这项研究得到了全国儿童医院阿比盖尔·韦克斯纳研究所的高性能计算设施的支持。这项工作得到了美国国立卫生研究院国家癌症研究所[U54 CA231641至SLL，R01 CA183776至SLL]的支持;亚历克斯的柠檬水摊位基金会[ERT青年研究员奖];佩洛托尼亚[ERT奖学金];和国家卫生与医学研究委员会CJ Martin海外生物医学奖学金[APP1111032至KIP]。

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<li>Tomazou, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Epigenome+Mapping+Reveals+Distinct+Modes+of+Gene+Regulation+and+Widespread+Enhancer+Reprogramming+by+the+Oncogenic+Fusion+Protein+EWS-FLI1%5BTitle%5D)+AND+%22Cell+Reports%22%5BJournal%5D)">Epigenome Mapping Reveals Distinct Modes of Gene Regulation and Widespread Enhancer Reprogramming by the Oncogenic Fusion Protein EWS-FLI1.</a> Cell Reports. 10, 1082-1095 (2015).</li>
<li>Sankar, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mechanism+and+relevance+of+EWS%2FFLI-mediated+transcriptional+repression+in+Ewing+sarcoma%5BTitle%5D)+AND+%22Oncogene%22%5BJournal%5D)">Mechanism and relevance of EWS/FLI-mediated transcriptional repression in Ewing sarcoma.</a> Oncogene. 32, 5089-5100 (2013).</li>
<li>Gangwal, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microsatellites+as+EWS%2FFLI+response+elements+in+Ewing%27s+sarcoma%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences+U.S.A%22%5BJournal%5D)">Microsatellites as EWS/FLI response elements in Ewing's sarcoma.</a> Proceedings of the National Academy of Sciences U.S.A. 105, 10149-10154 (2008).</li>
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</ol>

SLL作为Salarius Pharmaceuticals的顾问委员会成员和股东宣布存在利益冲突。SLL也是美国专利号的上市发明人。US 7，393，253 B2，"用于诊断和治疗尤文氏肉瘤的方法和组合物"和US 8，557，532，"耐药尤文氏肉瘤的诊断和治疗"。这不会改变我们对JoVE共享数据和材料的政策的遵守。

研究致癌转录因子的生化机制对于了解它们引起的疾病和设计新的治疗策略至关重要。在以染色体易位为特征的恶性肿瘤中尤其如此，导致融合转录因子。这些嵌合蛋白中包含的结构域可能与野生型蛋白质中存在的调节结构域缺乏有意义的相互作用，使在融合的背景下解释结构 - 功能信息的能力复杂化26，27，28。此外，许多这些致癌融合的特征是低复杂性的内在无序结构域10，13，29，30。
EWS结构域是这种本质无序结构域的一个例子，该域涉及各种致癌融合10。固有的无序性和重复性阻碍了理解EWS结构域所采用的分子机制的努力。先前研究结构 - 功能的努力在很大程度上诉诸于在报告基因测定的背景下或在细胞背景中使用不同的突变体，这些突变体无法概括相关的细胞背景，或者缺乏任何产生有意义的部分功能的结构变异11，17，25。此处介绍的方法解决了这些问题。在疾病相关细胞环境中进行结构-功能映射，下一代测序使转录组学谱分析能够在天然染色质的设置下评估转录因子功能。在EWS / FLI的DAF突变体的特定情况下，据报道DAF在使用分离的反应元件的报告基因测定中几乎没有活性，但在完整基因启动子的背景下显示活性，无论是在报告测定中还是在天然染色质中，都表明一个有趣的表型23。使用这里描述的方法更直接地解决了基因组中哪种类型的调节元件在疾病环境中反应最灵敏的问题。通过同时在其天然染色质环境中测试所有候选靶基因，转录组学方法更有可能识别具有部分功能的构建体。
使用与疾病相关的细胞背景的固有强度可能是这种技术的最大局限性。最重要的因素之一是为这些实验选择合适的细胞系统。许多来自具有特征性转录因子的恶性肿瘤的细胞系不容易耐受该转录因子的敲低，并且在许多情况下，特别是对于儿科癌症，真正的起源细胞仍然存在争议，并且癌基因在其他细胞背景中的表达是令人望而却步的毒性31，32 .在这些情况下，在不同的细胞背景中进行实验可能会有所帮助，只要研究人员在解释结果时要谨慎，并在更与疾病相关的细胞类型中适当地验证任何相关发现。
至关重要的是要仔细验证癌基因表达的稳定性和表型后果，并且只提交符合严格标准的测序样品。在这里，这包括用于确认敲低和挽救的蛋白质印迹，以及用于验证阳性对照的少量已知靶基因的qRT-PCR（图2）。同样重要的是，通过在每个批次中尽可能相似地仔细地进行细胞和RNA制备，尽可能减少批次变异性。
这里描述的方法在与其他类型的基因组数据配对时变得特别强大，这些数据与所研究的转录因子的全基因组功能有关。这种类型的结构功能分析的未来方向将扩展到包括ChIP-seq和ATAC-seq，以确定转录因子的结合以及染色质可及性的任何诱导变化。作为一套，这种类型的数据可以指出致癌转录因子的不同结构成分对功能的不同方面的贡献（即DNA结合与染色质修饰与共同调节剂招募）。总体而言，使用基于NGS的方法绘制融合转录因子的结构 - 功能关系可以揭示这些蛋白质致癌功能的生化决定因素的新见解。这对于进一步了解它们引起的疾病以及开发新的治疗策略非常重要。

