Name: flow-sorting and exome sequencing of the reed-sternberg cells of classical hodgkin lymphoma
Uploaded: 2017-06-10T13:00:00
Description: Watch this Scientific Journal Video about Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma at JoVE.com

The development of this project method was funded by the Department of Pathology and Laboratory Medicine of Weill Cornell Medical College. We acknowledge the Tri-Institutional Training Program in Computational Biology and Medicine for partial funding. We would like to thank the scientists who shared their time and knowledge with us, especially Maryke Appel; Dan Burgess; Iwanka Kozarewa; Chad Locklear; and everyone from the Weill Cornell Medical College Genomics Core Facility, including Jenny Zhang, Xiaobo (Shawn) Liang, Dong Xu, Wei Zhang, Huimin Shang, Tatiana Batson, and Tuo Zhang.

1. Tissue Processing and Freezing
<ol>
	<li>Collect lymph node tissue in phosphate-buffered saline (PBS) or Roswell Park Memorial Institute medium (RPMI) and process within 24 h of collection. Transfer excised lymph node tissue9 to a Petri dish containing 10 mL of RPMI with 2% fetal calf serum (FCS) and finely mince it with a fresh scalpel blade. Use the back of a 10-mL syringe plunger to further grind/dissociate the tissue.</li>
	<li>Transfer the liquid to a 50-mL conical tube through a 100 &#1...

<ol>
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Future applications or directions after mastering this technique
This work allows for exome sequencing from samples containing at least 10 ng of DNA. In the clinical context, this limit excludes most fine-needle aspiration samples due to insufficient material, but it includes adequate core biopsies and excisional biopsy samples. This will enable the acquisition of data from a larger set of possible samples.
Critical steps within the protocol...

Advancements in cancer genomics as a result of next-generation sequencing have led to significant breakthroughs in the identification of therapeutic targets and in prognostication for many hematologic and non-hematologic neoplasms. New individualized treatment strategies based on specific genomic alterations are rapidly being introduced in many tumor types (reviewed in references1,2). Despite significant progress in lymphoma genomics, the genome of the neoplastic HRS cells in classical Hodgkin lymphoma (CHL) had been underexplored. The investigations have been hampered by the scarcity of neoplastic HRS cells within a reactive microenvironment, making it difficult to isolate purified HRS cell populations3.
The method for isolating viable HRS cells from primary tumors was developed by Fromm et al.4,5,6. The method uses an eight-antibody cocktail, consisting of CD30, CD15, CD40, CD95, CD45 CD20, CD5, and CD64, to unequivocally identify HRS cells from a CHL tumor suspension. Using this methodology, we are able to isolate at least 1,000 viable HRS cells from fresh or frozen cell suspensions from tumor biopsies consisting of at least 107 cells (approximately 10 mg of tissue). The purity is greater than 90% by flow cytometric analysis and is estimated to be least 80% by exome genomic analysis of ten consecutive cases.
We have refined a flow cytometric cell isolation technique that has greatly eased the process, allowing for the rapid isolation of thousands of viable HRS cells from primary CHL tumors7. We have utilized the technique to produce what is believed to be the first whole-exome sequence of the tumor cells in primary cases of Hodgkin lymphoma. Our studies demonstrate the feasibility of high-throughput, genome-wide studies of individual CHL cases and have already led to the identification of novel genomic alterations with the potential to explain aspects of CHL pathogenesis.
We further developed a pipeline to utilize the extracted DNA for high-throughput genomic studies. In order to achieve reliable results from as few as 1,000 sorted HRS cells (thhe minimum obtained from sequential cases), we further developed a modified next-generation DNA library construction procedure8 that allowed us to increase adaptor ligation efficiency and to generate DNA fragment libraries without excessive amplification. This method allows for the analysis of routine clinical samples and the detection of recurrent mutations and chromosomal alterations7.

