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Taking the Idiopathic out of Juvenil...

Tarbell, Evan David.

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Taking the Idiopathic out of Juvenile Idiopathic Arthritis.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Taking the Idiopathic out of Juvenile Idiopathic Arthritis./
Author:	Tarbell, Evan David.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	164 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
Contained By:	Dissertations Abstracts International80-09B.
Subject:	Genetics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13427217
ISBN:	9780438945210

Taking the Idiopathic out of Juvenile Idiopathic Arthritis.
Tarbell, Evan David.

Taking the Idiopathic out of Juvenile Idiopathic Arthritis. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 164 p.

Source: Dissertations Abstracts International, Volume: 80-09, Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2019.

This item must not be added to any third party search indexes.

Cis-regulatory elements (CRMs) are genomic regions that exert spatiotemporal control over gene expression patterns, which is critical to cell identity and function and whose disruption can lead to disease phenotypes. Juvenile Idiopathic Arthritis (JIA) is a complex disease characterized by aberrant gene expression profiles in numerous immune tissues. Identifying altered CRMs that disrupt expression is a critical step in understanding the pathogenesis of JIA. ATAC-seq is a genome wide method for identifying accessible chromatin regions, which are typically CRMs, which can be performed on small numbers of cells. The low starting material requirement is ideal for pediatric research, due to the difficulty in obtaining large numbers of cells in children. However, current data analysis still utilizes approaches originally designed for ChIP-seq or DNase-seq, without taking into account the transposase digested DNA fragments that contain additional nucleosome positioning information. Here we present a novel algorithm for analyzing ATAC-seq data, HMMRATAC, which integrates various chromatin features present within an ATAC-seq library to accurately identify accessible CRMs. We then apply ATAC-seq and HMMRATAC to the CD4+ T cells of JIA patients, along with other genomic and transcriptomic approaches, to understand what factors may be driving the gene expression differences that have been observed in JIA.

ISBN: 9780438945210Subjects--Topical Terms:

530508
Genetics.

Taking the Idiopathic out of Juvenile Idiopathic Arthritis.
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500 $a Source: Dissertations Abstracts International, Volume: 80-09, Section: B.
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500 $a Advisor: Liu, Tao;Jarvis, James.
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506 $a This item must not be sold to any third party vendors.
520 $a Cis-regulatory elements (CRMs) are genomic regions that exert spatiotemporal control over gene expression patterns, which is critical to cell identity and function and whose disruption can lead to disease phenotypes. Juvenile Idiopathic Arthritis (JIA) is a complex disease characterized by aberrant gene expression profiles in numerous immune tissues. Identifying altered CRMs that disrupt expression is a critical step in understanding the pathogenesis of JIA. ATAC-seq is a genome wide method for identifying accessible chromatin regions, which are typically CRMs, which can be performed on small numbers of cells. The low starting material requirement is ideal for pediatric research, due to the difficulty in obtaining large numbers of cells in children. However, current data analysis still utilizes approaches originally designed for ChIP-seq or DNase-seq, without taking into account the transposase digested DNA fragments that contain additional nucleosome positioning information. Here we present a novel algorithm for analyzing ATAC-seq data, HMMRATAC, which integrates various chromatin features present within an ATAC-seq library to accurately identify accessible CRMs. We then apply ATAC-seq and HMMRATAC to the CD4+ T cells of JIA patients, along with other genomic and transcriptomic approaches, to understand what factors may be driving the gene expression differences that have been observed in JIA.
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