Wang Xian-min, Zhang Kui, Li Yan, Shi Kun, Liu Yi-ling, Yang Yan-feng, Fang Yu, Mao Meng
1 Department of Padiatric Cardiology, Chengdu Women's and Children's Central Hospital, Chengdu, Sichuan Province, People's Republic of China.
2 Department of Forensic Medicine, Zun Yi Medical College, Zunyi, People's Republic of China.
Cardiol Young. 2014 Jun;24(3):442-6. doi: 10.1017/S104795111300053X. Epub 2013 May 17.
Our aim is to screen miRNAs and genes related to tetralogy of Fallot and construct a co-expression network based on integrating miRNA and gene microarrays. We downloaded the gene expression profile GSE35490 (miRNA) and GSE35776 (mRNA) of tetralogy of Fallot from the Gene Expression Omnibus database, which includes eight normal and 15 disease samples from infants, and screened differentially expressed miRNAs and genes between normal and disease samples (cut-off: p < 0.05; FDR < 0.05; and log FC > 2 or log FC < -2); in addition, we downloaded human miRNA and their targets, which were collected in the miRNA targets prediction database TargetScan, and selected ones that also appeared in our differentially expressed miRNAs and their predicted targets (score >0.9) and then made a relationship of diff_miRNAs and diff_genes of our results. Finally, we uploaded all the diff_target genes into String, constructed a co-expression network regulated by diff_miRNAs, and performed functional analysis with the software DAVID. Comparing normal and disease lesion tissue, we got 32 and 875 differentially expressed miRNAs and genes, respectively, and found hsa-miR-124 with 34 diff_target genes and hsa-miR-138 with two diff_target genes. Then we constructed a co-expression network that contains 231 pairs of genes. Genes in the network were enriched into 14 function clusters, and the most significant one is protein localisation. We screened the tetralogy of Fallot-related hsa-miR-124 and hsa-miR-138 with their direct and indirect differentially expressed target genes, and found that protein localisation is the significant cause affecting tetralogy of Fallot. Our approach may provide the groundwork for a new therapy approach to treating tetralogy of Fallot.
我们的目标是筛选与法洛四联症相关的微小RNA（miRNA）和基因，并基于整合miRNA和基因微阵列构建共表达网络。我们从基因表达综合数据库下载了法洛四联症的基因表达谱GSE35490（miRNA）和GSE35776（mRNA），其中包括来自婴儿的8个正常样本和15个疾病样本，并筛选了正常样本和疾病样本之间差异表达的miRNA和基因（截断值：p < 0.05；FDR < 0.05；log FC > 2或log FC < -2）；此外，我们下载了在miRNA靶标预测数据库TargetScan中收集的人类miRNA及其靶标，并选择那些也出现在我们差异表达的miRNA及其预测靶标中的（得分>0.9），然后建立我们结果中差异miRNA和差异基因的关系。最后，我们将所有差异靶基因上传到String，构建由差异miRNA调控的共表达网络，并用DAVID软件进行功能分析。比较正常和疾病病变组织，我们分别得到了32个和875个差异表达的miRNA和基因，发现hsa-miR-124有34个差异靶基因，hsa-miR-138有2个差异靶基因。然后我们构建了一个包含231对基因的共表达网络。网络中的基因富集到14个功能簇中，最显著的是蛋白质定位。我们筛选了与法洛四联症相关的hsa-miR-124和hsa-miR-138及其直接和间接差异表达的靶基因，发现蛋白质定位是影响法洛四联症的重要原因。我们的方法可能为法洛四联症的新治疗方法奠定基础。
