このプロジェクト方法の開発は、Weill Cornell Medical Collegeの病理学および実験医学部門によって資金提供されました。私たちは、部分的な資金調達のために、計算生物学と医学の3つの機関のトレーニングプログラムを認めています。時間と知識を私たちと共有した科学者、特にMaryke Appelに感謝します。ダンバージェス; Iwanka Kozarewa;チャド・ロックリー; Jenny Zhang、Xiaobo（Shawn）Liang、Dong Xu、Wei Zhang、Huimin Shang、Tatiana Batson、Tuo Zhangを含むWeill Cornell Medical CollegeのGenomics Core Facilityの皆さんです。

<ol>
	<li>Abrams, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=National+Cancer+Institute's+Precision+Medicine+Initiatives+for+the+new+National+Clinical+Trials+Network.">National Cancer Institute's Precision Medicine Initiatives for the new National Clinical Trials Network.</a> American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting. , 71-76 (2014).</li><li>Gagan, J., Van Allen, E. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next-generation+sequencing+to+guide+cancer+therapy.">Next-generation sequencing to guide cancer therapy.</a> Genome medicine. 7, 80 (2015).</li><li>Matsuki, E., Younes, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lymphomagenesis+in+Hodgkin+lymphoma.">Lymphomagenesis in Hodgkin lymphoma.</a> Seminars in cancer biology. 34, 14-21 (2015).</li><li>Fromm, J. R., Kussick, S. J., Wood, B. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+and+purification+of+classical+Hodgkin+cells+from+lymph+nodes+by+flow+cytometry+and+flow+cytometric+cell+sorting.">Identification and purification of classical Hodgkin cells from lymph nodes by flow cytometry and flow cytometric cell sorting.</a> Am J Clin Pathol. 126 (5), 764-780 (2006).</li><li>Fromm, J. R., Thomas, A., Wood, B. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+cytometry+can+diagnose+classical+hodgkin+lymphoma+in+lymph+nodes+with+high+sensitivity+and+specificity.">Flow cytometry can diagnose classical hodgkin lymphoma in lymph nodes with high sensitivity and specificity.</a> Am J Clin Pathol. 131 (3), 322-332 (2009).</li><li>Roshal, M., Wood, B. L., Fromm, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+cytometric+detection+of+the+classical+hodgkin+lymphoma:+clinical+and+research+applications.">Flow cytometric detection of the classical hodgkin lymphoma: clinical and research applications.</a> Advances in hematology. 2011, 387034 (2011).</li><li>Reichel, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Flow+sorting+and+exome+sequencing+reveal+the+oncogenome+of+primary+Hodgkin+and+Reed-Sternberg+cells.">Flow sorting and exome sequencing reveal the oncogenome of primary Hodgkin and Reed-Sternberg cells.</a> Blood. 125 (7), 1061-1072 (2015).</li><li>Kozarewa, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Modified+Method+for+Whole+Exome+Resequencing+from+Minimal+Amounts+of+Starting+DNA.">A Modified Method for Whole Exome Resequencing from Minimal Amounts of Starting DNA.</a> PLoS ONE. 7 (3), e32617 (2012).</li><li>Brunicardi, F. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Schwartz's Principles of Surgery. , (2014).</li><li>Kantor, A. B., Roederer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FACS+analysis+of+leukocytes.">FACS analysis of leukocytes.</a> Handbook of Experimental Immunology. 2, (1996).</li><li>Sanders, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+pathways+of+adhesion+in+spontaneous+rosetting+of+T-lymphocytes+to+the+Hodgkin's+cell+line+L428.">Molecular pathways of adhesion in spontaneous rosetting of T-lymphocytes to the Hodgkin's cell line L428.</a> Cancer Res. 48 (1), 37-40 (1988).</li><li>Biosciences. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> FACSAria II User's Guide. Part No. 644832, Revision A. , (2009).</li><li>. Qubit 3.0 Fluorometer, Catalog Number Q33216 Available from: <a target="_blank" href="https://www.thermofisher.com/order/catalog/product/Q33216">https://www.thermofisher.com/order/catalog/product/Q33216</a> (2017)</li><li>Roche Nimblegen. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> SeqCap EZ Library SR User's Guide ver. 4.1. , (2013).</li><li>Li, H., Durbin, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+and+accurate+short+read+alignment+with+Burrows-Wheeler+transform.">Fast and accurate short read alignment with Burrows-Wheeler transform.</a> Bioinformatics. 25 (14), 1754-1760 (2009).</li><li>Li, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Sequence+Alignment/Map+format+and+SAMtools.">The Sequence Alignment/Map format and SAMtools.</a> Bioinformatics. 25 (16), 2078-2079 (2009).</li><li>Saunders, C. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Strelka:+accurate+somatic+small-variant+calling+from+sequenced+tumor-normal+sample+pairs.">Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs.</a> Bioinformatics. 28 (14), 1811-1817 (2012).</li><li>Cingolani, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+program+for+annotating+and+predicting+the+effects+of+single+nucleotide+polymorphisms,+SnpEff:+SNPs+in+the+genome+of+Drosophila+melanogaster+strain+w1118;+iso-2;+iso-3.">A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.</a> Fly (Austin). 6 (2), 80-92 (2012).</li><li>Dobin, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=STAR:+ultrafast+universal+RNA-seq+aligner.">STAR: ultrafast universal RNA-seq aligner.</a> Bioinformatics. 29 (1), 15-21 (2013).</li><li>Thorvaldsdottir, H., Robinson, J. T., Mesirov, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrative+Genomics+Viewer+(IGV):+high-performance+genomics+data+visualization+and+exploration.">Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.</a> Briefings in bioinformatics. 14 (2), 178-192 (2013).</li><li>. DNA copy number data analysis. v.R package version 1.34.0 Available from: <a target="_blank" href="https://omictools.com/dnacopy-tool">https://omictools.com/dnacopy-tool</a> (2013)</li></ol>

