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Development and Application of Computational Methods for Inferring the Molecular Mechanisms of Noncoding Genetic Variants / Alexandre Amlie-Wolf.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Amlie-Wolf, Alexandre, 1990- author.
- Language:
- English
- Subjects (All):
- Bioinformatics.
- Genetics.
- Neurosciences.
- Genomics and computational biology--Penn dissertations.
- Penn dissertations--Genomics and computational biology.
- Local Subjects:
- Bioinformatics.
- Genetics.
- Neurosciences.
- Genomics and computational biology--Penn dissertations.
- Penn dissertations--Genomics and computational biology.
- Genre:
- Academic theses.
- Physical Description:
- 1 online resource (299 pages)
- Contained In:
- Dissertations Abstracts International 81-04B.
- Place of Publication:
- [Philadelphia, Pennsylvania] : University of Pennsylvania ; Ann Arbor : ProQuest Dissertations & Theses, 2019.
- Language Note:
- English
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- The majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, affecting gene regulatory elements including transcriptional enhancers. However, characterizing their effects requires the integration of GWAS results with context-specific regulatory activity and linkage disequilibrium annotations to identify causal variants underlying noncoding association signals and the regulatory elements, tissue contexts, and target genes they affect. In this thesis, I developed INFERNO, an integrative computational method to address these questions. INFERNO integrates hundreds of functional genomics datasets spanning enhancer activity, transcription factor binding sites, and expression quantitative trait loci with GWAS summary statistics. INFERNO includes novel statistical methods to quantify empirical enrichments of tissue-specific enhancer overlap and to identify co-regulatory networks of dysregulated long noncoding RNAs (lncRNAs). I applied INFERNO to a range of brain-related phenotypes including schizophrenia, Alzheimer's disease (AD), and progressive supranuclear palsy (PSP). I describe detailed INFERNO results for AD including experimental validation where we detected genetic variation affecting a lncRNA which in turn regulates an important signaling pathway implicated in AD. I also present the results of a directed study of the 1.2 million base-pair H1/H2 inversion haplotype implicated in PSP, where we used INFERNO to disentangle the complex regulatory mechanisms present in this region, identifying target genes affected by the inversion and some independent of it. Finally, I describe the HiPPIE2 method which analyzes Hi-C chromatin conformation data to dynamically identify regulatory interactions with higher resolution than previous approaches. Application of HiPPIE2 to Hi-C data from a range of cell types elucidated the landscape of regulatory interactions and characterized specific transcription factors underlying enhancer-promoter interactions. This thesis work contributed novel algorithms for the integrative analysis of noncoding genetic associations, identified specific regulatory mechanisms dysregulated by genetic variation associated with a range of brain-related traits, and contributed novel analysis methodologies for Hi-C data.
- Notes:
- Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
- Advisors: Wang, Li-San; Committee members: Mingyao Li; Christopher Brown; Edward Lee; Gerard Schellenberg; Barbara Engelhardt.
- Department: Genomics and Computational Biology.
- Ph.D. University of Pennsylvania 2019.
- Local Notes:
- School code: 0175
- ISBN:
- 9781088337400
- Access Restriction:
- Restricted for use by site license.
- This item must not be sold to any third party vendors.
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