Name: candidate gene testing in clinical cohort studies with multiplexed genotyping and mass spectrometry
Uploaded: 2018-06-21T12:30:00.000+00:00
Duration: 5 min 53 s
Description: Watch this Scientific Journal Video about Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry at JoVE.com

作者没有确认。

本文所用的遗传物质在伦理上被批准用于儿童办公室 HREC (人类研究伦理学委员会) (CDF/07/492)、人类服务 HREC 部 (10/07) 和皇家儿童医院 HREC (27047)。
1. 设计复用试验
<ol><li>准备一个 SNP 列表进行化验设计。<ol>
<li>将目标区域输入到 Haploview (https://www.broadinstitute.org/haploview/downloads) 的标注器函数中。使用 LD (相关性, r2) 之间的 snp 跨越目标区域, 以生成一个 snps 列表, 它提供了所需的区域的全部覆盖, 所需的变体数量最少。生成一个 SNPs 列表, 以便捕获的所有等位基因都与用户定义的阈值 (e., r2 ≥0.8) 相关。</li>
	</ol></li>
	<li>前、逆、引引物的合适序列的识别<ol>
<li>在选择的检测设计工具中输入 snp 的生成列表。 注: 以下说明适用于用于生成具有代表性结果的化验设计工具, 如材料表中所述。</li>
		<li>一旦检测设计工具启动, 选择新的基因型设计。在 "设计名称" 字段中输入检测设计的名称。</li>
		<li>通过单击标记为 "编辑文本输入" 的按钮, 并通过按钮左侧的FASTA指示, 提供在步骤1.1.1 中生成的 SNP 列表。 注意: snp 可以输入为引用 (rs) SNP id 的文本列表, 或者以 FASTA 格式上载, 或者由该工具使用的 snp 组文件格式。要以这些格式上载文件, 请选择 "文件上载" 按钮。可以设计成单一化验的变体的上限, 称为 "好的", 是 40 snp。在开始运行之前, 可以指定作为设计优先级的 snp;这些将首先设计。可以指定控制 SNPs: 例如, 在样本混合 ups 或控件的情况下检测性别的测试, 以确定在使用低质量或劣质 DNA 时添加了足够的模板。然而, 应该指出, 使用控制和优先的 snps 可以减少可设计为单个井的 snps 的数量。</li>
		<li>从预设菜单中, 选择高复用 iPLEX 预设选项。从 "生物" 菜单中, 选择要 genotyped 的 DNA 所派生的有机体。对于这里提出的代表性结果, 这是人。 注意: 鼠标和牛的有机体也与该工具兼容。如果与植物或微生物等替代有机体合作, 也可以选择其他生物;然而, 由于缺乏一个参考基因组, 寻找近端 SNPs 和最佳引物区域的自动步骤将不可用。</li>
		<li>在 "数据库" 菜单中, 从 "化学" 菜单中选择 "基因组" 的最新版本, 或者在需要时进行替代生成。选择iPLEX和多路级别字段, 输入最高级别的复用:40。现在, 选择 "开始运行"。工具的 "步骤 1" 将开始。 注意: 在步骤1中, 该工具检索和格式化 SNP 序列。在这里, 错误可能包括 FASTA 文件的格式, 在这种情况下, FASTA 文件应按需要进行检查和重新格式化。另一个错误是 snp rs 数字与另一个 rs 号合并, 在这种情况下, 应该在 snp 数据库中搜索 rs 号, 如 NCBI 的 dbSNP, 以识别新的 SNP rs 号。在 SNP 周围的序列搜索任何已知的近端 SNPs 可能干扰底漆设计。潜在的 PCR 底漆站点被比较对基因组, 以避免非特异的放大由于多次命中在基因组。</li>
		<li>等待完成的 "步骤 2" 的设计工具, 其中近端的 SNPs 将被识别。 注意: 如果使用此步骤不支持的有机体, 如果此信息可用, 请在 IUPAC 注释中用近的 SNPs 注释序列。在此步骤中很少出现错误。然而, 如果选择了错误的参考有机体或基因组, 或者基因序列被输入而不是基因组 DNA, 可能会出现错误。要优化步骤 2, 请在 "高级设置" 下,如果在特定人群中工作, 可以根据人口筛选出 SNPs。稀有的 SNPs 也可以通过排除那些频率低于1% 的人来筛选出来。最后, 如果需要, 不具有验证状态或没有人口信息的 snp 也可以被排除。</li>
		<li>等待完成 "步骤 3" 的设计工具, 确定最佳底漆区域。如果选择了首选的底漆位置, 或者如果使用不同的有机体, 则通过将输入序列 (SNP 组文件) 标注为大写的首选底漆区域并在较低的序列的其余部分中手动输入底漆位置。情况下, 请从该步骤的 "高级设置" 菜单中选择 "保留案例"。 注意: 步骤 2 & 5月3日的错误包括: (1) 一个近 SNP 阻断了底漆的设计, 解决方案是用非模板底座进行掩模, 并订购一个像 Isonine 这样的通用底座的寡核苷酸, 或者, 设计两个引物, 一个与 proxim 的每个等位基因。阿 SNP, 或者, 设计一个底漆与共同的等位基因只。(2) 另一个常见的错误是, 没有为底漆确定一个独特的站点, 解决方案是修改扩增子长度, 以确定一个独特的站点。在本文所用的工具中, 缺省值为 80-120 bp。在 "3" 中的 "扩增子长度设置" 下的 "高级设置" 对话中, 可以更改 60-400 bp。确定最佳引物区域 "和也在" 4 的扩增子标签之下。设计化验。确保两者都已更改。然而, 应该注意的是, 不建议在使用退化的 DNA 时增加扩增子的长度。</li>
