to disclose.

The power of MULTI-seq stems from seamless integration of data from multiple experimental conditions or models and the enormous benefit in terms of cost and limiting batch effects. Utilizing MULTI-seq offers a laboratory unprecedented phenotyping depth. Non-genetic multiplexing methods such as cell hashing or nuclei hashing opened the door to multiplexed samples through the use of barcoded antibodies7,19,20. However, this relies on the availability of high affinity antibodies that recognize surface proteins expressed on cells or their nuclei, which will not be possible if these antibodies are unavailable or the cells do not express appropriate cell surface or nuclear antigens7. Because MULTI-seq utilizes lipid-modified oligo barcodes to stably incorporate into the cells or their nuclei, it allows researchers to gather transcriptomic data from up to 96 fresh or fixed samples in a cheaper and more broadly applicable manner6.
Following up on the initial MULTI-Seq phenotyping with paired scRNA-Seq and scATAC-Seq is suggested and showcased to gain an understanding of the genomic organization that coincides with the transcriptomic data1. This not only gives an idea of the heterochromatin and euchromatin regions but also valuable understanding of the transcription factor networks driving gene expression. A multi-omic approach can be used to reveal the dynamic chromatin changes that take place at key points of cell fate decisions and determine cellular trajectories in development and disease1,21,22. This can be accomplished through bioinformatically subjecting the data to pseudotime, cis-regulatory interactions and footprinting analysis5,23,24,25. Fixing the samples and sequencing multiple in a multiplexed run reduces sources of batch effect, enabling comparison across samples such as through a time course experiment.The number of tissue samples required depends on the scope of the experiment. When examining the phenotypes associated with embryonic time points, single retinas are often sufficient and can provide hundreds of thousands of cells. A single retina may not provide enough cells in more complex experimental schemes: ex vivo electroporations of retinal explants, probing for rare cell populations, or genetic models with insufficient CRE activation. While a single retina may provide a few hundred cells, these will not capture the full tissue complexity. For such experiments, optimization will be required based on a researcher&#39;s needs. Utilizing these techniques, one can gain insight into how the genes analyzed in MULTI-seq are regulated during dynamic processes such as development and disease.
Regulation of gene regulatory networks lies at the heart of understanding cellular processes and how they contribute to development and disease1,26,27. The workflow presented here can be used to identify these gene regulatory networks in specific cell types. However, this protocol has been optimized for use with mouse retinal tissue. Optimization of various steps, such as lysis or dissociation time, centrifugation speeds/times, and number of filtration steps may be required to maximize the number of cells or nuclei and minimize the cell debris in cell suspensions from other tissue types, ex vivo&#160;samples, or species, whether samples are fresh, frozen, or fixed in methanol. Methanol fixation time may need to be increased if samples show high levels of viable cells with trypan blue staining. The MULTI-seq technique introduces many additional wash steps over traditional scRNA-seq. To avoid the accidental disposal of valuable cells or DNA, it is prudent to optimize centrifugation speeds and maintain supernatants that would normally be discarded in the cell barcoding, post-GEM RT cleanup, and barcode library construction steps on ice until that step has been verified to be successful. One limitation to MULTI-seq is the limited number of cells, and therefore samples, that can be sequenced from a single well in the GEM generation step. It is recommended to not try to excessively overload cells during this step to avoid a substantial increase in doublet cell capture. Avoid loading a GEM well with more than 20,000 cells. Rather, multiple wells can be prepared from a single combined suspension and multiplexed during sequencing. This will require preparing a large enough volume of cell suspension for GEM generation and the addition of replicates to steps 5, 6, and 7 and will increase the cost of sequencing as more total reads are needed for more cells. With proper optimization, this workflow will enable cost and time efficient identification of cell type-specific phenotypes and gene regulatory networks.

