Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Jove-Journal of Visualized Experiments Pub Date : 2025-01-10 DOI:10.3791/67552
Dongyang Xu, Lu Tang, Philipp Kapranov
{"title":"Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library.","authors":"Dongyang Xu, Lu Tang, Philipp Kapranov","doi":"10.3791/67552","DOIUrl":null,"url":null,"abstract":"<p><p>The extent of functional sequences within the human genome is a pivotal yet debated topic in biology. Although high-throughput reverse genetic screens have made strides in exploring this, they often limit their scope to known genomic elements and may introduce non-specific effects. This underscores the urgent need for novel functional genomics tools that enable a deeper, unbiased understanding of genome functionality. This protocol introduces the Insertion-based Screen for functional Elements and Transcripts (InSET), a method for identifying lentivirus integration sites within a lentivirus-based insertional mutagenesis cell library. InSET facilitates the capture of genome-wide lentiviral integration sites, with next-generation sequencing used to detect and quantify flanking sequences. InSET's design enables the analysis of integration site abundance variations in phenotypic screens on a large scale, establishing it as a robust tool for forward genetics and for identifying functional genomic elements. A key benefit of InSET is its capacity to reveal previously unidentified genomic elements, including novel functional exons of both protein-coding and non-coding RNAs, independent of prior annotation. Overall, InSET holds significant value in studying the intricate complexity of the human genome and transcriptome, where many genomic elements await functional characterization.</p>","PeriodicalId":48787,"journal":{"name":"Jove-Journal of Visualized Experiments","volume":" 215","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jove-Journal of Visualized Experiments","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.3791/67552","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The extent of functional sequences within the human genome is a pivotal yet debated topic in biology. Although high-throughput reverse genetic screens have made strides in exploring this, they often limit their scope to known genomic elements and may introduce non-specific effects. This underscores the urgent need for novel functional genomics tools that enable a deeper, unbiased understanding of genome functionality. This protocol introduces the Insertion-based Screen for functional Elements and Transcripts (InSET), a method for identifying lentivirus integration sites within a lentivirus-based insertional mutagenesis cell library. InSET facilitates the capture of genome-wide lentiviral integration sites, with next-generation sequencing used to detect and quantify flanking sequences. InSET's design enables the analysis of integration site abundance variations in phenotypic screens on a large scale, establishing it as a robust tool for forward genetics and for identifying functional genomic elements. A key benefit of InSET is its capacity to reveal previously unidentified genomic elements, including novel functional exons of both protein-coding and non-coding RNAs, independent of prior annotation. Overall, InSET holds significant value in studying the intricate complexity of the human genome and transcriptome, where many genomic elements await functional characterization.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
插入诱变细胞文库中慢病毒功能相关整合位点的鉴定。
人类基因组中功能序列的范围是生物学中一个关键但有争议的话题。尽管高通量反向基因筛选在探索这方面取得了长足的进步,但它们往往将其范围限制在已知的基因组元件上,并可能引入非特异性效应。这强调了迫切需要新的功能基因组学工具,使更深入,公正的理解基因组功能。本协议引入了基于插入的功能元件和转录本筛选(InSET),这是一种在慢病毒插入突变细胞文库中识别慢病毒整合位点的方法。InSET有助于捕获全基因组慢病毒整合位点,下一代测序用于检测和量化侧翼序列。InSET的设计能够大规模地分析表型筛选中的整合位点丰度变化,使其成为向前遗传学和识别功能基因组元件的强大工具。InSET的一个主要优点是它能够揭示以前未识别的基因组元件,包括蛋白质编码rna和非编码rna的新功能外显子,而不依赖于先前的注释。总的来说,InSET在研究人类基因组和转录组的复杂复杂性方面具有重要价值,其中许多基因组元件等待功能表征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
期刊最新文献
Erratum: Flow Cytometry Analysis of Tissue Factor Expression in Human Platelets. Comparative In Vitro Staphylococcus aureus Biofilm Evaluation on 3D-Printed Polylactic Acid and Polyethylene Terephthalate Glycol-modified Surfaces. Capacity Planning of Wind-PV-Thermal-Storage Energy Bases Considering Intraday Adjustment Costs via Nested Generalized Benders Decomposition. An End-to-end Deep Learning Framework for Automated Woven Fabric Pattern Recognition using UNet, GAN, and CNN. Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1