# Simulation-based inference of yeast centromeres

## TL;DR

This paper introduces a novel stochastic method for inferring yeast centromere locations using Hi-C data and simulated contact maps, addressing the challenge of unknown centromere positions in many species.

## Contribution

It presents a new approach combining experimental Hi-C data with simulations to accurately locate centromeres in yeast genomes.

## Key findings

- Successfully infers centromere locations in budding yeast
- Combines experimental and simulated data for improved accuracy
- Addresses limitations of previous point-estimate methods

## Abstract

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.