癌症的一个子集，包括许多儿童和青春期的恶性肿瘤，其特征在于染色体易位，产生新的融合癌基因1，2，3，4，5，6。由此产生的融合蛋白经常作为致癌转录因子起作用，协调转录调控的广泛变化以促进肿瘤发生7，8。具有这些易位的癌症通常具有安静的突变景观，除了特征性融合之外，很少有反复出现的基因组畸变4，9。因此，直接靶向融合蛋白是这些疾病中一种有吸引力的治疗策略。然而，这些致癌转录因子通常由低复杂性，内在无序，转录激活结构域与DNA结合结构域（DBD）融合10，11，12，13，14组成。这些蛋白质的内在无序结构域（IDD）和DBD都已被证明很难用传统的药理学方法靶向。因此，开发新的治疗方法需要更详细的分子理解这些融合所采用的机制，以异常地调节基因表达。
EWSR1的N端IDD部分通常融合到癌症中的DBD，包括尤文氏肉瘤中的EWS / FLI，弥漫性小圆细胞肿瘤中的EWS / WT1以及软部分10的透明细胞肉瘤中的EWS /ATF1。EWS IDD在每次聚变中的机制作用尚不清楚。EWS/ETS系列融合，特别是EWS/FLI，是迄今为止功能最突出的融合。EWS/ FLI协调全基因组表观遗传和转录变化，导致数千个基因的激活和抑制7，11，15，16。研究表明，IDD对于转录共激活子（如p300，WDR5和BAF复合物）以及共抑制子（如NuRD复合物）的招募很重要11，15，17。EWS IDD与FLI1的C端部分的融合赋予了FLI1的ETS DBD新的DNA结合特异性，使得融合癌蛋白（EWS / FLI）结合到基因组的重复GGAA-微卫星区域除了共识ETS基序18，19，20之外。结合共激活子募集功能，EWS/FLI的这种紧急DNA结合活性促进GGAA-微卫星远端到转录起始位点（TSS）（"增强子样"微卫星）的从头增强子形成，并招募RNA聚合酶II以促进在TSS（"启动子样"微卫星）近端的GGAA-微卫星（"启动子样"微卫星）的转录11，15，16，21。
综上所述，这些数据使我们假设EWS域内的离散元素有助于为不同类型的EWS / FLI结合位点招募不同的共同调节因子。然而，在EWS / FLI的EWS部分内辨别这些元素以及它们如何运作，受到该领域高度重复和无序性质的阻碍。在这里，我们利用先前在尤文氏肉瘤细胞中发表的敲低-拯救系统来功能性地绘制EWS IDD中的这些元素。在这个系统中，EWS / FLI使用靶向FLI1基因的3'UTR的shRNA耗尽，并且使用缺乏3'UTR7，17，22的不同EWS / FLI突变cDNA构建体来挽救表达。这些实验集中在具有各种缺失的构建体上，以绘制EWS IDD与重要致癌表型之间的结构 - 功能关系，包括GGAA-微卫星报告基因构建体的激活，集落形成测定以及EWS / FLI激活和抑制基因的靶向验证7，17，22.然而，这些研究未能在EWS / FLI的EWS IDD中发现离散子结构域，这些子结构域对于激活或抑制都非常重要。所有测试的构建体要么能够激活和抑制特定的靶基因，导致有效的菌落形成，要么无法调节任何EWS / FLI靶基因，导致菌落形成7，17，22的丧失。
通过广泛采用下一代测序实现的转录组学分析通常用于比较两种情况下的基因表达特征，通常在筛选或描述性研究的背景下。相反，我们希望利用使用RNA测序（RNA-seq）捕获全基因组表达数据的能力来表征IDD对转录因子功能的贡献。在这种情况下，RNA-seq与敲低-救援系统配对，以探索EWS结构域的结构-功能关系。这种方法适用于其他融合转录因子，包括其他EWS融合或功能知之甚少的野生型转录因子，并且与用于功能图谱研究的其他测定（例如报告测定或靶向qRT-PCR）相比具有多种优势。这些包括在相关染色质环境中测试功能的结构决定因素，在一次测定中测试多种类型的响应元件的能力（即，活化和抑制，GGAA-微卫星和非微卫星等），以及由此产生的更好地检测部分功能的能力。
这种方法的成功实施取决于基于细胞的系统，该系统捕获感兴趣的表型（在这种情况下，A673细胞具有shRNA介导的EWS / FLI耗尽），以及适合基于细胞的系统的表达载体中的一组突变体构建体（在这种情况下，pMSCV-hygro具有各种3x-FLAG标记的EWS / FLI突变体将通过逆转录病毒转导递送）。建议对基于CRISPR的耗竭构建体、基于shRNA的耗竭构建体和cDNA表达构建体进行病毒转导，并进行适当的选择以产生稳定的细胞系，而不是瞬时转染。当转录组学数据可以与转录因子定位相关的其他数据和其他表型读数（如果可用）配对时，结果的下游解释得到加强。
在本文中，我们应用这种方法来表征EWS / FLI14的DAF突变体的活性。DAF突变体在EWS / FLI 14的EWS IDD的重复区域中有17个酪氨酸至丙氨酸突变。这种特殊的EWS突变体以前曾被报道过，当与ATF1 DBD14融合时，它无法激活报告基因表达。然而，初步的qRT-PCR数据表明，该突变体能够激活EWS / FLI靶标 NR0B123的转录。这里描述的转录组学方法能够成功检测DAF突变体的部分功能。通过将这些转录组学数据与有关EWS / FLI结合和识别基序的信息配对，我们进一步表明DAF突变体在GGAA-微卫星重复时保持功能。这些结果将DAF确定为第一个部分功能的EWS / FLI突变体，并突出了非微卫星基因的功能对肿瘤发生很重要（如报道23）。这证明了这种转录组学结构 - 功能映射方法的强大功能，可以深入了解致癌转录因子的功能。

