Scalable eQTL mapping using single-nucleus RNA-sequencing of recombined gametes from a small number of individuals
Phenotypic differences between individuals of a species are often caused by differences in gene expression, which are in turn caused by genetic variation. Expression quantitative trait locus (eQTL) analysis is a methodology by which we can identify such causal variants. Scaling eQTL analysis is costly due to the expense of generating mapping populations, and the collection of matched transcriptomic and genomic information. We developed a rapid eQTL analysis approach using single-cell/nucleus RNA sequencing of gametes from a small number of heterozygous individuals. Patterns of inherited polymorphisms are used to infer the recombinant genomes of thousands of individual gametes and identify how different haplotypes correlate with variation in gene expression. Applied to Arabidopsis pollen nuclei, our approach uncovers both cis- and trans-eQTLs, ultimately mapping variation in a master regulator of sperm cell development that affects the expression of hundreds of genes. This establishes snRNA-sequencing as a powerful, cost-effective method for the mapping of meiotic recombination, addressing the scalability challenges of eQTL analysis and enabling eQTL mapping in specific cell-types.
Authors
- José Antonio Campoy (ORCID: https://orcid.org/0000-0002-6018-5698)
- Korbinian Schneeberger (ORCID: https://orcid.org/0000-0002-5512-0443)
- Sergio Tusso (ORCID: https://orcid.org/0000-0002-0612-9230)
- Magdalena Marek (ORCID: https://orcid.org/0000-0001-6901-920X)
- Samija Amar (ORCID: https://orcid.org/0000-0001-7811-1614)
- Matthew T Parker (ORCID: https://orcid.org/0000-0002-0891-8495)
- Kristin S Krause (ORCID: https://orcid.org/0000-0001-9908-7035)
- Bruno Hüettel (ORCID: https://orcid.org/0000-0001-7165-1714)
Institutions
- Cluster of Excellence on Plant Sciences (DE)
- Max Planck Institute for Plant Breeding Research (DE)
- Max Planck Graduate Center (DE)
- Heinrich Heine University Düsseldorf (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- PLoS Biology
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1371/journal.pbio.3003085
- Citations
- 3
- Primary Topic
- Chromosomal and Genetic Variations
- Type
- article
- Field-Weighted Citation Impact
- 5.25
Funders
- Deutsche Forschungsgemeinschaft
- H2020 European Research Council