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Clin Epigenetics. 2016 Nov 21;8:123. eCollection 2016.

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs.

Author information

1
Clinical Bioinformatics, Saarland University, 66125 Saarbrücken, Germany.
2
Department of Human Genetics, Saarland University, Saarbrücken, Germany.
3
BGI-Shenzhen, Shenzhen, China.
4
BGI-Shenzhen, Shenzhen, China ; Complete Genomics (a BGI company), Mountain View, CA USA.

Abstract

BACKGROUND:

We present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-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 the miRBase. 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.

KEYWORDS:

BGISEQ; Biomarker discovery; Next-generation sequencing; miRNA

PMID:
27895807
PMCID:
PMC5117531
DOI:
10.1186/s13148-016-0287-1
[Indexed for MEDLINE]
Free PMC Article

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