We thank the rest of the members from the Javierre lab for their feedback on the manuscript. We thank CERCA Program, Generalitat de Catalunya, and the Josep Carreras Foundation for institutional support. This work was financed by FEDER/Spanish Ministry of Science and Innovation (RTI2018-094788-A-I00), the European Hematology Association (4823998), and the Spanish Association against Cancer (AECC) LABAE21981JAVI. BMJ is funded by La Caixa Banking Foundation Junior Leader project (LCF/BQ/PI19/11690001), LR is funded by an AGAUR FI fellowship (2019FI-B00017), and LT-D is funded by an FPI Fellowship (PRE2019-088005). We thank the biochemistry and molecular biology PhD program from the Universitat Aut&#242;noma de Barcelona for its support.&#160;None of the funders were involved at any point in the experimental design or manuscript writing.

A Comprehensive Approach to Studying the Promoter Interactome in Scarce Cells

The authors have nothing to disclose.

liCHi-C offers the capability of generating high-resolution promoter interactome libraries using a similar experimental framework from PCHi-C&#39;s but with a vastly reduced cell number. This is greatly achieved by eliminating unnecessary steps, such as phenol purification and biotin removal. In the classical in-nucleus ligation Hi-C protocol57 and its subsequent derivative technique PCHi-C, biotin is removed from non-ligated restriction fragments to avoid pulling down DNA fragments that are after...

Temporal gene expression drives cell differentiation and, ultimately, organism development, and its alteration is closely related to a wide plethora of diseases1,2,3,4,5. Gene transcription is finely regulated by the action of regulatory elements, which can be classified as proximal (i.e., gene promoters) and distal (e.g., enhancers or silencers), the latter of which are frequently located afar from their target genes and physically interact with them through chromatin looping to modulate gene expression6,7,8.
The identification of distal regulatory regions in the genome is a matter which is widely agreed upon, since these regions harbor specific histone modifications9,10,11 and contain specific transcription factor recognition motifs, acting as recruiting platforms for them12,13,14. Besides, in the case of enhancers and super-enhancers15,16, they also have low-nucleosome occupancy17,18 and are transcribed into non-coding eRNAs19,20.
Nonetheless, each distal regulatory element&#39;s target genes are more difficult to predict. More often than not, interactions between distal regulatory elements and their targets are cell-type and stimulus specific21,22, span hundreds of kilobases, bridging over other genes in any direction23,24,25, and can even be located inside intronic regions of their target gene or other non-intervening genes26,27. Furthermore, distal regulatory elements can also control more than one gene at the same time, and vice versa28,29. This positional complexity hinders pinpointing regulatory associations between them, and therefore, most of each regulatory element&#39;s targets in every cell type remain unknown.
During recent years, there has been a significant boom in the development of chromosome conformation capture (3C) techniques for studying chromatin interactions. The most widely used of them, Hi-C, allows to generate a map of all the interactions between every fragment of a cell&#39;s genome30. However, to detect significant interactions at the restriction fragment level, Hi-C relies on ultra-deep sequencing, prohibiting its use to routinely study the regulatory landscape of individual genes. To overcome this economic limitation, several enrichment-based 3C techniques have emerged, such as ChIA-PET31, HiChIP32, and its low-input counterpart HiCuT33. These techniques depend on the use of antibodies to enrich for genome-wide interactions mediated by a specific protein. Nonetheless, the unique feature of these 3C techniques is also the bane of their application; users count on the availability of high-quality antibodies for the protein of interest and cannot compare conditions in which the binding of the protein is dynamic.
Promoter Capture Hi-C (PCHi-C) is another enrichment-based 3C technique that circumvents these limitations34,35. By employing a biotinylated RNA probe enrichment system, PCHi-C is able to generate genome-wide high-resolution libraries of genomic regions interacting with 28,650 human- or 27,595 mouse-annotated gene promoters, also known as the promoter interactome. This approach allows one to detect significant long-range interactions at the restriction fragment level resolution of both active and inactive promoters, and robustly compare promoter interactomes between any condition independently of the dynamics of histone modifications or protein binding. PCHi-C has been widely used over recent years to identify promoter interactome reorganizations during cell differentiation36,37, identify the mechanism of action of transcription factors38,39, and discover new potential genes and pathways deregulated in disease by non-coding variants40,41,42,43,44,45,46,47,48, alongside new driver non-coding mutations49,50. Besides, by just modifying the capture system, this technique can be customized according to the biological question to interrogate any interactome (e.g., the enhancer interactome51 or the interactome of a collection of non-coding alterations41,52).
However, PCHi-C relies on a minimum of 20 million cells to perform the technique, which prevents the study of scarce cell populations such as the ones often used in developmental biology and clinical applications. For this reason, we have developed low input Capture Hi-C (liCHi-C), a new cost-effective and customizable method based on the experimental framework of PCHi-C to generate high-resolution promoter interactomes with low-cell input. By performing the experiment with minimal tube changes, swapping or eliminating steps from the original PCHi-C protocol, drastically reducing reaction volumes, and modifying reagent concentrations, library complexity is maximized and it is possible to generate high-quality libraries with as little as 50,000 cells53.
Low input Capture Hi-C (liCHi-C) has been benchmarked against PCHi-C and used to elucidate promoter interactome rewiring during human hematopoietic cell differentiation, discover potential new disease-associated genes and pathways deregulated by non-coding alterations, and detect chromosomal abnormalities53. The step-by-step protocol and the different quality controls through the technique are detailed here until the final generation of the libraries and their computational analysis.