著者は何も開示することはない。

この技術を習得した後のアプリケーションまたは方向 この研究により、少なくとも10ngのDNAを含むサンプルからのexomeシークエンシングが可能になります。臨床的な文脈において、この限界は、不十分な材料のために大部分の細針吸引試料を除外するが、適切な中核生検および切除生検試料を含む。これにより、可能なサンプルのより大きなセットからのデ?...

<html>次世代シークエンシングの結果としての癌ゲノミクスの進歩は、治療標的の同定および多くの血液学的および非血液学的新生物の予後診断において顕著なブレークスルーをもたらした。特定のゲノム改変に基づく新たな個別治療戦略は、多くの腫瘍型で急速に導入されている（参考文献1,2参照）。リンパ腫ゲノミクスの著しい進歩にもかかわらず、古典的ホジキンリンパ腫（CHL）における腫瘍性HRS細胞のゲノムは、過小発現していた。この研究は、反応性微小環境内の腫瘍性HRS細胞の不足により妨げられており、精製HRS細胞集団を単離することは困難である3 。 原発性腫瘍から生存可能なHRS細胞を単離するための方法は、Fromm et al。 図4に示すように 、この方法は、CD30、CD15、CD40、CD95、CD45 CD20、CD5およびCD64からなる8抗体カクテルを使用して、CHL腫瘍懸濁液からHRS細胞を明白に同定する。少なくとも10 7個の細胞（約10mgの組織）からなる腫瘍生検材料からの新鮮または凍結細胞懸濁液から少なくとも1,000個の生存可能なHRS細胞を単離することができる（フローサイトメトリー分析により90％以上であり、 10個の連続した症例のexomeゲノム分析によって少なくとも80％。 私たちは、フローサイトメトリーによる細胞単離技術を改良し、このプロセスを大幅に簡素化し、原発性CHL腫瘍から数千の生存可能なHRS細胞を迅速に単離することを可能にしました7 。本発明者らは、ホジキンリンパ腫の原発例における腫瘍細胞の最初の完全なエキソーム配列であると考えられるものを産生するためにこの技術を利用した。私たちの研究は、個々のCHL症例のゲノムワイドな高スループット研究の可能性を示しており、すでにCHL発症の側面を説明する可能性のある新規なゲノム改変の同定につながっている。 我々はさらに、ハイスループットゲノム研究のために抽出されたDNAを利用するためのパイプラインを開発した。 HRS細胞数が1,000個以下のHRS細胞からの信頼性の高い結果を得るために、アダプターライゲーション効率を高め、DNA断片ライブラリーを作製するための改変された次世代DNAライブラリー作製手順8を開発しました過度の増幅なしに。この方法は、ルーチンの臨床サンプルの分析と、再発性の突然変異および染色体の変化の検出を可能にする。

