Automated annotation of human centromeres with HORmon
- Olga Kunyavskaya1,
- Tatiana Dvorkina1,
- Andrey V. Bzikadze2,
- Ivan A. Alexandrov1 and
- Pavel A. Pevzner3
- 1Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia, 199034;
- 2Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, California 92093, USA;
- 3Department of Computer Science and Engineering, University of California, San Diego, California 92093, USA
Abstract
Recent advances in long-read sequencing opened a possibility to address the long-standing questions about the architecture and evolution of human centromeres. They also emphasized the need for centromere annotation (partitioning human centromeres into monomers and higher-order repeats [HORs]). Although there was a half-century-long series of semi-manual studies of centromere architecture, a rigorous centromere annotation algorithm is still lacking. Moreover, an automated centromere annotation is a prerequisite for studies of genetic diseases associated with centromeres and evolutionary studies of centromeres across multiple species. Although the monomer decomposition (transforming a centromere into a monocentromere written in the monomer alphabet) and the HOR decomposition (representing a monocentromere in the alphabet of HORs) are currently viewed as two separate problems, we show that they should be integrated into a single framework in such a way that HOR (monomer) inference affects monomer (HOR) inference. We thus developed the HORmon algorithm that integrates the monomer/HOR inference and automatically generates the human monomers/HORs that are largely consistent with the previous semi-manual inference.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.276362.121.
- Received November 3, 2021.
- Accepted May 6, 2022.
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