<table><tbody><tr><td>0.4 mM Biotin-14-dATP</td><td>Invitrogen</td><td>19524-016</td><td></td></tr><tr><td>0.5 M EDTA pH 8.0</td><td>Invitrogen</td><td>AM9260G</td><td></td></tr><tr><td>1 M Tris pH 8.0</td><td>Invitrogen</td><td>AM9855G</td><td></td></tr><tr><td>10x NEBuffer 2</td><td>New England Biolabs</td><td>B7002S</td><td>Referenced as restriction buffer 2 in the manuscript</td></tr><tr><td>10x PBS</td><td>Fisher Scientific</td><td>BP3994</td><td></td></tr><tr><td>10x T4 DNA ligase reaction buffer</td><td>New England Biolabs</td><td>B0202S</td><td></td></tr><tr><td>16% formaldehyde solution (w/v), methanol-free</td><td>Thermo Scientific</td><td>28908</td><td></td></tr><tr><td>20 mg/mL Bovine Serum Albumin</td><td>New England Biolabs</td><td>B9000S</td><td></td></tr><tr><td>5 M NaCl</td><td>Invitrogen</td><td>AM9760G</td><td></td></tr><tr><td>5PRIME Phase Lock Gel Light tubes</td><td>Qiuantabio</td><td>2302820</td><td>&lt;strong&gt;For phenol-chloroform purification in section 4&lt;/strong&gt; (DNA purification). Phase Lock Gel tubes are a commercial type of tubes specially designed to maximize DNA recovery after phenol-chloroform purifications while avoiding carryover of contaminants in the organic phase by containing a resin of intermediate density which settles between the organic and aqueous phase and isolates them. PLG tubes should be spun at 12,000 x g for 30 s before use to ensure that the resin is well-placed at the bottom of the tube</td></tr><tr><td>Adapters and PCR primers for library amplification</td><td>Integrated DNA Technologies</td><td>-</td><td>Bought as individual primers with PAGE purification for NGS</td></tr><tr><td>Cell scrappers</td><td>Nunc</td><td>179693</td><td>Or any other brand</td></tr><tr><td>Centrifuge (fixed-angle rotor for 1.5 mL tubes)</td><td>Any brand</td><td></td><td></td></tr><tr><td>CHiCAGO R package</td><td>1.14.0</td><td></td><td></td></tr><tr><td>CleanNGS beads</td><td>CleanNA</td><td>CNGS-0050</td><td></td></tr><tr><td>dATP, dCTP, dGTP, dTTP</td><td>Promega</td><td>U120A, U121A, U122A, U123A</td><td>Or any other brand</td></tr><tr><td>DNA LoBind tube, 1.5 mL</td><td>Eppendorf</td><td>30108051</td><td></td></tr><tr><td>DNA LoBind tube, 2 mL</td><td>Eppendorf</td><td>30108078</td><td></td></tr><tr><td>DNA polymerase I large (Klenow) fragment 5000 units/mL</td><td>New England Biolabs</td><td>M0210L</td><td></td></tr><tr><td>Dynabeads MyOne Streptavidin C1 beads</td><td>Invitrogen</td><td>65002</td><td>&lt;strong&gt;For biotin pull-down of the pre-captured library in section 8 &lt;/strong&gt;(biotin pull-down)</td></tr><tr><td>Dynabeads MyOne Streptavidin T1 