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HKLE-seq: an enrichment method for unbiased amplification and next-generation sequencing of all HERV-K and SVA (HKLE) insertion breakpoints genome-wide in human DNA samples

HKLE-seq: an enrichment method for unbiased amplification and next-generation sequencing of all HERV-K and SVA (HKLE) insertion breakpoints genome-wide in human DNA samples
HKLE-seq:一种富集方法,用于人类 DNA 样本中全基因组所有 HERV-K 和 SVA (HKLE) 插入断点的无偏扩增和新一代测序
批准号:
9442151
负责人:
So Young Ryu
金额:
$43.03万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-02-01 至 2021-01-31

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中文摘要
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英文摘要
In this proposal we seek to design an efficient tool for large-scale investigation of an understudied genetic feature. HERV-K and SVA elements (HKLEs), which both contain a HERV-K long terminal repeat, are insertionally polymorphic, act as promoters and enhancers, and alter genome structure and epigenetics. As such, HKLEs have demonstrable effects on the function of the surrounding genome, primarily through altering cis-gene expression. These effects suggest HKLEs may contribute to the germ-line causes and somatic progression of disease. Indeed, our preliminary studies suggest that these elements are associated with multiple sclerosis and glioblastoma, additionally HKLEs have been shown to be overexpressed in a variety of complex diseases including our study of childhood acute lymphoblastic leukemia. Currently, the most effective method to measure these important genomic features is via whole genome sequencing, which is prohibitively expensive and computationally burdensome. Previous methods to enrich sequencing data for insertion breakpoints are subject to sacrifices of specificity, PCR bias, and sequence errors. We propose to develop a method, HKLE-seq, that will harness the efficiency of target enrichment methods while incorporating features that reduce error and bias. Upon development, this method will be applied to future large-scale planned studies of multiple sclerosis, glioblastoma, and childhood acute lymphoblastic leukemia. Furthermore, HKLE-seq will be available for use by researchers conducting clinical and epidemiological studies worldwide.
期刊论文(1)
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会议论文
Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD.
使用 MetaMSD 整合多种定量蛋白质组分析。
DOI: 10.1007/978-1-0716-1967-4_16
发表时间: 2023
期刊: Methods in molecular biology (Clifton, N.J.)
影响因子: --
作者: [Ryu,SoYoung, Yun,MiriamP, Kim,Sujung]
通讯作者: Kim,Sujung
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