Inferring the gene coevolution network from deep comparative genomics

从深度比较基因组学推断基因协同进化网络

• 批准号: 2241312
• 负责人: Gavin Conant
• 金额: $ 49.96万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241312&HistoricalAwards=false
• 关键词: Inferring; gene; coevolution; network; deep

It is not surprising that a missing or damaged gene can be detrimental to the organism possessing it. It is more surprising that having extra copies of genes can also be harmful, as is the case with Down syndrome, where an extra, undamaged, copy of chromosome 21 is responsible for the syndrome’s symptoms. Geneticists believe that these extra genes are harmful because they encode proteins that need to work in concert with the proteins made by genes on other chromosomes. If these interacting proteins are not present in the correct numbers relative to each other, they can disrupt cellular activities. Unfortunately, no simple experiments can identify all the pairs of genes that need to work in balance with each other. Curiously however, there are also cells that have entire extra copies of the genome in their cells, possessing not two but four or more copies. Despite the extra copies, these polyploid cells are healthy and can be found in many forms of life. In fact, over evolutionary time, several important groups of organisms, including the vertebrates and all flowering plants, have undergone such polyploidy events and transmitted the resulting extra genes to their descendants. Importantly though, not all of the extra (or duplicated) genes are kept. As a result, the patterns of gene loss and survival seen after a polyploidy can be used to identify the pairs of genes that have dosage interactions with each other. In other words, by studying evolution after polyploidy across many different genomes, it will be possible to identify the interactions driving effects like those of Down syndrome, and to shed light on gene interactions in general.This project will use evolutionary modeling software developed by the investigators to analyze duplicate gene loss and retention after more than a dozen independent polyploidies. The team will improve this tool by adding the capacity to model polyploidies that occurred “on top of” other polyploidies. Then, using more than 60 individual genomes, the investigators will infer a network of genes where the connections between those genes represent dosage interactions. In this framework, pairs of interacting genes will be those for which differences in copy number between the pair is evolutionarily costly. With the network in hand, the researchers will use existing large-scale datasets on physical interactions between proteins, regulatory connections between genes and other biochemical information to understand why certain pairs of genes need to be maintained in similar copy number in order to function correctly.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

缺失或受损的基因可能对拥有该基因的生物体不利，这并不奇怪，更令人惊讶的是，拥有额外的基因拷贝也可能有害，就像唐氏综合症的情况一样，其中一个额外的、未受损的基因拷贝。遗传学家认为，21 号染色体是造成这种综合征的原因，因为它们编码的蛋白质需要与其他染色体上的基因产生的蛋白质协同工作，如果这些相互作用的蛋白质的数量不正确。彼此之间，它们可以破坏细胞不幸的是，没有简单的实验可以识别所有需要相互平衡工作的基因对，但奇怪的是，也有一些细胞在其细胞中拥有完整的额外基因组拷贝，而不是两个，而是四个或更多。尽管有额外的拷贝，这些多倍体细胞是健康的，并且可以在许多生命形式中找到。事实上，在进化过程中，包括脊椎动物和所有开花植物在内的几个重要的生物体群体都经历了这种多倍体事件并传播。由此产生的额外基因但重要的是，并非所有额外（或重复）的基因都被保留，因此，多倍体后观察到的基因丢失和存活模式可用于识别彼此存在剂量相互作用的基因对。换句话说，通过研究许多不同基因组的多倍体后的进化，将有可能识别像唐氏综合症那样的相互作用驱动效应，并揭示一般的基因相互作用。该项目将使用由研究人员分析重复基因的丢失和保留在十多个独立的多倍体之后，该团队将通过添加对其他多倍体“之上”发生的多倍体进行建模的能力来改进该工具，然后，使用 60 多个单独的基因组，研究人员将推断出一个基因网络。在这个框架中，基因对之间的拷贝数差异在进化上是昂贵的，研究人员将使用现有的物理相互作用的大规模数据集。蛋白质之间，基因和其他生化信息之间的调控联系，以了解为什么某些基因对需要保持相似的拷贝数才能正常发挥作用。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和技术进行评估，被认为值得支持。更广泛的影响审查标准。

项目成果

POInTbrowse: orthology prediction and synteny exploration for paleopolyploid genomes

POInTbrowse：古多倍体基因组的同源预测和同线性探索

• DOI: 10.1186/s12859-023-05298-w
• 发表时间: 2023-04-27
• 期刊: BMC Bioinformatics
• 影响因子: 3
• 作者: Siddiqui, Mustafa;Conant, Gavin C.
• 通讯作者: Conant, Gavin C.

Interlocus Gene Conversion, Natural Selection, and Paralog Homogenization

位点间基因转换、自然选择和旁系同源同质化

• DOI: 10.1093/molbev/msad198
• 发表时间: 2023-09-01
• 期刊: Molecular Biology and Evolution
• 影响因子: 10.7
• 作者: Yang, Yixuan;Xu, Tanchumin;Conant, Gavin;Kishino, Hirohisa;Thorne, Jeffrey L.;Ji, Xiang
• 通讯作者: Ji, Xiang