beads</td><td>Invitrogen</td><td>65602</td><td>&lt;strong&gt;For biotin pull-down of the post-captured library in section 11&lt;/strong&gt; (biotin pull-down and PCR amplification)</td></tr><tr><td>DynaMag-2</td><td>Invitrogen</td><td>12321D</td><td>Or any other magnet suitable for 1.5 ml tubeL</td></tr><tr><td>Ethanol absolute</td><td>VWR</td><td>20821.321</td><td></td></tr><tr><td>FBS, qualified</td><td>Gibco</td><td>10270-106</td><td>Or any other brand</td></tr><tr><td>Glycine</td><td>Fisher BioReagents</td><td>BP381-1</td><td></td></tr><tr><td>GlycoBlue Coprecipitant</td><td>Invitrogen</td><td>AM9515</td><td>&lt;strong&gt;Used for DNA coprecipitation in section 4&lt;/strong&gt; (DNA purification)</td></tr><tr><td>HiCUP</td><td>0.8.2</td><td></td><td></td></tr><tr><td>HindIII, 100 U/&amp;micro;L</td><td>New England Biolabs</td><td>R0104T</td><td></td></tr><tr><td>IGEPAL CA-630</td><td>Sigma-Aldrich</td><td>I8896-50ML</td><td></td></tr><tr><td>Klenow EXO- 5000 units/mL</td><td>New England Biolabs</td><td>M0212L</td><td></td></tr><tr><td>Low-retention filter tips&amp;nbsp;(10 &amp;micro;L, 20 &amp;micro;L, 200 &amp;micro;L and 1000 &amp;micro;L)</td><td>ZeroTip</td><td>PMT233010, PMT252020, PMT231200, PMT252000</td><td></td></tr><tr><td>M220 Focused-ultrasonicator</td><td>Covaris</td><td>500295</td><td></td></tr><tr><td>Micro TUBE AFA Fiber Pre-slit snap cap 6 x 16 mm vials</td><td>Covaris</td><td>520045</td><td>&lt;strong&gt;For sonication in section 6&lt;/strong&gt; (sonication)</td></tr><tr><td>NheI-HF, 100 U/&amp;micro;L</td><td>New England Biolabs</td><td>R3131M</td><td></td></tr><tr><td>Nuclease-free molecular biology grade water</td><td>Sigma-Aldrich</td><td>W4502</td><td></td></tr><tr><td>PCR primers for quality controls</td><td>Integrated DNA Technologies</td><td>-</td><td></td></tr><tr><td>PCR strips&amp;nbsp;and caps</td><td>Agilent Technologies</td><td>410022, 401425</td><td></td></tr><tr><td>Phenol: Chloroform: Isoamyl Alcohol 25:24:1, Saturated with 10 mM Tris, pH 8.0, 1 mM EDTA</td><td>Sigma-Aldrich</td><td>P3803</td><td></td></tr><tr><td>Phusion&amp;nbsp;High-Fidelity PCR Master Mix with HF Buffer</td><td>New England Biolabs</td><td>M0531L</td><td>&lt;strong&gt;For amplification of the library in sections 9 &lt;/strong&gt;(dATP-tailing, adapter ligation and PCR amplification)&lt;br/&gt; &lt;strong&gt;and 11&lt;/strong&gt; (biotin pull-down and PCR amplification)</td></tr><tr><td>Protease inhibitor cocktail (EDTA-free)</td><td>Roche</td><td>11873580001</td><td></td></tr><tr><td>Proteinase K, recombinant, PCR grade</td><td>Roche</td><td>3115836001</td><td></td></tr><tr><td>Qubit 1x dsDNA High Sensitivity