The Predicting Algorithm of Barrier Tree in RNA Folding Structure

Author(s):  
Zhendong Liu ◽  
Fanghan Liu ◽  
Yurong Yang ◽  
Jiwei Wang ◽  
Hailin Zhang
Author(s):  
Zhendong Liu ◽  
Qingxia Kong ◽  
Yaoyao Fu ◽  
Hongchao Ye ◽  
Shimin Zhao ◽  
...  

2014 ◽  
Vol 16 (4) ◽  
pp. 229 ◽  
Author(s):  
Zhendong Liu ◽  
Daming Zhu ◽  
Hongwei Ma

2000 ◽  
Vol 182 (19) ◽  
pp. 5399-5408 ◽  
Author(s):  
Nathalie Goupil-Feuillerat ◽  
Gérard Corthier ◽  
Jean-Jacques Godon ◽  
S. Dusko Ehrlich ◽  
Pierre Renault

ABSTRACT The α-acetolactate decarboxylase (ALDC) gene, aldB, is the penultimate gene of the leu-ilv-ald operon, which encodes the three branched-chain amino acid (BCAA) biosynthesis genes in Lactococcus lactis. Its product plays a dual role in the cell: (i) it catalyzes the second step of the acetoin pathway, and (ii) it controls the pool of α-acetolactate during leucine and valine synthesis. It can be transcribed from the two promoters present upstream of the leu and ilv genes (P1 and P2) or independently under the control of its own promoter (P3). In this paper we show that the production of ALDC is limited by two mechanisms. First, the strength of P3 decreases greatly during starvation for BCAAs and under other conditions that generally provoke the stringent response. Second, although aldB is actively transcribed from P1 and P2 during BCAA starvation, ALDC is not significantly produced from these transcripts. The aldB ribosome binding site (RBS) appears to be entrapped in a stem-loop, which is itself part of a more complex RNA folding structure. The function of the structure was studied by mutagenesis, using translational fusions with luciferase genes to assess its activity. The presence of the single stem-loop entrapping the aldB RBS was responsible for a 100-fold decrease in the level of aldB translation. The presence of a supplementary secondary structure upstream of the stem-loop led to an additional fivefold decrease of aldB translation. Finally, the translation of the ilvA gene terminating in the latter structure decreased the level of translation of aldBfivefold more, leading to the complete extinction of the reporter gene activity. Since three leucines and one valine are present among the last six amino acids of the ilvA product, we propose that pausing of the ribosomes during translation could modulate the folding of the messenger, as a function of BCAA availability. The purpose of the structure-dependent regulation could be to ensure the minimal production of ALDC required for the control of the acetolactate pool during BCAA synthesis but to avoid its overproduction, which would dissipate acetolactate. Large amounts of ALDC, necessary for operation of the acetoin pathway, could be produced under favorable conditions from the P3 transcripts, which do not contain the secondary structures.


Author(s):  
Zhendong Liu ◽  
Daming Zhu ◽  
Qionghai Dai

The prediction of RNA structure with pseudoknots is a nondeterministic polynomial-time hard (NP-hard) problem; according to minimum free energy models and computational methods, we investigate the RNA-pseudoknotted structure. Our paper presents an efficient algorithm for predicting RNA structure with pseudoknots, and the algorithm takes O([Formula: see text]) time and O([Formula: see text]) space, the experimental tests in Rfam10.1 and PseudoBase indicate that the algorithm is more effective and precise. The predicting accuracy, the time complexity and space complexity outperform existing algorithms, such as Maximum Weight Matching (MWM) algorithm, PKNOTS algorithm and Inner Limiting Layer (ILM) algorithm, and the algorithm can predict arbitrary pseudoknots. And there exists a [Formula: see text] ([Formula: see text]) polynomial time approximation scheme in searching maximum number of stackings, and we give the proof of the approximation scheme in RNA-pseudoknotted structure. We have improved several types of pseudoknots considered in RNA folding structure, and analyze their possible transitions between types of pseudoknots.


Author(s):  
Qingxia Kong ◽  
Zhendong Liu ◽  
Xiaobing Tang ◽  
Zhaohui Yang ◽  
Yaoyao Fu ◽  
...  

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yichao Li ◽  
Jingjing Chen ◽  
Shengdar Q. Tsai ◽  
Yong Cheng

AbstractPrime editing is a revolutionary genome-editing technology that can make a wide range of precise edits in DNA. However, designing highly efficient prime editors (PEs) remains challenging. We develop Easy-Prime, a machine learning–based program trained with multiple published data sources. Easy-Prime captures both known and novel features, such as RNA folding structure, and optimizes feature combinations to improve editing efficiency. We provide optimized PE design for installation of 89.5% of 152,351 GWAS variants. Easy-Prime is available both as a command line tool and an interactive PE design server at: http://easy-prime.cc/.


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