Dengue virus m6A methylation modification site identification and analysis method based on MeRIP-seq

Abstract

The invention discloses a method for identifying and analyzing m6A methylation modification sites of dengue viruses based on MeRIP-seq, which comprises the following steps of: sequencing by combining a specific m6A antibody with m6A modified RNA (Ribonucleic Acid), and mapping reads onto a reference genome by using HISAT2 and other software packages to determine 6 m6A peaks of DENV-I type and 5 m6A peaks of DENV-II type. The method can identify and locate m6A modification, can be used for m6A methylation analysis of a whole transcriptome level, and can provide distribution and abundance information about m6A methylation sites in transcripts. The method is suitable for identification and analysis of m6A methylation modification sites after virus infection, and can solve some problems brought to actual work due to special conditions that dengue virus typing is diversified and the virus does not have polyA tails.

Description

Technical Field

[0001] The present invention relates to RNA 6 A modified detection technology, specifically involving a dengue virus m based on MeRIP-seq 6 A. Methylation modification site identification and analysis method. Background Art

[0002] Dengue fever is a mosquito-borne disease caused by dengue virus (DENV), which is mainly transmitted by Aedes aegypti and Aedes albopictus. Dengue virus belongs to the family Flaviviridae. Its genome is a single-stranded positive-sense RNA with high genetic diversity. DENV can be divided into four serotypes (DENV-1 to DENV-4) based on its antigenic and genetic characteristics, and there are multiple genotypes within each serotype. In recent years, dengue fever has shown a clear trend of spreading around the world, especially in tropical and subtropical regions, and its epidemic situation has attracted widespread attention and research. Dengue virus infection can cause typical dengue symptoms such as high fever, headache, muscle and joint pain. In severe cases, it can lead to bleeding tendency, shock and even death. The population is generally susceptible, and after infection, they can acquire immunity to the same type of virus, but have lower immunity to infection with other types of viruses. The expenditure of medical expenses, loss of labor, and mosquito control measures taken to prevent the spread of the virus will increase social costs.

[0003] m 6 A methylation modification is a common epigenetic modification in eukaryotes, which can mark specific mRNAs and regulate the expression of immune-related genes by affecting the stability and translation efficiency of mRNAs. 6 As a post-transcriptional functional regulatory molecule, A has different regulatory effects on different viral infections. 6 A modification plays an important role in virus-host interaction and can participate in antiviral immune response and cell metabolism remodeling by affecting viral replication, regulating host cell metabolism, and serving as a potential antiviral target. 6 The study of the accurate location of A modification can provide important theoretical basis for related fields and promote the development of mRNA epitranscriptomics. 6 ASequencing is expensive, especially for viral infections, and the computational methods and analysis are imperfect. Summary of the invention

[0004] In order to overcome the above-mentioned shortcomings and deficiencies of the prior art, the object of the present invention is to provide a dengue virus mRNA based on MeRIP-seq. 6A method for identifying and analyzing methylation modification sites, which combines immunoprecipitation, RNA sequencing and bioinformatics technology to mRNA expression in viral genomes after dengue virus infection of cells. 6 A. Identification and analysis of methylation modification sites. 6 A methylation modification site identification method, the key issues to be solved are total RNA extraction after dengue virus infection, cDNA library construction, m 6 Identification of A modification sites.

[0005] MeRIP-seq is a method that combines RNA immunoprecipitation (RIP), RNA sequencing (RNA-seq), and bioinformatics to detect mRNAs with high accuracy across the entire genome. 6 A modification. Mainly through mRNA fragmentation, using specific m 6 A antibody is incubated with the broken RNA fragments. This process can enrich the methylated RNA and further sequence and analyze the methylation pattern. MeRIP-seq is not only used to study the gene expression regulation of RNA methylation modification in viruses, the relationship between changes in RNA methylation modification and disease occurrence, but can also be used to reveal changes in RNA methylation in specific cancer types, and provide therapeutic targets and ideas.

[0006] The purpose of the present invention is achieved through the following technical solutions.