kit</td><td>Invitrogen</td><td>Q33230</td><td>&lt;strong&gt;For DNA quantification after precipitation in section 4&lt;/strong&gt; (DNA purification)</td></tr><tr><td>Qubit assay tubes</td><td>Invitrogen</td><td>Q32856</td><td></td></tr><tr><td>rCutsmart buffer</td><td>New England Biolabs</td><td>B6004S</td><td></td></tr><tr><td>RPMI Medium 1640 1x + GlutaMAX</td><td>Gibco</td><td>61870-010</td><td>Or any other brand</td></tr><tr><td>SDS - Solution 10% for molecular biology</td><td>PanReac AppliChem</td><td>A0676</td><td></td></tr><tr><td>Sodium acetate pH 5.2</td><td>Sigma-Aldrich</td><td>S7899-100ML</td><td></td></tr><tr><td>SureSelect custom 3-5.9 Mb library</td><td>Agilent Technologies</td><td>5190-4831</td><td>Custom designed mouse or human capture system, used for the capture</td></tr><tr><td>SureSelect Target Enrichment Box 1</td><td>Agilent Technologies</td><td>5190-8645</td><td>&lt;strong&gt;Used for the capture&lt;/strong&gt;</td></tr><tr><td>SureSelect Target Enrichment Kit ILM PE Full Adapter</td><td>Agilent Technologies</td><td>931107</td><td>&lt;strong&gt;Used for the capture&lt;/strong&gt;</td></tr><tr><td>T4 DNA ligase 1 U/&amp;micro;L</td><td>Invitrogen</td><td>15224025</td><td>&lt;strong&gt;For ligation in section 3&lt;/strong&gt; (ligation and decrosslink)</td></tr><tr><td>T4 DNA ligase 2000000/mL</td><td>New England Biolabs</td><td>M0202T</td><td>&lt;strong&gt;For ligation in section 9&lt;/strong&gt; (dATP-tailing, adapter ligation and PCR amplification)</td></tr><tr><td>T4 DNA polymerase 3000 units/mL</td><td>New England Biolabs</td><td>M0203L</td><td></td></tr><tr><td>T4 PNK 10000 units/mL</td><td>New England Biolabs</td><td>M0201L</td><td></td></tr><tr><td>Tapestation 4200 instrument</td><td>Agilent Technologies</td><td></td><td>&lt;strong&gt;For automated electrophoresis in section 9&lt;/strong&gt; (dATP-tailing, adapter ligation, and PCR amplification) &lt;strong&gt;and&lt;br/&gt; section 11&lt;/strong&gt; (Biotin pull-down and PCR amplification). Any other automated electrophoresis system is valid</td></tr><tr><td>Tapestation reagents</td><td>Agilent Technologies</td><td>5067-5582, 5067-5583, 5067-5584, 5067-5585,</td><td>&lt;strong&gt;For automated electrophoresis in section 9&lt;/strong&gt; (dATP-tailing, adapter ligation, and PCR amplification) &lt;strong&gt;and&lt;br/&gt; section 11&lt;/strong&gt; (Biotin pull-down and PCR amplification). Any other automated electrophoresis system is valid</td></tr><tr><td>Triton X-100 for molecular biology</td><td>PanReac AppliChem</td><td>A4975</td><td></td></tr><tr><td>Tween 20</td><td>Sigma-Aldrich</td><td>P9416-50ML</td><td></td></tr></tbody></table>

