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Evaluation of Whole Exome Sequencing technology in cohort dataset and quantification of phenotypic alterations in a model organism.

机译:对队列数据集中的全外显子组测序技术进行评估,并对模型生物中的表型改变进行量化。

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摘要

This dissertation outlines bioinformatics approaches to improve genotypic and phenotypic analysis of disease variants. The first study is focused on improving the Whole Exome Sequencing (WES) technology. WES is a clinical diagnostic tool for discovering the genetic basis of many diseases, which takes advantage of the high coverage in target regions and provides a high probability of variant detection in protein coding regions. A major shortcoming of WES is the uneven coverage, which undermines its ability to detect deleterious mutations. Variant calling in specific low coverage regions is not accurate resulting in missing heritability. An examination of WES coverage by different capture technologies identified several parameters that affect coverage. The coverage could not be improved by increasing the number of sequencing runs. The low coverage regions had non-random distribution in the genome with a predominant clustered occurrence in regions enriched in duplicated sequences. These studies revealed that a significant number of reads were mistakenly discarded in WES datasets because of problems associated with mapping strategies. To improve the mapping results, a program, Rescuer, was developed. Rescuer first clusters overlapping reads mapped to multiple locations on the reference genome, and then assembles adjacent reads into longer contigs, which can be uniquely matched to target regions. Employing Rescuer, it was possible to achieve 10-20% improvement in the coverage. Rescuer significantly contributes towards variant detection in clinical investigations and accounts for some of the missing heritability issues in the study of complex diseases.;A second study focused on improving methods for functional validation of disease associated variants in experimental studies using a model organism, Drosophila melanogaster. Drosophila eye is used as a model to study basic developmental and cellular processes, genes and genetic interactions and human diseases including neurodevelopmental disorders, neurodegenerative disorders, cancer and more recently intellectual disability. Over 2500 genes are involved in the Drosophila melanogaster eye development. These genes account for about two-thirds of the vital genes in the genome making the fly eye an excellent experimental system for genetic screening. However, current strategies for functional screening of genes using the fly eye have been limited by a lack of highly sensitive and quantitative assays. To address this problem, a quantitative tool for functional analysis of genes and genetic interactions in the experimental Drosophila eye system was developed. The algorithm, implemented as Flynotyper software, uses a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. Flynotyper eliminates the need for qualitatively rank ordering the eye phenotypes and provides an accurate and automated method for eye phenotyping, documenting a broad range of impact for quantitative functional screens. The Rescuer and Flynotyper software packages developed in this study considerably improve detection of variants and provide quantitative assessments phenotypic variation in a model organism. These studies are likely to contribute to better assessment of the role of genetic variants in normal cellular processes and in disease conditions.
机译:本文概述了改善疾病变异的基因型和表型分析的生物信息学方法。第一项研究的重点是改进全外显子组测序(WES)技术。 WES是用于发现许多疾病的遗传基础的临床诊断工具,它利用了靶区域的高覆盖率,并提供了在蛋白质编码区域进行变异检测的高可能性。 WES的主要缺点是覆盖范围不均匀,这削弱了它检测有害突变的能力。在特定的低覆盖区域中进行变体调用不准确,导致缺少遗传性。通过不同的捕获技术对WES覆盖范围的检查确定了影响覆盖范围的几个参数。不能通过增加测序运行次数来提高覆盖率。低覆盖区域在基因组中具有非随机分布,在富集重复序列的区域中主要以簇状出现。这些研究表明,由于映射策略相关的问题,在WES数据集中错误地丢弃了大量读取。为了改善映射结果,开发了Rescuer程序。救援分子首先将重叠的读段聚类到参考基因组的多个位置,然后将相邻的读段组装成更长的重叠群,可以与目标区域进行唯一匹配。使用Rescuer,可以将覆盖率提高10-20%。 Rescuer在临床研究中显着促进了变异检测,并解决了复杂疾病研究中遗漏的一些遗传性问题。第二项研究着重于改进使用模式生物果蝇(Drosophila melanogaster)在实验研究中对疾病相关变异进行功能验证的方法。果蝇眼用作研究基本发育和细胞过程,基因和遗传相互作用以及人类疾病(包括神经发育障碍,神经退行性疾病,癌症和最近的智力障碍)的模型。果蝇眼发育涉及2500多个基因。这些基因约占基因组重要基因的三分之二,使蝇眼成为进行遗传筛选的出色实验系统。然而,由于缺乏高度灵敏和定量的测定方法,目前使用蝇眼进行基因功能筛选的策略受到了限制。为了解决这个问题,开发了一种定量工具,用于对果蝇眼系统中的基因和遗传相互作用进行功能分析。该算法以Flynotyper软件的形式实现,它使用一系列图像处理操作来自动检测蝇眼和单个眼孔,并计算表型得分,以衡量蝇眼中排列方式的无序性。 Flynotyper消除了对眼睛表型进行定性排序的需求,并为眼睛表型提供了一种准确而自动化的方法,从而证明了对定量功能屏幕的广泛影响。在这项研究中开发的Rescuer和Flynotyper软件包极大地改善了变体的检测,并提供了对模型生物体表型变异的定量评估。这些研究可能有助于更好地评估遗传变异在正常细胞过程和疾病状况中的作用。

著录项

  • 作者

    Wang, Qingyu.;

  • 作者单位

    The Pennsylvania State University.;

  • 授予单位 The Pennsylvania State University.;
  • 学科 Bioinformatics.;Neurosciences.;Genetics.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 183 p.
  • 总页数 183
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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