Understanding how genes can influence cell fate plays a key role in interrogating processes such as disease and embryonic progression. The complex relationships between transcription factors and their target genes can be grouped in gene regulatory networks. Mounting evidence places these gene regulatory networks at the center of both disease and development across evolutionary lineages1. While previous techniques such as qRT-PCR focused on a single gene or set of genes, the application of high-throughput sequencing technology allows for the profiling of complete cellular transcriptomes.
RNA-seq offers a glimpse into large scale transcriptomics2,3. Single-cell RNA sequencing (scRNA-seq) gives investigators the ability to not only profile transcriptomes but link specific cell types with gene expression profiles4. This is achieved bioinformatically by feeding individual cell profiles into sorting algorithms using known gene markers5. Multiplexing using lipid-tagged indices sequencing (MULTI-seq) offers unprecedented diversity in the number of scRNA-Seq profiles that can be collected6. This lipid based technique differs from other sample indexing techniques such as cell-hashing that rely on the presence of surface antigens and high affinity antibodies instead of plasma membrane integration7. Not only is it now possible to profile gene expression profiles into cell types but different experiments can be combined into a single sequencing library, dramatically lowering the cost of an individual scRNA-seq experiment6. The cost of scRNA-seq may seem prohibitive for use in phenotyping experiments where many different genotypes, conditions or patient samples are analyzed, but multiplexing allows the combination of up to 96 samples in a single library6.
Profiling gene expression via scRNA-seq has not been the only high-throughput sequencing-based technique to revolutionize the current understanding of how molecular mechanisms dictate cell fate. While understanding which gene transcripts are present in a cell enables the identification of cell type, equally important is understanding how genomic organization regulates development and disease progression. Early studies relied on detecting DNase-mediated cleavage of sequences not bound to histones, followed by sequencing of the resulting DNA fragments to identify regions of open chromatin. In contrast, single cell assay for transposon accessible chromatin sequencing (scATAC-seq) allows researchers to probe DNA with a domesticated transposon to readily profile open chromatin at the single nucleotide level8. This has gone through a similar scaling to scRNA-seq and now investigators can identify individual cell types and profile phenotypes across thousands of individual genomes8.
The pairing of scRNA-seq and scATAC-seq has allowed researchers the ability to profile thousands of cells to determine cell populations, genomic organization, and gene regulatory networks in disease models and developmental processes9,10,11,12. Here the authors outline how to first utilize MULTI-seq to condense phenotyping of a myriad of animal models and employ paired scRNA-seq and scATAC-seq to gain a better understanding of the chromatin landscape and regulatory networks in these animal models.

