scholarly journals PRIME-3D2D is a 3D2D model to predict binding sites of protein–RNA interaction

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Juan Xie ◽  
Jinfang Zheng ◽  
Xu Hong ◽  
Xiaoxue Tong ◽  
Shiyong Liu
Keyword(s):  
Full Advantage ◽  
High Throughput ◽  
Binding Sites ◽  
High Throughput Sequencing ◽  
Secondary Structures ◽  
Biological Processes ◽  
Genome Wide ◽  
Rna Interaction ◽  
Rna Complexes ◽  
Better Than

AbstractProtein-RNA interaction participates in many biological processes. So, studying protein–RNA interaction can help us to understand the function of protein and RNA. Although the protein–RNA 3D3D model, like PRIME, was useful in building 3D structural complexes, it can’t be used genome-wide, due to lacking RNA 3D structures. To take full advantage of RNA secondary structures revealed from high-throughput sequencing, we present PRIME-3D2D to predict binding sites of protein–RNA interaction. PRIME-3D2D is almost as good as PRIME at modeling protein–RNA complexes. PRIME-3D2D can be used to predict binding sites on PDB data (MCC = 0.75/0.70 for binding sites in protein/RNA) and transcription-wide (MCC = 0.285 for binding sites in RNA). Testing on PDB and yeast transcription-wide data show that PRIME-3D2D performs better than other binding sites predictor. So, PRIME-3D2D can be used to predict the binding sites both on PDB and genome-wide, and it’s freely available.

Comparison of high throughput sequencing to standard protocols for virus detection in berry crops

Plant Disease ◽  
2021 ◽  
Author(s):  
Dan Edward Veloso Villamor ◽  
Karen E Keller ◽  
Robert Martin ◽  
Ioannis Emmanouil Tzanetakis
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Wide Spectrum ◽  
Virus Detection ◽  
Rt Pcr ◽  
Host Interactions ◽  
Growing Seasons ◽  
Berry Crops ◽  
Sampling Times ◽  
Better Than

A comprehensive study comparing virus detection between high throughput sequencing (HTS) and standard protocols in 30 berry selections (12 Fragaria, 10 Vaccinium and 8 Rubus) with known virus profiles was completed. The study examined temporal detection of viruses at four sampling times encompassing two growing seasons. Within the standard protocols, RT-PCR proved better than biological indexing. Detection of known viruses by HTS and RT-PCR nearly mirrored each other. HTS provided superior detection compared to RT-PCR on a wide spectrum of virus variants and discovery of novel viruses. More importantly, in most cases where the two protocols showed parallel virus detection, 11 viruses in 16 berry selections were not consistently detected by both methods at all sampling points. Based on these data we propose a four sampling times/two-year testing requirement for berry and potentially other crops to ensure that no virus remains undetected independent of titer, distribution or other virus/virus or virus/host interactions.

Genome-wide identification of low phosphorus responsive microRNAs in two soybean genotypes by high-throughput sequencing

2020 ◽  
Vol 20 (6) ◽  
pp. 825-838
Author(s):  
Xiaoqian Liu ◽  
Shanshan Chu ◽  
Chongyuan Sun ◽  
Huanqing Xu ◽  
Jinyu Zhang ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Genome Wide ◽  
Low Phosphorus ◽  
Soybean Genotypes

scholarly journals Small RNA Expression Profiling by High-Throughput Sequencing: Implications of Enzymatic Manipulation

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Fanglei Zhuang ◽  
Ryan T. Fuchs ◽  
G. Brett Robb
Keyword(s):  
High Throughput ◽  
Expression Profiling ◽  
Messenger Rna ◽  
High Throughput Sequencing ◽  
Biological Processes ◽  
Cellular Processes ◽  
Disease States ◽  
Powerful Approach ◽  
Sequencing Library ◽  
Rna Expression Profiling

Eukaryotic regulatory small RNAs (sRNAs) play significant roles in many fundamental cellular processes. As such, they have emerged as useful biomarkers for diseases and cell differentiation states. sRNA-based biomarkers outperform traditional messenger RNA-based biomarkers by testing fewer targets with greater accuracy and providing earlier detection for disease states. Therefore, expression profiling of sRNAs is fundamentally important to further advance the understanding of biological processes, as well as diagnosis and treatment of diseases. High-throughput sequencing (HTS) is a powerful approach for both sRNA discovery and expression profiling. Here, we discuss the general considerations for sRNA-based HTS profiling methods from RNA preparation to sequencing library construction, with a focus on the causes of systematic error. By examining the enzymatic manipulation steps of sRNA expression profiling, this paper aims to demystify current HTS-based sRNA profiling approaches and to aid researchers in the informed design and interpretation of profiling experiments.

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