		<li>等待完成的化验设计步骤 ("步骤 4" 的设计工具), 这里的工具旨在提供最佳的通行证分离之间的推广引物和所有 SNPs 的等位基因在复用设计。完成此步骤后, 导出寡聚顺序文件, 它被格式化为通过选择的寡聚排序供应商轻松订购。 注: 放大底漆 (前 (F) 和反向 (R)) 的设计, 以产生最佳的扩增子大小为80至 120 bp。放大底漆质量必须有别于外延底漆及其产品, 以避免在质量谱和总体 PCR 性能方面产生冲突。引伸底漆应为15至30核苷酸长 (4500-9000 Da), 设计, 使 3 ' 年底将附加直接相邻的多态性的站点。所有这些设置都将在用于生成代表结果的工具中自动设置。</li>
	</ol></li>
	<li>从所选的工具和从低聚物提供商的订购底漆导出设计:25 nmol 的 PCR 引物 (向前和反向), 和 100 nmol 的每一个引伸底漆。见表 1用于生成代表结果的引物。</li>
</ol>2. 基因分型 (1-2 天)
<ol><li>准备放大底漆。<ol>
<li>如果冻干底漆被订购, 用分子级水进行重组。使用100微米/ul 的浓度为正向和反向底漆和500微米/ul 的延伸。</li>
		<li>池向前 & 反向引物为每复用化验成一个股票底漆混合, 包含每一个底漆浓度为0.5 毫米。 注: 例如, 400 ul 底漆池为400反应: <img alt="Equation" src="/files/ftp_upload/57601/57601eq1v2.jpg"> 2每个底漆的 ul, 在浓度为100微米/ul, 是需要的股票底漆池。对于具有60正向和反向底漆的30丛试验, 需要总共120个引物 ul (浓缩底漆池)。280 ul 分子级水将被添加到最后的体积 400 ul 的底漆混合。</li>
	</ol></li>
	<li>聚合酶链反应扩增 (PCR)
	<ol>
<li>做一个主混合 PCR 包含100毫微米的底漆混合以上, 500 微米的 dNTPs, 2 毫米的氯化镁2, 和 0.5 U 的 DNA 聚合酶。1 U 是需要大于26丛的化验。请参阅表 2。</li>
		<li>添加 4 ul 的这个混合到每个井的384井 PCR 板, 连同 1 ul 的基因组 DNA 在浓度 5-10 ng/ul。 注: 质量控制也应包括在板上, 如非模板控制, 和一个积极的控制, 以前表现良好的检测 (在测试运行期间)。如果运行多个板块, 来自另一板块 (s) 的多个 DNA 样本, 则应作为板间变异的技术控制运行。</li>
		<li>将板材在室温下以 200 x g 为1分钟进行离心, 以确保所有液体都包含在板井的底部。</li>
		<li>运行 PCR 与以下 thermocycler 条件: 4 分钟孵化在94°c 激活 DNA 聚合酶;45个周期以下 (变性在94°c 为二十年代, 退火在56°c 为三十年代和引伸在72°c 为1分钟) 和然后最后的引伸在72°c 为3分钟. 参考表 3中的 PCR 程序。</li>
		<li>进行琼脂糖凝胶电泳, 确保 DNA 扩增成功。在 2% (µL) 琼脂糖凝胶上使用 1 PCR 产品 (3 µL 的负载缓冲器), 并将琼脂糖粉和0.5% 三硼酸 EDTA (no) 缓冲剂混合制成, 并在 45 v 上运行100分钟。</li>
	</ol></li>
	<li>虾碱性磷酸酶 (SAP) 纯化步骤 注意: 此步骤用于移除未合并的核苷酸。SAP 酶将磷酸盐组组织在一起, 防止过量底漆和未合并的 dNTPs 干扰即将到来的延伸反应。<ol>
<li>制作一个主组合, 其中包含1.7 个单位/ul 的虾碱性磷酸酶 (sap) 酶, 10x sap 缓冲, 并弥补体积与分子级水。请参阅表 4。</li>
		<li>添加 2 ul 新组成的 SAP 主混合到每一个良好的板块, 已经包含 5 ul 从 PCR 反应。离心机简要和返回到 thermocycler 在37°c 40 分钟, 然后在85°c 5 分钟的酶失活。请参阅表 5。</li>
	</ol></li>
	<li>底漆延伸反应 注: 延长底漆组合中的引伸引物的浓度必须按尺寸 (线性底漆调整) 调整。这是因为在峰值强度 (质量谱) 和产品质量上存在反向关系。调整引伸底漆浓度纠正这种关系, 产生同等强度的峰值。表 6 & 7提供了用于产生代表性结果的调整底漆。所提供的体积是产生1.5 毫升的延伸底漆组合。<ol>
<li>使用梯度算法计算每个底漆的稀释系数, 可从阿金纳生物科学 ("线性底漆调整") 中获得, 它可以调整底漆的质量和浓度, 以及复用反应中的引物总数 (见表 6 & 7)。输入 UEP 质量为每个底漆进入 UEP_MASS 领域的线性底漆调整表。 注: 该底漆的质量调整浓度将自动计算在细胞与标题文本 "目标反应浓度 (µM)。要添加到底漆池的底漆体积将输出在标头文本 "卷料底漆" 下的单元格中, 以添加到池中 (µL)。将添加到底漆池中的水量, 以弥补计算出的浓度是输出到的细胞旁边的文本 "PCR 等级 RNase 免费 H2O 增加底漆池 (µL)。</li>
