Computational prediction of genetic systems in prokaryotes

原核生物遗传系统的计算预测

• 批准号: RGPIN-2018-06180
• 负责人: MorenoHagelsieb, Gabriel
• 金额: $ 2.62万
• 依托单位: Wilfrid Laurier University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745824
• 关键词: Computational; prediction; genetic; systems; prokaryotes

DNA sequencing constantly reveals vast numbers of genes that cannot be annotated with a function by their similarity to known genes (function by homology). These unknown genes seem to outnumber those that can be assigned a function. Predicting functional associations, such as those between genes whose products work in the same biochemical pathway, can help suggest functions to the products of orphan genes, and might also help refine functional annotations predicted by homology. The most reliable clue to functional associations in prokaryotes (Bacteria and Archaea) might be the prediction of operons, adjacent genes in the same DNA strand transcribed into a single messenger RNA. Functional associations between separated genes can be inferred from equivalent genes predicted to be in an operon in a different genome (operon rearrangements).The proposed research program focuses on three main objectives: (1) developing and testing strategies for organizing proteins into functional families; (2) improving and streamlining the prediction of operons and the transference of functional associations across genomes; (3) To study the evolution of genetic systems by following their associations and reassociations across genomes and metagenomes.Predicted functional associations can be organized into networks. The structure and properties of these networks can help identify probable false positives, and produce clusters of genes thus organized into potential functional groups. Gene products will be organized into protein families. In turn, these families will be organized into groups of functionally interacting families. Such organization might suggest later experimental examination of functions, and the prioritization of experimental work. Associations of uncommon genes to known functions, will help discover different ways in which life forms have solved similar problems. Unknown groups will also help discover different ways in which life has solved similar problems, or even lead to discovering novel biochemistries.Our results will be important for end users interested in finding novel genes involved in particular functions. For example, the work will point to novel genes associated with activities of environmental and industrial interest, such as groups of genes associated with cellulose degradation, useful in the biofuel industry; or with cellulose biosynthesis, useful in manufacturing of biodegradable items. The results will also impact the design of artificial biological systems. For example, we expect to find novel versions of existing functional modules, which would facilitate the selection of versions with predictable behaviours for biosystem engineering.

DNA测序不断地揭示了大量的基因，这些基因不能通过它们与已知基因的相似性来标注功能（功能通过同源性）。这些未知基因的数量似乎超过了那些被赋予某种功能的基因。预测功能关联，例如产物在同一生化途径中工作的基因之间的功能关联，可以帮助提示孤儿基因产物的功能，也可能有助于完善同源性预测的功能注释。在原核生物（细菌和古细菌）中，最可靠的功能关联线索可能是对操纵子的预测，操纵子是同一DNA链中转录成单个信使RNA的邻近基因。分离基因之间的功能关联可以从预测在不同基因组的操纵子中的等效基因推断出来（操纵子重排）。提出的研究计划侧重于三个主要目标：(1)开发和测试将蛋白质组织成功能家族的策略；(2)改进和简化操纵子的预测和跨基因组功能关联的转移；(3)通过追踪遗传系统在基因组和宏基因组间的关联和再关联来研究遗传系统的进化。预测的功能关联可以组织成网络。这些网络的结构和特性可以帮助识别可能的假阳性，并产生基因簇，从而组织成潜在的功能群。基因产物将被组织成蛋白质家族。反过来，这些家庭将被组织成功能相互作用的家庭群体。这样的组织可能建议以后对功能进行实验检查，并确定实验工作的优先次序。将不常见的基因与已知的功能联系起来，将有助于发现生命形式解决类似问题的不同方式。未知群体还将有助于发现生命解决类似问题的不同方式，甚至有助于发现新的生物化学。我们的结果将对有兴趣寻找涉及特定功能的新基因的最终用户很重要。例如，这项工作将指出与环境和工业利益活动相关的新基因，例如与纤维素降解相关的基因群，在生物燃料工业中有用；或者用纤维素生物合成，用于制造可生物降解的物品。研究结果也将影响人工生物系统的设计。例如，我们期望找到现有功能模块的新版本，这将有助于生物系统工程中具有可预测行为的版本的选择。