CN114550821B - 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法 - Google Patents

快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法 Download PDF

Info

Publication number
CN114550821B
CN114550821B CN202210261235.0A CN202210261235A CN114550821B CN 114550821 B CN114550821 B CN 114550821B CN 202210261235 A CN202210261235 A CN 202210261235A CN 114550821 B CN114550821 B CN 114550821B
Authority
CN
China
Prior art keywords
mouse
sequence
mir
mmu
promoter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210261235.0A
Other languages
English (en)
Other versions
CN114550821A (zh
Inventor
蒋澜
王祖贞
吕坤
童九翠
杨建课
冯翔
邓汉诺
罗天乐
汪乐瑶
杜金锐
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
First Affiliated Hospital of Wannan Medical College
Original Assignee
First Affiliated Hospital of Wannan Medical College
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by First Affiliated Hospital of Wannan Medical College filed Critical First Affiliated Hospital of Wannan Medical College
Priority to CN202210261235.0A priority Critical patent/CN114550821B/zh
Publication of CN114550821A publication Critical patent/CN114550821A/zh
Application granted granted Critical
Publication of CN114550821B publication Critical patent/CN114550821B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/30Detection of binding sites or motifs

Landscapes

  • Bioinformatics & Cheminformatics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Genetics & Genomics (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Chemical & Material Sciences (AREA)
  • Molecular Biology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Analytical Chemistry (AREA)
  • Evolutionary Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

本发明公开一种快速筛选小鼠mmu‑miR‑25‑3p与启动子结合靶点的方法,包括如下步骤:下载小鼠最新基因组序列和对应的注释文件,以及小鼠mmu‑miR‑25‑3p序列文件;从下载的小鼠最新基因组序列中提取小鼠最新基因组序列的染色体长度,并由此从小鼠最新基因组序列和对应的注释文件中提取启动子的序列;通过seedVicious软件筛选小鼠mmu‑miR‑25‑3p序列与S2提取的启动子序列,保留与miRNA种子序列完全匹配靶标的种类,获得mmu‑miR‑25‑3p与启动子靶标的预测结果。本发明利用现有数据和软件,在计算机上实现快速对小鼠mmu‑miR‑25‑3p与启动子结合靶点的筛选。