<table><tbody><tr><td>&lt;strong&gt;Wet Lab Reagents&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>anti-FLI rabbit pAb</td><td>Abcam</td><td>ab15289</td><td>1:500</td></tr><tr><td>anti-lamin B1 rabbit pAb</td><td>Abcam</td><td>ab16048</td><td>1:2000</td></tr><tr><td>Cell-based system for introduction of mutant constructs</td><td></td><td></td><td>Determined by cell system used</td></tr><tr><td>Cryotubes</td><td></td><td></td><td>For viral aliquots</td></tr><tr><td>DMEM</td><td>Corning Cellgro</td><td>10-013-CV</td><td>For viral production</td></tr><tr><td>Fetal bovine serum</td><td>Gibco</td><td>16000-044</td><td>For viral production</td></tr><tr><td>G418</td><td>ThermoFisher</td><td>10131027</td><td>For viral production</td></tr><tr><td>HEK293-EBNAs</td><td>ATCC</td><td>CRL-10852</td><td>For viral production</td></tr><tr><td>HEPES</td><td>Gibco</td><td>15630106</td><td></td></tr><tr><td>Hygromycin B</td><td>ThermoFisher</td><td>10687010</td><td></td></tr><tr><td>M2 anti-FLAG mouse mAb</td><td>Sigma</td><td>F3165</td><td>1:2000</td></tr><tr><td>Near IR-secondary antibodies</td><td>Li-Cor</td><td></td><td></td></tr><tr><td>Optimem</td><td>Gibco</td><td>31985062</td><td>For viral production</td></tr><tr><td>Penicillin/Streptomycin/Glutamine</td><td>Gibco</td><td>10378-016</td><td>For viral production</td></tr><tr><td>Polybrene</td><td>Sigma</td><td>TR-1003-G</td><td>For viral transduction</td></tr><tr><td>Puromycin</td><td>Sigma</td><td>P8833</td><td>Stored at 2 mg/mL stock</td></tr><tr><td>RNeasy Plus kit</td><td>Qiagen</td><td>74136</td><td>Has gDNA removal columns</td></tr><tr><td>Selection reagents</td><td></td><td></td><td>As dictated by cell system used</td></tr><tr><td>Sodium Pyruvate</td><td>Gibco</td><td>11360-070</td><td>For viral production</td></tr><tr><td>Tissue culture media</td><td></td><td></td><td>Determined by cell system used</td></tr><tr><td>TransIT-LT1</td><td>Mirus</td><td>MIR 2304</td><td>For viral production</td></tr><tr><td></td><td></td><td></td><td></td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Access to HPC environment</td><td></td><td></td><td></td></tr><tr><td>AnnotationDbi</td><td></td><td></td><td>1.38.2</td></tr><tr><td>Cairo</td><td></td><td></td><td>1.5-10</td></tr><tr><td>DESeq2</td><td></td><td></td><td>1.16.1</td></tr><tr><td>genefilter</td><td></td><td></td><td>1.58.1</td></tr><tr><td>ggbiplot</td><td></td><td></td><td>0.55</td></tr><tr><td>ggplot2</td><td></td><td></td><td>3.1.1</td></tr><tr><td>org.Hs.eg.db</td><td></td><td></td><td>3.4.1</td></tr><tr><td>pheatmap</td><td></td><td></td><td>1.0.12</td></tr><tr><td>PuTTY</td><td></td><td></td><td></td></tr><tr><td>R</td><td></td><td></td><td>3.4.0</td></tr><tr><td>RColorBrewer</td><td></td><td></td><td>1.1-2</td></tr><tr><td>reshape2</td><td></td><td></td><td>1.4.3</td></tr><tr><td>rgl</td><td></td><td></td><td>0.100.19</td></tr><tr><td>R-studio</td><td></td><td></td><td></td></tr><tr><td>STAR</td><td></td><td></td><td>Version 2.6 or later</td></tr><tr><td>sva</td><td></td><td></td><td>3.24.4</td></tr><tr><td>TrimGalore!</td><td></td><td></td><td></td></tr><tr><td>WinSCP</td><td></td><td></td><td></td></tr></tbody></table>

mapping the structure-function relationships of disordered oncogenic transcription factors using transcriptomic analysis

许多癌症的特征在于染色体易位，导致致癌融合转录因子的表达。通常，这些蛋白质包含与另一种蛋白质的DNA结合结构域（DBD）融合的内在无序结构域（IDD），并协调广泛的转录变化以促进恶性肿瘤。这些融合通常是它们引起的癌症中唯一反复出现的基因组畸变，使它们成为有吸引力的治疗靶点。然而，靶向致癌转录因子需要更好地了解低复杂性IDD在其功能中所起的机制作用。EWSR1 的 N 端结构域是一种 IDD，涉及多种致癌融合转录因子，包括 EWS/FLI、EWS/ATF 和 EWS/WT1。在这里，我们使用RNA测序来研究EWS结构域的结构特征，这些结构域对Ewing肉瘤中EWS / FLI的转录功能很重要。首先进行shRNA介导的尤文氏肉瘤细胞内源性融合的消耗，该细胞与各种EWS突变体构建体的异位表达配对。然后使用RNA测序来分析表达这些构建体的细胞的转录组，以表征与EWS结构域突变相关的功能缺陷。通过将转录组学分析与先前发表的有关EWS / FLI DNA结合基序和基因组定位的信息以及转化能力的功能测定相结合，我们能够确定对肿瘤发生重要的EWS / FLI的结构特征，并定义一组对尤文氏肉瘤至关重要的EWS / FLI靶基因。本文证明了使用RNA测序作为绘制致癌转录因子内在无序结构域的结构 - 功能关系的方法。

