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Inferring the gene coevolution network from deep comparative genomics

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
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-01-01 至 2026-12-31

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中文摘要
翻译
一个缺失或受损的基因会对拥有它的生物体有害,这并不奇怪。更令人惊讶的是,拥有额外的基因拷贝也可能是有害的,就像唐氏综合症的情况一样,21号染色体的一个额外的、未受损的拷贝是导致综合症症状的原因。遗传学家认为,这些额外的基因是有害的,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相对于彼此的数量不正确,它们可能会破坏细胞活动。不幸的是,没有简单的实验可以确定所有需要相互平衡工作的基因对。然而,奇怪的是,也有细胞在其细胞中拥有完整的额外基因组拷贝,拥有不是两个而是四个或更多个拷贝。尽管有额外的拷贝,这些多倍体细胞是健康的,可以在许多形式的生命中找到。事实上,在进化过程中,几个重要的生物群体,包括脊椎动物和所有开花植物,都经历了这样的多倍性事件,并将由此产生的额外基因传递给它们的后代。但重要的是,并非所有额外的(或重复的)基因都被保留下来。因此,在多倍体之后看到的基因丢失和存活的模式可以用于识别彼此具有剂量相互作用的基因对。也就是说,通过研究多个不同基因组的多倍化后的进化,就可以确定像唐氏综合症那样的相互作用,从而揭示基因间的相互作用。本项目将使用研究人员开发的进化建模软件,分析十多个独立多倍化后重复基因的丢失和保留。该团队将通过增加对发生在其他多倍体之上的多倍体建模的能力来改进这个工具。然后,使用60多个个体基因组,研究人员将推断出一个基因网络,其中这些基因之间的连接代表剂量相互作用。在这个框架中,相互作用的基因对将是那些对之间的拷贝数差异在进化上是昂贵的。有了这个网络,研究人员将利用现有的关于蛋白质之间物理相互作用的大规模数据集,基因和其他生物化学信息之间的调控联系,以了解为什么某些基因对需要保持在相似的拷贝数,以正确发挥作用。这个奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的智力价值和更广泛的支持影响审查标准。
英文摘要
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.
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