<table><tbody><tr><td>10 &amp;micro;L, 200 &amp;micro;L, 1000 &amp;micro;L pipette filter tips</td><td></td><td></td><td></td></tr><tr><td>10% Tween 20</td><td>Bio-Rad</td><td>1662404</td><td></td></tr><tr><td>100 &amp;micro;M Barcode Solution</td><td>Request from Gartner lab</td><td>https://docs.google.com/forms/d/1bAzXFEvDEJse_cMvSUe_yDaP&lt;br/&gt; rJpAau4IPx8m5pauj3w/viewform?ts=5c47a897&amp;amp;edit_requested&lt;br/&gt; =true</td><td></td></tr><tr><td>100% Ethanol</td><td>Millipore Sigma</td><td>E7023-500ML</td><td></td></tr><tr><td>100% Methanol</td><td>Millipore Sigma</td><td>322415-100ML</td><td></td></tr><tr><td>10x Chip Holder</td><td>10x Genomics</td><td>1000195</td><td></td></tr><tr><td>10x Chromium controller &amp;amp; Accessory Kit</td><td>10x Genomics</td><td>PN-120263</td><td></td></tr><tr><td>15mL Centrifuge Tube</td><td>Quality Biological</td><td>P886-229411</td><td></td></tr><tr><td>40 &amp;micro;m FlowMi Cell Strainer</td><td>Bel-Art</td><td>H13680-0040</td><td></td></tr><tr><td>50 &amp;micro;M Anchor Solution</td><td>Sigma or request from Gartner lab</td><td>https://docs.google.com/forms/d/1bAzXFEvDEJse_cMvSUe_yDaP&lt;br/&gt; rJpAau4IPx8m5pauj3w/viewform?ts=5c47a897&amp;amp;edit_requested&lt;br/&gt; =true</td><td></td></tr><tr><td>50 &amp;micro;M Co-Anchor Solution</td><td>Sigma or request from Gartner lab</td><td>https://docs.google.com/forms/d/1bAzXFEvDEJse_cMvSUe_yDaP&lt;br/&gt; rJpAau4IPx8m5pauj3w/viewform?ts=5c47a897&amp;amp;edit_requested&lt;br/&gt; =true</td><td></td></tr><tr><td>5200 Fragment Analyzer system</td><td>Agilent</td><td>M5310AA</td><td></td></tr><tr><td>70 um FlowMi cell strainer</td><td>Bel-Art</td><td>H13680-0070</td><td></td></tr><tr><td>Allegra X-12R Centrifuge</td><td>VWR</td><td>BK392302</td><td></td></tr><tr><td>Bovine Serum Albumin</td><td>Sigma-Aldrich</td><td>A9647</td><td></td></tr><tr><td>Chromium Next GEM Chip G</td><td>10x Genomics</td><td>PN-1000120</td><td></td></tr><tr><td>Chromium Next GEM Chip H</td><td>10x Genomics</td><td>PN-1000161</td><td></td></tr><tr><td>Chromium Next Gem Single Cell ATAC Reagent Kit v1.1</td><td>10x Genomics</td><td>PN-1000175</td><td></td></tr><tr><td>Chromium Single Cell 3&#039; GEM, Library &amp;amp; Gel Bead Kit v3.1</td><td>10x Genomics</td><td>PN-1000121</td><td></td></tr><tr><td>Digitonin</td><td>Fisher Scientific</td><td>BN2006</td><td></td></tr><tr><td>Dissection microscope</td><td>Leica</td><td></td><td></td></tr><tr><td>DNA LoBind Tubes, 1.5 mL</td><td>Eppendorf</td><td>22431021</td><td></td></tr><tr><td>Dry Ice</td><td></td><td></td><td></td></tr><tr><td>EVA Foam Ice Pan</td><td>Tequipment</td><td>04393-54</td><td></td></tr><tr><td>FA 12-Capillary Array Short, 33 cm</td><td>Agilent</td><td>A2300-1250-3355</td><td></td></tr><tr><td>Fisherbrand Isotemp Water Bath</td><td>Fisher Scientific</td><td>15-460-20Q</td><td></td></tr><tr><td>Forma CO2 Water Jacketed Incubator</td><td>ThermoFisher Scientific</td><td>3110</td><td></td></tr><tr><td>Glycerol 50% Aqueous solution</td><td>Ricca Chemical Company</td><td>3290-32</td><td></td></tr><tr><td>Hausser Scientific Bright-Line Counting Chamber</td><td>Fisher Scientific</td><td>02-671-51B</td><td></td></tr><tr><td>Illumina NextSeq or NovaSeq</td><td>Illumina</td><td></td><td></td></tr><tr><td>Kapa Hifi Hotstart ReadyMix</td><td>HiFi</td><td>7958927001</td><td></td></tr><tr><td>Low TE Buffer</td><td>Quality Biological</td><td>351-324-721</td><td></td></tr><tr><td>Magnesium Chloride Solution 1 M</td><td>Sigma-Aldrich</td><td>M1028</td><td></td></tr><tr><td>Magnetic Separator Rack for 1.5 mL tubes</td><td>Millipore Sigma</td><td>20-400</td><td></td></tr><tr><td>Magnetic Separator Rack for 200 &amp;micro;L tubes</td><td>10x Genomics</td><td>NC1469069</td><td></td></tr><tr><td>MULTI-seq Primer</td><td>Sigma or IDT</td><td>See sequence list</td><td></td></tr><tr><td>MyFuge Mini Centrifuge</td><td>Benchmark Scientific</td><td>C1008</td><td></td></tr><tr><td>Nonidet P40 Substitute</td><td>Sigma-Aldrich</td><td>74385</td><td></td></tr><tr><td>Nuclease-free water</td><td>Fisher Scientific</td><td>AM9937</td><td></td></tr><tr><td>P2, P10, P20, P200, P1000 micropipettes</td><td>Eppendorf</td><td></td><td></td></tr><tr><td>Papain Dissociation System</td><td>Worthington Biochemical Corporation</td><td>LK003150</td><td></td></tr><tr><td>PBS pH 7.4 (1X)</td><td>Fisher Scientific</td><td>10010-023</td><td></td></tr><tr><td>Qiagen Buffer EB</td><td>Qiagen</td><td>19086</td><td></td></tr><tr><td>Refridgerated Centrifuge 5424 R</td><td>Eppendorf</td><td>2231000655</td><td></td></tr><tr><td>RNase-free Disposable Pellet Pestles</td><td>Fisher Scientific</td><td>12-141-368</td><td></td></tr><tr><td>RNasin Plus RNase Inhibitor</td><td>Promega</td><td>N2615</td><td></td></tr><tr><td>RPI primer</td><td>Sigma or IDT</td><td>See sequence list</td><td></td></tr><tr><td>Single Index Kit N, Set A</td><td>10x Genomics</td><td>PN-1000212</td><td></td></tr><tr><td>Single Index Kit T Set A</td><td>10x Genomics</td><td>PN-1000213</td><td></td></tr><tr><td>Sodium Chloride Solution 5 M</td><td>Sigma-Aldrich</td><td>59222C</td><td></td></tr><tr><td>SPRIselect Reagent Kit</td><td>Beckman Coulter</td><td>B23318</td><td></td></tr><tr><td>Standard Disposable Transfer Pipettes</td><td>Fisher Scientific</td><td>13-711-7M</td><td></td></tr><tr><td>TempAssure PCR 8-tube strip</td><td>USA Scientific</td><td>1402-4700</td><td></td></tr><tr><td>Trizma Hydrochloride Solution, pH 7.4</td><td>Sigma-Aldrich</td><td>T2194</td><td></td></tr><tr><td>Trypan Blue Solution, 0.4% (w/v)</td><td>Corning</td><td>25-900-CI</td><td></td></tr><tr><td>Universal I5 primer</td><td>Sigma or IDT</td><td>See sequence list</td><td></td></tr><tr><td>Veriti Thermal Cycler</td><td>Applied Biosystems</td><td>4375786</td><td></td></tr><tr><td>Vortex Mixer</td><td>VWR</td><td>10153-838</td><td></td></tr></tbody></table>