an integrated workflow to study the promoter-centric spatio-temporal genome architecture in scarce cell populations

Spatiotemporal gene transcription is tightly regulated by distal regulatory elements, such as enhancers and silencers, which rely on physical proximity with their target gene promoters to control transcription. Although these regulatory elements are easy to identify, their target genes are difficult to predict, since most of them are cell-type specific and may be separated by hundreds of kilobases in the linear genome sequence, skipping over other non-target genes. For several years, Promoter Capture Hi-C (PCHi-C) has been the gold standard for the association of distal regulatory elements to their target genes. However, PCHi-C relies on the availability of millions of cells, prohibiting the study of rare cell populations such as those commonly obtained from primary tissues. To overcome this limitation, low input Capture Hi-C (liCHi-C), a cost-effective and customizable method to identify the repertoire of distal regulatory elements controlling each gene of the genome, has been developed. liCHi-C relies on a similar experimental and computational framework as PCHi-C, but by employing minimal tube changes, modifying&#160;the reagent concentration and volumes, and swapping or eliminating steps, it accounts&#160;for minimal material loss during library construction. Collectively, liCHi-C enables the study of gene regulation and spatiotemporal genome organization in the context of developmental biology and cellular function.

liCHi-C offers the possibility of generating high-quality and resolution genome-wide promoter interactome libraries with as little as 50,000 cells53. This is accomplished by &#8211; besides the drastic reduction of reaction volumes and the use of DNA low-binding plasticware throughout the protocol&#160;&#8211; removing unnecessary steps from the original protocol, in which significant material losses occur. These include the phenol purification after decrosslinking, the biotin removal, and subsequ...

Watch this Scientific Journal Video about An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations at JoVE.com

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations  

Gene expression is regulated by interactions of gene promoters with distal regulatory elements. Here, we descirbe how low input Capture Hi-C (liCHi-C) allows the identification of these interactions in rare cell types, which were previously unmeasurable.

An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

Spatiotemporal gene transcription is tightly regulated by distal regulatory elements, such as enhancers and silencers, which rely on physical proximity ...

an-integrated-workflow-to-study-promoter-centric-spatio-temporal

Research

JoVE Journal

Genetics

1.9K Views.  Josep Carreras Leukaemia Research Institute. Met liCHi-C is de belangrijkste vraag die we proberen te beantwoorden hoe het chromatine interageert in de kern, en dus om een nieuwe laag van genregulatie te begrijpen. We hebben met liCHi-C bewezen dat we de genoomorganisatie van een bepaald monster kunnen onderzoeken, de niet-coderende mutatie geassocieerd met ziekte kunnen koppelen aan potentiële aangetaste genen en chromosomale herschikkingen kunnen detecteren, zoals translocatie, bijvoorbeeld in tumormonsters. Nu kunnen we de 3D-chroma...

Video: Author Spotlight: een geïntegreerde workflow om de promotor-centrische spatio-temporele genoomarchitectuur in schaarse celpopulaties te bestuderen  

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 ...

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture (4C)

During mammalian development, cell fates are determined through the establishment of regulatory networks that define the specificity, timing, and spatial patterns of gene expression. Embryoid bodies (EBs) derived from pluripotent stem cells have been a popular model to study the differentiation of the main three germ layers and to define regulatory circuits during cell fate specification. Although it is well-known that tissue-specific enhancers play an important role in these networks by interacting with promoters, assigning them to their relevant target genes still remains challenging. To make this possible, quantitative approaches are needed to study enhancer-promoter contacts and their dynamics during development. Here, we adapted a 4C method to define enhancers and their contacts with cognate promoters in the EB differentiation model. The method uses frequently cutting restriction enzymes, sonication, and a nested-ligation-mediated PCR protocol compatible with commercial DNA library preparation kits. Subsequently, the 4C libraries are subjected to high-throughput sequencing and analyzed bioinformatically, allowing detection and quantification of all sequences that have contacts with a chosen promoter. The resulting sequencing data can also be used to gain information about the dynamics of enhancer-promoter contacts during differentiation. The technique described for the EB differentiation model is easy to implement.

Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C

We report the application of quantitative chromosome conformation capture followed by high-throughput sequencing in embryoid bodies generated from embryonic stem cells. This technique allows to identify and quantitate the contacts between putative enhancers and promoter regions of a given gene during embryonic stem cell differentiation.

During mammalian development, cell fates are determined through the establishment of regulatory networks that define the specificity, timing, and spatial ...

Reusable Single Cell for Iterative Epigenomic Analyses

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic marks in a single cell and requiring data from other cells to distinguish signal from experimental background noise in a single cell. This paper describes a method to reuse the same single cell for iterative epigenomic analyses. 
In this experimental method, cellular proteins are first anchored to a polyacrylamide polymer instead of crosslinking them to protein and DNA, alleviating structural bias. This critical step allows repeated experiments with the same single cell. Next, a random primer with a scaffold sequence for proximity ligation is annealed to the genomic DNA, and the genomic sequence is added to the primer by extension using a DNA polymerase. Subsequently, an antibody against an epigenetic marker and control IgG, each labeled with different DNA probes, are bound to the respective targets in the same single cell. 
Proximity ligation is induced between the random primer and the antibody by adding a connector DNA with complementary sequences to the scaffold sequence of the random primer and the antibody-DNA probe. This approach integrates antibody information and nearby genome sequences in a single DNA product of proximity ligation. By enabling repeated experiments with the same single cell, this method allows an increase in data density from a rare cell and statistical analysis using only IgG and antibody data from the same cell. The reusable single cells prepared by this method can be stored for at least a few months and reused later to broaden epigenetic characterization and increase data density. This method provides flexibility to researchers and their projects.

The present protocol describes a single-cell method for iterative epigenomic analyses using a reusable single cell. The reusable single cell allows analyses of multiple epigenetic marks in the same single cell and statistical validation of the results.

Current single-cell epigenome analyses are designed for single use. The cell is discarded after a single use, preventing analysis of multiple epigenetic ...

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro when stem cells are spatially confined onto micropatterns, thus setting up experimental models which offer unique opportunities to identify, in vitro, the fundamental principles of biological organisation.
Here we describe our own implementation of the methodology. We adapted a photo-patterning technique to reduce the need for specialized equipment to make it easier to establish the method in a standard cell biology laboratory. We also developed a free, open-source and easy to install image analysis framework in order to precisely measure the preferential positioning of sub-populations of cells within colonies of standard shapes and sizes. This method makes it possible to reveal the existence of patterning events even in seemingly disorganized populations of cells. The technique provides quantitative insights and can be used to decouple influences of the environment (e.g., physical cues or endogenous signaling), on a given patterning process.

The method presented here uses micropatterning together with quantitative imaging to reveal spatial organization within mammalian cultures. The technique is easy to establish in a standard cell biology laboratory and offers a tractable system to study patterning in vitro.

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro ...

