Bioinformatics Tutorial
Files Needed
  • Getting Started
    • Setup
    • Run jobs in a Docker
    • Run jobs in a cluster [Advanced]
  • Part I. Programming Skills
    • 1.Linux
      • 1.1.Basic Command
      • 1.2.Practice Guide
      • 1.3.Linux Bash
    • 2.R
      • 2.1.R Basics
      • 2.2.Plot with R
    • 3.Python
  • PART II. BASIC ANALYSES
    • 1.Blast
    • 2.Conservation Analysis
    • 3.Function Analysis
      • 3.1.GO
      • 3.2.KEGG
      • 3.3.GSEA
    • 4.Clinical Analyses
      • 4.1.Survival Analysis
  • Part III. NGS DATA ANALYSES
    • 1.Mapping
      • 1.1 Genome Browser
      • 1.2 bedtools and samtools
    • 2.RNA-seq
      • 2.1.Expression Matrix
      • 2.2.Differential Expression with Cufflinks
      • 2.3.Differential Expression with DEseq2 and edgeR
    • 3.ChIP-seq
    • 4.Motif
      • 4.1.Sequence Motif
      • 4.2.Structure Motif
    • 5.RNA Network
      • 5.1.Co-expression Network
      • 5.2.miRNA Targets
      • 5.3. CLIP-seq (RNA-Protein Interaction)
    • 6.RNA Regulation - I
      • 6.1.Alternative Splicing
      • 6.2.APA (Alternative Polyadenylation)
      • 6.3.Chimeric RNA
      • 6.4.RNA Editing
      • 6.5.SNV/INDEL
    • 7.RNA Regulation - II
      • 7.1.Translation: Ribo-seq
      • 7.2.RNA Structure
    • 8.cfDNA
      • 8.1.Basic cfDNA-seq Analyses
  • Part IV. MACHINE LEARNING
    • 1.Machine Learning Basics
      • 1.1 Data Pre-processing
      • 1.2 Data Visualization & Dimension Reduction
      • 1.3 Feature Extraction and Selection
      • 1.4 Machine Learning Classifiers/Models
      • 1.5 Performance Evaluation
    • 2.Machine Learning with R
    • 3.Machine Learning with Python
  • Part V. Assignments
    • 1.Precision Medicine - exSEEK
      • Help
      • Archive: Version 2018
        • 1.1.Data Introduction
        • 1.2.Requirement
        • 1.3.Helps
    • 2.RNA Regulation - RiboShape
      • 2.0.Programming Tools
      • 2.1.RNA-seq Analysis
      • 2.2.Ribo-seq Analysis
      • 2.3.SHAPE Data Analysis
      • 2.4.Integration
    • 3.RNA Regulation - dsRNA Code
    • 4.Single Cell Data Analysis
      • Help
  • 5.Model Programming
  • Appendix
    • Appendix I. Keep Learning
    • Appendix II. Databases & Servers
    • Appendix III. How to Backup
    • Appendix IV. Teaching Materials
    • Appendix V. Software and Tools
    • Appendix VI. Genome Annotations
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  • 0) 背景介绍
  • 0.1) RNA Interference, dsRNA and small RNA
  • 0.2) dsRNAs in immune responses
  • 0.3) Question: dsRNA codes?
  • 1)数据集介绍
  • 数据集(Input Data):
  • 下载方式
  • 2) 报告要求
  • Help
  • 休息一会

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  1. Part V. Assignments

3.RNA Regulation - dsRNA Code

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“RNA 而不是 DNA 才是细胞的计算引擎。”

-- RNA: 掌控生命后台 《环球科学》 (Scientific American) 2024年7月刊封面文章

0) 背景介绍

0.1) RNA Interference, dsRNA and small RNA

RNA干扰(RNA interference,简称RNAi)是一种天然存在于生物体内的基因沉默机制,同时也是一项重要的实验技术和疾病治疗技术。RNA干扰是指在生物进化过程中高度保守的、由双链RNA(double stranded RNA, dsRNA)引发的基因沉默现象。它通过特异性降解同源mRNA,从而阻断特定基因的表达。

