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鱼类进化发育生物学:迈向物种特异性和基于知识的相互作用组学

Fish Evo-Devo: Moving Toward Species-Specific and Knowledge-Based Interactome.

作者信息

Ahi Ehsan Pashay

机构信息

Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland.

出版信息

J Exp Zool B Mol Dev Evol. 2025 May;344(3):158-168. doi: 10.1002/jez.b.23287. Epub 2025 Jan 27.

DOI:10.1002/jez.b.23287
PMID:40170296
Abstract

A knowledge-based interactome maps interactions among proteins and molecules within a cell using experimental data, computational predictions, and literature mining. These interactomes are vital for understanding cellular functions, pathways, and the evolutionary conservation of protein interactions. They reveal how interactions regulate growth, differentiation, and development. Transitioning to functionally validated interactomes is crucial in evolutionary developmental biology (Evo-Devo), especially for non-model species, to uncover unique regulatory networks, evolutionary novelties, and reliable gene interaction models. This enhances our understanding of complex trait evolution across species. The European Evo-Devo 2024 conference in Helsinki hosted the first fish-specific Evo-Devo symposium, highlighting the growing interest in fish models. Advances in genome annotation, genome editing, imaging, and molecular screening are expanding fish Evo-Devo research. High-throughput molecular data have enabled the deduction of gene regulatory networks. The next steps involve creating species-specific interactomes, validating them functionally, and integrating additional molecular data to deepen the understanding of complex regulatory interactions in fish Evo-Devo. This short review aims to address the logical steps for this transition, as well as the necessities and limitations of this journey.

摘要

基于知识的相互作用组利用实验数据、计算预测和文献挖掘来绘制细胞内蛋白质和分子之间的相互作用。这些相互作用组对于理解细胞功能、信号通路以及蛋白质相互作用的进化保守性至关重要。它们揭示了相互作用如何调节生长、分化和发育。在进化发育生物学(Evo-Devo)中,尤其是对于非模式物种而言,向经过功能验证的相互作用组转变对于揭示独特的调控网络、进化新奇性和可靠的基因相互作用模型至关重要。这增强了我们对跨物种复杂性状进化的理解。在赫尔辛基举行的2024年欧洲Evo-Devo会议举办了首届鱼类特异性Evo-Devo研讨会,凸显了对鱼类模型日益增长的兴趣。基因组注释、基因组编辑、成像和分子筛选方面的进展正在扩展鱼类Evo-Devo研究。高通量分子数据使得基因调控网络的推导成为可能。接下来的步骤包括创建物种特异性的相互作用组,对其进行功能验证,并整合更多分子数据,以加深对鱼类Evo-Devo中复杂调控相互作用的理解。这篇简短的综述旨在阐述这一转变的逻辑步骤,以及这一过程中的必要性和局限性。

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