		<li>取线性底漆调整文件中指定的每一底漆的体积, 并组成底漆池。添加算法计算的水量, 以稀释在步进2.4.1 中确定的底漆池。 注: 如果梯度算法方法不可用, 另一种方法是将引物分为低质量和高质量, 并将高质量引物的浓度与低质量基团相加。高丛检测 (即19个 SNPs) 可能需要三或四组。然而, 该方法不会作为最佳的调用速率作为梯度算法的方法产生。</li>
		<li>装配扩展主组合。对于低丛检测 (1-18 丛), 添加 0.2 ul 的缓冲, 0.1 ul 的终止混合, 0.94 ul 的溶血磷脂酸调整底漆混合, 0.0205 ul 的酶 (准备在冰上)。对于高丛试验 (19-36 丛), 加入双重浓度的终止混合和酶 (终止混合 0.2 ul 和 iPLEX 酶 0.041 ul)。请参阅表 8。</li>
		<li>添加 2 ul 的延伸反应大师混合到板块从先前的反应, 现在把总体积到 9 ul 每井。离心机简要地和地方在 thermocycler:94 °c 为三十年代最初的孵化, 40 个周期 1 x 94 °c 为 5 s 与 5 x (52 °c 为 5 s, 跟随80°c 为 5 s), 然后72°c 为3分钟. 请参阅表 9。</li>
	</ol></li>
	<li>树脂提纯。 注: 过量的盐现在可以从反应中去除与树脂的使用。<ol>
<li>将 16 ul 的去离子水添加到回收板的井中, 使板材中的体积达到 25 ul。</li>
		<li>适用于树脂, 通常6毫克的酒窝树脂板 (单独购买), 均匀地对整个板材。将树脂在树脂酒窝板中干燥20分钟, 然后再应用于反应板。加入树脂后, 在室温下用手或用悬浮搅拌机以慢速 (e.、7.5 rpm) 旋转板材5分钟。 注: 在将基因型分析物加载到基因分型芯片之前, 样品和化验布局必须输入软件界面。这可以使用分析设计工具中的设计摘要文件来实现。</li>
	</ol></li>
	<li>在质谱平台上的测量。<ol>
<li>离心板在 3200 x g 5 分钟, 以避免树脂应用于质谱芯片。</li>
		<li>在运行之前, 将样品的板布局上载到系统的软件接口。 注意: 步骤2.6.3 只应由训练有素的人员执行。</li>
		<li>将分型分析物混合物从盘子中应用到分基因芯片上, 配以配药系统。接着, 将芯片加载到 MALDI 系统上, 从分析物混合物中生成质谱, 然后借助平台的软件接口解释。 注: 系统通过在每个 "垫" 上指示紫外线光的短脉冲, 与质谱芯片上的基因分型板的单个井相对应, 生成质量谱。这种脉冲会导致分析物的解吸和电离。这些电离 DNA 分子然后被推进到真空管的顶部由高压静电场, 分离轻的离子, 移动更快和到达探测器首先, 从重的离子。这些分析物的 "飞行时间" 由系统记录, 每个 DNA 片段的质量可以被确定, 因而可以推断出在 SNP 上存在的核苷酸基。</li>
	</ol></li>
</ol>3. 基因分型数据
注: 质量控制和数据解释不是本方法文件的重点。但是, 下面将简要介绍质量谱的解释。
<ol><li>质谱的手工检验和质量控制。 注: 原始质量谱由系统生成, 并与材料表中列出的软件进行分析。采用高斯混合聚类方法对该输出进行概率基因分型调用。<ol>
<li>打开分析软件。选择打字员分析器。从 "文件" 菜单中, 选择 "从文件中打开井", 然后使用步骤2.6.3 中生成的频谱数据选择 xml 文件。运行的芯片名称应该是可见的, 选择它, 384 井板的 "红绿灯" 窗格将显示在选定井中的 snp 列表中。在此处, 选择 "调用群集图" 以查看每个 SNP 的散点图数据点。 注意: 建议对低强度 SNPs 应用 "无调用" 结果。在用于代表结果的软件中, 提出了一种比默认值高5的聚类级切断方法, 用于严格的质量控制。此设置可在 "后处理群集" 窗格中的 "参数" 下的 "幅度截止" 字段中进行调整。从 "工具" 选项卡中选择 " Autocluster " 以运行群集分析。</li>
		<li>通过检查后处理窗格中的笛卡尔地块, 对基因型调用进行手动检查。在 "分析" 窗格中, 选择感兴趣的 SNP, 然后单击 "后处理群集" 选项卡, 用样本 id 和 SNP 的相应基因型将可见一个具有基因组聚类的簇图。</li>
		<li>检查基因型调用簇, 并评估每个个体调用集群与其他调用 SNP 的程度。该软件为每个基因型提供了一些边界线, 以供指导;参见基因型调用聚类图从IL13 SNP (图 1) 的例子。如果调用不与其他调用紧密地聚集在一起, 并且在群集中不存在, 或者如果它的强度很低, 请右键单击数据点并选择 "更改调用" 以手动将其设置为 "无呼叫"。</li>
		<li>为了确保高品质的基因分型数据用于下游分析, 排除了 SNPs 和在 QC 门槛下的呼叫率的个人,例如90%。一旦对呼叫数据进行了适当的调整, 就可以导出统计应用程序的数据。在用于生成代表结果的软件 (在材料表中列出), 这是通过 "视图" 菜单中的 "板数据选择" 和 "另存为" 选择的。</li>
	</ol>
</li>
</ol>

