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Computational Approaches Identify Novel Risk Loci and Interactions in Heart Defects.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational Approaches Identify Novel Risk Loci and Interactions in Heart Defects./
作者:	Pittman, Maureen.
面頁冊數:	1 online resource (161 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-09, Section: B.
Contained By:	Dissertations Abstracts International84-09B.
標題:	Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30310974click for full text (PQDT)
ISBN:	9798377642831

Computational Approaches Identify Novel Risk Loci and Interactions in Heart Defects.
Pittman, Maureen.

Computational Approaches Identify Novel Risk Loci and Interactions in Heart Defects. - 1 online resource (161 pages)

Source: Dissertations Abstracts International, Volume: 84-09, Section: B.

Thesis (Ph.D.)--University of California, San Francisco, 2023.

Includes bibliographical references

Congenital heart defects (CHD) occur in nearly one percent of live births each year and are the leading cause of defect-associated infant mortality. In spite of the growing size of disease cohorts, the molecular underpinnings of most cases remain unexplained. Given its high recurrence rate in families, we expect much of this contribution to be found within patient genomes, but extensive genetic heterogeneity limits our ability to statistically confirm risk loci. Previously-validated causal mutations occur in a wide range of genes that encode for proteins in signaling and migration, chromatin remodelers that induce lineage specification, and transcription factors regulating the expression of these genes. In order to identify cryptic risk loci, my thesis has focused on creating novel computational approaches to overcome statistical challenges and broaden our understanding of the mechanisms that can lead to CHD. By integrating protein-protein interaction networks of cardiac transcription factors with whole exome sequencing, I showed that interactors are enriched for rare and de novo mutations in CHD patients. I developed a variant prioritization scheme for de novo variants, which identified a GLYR1 mutation that destabilizes its interaction with cardiac transcription factor GATA4. I describe GCOD, a novel algorithm that uses probabilistic modeling to identify sets of genes predicted to interact in the etiology of CHD, including a novel genetic interaction between GATA6 and POR. Finally, in addition to coding mutations, I aimed to assess whether disruption to chromatin organization contributes to disease by characterizing three CHD patient variants that I predicted would alter the regulatory landscape of heart-relevant genes. My work has increased our repertoire of known and suspected disease loci in CHD and related developmental co-morbidities, and provided evidence of oligogenic combinations and disrupted genome folding as a mechanism in CHD.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798377642831Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Congenital heart defectsIndex Terms--Genre/Form:

542853
Electronic books.

Computational Approaches Identify Novel Risk Loci and Interactions in Heart Defects.
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