<table border="0" cellpadding="0" cellspacing="0" width="1576">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Petri or Cell Culture Dish (sterile)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td style="width:535px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">RPMI-1640 Media</td>
			<td>Roswell Park Memorial Institute</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Fetal Calf Serum (FCS), (heat inactivated)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td colspan="2" height="21" style="height:21px;">Freezing Media (RPMI, 20% FCS, 10% dimethylsulfoxide (DMSO))-make fresh and keep sterile</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">RPMI with 2% FCS (make fresh or store for up to 1 month)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">scalpel with fresh blade</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10 ml syringe (no needle)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cryogenic vials</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">50 ml conical centrifuge tubes, force</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Centrifuge</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td>capable of handling 50 ml conical centrifuge tubes and providing 400g</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Hepes buffer(1M, cell culture grade)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">phosphate buffered saline (PBS)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Pluoronic-F68</td>
			<td style="width:352px;">Thermo-Fisher</td>
			<td style="width:119px;">24040-032</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">DNAase-I</td>
			<td style="width:352px;">Sigma-Aldrich, St. Louis, MO</td>
			<td style="width:119px;">D4527-10KU</td>
			<td>store as 5mg/ml in RPMI in -200C</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Bovine Serum Albumin (BSA)</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Sort Media (PBS+2%BSA+25mM HEPES+ Pluoronic &#8211;F68 (1X))</td>
			<td style="width:352px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">CD64-FITC (22)</td>
			<td style="width:352px;">Beckman Coulter, Miami, FL</td>
			<td style="width:119px;"></td>
			<td>20 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD30-PE (BerH83)</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td>20 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD5-ECD (BL1a)</td>
			<td style="width:352px;">Beckman Coulter, Miami, FL</td>
			<td style="width:119px;"></td>
			<td>10 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD40-PerCP-eFluor 710 (1C10)</td>
			<td style="width:352px;">Ebiosciences, San Diego, CA</td>
			<td style="width:119px;"></td>
			<td>5 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD20-PC7 (B9E9)</td>
			<td style="width:352px;">Beckman Coulter, Miami, FL</td>
			<td style="width:119px;"></td>
			<td>10 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD15-APC (HI98)</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td>20 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD45 APC-H7 (2D1)</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td>Can be substituted with 10 uL suggested volume of CD45-Krome Orange (J.33, Beckman Coulter); Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD95-Pacific Blue (DX2)</td>
			<td style="width:352px;">Life Technologies, Grand Island, NY</td>
			<td style="width:119px;"></td>
			<td>5 uL suggested starting volume; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">CD2 (5 &#956;g; clone RPA-2.10)</td>
			<td style="width:352px;">Biolegend, San Diego, CA</td>
			<td style="width:119px;"></td>
			<td>For optional protocol; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">CD54 (10 &#956;g; clone 84H10)</td>
			<td style="width:352px;">Serotec, Oxford, United Kingdom</td>
			<td style="width:119px;"></td>
			<td>For optional protocol; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">CD58 (10 &#956;g; clone TS2/9)</td>
			<td style="width:352px;">eBioscience, San Diego, CA</td>
			<td style="width:119px;"></td>
			<td>For optional protocol; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">LFA-1 (12 &#956;g; clone MHM23)</td>
			<td style="width:352px;">Novus Biologicals, Littleton, CO</td>
			<td style="width:119px;"></td>
			<td>For optional protocol; Titering is suggested</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BD CS&#38;T Beads</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BD Accudrop Beads</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BC Versa Comp antibody capture beads</td>
			<td style="width:352px;">Beckman Coulter, Miami, FL</td>
			<td style="width:119px;"></td>
			<td>Compensation Beads</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">BD-FACS ARIA special research order instrument using 5 lasers</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td>any BD-FACS aria with capabilities to detect the fluorochromes in the antibody panel should be sufficient</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Wizard</td>
			<td style="width:352px;">Promega</td>
			<td>A2360</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10 mM Tris-Cl buffer</td>
			<td style="width:352px;">NA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Qubit dsDNA HS Assay kit</td>
			<td>Life Technologies, Carlsbad, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">S2 Sonicator</td>
			<td style="width:352px;">Covaris, Woburn, MA</td>
			<td style="width:119px;"></td>
			<td>Alternatives may be substituted</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">microTUBE</td>
			<td style="width:352px;">Covaris, Woburn, MA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Low-Throughput Library Preparation Kit</td>
			<td style="width:352px;">Kapa Biosystems, Wilmington, MA</td>
			<td>KK8221</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Sybr Green</td>
			<td style="width:352px;">Sigma-Aldrich, St. Louis, MO</td>
			<td style="width:119px;">S9430</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Agencourt AMPure XP Beads</td>
			<td style="width:352px;">Beckman Coulter, Miami, FL</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Bioanalyzer</td>
			<td style="width:352px;">Agilent Technologies, Santa Clara, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SeqCap EZ Exome v.3.0</td>
			<td style="width:352px;">Roche Nimblegen</td>
			<td style="width:119px;">6465684001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">HiSeq</td>
			<td style="width:352px;">Illumina</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">TruSeq-style Universal adapter</td>
			<td style="width:352px;">Integrated DNA Technologies (IDT), Coralville, Iowa</td>
			<td style="width:119px;"></td>
			<td>HPLC purification; AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGAT*C*T</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">TruSeq-style index adapter</td>
			<td style="width:352px;">Integrated DNA Technologies (IDT), Coralville, Iowa</td>
			<td style="width:119px;"></td>
			<td>HPLC purification; /5Phos/GATCGGAAGAGCACACGTCTGAACTCCAGTCACNNNNNNATCTCGTATGCCGTCTTCTGCTTG</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">TruSeq-style PCR primer 1</td>
			<td style="width:352px;">Integrated DNA Technologies (IDT), Coralville, Iowa</td>
			<td style="width:119px;"></td>
			<td>AATGATACGGCGACCACCGAGA</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">TruSeq-style PCR primer 2</td>
			<td style="width:352px;">Integrated DNA Technologies (IDT), Coralville, Iowa</td>
			<td style="width:119px;"></td>
			<td>CAAGCAGAAGACGGCATACGAG</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">Nuclease Free Duplex Buffer</td>
			<td style="width:352px;">Integrated DNA Technologies (IDT), Coralville, Iowa</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">BD FACSDIVA software</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">BD Falcon Tubes</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:571px;">BD Flow Tubes</td>
			<td style="width:352px;">BD Biosciences, San Jose, CA</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
	</tbody>
</table>