<ol>
	<li>Aronson, S. J., Rehm, H. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Building+the+foundation+for+genomics+in+precision+medicine.">Building the foundation for genomics in precision medicine.</a> Nature. 526 (7573), 336-342 (2015).</li><li>Ball, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Designing+a+GWAS:+power,+sample+size,+and+data+structure.">Designing a GWAS: power, sample size, and data structure.</a> Genome-Wide Association Studies and Genomic Prediction. , 37-98 (2013).</li><li>Kwon, J. M., Goate, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+candidate+gene+approach.">The candidate gene approach.</a> Alcohol research and health. 24 (3), 164-168 (2000).</li><li>Oeth, P., Mistro, G. D., Marnellos, G., Shi, T., van den Boom, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Qualitative+and+quantitative+genotyping+using+single+base+primer+extension+coupled+with+matrix-assisted+laser+desorption/ionization+time-of-flight+mass+spectrometry+(MassARRAY).">Qualitative and quantitative genotyping using single base primer extension coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MassARRAY).</a> Single Nucleotide Polymorphisms: Methods and Protocols. , 307-343 (2009).</li><li>Pusch, W., Kostrzewa, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+MALDI-TOF+mass+spectrometry+in+screening+and+diagnostic+research.">Application of MALDI-TOF mass spectrometry in screening and diagnostic research.</a> Current pharmaceutical design. 11 (20), 2577-2591 (2005).</li><li>Su, K. Y., 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=Pretreatment+epidermal+growth+factor+receptor+(EGFR)+T790M+mutation+predicts+shorter+EGFR+tyrosine+kinase+inhibitor+response+duration+in+patients+with+non-small-cell+lung+cancer.">Pretreatment epidermal growth factor receptor (EGFR) T790M mutation predicts shorter EGFR tyrosine kinase inhibitor response duration in patients with non-small-cell lung cancer.</a> Journal of clinical oncology. 30 (4), 433-440 (2012).</li><li>Singhal, N., Kumar, M., Kanaujia, P. K., Virdi, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MALDI-TOF+mass+spectrometry:+an+emerging+technology+for+microbial+identification+and+diagnosis.">MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis.</a> Frontiers in microbiology. 6, 791 (2015).</li><li>Cricca, M., 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=High-throughput+genotyping+of+high-risk+Human+Papillomavirus+by+MALDI-TOF+Mass+Spectrometry-based+method.">High-throughput genotyping of high-risk Human Papillomavirus by MALDI-TOF Mass Spectrometry-based method.</a> New Microbiologica. 38 (2), 211-223 (2015).</li><li>Ashley, S., 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=Genetic+Variation+at+the+Th2+Immune+Gene+IL13+is+Associated+with+IgE-mediated+Paediatric+Food+Allergy.">Genetic Variation at the Th2 Immune Gene IL13 is Associated with IgE-mediated Paediatric Food Allergy.</a> Clinical &amp; Experimental Allergy. 47 (8), 1032-1037 (2017).</li><li>Bousman, C. A., 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=Effects+of+NRG1+and+DAOA+genetic+variation+on+transition+to+psychosis+in+individuals+at+ultra-high+risk+for+psychosis.">Effects of NRG1 and DAOA genetic variation on transition to psychosis in individuals at ultra-high risk for psychosis.</a> Translational psychiatry. 3 (4), e251 (2013).</li><li>Moffatt, M. F., 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+large-scale,+consortium-based+genomewide+association+study+of+asthma.">A large-scale, consortium-based genomewide association study of asthma.</a> New England Journal of Medicine. 363 (13), 1211-1221 (2010).</li><li>Granada, M., 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+genome-wide+association+study+of+plasma+total+IgE+concentrations+in+the+Framingham+Heart+Study.">A genome-wide association study of plasma total IgE concentrations in the Framingham Heart Study.</a> Journal of Allergy and Clinical Immunology. 129 (3), 840-845 (2012).</li><li>Oeth, 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=iPLEX+assay:+Increased+plexing+efficiency+and+flexibility+for+MassARRAY+system+through+single+base+primer+extension+with+mass-modified+terminators.">iPLEX assay: Increased plexing efficiency and flexibility for MassARRAY system through single base primer extension with mass-modified terminators.</a> Sequenom application note. 27, (2005).</li><li>Ellis, J. A., Ong, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+MassARRAY+System+for+Targeted+SNP+Genotyping.">The MassARRAY System for Targeted SNP Genotyping.</a> Genotyping: Methods and Protocols. , 77-94 (2017).</li><li>Johnson, A. D., 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=SNAP:+A+web-based+tool+for+identification+and+annotation+of+proxy+SNPs+using+HapMap.">SNAP: A web-based tool for identification and annotation of proxy SNPs using HapMap.</a> Bioinformatics. 24 (24), 2938-2939 (2008).</li></ol>