Developmental Biology

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, into close spatial proximity 2-6. Deciphering the relationship between chromosome organization and genome activity will aid in understanding genomic processes, like transcription and replication. However, little is known about how chromosomes fold. Microscopy is unable to distinguish large numbers of loci simultaneously or at high resolution. To date, the detection of chromosomal interactions using chromosome conformation capture (3C) and its subsequent adaptations required the choice of a set of target loci, making genome-wide studies impossible 7-10.
We developed Hi-C, an extension of 3C that is capable of identifying long range interactions in an unbiased, genome-wide fashion. In Hi-C, cells are fixed with formaldehyde, causing interacting loci to be bound to one another by means of covalent DNA-protein cross-links. When the DNA is subsequently fragmented with a restriction enzyme, these loci remain linked. A biotinylated residue is incorporated as the 5' overhangs are filled in. Next, blunt-end ligation is performed under dilute conditions that favor ligation events between cross-linked DNA fragments. This results in a genome-wide library of ligation products, corresponding to pairs of fragments that were originally in close proximity to each other in the nucleus. Each ligation product is marked with biotin at the site of the junction. The library is sheared, and the junctions are pulled-down with streptavidin beads. The purified junctions can subsequently be analyzed using a high-throughput sequencer, resulting in a catalog of interacting fragments.
Direct analysis of the resulting contact matrix reveals numerous features of genomic organization, such as the presence of chromosome territories and the preferential association of small gene-rich chromosomes. Correlation analysis can be applied to the contact matrix, demonstrating that the human genome is segregated into two compartments: a less densely packed compartment containing open, accessible, and active chromatin and a more dense compartment containing closed, inaccessible, and inactive chromatin regions. Finally, ensemble analysis of the contact matrix, coupled with theoretical derivations and computational simulations, revealed that at the megabase scale Hi-C reveals features consistent with a fractal globule conformation.

The Hi-C method allows unbiased, genome-wide identification of chromatin interactions (1). Hi-C couples proximity ligation and massively parallel sequencing. The resulting data can be used to study genomic architecture at multiple scales: initial results identified features such as chromosome territories, segregation of open and closed chromatin, and chromatin structure at the megabase scale.

The three-dimensional folding of chromosomes compartmentalizes the genome and and can bring distant functional elements, such as promoters and enhancers, ...

Biology

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.

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 ...

Neuroscience

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators.
Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1&#160;to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Presented is a flexible informatics workflow enabling multiplexed image-based analysis of fluorescently labeled cells. The workflow quantifies nuclear and cytoplasmic markers and computes marker translocation between these compartments. Procedures are provided for perturbation of cells using siRNA and reliable methodology for marker detection by indirect immunofluorescence in 96-well formats.

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly ...

DamID-seq: Genome-wide Mapping of Protein-DNA Interactions by High Throughput Sequencing of Adenine-methylated DNA Fragments

The DNA adenine methyltransferase identification (DamID) assay is a powerful method to detect protein-DNA interactions both locally and genome-wide. It is an alternative approach to chromatin immunoprecipitation (ChIP). An expressed fusion protein consisting of the protein of interest and the E. coli DNA adenine methyltransferase can methylate the adenine base in GATC motifs near the sites of protein-DNA interactions. Adenine-methylated DNA fragments can then be specifically amplified and detected. The original DamID assay detects the genomic locations of methylated DNA fragments by hybridization to DNA microarrays, which is limited by the availability of microarrays and the density of predetermined probes. In this paper, we report the detailed protocol of integrating high throughput DNA sequencing into DamID (DamID-seq). The large number of short reads generated from DamID-seq enables detecting and localizing protein-DNA interactions genome-wide with high precision and sensitivity. We have used the DamID-seq assay to study genome-nuclear lamina (NL) interactions in mammalian cells, and have noticed that DamID-seq provides a high resolution and a wide dynamic range in detecting genome-NL interactions. The DamID-seq approach enables probing NL associations within gene structures and allows comparing genome-NL interaction maps with other functional genomic data, such as ChIP-seq and RNA-seq.

We describe herein an assay by coupling DNA adenine methyltransferase identification (DamID) to high throughput sequencing (DamID-seq). This improved method provides a higher resolution and a wider dynamic range, and allows analyzing DamID-seq data in conjunction with other high throughput sequencing data such as ChIP-seq, RNA-seq, etc.

The DNA adenine methyltransferase identification (DamID) assay is a powerful method to detect protein-DNA interactions both locally and genome-wide. It is ...

An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

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