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使用网络方法探索原生生物细胞群体内的生物相互作用。

Exploring biotic interactions within protist cell populations using network methods.

作者信息

Cheng Shu, Price Dana C, Karkar Slim, Bhattacharya Debashish

机构信息

Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, New Jersey, 08901, USA.

出版信息

J Eukaryot Microbiol. 2014 Jul-Aug;61(4):399-403. doi: 10.1111/jeu.12113. Epub 2014 May 16.

Abstract

The study of diseased human cells and of cells isolated from the natural environment will likely be revolutionized by single cell genomics (SCG). Here, we used protein similarity networks to explore within- and between-cell DNA differences from SCG data derived from six individual rhizarian cells related to Paulinella ovalis and proteins from the complete genome of another rhizarian, Bigelowiella natans. We identified shared and distinct DNA components within our SCG data and between P. ovalis and B. natans. We show that network properties such as assortativity and degree effectively discriminate genome features between SCG assemblies and that SCG data follow the power law with a small number of protein families dominating networks.

摘要

对患病人类细胞以及从自然环境中分离出的细胞的研究可能会因单细胞基因组学(SCG)而发生变革。在此,我们使用蛋白质相似性网络,从与卵形保罗虫相关的六个根足虫单细胞的SCG数据以及另一种根足虫——纳氏比吉洛虫的全基因组蛋白质中,探索细胞内和细胞间的DNA差异。我们在SCG数据内部以及卵形保罗虫和纳氏比吉洛虫之间识别出了共享和独特的DNA成分。我们表明,诸如 assortativity 和 degree 等网络属性能够有效区分SCG组装之间的基因组特征,并且SCG数据遵循幂律,少数蛋白质家族主导着网络。

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