RNA干扰的核心机制包括了双链RNA(dsRNA)的生成,RNA干扰的启动通常需要双链RNA(dsRNA),这些双链RNA可以是外源引入的,也可以是内源产生的。通过dsRNA加工生成small RNA 的类型和调控机制主要包括miRNA/siRNA/piRNA三类,如下图所示 (Figure 1)。

0.2) dsRNAs in immune responses

随着科研的进展,人们发现双链RNA(dsRNA)远不止上述3种,还包括如下表 (Table 1) 中所示的很多不同长度的dsRNA及其感应识别受体(sensors)。 这些不同的dsRNAs在免疫系统中具有重要作用,尤其是在抗病毒和抗肿瘤免疫反应中。

以下是关于dsRNA在免疫中的作用及相关机制的详细说明:

1. dsRNA的识别机制

dsRNA是一种由两条互补RNA链组成的分子,常见于病毒感染过程中。免疫系统通过特定的模式识别受体(PRR)来识别dsRNA,从而启动免疫反应 (Figure 2)。主要的感应识别受体 (sensor) 包括:

  • PKR(蛋白激酶R):一种激酶,可被dsRNA激活,抑制蛋白质合成,从而阻止病毒复制。

  • MDA5(黑色素瘤分化相关基因5)和RIG-I(视黄酸诱导基因I):这两种受体属于RIG-I样受体(RLR)家族,负责识别细胞质中的dsRNA,并激活下游信号通路。

  • TLR3(Toll样受体3):主要存在于细胞内体中,能够识别dsRNA并触发免疫反应。


2. dsRNA激活的免疫反应

当dsRNA被上述受体识别后,会通过以下机制激活免疫反应:

  • 干扰素(IFN)的产生:dsRNA的识别会激活IRF3(干扰素调节因子3)和NF-κB等转录因子,促进IFN-α/β的表达。这些干扰素通过JAK-STAT信号通路进一步激活抗病毒基因的表达,从而抑制病毒复制。

  • 炎症反应的启动:dsRNA的识别还会引发促炎性细胞因子的释放,如IL-6和TNF-α,增强炎症反应以清除病原体。


3. dsRNA在抗病毒免疫中的作用

dsRNA是许多病毒(如流感病毒、冠状病毒等)的标志性分子。免疫系统能够通过识别dsRNA快速启动抗病毒反应:

  • 先天免疫的激活:dsRNA通过激活PKR、MDA5等受体,触发干扰素反应,限制病毒在宿主细胞中的复制。

  • 适应性免疫的调节:干扰素不仅能直接抑制病毒,还能通过增强抗原呈递和T细胞活化,促进适应性免疫反应。


4. dsRNA在抗肿瘤免疫中的作用

dsRNA在抗肿瘤免疫中也具有重要作用,尤其是在肿瘤免疫治疗中:

  • 抗肿瘤免疫的激活:dsRNA通过“病毒拟态”机制,被细胞质中的PRR识别后,诱导干扰素反应,增强抗肿瘤免疫。

  • 免疫检查点抑制剂(ICI)的协同作用:dsRNA的免疫刺激作用能够提升ICI(如PD-1抑制剂)的治疗效果,帮助免疫系统更有效地识别和攻击肿瘤细胞。


5. dsRNA在疾病中的潜在影响

dsRNA的免疫作用并非总是有益。在某些病理条件下,内源性dsRNA的过度生成可能引发以下问题:

