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Evaluation of whole exome sequencing technology in cohort dataset and quantification of phenotypic alterations in a model organism

Author:
Wang, Qingyu
Published:
[University Park, Pennsylvania] : Pennsylvania State University, 2016.
Physical Description:
1 electronic document
Additional Creators:
Altman, Naomi S. and Girirajan, Santhosh
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Open Access.
Summary:
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.
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Dissertation Note:
Ph.D. Pennsylvania State University 2016.
Reproduction Note:
Microfilm (positive). 1 reel ; 35 mm. (University Microfilms 10-154616)
Technical Details:
The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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