[0007] A dengue virus mRNA based on MeRIP-seq 6 A methylation modification site identification and analysis method, including sample pretreatment, genomic RNA extraction, quality detection and sequencing, data analysis, characterized in that: a method combining RNA immunoprecipitation and high-throughput sequencing technology, using specific anti-m 6 A antibody binding m 6 A modified RNA, and then sequence analysis was performed to achieve m 6 Identification and localization of A modifications; m 6 A methylation analysis can provide information about m 6 ADistribution and abundance information of methylation sites in transcripts.

[0008] Furthermore, the analysis method comprises the following steps: (1) Viral RNA extraction: Extract RNA according to the instructions of the total RNA extraction kit (TRIzol); (2) Quality control: The extracted total RNA was separated and purified, and the total amount and purity of the total RNA were quality controlled using an ultra-micro spectrophotometer and verified by agarose gel electrophoresis. (3) Sequencing: Digestion removes ribosomal RNA from total RNA, fragments the remaining RNA, and combines it with immunomagnetic beads and mRNA. 6 A antibody was premixed in IP buffer and immunoprecipitated (IP); then E. coli DNA polymerase I (E. coli DNA polymerase I) and ribonuclease H (RNase H) were used for duplex synthesis to convert the DNA and RNA composite duplexes into DNA duplexes, and dUTP Solution was added to the duplexes to fill the ends of the duplexes into blunt ends; then an A base was added to each end to enable it to connect to the linker with a T base at the end, and then the size of its fragments was screened and purified using magnetic beads; the duplexes were digested with UDG enzyme, and then PCR-pre-denaturation was performed to form a library with a fragment size of 300bp±50bp; (4) Bioinformatics analysis: Quality control and filtering of raw data obtained from high-throughput sequencing to remove low-quality sequences and adapter sequences; aligning the filtered data to the reference genome to determine m 6 A is the specific location of the modification site; detect the peak in the comparison result, i.e. m 6 A is the region where the modification site is located, and these peaks are annotated and distributed; m 6 A modification sites were compared and analyzed to identify differences 6 A modification site.

[0009] Furthermore, step (4) bioinformatics analysis includes: Use fastp software to filter reads and remove some low-quality reads and low-quality bases; The HISAT2 software package was used to align the reads of all samples with the reference genome; Exomepeak is used to predict the presence of m in the genome 6 A. Methylated regions and identification of regions with differential methylation modifications in the genome; Annotate the peaks using ANNOVAR software; predict the peak motifs using HOMER software; perform differential gene analysis using DESeq2 or edgeR; Finally, GSEA software and MSigDB were used to perform gene set enrichment analysis to determine whether a group of gene sets in specific GO Terms and KEGG pathways showed significant differences between the two groups.

[0010] Furthermore, the ultra-micro spectrophotometer in step (2) is NanoDrop ND-1000.

[0011] Furthermore, the PCR-pre-denaturation in step (3) is specifically as follows: 95°C for 3 minutes, 98°C for a total of 8 cycles of 15 seconds each, annealing at 60°C for 15 seconds, extension at 72°C for 30 seconds, and finally extension at 72°C for 5 minutes.

[0012] Compared with the prior art, the present invention has the following advantages and beneficial effects: The method of the present invention is applicable to m 6 The identification and analysis of A methylation modification sites can solve some problems in practical work caused by the special situation that dengue virus is diverse in typing and the virus itself does not have a polyA tail. 6 A modification map, to further carry out the analysis of the pathogenicity and pathogenic mechanism of the virus, and to lay a good foundation for the development of molecular detection technology. The advantages of this method are that DESeq2 was used in biological replication, and edgeR was used for differential gene analysis without biological replication; unknown motif prediction was performed on the peak using HOMER software to detect whether there was a classic motif in the callpeak result, which was RRACH in animals and plants, and URUAY unique to plants; the peak was annotated using ANNOVAR software, which was different from the previous use of ChIPseeker, where some peaks were annotated to the area closest to TSS (transcription start point), making m 6 A comment is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of the MeRIP-seq experiment in the examples.

[0014] Figure 2 DENV-I type m in the embodiment 6 A peak position.

