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人类增强子的诱变敏感性图谱

Mutagenesis Sensitivity Mapping of Human Enhancers .

作者信息

Kosicki Michael, Zhang Boyang, Pampari Anusri, Akiyama Jennifer A, Plajzer-Frick Ingrid, Novak Catherine S, Tran Stella, Zhu Yiwen, Kato Momoe, Hunter Riana D, von Maydell Kianna, Barton Sarah, Beckman Erik, Kundaje Anshul, Dickel Diane E, Visel Axel, Pennacchio Len A

机构信息

Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA.

Department of Genetics, Stanford University, Stanford, CA, USA.

出版信息

bioRxiv. 2024 Sep 8:2024.09.06.611737. doi: 10.1101/2024.09.06.611737.

Abstract

Distant-acting enhancers are central to human development. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease. Here, we determined the functional sensitivity to mutagenesis of human developmental enhancers . Focusing on seven enhancers active in the developing brain, heart, limb and face, we created over 1700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-basepair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modeling, we annotated critical nucleotides at base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes to function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features required for their normal function and provide a rich resource for further exploration of human enhancer logic.

摘要

远距离作用增强子对人类发育至关重要。然而,我们对其功能序列特征的有限了解阻碍了对疾病中增强子突变的解读。在此,我们确定了人类发育增强子对诱变的功能敏感性。聚焦于在发育中的脑、心脏、肢体和面部活跃的七个增强子,我们为超过260个诱变的增强子等位基因创建了1700多只转基因小鼠。对12个碱基对的片段进行系统性突变,使得每个增强子中的每个序列特征至少被改变一次。我们发现,所有片段中有69%是正常活性所必需的,突变导致功能丧失(60%)比功能获得(9%)更为常见。通过预测建模,我们在碱基对分辨率下注释了关键核苷酸。这些机器学习模型预测的绝大多数基序(88%)与功能变化一致,并且模型显示出相当高的敏感性,识别出了所有功能片段中的59%。综合来看,我们的结果表明人类增强子包含大量正常功能所需的序列特征,并为进一步探索人类增强子逻辑提供了丰富资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9547/11398460/320eca66549a/nihpp-2024.09.06.611737v1-f0001.jpg

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