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通过数据整合解析黑腹果蝇的三维基因组组织

The three-dimensional genome organization of Drosophila melanogaster through data integration.

作者信息

Li Qingjiao, Tjong Harianto, Li Xiao, Gong Ke, Zhou Xianghong Jasmine, Chiolo Irene, Alber Frank

机构信息

Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, 1050 Childs Way, Los Angeles, CA, 90089, USA.

Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA.

出版信息

Genome Biol. 2017 Jul 31;18(1):145. doi: 10.1186/s13059-017-1264-5.

Abstract

BACKGROUND

Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome's organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments.

RESULTS

Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data.

CONCLUSIONS

Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.

摘要

背景

在高等真核生物的细胞核中,基因组结构是动态且非随机组织的。为了使三维基因组结构模型的准确性和覆盖范围最大化,整合所有关于基因组组织的可用实验信息来源非常重要。整合来自各种互补实验方法的数据仍然是一项重大挑战。在这里,我们提出一种数据整合方法,以确定一组完整的三维基因组结构,这些结构在统计上与全基因组染色体构象捕获(Hi-C)和核纤层-DamID实验的数据一致。

结果

我们的结构以拓扑结构域的分辨率解析基因组,并同时重现两组实验数据。重要的是,这种数据反卷积框架允许细胞之间的结构异质性,因此考虑了基因组结构预期的可塑性。作为一个案例研究,我们选择了黑腹果蝇胚胎细胞,这两种数据类型都可获得。我们的三维基因组结构对初始数据集中不可直接看到的结构特征具有很强的预测能力,并从独立的和我们自己的成像实验中重现了黑腹果蝇基因组组织的实验特征。它们还揭示了关于基因组组织及其功能相关性的一些新见解,包括不同染色体异染色质卫星的首选位置,以及在原始Hi-C或核纤层-DamID数据中无法直接观察到的同源配对观察结果。

结论

我们的方法允许系统地整合Hi-C和核纤层-DamID数据以进行完整的三维基因组结构计算,同时还明确考虑了基因组结构的变异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9501/5576134/2d4b90fd51ec/13059_2017_1264_Fig1_HTML.jpg

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