multiplexed analysis of retinal gene expression and chromatin accessibility using scrna-seq and scatac-seq

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during development and in disease states. Single-cell RNA sequencing allows us to comprehensively profile gene expression changes observed in retinal development and disease at a cellular level, while single-cell ATAC-Seq allows analysis of chromatin accessibility and transcription factor binding to be profiled at similar resolution. Here the use of these techniques in the developing retina is described, and MULTI-Seq is demonstrated, where individual samples are labeled with a modified oligonucleotide-lipid complex, enabling researchers to both increase the scope of individual experiments and substantially reduce costs.

This workflow lays out a strategy for investigation of developmental phenotypes and regulatory processes using single cell sequencing. MULTI-seq sample multiplexing enables an initial low-cost phenotyping assay while paired collection and fixation of samples for scRNA-seq and scATAC-seq allows for more in-depth investigation (Figure 1).
MULTI-seq barcoding enables the combined sequencing of multiple samples and their subsequent computational deconvolution. The sample of origin can be determined for each cell based on their barcode expression (Figure 2A). These combined samples can be analyzed as a single dataset for the purposes of cell clustering and cell type identification (Figure 2B). Because each cell is barcoded before GEM generation, cell doublets will have a high probability of showing expression for multiple MULTI-seq barcodes and a majority of doublets can therefore be identified and removed prior to clustering and cell type identification (Figure 2C). Increasing the number of cells used in the GEM generation step will increase the proportion of doublets found. scATAC-seq can be used to generate a dataset with cell types to match those found by scRNA-seq (Figure 2D). The pairing of scRNA-seq gene expression and scATAC-seq DNA accessibility information enables the reconstruction of gene regulatory networks.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62239/62239fig01.jpg" /> 
Figure 1: Schematic demonstrating the use of MULTI-Seq in initial analysis, followed by separate scRNA-Seq and scATAC-Seq analysis in in-depth characterization of phenotypes, treatments, or disease states of interest. <a href="https://www.jove.com/files/ftp_upload/62239/62239fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62239/62239fig02.jpg" /> 
Figure 2: UMAP dimensional reduction representations of MULTI-seq data for an allelic series of P0 Sstr2 knockout mice demonstrating (a) the deconvolution of genotype for each cell in the dataset and (b) the identification of cell types in the dataset. Overloading cells during the GEM generation and barcoding step will result in an increase in cell doublets like those as seen in (c), which shows the data from (a) and (b) before doublet removal and reclustering. In (d), scATAC-Seq data from GFP-positive cells obtained at E16 from retinal explants electroporated with a GFP-expressing control plasmid at E14. Cell types are annotated based on accessibility of cell type-specific genes. This figure has been modified from Weir, K., Kim, D. W., Blackshaw, S. Regulation of retinal neurogenesis by somatostatin signaling. bioRxiv 2020.09.26.314104 (2020) doi:10.1101/2020.09.26.31410418 and original, unpublished data. <a href="https://www.jove.com/files/ftp_upload/62239/62239fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq at JoVE.com