flow-sorting and exome sequencing of the reed-sternberg cells of classical hodgkin lymphoma

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically comprise less than 1% of the tumor mass. Material derived from bulk tumor contains tumor content at a concentration insufficient for characterization. Therefore, fluorescence activated cell sorting using eight antibodies, as well as side- and forward-scatter, is described here as a method of rapidly separating and concentrating with high purity thousands of HRS cells from the tumor for subsequent study. At the same time, because standard protocols for exome sequencing typically require 100-1,000 ng of input DNA, which is often too high, even with flow sorting, we also provide an optimized, low-input library construction protocol capable of producing high-quality data from as little as 10 ng of input DNA. This combination is capable of producing next-generation libraries suitable for hybridization capture of whole-exome baits or more focused targeted panels, as desired. Exome sequencing of the HRS cells, when compared against healthy intratumor T or B cells, can identify somatic alterations, including mutations, insertions and deletions, and copy number alterations. These findings elucidate the molecular biology of HRS cells and may reveal avenues for targeted drug treatments.

A bioanalyzer plot should be taken after library amplification and 0.8x bead cleanup. One should see a &#34;normal-like&#34; distribution of fragment sizes in the desired range (Figure 2a). Deviations from this shape, such as a visible &#34;shoulder&#34; in the curve, indicate the presence of a high or low molecular weight artifact. For example, Figure 2b-2d shows examples of libraries containing visible artifact...

Watch this Scientific Journal Video about Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma at JoVE.com

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically ...