  • 自身免疫性疾病:如系统性红斑狼疮(SLE)中,内源性dsRNA的异常积累可能激活免疫系统,导致自身组织损伤。

  • 细胞应激反应:在病毒感染或肿瘤微环境中,dsRNA的过度生成可能触发细胞应激机制,影响细胞稳态。


总结

各类dsRNAs在免疫系统中扮演着关键角色,其通过激活模式识别受体(如PKR、MDA5、TLR3等),触发干扰素和炎症反应,从而在抗病毒和抗肿瘤免疫中发挥重要作用。然而,dsRNA的过度生成也可能导致自身免疫性疾病等问题。因此,深入研究dsRNA的免疫调节机制,有助于开发更有效的免疫治疗策略。

参考文献:

2024 Nature Reviews | Immunology - Novel insights into double-stranded RNA-mediated immunopathology

2022 Nature Reviews Cellular origins of dsRNA, their recognition and consequences

0.3) Question: dsRNA codes?

Question 1. How does a protein/sensor recognize a specific kind of dsRNA?

不同类型的免疫细胞,在不同生理和病理条件下,会不会有特异的dsRNAs的富集?这些特异的dsRNAs又具有哪些codes?被哪些sensors所识别? 激活了哪些下游的免疫应答通路?这些都是未能被很好回答的科学问题。

参考文献:

2022 Nature - MicroRNA sequence codes for small extracellular vesicle release and cellular retention

2024 Nature Reviews | Immunology - Novel insights into double-stranded RNA-mediated immunopathology

2012 Nature Structural & Molecular Biology - Turning Dicer on its head

2019 Cell - Structure and Degradation of Circular RNAs Regulate PKR Activation in Innate Immunity

Question 2. What are the upstream and downstream codes in dsRNAs?

很多的感应受体蛋白(sensor)例如MDA5,识别的信号是dsRNA的双链区(例如hairpin发卡结构中的stem区)的长度(如下图 Figure 4 的右边所示)。可以理解成upstream code。

而有些dsRNA在被受体蛋白识别后,还会被进一步加工成small RNA(如下图 Figure4 的左边3个所示):miRNA、siRNA和piRNA都有前体(例如pre-miRNA大约100nt)和成熟体(例如成熟的miRNA/siRNA/piRNA序列大约20-30nt)。前体(precursor)的长度和成熟体的长度有着不同的生物学意义,可以理解成upstream code和downstream code(Figure 4)。

这些uptream and downstream codes分别有哪些? 是什么?只是长度么?也是未能被完全理解的科学问题。

1)数据集介绍

数据集(Input Data):

  • Pre-defined dsRNA regions in human genome

  • Mapped reads (e.g., bam files)

    • in different types of immune cells and cell-free components (e.g., EV, non-EV in plasma, platelet)

    • from different persons of disease status (e.g., SLE Patients, Healthy Controls)

下载方式

  • 联系助教下载

2) 报告要求

  • 提交一份完整的工作报告 (中英文不限),需要提供主要的代码

报告模板可以参考如下文章:

2021 Nature - MicroRNA sequence codes for small extracellular vesicle release and cellular retention

  • 报告关键内容(评分点)

    • 阐述(和发现)在不同免疫细胞和EV等细胞外组分中的dsRNA的不同特征(codes),解释和讨论其可能的机理(比如不同的RNA Binding Protein (RBP)的结合?)。

    • 在自身免疫疾病SLE病人和正常人之间分析上述dsRNA及其特征的异同,解释和讨论其可能的致病机理。

Help

  1. Analysis Outline:

    1. Step 1. Prepare data matrix: Pre-defined dsRNA regions + RNA-seq data (mapped reads) in each type of cell of each person

    2. Step 2. Group/Categorize dsRNAs: Differential Expression Analysis (e.g., patients vs. healthy controls, EV vs. non-EV in plasma, etc) + Co-expression Network and Clustering Analysis + ...

    3. Step 3. Find codes enriched in different groups: codes include Sequence Motif (tool: meme), Length, Structure (tools: RNAcontext, RNApromo, new AI tool), etc. (Sequence motif analysis is relatively easier than length and structure analyses, which has less credit in the final score).

