Gelsinger Diego Rivera, DiRuggiero Jocelyne
Department of Biology, The Johns Hopkins University, Baltimore, MD 21218, USA.
Genes (Basel). 2018 Mar 5;9(3):141. doi: 10.3390/genes9030141.
Small non-coding RNAs (sRNAs) are ubiquitously found in the three domains of life playing large-scale roles in gene regulation, transposable element silencing and defense against foreign elements. While a substantial body of experimental work has been done to uncover function of sRNAs in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. Recently, high throughput studies using RNA-sequencing revealed that sRNAs are broadly expressed in the Archaea, comprising thousands of transcripts within the transcriptome during non-challenged and stressed conditions. Antisense sRNAs, which overlap a portion of a gene on the opposite strand (-acting), are the most abundantly expressed non-coding RNAs and they can be classified based on their binding patterns to mRNAs (3' untranslated region (UTR), 5' UTR, CDS-binding). These antisense sRNAs target many genes and pathways, suggesting extensive roles in gene regulation. Intergenic sRNAs are less abundantly expressed and their targets are difficult to find because of a lack of complete overlap between sRNAs and target mRNAs (-acting). While many sRNAs have been validated experimentally, a regulatory role has only been reported for very few of them. Further work is needed to elucidate sRNA-RNA binding mechanisms, the molecular determinants of sRNA-mediated regulation, whether protein components are involved and how sRNAs integrate with complex regulatory networks.
小非编码RNA(sRNA)广泛存在于生命的三个域中,在基因调控、转座元件沉默和对外源元件的防御中发挥着重要作用。虽然已经开展了大量实验工作来揭示sRNA在细菌和真核生物中的功能,但sRNA在古菌中的功能作用仍知之甚少。最近,利用RNA测序进行的高通量研究表明,sRNA在古菌中广泛表达,在未受挑战和应激条件下的转录组中包含数千个转录本。反义sRNA与相反链上的部分基因重叠(反式作用),是表达最丰富的非编码RNA,它们可以根据与mRNA的结合模式进行分类(3'非翻译区(UTR)、5'UTR、CDS结合)。这些反义sRNA靶向许多基因和途径,表明其在基因调控中具有广泛作用。基因间sRNA表达较少,由于sRNA与靶mRNA之间缺乏完全重叠(顺式作用),其靶标难以找到。虽然许多sRNA已通过实验验证,但只有极少数sRNA的调控作用得到报道。需要进一步开展工作来阐明sRNA-RNA结合机制、sRNA介导调控的分子决定因素、是否涉及蛋白质成分以及sRNA如何与复杂的调控网络整合。