Description

快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法
技术领域
本发明属于生物医学技术领域,具体设涉及一种快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法。
背景技术
microRNAs(miRNAs)是一种小的,类似于siRNA的分子,由高等真核生物基因组编码,miRNA通过和靶基因mRNA碱基配对引导沉默复合体(RISC)降解mRNA或阻碍其翻译。miRNAs在物种进化中相当保守,在植物、动物和真菌中发现的miRNAs只在特定的组织和发育阶段表达,miRNA组织特异性和时序性,决定组织和细胞的功能特异性,表明miRNA在细胞生长和发育过程的调节过程中起多种作用。目前对于microRNAs的研究越来越被重视,其对于很多疾病的诊断有着重大价值。
启动子是一段位于结构基因5'端上游区的DNA序列,能活化RNA聚合酶,使之与模板DNA准确地相结合并具有转录起始的特异性。因为基因的特异性,转录取决于酶与启动子能否有效地形成二元复合物,故RNA聚合酶如何有效地找到启动子并与之相结合是转录起始过程中首先要解决的问题。有实验表明,对许多启动子来说,RNA聚合酶与之相结合的速率至少比布朗运动中的随机碰撞高100倍。
因此为了更好更方便的研究microRNAs,我们需要对其与启动子的结合靶点进行有效筛选,以供后续实用。
发明内容
发明目的:本发明目的在于针对现有技术的不足,提供一种快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法。
技术方案:本发明所述快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,包括如下步骤:
S1、下载小鼠最新基因组序列和对应的注释文件,以及小鼠mmu-miR-25-3p序列文件;
S2、在计算机中,将小鼠最新基因组序列对应的注释文件由gff格式转换为bed格式;从下载的小鼠最新基因组序列中提取小鼠最新基因组序列的染色体长度,并由此从小鼠最新基因组序列和对应的注释文件中提取启动子的序列;
S3、通过seedVicious软件筛选小鼠mmu-miR-25-3p序列与S2提取的启动子序列,保留与miRNA种子序列完全匹配靶标的种类,获得mmu-miR-25-3p与启动子靶标的预测结果。
本发明进一步优选地技术方案为,在步骤S1中从GENCODE数据库中下载小鼠最新基因组序列fasta和对应的注释文件gff,从miRBase数据库中下载小鼠mmu-miR-25-3p序列fasta文件。
作为优选地,步骤S2中在对基因组序列和注释文件进行处理前,先通过计算机的终端平台将下载的文件解压。
优选地,步骤S2中通过samtools软件提取小鼠最新基因组序列的染色体长度。
优选地,步骤S2中通过bedtools软件提取启动子序列。
有益效果:本发明利用现有数据和软件,在计算机上实现快速对小鼠mmu-miR-25-3p与启动子结合靶点的筛选,避开了很多前人开发的工作无法直接使用或软件不再维护的问题,方便后续研究microRNAs使用。
具体实施方式
下面对本发明技术方案进行详细说明,但是本发明的保护范围不局限于所述实施例。
实施例:一种快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,以下步骤全部在计算机的终端上完成,具体如下:
S1、下载安装samtools、bedtools、bedops和seedVicious软件:
下载安装samtools
https://github.com/samtools/samtools/releases/download/1.14/samtools-1.14.tar.bz2
放置在soft文件夹中。
>tar-jxvf samtools-1.14.tar.bz2
>cd/Users/Documents/soft/samtools-1.14
>./configure--prefix=/Users/Documents/soft/samtools-1.14
>make
>make install
>echo‘export PATH=$PATH:~/Users/Documents/soft/samtools-1.14’>>~/.bashrc
>source~/.bashrc
下载安装bedtools
>cd~/Users/Documents/soft
>wget
https://github.com/arq5x/bedtools2/releases/download/v2.29.1/bedtools-2.29.1.tar.gz
>tar-zxvf bedtools-2.29.1.tar.gz
>cd bedtools2
>make
>echo'export PATH=$PATH:~/Users/Documents/soft/bedtools2'>>~/.bashrc
>source~/.bashrc
下载安装bedops
根据计算机系统,下载最新bedops进行安装https://bedops.readthedocs.io/en/latest/。
下载安装seedVicious
>cd~/Users/Documents/soft
>curl-O https://seedvicious.essex.ac.uk/seedVicious_v1.3_x64.tar.gz
tar-xvf seedVicious_v1.3_x64.tar.gz
>echo'export PATH=$PATH:~/Users/Documents/soft/seedVicious_v1.3_x64'>>~/.bashrc
>source~/.bashrc
>seedViciousTest
>seedVicious–help
S2、下载小鼠最新基因组序列和对应的注释文件,以及小鼠mmu-miR-25-3p序列文件:
下载GENCODE数据库中小鼠最新基因组序列fasta和注释文件gff。
https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_mouse/release_M28/GRCm39.gen ome.fa.gz
https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_mouse/release_ M28/gencode.vM28.basic.annotation.gff3.gz
下载miRBase数据库中小鼠mmu-miR-25-3p序列fasta文件,并命名为mmu_miR_25_3p.fa,具体序列如下:
>mmu-miR-25-3p
CAUUGCACUUGUCUCGGUCUGA。
S3、数据整理,在计算机中,将小鼠最新基因组序列对应的注释文件由gff格式转换为bed格式;从下载的小鼠最新基因组序列中提取小鼠最新基因组序列的染色体长度,并由此从小鼠最新基因组序列和对应的注释文件中提取启动子的序列:
打开终端terminal
解压gencode.vM28.basic.annotation.gff3.gz
>gzip-d gencode.vM28.basic.annotation.gff3.gz
提取gff文件的所有基因位置,转换成bed格式
>awk'{if($3~/^gene$/)print}'gencode.vM28.basic.annotation.gff3>mmgenes28.gff
>gff2bed<mmgenes28.gff>mmgenes28.bed
提取染色体长度
>gzip-d GRCm39.genome.fa.gz
>samtools faidx GRCm39.genome.fa
>cut-f 1,2 GRCm39.genome.fa.fai>chr.len
提取启动子promoter的序列
>bedtools flank-i mmgenes28.bed-g chr.len-l 2000-r 0-s>promoter2000.bed
>bedtools getfasta-s-fi GRCm39.genome.fa-bed promoter2000.bed-fopromoter2000.fa-name
S4、通过seedVicious软件筛选小鼠mmu-miR-25-3p序列与S2提取的启动子序列,保留与miRNA种子序列完全匹配靶标的种类,获得mmu-miR-25-3p与启动子靶标的预测结果:
>cd mouse
>seedVicious-i promoter2000.fa-m mmu_miR_25_3p.fa-ve-o miR25promoter_ve.txt
>seedVicious-i promoter2000.fa-m mmu_miR_25_3p.fa-e-o miR25promoter_e.txt
保留与miRNA种子序列(seed sequence)完全匹配靶标的种类,即miR25promoter_e.txt表中第四列type的8mer,获得879个mmu-miR-25-3p与启动子靶标的预测结果。mmu-miR-25-3p与某基因启动子靶标的具体位置图可以参考miR25promoter_ve.txt。
如上所述,尽管参照特定的优选实施例已经表示和表述了本发明,但其不得解释为对本发明自身的限制。在不脱离所附权利要求定义的本发明的精神和范围前提下,可对其在形式上和细节上作出各种变化。

