ABI: Development: Cloud-based Identification and Visualization of Lateral Gene Transfers in Genome Data

ABI：开发：基因组数据中横向基因转移的基于云的识别和可视化

• 批准号: 1457957
• 负责人: Julie Hotopp
• 金额: $ 70.53万
• 依托单位: University of Maryland at Baltimore
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1457957&HistoricalAwards=false
• 关键词: ABI; Development; Cloud; based; Identification

All genomes accumulate mutations that are both beneficial and detrimental to the organism. For example, mutations occur upon exposure to sun in the genome of skin cells that can ultimately lead to the development of skin cancer. Mutations range in size from single base pair alterations to massive insertions and deletions that can span over a million base pairs. The best understood mutations are those that involve alteration, insertion, or deletion of a single base pair, where there are numerous tools for identifying and validating such changes. Yet in many organisms, it is increasingly appreciated that large, even massive, insertions of DNA can occur from other organisms, termed lateral gene transfer, that have the potential to have a profound effect on the organism, either detrimental or beneficial. For example, large insertional mutations led to the transition of endosymbionts to organelles like mitochondria and chloroplasts. This project seeks to improve tools previously developed to identify such lateral gene transfers from genome sequencing data, and to make these tools available to the research community after ensuring that they are more robust and user friendly. The team has already used these tools to identify integration of bacterial DNA into numerous animal genomes, including into human somatic cell genomes of individuals with cancer, where such mutations may be oncogenic. Making the tools available to more scientists should increase the understanding of the occurrence and importance of such mutations in all organisms. In addition, this proposal seeks to develop YouTube whiteboard videos to educate the general public about these mutations, genomics, and the tools developed in this proposal. The first of these videos can be found at: https://www.youtube.com/watch?v=PZG4qjVjJ70.Lateral gene transfer (LGT, synonymous with horizontal gene transfer or HGT) is the movement of DNA between diverse organisms. It is one form of insertional mutagenesis and can be advantageous or deleterious. In bacteria, LGT has been implicated in antibiotic resistance, pathogenesis, and bioremediation. While the greatest focus has been on bacteria, it has become increasingly clear that it occurs in eukaryotes as well. For example, our research focuses on interdomain LGT between bacteria and Metazoans, which is increasingly described. This has led to the hypothesis that that LGT may have contributed more to the evolution of phenotypes in eukaryotes than previously assumed. However, there continue to be barriers to detecting LGT, particularly in Metazoan genomes. The goal of this project is to develop a bioinformatics resource in the form of a virtual machine to aid in the detection of LGT. This tool can be used to detect LGT between any suspected donor-recipient pair, including endosymbiont-host and organelle-host pairs as well as organelle-organelle, bacteria-bacteria, and viral-host, to name just a few. Such a tool could also be used by metagenomics researchers teasing apart LGT from assembly artifacts, geneticists trying to identify the integration site of a transposon following a selective screen, and for identification of integration sites for known mobile elements. Essentially, this tool can be used to detect the integration of novel DNA in any genome with some knowledge about the donor and/or recipient genome. Most sequence analysis tools have focused on SNPs or small insertions/deletions. The development of bioinformatics tools to detect larger insertions is an area that has been under-served and currently lacks robust bioinformatics tools. This proposal aims to meet those needs. Ongoing results of the project can be found at: http://lgt.igs.umaryland.edu/nsf_abi.

所有的基因组都会积累对生物体有利和有害的突变。例如，皮肤细胞基因组在暴露于阳光下时发生突变，最终可能导致皮肤癌的发展。突变的大小范围从单个碱基对的改变到可以跨越一百万个碱基对的大量插入和缺失。最好理解的突变是那些涉及单个碱基对的改变、插入或缺失的突变，其中有许多工具用于识别和验证这些变化。然而，在许多生物体中，越来越多的人认识到，大的，甚至是大量的DNA插入可以发生在其他生物体中，称为横向基因转移，这有可能对生物体产生深远的影响，无论是有害的还是有益的。例如，大的插入突变导致内共生体转变为线粒体和叶绿体等细胞器。该项目旨在改进以前开发的用于从基因组测序数据中识别此类横向基因转移的工具，并在确保这些工具更加强大和用户友好之后，将其提供给研究界。该团队已经使用这些工具来识别细菌DNA整合到许多动物基因组中，包括癌症患者的人体细胞基因组中，这些突变可能是致癌的。让更多的科学家使用这些工具应该会增加对所有生物体中此类突变的发生和重要性的理解。此外，该提案旨在开发YouTube白板视频，以教育公众了解这些突变，基因组学以及本提案中开发的工具。这些视频中的第一个可以在https://www.youtube.com/watch?上找到v= PZG 4 qjVjJ 70.横向基因转移（Lateral gene transfer，LGT）是DNA在不同生物体之间的转移。它是插入诱变的一种形式，可以是有利的，也可以是有害的。在细菌中，LGT与抗生素耐药性、发病机制和生物修复有关。虽然最大的焦点是细菌，但越来越清楚的是，它也发生在真核生物中。例如，我们的研究重点是细菌和后生动物之间的域间LGT，这是越来越多的描述。这导致了一种假设，即LGT可能比以前假设的对真核生物表型的进化贡献更大。然而，检测LGT仍然存在障碍，特别是在后生动物基因组中。该项目的目标是以虚拟机的形式开发生物信息学资源，以帮助检测LGT。该工具可用于检测任何疑似供体-受体对之间的LGT，包括内共生体-宿主和细胞器-宿主对以及细胞器-细胞器、细菌-细菌和病毒-宿主，仅举几例。这样的工具也可以被宏基因组学研究人员从组装工件中分离出LGT，遗传学家试图在选择性筛选后识别转座子的整合位点，以及识别已知移动的元件的整合位点。基本上，该工具可用于检测新DNA在任何基因组中的整合，具有关于供体和/或受体基因组的一些知识。大多数序列分析工具都集中在SNP或小的插入/缺失上。开发生物信息学工具来检测更大的插入是一个服务不足的领域，目前缺乏强大的生物信息学工具。本提案旨在满足这些需求。该项目的持续成果可在http://lgt.igs.umaryland.edu/nsf_abi上查阅。