TFOFinder: Python program for identifying purine-only double-stranded stretches in the predicted secondary structure(s) of RNA targets.

IF 4.3 2区 生物学
PLoS Computational Biology Pub Date : 2023-08-25 eCollection Date: 2023-08-01 DOI:10.1371/journal.pcbi.1011418
Atara Neugroschl, Irina E Catrina
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引用次数: 0

Abstract

Nucleic acid probes are valuable tools in biology and chemistry and are indispensable for PCR amplification of DNA, RNA quantification and visualization, and downregulation of gene expression. Recently, triplex-forming oligonucleotides (TFO) have received increased attention due to their improved selectivity and sensitivity in recognizing purine-rich double-stranded RNA regions at physiological pH by incorporating backbone and base modifications. For example, triplex-forming peptide nucleic acid (PNA) oligomers have been used for imaging a structured RNA in cells and inhibiting influenza A replication. Although a handful of programs are available to identify triplex target sites (TTS) in DNA, none are available that find such regions in structured RNAs. Here, we describe TFOFinder, a Python program that facilitates the identification of intramolecular purine-only RNA duplexes that are amenable to forming parallel triple helices (pyrimidine/purine/pyrimidine) and the design of the corresponding TFO(s). We performed genome- and transcriptome-wide analyses of TTS in Drosophila melanogaster and found that only 0.3% (123) of total unique transcripts (35,642) show the potential of forming 12-purine long triplex forming sites that contain at least one guanine. Using minimization algorithms, we predicted the secondary structure(s) of these transcripts, and using TFOFinder, we found that 97 (79%) of the identified 123 transcripts are predicted to fold to form at least one TTS for parallel triple helix formation. The number of transcripts with potential purine TTS increases when the strict search conditions are relaxed by decreasing the length of the probe or by allowing up to two pyrimidine inversions or 1-nucleotide bulge in the target site. These results are encouraging for the use of modified triplex forming probes for live imaging of endogenous structured RNA targets, such as pre-miRNAs, and inhibition of target-specific translation and viral replication.

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TFOFinder:Python程序,用于识别预测的RNA靶标二级结构中仅嘌呤的双链延伸。
核酸探针是生物学和化学中有价值的工具,对于DNA的PCR扩增、RNA的定量和可视化以及基因表达的下调都是必不可少的。最近,三链形成寡核苷酸(TFO)由于其在生理pH下通过结合主链和碱基修饰来识别富含嘌呤的双链RNA区域的选择性和敏感性提高而受到越来越多的关注。例如,三链形成肽核酸(PNA)低聚物已被用于对细胞中的结构化RNA进行成像并抑制甲型流感复制。尽管有少数程序可用于识别DNA中的三重靶位点(TTS),但没有一个程序可用于在结构化RNA中发现此类区域。在这里,我们描述了TFOFinder,这是一个Python程序,有助于识别分子内仅嘌呤的RNA双链体,该双链体可形成平行的三螺旋(嘧啶/嘌呤/嘧啶),并设计相应的TFO。我们对黑腹果蝇的TTS进行了全基因组和转录组分析,发现只有0.3%(123)的总独特转录物(35642)显示出形成12个嘌呤长三链形成位点的潜力,这些位点含有至少一种鸟嘌呤。使用最小化算法,我们预测了这些转录物的二级结构,并使用TFOFinder,我们发现识别的123个转录物中有97个(79%)被预测折叠以形成至少一个TTS,用于平行三螺旋形成。当通过减少探针的长度或通过在靶位点中允许最多两个嘧啶反转或1-核苷酸凸起来放松严格的搜索条件时,具有潜在嘌呤TTS的转录物的数量增加。这些结果对于使用修饰的三链形成探针对内源性结构RNA靶标(如前miRNA)进行实时成像以及抑制靶标特异性翻译和病毒复制是令人鼓舞的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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