Claims (5)

1.一种快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,其特征在于,包括如下步骤:
S1、下载小鼠最新基因组序列和对应的注释文件,以及小鼠mmu-miR-25-3p序列文件;
S2、在计算机中,将小鼠最新基因组序列对应的注释文件由gff格式转换为bed格式;从下载的小鼠最新基因组序列中提取小鼠最新基因组序列的染色体长度,并由此从小鼠最新基因组序列和对应的注释文件中提取启动子的序列;
S3、通过seedVicious软件筛选小鼠mmu-miR-25-3p序列与S2提取的启动子序列,保留与miRNA种子序列完全匹配靶标的种类,获得mmu-miR-25-3p与启动子靶标的预测结果。
2.根据权利要求1所述的快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,其特征在于,在步骤S1中从GENCODE数据库中下载小鼠最新基因组序列fasta和对应的注释文件gff,从miRBase数据库中下载小鼠mmu-miR-25-3p序列fasta文件。
3.根据权利要求2所述的快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,其特征在于,步骤S2中在对基因组序列和注释文件进行处理前,先通过计算机的终端平台将下载的文件解压。
4.根据权利要求3所述的快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,其特征在于,步骤S2中通过samtools软件提取小鼠最新基因组序列的染色体长度。
5.根据权利要求4所述的快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法,其特征在于,步骤S2中通过bedtools软件提取启动子序列。
CN202210261235.0A 2022-03-16 2022-03-16 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法 Active CN114550821B (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210261235.0A CN114550821B (zh) 2022-03-16 2022-03-16 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210261235.0A CN114550821B (zh) 2022-03-16 2022-03-16 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法

Publications (2)

Publication Number Publication Date
CN114550821A CN114550821A (zh) 2022-05-27
CN114550821B true CN114550821B (zh) 2023-05-30

Family

ID=81662946

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210261235.0A Active CN114550821B (zh) 2022-03-16 2022-03-16 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法

Country Status (1)

Country Link
CN (1) CN114550821B (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118116454A (zh) * 2024-02-01 2024-05-31 西南大学 miRNA靶标集成自动分析方法及计算机程序产品

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102839192A (zh) * 2011-06-24 2012-12-26 中国人民解放军第二军医大学 miRNA吸收载体、其制备及用途
CN103509797A (zh) * 2013-10-09 2014-01-15 中山大学 一种小分子rna及其制备方法和在特异性上调基因转录活性的药物中的应用

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110747269A (zh) * 2019-10-25 2020-02-04 上海交通大学 用于pcos诊断的颗粒细胞生物标志物及其筛选方法和诊断试剂盒
CN113528669A (zh) * 2021-08-19 2021-10-22 柳州市工人医院 一种利用Small RNA测序技术揭示miRNA对肝癌作用机制的方法