初步的qRT-PCR数据表明，一种名为DAF的EWS / FLI突变体在EWS的重复和无序区域具有特异性酪氨酸至丙氨酸突变，保持了激活EWS / FLI靶基因的能力，但未能抑制关键靶基因23。为了更好地理解EWS域中的这些残基与EWS/FLI功能之间的关系，使用了上述描述并在 图1 中概述的协议。A673尤文氏肉瘤细胞被病毒转导，用shRNA靶向 FLI1的3'UTR，导致内源性EWS/FLI的消耗。经过4天的选择，用不同3XFLAG标记的EWS/FLI突变体的病毒转导挽救了EWS/FLI功能，以空载体为对照，无需救援。一种缺乏EWS结构域的非功能突变体（称为Δ22）被用作阴性对照，野生型EWS/ FLI（称为wtEF）被用作阳性对照（图2A）。DAF 被用作测试构造，但如果需要，可以使用多个测试构造。选择细胞另外10天以使构建表达稳定，然后收集RNA（使用gDNA去除步骤），蛋白质和菌落形成测定。收集了四个重复项，并显示有效敲低和挽救的具有代表性的qRT-PCR和蛋白质印迹如图 2B-D所示。应该注意的是，DAF拯救的细胞未能形成 如图2E所示的集落，表明致癌转化受损。
在完成重复验证和表型测定后，RNA被提交给全国儿童医院的基因组医学研究所进行文库制备和下一代测序，并收集了约5000万个150-bp配对端读数。数据以 fastq.gz 文件的形式返回。使用TrimGalore从这些文件中删除低质量的读数，STAR用于将读数与人类基因组hg19对齐并计算每个基因的读数。hg19 用于与下游分析中使用的 EWS/FLI 的其他精选数据集兼容。这些读取计数被合并到所有样本的单个计数矩阵中，其中前6行如图 3所示。
计数最初通过DESeq2运行，没有批量归一化，但是，对样品到样品距离的目视检查显示了潜在的混杂批效应，如图4A中的红色箭头突出显示所示。这可能是由于培养物中细胞的通过和每批处理的差异而引入的生物变异性引起的。批处理效果的归一化是使用 ComBat 执行的，通常建议使用。批量归一化数据的样品到样品距离如图4B所示。在批量归一化之后，DESeq2用于生成相对于基线的三个结构（wtEF，Δ22和DAF）的转录谱。请注意，虽然"亲本"A673细胞（模拟敲低和模拟救援，此处称为"iLuc"）包括在差异分析中，但本实验的参考是EWS / FLI耗尽的细胞，称为iEF细胞。通过将iLuc样品与iEF进行比较，可以生成内源性蛋白质的转录谱，这可能对了解救援系统的工作原理感兴趣，但这不是此特定分析的目标。为突变体生成的转录谱包括iEF的正（wtEF）和阴性（Δ22）对照，因此这些应作为其他突变体的基准。这很重要，因为本例中的阳性对照没有完全概括内源性EWS / FLI的功能，如其他地方7，23所讨论的那样。
图5中的主成分分析（PCA）表明，DAF的转录谱介于wtEF和Δ22之间，证实了部分功能。此外，样本中1000个最可变基因的分层聚类表明，DAF未能抑制EWS / FLI靶基因，仅部分保留了基因激活活性，如图6A和图S5所示。ToppGene分析表明，DAF激活的基因类别在功能上与DAF无功能的EWS / FLI激活靶标不同（图6B）。有趣的是，wtEF拯救的激活基因的功能，但不是DAF，似乎与转录控制和染色质调节有关。根据集落形成测定的结果，应进一步分析来自该核心基因特征的基因在EWS / FLI介导的肿瘤发生中的作用。EWS / FLI介导的基因抑制的重要性之前已经描述过17。
众所周知，EWS/FLI对GGAA-微卫星重复元素19、22具有独特的结合亲和力，并且这些元素的结合驱动下游基因调控11、15、18、20、22。这些微卫星的特征在于与激活或抑制有关，并且要么靠近（<5 kb）TSS，要么远端到（>5 kb）TSS25。此外，还有一些EWS / FLI调控的基因具有高亲和力（HA）ETS基序，与TSS23近端。为了进一步分析DAF功能的特征以及DAF能够挽救哪些类型的EWS/FLI激活基因，分析了与这些不同类别相关的基因的差异表达。有趣的是，DAF最能够拯救GGAA-微卫星激活基因，但无法拯救HA位点附近的激活基因，如图7所示。从分层聚类中可以看出，DAF 无法拯救跨主题类的 EWS/FLI 介导的压制。这些数据表明，DAF保留了EWS的足够结构特征，可以与GGAA微卫星结合并从TSS的近端和远端激活。这可能是由于完整的SYGQ域被认为对GGAA重复的EWS / FLI活动很重要。这些数据还表明，DAF中突变的特定酪氨酸在HA位点的EWS / FLI介导的基因调控以及基因抑制中起着重要作用，但知之甚少，这突出了进一步研究的一个重要领域。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61564/61564fig01.jpg"> 图 1:工作流。描述通过转录组学执行结构-功能映射的分步过程。细胞首先准备表达结构 - 功能映射所需的结构套件。表达后，收获细胞的RNA和蛋白质，并测定相关表型。验证了结构的表达，并重复该过程3-4次以收集独立的生物学重复。然后将RNA提交用于下一代测序（NGS）。收到数据后，对数据进行质量修整、对齐，并计算每个成绩单的计数。使用DESeq2控制批处理效应，并确定转录组学特征和差异表达。可以合并分层聚类和下游分析，集成其他组学数据集和不同的路径或功能分析。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig01large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61564/61564fig02.jpg"> 图2:构建体表达和相关测定的验证。（A） 示意图，描述了本例中测试的结构。（B） 免疫印迹对内源性 EWS/FLI 的敲低和 3X-FLAG 标记构建体表达的验证。（C，D）通过qRT-PCR验证EWS/FLI（C）活化靶基因NR0B1和（D）抑制靶基因TGFBR2的构建活性。数据以平均 +/- 标准差表示。P值是用Tukey诚实显著性检验计算的。