作者没有什么可透露的。

在这里, 我们演示了用质谱复用基因分型的方法。用 PCR 配对的 MALDI 质谱4与材料表13中所列的化学分析结果进行了研究。在这个平台上, 我们在实验室的40小时内共生成了11295个基因型, 1255 个个体9个 snp。
我们通过在发现临床队列 phenotyped 对食物过敏和独立复制的候选基因IL13中生成和分析 SNP 数据, 说明该技术在回答遗传假说方面的有用性。该平台相对健壮, 以降低 DNA 质量, 需要最小的起始材料, 输入只有 10 ng。协议中的关键步骤包括以下内容: 仔细排查分析设计过程, 确保在复用检测中最大 SNP 夹杂, 在扩增 PCR 过程中成功地放大目标区域, 成功的单在扩展反应过程中的核苷酸扩展, 并将检测和样品板布局加载到分析软件中, 以便软件准确地分配质量谱数据。
如前所述, 除人类外, 检测设计工具与老鼠和牛多态性的使用是相容的。对于其他有机体, 如微生物或植物, "其他" 可以选择在 "有机体" 菜单。然而, 寻找近端 SNPs 和确定最佳底漆区域的自动化步骤将不可用。
在设计过程中, 如果一个近 snp 阻止了最佳引物区域的识别, 你可以从设计中移除 SNP, 然后在高 LD 中选择另一个 (例如, r2 = 1), 或者选择设计两个引物, 一个参照snp 的等位基因和一个有替代的基因, 或设计一个与共同的等位基因的底漆, 或掩盖 SNP 与一个普遍的基础 (如肌苷)。如果确定底漆的唯一站点有问题, 可以更改扩增子长度设置以查找唯一的站点。默认设置是 80-120 bp, 但这可以修改从 60-400 bp。然而, 应该指出, 如果使用退化的 DNA (例如, 从 FFPE 组织), 它不是理想的增加扩增子长度。
该工具的检测设计步骤中的错误可能包括高发夹或底漆二聚体电位。这两种设置都可以轻松地尝试容纳设计。但是, 建议在0.8 以下不放宽阈值;从0.9 开始, 看看这个设置是否足以挽救 SNPs, 并仅在必要时减少到0.8。在高级设置中, 可以在 "4" 的 "复合" 选项卡下更改设计迭代的数量 (最多10个)。设计化验 ", 以及最佳的迭代选择标准, 以最高平均多路或最少拒绝的低丛。增加设计迭代的数量可能是有利的, 因为该工具将按照所提供的顺序采取第一个 SNP, 并将设计一个检测。然后测试下 SNP 是否与同一复用检测兼容。因此, SNPs 的顺序是重要的。选择多个迭代选项后, 软件将随机化 SNPs 的顺序并尝试其他迭代。这可能会增加能被设计成每个多路的 SNPs 的数量, 或者可能减少 snp 拒绝的数量。然而, 它也将在一个时间成本, 因为设计工具将需要更长的这一步。
多重基因分型是一种快速和负担得起的方法来调查感兴趣的基因座。该方法进行了简化, 允许在10小时内运行大约760个40丛 SNPs 的样本, 允许成千上万的基因型在不到一天的时间内生成14。通过平台提供的工具可以很容易地分析质量谱。
对该平台的一些限制包括估计损失 5-10% 的 SNPs, 将失败的化验设计过程。有时可以通过选择替代标记或代理 SNP 来纠正这一点。广研所的 SNP 注释和代理搜索 (快照) 数据库是一种便于识别代理 SNPs15的工具。该系统的另一个局限性是, 它是一个目标平台, 因此不允许进行广泛的新奇发现, 就像全基因组方法所实现的那样。此外, 由于该方法使用标记 SNP 代理来最大化基因覆盖范围, 因此可能需要精细映射研究来确定精确的因果变体。
多重基因分型仍然是一个有用的平台, 以审问疾病相关的 snp 确定的 GWA 研究方法或假设驱动候选和路径基因探索。未来的平台应用可能是诊断和筛选领域, 如癌症和临床病毒学的新用途。综合多路基因分型与质谱法是一种快速、经济、可靠的中等吞吐量的基因型候选基因位的方法。