The overall goal of this procedure is to separate and concentrate viable Hodgkin Reed-Sternberg or HRS cells from inflammatory lymphocytic classical Hodgkin lymphoma or CHL tumors for the generation and analysis of high quality whole exome next generation sequencing data. This method can answer key questions in CHR biology, including identification of key driver mutations, immuno escape mutations, and also looking at genic diversity within the classification. This technique yields tumor derived DNA that is very high in quality and purity.Facilitating the generation of next generation sequencing libraries without the need for a pre-amplification step. This technique may have important implications towards the diagnosis of Hodgkin lymphoma as it may help with a sub classification and prognostication. It may also influence a choice of therapy, as some alterations may indicate suscept-ivity or resistance to specific drugs.Jonathan From first has this idea when he discovered how to visualize HRS cells by flow cytometry and perform the first sorting experiments with these cells. Before preparing the cells, mix the pre-titred antibodies in a dark glass vial. Then, add PBS and BSA to bring the antibody cocktail up to a 100 microliter volume.And transfer the vial from liquid nitrogen into an ice bucket or dry ice. Next, rapidly thaw the cells of interest in a 37 degrees Celsius water bath. When only a small frozen portion remains, pour the cells into a 50 milliliter conical tube containing 45 milliliters of 37 degrees celsius thawing medium, and rinse the cryogenic vial two times with one milliliter of fresh thawing medium.After pooling both rinses, allow the cells to digest at room temperature for 15 minutes. When the cells have re-equilibrated, collect them by centrifugation. Aspirate all but the last 200 microliters of the supernatant.Re suspend the cells in the remaining thawing medium and allow the cells to rest for another two to three minutes. Then, incubate the cells in 100 microliters of the antibody cocktail for 15 minutes at room temperature, protected from light. At the end of the incubation, wash the cells in three milliliters of sorting medium, re-suspending the pellet in one milliliter of fresh sorting medium.Then, filter the cells through a five milliliter flow tube top strainer. Rinsing the tube and the strainer with an additional one milliliter of sorting medium, and hold the cells on ice. Before beginning the cell sorting, in the flow cytometer software under the experiment menu, select new experiment and open the instrument status window.In the parameters tab, delete any unused parameters. Then, reopen the experiment tab and select the compensation setup to create the compensation controls. In the browser window, click the plus sign to expand the compensation control specimen, and run the compensation control tubes without recording the data.Adjust the detector voltages as necessary so that the positively stained bead populations for each flora chrome are between the 10, 000 and 100, 000 channel. And of the brightest in their primary detection channel. Record the voltages needed for each parameter for each tube.Then, under the compensation control specimen, single left click to highlight the unstained control tube and load the unstained control tube onto the sample stage. In the acquisition control window, click load, and run the individual compensation controls into the detector voltage fields for all the parameters to manually enter the determined voltages. Click record to obtain the unstained control data.Then run all of the remaining compensation controls, recording the data without changing any of the detector settings. When all of the controls have been analyzed, run a tube of sterile deionized water for five minutes to clear the instrument of any residual material before proceeding. To gate the cells for HRS sorting, load the experimental tube and record at least 100, 000 events while adjusting the flow rate to acquire 3, 000 to 4, 000 events per second.Make sure you record enough events to visualize a population that can be as few as one in 1, 000 cells. To identify the somatic B and T cell controls, gate on the CD20, and CD5 positive cells respectively. When all of the gates have been set, sort the cells into pre chilled 15 milliliter conical tubes containing seven to eight milliliters of collection medium.At the end of the sort, transfer the isolated cell populations into 1.5 milliliter micro centrifuge tubes. And pellet the cells by centrifugation. Then, wash the cells in one milliliter of fresh PBS and remove the supernatants from each tube, taking care not to disturb the tiny pellets.After library amplification and point 8X bead cleanup, a normal light distribution of fragment sizes in the desired range should be observed. Libraries that exhibit deviations from this shape indicate the presence of a high or low molecular weight artifact, and ideally should not be sequenced. For example, and adapter dimer may sometimes carry over through the first pointed X bead cleanup, appearing as a sharp peak centered around 125 to 130 base pairs.In this case, an additional pointed X bead clean up should be performed, followed by a repeat visualization of the size distribution to ensure the successful removal of the dimer. After multiplexing sequencing of four samples per lane, a median depth of coverage of 50 to 100 X across the target is achievable. Although copy number plots generated from a one nanogram library may results in spurious copy number gains and losses.Approximately 70%of cases of classical Hodgkin lymphoma carry B2M and 820 mutations, and or deletions that appear to be clonal, and that can be used to estimate the relative tumor content. If T cells are used as the somatic controls, HRS sequencing will demonstrate significant copy number gains in the positions corresponding to the T cell receptor alpha, delta, and beta positions. As well as significant losses in the B cell receptor heavy, and kappa light chain positions with an overall mutational burden of 100 to 400 somatic mutations per exome case.Once mastered, this technique including the cell sorting and the sequencing library construction, can be completed in three to four days if it is performed properly. Following this procedure, we can perform larger prospective studies and other methods, like epigenetics, proteomics, and metabalomics to gain more knowledge about Hodgkin lymphoma and progress towards more specific personalized therapies. After its development the method allowed us to study HRS cells with high purity in relatively large numbers.After watching this video, you should have a good understanding of how to isolate HRS cells and to initiate their genomic analysis.

