Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.
Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.
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用于精准医学的功能增益变异组学和多组学网络生物学。
DOI：
10.1007/978-1-0716-3163-8_24
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Yi,SStephen
中科院分区：
文献类型：
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作者：
Li,MarkM;Awasthi,Sharad;Ghosh,Sumanta;Bisht,Deepa;CobanAkdemir,ZeynepH;Sheynkman,GloriaM;Sahni,Nidhi;Yi,SStephen
传统上，疾病原因突变被认为会扰乱基因功能。然而，越来越清楚的是，许多有害的突变可能会表现出“功能获得”(GOF)行为。对这种突变的系统研究一直缺乏，而且在很大程度上被忽视了。下一代测序的进展已经确定了数千种扰乱蛋白质正常功能的基因组变异，进一步导致了疾病中不同的表型后果。阐明由GOF突变重新连接的功能通路对于确定致病变体及其由此产生的治疗责任的优先顺序至关重要。在不同的细胞类型(具有不同的基因类型)中，精确的信号转导控制细胞的决定，包括基因调节和表型输出。当信号转导因GOF突变而出错时，就会产生各种疾病类型。对GOF突变引起的网络扰动的定量和分子理解可能为以前的全基因组关联研究中的“缺失遗传性”提供解释。我们预见，这将有助于推动当前的范式，以彻底的功能和量化的模型，所有的GOF突变及其与疾病发展和进展有关的机械性分子事件。许多与基因型-表型关系有关的基本问题仍未得到解决。例如，哪些GOF突变是基因调控和细胞决策的关键？不同监管级别的GOF机制是什么？相互作用网络如何在GOF突变后重新连接？有没有可能利用GOF突变来重新编程细胞中的信号转导，目的是治愈疾病？为了开始解决这些问题，我们将涵盖关于GOF疾病突变及其多组网络特征的广泛主题。我们强调了GOF突变的基本功能，并在信号网络的背景下讨论了潜在的机制效应。我们还讨论了生物信息学和计算资源方面的进展，这将极大地帮助研究GOF突变的功能和表型后果。
Traditionally, disease causal mutations were thought to disrupt gene function. However, it becomes more clear that many deleterious mutations could exhibit a “gain-of-function” (GOF) behavior. Systematic investigation of such mutations has been lacking and largely overlooked. Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in disease. Elucidating the functional pathways rewired by GOF mutations will be crucial for prioritizing disease-causing variants and their resultant therapeutic liabilities. In distinct cell types (with varying genotypes), precise signal transduction controls cell decision, including gene regulation and phenotypic output. When signal transduction goes awry due to GOF mutations, it would give rise to various disease types. Quantitative and molecular understanding of network perturbations by GOF mutations may provide explanations for ‘missing heritability” in previous genome-wide association studies. We envision that it will be instrumental to push current paradigm toward a thorough functional and quantitative modeling of all GOF mutations and their mechanistic molecular events involved in disease development and progression. Many fundamental questions pertaining to genotype–phenotype relationships remain unresolved. For example, which GOF mutations are key for gene regulation and cellular decisions? What are the GOF mechanisms at various regulation levels? How do interaction networks undergo rewiring upon GOF mutations? Is it possible to leverage GOF mutations to reprogram signal transduction in cells, aiming to cure disease? To begin to address these questions, we will cover a wide range of topics regarding GOF disease mutations and their characterization by multi-omic networks. We highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also discuss advances in bioinformatic and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of GOF mutations.