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Q-Nuc: a bioinformatics pipeline for the quantitative analysis of nucleosomal profiles

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Abstract

Nucleosomal profiling is an effective method to determine the positioning and occupancy of nucleosomes, which is essential to understand their roles in genomic processes. However, the positional randomness across the genome and its relationship with nucleosome occupancy remains poorly understood. Here we present a computational method that segments the profile into nucleosomal domains and quantifies their randomness and relative occupancy level. Applying this method to published data, we find on average ~ 3-fold differences in the degree of positional randomness between regions typically considered “well-ordered”, as well as an unexpected predominance of only two types of domains of positional randomness in yeast cells. Further, we find that occupancy levels between domains actually differ maximally by ~ 2–3-fold in both cells, which has not been described before. We also developed a procedure by which one can estimate the sequencing depth that is required to identify nucleosomal positions even when regional positional randomness is high. Overall, we have developed a pipeline to quantitatively characterize domain-level features of nucleosome randomness and occupancy genome-wide, enabling the identification of otherwise unknown features in nucleosomal organization.

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Acknowledgements

This work was supported by grants from National Basic Research Program of China (2018YFC1003501), the National Natural Science Foundation of China (Nos. 11374207, 31501054, 31670722, 31971151, 81627801 and 81972909) and the U.S. National Institutes of Health (R01CA204962 and R21AI126308 to J.L.).

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Authors and Affiliations

  1. State Key Laboratory for Oncogenes and Bio-ID Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Yuan Wang, Hua Li, Daniel M. Czajkowsky & Zhifeng Shao

  2. Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, 200240, China

    Qiu Sun

  3. Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, 60607, USA

    Jie Liang

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  1. Yuan Wang
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  3. Jie Liang
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  4. Hua Li
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Contributions

ZS conceived and designed the project. YW performed almost all of the data analysis. QS, JL and DMC performed some of the data analysis. YW, HL, DMC and ZS wrote the manuscript. DMC and ZS are senior authors of this manuscript. All authors read and approved the final manuscript.

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Correspondence to Hua Li or Daniel M. Czajkowsky.

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The authors have declared no competing interests.

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Wang, Y., Sun, Q., Liang, J. et al. Q-Nuc: a bioinformatics pipeline for the quantitative analysis of nucleosomal profiles. Interdiscip Sci Comput Life Sci 12, 69–81 (2020). https://doi.org/10.1007/s12539-019-00354-7

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