小柯机器人

美国纽约大学格罗斯曼医学院Aristotelis Tsirigos和Bo Xia团队合作的最新研究，利用计算机程序对细胞类型特异性3D染色质结构进行高通量筛选和预测。相关论文于2023年1月9日发表在《自然—生物技术》杂志上。

研究人员研发了C.Origami，这是一种多模态深度神经网络，它使用DNA序列和两种细胞类型特异性基因组特征（CTCF结合和染色质可及性）对细胞类型特异性染色质组织进行从头预测。C.Origami使计算机实验能够检索遗传变化对染色质相互作用的影响。研究人员进一步开发了一种计算机遗传筛选方法，以评估单个DNA元件如何促进染色质组织，并确定共同决定染色质结构的假定细胞类型特异性反式作用调节因子。将这种方法应用于白血病细胞和正常T细胞，研究证明由C.Origami计算机遗传筛检索到的细胞类型特异性特征，可用于系统地发现正常和疾病相关生物系统中的新型染色质调节回路。

据介绍，研究染色质结构如何决定细胞类型特异性基因表达仍然具有挑战性。测量三维染色质组织的实验方法（如Hi-C）成本高且具有技术局限性，限制了它们的广泛应用，特别是在高通量遗传筛选中。

附：英文原文

Title: Cell-type-specific prediction of 3D chromatin organization enables high-throughput in silico genetic screening

Author: Tan, Jimin, Shenker-Tauris, Nina, Rodriguez-Hernaez, Javier, Wang, Eric, Sakellaropoulos, Theodore, Boccalatte, Francesco, Thandapani, Palaniraja, Skok, Jane, Aifantis, Iannis, Feny, David, Xia, Bo, Tsirigos, Aristotelis

Issue&Volume: 2023-01-09

Abstract: Investigating how chromatin organization determines cell-type-specific gene expression remains challenging. Experimental methods for measuring three-dimensional chromatin organization, such as Hi-C, are costly and have technical limitations, restricting their broad application particularly in high-throughput genetic perturbations. We present C.Origami, a multimodal deep neural network that performs de novo prediction of cell-type-specific chromatin organization using DNA sequence and two cell-type-specific genomic features—CTCF binding and chromatin accessibility. C.Origami enables in silico experiments to examine the impact of genetic changes on chromatin interactions. We further developed an in silico genetic screening approach to assess how individual DNA elements may contribute to chromatin organization and to identify putative cell-type-specific trans-acting regulators that collectively determine chromatin architecture. Applying this approach to leukemia cells and normal T cells, we demonstrate that cell-type-specific in silico genetic screening, enabled by C.Origami, can be used to systematically discover novel chromatin regulation circuits in both normal and disease-related biological systems.

DOI: 10.1038/s41587-022-01612-8

Source: https://www.nature.com/articles/s41587-022-01612-8

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex