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

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 differe...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5117531/
https://www.ncbi.nlm.nih.gov/pubmed/27895807
http://dx.doi.org/10.1186/s13148-016-0287-1
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.