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Here, the authors showcase the utility of MULTI-seq for phenotyping and subsequent paired scRNA-seq and scATAC-seq in characterizing the transcriptomic and chromatin accessibility profiles in retina.

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during ...

multiplexed-analysis-retinal-gene-expression-chromatin-accessibility

Universidad San Sebastian

Research

JoVE Journal

Neuroscience

3.5K Views.  Johns Hopkins University School of Medicine. Here, the authors showcase the utility of MULTI-seq for phenotyping and subsequent paired scRNA-seq and scATAC-seq in characterizing the transcriptomic and chromatin accessibility profiles in retina.

Video: Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions of chromatin. These regions represent regulatory DNA elements (e.g., promoters, enhancers, locus control regions, insulators) to which transcription factors bind. Mapping the accessible chromatin landscape is a powerful approach for uncovering active regulatory elements across the genome. This information serves as an unbiased approach for discovering the network of relevant transcription factors and mechanisms of chromatin structure that govern gene expression programs. ATAC-seq is a robust and sensitive alternative to DNase I hypersensitivity analysis coupled with next-generation sequencing (DNase-seq) and formaldehyde-assisted isolation of regulatory elements (FAIRE-seq) for genome-wide analysis of chromatin accessibility and to the sequencing of micrococcal nuclease-sensitive sites (MNase-seq) to determine nucleosome positioning. We present a detailed ATAC-seq protocol optimized for human primary immune cells i.e. CD4+ lymphocytes (T helper 1 (Th1) and Th2 cells). This comprehensive protocol begins with cell harvest, then describes the molecular procedure of chromatin tagmentation, sample preparation for next-generation sequencing, and also includes methods and considerations for the computational analyses used to interpret the results. Moreover, to save time and money, we introduced quality control measures to assess the ATAC-seq library prior to sequencing. Importantly, the principles presented in this protocol allow its adaptation to other human immune and non-immune primary cells and cell lines. These guidelines will also be useful for laboratories which are not proficient with next-generation sequencing methods.

Assay for Transposase-Accessible Chromatin coupled with high-throughput sequencing (ATAC-seq) is a genome-wide method to uncover accessible chromatin. This is a step-by-step ATAC-seq protocol, from molecular to the final computational analysis, optimized for human lymphocytes (Th1/Th2). This protocol can be adopted by researchers without prior experience in next-generation sequencing methods.

Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method used for the identification of open (accessible) regions ...

Genetics

ATAC-seq Assay with Low Mitochondrial DNA Contamination from Primary Human CD4+ T Lymphocytes

ATAC-seq has become a widely used methodology in the study of epigenetics due to its rapid and simple approach to mapping genome-wide accessible chromatin. In this paper we present an improved ATAC-seq protocol that reduces contaminating mitochondrial DNA reads. While previous ATAC-seq protocols have struggled with an average of 50% contaminating mitochondrial DNA reads, the optimized&#160;lysis buffer introduced in this protocol reduces mitochondrial DNA contamination to an average of 3%. This improved ATAC-seq protocol allows for a near 50% reduction in the sequencing cost. We demonstrate how these high-quality ATAC-seq libraries can be prepared from activated CD4+ lymphocytes, providing step-by-step instructions from CD4+ lymphocyte isolation from whole blood through data analysis. This improved ATAC-seq protocol has been validated in a wide range of cell types and will be of immediate use to researchers studying chromatin accessibility.