[0015] Figure 3 DENV-II type m in the embodiment 6 A peak position. DETAILED DESCRIPTION

[0016] The present invention is further described in detail below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0017] A dengue virus m based on MeRIP-seq in this example 6A method for identifying and analyzing methylation modification sites includes sample pretreatment of dengue virus infected Huh-7 cells, extraction of genomic RNA, quality detection and sequencing.

[0018] The extracted dengue virus infected Huh-7 cell sequencing data was subjected to bioinformatics analysis. First, after removing low-quality and adapter sequences, the reads were mapped to the reference genome using the HISAT2 software package. Exomepeak was used to predict the m 6 A methylated regions and regions with differential methylation modifications on the genome were identified. The peaks were then annotated using ANNOVAR software. The peaks were then motif predicted using HOMER software, and differential gene analysis was performed using DESeq2 (edgeR was used if there was no biological replication). Gene set enrichment analysis was performed using GSEA software and MSigDB to determine whether a set of genes in a specific GO Terms or KEGG pathway showed significant differences between the two groups.

[0019] Table 1 DENV-Ⅰ type m 6 A's peak position information

[0020] Table 2 DENV-Ⅱ type m 6 A's peak position information

[0021] The specific experimental process of this embodiment is as follows.

[0022] 1. Nucleic acid extraction Extract genomic RNA according to the instructions of the total RNA extraction kit (spin column type).

[0023] 2. Quality Control and Sequencing The total amount and purity of the isolated and purified total RNA were quality controlled using NanoDrop ND-1000. The integrity of the RNA was then tested using Bioanalyzer 2100 and verified using agarose electrophoresis. Concentrations > 50 ng / μL, RIN values ​​> 7.0, OD260 / 280 > 1.8, and total RNA > 25 μg were sufficient for downstream experiments.

[0024] The Epicentre Ribo-Zero Gold Kit was used to digest and remove the ribosomal RNA (rRNA) of the total RNA. The remaining RNA after the ribosomal RNA was removed was fragmented using the NEBNext® Magnesium RNA Fragmentation Module at 86°C for 7 minutes. The fragmented RNA was mixed with the Dynabeads Antibody Coupling Kit and m 6 A antibody was premixed in IP buffer and IP was performed. The IP product was synthesized into cDNA by reverse transcriptase (Invitrogen SuperScript™ II ReverseTranscriptase). Then, E. coli DNA polymerase I was used to synthesize the second strand with RNase H, and the DNA and RNA complex double strands were converted into DNA double strands. At the same time, dUTPSolution was incorporated into the second strand to fill the ends of the double-stranded DNA into blunt ends. Then, an A base was added to each end to enable it to be connected to the adapter with a T base at the end, and then the fragment size was screened and purified using magnetic beads. The second strand was digested with UDG enzyme, and then PCR was performed - pre-denaturation at 95℃ for 3 minutes, denaturation at 98℃ for a total of 8 cycles for 15 seconds each, annealing to 60℃ for 15 seconds, extension at 72℃ for 30 seconds, and finally extension at 72℃ for 5 minutes to form a library with a fragment size of 300bp±50bp. Finally, Illumina Novaseq™6000 was used for paired-end sequencing according to standard operations, and the sequencing mode was PE150.

[0025] 3. Bioinformatics analysis 3.1 Quality control of raw data cDNA constructed from RNA extracted from samples using the Illumina Novaseq TM 6000 sequencing platform The library was sequenced using the Illumina PE-150 strategy. The original reads from the sequencer contain adapter sequences and some low-quality reads, which will affect subsequent data analysis. Therefore, in order to obtain high-quality reads, Use fastp (https: / / github.com / OpenGene / fastp, version: fastp-0.19.4) to further filter the reads. The parameters are as follows: 1) Remove the connector; 2) Remove reads containing polyA and polyG; 3) remove reads containing more than 5% N; 4) Remove low-quality reads, where low-quality (Q value ≤ 20) bases exceed 20%.

