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Tracking miRNA precursor metabolic products and processing sites through completely analyzing high-throughput sequencing data

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Abstract

The small non-coding important regulatory molecules, microRNAs (miRNAs), have been widely and deeply studied especially combining high-throughput sequencing technologies. Here, we attempted to track detailed miRNA precursor metabolic products and gain further insight into pre-miRNA processing by completely analyzing high-throughput sequencing data. Highly expressed miRNA precursors could be entirely covered by various short RNAs and small RNA fragments with a hierarchical distribution. miRNAs and some miRNA* regions were detected quite abundant short RNAs as expected, while other regions of precursors were found shorter RNAs or small fragments with fewer sequence counts. Furthermore, we developed a method to analyze relative expression levels of special RNA classes according to divergence of 5′ and 3′ ends, respectively. Generally, there were several quite abundant RNA classes from a given miRNA locus, which suggested dominant cleavage sites of Drosha and Dicer during pre-miRNA processing. Compared with 3′ end, dominant cleavage site in 5′ end always focused on a specific position, which ensured conservation of the identity of miRNA (5′-seed sequence, nucleotides 2–8). Overall, a comprehensive analysis of sequencing data can be used to track pre-miRNA metabolic products and mechanism of pre-miRNA processing and metabolism.

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Acknowledgments

This work was supported by projects 30871393, 30900836 and 60971021 of the National Natural Science Foundation of China and funded by Tsinghua National Laboratory for Information Science and Technology (TNList) Cross-discipline Foundation. The work was also supported by a research grant from the Innovation Project for Graduate Students of Jiangsu Province (No. CX10B_081Z), the Scientific Research Foundation of Graduate School of Southeast University, science & technology project in Nanjing (201001095) and pre-research Project for National Natural Science Foundation Supported by Southeast University (KJ2010442). The authors have declared that no competing interests exist.

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Authors and Affiliations

  1. State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China

    Li Guo, Hailing Li, Jiafeng Lu, Qi Yang, Yunfei Bai & Zuhong Lu

  2. Key Laboratory of Child Development and Learning Science of Ministry of Education, Southeast University, Nanjing, 210096, China

    Qinyu Ge, Wanjun Gu & Zuhong Lu

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  1. Li Guo
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  2. Hailing Li
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  3. Jiafeng Lu
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  4. Qi Yang
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  5. Qinyu Ge
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  6. Wanjun Gu
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  7. Yunfei Bai
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  8. Zuhong Lu
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Corresponding authors

Correspondence to Li Guo or Zuhong Lu.

Additional information

Li Guo and Hailing Li contributed equally to this work.

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11033_2011_950_MOESM1_ESM.tif

Fig. S1. An example of tracking miRNA precursor metabolic products based on high-throughput sequencing. Accurate mapping is performed using Bowtie, and short RNAs are not showed here if their sequence counts are less than 10. Two distinct regions that can yield hsa-miR-24 and hsa-miR-24-2* are accumulated with various short RNAs with various 5′ and/or 3′ ends, and these called multiple isomiRs always are detected with higher copy numbers. Other regions of hsa-mir-24 also can be detected all kinds of mutual overlapping shorter RNAs (especially shorter RNAs with 6 nt length). In fact, we can track detailed metabolic process with continuous lengths of short RNAs, but short RNAs more than 6 nt length always have fewer sequence counts. (TIFF 80 kb)

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Guo, L., Li, H., Lu, J. et al. Tracking miRNA precursor metabolic products and processing sites through completely analyzing high-throughput sequencing data. Mol Biol Rep 39, 2031–2038 (2012). https://doi.org/10.1007/s11033-011-0950-8

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  • DOI: https://doi.org/10.1007/s11033-011-0950-8

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