Here, we present a protocol to perform an assay for transposase-accessible chromatin sequencing (ATAC-seq) on activated CD4+ human lymphocytes. The protocol has been modified to minimize contaminating mitochondrial DNA reads from 50% to 3% through the introduction of a new lysis buffer.

ATAC-seq has become a widely used methodology in the study of epigenetics due to its rapid and simple approach to mapping genome-wide accessible ...

Single-cell Profiling of Developing and Mature Retinal Neurons

Highly specialized, but exceedingly small populations of cells play important roles in many tissues. The identification of cell-type specific markers and gene expression programs for extremely rare cell subsets has been a challenge using standard whole-tissue approaches. Gene expression profiling of individual cells allows for unprecedented access to cell types that comprise only a small percentage of the total tissue1-7. In addition, this technique can be used to examine the gene expression programs that are transiently expressed in small numbers of cells during dynamic developmental transitions8.
This issue of cellular diversity arises repeatedly in the central nervous system (CNS) where neuronal connections can occur between quite diverse cells9. The exact number of distinct cell types is not precisely known, but it has been estimated that there may be as many as 1000 different types in the cortex itself10. The function(s) of complex neural circuits may rely on some of the rare neuronal types and the genes they express. By identifying new markers and helping to molecularly classify different neurons, the single-cell approach is particularly useful in the analysis of cell types in the nervous system. It may also help to elucidate mechanisms of neural development by identifying differentially expressed genes and gene pathways during early stages of neuronal progenitor development.
As a simple, easily accessed tissue with considerable neuronal diversity, the vertebrate retina is an excellent model system for studying the processes of cellular development, neuronal differentiation and neuronal diversification. However, as in other parts of the CNS, this cellular diversity can present a problem for determining the genetic pathways that drive retinal progenitors to adopt a specific cell fate, especially given that rod photoreceptors make up the majority of the total retinal cell population11. Here we report a method for the identification of the transcripts expressed in single retinal cells (Figure 1). The single-cell profiling technique allows for the assessment of the amount of heterogeneity present within different cellular populations of the retina2,4,5,12. In addition, this method has revealed a host of new candidate genes that may play role(s) in the cell fate decision-making processes that occur in subsets of retinal progenitor cells8. With some simple adjustments to the protocol, this technique can be utilized for many different tissues and cell types.

A method for the isolation of single retinal cells and subsequent amplification of their cDNAs is described. Single-cell transcriptomics reveals the degree of cellular heterogeneity present in a tissue and uncovers new marker genes for rare cell populations. The accompanying protocol can be adjusted to suit many different cell types.

Highly specialized, but exceedingly small populations of cells play important roles in many tissues. The identification of cell-type specific markers and ...

Adipocyte-Specific ATAC-Seq with Adipose Tissues Using Fluorescence-Activated Nucleus Sorting

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a robust technique that enables genome-wide chromatin accessibility profiling. This technique has been useful for understanding the regulatory mechanisms of gene expression in a range of biological processes. Although ATAC-seq has been modified for different types of samples, there have not been effective modifications of ATAC-seq methods for adipose tissues. Challenges with adipose tissues include the complex cellular heterogeneity, large lipid content, and high mitochondrial contamination. To overcome these problems, we have developed a protocol that allows adipocyte-specific ATAC-seq by employing fluorescence-activated nucleus sorting with adipose tissues from the transgenic reporter Nuclear tagging and Translating Ribosome Affinity Purification (NuTRAP) mouse. This protocol produces high-quality data with minimal wasted sequencing reads while reducing the amount of nucleus input and reagents. This paper provides detailed step-by-step instructions for the ATAC-seq method validated for the use of adipocyte nuclei isolated from mouse adipose tissues. This protocol will aid in the investigation of chromatin dynamics in adipocytes upon diverse biological stimulations, which will allow for novel biological insights.

We present a protocol for assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) specifically on adipocytes using nucleus sorting with adipose tissues isolated from transgenic reporter mice with nuclear fluorescence labeling.

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a robust technique that enables genome-wide chromatin ...

