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RNA Turnover and Trisomy: Inferring ...

Hunter, Samuel.

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RNA Turnover and Trisomy: Inferring RNA Decay Rates Throughout the Interferon Response in Down Syndrome.

Record Type:	Electronic resources : Monograph/item
Title/Author:	RNA Turnover and Trisomy: Inferring RNA Decay Rates Throughout the Interferon Response in Down Syndrome./
Author:	Hunter, Samuel.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	168 p.
Notes:	Source: Dissertations Abstracts International, Volume: 84-11, Section: B.
Contained By:	Dissertations Abstracts International84-11B.
Subject:	Molecular biology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30247441
ISBN:	9798379532727

RNA Turnover and Trisomy: Inferring RNA Decay Rates Throughout the Interferon Response in Down Syndrome.
Hunter, Samuel.

RNA Turnover and Trisomy: Inferring RNA Decay Rates Throughout the Interferon Response in Down Syndrome. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 168 p.

Source: Dissertations Abstracts International, Volume: 84-11, Section: B.

Thesis (Ph.D.)--University of Colorado at Boulder, 2023.

This item must not be sold to any third party vendors.

Trisomy 21 is a genetic abnormality in which chromosome 21 is triplicated. Increasing DNA copy number has drastic consequences on the production and regulation of RNA. Dysregulated RNA levels in individuals with Trisomy 21 contribute to many disease phenotypes, including an aberrant interferon response. Such "interferonopathies" have been well characterized in steady state assays; however, it is unknown whether differences in RNA production and turnover dynamics exist in the trisomy 21 interferon response. Difficulties in probing RNA dynamics in trisomy 21 are threefold. First, in comparison with their steady state counterparts, nascent RNA production assays (such as GRO-seq and PRO-seq) are challenging and prone to technical noise. Second, differential analysis of high-throughput RNA assays in trisomic backgrounds requires additional statistical considerations. Lastly, high throughput RNA turnover assays utilize modified RNA-seq protocols with toxic metabolic labels, which can confound results. Thus, I first benchmarked and demonstrated technical signatures left by protocol variations in nascent sequencing library generation. Next, I developed a modified pipeline for differential analysis when using trisomic libraries, which properly account for the trisomic condition and normalizes read counts accordingly. Finally, I utilized these new modified pipelines in an analysis of PRO- and RNA-seq libraries generated from a time series of interferon treatment in trisomic and disomic lymphoblastoid cell lines. I utilized this time series to develop a computational method to infer RNA degradation rates across time.

ISBN: 9798379532727Subjects--Topical Terms:

517296
Molecular biology.
Subjects--Index Terms:

RNA degradation

RNA Turnover and Trisomy: Inferring RNA Decay Rates Throughout the Interferon Response in Down Syndrome.
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520 $a Trisomy 21 is a genetic abnormality in which chromosome 21 is triplicated. Increasing DNA copy number has drastic consequences on the production and regulation of RNA. Dysregulated RNA levels in individuals with Trisomy 21 contribute to many disease phenotypes, including an aberrant interferon response. Such "interferonopathies" have been well characterized in steady state assays; however, it is unknown whether differences in RNA production and turnover dynamics exist in the trisomy 21 interferon response. Difficulties in probing RNA dynamics in trisomy 21 are threefold. First, in comparison with their steady state counterparts, nascent RNA production assays (such as GRO-seq and PRO-seq) are challenging and prone to technical noise. Second, differential analysis of high-throughput RNA assays in trisomic backgrounds requires additional statistical considerations. Lastly, high throughput RNA turnover assays utilize modified RNA-seq protocols with toxic metabolic labels, which can confound results. Thus, I first benchmarked and demonstrated technical signatures left by protocol variations in nascent sequencing library generation. Next, I developed a modified pipeline for differential analysis when using trisomic libraries, which properly account for the trisomic condition and normalizes read counts accordingly. Finally, I utilized these new modified pipelines in an analysis of PRO- and RNA-seq libraries generated from a time series of interferon treatment in trisomic and disomic lymphoblastoid cell lines. I utilized this time series to develop a computational method to infer RNA degradation rates across time.
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