<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

古典的ホジキンリンパ腫のホジキンリード - スターンバーグ細胞は、炎症性リンパ球のバックグラウンド内にまばらに分布しており、典型的には腫瘍質量の1％未満を構成する。バルク腫瘍に由来する物質は、特徴付けに不十分な濃度で腫瘍含量を含む。したがって、8個の抗体を用いた蛍光活性化細胞選別、ならびに側方および前方散乱は、後の研究のために腫瘍から高純度のHRS細胞を迅速に分離および濃縮する方法としてここに記載されている。同時に、exomeシークエンシングの標準プロトコールでは、通常、フローソーティングでも高すぎることが多い100〜1,000 ngの入力DNAが必要であるため、高品質のライブラリー構築プロトコールを最適化して提供しますわずか10 ngの入力DNAからのデータ。この組み合わせは、全eのハイブリダイゼーション捕捉に適した次世代ライブラリーを作製することができるxome baitsまたはより集中したターゲットパネルを必要に応じて選択します。 HRS細胞のある種の配列決定は、健常な腫瘍内のT細胞またはB細胞と比較した場合、突然変異、挿入および欠失、およびコピー数の変化を含む体細胞変化を同定することができる。これらの知見は、HRS細胞の分子生物学を解明し、標的薬物治療の道筋を明らかにする可能性がある。

バイオアナライザープロットは、ライブラリー増幅および0.8xビーズクリーンアップの後に行う必要があります。所望の範囲内のフラグメントサイズの「通常のような」分布を見るはずです（ 図2a ）。曲線の目に見える「肩」のようなこの形状からの逸脱は、高分子量または低分子量の人工物の存在を示す。例えば、 図2b〜2d</stro...

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

ここでは、古典的なホジキンリンパ腫（HL）細胞から高品質、全exomeデータを生成するように設計された、フローサイトメトリーによる細胞ソーティングと低入力、次世代ライブラリー構築プロトコルを説明します。

古典的なホジキンリンパ腫のリードステルベルグ細胞のフローソーティングとExome配列決定

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

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

Research

JoVE Journal

Genetics

9.9K ビュー.  Memorial Sloan Kettering Cancer Center. ここでは、古典的なホジキンリンパ腫（HL）細胞から高品質、全exomeデータを生成するように設計された、フローサイトメトリーによる細胞ソーティングと低入力、次世代ライブラリー構築プロトコルを説明します。 

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

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.

単一細胞のシーケンシングを使用したコピー数変化の検出

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

遺伝学

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.

のトランスクリプトーム解析<em&gt; C</em&gt;。<em&gt;エレガンス</emギャラクシープロジェクトのタキシードスイートを通じて&gt; RNAシーケンスデータ

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.

G2-seq: 高スループット シーケンス ベースを識別する方法後半ゲノムの領域を複製します。

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.

堅牢な DNA の隔離および標本の高スループット シーケンス ライブラリーの構築

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.

次世代シーケンシングのフルレングスの HIV-1 Proviruses 近くの増幅

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.

円の染色体構造の次世代シーケンシングによる遺伝子制御配列の高スループット識別キャプチャ (4 C seq)

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.

分離、シーケンスおよびヒト間葉系幹細胞からの細胞のマイクロ Rna を分析

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, ...

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.

無呼吸性遺伝子検査用半導体シーケンシング

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.

ナノポアシーケンシングを用いた全血からの mRNA の配列決定

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

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to normal and pathological conditions. The goal of this protocol is to generate high-quality, large-scale transcriptome data of each endocrine cell type with the use of a droplet-based microfluidic single-cell RNA sequencing technology. Such data can be utilized to build the gene expression profile of each endocrine cell type in normal or specific conditions. The process requires careful handling, accurate measurement, and rigorous quality control. In this protocol, we describe detailed steps for human pancreatic islets dissociation, sequencing, and data analysis. The representative results of about 20,000 human single islet cells demonstrate the successful application of the protocol.

Here, we present a protocol to generate high-quality, large-scale transcriptome data of single cells from isolated human pancreatic islets using a droplet-based microfluidic single-cell RNA sequencing technology.

ヒト膵島の単一細胞RNAシーケンシングと解析

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to ...

古典的なホジキンリンパ腫のリードステルベルグ細胞のフローソーティングとExome配列決定

要約

さらに動画を探す

PLAYLIST