flow-sorting-exome-sequencing-reed-sternberg-cells-classical-hodgkin

Research

JoVE Journal

Genetics

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and microbial populations. Traditional methods for assessing genetic heterogeneity have been limited by low resolution, low sensitivity, and/or low specificity. Single cell sequencing has emerged as a powerful tool for detecting genetic heterogeneity with high resolution, high sensitivity and, when appropriately analyzed, high specificity. Here we provide a protocol for the isolation, whole genome amplification, sequencing, and analysis of single cells. Our approach allows for the reliable identification of megabase-scale copy number variants in single cells. However, aspects of this protocol can also be applied to investigate other types of genetic alterations in single cells.

Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged as a powerful tool for gene-expression analysis and transcriptome mapping. However, handling RNA-Seq datasets requires sophisticated computational expertise and poses inherent challenges for biology researchers. This bottleneck has been mitigated by the open access Galaxy project that allows users without bioinformatics skills to analyze RNA-Seq data, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID), a Gene Ontology (GO) term analysis suite that helps derive biological meaning from large data sets. However, for first-time users and bioinformatics' amateurs, self-learning and familiarization with these platforms can be time-consuming and daunting. We describe a straightforward workflow that will help C. elegans researchers to isolate worm RNA, conduct an RNA-Seq experiment and analyze the data using Galaxy and DAVID platforms. This protocol provides stepwise instructions for using the various Galaxy modules for accessing raw NGS data, quality-control checks, alignment, and differential gene expression analysis, guiding the user with parameters at every step to generate a gene list that can be screened for enrichment of gene classes or biological processes using DAVID. Overall, we anticipate that this article will provide information to C. elegans researchers undertaking RNA-Seq experiments for the first time as well as frequent users running a small number of samples.

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Galaxy and DAVID have emerged as popular tools that allow investigators without bioinformatics training to analyze and interpret RNA-Seq data. We describe a protocol for C. elegans researchers to perform RNA-Seq experiments, access and process the dataset using Galaxy and obtain meaningful biological information from the gene lists using DAVID.

Next generation sequencing (NGS) technologies have revolutionized the nature of biological investigation. Of these, RNA Sequencing (RNA-Seq) has emerged ...

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have been directed toward elucidation of the location and timing of initiation of genome duplication rather than its completion. However, it is critical that we understand regions of the genome that are last to complete replication, because these regions suffer elevated levels of chromosomal breakage and mutation, and they have been associated with both disease and aging. Here we describe how we have extended a technique that has been used to monitor replication initiation to instead identify those regions of the genome last to complete replication. This approach is based on a combination of flow cytometry and high throughput sequencing. Although this report focuses on the application of this technique to yeast, the approach can be used with any cells that can be sorted in a flow cytometer according to DNA content.