* p < 0.05， ** p < 0.01， *** p < 0.005 （E） 用于评估构建体转化活性的软琼脂测定的菌落计数。P值是用Tukey诚实显著性检验计算的。* p < 0.05， ** p < 0.01， *** p < 0.005.此图改编自 Theisen 等人23<a href="https://www.jove.com/files/ftp_upload/61564/61564fig02large.jpg" target="_blank">请单击此处查看此图的放大版本。</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61564/61564fig03.jpg"> 图 3:用于分析的最终整理计数数据。计数文件前6行的屏幕截图，其中包含要进行批量归一化和分析的所有样本的基因计数。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig03large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61564/61564fig04v3.jpg"> 图 4:样本到样本距离热图。（A） 样本到样本距离图，显示原始计数数据的样本聚类。按批次和按样品聚类的样品用红色箭头表示。（B） 使用 ComBat 进行批量归一化后的样品到样品距离图。此处，来自所有仿行的样本独立于批处理聚集在一起。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig04large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61564/61564fig05.jpg"> 图 5:差异表达分析的结果。（A） 为所有样品生成的转录组学特征的主体成分分析（PCA）图显示了强烈的样品内聚类，并表明DAF在阳性（wtEF）和阴性（Δ22）对照之间是中间的。（B） 火山图显示与每个构造中基因的 log2FoldChange 对图的 -log（p-值）。调整后 p 值< 0.05 且|log2（FoldChange）|> 1 被视为显著的，并以红色显示。面板5B改编自Theisen等人，请<a href="https://www.jove.com/files/ftp_upload/61564/61564fig05large.jpg" target="_blank">点击此处查看此图的放大版本。</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/61564/61564fig06.jpg"> 图6:用于识别基因类别的分层聚类。（A） 所有构建体中前 1000 个最可变基因的分层聚类和基线 iEF 显示 DAF 部分挽救了 EWS/FLI 介导的基因激活。（B） 来自ToppGene的基因本体（分子功能）结果显示了被DAF拯救或未获救的EWS/ FLI激活基因的功能富集。图6B改编自Theisen等人，请<a href="https://www.jove.com/files/ftp_upload/61564/61564fig06large.jpg" target="_blank">点击此处查看此图的放大版本。</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/61564/61564fig07.jpg"> 图7:对不同结构的不同转录因子响应元素的详细分析:（A）示意图，通过将其他可用数据集与此处的转录组学配置文件相结合，描述了用于生成面板（B）和（C）的数据处理。（B，C）汇编显示了对不同类别的直接EWS/FLI-（B）激活和（C）抑制目标的救援。纳入的基因仅是内源性EWS/FLI可检测差异表达的基因。在每个饼图中，灰色描绘了未被构建体拯救的基因部分。红色表示被差异激活的基因部分，蓝色表示被差异抑制的基因部分。此图改编自 Theisen 等人23<a href="https://www.jove.com/files/ftp_upload/61564/61564fig07large.jpg" target="_blank">请单击此处查看此图的放大版本。</a>
图 S1:将 fastq.gz 文件加载到 HPC 环境中，进行修整和对齐。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig01.jpg" target="_blank">请点击此处下载此图。</a>
图 S2:整理样本中的读取计数并使用 ComBat 运行批处理规范化。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig02.jpg" target="_blank">请点击此处下载此图。</a>
图 S3:运行 DESeq2 并提取差异表达分析的结果。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig03.jpg" target="_blank">请点击此处下载此图。</a>
图 S4:分析输出。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig04.jpg" target="_blank">请点击此处下载此图。</a>
图S5:用于识别基因类别的分层聚类: 所有构建体中前1000个最可变基因的分层聚类，基线iEF分类为 k 个聚类。在本例中 k=7，但此参数由用户设置，如图 S4D所示。 <a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig05.jpg" target="_blank">请点击此处下载此图。</a>
表S1:具有簇注释的基因列表（Ensembl基因ID）。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/Table_S1.xlsx" target="_blank">请点击此处下载此表格。</a>