在人类复杂的疾病中, 遗传变异有助于疾病的易感性和量化这些变种可能有助于了解发病机制, 识别高危患者组和治疗应答者。的确, 精确医学的承诺依赖于利用基因组信息来识别患者亚群1。不幸的是, 在复杂的疾病生物学空间中, 疾病表型的基础是大量的遗传异质性、低显性和可变表现力, 在基因组范围内识别小说的队列大小要求候选人往往是令人望而却步的大2。另外, 有针对性的候选基因方法首先是关于疾病病因学3中特定基因/通路的先验假说。通路分析工具通常用于调查确定的靶位点的病理生理学, 从而产生许多候选通路。我们在这里演示了一个多重基因分型方法, 允许调查数以万计的 snp 与一个化验, 适合人类队列研究4。这种方法是相对较高的通过投入, 允许成百上千的 DNA 样本被 genotyped 新的发现研究和研究的特定途径。这里概述的方法是有用的识别风险等位基因及其与临床特征的关联, 以相对快速和廉价的方式。该平台为5、6和最近的微生物感染7和人乳突病毒8的筛查和诊断目的提供了极大的优势。
本议定书首先从选择一组基因进行调查, 即目标区域, 通常是通过文献检索确定的, 或者是对参与疾病过程的先验假说;也可能被选为复制, 作为一个发现基因组范围的协会 (GWA) 研究的主要协会。从基因组, 研究员将选择一个精致的标签 SNPs 列表。即, 在该区域的变种之间的连锁不平衡 (LD) 或相关性, 用来确定一个代表的 "标记 snp" 的一组 snp 在高 LD, 称为单体。该区域的高 LD 意味着, snp 经常被遗传在一起, 这样, 基因型一 SNP 就足以代表单体中所有 SNPs 的变异。或者, 如果对来自许多地区的 SNPs 的明确列表进行跟踪, GWA 研究的复制, 这个过程可能是不必要的。对于复用基因分型, 必须围绕这些目标设计一个化验, 以便放大引物与延伸底漆和产品的质量不同, 以产生解释质谱。这些参数很容易实现的多重基因分型分析设计工具。该设计的正反引物将被用来瞄准感兴趣的标记并放大包含 SNP 的序列。引伸引物直接附着在 SNPs 上, 并添加了一个与 snp 互补的单质量修饰的 "终结者" 基础。终止者基地防止进一步扩展脱氧核糖核酸。该基的质量修正使不同的碎片由一个单一的基地被检测到质谱。将含有基因分型化学的板块应用于一种用于质谱平台测量的芯片。在对系统检测到的原始基因分型调用应用适当的质量控制后, 可以导出数据并用于统计分析, 以测试与疾病表的相关性。

<table><tbody><tr><td>Genomic DNA&amp;nbsp;</td><td>-</td><td>-</td><td>1 &amp;mu;L at a concentration of 5-10 ng/&amp;mu;L</td></tr><tr><td>Primers: forward and reverse amplification and extension</td><td>IDT</td><td>-</td><td>see manuscript section 1.2.1 on design of primers</td></tr><tr><td>Deionized water&amp;nbsp;</td><td>E.g. Milli-Q water&amp;nbsp;</td><td>-</td><td>deionized with 18.2 M&amp;Omega;.cm resistivity</td></tr><tr><td>Genotyping reagent kit. iPLEX Gold Chemistry reagent set&amp;nbsp;</td><td>Agena Bioscience</td><td>#10148-2</td><td>includes all reagents for reactions in 2.2.1, 2.3.1 and 2.4.2 , chip and resin</td></tr><tr><td>PCR plates (384-well)</td><td>Abgene</td><td>#ABGAB-1384</td><td>For the MassARRAY system plates by Abgene are compatible</td></tr><tr><td>Micropipettes</td><td></td><td></td><td>single and 8-channel</td></tr><tr><td>Centrifuge&amp;nbsp;</td><td></td><td></td><td>compatible with 384-well plates</td></tr><tr><td>Thermocycler</td><td></td><td></td><td>compatible with PCR programs as detailed in 2.2.4, 2.3.2 and 2.4.3</td></tr><tr><td>Dimple resin plate&amp;nbsp;</td><td>Agena Bioscience</td><td></td><td>6mg, 384-well</td></tr><tr><td>Plate rotator&amp;nbsp;</td><td></td><td></td><td></td></tr><tr><td>MassARRAY Analyzer 4 System</td><td>Agena Biosciences</td><td></td><td>MALDI-TOF (matrix-assisted laser desorption/ionization &amp;ndash; time of flight) Mass Spectrometer.</td></tr><tr><td>RS1000 Nanodispenser</td><td>Agena Biosciences</td><td></td><td></td></tr><tr><td>Assay Design Suite</td><td>Agena Biosciences</td><td></td><td>Tool used to design the multiplex genotyping assays</td></tr><tr><td>Hot Start Taq</td><td></td><td></td><td>DNA polymerase enzyme&amp;nbsp;</td></tr><tr><td>Resin&amp;nbsp;</td><td>Agena Biosciences</td><td></td><td>Supplied with iPLEX kit</td></tr></tbody></table>

candidate gene testing in clinical cohort studies with multiplexed genotyping and mass spectrometry

复杂的疾病往往是由多种常见的遗传变异所支撑的, 它们导致了疾病的易感性。在这里, 我们描述了一个经济高效的标签单核苷酸多态性 (SNP) 方法, 使用多路基因分型检测与质谱, 以调查基因通路协会的临床团体。我们研究食品过敏候选者轨迹Interleukin13 (IL13) 作为一个例子。此方法利用区域内的共享链接不平衡 (LD) 有效地最大化覆盖率。然后将所选的 LD snps 设计成多路复用检测, 使多达40种不同的 snps 同时进行分析, 提高成本效益。聚合酶链反应 (PCR) 用于放大目标基因座, 其次是单核苷酸扩展, 然后用基质辅助激光解吸/电离时间 (MALDI) 质谱测量 amplicons。用基因型呼叫软件对原始输出进行分析, 采用严格的质量控制定义和截割方法, 确定高概率基因型, 并输出数据分析。