    4. Step 4: Interpret the data: associate with other data (GO/KEGG, RBP binding data, …); consider biological meanings in upstream codes and downstream codes.

  2. Upstream codes (Figure 4):例如pre-miRNA这样的发卡结构(hairpin)中的stem长度是一个定值,建议可以通过RNAfold或者RNAstructure软件预测RNA二级结构,然后对stem双链区的长度进行统计来得到。

  3. Downstream codes (Figures 4):成熟的small RNA sequences的单链长度一般是一个比较小的定值(例如成熟的miRNA单链和成熟的piRNA单链在人类细胞中都是一个定长),建议可以通过pair-end sequencing reads中的 ‘insert size’ 来计算和统计发现特定长度的小RNA单链。

休息一会

The 2006 Nobel Prize in Physiology or Medicine has been jointly awarded to Andrew Z. Fire and Craig C. Mello for their discovery of “RNA interference – gene silencing by double-stranded RNA".

This year’s Nobel Laureates have discovered a fundamental mechanism for controlling the flow of genetic information. Our genome operates by sending instructions for the manufacture of proteins from DNA in the nucleus of the cell to the protein synthesizing machinery in the cytoplasm. These instructions are conveyed by messenger RNA (mRNA). In 1998, the American scientists Andrew Fire and Craig Mello published their discovery of a mechanism that can degrade mRNA from a specific gene. This mechanism, RNA interference, is activated when RNA molecules occur as double-stranded pairs in the cell. Double-stranded RNA activates biochemical machinery which degrades those mRNA molecules that carry a genetic code identical to that of the double-stranded RNA. When such mRNA molecules disappear, the corresponding gene is silenced and no protein of the encoded type is made.

RNA interference occurs in plants, animals, and humans. It is of great importance for the regulation of gene expression, participates in defense against viral infections, and keeps jumping genes under control. RNA interference is already being widely used in basic science as a method to study the function of genes and it may lead to novel therapies in the future.

The 2024 Nobel Prize in Physiology or Medicine has been awarded to two Americans, Victor Ambros and Gary Ruvkun, for their discovery of microRNAs, which plays a key role in controlling and regulating gene activity in animals and plants.

The C. elegans worm is once again in the spotlight of the Nobel Prize. The tiny worm had already been recognised for facilitating the discovery in 2002 of the genetic regulations of organ development and programmed cell death and in 2006 of RNA interference - gene silencing by double-stranded RNA. This year, the little nematode is involved in the ground-breaking “discovery of microRNAs and their role in post-transcriptional gene regulation.” This seminal work discovered a new and unexpected mechanism of gene regulation that helps our understanding of embryological development, normal physiology and diseases such as cancer.

在上述“”一节中,我们提到不同的感应识别受体(sensor)会识别不同的长度的dsRNAs(Table 1, Figure 2)。除了长度之外,不同的dsRNA可能还会有特异的sequence motif, structure motif等其他codes,会被不同的sensor所识别,可能的机理如下图所示 (Figure 3)。

整个报告的目标是回答 中的两个科学问题。

dsRNA的识别机制
0.3) Question: dsRNA codes
Figure 1. Type of small RNAs
Table 1. dsRNA length sensitivity of dsRNA sensors(dsRNA, double-stranded RNA; ND, not determined; NLRP1, NOD-, LRR- and pyrin domain-containing 1; OAS, oligoadenylate synthase; PKR, protein kinase R; RIPLET, E3 ubiquitin-protein ligase RNF135; RLR, RIG-I-like receptor; TLR3, Toll-like receptor 3; TRIM65, tripartite motif-containing protein 65.) (2022 Nature Reviews Cellular origins of dsRNA, their recognition and consequences)
Figure 2. dsRNA sensors in different immune pathways (Young et al., Biochem Soc Trans. 2024)
Figure 3. dsRNA codes: sequence, length, structure
Figure 4. Upstream and downstream codes for precursor and mature sequence
2006 Nobel Prize
2024 Nobel Prize