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coelsch: Platform-agnostic single-cell analysis of meiotic recombination events

Parker, M. T.; Amar, S.; Freudigmann, J.; Walkemeier, B.; Dong, X.; Solier, V.; Marek, M.; Huettel, B.; Mercier, R.; Schneeberger, K.

2026-02-04 bioinformatics
10.64898/2026.02.02.701279 bioRxiv
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BackgroundMeiotic recombination creates genetic diversity through reciprocal exchange of haplotypes between homologous chromosomes. Scalable and robust methods for mapping recombination breakpoints are essential for understanding meiosis and for genetic mapping. Single cell sequencing of gametes offers a direct approach to recombination mapping, yet the effect of technical differences between single-cell sequencing methods for crossover detection remains unclear. ResultsWe benchmark single cell methods for droplet-based chromatin accessibility and RNA sequencing and plate-based whole-genome amplification for mapping meiotic recombination in Arabidopsis thaliana. For this purpose we introduce two novel open-source tools coelsch_mapping_pipeline and coelsch for haplotype-aware alignment and per-cell crossover detection, using them to recover known recombination frequencies and quantify the effects of coverage sparsity. We subsequently apply our approach to a panel of 40 recombinant F hybrids derived from crosses of 22 diverse natural accessions, successfully recovering genetic maps for 34 F1s in a single dataset. This analysis reveals substantial variation in recombination rate and identifies a [~]10 Mb pericentric inversion in the accession Zin-9, the largest natural inversion reported in A. thaliana to date. ConclusionsThese results demonstrate the applicability and scalability of single-cell gamete sequencing for high-throughput mapping of meiotic recombination, and highlight the strengths and limitations of different single-cell modalities. The accompanying open-source tools provide a framework for haplotyping and crossover detection analysis using sparse single-cell sequencing data. Our methodology enables parallel analysis of large numbers of hybrids in a single dataset, removing a major technical barrier to large-scale studies of natural variation in recombination rate.

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