CATCH-UP: A High-Throughput Upstream-Pipeline for Bulk ATAC-Seq and ChIP-Seq Data

Assay for transposase-accessible chromatin (ATAC) and chromatin immunoprecipitation (ChIP), coupled with next-generation sequencing (NGS), have revolutionized the study of gene regulation. A lack of standardization in the analysis of the highly dimensional datasets generated by these techniques has made reproducibility difficult to achieve, leading to discrepancies in the published, processed data. Part of this problem is due to the diverse range of bioinformatic tools available for the analysis of these types of data. Secondly, a number of different bioinformatic tools are required sequentially to convert raw data into a fully processed and interpretable output, and these tools require varying levels of computational skills. Furthermore, there are many options for quality control that are not uniformly employed during data processing. We address these issues with a complete assay for transposase-accessible chromatin sequencing (ATAC-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) upstream pipeline (CATCH-UP), an easy-to-use, Python-based pipeline for the analysis of bulk ChIP-seq and ATAC-seq datasets from raw fastq files to visualizable bigwig tracks and peaks calls. This pipeline is simple to install and run, requiring minimal computational knowledge. The pipeline is modular, scalable, and parallelizable on various computing infrastructures, allowing for easy reporting of methodology to enable reproducible analysis of novel or published datasets.

ATAC-seq and ChIP-seq allow detailed investigation of gene regulation; however, processing these data types is challenging and often inconsistent between research groups. We present CATCH-UP: an easy-to-use computational pipeline that allows standardized and reproducible data processing and analysis of new and published ATAC/ChIP-seq datasets.

Assay for transposase-accessible chromatin (ATAC) and chromatin immunoprecipitation (ChIP), coupled with next-generation sequencing (NGS), have ...

ATAC-Seq Optimization for Cancer Epigenetics Research

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

ATAC-seq is a DNA sequencing method that uses the hyperactive mutant transposase, Tn5, to map changes in chromatin accessibility mediated by transcription factors. ATAC-seq enables the discovery of the molecular mechanisms underlying phenotypic alterations in cancer cells. This protocol outlines optimization procedures for ATAC-seq in epithelial cell types, including cancer cells.

The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the ...

Cancer Research

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental biology. It has been successfully used to identify rare cell populations, discover novel marker genes, and decode spatial and temporal developmental information. The single cell method has also evolved from the microfluidic based Fluidigm C1 technology to the droplet-based solutions in the last two to three years. Here we used the heart as an example to demonstrate how to profile the mouse embryonic tissue cells using the droplet based scRNA-Seq method. In addition, we have integrated two strategies into the workflow to profile multiple samples in a single experiment. Using one of the integrated methods, we have simultaneously profiled more than 9,000 cells from eight heart samples. These methods will be valuable to the developmental biology field by providing a cost-effective way to simultaneously profile single cells from different genetic backgrounds, developmental stages, or anatomical locations.

Here we presented a multiplexed single cell mRNA sequencing method to profile gene expression in mouse embryonic tissues. The droplet-based single cell mRNA sequencing (scRNA-Seq) method in combination with multiplexing strategies can profile single cells from multiple samples simultaneously, which significantly reduces reagent costs and minimizes experimental batch effects.

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental ...

Developmental Biology

Nuclei Isolation from Mouse Cardiac Progenitor Cells at Single-Cell Resolution

Nuclei Isolation from Mouse Cardiac Progenitor Cells for Epigenome and Gene Expression Profiling at Single-Cell Resolution

The developing heart is a complex structure containing various progenitor cells controlled by complex regulatory mechanisms. The examination of the gene expression and chromatin state of individual cells allows the identification of the cell type and state. Single-cell sequencing approaches have revealed a number of important characteristics of cardiac progenitor cell heterogeneity. However, these methods are generally restricted to fresh tissue, which limits studies with diverse experimental conditions, as the fresh tissue must be processed at once in the same run to reduce the technical variability. Therefore, easy and flexible procedures to produce data from methods such as single-nucleus RNA sequencing (snRNA-seq) and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing (snATAC-seq) are needed in this area. Here, we present a protocol to rapidly isolate nuclei for subsequent single-nuclei dual-omics (combined snRNA-seq and snATAC-seq). This method allows the isolation of nuclei from frozen samples of cardiac progenitor cells and can be combined with platforms that use microfluidic chambers.

