Stiens Jennifer, Arnvig Kristine B, Kendall Sharon L, Nobeli Irene
Institute of Structural and Molecular Biology, Biological Sciences, Birkbeck, University of London, London, UK.
Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK.
Mol Microbiol. 2022 Jan;117(1):20-31. doi: 10.1111/mmi.14862. Epub 2021 Dec 27.
A definitive transcriptome atlas for the non-coding expressed elements of the members of the Mycobacterium tuberculosis complex (MTBC) does not exist. Incomplete lists of non-coding transcripts can be obtained for some of the reference genomes (e.g., M. tuberculosis H37Rv) but to what extent these transcripts have homologues in closely related species or even strains is not clear. This has implications for the analysis of transcriptomic data; non-coding parts of the transcriptome are often ignored in the absence of formal, reliable annotation. Here, we review the state of our knowledge of non-coding RNAs in pathogenic mycobacteria, emphasizing the disparities in the information included in commonly used databases. We then proceed to review ways of combining computational solutions for predicting the non-coding transcriptome with experiments that can help refine and confirm these predictions.
目前尚不存在针对结核分枝杆菌复合群（MTBC）成员非编码表达元件的完整转录组图谱。对于某些参考基因组（如结核分枝杆菌H37Rv），可以获取不完整的非编码转录本列表，但这些转录本在密切相关物种甚至菌株中的同源程度尚不清楚。这对转录组数据分析具有影响；在缺乏正式、可靠注释的情况下，转录组的非编码部分常常被忽略。在这里，我们回顾了致病性分枝杆菌中非编码RNA的知识现状，强调了常用数据库中所含信息的差异。然后，我们继续回顾将预测非编码转录组的计算解决方案与有助于完善和证实这些预测的实验相结合的方法。