Watch this Scientific Journal Video about Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis at JoVE.com

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

内在无序结构域对致癌融合转录因子功能很重要。为了治疗靶向这些蛋白质，需要更详细地了解这些结构域所采用的调节机制。在这里，我们使用转录组学来绘制尤文氏肉瘤中内在无序的EWS结构域的重要结构特征。

使用转录组学分析绘制无序致癌转录因子的结构-功能关系

Many cancers are characterized by chromosomal translocations which result in the expression of oncogenic fusion transcription factors. Typically, these ...

mapping-structure-function-relationships-disordered-oncogenic

Research

JoVE Journal

Cancer Research

2.7K 次观看.  Abigail Wexner Research Institute at Nationwide Children's Hospital. 内在无序结构域对致癌融合转录因子功能很重要。为了治疗靶向这些蛋白质，需要更详细地了解这些结构域所采用的调节机制。在这里，我们使用转录组学来绘制尤文氏肉瘤中内在无序的EWS结构域的重要结构特征。

视频: Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

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.

转录因子结合、转录、翻译和营业额的实时分析在细胞激活过程中显示全球事件

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

科研

遗传学

CRISPR-Mediated Reorganization of Chromatin Loop Structure

Recent studies have clearly shown that long-range, three-dimensional chromatin looping interactions play a significant role in the regulation of gene expression, but whether looping is responsible for or a result of alterations in gene expression is still unknown. Until recently, how chromatin looping affects the regulation of gene activity and cellular function has been relatively ambiguous, and limitations in existing methods to manipulate these structures prevented in-depth exploration of these interactions. To resolve this uncertainty, we engineered a method for selective and reversible chromatin loop re-organization using CRISPR-dCas9 (CLOuD9). The dynamism of the CLOuD9 system has been demonstrated by successful localization of CLOuD9 constructs to target genomic loci to modulate local chromatin conformation. Importantly, the ability to reverse the induced contact and restore the endogenous chromatin conformation has also been confirmed. Modulation of gene expression with this method establishes the capacity to regulate cellular gene expression and underscores the great potential for applications of this technology in creating stable de novo chromatin loops that markedly affect gene expression in the contexts of cancer and development.

Chromatin looping plays a significant role in gene regulation; however, there have been no technological advances that allow for selective and reversible modification of chromatin loops. Here we describe a powerful system for chromatin loop re-organization using CRISPR-dCas9 (CLOuD9), demonstrated to selectively and reversibly modulate gene expression at targeted loci.

CRISPR 的染色质环结构重组

Recent studies have clearly shown that long-range, three-dimensional chromatin looping interactions play a significant role in the regulation of gene ...

Methods for Evaluating the Role of c-Fos and Dusp1 in Oncogene Dependence

The demonstration of tyrosine kinase inhibitors (TKIs) in treating chronic myeloid leukemia (CML) has heralded a new era in cancer therapeutics. However, a small population of cells does not respond to TKI treatment, resulting in minimal residual disease (MRD); even the most potent TKIs fail to eradicate these cells. These MRD cells serve as a reservoir to develop resistance to therapy. Why TKI treatment is ineffective against MRD cells is not known. Growth factor signaling is implicated in supporting the survival of MRD cells during TKI treatment, but a mechanistic understanding is lacking. Recent studies demonstrated that an elevated c-Fos and Dusp1 expression as a result of convergent oncogenic and growth factor signaling in MRD cells mediate TKI resistance. The genetic and chemical inhibition of c-Fos and Dusp1 renders CML exquisitely sensitive to TKIs and cures CML in both genetic and humanized mouse models. We identified these target genes using multiple microarrays from TKI-sensitive and -resistant cells. Here, we provide methods for target validation using in vitro and in vivo mouse models. These methods can easily be applied to any target for genetic validation and therapeutic development.

Here, we describe protocols for the genetic and chemical validation of c-Fos and Dusp1 as a drug target in leukemia using in vitro and in vivo genetic and humanized mouse models. This method can be applied to any target for genetic validation and therapeutic development.

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

The demonstration of tyrosine kinase inhibitors (TKIs) in treating chronic myeloid leukemia (CML) has heralded a new era in cancer therapeutics. However, ...

癌症研究

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential expression of groups of genes in tumor RNA-seq in a way that may be helpful for advancing precision oncology. However, CorEx produces many factors that can be challenging to analyze and connect to existing understanding. To facilitate such connections, we have built a website, CorExplorer, that allows users to interactively explore the data and answer common questions related to its analysis. We trained CorEx on RNA-seq gene expression data for four tumor types: ovarian, lung, melanoma, and colorectal. We then incorporated corresponding survival, protein-protein interactions, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments, and heatmaps into the website for association with the factor graph visualization. Here we employ example protocols to illustrate use of the database for comprehending the significance of the learned tumor factors in the context of this external data.

We introduce the CorExplorer web portal, an resource for exploration of tumor RNA sequencing factors found by the machine learning algorithm CorEx (Correlation Explanation), and show how factors can be analyzed relative to survival, database annotations, protein-protein interactions, and one another to gain insight into tumor biology and therapeutic interventions.

分析肿瘤基因表达因子与CorExplorer门户网站

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility ...

Identification of Transcription Factor Regulators using Medium-Throughput Screening of Arrayed Libraries and a Dual-Luciferase-Based Reporter

Transcription factors can alter the expression of numerous target genes that influence a variety of downstream processes making them good targets for anti-cancer therapies. However, directly targeting transcription factors is often difficult and can cause adverse side effects if the transcription factor is necessary in one or more adult tissues. Identifying upstream regulators that aberrantly activate transcription factors in cancer cells offers a more feasible alternative, particularly if these proteins are easy to drug. Here, we describe a protocol that can be used to combine arrayed medium-scale lentiviral libraries and a dual-luciferase-based transcriptional reporter assay to identify novel regulators of transcription factors in cancer cells. Our approach offers a quick, easy, and inexpensive way to test hundreds of genes in a single experiment. To demonstrate the use of this approach, we performed a screen of an arrayed lentiviral RNAi library containing several regulators of Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), two transcriptional co-activators that are the downstream effectors of the Hippo pathway. However, this approach could be modified to screen for regulators of virtually any transcription factor or co-factor and could also be used to screen CRISPR/CAS9, cDNA, or ORF libraries.

