| Objective(s): 1.In order to better understand coronary heart disease(CAD)differentially expressed genes and their possible regulatory mechanisms,our research team intends to collect blood samples from atherosclerosis(AS)group and control group.These samples will be utilized for whole-transcriptome sequencing as well as bioinformatics analysis.2.Through bioinformatics analysis results,a target molecular axis was constructed,and in human coronary artery plaque tissue,CAD patient blood and macrophage foam cells,the RT-q PCR technology was used to observe and compare the gene expression in the target molecular axis: Lnc RNA AC005082.1/miR-1908-3p/SLC5A10.This novel hypothesis has the potential to clarify the mechanisms of AS and be the clinical diagnosis and treatment target of CAD.Methods:(1)Recruit patients who were hospitalized to the Second Affiliated Hospital of Kunming Medical University in October 2021 and had confirmed coronary artery AS by coronary angiography as the research participants.Among them,patients with coronary artery stenosis ≥ 50% were in the AS group,and patients with coronary artery without stenosis were in the control group.Trained personnel will collect blood samples for whole-transcriptome sequencing after informing the individuals about the study and obtaining their informed permission.(2)After the quality assessment and pre-processing of the original data,we have a tendency to use the clean data to bioinformatics analysis,which includes: A.The data from each sample was examined using the strategy of sequence similarity comparison to understand the factor varieties and their expression abundance,and the FPKM value was calculated using Cufflink’s software package after establishing a database with the known reference gene sequence and annotation file.Finally,the result of data is displayed using the box-plot,the FPKM value density curve,the FPKM value stacked column chart,correlation coefficient diagram,PCA diagram and cluster analysis diagram;B.Standardize the number of genes in each sample using DESeq2 software,compute the difference multiple,and examine the significance of the difference in gene expression level using the negative binomial distribution technique.The difference genes should next be screened using the results of the different multiple and different significance tests,and the selected genes should then be subjected to GO and KEGG enrichment analyses.C.Using the miRanda software,the target molecular axis is identified by analyzing the Lnc RNA-miRNA interaction and calculating the corresponding p value,extracting the first 300 miRNAs-Lnc RNA interaction pairs with low p values.Using the database targetscan 7.2 to predict the target m RNA in accordance with the miRNA list,and comparing the target m RNA with the list of differentially expressed protein-coding genes to determine the target molecular axis.(3)Using RT-q PCR,the gene expression in the target molecular axis in the human coronary artery plaque tissue,CAD patient blood and macrophage foam cells was examined and contrasted.Results:(1)Whole transcriptome sequencing yielded 144.34 G of clean data.The distribution of Q30 bases varied from 91.38% to 94.36%,and the effective data volume of each sample ranged from 10.79 G to 13.62 G.The results of the sequencing process were of high quality.(2)Protein-coding genes are expressed about at the same level in samples from each group,and gene expression is distributed somewhat normally,the correlation coefficient between the other samples is high,and has similar gene expression profiles.This data can be used for subsequent differential gene screening analysis.(3)The number of differentially expressed encoding genes were 164,of which 42 were up-regulated and 122 were down-regulated.The findings of the GO function analyses showed that 817 GO annotations were found for the differentially expressed coding genes,including 508 GO annotations for biological processes,139 GO annotations for cellular components,and 170 GO annotations for molecular functions;266 GO annotations were found for the differentially expressed up-regulated coding genes,including 143 GO annotations for biological processes,66 GO annotations for cellular components,and 57 GO annotations for molecular functions;654 GO annotations were found for the differentially expressed down-regulated coding genes,including 411 GO annotations for biological processes,106 GO annotations for cellular components,and 137 GO annotations for molecular functions.According to the finding of KEGG pathway enrichment analysis,189 pathways were overall enriched by the differentially expressed coding genes,42 pathways were overall enriched by the differentially expressed up-regulated coding genes,and 175 pathways were overall enriched by the differentially expressed down-regulated coding genes.(4)By integrating CPC,CNCI,PLEK and Pfam database’s Lnc RNA coding ability prediction results,it is found that 16720 Lnc RNAs may have protein coding ability.Lnc RNAs are expressed about at the same level in samples from each group,and gene expression is distributed somewhat normally,the correlation coefficient between the other samples is high,and has similar gene expression profiles.This data can be used for subsequent differential gene screening analysis.(5)The number of differentially expressed Lnc RNAs were 633,of which172 were up-regulated and 461 were down-regulated.The findings of the GO function analyses showed that 2002 GO annotations were found for the differentially expressed Lnc RNAs,including 1301 GO annotations for biological processes,320 GO annotations for cellular components,and 381 GO annotations for molecular functions;840 GO annotations found for the differentially expressed up-regulated Lnc RNAs,including 538 GO annotations for biological processes,160 GO annotations for cellular components,and 142 GO annotations for molecular functions;1615 GO annotations were found for the differentially expressed down-regulated Lnc RNAs,including 1024 GO annotations for biological processes,274 GO annotations for cellular components,and 317 GO annotations for molecular functions.According to the finding of KEGG pathway enrichment analysis,343 pathways were overall enriched by the differentially expressed Lnc RNAs,181 pathways were overall enriched by the differentially expressed up-regulated Lnc RNAs,and 301 pathways were overall enriched by the differentially expressed down-regulated Lnc RNAs.(6)According to the results of the Lnc RNA-miRNA interaction investigation,miR-1908-3p strongly interacted with the Lnc RNA-AC005082.1.It was discovered through the target m RNA prediction of miR-1908-3p that it had a targeted binding relationship with SLC5A10 that differentially expressed between AS group and control group.Validate the target molecular axis by combining the two results:Lnc RNA-AC005082.1miR-1908-3p/SLC5A10.(7)RT-q PCR results showed that compared with control group,Lnc RNA-AC005082.1 and m RNA-SLC5A10 were decreased in the human coronary artery plaque tissue,CAD patient blood and macrophage foam cells,and miR-1908-3p was increased in them.Conclusion(s): 1.164 protein-coding genes were differentially expressed in CAD patients compared to healthy individuals,42 of which were up-regulated and 122 of which were down-regulated.Besides,there also were 633 differentially expressed Lnc RNA,of which 172 were up-regulated and 461 were down-regulated;2.There is a targeted binding relationship between Lnc RNA AC005082.1 and miR-1908-3p,as well as between miR-1908-3p and m RNA SLC5A10.The target molecular axis is Lnc RNA AC005082.1/miR-1908-3p/SLC5A10;3.Lnc RNA-AC005082.1 and m RNA-SLC5A10 expression decreased in the human coronary artery plaque tissue,CAD patient blood and macrophage foam cells.miR-1908-3p expression increased in them.4.Lnc RNA-AC005082.1,miR-1908-3p and SLC5A10 are the potential targets for diagnosis and treatment of AS. |
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