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<p>Changes in gene regulation largely contribute to differences in cellular identities and phenotypes between species. Single-nucleus assays for transposase-accessible chromatin with sequencing (snATAC-seq) are an efficient strategy to identify putative gene regulatory elements and provide new insight into evolutionary divergence of regulatory programmes. However, no dedicated framework exists to integrate and compare snATAC-seq data across species, while methods designed for single-cell gene expression data have serious limitations. Here we present sPYce, a cross-species snATAC-seq integration method that relies on sequence composition similarities through <i>k</i>-mer histograms of regulatory regions, removing the need for genome alignments to anchor data from different species. sPYce can embed datasets from multiple species into the same mathematical space and permits further downstream analysis steps. We benchmarked sPYce against existing approaches on two publicly available datasets spanning more than 160 myr of evolution, showing that it successfully uncovers conserved cellular programmes while preserving biologically relevant species-specific differences. By comparing cerebellar development in mice and opossums, sPYce identifies regulatory divergence in granule cell differentiation programmes, particularly driven by nuclear factor 1. As an easy-to-use, alignment-free cross-species snATAC-seq integration approach, sPYce opens new perspectives to compare gene regulatory evolution across species.</p>

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Alignment-free integration of single-nucleus ATAC-seq across species with sPYce

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月2日

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  • Leo Zeitler,
  • Camille Berthelot

摘要

Changes in gene regulation largely contribute to differences in cellular identities and phenotypes between species. Single-nucleus assays for transposase-accessible chromatin with sequencing (snATAC-seq) are an efficient strategy to identify putative gene regulatory elements and provide new insight into evolutionary divergence of regulatory programmes. However, no dedicated framework exists to integrate and compare snATAC-seq data across species, while methods designed for single-cell gene expression data have serious limitations. Here we present sPYce, a cross-species snATAC-seq integration method that relies on sequence composition similarities through k-mer histograms of regulatory regions, removing the need for genome alignments to anchor data from different species. sPYce can embed datasets from multiple species into the same mathematical space and permits further downstream analysis steps. We benchmarked sPYce against existing approaches on two publicly available datasets spanning more than 160 myr of evolution, showing that it successfully uncovers conserved cellular programmes while preserving biologically relevant species-specific differences. By comparing cerebellar development in mice and opossums, sPYce identifies regulatory divergence in granule cell differentiation programmes, particularly driven by nuclear factor 1. As an easy-to-use, alignment-free cross-species snATAC-seq integration approach, sPYce opens new perspectives to compare gene regulatory evolution across species.