To identify novel regulators of transcription factors, we developed an approach to screen arrayed lentiviral or retroviral RNAi libraries using a dual-luciferase-based transcriptional reporter assay. This approach offers a quick and relatively inexpensive way to screen hundreds of candidates in a single experiment.

使用阵列库的中等通量筛选和基于双 Luciferase 的分录报告器识别转录因子稳压器

Transcription factors can alter the expression of numerous target genes that influence a variety of downstream processes making them good targets for ...

Defining Gene Functions in Tumorigenesis by Ex vivo Ablation of Floxed Alleles in Malignant Peripheral Nerve Sheath Tumor Cells

The development of new drugs that precisely target key proteins in human cancers is fundamentally altering cancer therapeutics. However, before these drugs can be used, their target proteins must be validated as therapeutic targets in specific cancer types. This validation is often performed by knocking out the gene encoding the candidate therapeutic target in a genetically engineered mouse (GEM) model of cancer and determining what effect this has on tumor growth. Unfortunately, technical issues such as embryonic lethality in conventional knockouts and mosaicism in conditional knockouts often limit this approach. To overcome these limitations, an approach to ablating a floxed embryonic lethal gene of interest in short-term cultures of malignant peripheral nerve sheath tumors (MPNSTs) generated in a GEM model was developed.
This paper describes how to establish a mouse model with the appropriate genotype, derive short-term tumor cultures from these animals, and then ablate the floxed embryonic lethal gene using an adenoviral vector that expresses Cre recombinase and enhanced green fluorescent protein (eGFP). Purification of cells transduced with adenovirus using fluorescence-activated cell sorting (FACS) and the quantification of the effects that gene ablation exerts on cellular proliferation, viability, the transcriptome, and orthotopic allograft growth is then detailed. These methodologies provide an effective and generalizable approach to identifying and validating therapeutic targets in vitro and in vivo. These approaches also provide a renewable source of low-passage tumor-derived cells with reduced in vitro growth artifacts. This allows the biological role of the targeted gene to be studied in diverse biologic processes such as migration, invasion, metastasis, and intercellular communication mediated by the secretome.

Defining Gene Functions in Tumorigenesis by Ex vivo Ablation of Floxed Alleles in Malignant Peripheral Nerve Sheath Tumor Cells

Here, we present a protocol for performing gene knockouts that are embryonic lethal in vivo in genetically engineered mouse model-derived tumors and then assessing the effect that the knockout has on tumor growth, proliferation, survival, migration, invasion, and the transcriptome in vitro and in vivo.

通过恶性周围神经鞘肿瘤细胞中絮状等位基因的 离体 消融来定义肿瘤发生的基因功能

The development of new drugs that precisely target key proteins in human cancers is fundamentally altering cancer therapeutics. However, before these ...

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

While the transcription regulation of protein coding genes was extensively studied, little is known on how transcription factors are involved in transcription of non-coding RNAs, specifically of microRNAs. Here, we propose a strategy to study the potential role of transcription factor in regulating transcription of microRNAs using publically available data, computational resources and high throughput data. We use the H3K4me3 epigenetic signature to identify microRNA promoters and chromatin immunoprecipitation (ChIP)-sequencing data from the ENCODE project to identify microRNA promoters that are enriched with transcription factor binding sites. By transfecting cells of interest with shRNA targeting a transcription factor of interest and subjecting the cells to microRNA array, we study the effect of this transcription factor on the microRNA transcriptome. As an illustrative example we use our study on the effect of STAT3 on the microRNA transcriptome of chronic lymphocytic leukemia (CLL) cells.

Herein we propose a strategy to study the effect of a transcription factor of interest on the microRNA transcriptome using publically available data, computational resources and high throughput data from microRNA arrays after transfecting cells with small hairpin (sh)RNA targeting a transcription factor of interest.

描述了微RNA转录的转录因子依赖调节

While the transcription regulation of protein coding genes was extensively studied, little is known on how transcription factors are involved in ...

生物工程

Single-Molecule Imaging of EWS-FLI1 Condensates Assembling on DNA

The fusion genes resulting from chromosomal translocation have been found in many solid tumors or leukemia. EWS-FLI1, which belongs to the FUS/EWS/TAF15 (FET) family of fusion oncoproteins, is one of the most frequently involved fusion genes in Ewing sarcoma. These FET family fusion proteins typically harbor a low-complexity domain (LCD) of FET protein at their N-terminus and a DNA-binding domain (DBD) at their C-terminus. EWS-FLI1 has been confirmed to form biomolecular condensates at its target binding loci due to LCD-LCD and LCD-DBD interactions, and these condensates can recruit RNA polymerase II to enhance gene transcription. However, how these condensates are assembled at their binding sites remains unclear. Recently, a single-molecule biophysics method-DNA Curtains-was applied to visualize these assembling processes of EWS-FLI1 condensates. Here, the detailed experimental protocol and data analysis approaches are discussed for the application of DNA Curtains in studying the biomolecular condensates assembling on target DNA.

Here, we describe the use of the single-molecule imaging method, DNA Curtains, to study the biophysical mechanism of EWS-FLI1 condensates assembling on DNA.