[0026] 3.2 Data comparison The HISAT2 (https: / / daehwankimlab.github.io / hisat2 / , version: hisat2-2.2.1) package was used to align the reads of all samples with the reference genome of the species under study. The reads were then mapped to the reference genome. HISAT2 allows multiple alignments per read (up to 20 by default) and allows up to two mismatches when mapping reads to the reference genome.

[0027] 3.3、Detection m 6 A modified region Exomepeak is used to predict the presence of m in the genome 6 A is a methylation-modified region with the following parameters: p_cutoff=1 p_adj_cutoff=NULL log2FC_cutoff=0 parallel=4 3.4 Difference m 6 A modification identification Exomepeak is also used to identify regions with different methylation modifications in the genome. The parameters are as follows: p_cutoff=1 p_adj_cutoff=NULL log2FC_cutoff=0 parallel=4 3.5. Annotation, distribution statistics, and motif identification of differentially expressed genes The peaks were annotated using ANNOVAR software, and then motif prediction was performed using HOMER software with the following parameters: -size 200 -len 5,8,10 3.6 Quantitative analysis of gene abundance The reads of each sample were assembled using StringTie (http: / / ccb.jhu.edu / software / stringtie / , version: stringtie-2.1.2) with default parameters. StringTie and ballgown (http: / / www.bioconductor.org / packages / release / bioc / html / ballgown.html) were used to estimate the expression levels of all transcripts, and the expression abundance of mRNA was analyzed by calculating the FPKM (fragments per kilobase of transcript per million reads) value.

[0028] 3.7. Analysis of Differentially Expressed Genes (DEGs) Differential gene analysis was performed using DESeq2 (edgeR was used without biological replicates). Genes with an absolute value of the difference fold greater than or equal to 2 and p less than 0.05 were considered to be significantly different. These significantly different genes were also the subject of KEGG and GO enrichment analysis in the next step.

[0029] 3.8 GO and KEGG enrichment analysis First, all differentially expressed genes were mapped to GO Terms in the Gene Ontology database (http: / / www.geneontology.org / ), the number of genes for each term was calculated, and the GO Terms that were significantly enriched in the differentially expressed genes compared with the genomic background were defined by the hypergeometric test. KEGG is a major public pathway-related database. Pathway enrichment analysis determines the metabolic pathways or signal transduction pathways that are significantly enriched in differentially expressed genes (DEGs) by comparing with the entire genomic background. GO Terms that meet the p<0.05 condition are defined as GO Terms that are significantly enriched in differentially expressed genes. Through this analysis, the main biological functions played by differentially expressed genes can be identified.

[0030] 3.9. Gene set enrichment analysis Gene set enrichment analysis was performed using GSEA software and MSigDB to determine whether a set of genes in a specific GO Terms or KEGG pathway showed significant differences between the two groups. Briefly, we input the gene expression matrix and sorted the genes by the Signal2Noise normalization method. Enrichment scores and p-values ​​were calculated under default parameters. GO Terms and KEGG pathways that met |NES|>1, NOM p-val<0.05, and FDR q-val<0.25 were considered to be different between the two groups.

[0031] 3.10. Variable splicing analysis The ASprofile software was used to identify variable splicing events and to count the number of various variable splicing events.

[0032] This embodiment provides a dengue virus m based on MeRIP-seq 6 A method for identifying and analyzing methylation modification sites. This method successfully extracted whole-genome RNA, constructed libraries for sequencing, used the HISAT2 software package to align the reads of all samples with the reference genome, and used exomepeak to predict the m 6 The method successfully extracted viral genomic RNA, mapped the reads to the reference genome using the HISAT2 software package, and identified six mRNAs of DENV-Ⅰ. 6 Peak A (as shown in Table 1, Figure 2 ) and DENV-Ⅱ 5 m 6 Peak A (as shown in Table 2, Figure 3 ).

Claims

1. A dengue virus mRNA based on MeRIP-seq 6 A methylation modification site identification and analysis method, including sample pretreatment, genomic RNA extraction, quality detection and sequencing, and data analysis, characterized in that: The method combines RNA immunoprecipitation and high-throughput sequencing technology, using specific anti-m 6 A antibody binding m 6 A modified RNA, and then sequence analysis was performed to achieve m 6 A recognition and localization of modifications; For whole transcriptome level m 6 A methylation analysis can provide information about m 6 ADistribution and abundance information of methylation sites in transcripts.

