CPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Fehlmann, Tobias; Reinheimer, Stefanie; Geng, Chunyu; Su, Xiaoshan; Drmanac, Snezana; Alexeev, Andrei; Zhang, Chunyan; Backes, Christina; Ludwig, Nicole; Hart, Martin; An, Dan; Zhu, Zhenzhen; Xu, Chongjun; Chen, Ao; Ni, Ming; Liu, Jian; Li, Yuxiang; Poulter, Matthew; Li, Yongping; Stähler, Cord; Drmanac, Radoje; Xu, Xun; Meese, Eckart; Keller, Andreas
• Is Part Of: Clinical epigenetics. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 11
• Publication Date: 2016-12
• Subjects: Next-generation sequencing -- miRNA -- Biomarker discovery -- BGISEQ; Epigenesis -- Periodicals; Genetic regulation -- Periodicals; Human cytogenetics -- Periodicals; Human molecular genetics -- Periodicals; Cancer -- Genetic aspects -- Periodicals; 611.01816
• DOI: 10.1186/s13148-016-0287-1
• Languages: English
• ISSNs: 1868-7075

Abstract

Abstract Background We present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-basedBGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques. Results Starting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to themiRBase . Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood. Conclusions While there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.