We describe a technique for combining flow cytometry and high throughput sequencing to identify late replicating regions of the genome.

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near full-length (intact and defective), HIV-1 proviruses. FLIPS allows determination of the genetic composition of integrated HIV-1 within a cell population. Through identifying defects within HIV-1 proviral sequences that arise during reverse transcription, such as large internal deletions, deleterious stop codons/hypermutation, frameshift mutations, and mutations/deletions in cis acting elements required for virion maturation, FLIPS can identify integrated proviruses incapable of replication. The FLIPS assay can be utilized to identify HIV-1 proviruses that lack these defects and are&#160;therefore potentially replication-competent. The FLIPS protocol involves: lysis of HIV-1 infected cells, nested PCR of near full-length HIV-1 proviruses (using primers targeted to the HIV-1 5&#39; and 3&#39; LTR), DNA purification and quantification, library preparation for Next-generation Sequencing (NGS), NGS, de novo assembly of proviral contigs, and a simple process of elimination for identifying replication-competent proviruses. FLIPS provides advantages over traditional methods designed to sequence integrated HIV-1 proviruses, such as single-proviral sequencing. FLIPS amplifies and sequences near full-length proviruses enabling replication competency to be determined, and also uses fewer amplification primers, preventing the consequences of primer mismatches. FLIPS is a useful tool for understanding the genetic landscape of integrated HIV-1 proviruses, especially within the latent reservoir, however, its utilization can extend to any application in which the genetic composition of integrated HIV-1 is required.

Full-length individual proviral sequencing (FLIPS) provides an efficient and high-throughput method for the amplification and sequencing of single, near full-length (intact and defective) HIV-1 proviruses and allows for determination of their potential replication-competency. FLIPS overcomes limitations of previous assays designed to sequence the latent HIV-1 reservoir.

The Full-Length Individual Proviral Sequencing (FLIPS) assay is an efficient and high-throughput method designed to amplify and sequence single, near ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

Isolating, Sequencing and Analyzing Extracellular MicroRNAs from Human Mesenchymal Stem Cells

Extracellular and circulating RNAs (exRNA) are produced by many cell types of the body and exist in numerous bodily fluids such as saliva, plasma, serum, milk and urine. One subset of these RNAs are the posttranscriptional regulators &#8211; microRNAs (miRNAs). To delineate the miRNAs produced by specific cell types, in vitro culture systems can be used to harvest and profile exRNAs derived from one subset of cells. The secreted factors of mesenchymal stem cells are implicated in alleviating numerous diseases and is used as the in vitro model system here. This paper describes the process of collection, purification of small RNA and library generation to sequence extracellular miRNAs. ExRNAs from culture media differ from cellular RNA by being low RNA input samples, which calls for optimized procedures. This protocol provides a comprehensive guide to small exRNA sequencing from culture media, showing quality control checkpoints at each step during exRNA purification and sequencing.

This protocol demonstrates how to purify extracellular microRNAs from cell culture media for small RNA library construction and next generation sequencing. Various quality control checkpoints are described to allow readers to understand what to expect when working with low input samples like exRNAs.

Extracellular and circulating RNAs (exRNA) are produced by many cell types of the body and exist in numerous bodily fluids such as saliva, plasma, serum, ...

