Stiens Jennifer, Tan Yen Yi, Joyce Rosanna, Arnvig Kristine B, Kendall Sharon L, Nobeli Irene
Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK.
Division of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Mol Microbiol. 2023 Apr;119(4):381-400. doi: 10.1111/mmi.15055. Epub 2023 Mar 27.
A whole genome co-expression network was created using Mycobacterium tuberculosis transcriptomic data from publicly available RNA-sequencing experiments covering a wide variety of experimental conditions. The network includes expressed regions with no formal annotation, including putative short RNAs and untranslated regions of expressed transcripts, along with the protein-coding genes. These unannotated expressed transcripts were among the best-connected members of the module sub-networks, making up more than half of the 'hub' elements in modules that include protein-coding genes known to be part of regulatory systems involved in stress response and host adaptation. This data set provides a valuable resource for investigating the role of non-coding RNA, and conserved hypothetical proteins, in transcriptomic remodelling. Based on their connections to genes with known functional groupings and correlations with replicated host conditions, predicted expressed transcripts can be screened as suitable candidates for further experimental validation.
利用来自公开可用的RNA测序实验的结核分枝杆菌转录组数据创建了一个全基因组共表达网络，这些实验涵盖了各种各样的实验条件。该网络包括没有正式注释的表达区域，包括推定的短RNA和表达转录本的非翻译区域，以及蛋白质编码基因。这些未注释的表达转录本是模块子网中连接性最好的成员之一，在包含已知参与应激反应和宿主适应的调节系统的蛋白质编码基因的模块中，构成了超过一半的“枢纽”元件。该数据集为研究非编码RNA和保守的假设蛋白质在转录组重塑中的作用提供了宝贵资源。基于它们与具有已知功能分组的基因的连接以及与复制的宿主条件的相关性，可以筛选预测的表达转录本作为进一步实验验证的合适候选者。