EWS-FLI1凝聚物在DNA上组装的单分子成像

The fusion genes resulting from chromosomal translocation have been found in many solid tumors or leukemia. EWS-FLI1, which belongs to the FUS/EWS/TAF15 ...

生物化学

Proximity Ligation Assay to Study Oncogene-Derived Transcription-Replication Conflicts

Both DNA replication and RNA transcription utilize genomic DNA as their template, necessitating spatial and temporal separation of these processes. Conflicts between the replication and transcription machinery, termed transcription-replication conflicts (TRCs), pose a considerable risk to genome stability, a critical factor in cancer development. While several factors regulating these collisions have been identified, pinpointing primary causes remains difficult due to limited tools for direct visualization and clear interpretation. In this study, we directly visualize TRCs using a proximity ligation assay (PLA), leveraging antibodies specific to PCNA and phosphorylated CTD of RNA polymerase II. This approach allows precise measurement of TRCs between replication and transcription processes mediated by RNA polymerase II. The method is further enhanced through DNA primers conjugated covalently to these antibodies, coupled with PCR amplification using fluorescent probes, providing a highly sensitive and specific means of detecting endogenous TRCs. Fluorescence microscopy enables the visualization of these conflicts, offering a powerful tool to study genome instability mechanisms associated with cancer. This technique addresses the gap in direct TRC visualization, allowing for a more comprehensive analysis and understanding of the underlying processes driving genome instability in cells.

Here, we present a sensitive and specific method to detect oncogene-induced transcription-replication conflicts (TRCs) using the proximity ligation assay (PLA). This approach leverages specific antibodies targeting PCNA and phospho-CTD RNAPII, enabling the assessment of TRC prevalence between RNA polymerase II transcription and DNA replication machinery.

用于研究癌基因衍生的转录-复制冲突的邻位连接测定

Both DNA replication and RNA transcription utilize genomic DNA as their template, necessitating spatial and temporal separation of these processes. ...

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFR&#945;+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

In mammalian cells, gene transcription is regulated in a cell type specific manner by the interactions of transcriptional factors with genomic DNA. Lineage-specific transcription factors are considered to play essential roles in cell specification and differentiation during development. ChIP coupled with high-throughput DNA sequencing (ChIP-seq) is widely used to analyze genome-wide binding sites of transcription factors (or its associated complex) to genomic DNA. However, a large number of cells are required for one standard ChIP reaction, which makes it difficult to study the limited number of isolated primary cells or rare cell populations. In order to understand the regulatory mechanism of oligodendrocyte lineage-specific transcription factor Olig2 in acutely purified mouse OPCs, a detailed method using ChIP-seq to identify the genome-wide binding sites of Olig2 (or Olig2 complex) is shown. First, the protocol explains how to purify the platelet-derived growth factor receptor alpha (PDGFR&#945;) positive OPCs from mouse brains. Next, Olig2 antibody mediated ChIP and library construction are performed. The last part describes the bioinformatic software and procedures used for Olig2 ChIP-seq analysis. In summary, this paper reports a method to analyze the genome-wide bindings of transcriptional factor Olig2 in acutely purified brain OPCs.

Here we present a protocol which is designed to analyze the genome-wide binding of the oligodendrocyte transcription factor 2 (Olig2) in acutely purified brain oligodendrocyte precursor cells (OPCs) by performing low-cell chromatin immunoprecipitation (ChIP), library preparation, high-throughput sequencing and bioinformatic data analysis.

低细胞染色质免疫沉淀测序分析 Olig2 基因组结合位点在急性纯化 PDGFRα + 细胞中的转录因子鉴定

In mammalian cells, gene transcription is regulated in a cell type specific manner by the interactions of transcriptional factors with genomic DNA. ...

使用转录组学分析绘制无序致癌转录因子的结构-功能关系

摘要

探索更多视频

转录因子结合、转录、翻译和营业额的实时分析在细胞激活过程中显示全球事件

CRISPR 的染色质环结构重组

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

分析肿瘤基因表达因子与CorExplorer门户网站

使用阵列库的中等通量筛选和基于双 Luciferase 的分录报告器识别转录因子稳压器

通过恶性周围神经鞘肿瘤细胞中絮状等位基因的离体消融来定义肿瘤发生的基因功能

描述了微RNA转录的转录因子依赖调节

EWS-FLI1凝聚物在DNA上组装的单分子成像

用于研究癌基因衍生的转录-复制冲突的邻位连接测定

低细胞染色质免疫沉淀测序分析 Olig2 基因组结合位点在急性纯化 PDGFRα + 细胞中的转录因子鉴定

使用转录组学分析绘制无序致癌转录因子的结构-功能关系

摘要

探索更多视频

转录因子结合、转录、翻译和营业额的实时分析在细胞激活过程中显示全球事件

CRISPR 的染色质环结构重组

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

分析肿瘤基因表达因子与CorExplorer门户网站

使用阵列库的中等通量筛选和基于双 Luciferase 的分录报告器识别转录因子稳压器

通过恶性周围神经鞘肿瘤细胞中絮状等位基因的 离体 消融来定义肿瘤发生的基因功能

描述了微RNA转录的转录因子依赖调节

EWS-FLI1凝聚物在DNA上组装的单分子成像

用于研究癌基因衍生的转录-复制冲突的邻位连接测定

低细胞染色质免疫沉淀测序分析 Olig2 基因组结合位点在急性纯化 PDGFRα + 细胞中的转录因子鉴定

通过恶性周围神经鞘肿瘤细胞中絮状等位基因的离体消融来定义肿瘤发生的基因功能