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely related biochemical pathways. Previous methods such as the Synthetic Genetic Array (SGA) analysis, and random mutagenesis techniques using ultraviolet (UV) or chemicals like ethyl methanesulfonate (EMS) or N-ethyl-N- nitrosourea (ENU), have been widely used but are often costly and laborious. Also, these mutagen-based screening methods are frequently associated with severe side effects on the organism, inducing multiple mutations that add to the complexity of isolating the suppressors. Here, we present a simple and effective protocol to identify suppressor mutations in mutants which confer a growth defect in Schizosaccharomyces pombe. The fitness of cells with a growth deficiency in standard rich liquid media or synthetic liquid media can be monitored for recovery using an automated 96-well plate reader over an extended period. Once a cell acquires a suppressor mutation in the culture, its descendants outcompete those of the parental cells. The recovered cells that have a competitive growth advantage over the parental cells can then be isolated and backcrossed with the parental cells. The suppressor mutations are then identified using whole-genome sequencing. Using this approach, we have successfully isolated multiple suppressors that alleviate the severe growth defects caused by loss of Elf1, an AAA+ family ATPase that is important in nuclear mRNA transport and maintenance of genomic stability. There are currently over 400 genes in S. pombe with mutants conferring a growth defect. As many of these genes are uncharacterized, we propose that our method will hasten the identification of novel functional interactions with this user-friendly, high-throughput approach.

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

We present a simple suppressor screen protocol in fission yeast. This method is efficient, mutagen-free, and&#160; selective&#160; for&#160; mutations that&#160; often&#160; occur at&#160; &#160;a&#160; single&#160; genomic&#160; locus.&#160; The protocol is suitable for isolating suppressors that alleviate growth defects in liquid culture that are caused by a mutation or a drug.

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely ...

Semiconductor Sequencing for Preimplantation Genetic Testing for Aneuploidy

Chromosomal aneuploidy, one of the main causes leading to embryonic development arrest, implantation failure, or pregnancy loss, has been well documented in human embryos. Preimplantation genetic testing for aneuploidy (PGT-A) is a genetic test that significantly improves reproductive outcomes by detecting chromosomal abnormalities of embryos. Next-generation sequencing (NGS) provides a high-throughput and cost-effective approach for genetic analysis and has shown clinical applicability in PGT-A. Here, we present a rapid and low-cost semiconductor sequencing-based NGS method for screening of aneuploidy in embryos. The first step of the workflow is whole genome amplification (WGA) of the biopsied embryo specimen, followed by construction of sequencing library, and subsequent sequencing on the semiconductor sequencing system. Generally, for a PGT-A application, 24 samples can be loaded and sequenced on each chip generating 60&#8722;80 million reads at an average read length of 150 base pairs. The method provides a refined protocol for performing template amplification and enrichment of sequencing library, making the PGT-A detection reproducible, high-throughput, cost-efficient, and timesaving. The running time of this semiconductor sequencer is only 2&#8722;4 hours, shortening the turnaround time from receiving samples to issuing reports into 5 days. All these advantages make this assay an ideal method to detect chromosomal aneuploidies from embryos and thus, facilitate its wide application in PGT-A.

Here, we introduce a semiconductor sequencing method for preimplantation genetic testing for aneuploidy (PGT-A) with the advantages of short turnaround time, low cost, and high throughput.

Chromosomal aneuploidy, one of the main causes leading to embryonic development arrest, implantation failure, or pregnancy loss, has been well documented ...

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, and was deployed to West Africa during the recent Ebola virus epidemic, highlighting this possibility. In addition to its practical advantages (low cost, ease of equipment transport and use), this technology also provides fundamental advantages over second-generation sequencing approaches, particularly the very long read length, ability to directly sequence RNA, and real-time availability of data. Raw read accuracy is lower than with other sequencing platforms, which represents the main limitation of this technology; however, this can be partially mitigated by the high read depth generated. Here, we present a field-compatible protocol for sequencing of the mRNAs encoding for Niemann-Pick C1, which is the cellular receptor for ebolaviruses. This protocol encompasses extraction of RNA from animal blood samples, followed by RT-PCR for target enrichment, barcoding, library preparation, and the sequencing run itself, and can be easily adapted for use with other DNA or RNA targets.

Nanopore sequencing is a novel technology that allows cost-effective sequencing in remote locations and resource-poor settings. Here, we present a protocol for sequencing of mRNAs from whole blood that is compatible with such conditions.

Sequencing in remote locations and resource-poor settings presents unique challenges. Nanopore sequencing can be successfully used under such conditions, ...