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

所有的基因组都积累了对有机体既有利又有害的突变。例如，皮肤细胞基因组在暴露在阳光下时会发生突变，最终可能导致皮肤癌的发展。突变的大小从单碱基对的改变到跨越100多万个碱基对的大规模插入和缺失。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，其中有许多工具可以识别和验证这些变化。然而，在许多生物体中，人们越来越认识到，大量甚至大量的DNA插入可以从其他生物体发生，称为侧向基因转移，这可能会对生物体产生深远的影响，无论是有害的还是有益的。例如，较大的插入突变导致内共生体向线粒体和叶绿体等细胞器过渡。该项目旨在改进以前开发的从基因组测序数据中识别这种横向基因转移的工具，并在确保这些工具更强大和用户友好之后，使这些工具可供研究界使用。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，包括整合到癌症患者的人类体细胞基因组中，其中这种突变可能是致癌的。将这些工具提供给更多的科学家应该会增加对这种突变在所有生物体中的发生和重要性的理解。此外，该提案寻求开发YouTube白板视频，以教育普通公众了解这些突变、基因组学以及在该提案中开发的工具。这些视频中的第一个可以在：https://www.youtube.com/watch?v=PZG4qjVjJ70.Lateral基因转移(lgt，同义词为水平基因转移或hgt)是DNA在不同生物体之间的移动。它是插入突变的一种形式，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。虽然最大的关注点是细菌，但越来越清楚的是，它也存在于真核生物中。例如，我们的研究集中在细菌和后生动物之间的域间LGT，这一点越来越多地被描述。这导致了一种假设，即LGT对真核生物表型进化的贡献可能比之前假设的更大。然而，检测LGT仍然存在障碍，特别是在后生动物基因组中。该项目的目标是开发一种以虚拟机形式的生物信息学资源，以帮助检测LGT。该工具可用于检测任何可疑的供受者对之间的LGT，包括内共生菌-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。这样的工具也可以用于元基因组学研究人员梳理LGT与组装人工制品，遗传学家试图在选择性筛选后确定转座子的整合位点，并用于鉴定已知移动元件的整合位点。从本质上讲，这个工具可以用来检测对供体和/或受体基因组有一定了解的任何基因组中新的DNA的整合。大多数序列分析工具都专注于SNP或小的插入/缺失。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。这项提议旨在满足这些需求。该项目正在进行的成果可在以下网址查阅：http://lgt.igs.umaryland.edu/nsf_abi.

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.