人工智能识别改变基因表达的启动子变异

IF 29 1区 生物学 Q1 GENETICS & HEREDITY
Tiago Faial
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引用次数: 0

摘要

解释非编码遗传变异的功能后果仍然是基因组学领域的一个关键挑战,特别是在人类罕见疾病的背景下。为了帮助解决这个问题,Jaganathan等人报告了一种名为PromoterAI的深度神经网络的发展,该网络专门识别预计会影响基因表达的启动子变异。作者首先训练PromoterAI来预测dna酶过敏、转录因子结合、组蛋白修饰和单核苷酸分辨率的基因表达。然后,他们创建了一个训练数据集,该数据集由数千个与多种组织中异常基因表达相关的启动子变体组成。这是用来微调PromoterAI。研究人员使用了几种方法来验证PromoterAI的预测。首先,对等位基因频率数据的分析表明,PromoterAI所选择的变异在人群中被强烈地耗尽,这表明它们具有潜在的有害作用。对英国生物银行队列的分析强调了PromoterAI的预测与蛋白质丰度和数量性状之间的强烈相关性。最后,PromoterAI被用于研究来自英国基因组学队列的未确诊罕见疾病患者。启动子ai变异在孟德尔病基因的启动子中富集,这些基因与患者的表型相关。这在被认为具有显性功能丧失效应的基因中尤其明显。原始参考文献:Science 389, eads7373 (2025)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI identifies promoter variants that alter gene expression
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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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