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空间飞行微重力下 基因转录的网络分析。

Network Analysis of Gene Transcriptions of in Spaceflight Microgravity.

机构信息

Department of Electrical and Computer Engineering, University of Puerto Rico, Mayaguez, PR 00681-9000, USA.

Department of Bioengineering, University of Puerto Rico, Mayaguez, PR 00681-9000, USA.

出版信息

Genes (Basel). 2021 Feb 25;12(3):337. doi: 10.3390/genes12030337.

Abstract

The transcriptomic datasets of the plant model organism grown in the International Space Station provided by GeneLab have been mined to isolate the impact of spaceflight microgravity on gene expressions related to root growth. A set of computational tools is used to identify the hub genes that respond differently in spaceflight with controlled lighting compared to on the ground. These computational tools based on graph-theoretic approaches are used to infer gene regulatory networks from the transcriptomic datasets. The three main algorithms used for network analyses are LASSO, Pearson correlation, and the HITS algorithm. Graph-based spectral analyses reveal distinct properties of the spaceflight microgravity networks for the WS, Col-0, and mutant ecotypes. The set of hub genes that are significantly altered in spaceflight microgravity are mainly involved in cell wall synthesis, protein transport, response to auxin, stress responses, and catabolic processes. Network analysis highlights five important root growth-regulating hub genes that have the highest outdegree distribution in spaceflight microgravity networks. These concerned genes coding for proteins are identified from the Gene Regulatory Networks (GRNs) corresponding to spaceflight total light environment. Furthermore, network analysis uncovers genes that encode nucleotide-diphospho-sugar interconversion enzymes that have higher transcriptional regulation in spaceflight microgravity and are involved in cell wall biosynthesis.

摘要

利用 GeneLab 提供的在国际空间站种植的植物模式生物 的转录组数据集,挖掘了太空微重力对与根生长相关的基因表达的影响。使用一组计算工具来识别在受控光照下的空间飞行与地面相比反应不同的枢纽基因。这些基于图论方法的计算工具用于从转录组数据集中推断基因调控网络。用于网络分析的三个主要算法是 LASSO、Pearson 相关和 HITS 算法。基于图的谱分析揭示了 WS、Col-0 和突变体生态型的空间微重力网络的独特性质。在空间微重力中显著改变的枢纽基因集主要参与细胞壁合成、蛋白质运输、对生长素的反应、应激反应和分解代谢过程。网络分析突出了五个在空间微重力网络中具有最高出度分布的重要根生长调节枢纽基因。这些与编码蛋白质的基因是从对应于空间飞行总光照环境的基因调控网络 (GRN) 中鉴定出来的。此外,网络分析揭示了编码核苷酸二磷酸糖转化酶的基因,这些基因在空间微重力中具有更高的转录调控,并且参与细胞壁生物合成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cba7/7996555/2124785dda4f/genes-12-00337-g001.jpg

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