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Simulation-based inference of yeast centromeres

Published: August 29, 2025 | arXiv ID: 2509.00200v1

By: Eloïse Touron , Pedro L. C. Rodrigues , Julyan Arbel and more

Potential Business Impact:

Finds hidden spots on chromosomes in yeast.

Business Areas:
Bioinformatics Biotechnology, Data and Analytics, Science and Engineering

The chromatin folding and the spatial arrangement of chromosomes in the cell play a crucial role in DNA replication and genes expression. An improper chromatin folding could lead to malfunctions and, over time, diseases. For eukaryotes, centromeres are essential for proper chromosome segregation and folding. Despite extensive research using de novo sequencing of genomes and annotation analysis, centromere locations in yeasts remain difficult to infer and are still unknown in most species. Recently, genome-wide chromosome conformation capture coupled with next-generation sequencing (Hi-C) has become one of the leading methods to investigate chromosome structures. Some recent studies have used Hi-C data to give a point estimate of each centromere, but those approaches highly rely on a good pre-localization. Here, we present a novel approach that infers in a stochastic manner the locations of all centromeres in budding yeast based on both the experimental Hi-C map and simulated contact maps.

Country of Origin
🇫🇷 France

Page Count
13 pages

Category
Statistics:
Machine Learning (Stat)