dna triple helix
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2021 ◽  
Vol 143 (40) ◽  
pp. 16693-16699
Author(s):  
Tianqing Zhang ◽  
Bryan Wei




Author(s):  
Kai Zhang ◽  
Zhenqiang Fan ◽  
Sha Zhu ◽  
Yuedi Ding ◽  
Minhao Xie ◽  
...  

In this paper, we present the first idea of using a DNA triple helix structure to inhibit CRISPR-Cas12a activity and apply it to the design of an electrochemiluminescent biosensor for...



2020 ◽  
Vol 1 (6) ◽  
pp. 100080
Author(s):  
Kyle J. Gibson ◽  
Aleksander Prominski ◽  
Margaret S. Lee ◽  
Timothy M. Cronin ◽  
John Parker ◽  
...  




2019 ◽  
Vol 47 (14) ◽  
pp. 7213-7222 ◽  
Author(s):  
Charlotte N Kunkler ◽  
Jacob P Hulewicz ◽  
Sarah C Hickman ◽  
Matthew C Wang ◽  
Phillip J McCown ◽  
...  

AbstractRecent studies suggest noncoding RNAs interact with genomic DNA, forming an RNA•DNA–DNA triple helix that regulates gene expression. However, base triplet composition of pyrimidine motif RNA•DNA–DNA triple helices is not well understood beyond the canonical U•A–T and C•G–C base triplets. Using native gel-shift assays, the relative stability of 16 different base triplets at a single position, Z•X–Y (where Z = C, U, A, G and X–Y = A–T, G–C, T–A, C–G), in an RNA•DNA–DNA triple helix was determined. The canonical U•A–T and C•G–C base triplets were the most stable, while three non-canonical base triplets completely disrupted triple-helix formation. We further show that our RNA•DNA–DNA triple helix can tolerate up to two consecutive non-canonical A•G–C base triplets. Additionally, the RNA third strand must be at least 19 nucleotides to form an RNA•DNA–DNA triple helix but increasing the length to 27 nucleotides does not increase stability. The relative stability of 16 different base triplets in DNA•DNA–DNA and RNA•RNA–RNA triple helices was distinctly different from those in RNA•DNA–DNA triple helices, showing that base triplet stability depends on strand composition being DNA and/or RNA. Multiple factors influence the stability of triple helices, emphasizing the importance of experimentally validating formation of computationally predicted triple helices.



2018 ◽  
Vol 46 (19) ◽  
pp. 9951-9959 ◽  
Author(s):  
Alessio Ottaviani ◽  
Federico Iacovelli ◽  
Andrea Idili ◽  
Mattia Falconi ◽  
Francesco Ricci ◽  
...  


2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Asako Isogawa ◽  
Robert P. Fuchs ◽  
Shingo Fujii


2017 ◽  
Vol 139 (15) ◽  
pp. 5321-5329 ◽  
Author(s):  
Federico Iacovelli ◽  
Andrea Idili ◽  
Alessandro Benincasa ◽  
Davide Mariottini ◽  
Alessio Ottaviani ◽  
...  


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