2022年7月11日，美国加州大学洛杉矶分校Frank Alber团队在《自然—方法学》杂志发表论文。该研究通过整合基因组建模平台揭示3D基因组组织中罕见接触事件的重要性。

研究人员开发了一种多模态数据整合方法，用于产生单细胞基因组结构的群体，该群体对基因和核体的核位置、局部染色质压实和功能相关的染色质的空间分离具有高度预测性。研究人员证明，多模态数据整合可以补偿一些数据的系统误差，并能极大地提高基因组结构模型的准确性和覆盖率。

研究人员还表明，不同正交数据源的替代组合可以汇聚到具有类似预测能力的模型。此外，这项研究揭示了低频（"罕见"）染色体间接触对准确预测全局性核结构的关键贡献，包括基因和染色体的定位。总的来说，这些结果突出了多模式数据整合对基因组结构分析的好处，并可通过整合基因组建模软件包获得。

据悉，众多基于测序的技术和显微镜技术为揭示基因组的三维组织，和基因组功能的关键调节过程之间的关系提供了手段。

附：英文原文

Title: Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations

Author: Boninsegna, Lorenzo, Yildirim, Asli, Polles, Guido, Zhan, Yuxiang, Quinodoz, Sofia A., Finn, Elizabeth H., Guttman, Mitchell, Zhou, Xianghong Jasmine, Alber, Frank

Issue&Volume: 2022-07-11

Abstract: A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.

DOI: 10.1038/s41592-022-01527-x

Source: https://www.nature.com/articles/s41592-022-01527-x