Shanliang Zhong1, Siying Zhou2, Sujin Yang3, Xinnian Yu4, Hanzi Xu5, Jinyan Wang3, Qian Zhang3, Mengmeng Lv6, Jifeng Feng7. 1. Center of Clinical Laboratory Science, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, 210009, China. 2. The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, China. 3. Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 211166, China. 4. Department of Medical Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, 210009, China. 5. Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, 210009, China. 6. Department of Gynecologic Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, 210009, China. 7. Department of Medical Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, 210009, China. feng_jifeng@sina.com.
Abstract
OBJECTIVE: At present, no studies have established internal control genes for circular RNA (circRNA) analyses. We aimed to identify reference circRNAs for real-time quantitative PCR (RT-qPCR). RESULTS: After analyzing the RNA-seq data, we obtained 50 circRNAs that were expressed in all samples. We ranked these 50 circRNAs according to their stability and obtained the six most stable circRNAs. We further evaluated the stability of the six circRNAs and three linear control genes (i.e., GAPDH, β-actin and 18S rRNA) in 22 cell lines. Our results indicated that hsa_circ_0000284 (circHIPK3) and hsa_circ_0000471 (circN4BP2L2) were the two most stable genes. After removing linear RNAs or including the cells treated with Adriamycin, NH4Cl and shikonin, the two most stable genes were hsa_circ_0000471 and hsa_circ_0000284. The amplification efficiency was 100% for hsa_circ_0000471 and 95% for hsa_circ_0000284. CONCLUSIONS: In conclusion, since the stability of circRNAs is higher than that of linear RNAs, hsa_circ_0000284 and hsa_circ_0000471 may be used as reference genes not only for circRNAs but also for other kinds of RNAs. The findings in the present study fill the gap of lacking reference genes in the detection of circRNAs.
OBJECTIVE: At present, no studies have established internal control genes for circular RNA (circRNA) analyses. We aimed to identify reference circRNAs for real-time quantitative PCR (RT-qPCR). RESULTS: After analyzing the RNA-seq data, we obtained 50 circRNAs that were expressed in all samples. We ranked these 50 circRNAs according to their stability and obtained the six most stable circRNAs. We further evaluated the stability of the six circRNAs and three linear control genes (i.e., GAPDH, β-actin and 18S rRNA) in 22 cell lines. Our results indicated that hsa_circ_0000284 (circHIPK3) and hsa_circ_0000471 (circN4BP2L2) were the two most stable genes. After removing linear RNAs or including the cells treated with Adriamycin, NH4Cl and shikonin, the two most stable genes were hsa_circ_0000471 and hsa_circ_0000284. The amplification efficiency was 100% for hsa_circ_0000471 and 95% for hsa_circ_0000284. CONCLUSIONS: In conclusion, since the stability of circRNAs is higher than that of linear RNAs, hsa_circ_0000284 and hsa_circ_0000471 may be used as reference genes not only for circRNAs but also for other kinds of RNAs. The findings in the present study fill the gap of lacking reference genes in the detection of circRNAs.
Entities:
Keywords:
Circular RNAs; Control genes; Normalization genes; circHIPK3; circN4BP2L2; circRNAs