Watch this Scientific Journal Video about Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry at JoVE.com

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

应用多重基因分型和质谱法进行临床队列研究的候选基因检测

鉴定导致复杂人类疾病的遗传变异使我们能够确定新的机制。在这里, 我们展示了一个多重基因分型方法的候选基因或基因通路分析, 最大限度地扩大覆盖率, 以低成本, 并服从队列为基础的研究。

Complex diseases are often underpinned by multiple common genetic variants that contribute to disease susceptibility. Here, we describe a cost-effective ...

candidate-gene-testing-clinical-cohort-studies-with-multiplexed

Nanyang Technological University

Research

JoVE Journal

Genetics

10.1K 次观看.  Max-Delbrück Center for Molecular Medicine. 鉴定导致复杂人类疾病的遗传变异使我们能够确定新的机制。在这里, 我们展示了一个多重基因分型方法的候选基因或基因通路分析, 最大限度地扩大覆盖率, 以低成本, 并服从队列为基础的研究。

视频: Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia

There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1 and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo mutations. This is the case for autism and schizophrenia3. The male-to-female ratio of mutation rate is estimated at about 4&#x2013;6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo mutations would more frequently come from males, particularly older males4. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.

Molecular genetic strategy for finding de novo mutations causing common disorders such as autism and schizophrenia.

一项战略，以确定在常见的疾病，如自闭症和精神分裂症的新突变

There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, ...

科研

医学

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Advancements in the cost and speed of next generation genetic sequencing have generated an explosion of clinical whole exome and whole genome testing. While this has led to increased identification of likely pathogenic mutations associated with genetic syndromes, it has also dramatically increased the number of incidentally found genetic variants of unknown significance (VUS). Determining the clinical significance of these variants is a major challenge for both scientists and clinicians. An approach to assist in determining the likelihood of pathogenicity is signal-to-noise analysis at the protein sequence level. This protocol describes a method for amino acid-level signal-to-noise analysis that leverages variant frequency at each amino acid position of the protein with known protein topology to identify areas of the primary sequence with elevated likelihood of pathologic variation (relative to population &#34;background&#34; variation). This method can identify amino acid residue location &#34;hotspots&#34; of high pathologic signal, which can be used to refine the diagnostic weight of VUSs such as those identified by next generation genetic testing.

Amino acid-level signal-to-noise analysis determines the prevalence of genetic variation at a given amino acid position normalized to background genetic variation of a given population. This allows for identification of variant &#34;hotspots&#34; within a protein sequence (signal) that rises above the frequency of rare variants found in a population (noise).

遗传变异的氨基酸级信噪比分析确定变异致病性的可能性

Advancements in the cost and speed of next generation genetic sequencing have generated an explosion of clinical whole exome and whole genome testing. ...

遗传学

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in&#160;patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.

Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.

患者生物流体中肿瘤相关循环DNA的检测与监测

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular ...

癌症研究

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Next-generation sequencing has gained increasing importance in the clinical application in the determination of genetic variants. In the pre-implantation genetic test, this technique has its unique advantages in scalability, throughput, and cost. For the pre-implantation genetic test for aneuploidy analysis, the semiconductor-based next-generation sequencing (NGS) system presented here provides a comprehensive approach to determine structural genetic variants at a minimum resolution of 8 Mb. From sample acquisition to the final report, the working process requires multiple steps with close adherence to protocols. Since various critical steps could determine the outcome of amplification, quality of the library, coverage of reads, and output of data, descriptive information with visual demonstration other than words could offer more detail to the operation and manipulation, which may have a great impact on the results of all critical steps. The methods presented herein will display the procedures involved in whole genome amplification (WGA) of biopsied Trophectoderm (TE) cells, genomic library construction, sequencer management, and finally, generating copy number variants' reports.

The protocol presents the overall in-lab procedures required in pre-implantation genetic testing for aneuploidy on a semiconductor-based next-generation sequencing platform. Here we present the detailed steps of whole genome amplification, DNA fragment selection, library construction, template preparation, and sequencing working flow with representative results.

基于半导体的下一代测序平台上非整倍体的植入前基因检测

Next-generation sequencing has gained increasing importance in the clinical application in the determination of genetic variants. In the pre-implantation ...