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102839192A (zh) * 2011-06-24 2012-12-26 中国人民解放军第二军医大学 miRNA吸收载体、其制备及用途
CN103509797A (zh) * 2013-10-09 2014-01-15 中山大学 一种小分子rna及其制备方法和在特异性上调基因转录活性的药物中的应用

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Antonio Marco.SeedVicious: Analysis of microRNA target and near-target sites.POLS ONE.2018,第1-9页. *
刘伟."人类转录因子靶基因预测、分析及数据库构建".中国博士学位论文全文数据库 基础科技辑.2018,(第undefined期),第93-104页. *
毕润磊等.miR⁃212⁃5p 相关ceRNA 调控网络在巨噬细胞极化中的作用.皖南医学院学报.2021,全文. *

Also Published As

Publication number Publication date
CN114550821A (zh) 2022-05-27

Similar Documents

Publication Publication Date Title
Kuo et al. Detection of RNA–DNA binding sites in long noncoding RNAs
Wang Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies
McCartney‐Melstad et al. Exon capture optimization in amphibians with large genomes
Schattner et al. Genome-wide searching for pseudouridylation guide snoRNAs: analysis of the Saccharomyces cerevisiae genome
Veneziano et al. Computational approaches for the analysis of ncRNA through deep sequencing techniques
Cullum et al. The next generation: using new sequencing technologies to analyse gene regulation
Wilhelm et al. Defining transcribed regions using RNA-seq
Kanke et al. miRquant 2.0: an expanded tool for accurate annotation and quantification of microRNAs and their isomiRs from small RNA-sequencing data
Liu et al. Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development
Chou et al. Tailor: a computational framework for detecting non-templated tailing of small silencing RNAs
CN114550821B (zh) 快速筛选小鼠mmu-miR-25-3p与启动子结合靶点的方法
Stone et al. The application of RNA-seq to the comprehensive analysis of plant mitochondrial transcriptomes
CN105274198A (zh) 一种基于转录组测序开发鸟巢蕨est-ssr引物的方法
Iwasaki-Yokozawa et al. Genome-scale embryonic developmental profile of gene expression in the common house spider Parasteatoda tepidariorum
Liang et al. WBSA: web service for bisulfite sequencing data analysis
CN114566218B (zh) 快速筛选人源hsa-miR-576-3p与启动子结合靶点的方法
Jiang et al. Three-nucleotide periodicity of nucleotide diversity in a population enables the identification of open reading frames
Liu et al. Evaluation of experimental design and computational parameter choices affecting analyses of ChIP-seq and RNA-seq data in undomesticated poplar trees
Pereira et al. RNA‐seq: applications and best practices
CN110506114B (zh) Pcr引物对及其应用
Rosikiewicz et al. OverGeneDB: a database of 5′ end protein coding overlapping genes in human and mouse genomes
Kendall et al. Computational methods for DNA copy-number analysis of tumors
Yang et al. CRISPRlnc: a machine learning method for lncRNA-specific single-guide RNA design of CRISPR/Cas9 system
US20190325987A1 (en) Direct Interaction Between 5&#39; UTR and 3&#39; UTR Enhances miRNA Translation Repression
Yao et al. Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CB03 Change of inventor or designer information
CB03 Change of inventor or designer information

Inventor after: Lv Kun

Inventor after: Du Jinrui

Inventor after: Jiang Lan

Inventor after: Wang Zuzhen

Inventor after: Tong Jiucui

Inventor after: Yang Jianke

Inventor after: Feng Xiang

Inventor after: Deng Hannuo

Inventor after: Luo Tianle

Inventor after: Wang Leyao

Inventor before: Jiang Lan

Inventor before: Du Jinrui

Inventor before: Wang Zuzhen

Inventor before: Lv Kun

Inventor before: Tong Jiucui

Inventor before: Yang Jianke

Inventor before: Feng Xiang

Inventor before: Deng Hannuo

Inventor before: Luo Tianle

Inventor before: Wang Leyao