Biological Processes Discovered by High-Throughput Sequencing

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.

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

Journal of Nucleic Acids ◽

10.1155/2012/360358 ◽

2012 ◽

Vol 2012 ◽

pp. 1-15 ◽

Cited By ~ 20

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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Episo: quantitative estimation of RNA 5-methylcytosine at isoform level by high-throughput sequencing of RNA treated with bisulfite

Bioinformatics ◽

10.1093/bioinformatics/btz900 ◽

2019 ◽

Vol 36 (7) ◽

pp. 2033-2039 ◽

Cited By ~ 2

Author(s):

Junfeng Liu ◽

Ziyang An ◽

Jianjun Luo ◽

Jing Li ◽

Feifei Li ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Quantitative Estimation ◽

Supplementary Information ◽

Biological Processes ◽

Single Nucleotide ◽

Rna Immunoprecipitation ◽

Nucleotide Resolution ◽

Human And Mouse ◽

Single Nucleotide Resolution

Abstract Motivation RNA 5-methylcytosine (m5C) is a type of post-transcriptional modification that may be involved in numerous biological processes and tumorigenesis. RNA m5C can be profiled at single-nucleotide resolution by high-throughput sequencing of RNA treated with bisulfite (RNA-BisSeq). However, the exploration of transcriptome-wide profile and potential function of m5C in splicing remains to be elucidated due to lack of isoform level m5C quantification tool. Results We developed a computational package to quantify Epitranscriptomal RNA m5C at the transcript isoform level (named Episo). Episo consists of three tools: mapper, quant and Bisulfitefq, for mapping, quantifying and simulating RNA-BisSeq data, respectively. The high accuracy of Episo was validated using an improved m5C-specific methylated RNA immunoprecipitation (meRIP) protocol, as well as a set of in silico experiments. By applying Episo to public human and mouse RNA-BisSeq data, we found that the RNA m5C is not evenly distributed among the transcript isoforms, implying the m5C may subject to be regulated at isoform level. Availability and implementation Episo is released under the GNU GPLv3+ license. The resource code Episo is freely accessible from https://github.com/liujunfengtop/Episo (with Tophat/cufflink) and https://github.com/liujunfengtop/Episo/tree/master/Episo_Kallisto (with Kallisto). Supplementary information Supplementary data are available at Bioinformatics online.

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Non-micro-short RNAs: the new kids on the block

Molecular Biology of the Cell ◽

10.1091/mbc.e12-10-0716 ◽

2012 ◽

Vol 23 (24) ◽

pp. 4664-4667 ◽

Cited By ~ 5

Author(s):

Bijan K. Dey ◽

Adam C. Mueller ◽

Anindya Dutta

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Noncoding Rnas ◽

Mechanisms Of Action ◽

Biological Processes ◽

Large Group ◽

Small Noncoding Rnas ◽

Short Rnas ◽

Functional Classes ◽

Functional Relevance

The advent of ultra–high-throughput sequencing has led to the discovery of a large group of small, noncoding RNAs that are not microRNAs. The functional relevance of microRNAs has been well established over the last decade. In this Perspective, we focus on the non-micro-short RNAs that comprise a variety of functional classes and range from 16–40 nucleotides in size. We will highlight how some of these non-micro-short RNAs were discovered, as well as their biogenesis, potential mechanisms of action, and role in diverse biological processes, development, and disease. Finally, we will describe what must be done to further our understanding of these enigmatic molecules.

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