权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Computational methods for detecting patterns of complex genomic variation

检测复杂基因组变异模式的计算方法

基本信息

批准号：
10543106
负责人：
Vineet Bafna
金额：
$ 30.1万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10543106
关键词：
Architecture Bioinformatics Biological Sciences Cataloging Cells Cervical Collaborations Complex Computing Methodologies Cytogenetics DNA Sequence Rearrangement Data Detection Development Directed Molecular Evolution Disease Disparate Elements Epigenetic Process Event Evolution Funding Gene Amplification Genetic Variation Genome Genomic Segment Grant Haplotypes Histologic Human Human Genome Human Papilloma Virus-Related Malignant Neoplasm Image Location Malignant Neoplasms Maps Mechanics Mediating Metaphase Nature Oncogenes Optics Pattern Play Publications Research Role Sampling Somatic Cell Source Structure Tandem Repeat Sequences Technology Transcript Variant Viral Viral Genome Virus Integration Work cancer diagnosis cancer subtypes chromothripsis computerized tools data integration detection method extrachromosomal DNA genomic signature genomic variation nanopore novel tool whole genome

项目摘要

Project Summary Structural variations (SVs) – involving changes in copy number, inversions, translocations, and other mechanisms– are an important source of genetic variation. They occur in the germ-line and also in so- matic cells, where they sometimes play an outsized role in diseases, cancer being a prominent example. Much work has been done in identifying and cataloging `simple' variants such as deletions, duplications, translocations, and others. In contrast, our continuing proposal is about `complex' structural variation, characterized by extensive structural changes involving multiple breakpoints and simple SV events. In previous research funded by the grant (17 publications), we developed and extended tools for identifying complex SVs including Breakage Fusion Bridge characterized by speciﬁc copy number patterns, detec- tion of chains of disparate genomic segments as deﬁned by Chromothripsis and Chromoplexy, and viral mediated rearrangements. Perhaps most relevant to the current proposal, is the problem of determining architecture and origin of focal ampliﬁcation of smaller (< 10Mb) genomic segments. Working with col- laborators, we observed an abundance of large circular, extrachromosomal DNA (Turner, Nature 2017), detecting them in 40% of all cancer samples across a multitude of histological subtypes. EcDNA are hot- spots for complex, even multi-chromosomal genomic rearrangements, and o↵er a mechanistic explanation of focal ampliﬁcations. These discoveries were supported by the devlopment of many computational tools: AmpliconArchitect (AA) for reconstructing the ﬁne structure of ecDNA using Illumina short-reads, ViFi for identifying complex variation due to viral integration in humans, and ecDetect for detection and quantiﬁcation of ecDNA in cytogenetic images acquired in metaphase. For this grant, we will (i) develop Amplicon Reconstructor (AR) as a tool for disambiguated AA reconstructed amplicons using long reads–Oxford Nanopore, Paciﬁc Biosciences, and Optical Nanopore technology; (ii) use AR to understand the evolution of complex structural variation thorugh directed evolution of ecDNA in the lab; and (iii), integrate data from thousands of whole genome sequences, transcript and other epigenetic data to elucidate the functional aspects of ecDNA elements.

项目摘要结构变异(SVS)--涉及拷贝数、倒位、易位等方面的变化机制--是遗传变异的重要来源。它们出现在生殖系中，也出现在- 马季奇细胞有时在疾病中扮演着非常重要的角色，癌症就是一个突出的例子。在识别和编目“简单”变体方面做了大量工作，如删除、重复、易位，以及其他。相比之下，我们继续提出的建议是关于“复杂的”结构变化，以涉及多个断点和简单SV事件的广泛结构变化为特征。在……里面在之前由赠款资助的研究(17篇出版物)中，我们开发和扩展了工具来确定包括断裂融合桥在内的复杂SVS，其特征是ﬁc拷贝数模式，检测- 不同的基因组节段链的连接，如由染色质和多染色质所致的deﬁNed，以及病毒调解的重排。也许与当前提案最相关的是确定较小(&lt；10Mb)基因组片段的焦点扩增ﬁ的结构和来源。与科尔合作- 实验室，我们观察到了大量的大的圆形，染色体外的DNA(Turner，自然，2017)，在许多组织亚型的所有癌症样本中检测到它们的40%。EcDNA很火爆- 斑点，复杂的，甚至多个染色体的基因组重排，和o↵er一个机械的解释焦点放大ﬁ阳离子。这些发现得到了许多计算工具的发展的支持：扩增结构(AA)，用于使用Illumina短读来重建ecDNA的ﬁNe结构， ViFi用于识别由于病毒整合而在人类体内产生的复杂变异，ecDetect用于检测中期细胞遗传学图像中ECDNA的定量ﬁ阳离子。对于这笔赠款，我们将：(I) 开发扩增子重构器(AR)作为使用LONG来消除AA重构扩增歧义的工具阅读-牛津纳米孔、Paciﬁc生物科学和光学纳米孔技术；(Ii)使用AR来理解通过实验室中ecDNA的定向进化来实现复杂结构变异的进化；以及(Iii)，整合来自数千个全基因组序列、转录本和其他表观遗传学数据的数据以阐明 EcDNA元件的功能方面。

项目成果

期刊论文数量（45）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

FaNDOM: Fast nested distance-based seeding of optical maps.

DOI：
10.1016/j.patter.2021.100248
发表时间：
2021-05-14
期刊：
Patterns (New York, N.Y.)
影响因子：
0
作者：
Raeisi Dehkordi S;Luebeck J;Bafna V
通讯作者：
Bafna V

HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies.

DOI：
10.1101/gr.213462.116
发表时间：
2017-05
期刊：
Genome research
影响因子：
7
作者：
Edge P;Bafna V;Bansal V
通讯作者：
Bansal V

FastViFi: Fast and accurate detection of (Hybrid) Viral DNA and RNA.

DOI：
10.1093/nargab/lqac032
发表时间：
2022-06
期刊：
NAR genomics and bioinformatics
影响因子：
4.6
作者：
通讯作者：

Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors.

含有 ecDNA 的肿瘤中双链 DNA 损伤和修复库的转录免疫抑制和上调。

DOI：
10.1101/2023.04.24.537925
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Lin,MiinS;Jo,Se-Young;Luebeck,Jens;Chang,HowardY;Wu,Sihan;Mischel,PaulS;Bafna,Vineet
通讯作者：
Bafna,Vineet

Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA.

DOI：
10.1038/s41586-022-04398-6
发表时间：
2022-03
期刊：
Nature
影响因子：
64.8
作者：
Bergstrom EN;Luebeck J;Petljak M;Khandekar A;Barnes M;Zhang T;Steele CD;Pillay N;Landi MT;Bafna V;Mischel PS;Harris RS;Alexandrov LB
通讯作者：
Alexandrov LB