Detecting DNA modifications from SMRT sequencing data by modeling sequence context dependence of polymerase kinetic.
Detecting DNA modifications from SMRT sequencing data by modeling sequence context dependence of polymerase kinetic.
复制标题
DOI：
10.1371/journal.pcbi.1002935
复制
发表时间：
2013
影响因子：
4.3
通讯作者：
Schadt E
中科院分区：
文献类型：
--
作者：
Feng Z;Fang G;Korlach J;Clark T;Luong K;Zhang X;Wong W;Schadt E
DNA修饰，如甲基化和DNA损伤，可以在生物系统中发挥关键的调节作用。单分子、真实的时间（SMRT）测序技术产生DNA序列以及DNA聚合酶动力学信息，其可用于直接检测DNA修饰。我们证明，当地的序列上下文有很强的影响，在附近的掺入位点的DNA聚合酶动力学在DNA合成反应，允许的可能性，估计预期的动力学速率的酶在掺入位点使用收集的动力学速率信息从现有的SMRT测序数据（历史数据）覆盖相同的本地序列上下文的兴趣。我们开发了一个经验贝叶斯分层模型，将历史数据。实验结果表明，该模型可以大大提高DNA修饰检测的准确率，降低对控制数据覆盖率的要求。对于一些具有强信号的DNA修饰，通过使用历史数据作为对照的替代，甚至不需要对照样品。因此，通过使用该模型可以大大降低测序成本。我们在一个名为seqPatch的R包中实现了该模型，该包可在https://github.com/zhixingfeng/seqPatch上获得。DNA修饰已经在从细菌到人类的各种生物体中发现。许多现有的研究表明，它们在发育、疾病、细菌毒力等方面发挥着重要作用。然而，对于许多类型的DNA修饰，例如N6-甲基腺嘌呤和8-oxoG，目前还没有一种高效准确的检测方法。单分子真实的时间（SMRT）测序不仅产生DNA序列，而且产生DNA聚合酶动力学信息。动力学信息对测序的DNA模板中的DNA修饰敏感，因此可用于检测广泛的DNA修饰类型。通常的检测策略是病例对照法，该方法比较天然样品和已去除修饰的对照样品之间的动力学信息。然而，生成对照样品使成本加倍。我们提出了一个分层模型，它可以结合现有的SMRT测序数据，以提高检测准确性，降低控制样品的覆盖率要求，甚至在某些情况下避免需要控制样品。我们在已知修饰位点的质粒和大肠杆菌的SMRT测序数据上测试了我们的方法。coliK-12菌株进行测序，结果表明，该方法可以大大提高检测准确率，降低测序成本。
DNA modifications such as methylation and DNA damage can play critical regulatory roles in biological systems. Single molecule, real time (SMRT) sequencing technology generates DNA sequences as well as DNA polymerase kinetic information that can be used for the direct detection of DNA modifications. We demonstrate that local sequence context has a strong impact on DNA polymerase kinetics in the neighborhood of the incorporation site during the DNA synthesis reaction, allowing for the possibility of estimating the expected kinetic rate of the enzyme at the incorporation site using kinetic rate information collected from existing SMRT sequencing data (historical data) covering the same local sequence contexts of interest. We develop an Empirical Bayesian hierarchical model for incorporating historical data. Our results show that the model could greatly increase DNA modification detection accuracy, and reduce requirement of control data coverage. For some DNA modifications that have a strong signal, a control sample is not even needed by using historical data as alternative to control. Thus, sequencing costs can be greatly reduced by using the model. We implemented the model in a R package named seqPatch, which is available at https://github.com/zhixingfeng/seqPatch. DNA modifications have been found in a wide range of living organisms, from bacteria to human. Many existing studies have shown that they play important roles in development, disease, bacteria virulence, etc. However, for many types of DNA modification, for example N6-methyladenine and 8-oxoG, there is not an efficient and accurate detection method. Single molecule real time (SMRT) sequencing not only generates DNA sequences, but also generates DNA polymerase kinetic information. The kinetic information is sensitive to DNA modifications in the sequenced DNA template, and therefore can be used for detecting a wide range of DNA modification types. The usual detection strategy is a case-control method, which compare kinetic information between native sample and a control sample whose modifications have been removed. However, generating a control sample doubles the cost. We proposed a hierarchical model, which can incorporate existing SMRT sequencing data to increase detection accuracy and reduce coverage requirement of control sample or even avoid the need of a control sample in some cases. We tested our method on SMRT sequencing data of plasmids with known modified sites and E. coli K-12 strain to demonstrate our method can greatly increase detection accuracy and reduce sequencing cost.
登录
查看更多内容
影响因子：
48
作者：
Flusberg, Benjamin A.;Webster, Dale R.;Lee, Jessica H.;Travers, Kevin J.;Olivares, Eric C.;Clark, Tyson A.;Korlach, Jonas;Turner, Stephen W.
通讯作者：
Turner, Stephen W.
影响因子：
3.5
作者：
Schadt, Eric E.;Turner, Steve;Kasarskis, Andrew
通讯作者：
Kasarskis, Andrew
影响因子：
2.9
作者：
BLOOM, LB;OTTO, MR;BEECHEM, JM
通讯作者：
BEECHEM, JM
影响因子：
4.5
作者：
Friedman, JH
通讯作者：
Friedman, JH
影响因子：
56.9
作者：
Eid, John;Fehr, Adrian;Turner, Stephen
通讯作者：
Turner, Stephen