Author Spotlight: Nuclei Isolation from Mouse Cardiac Progenitor Cells for Epigenome and Gene Expression Profiling at Single-Cell Resolution  

Here, we present a protocol describing cell nuclei preparation. After microdissection and enzymatic dissociation of cardiac tissue into single cells, the progenitor cells were frozen, followed by isolation of pure viable cells, which were used for single-nucleus RNA sequencing and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing analyses.

The developing heart is a complex structure containing various progenitor cells controlled by complex regulatory mechanisms. The examination of the gene ...

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

The discovery of cell type-specific markers can provide insight into cellular function and the origins of cellular heterogeneity. With a recent push for the improved understanding of neuronal diversity, it is important to identify genes whose expression defines various subpopulations of cells. The retina serves as an excellent model for the study of central nervous system diversity, as it is composed of multiple major cell types. The study of each major class of cells has yielded genetic markers that facilitate the identification of these populations. However, multiple subtypes of cells exist within each of these major retinal cell classes, and few of these subtypes have known genetic markers, although many have been characterized by morphology or function. A knowledge of genetic markers for individual retinal subtypes would allow for the study and mapping of brain targets related to specific visual functions and may also lend insight into the gene networks that maintain cellular diversity. Current avenues used to identify the genetic markers of subtypes possess drawbacks, such as the classification of cell types following sequencing. This presents a challenge for data analysis and requires rigorous validation methods to ensure that clusters contain cells of the same function. We propose a technique for identifying the morphology and functionality of a cell prior to isolation and sequencing, which will allow for the easier identification of subtype-specific markers. This technique may be extended to non-neuronal cell types, as well as to rare populations of cells with minor variations. This protocol yields excellent-quality data, as many of the libraries have provided read depths greater than 20 million reads for single cells. This methodology overcomes many of the hurdles presented by Single-cell RNA-Seq and may be suitable for researchers aiming to profile cell types in a straightforward and highly efficient manner.

Here, we present a combinatorial approach for classifying neuronal cell types prior to isolation and for the subsequent characterization of single-cell transcriptomes. This protocol optimizes the preparation of samples for successful RNA Sequencing (RNA-Seq) and describes a methodology designed specifically for the enhanced understanding of cellular diversity.

The discovery of cell type-specific markers can provide insight into cellular function and the origins of cellular heterogeneity. With a recent push for ...

Scalable ATAC-seq Protocol for Chromatin Accessibility in Rodent Neutrophils

ATAC-Seq Library Preparation of Murine Bone Marrow-Derived Neutrophils

Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) is a powerful, high-throughput technique for assessing chromatin accessibility and understanding epigenomic regulation. Neutrophils, as a crucial leukocyte type in immune responses, undergo substantial chromatin architectural changes during differentiation and activation, which significantly impact the gene expression necessary for their functions. ATAC-seq has been instrumental in uncovering key transcription factors in neutrophil maturation, revealing pathogen-specific epigenomic signatures, and identifying therapeutic targets for autoimmune diseases. However, neutrophils' sensitivity to the external milieu complicates high-quality ATAC-seq data production. Here, we propose a scalable protocol for preparing ATAC-seq libraries from rodent bone marrow-derived neutrophils, featuring improved immunomagnetic separation to ensure optimal cell viability and high-quality libraries. The vital elements impacting the library quality and optimization principles for methodological extension are discussed in detail. This protocol will support the researchers who are willing to study the chromatin architecture and epigenomic reprogramming of neutrophils, advancing studies in basic and clinical immunology.

This manuscript outlines a protocol for preparing an ATAC-seq library of neutrophils from murine bone marrow, aiming to guarantee optimal neutrophil viability and high library quality. It offers step-by-step instructions on BMC preparation, immunomagnetic sorting, and library construction, serving as a valuable guide, especially for newcomers to studying neutrophils.

Assay for Transposase-Accessible Chromatin with sequencing (ATAC-seq) is a powerful, high-throughput technique for assessing chromatin accessibility and ...