2. A dengue virus m based on MeRIP-seq as claimed in claim 1 6 A method for identifying and analyzing methylation modification sites, characterized in that: The steps include: (1) Viral RNA extraction: Extract RNA according to the instructions of the total RNA extraction kit; (2) Quality control: The extracted total RNA samples were separated and purified, and the total amount and purity of the total RNA were quality controlled using an ultra-micro spectrophotometer and verified by agarose gel electrophoresis. (3) Sequencing: Digestion removes ribosomal RNA from total RNA, fragments the remaining RNA, and combines it with immunomagnetic beads and mRNA. 6 A antibody was premixed in IP buffer and then immunoprecipitated; E. coli DNA polymerase I was then used to synthesize the second strand with ribonuclease H to convert the DNA and RNA composite double strands into DNA double strands, and dUTP Solution was added to the second strand to fill the ends of the double-stranded DNA into blunt ends; an A base was added to each end to enable it to connect to the adapter with a T base at the end, and then the size of the fragment was screened and purified using magnetic beads; the second strand was digested with UDG enzyme, and then PCR-pre-denaturation was performed to form a library with a fragment size of 300bp±50bp; (4) Bioinformatics analysis: Quality control and filtering of raw data obtained from high-throughput sequencing to remove low-quality sequences and adapter sequences; aligning the filtered data to the reference genome to determine m 6 A is the specific location of the modification site; detect the peak in the comparison result, i.e. m 6 A is the region where the modification site is located, and these peaks are annotated and distributed; m 6 A modification sites were compared and analyzed to identify differences 6 A modification site.

3. A dengue virus m based on MeRIP-seq as claimed in claim 2 6 A method for identifying and analyzing methylation modification sites, characterized in that: Step (4) Bioinformatics analysis uses fastp software to filter reads and remove some low-quality reads and low-quality bases.

4. A dengue virus m based on MeRIP-seq as claimed in claim 3 6 A method for identifying and analyzing methylation modification sites, characterized in that: In step (4), the HISAT2 software package is used to align the reads of all samples with the reference genome.

5. A dengue virus m based on MeRIP-seq as claimed in claim 4 6 A method for identifying and analyzing methylation modification sites, characterized in that: In step (4), exomepeak is used to predict the m 6 A. Methylated regions and identification of regions with differential methylation modifications in the genome.

6. A dengue virus m based on MeRIP-seq as claimed in claim 5 6 A method for identifying and analyzing methylation modification sites, characterized in that: In step (4), the peaks are annotated using ANNOVAR software, and then the peak motifs are predicted using HOMER software.

7. A dengue virus m based on MeRIP-seq as claimed in claim 6 6 A method for identifying and analyzing methylation modification sites, characterized in that: In step (4), DESeq2 was used when there were biological replicates, and edgeR was used for differential gene analysis when there were no biological replicates.

8. A dengue virus mRNA based on MeRIP-seq as claimed in claim 6 6 A method for identifying and analyzing methylation modification sites, characterized in that: Step (4) Finally, GSEA software and MSigDB were used to perform gene set enrichment analysis to determine whether a set of genes in a specific GOTerms or KEGG pathway showed significant differences between the two groups.

9. A dengue virus m based on MeRIP-seq as claimed in claim 2 6 A method for identifying and analyzing methylation modification sites, characterized in that: The ultra-micro spectrophotometer in step (2) is NanoDrop ND-1000.

10. A dengue virus m based on MeRIP-seq as claimed in claim 2 6 A method for identifying and analyzing methylation modification sites, characterized in that: The PCR-pre-denaturation described in step (3) is specifically as follows: hold at 95°C for 3 minutes, denature at 98°C for a total of 8 cycles of 15 seconds each, anneal to 60°C for 15 seconds, extend at 72°C for 30 seconds, and finally extend at 72°C for 5 minutes.

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