基因组规模筛选，用于识别和比较肿瘤中的治疗靶点

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are derived from Schwann cells or their precursors. In patients with the tumor susceptibility syndrome neurofibromatosis type 1 (NF1), MPNSTs are the most common malignancy and the leading cause of death. These rare and aggressive soft-tissue sarcomas offer a stark future, with 5-year disease-free survival rates of 34-60%. Treatment options for individuals with MPNSTs are disappointingly limited, with disfiguring surgery being the foremost treatment option. Many once-promising therapies such as tipifarnib, an inhibitor of Ras signaling, have failed clinically. Likewise, phase II clinical trials with erlotinib, which targets the epidermal growth factor (EFGR), and sorafenib, which targets the vascular endothelial growth factor receptor (VEGF), platelet-derived growth factor receptor (PDGF), and Raf, in combination with standard chemotherapy, have also failed to produce a response in patients. 
In recent years, functional genomic screening methods combined with genetic profiling of cancer cell lines have proven useful for identifying essential cytoplasmic signaling pathways and the development of target-specific therapies. In the case of rare tumor types, a variation of this approach known as cross-species comparative oncogenomics is increasingly being used to identify novel therapeutic targets. In cross-species comparative oncogenomics, genetic profiling and functional genomics are performed in genetically engineered mouse (GEM) models and the results are then validated in the rare human specimens and cell lines that are available. 
This paper describes how to identify candidate driver gene mutations in human and mouse MPNST cells using whole exome sequencing (WES). We then describe how to perform genome-scale shRNA screens to identify and compare critical signaling pathways in mouse and human MPNST cells and identify druggable targets in these pathways. These methodologies provide an effective approach to identifying new therapeutic targets in a variety of human cancer types.

作者聚焦:通过基因组规模 shRNA 筛选寻找恶性周围神经鞘瘤的新治疗靶点 

We have developed a cross-species comparative oncogenomics approach utilizing genomic analyses and functional genomic screens to identify and compare therapeutic targets in tumors arising in genetically engineered mouse models and the corresponding human tumor type.

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are derived from Schwann cells or their precursors. In patients with the tumor susceptibility syndrome ...

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been understood at molecular level. One of the mechanisms mediating the effect of DNA variants on phenotypes is gene expression, which has been shown to be particularly relevant for complex traits1.
This method tests in a cellular context the effect of specific DNA sequences on gene expression. The principle is to measure the relative abundance of transcripts arising from the two alleles of a gene, analysing cells which carry one copy of the DNA sequences associated with disease (the risk variants)2,3. Therefore, the cells used for this method should meet two fundamental genotypic requirements: they have to be heterozygous both for DNA risk variants and for DNA markers, typically coding polymorphisms, which can distinguish transcripts based on their chromosomal origin (Figure 1). DNA risk variants and DNA markers do not need to have the same allele frequency but the phase (haplotypic) relationship of the genetic markers needs to be understood. It is also important to choose cell types which express the gene of interest. This protocol refers specifically to the procedure adopted to extract nucleic acids from fibroblasts but the method is equally applicable to other cells types including primary cells.
DNA and RNA are extracted from the selected cell lines and cDNA is generated. DNA and cDNA are analysed with a primer extension assay, designed to target the coding DNA markers4. The primer extension assay is carried out using the MassARRAY (Sequenom)5 platform according to the manufacturer's specifications. Primer extension products are then analysed by matrix-assisted laser desorption/ionization time of-flight mass spectrometry (MALDI-TOF/MS). Because the selected markers are heterozygous they will generate two peaks on the MS profiles. The area of each peak is proportional to the transcript abundance and can be measured with a function of the MassARRAY Typer software to generate an allelic ratio (allele 1: allele 2) calculation. The allelic ratio obtained for cDNA is normalized using that measured from genomic DNA, where the allelic ratio is expected to be 1:1 to correct for technical artifacts. Markers with a normalised allelic ratio significantly different to 1 indicate that the amount of transcript generated from the two chromosomes in the same cell is different, suggesting that the DNA variants associated with the phenotype have an effect on gene expression. Experimental controls should be used to confirm the results.

Genetic associations often remain unexplained at a functional level. This method aims to assess the effect of phenotype-associated genetic markers on gene expression by analyzing cells heterozygous for transcribed SNPs. The technology allows accurate measurement by MALDI-TOF mass spectrometry to quantify allele-specific primer extension products.

等位基因特异性基因表达检测，测试的遗传协会的功能基础

The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been ...

生物学

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench (&#34;wet bench&#34;) and data analyses conducted using bioinformatics pipelines (&#34;dry bench&#34;). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible &#34;tag&#34; PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.

An integrated system for targeted next-generation sequencing of oncology specimens is described. This cross-platform system is optimized for low-quality and low-quantity tumor biopsies, accommodates low DNA inputs, includes well-characterized multi-variant controls, and features a novel variant caller that is informed by quantitative pre-analytical quality control measures.

低质量和低数量肿瘤活检丰枯台过程的集成优化了有针对性的下一代测序

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench (&#34;wet bench&#34;) and data analyses conducted using ...

Infinium Assay for Large-scale SNP Genotyping Applications

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina&#39;s panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.

A protocol is described that uses Illumina&#39;s Infinium assays to perform large-scale genotyping. These assays can reliably genotype millions of SNPs across hundreds of individual DNA samples in three days. Once generated, these genotypes can be used to check for associations with a variety of different diseases or phenotypes.

应用多重基因分型和质谱法进行临床队列研究的候选基因检测

摘要

探索更多视频

此视频中的章节

一项战略，以确定在常见的疾病，如自闭症和精神分裂症的新突变

遗传变异的氨基酸级信噪比分析确定变异致病性的可能性

患者生物流体中肿瘤相关循环DNA的检测与监测

基于半导体的下一代测序平台上非整倍体的植入前基因检测

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

等位基因特异性基因表达检测，测试的遗传协会的功能基础

低质量和低数量肿瘤活检丰枯台过程的集成优化了有针对性的下一代测序

Infinium检测的大型SNP基因分型应用