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This work develops a computationally efficient method for approximating cline parameters for large number of loci, and applies it to genomic data from across a hybrid zone between flower colour varieties of Antirrhinum majus.
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Identification of the genomic regions that contribute to reproductive isolation and how they interact is a major goal of evolutionary genetics. Much effort has focused on locating candidate genes and potential barrier loci by scanning genomes for regions of excess differentiation (FST). An alternative, and perhaps more robust approach, is to scan for genomic regions exhibiting steep clines in allele frequency across a hybrid zone. We develop a computationally efficient method for approximating cline parameters for large number of loci, and apply it to genomic data from across a hybrid zone between flower colour varieties of Antirrhinum majus (A. m. m var. pseudomajus and A. m. m var. striatum). Most steep clines are clustered in seven genomic regions, only four of which were present from FST scans between all pair-wise comparisons. Six of these regions carry previously identified loci that influence flower colour in the hybrid zone. The seventh region harbours a novel locus, RUBIA, modifying magenta intensity. Clines at RUBIA approached fixation on the magenta side of the hybrid zone, whilst remaining polymorphic on the yellow side. This polymorphism on the yellow side may reflect a smaller phenotypic effect of RUBIA in yellow compared to magenta genetic backgrounds. Our findings illustrate how whole-genome cline scans in hybrid zones can robustly detect genomic regions contributing to phenotypic differences and highlight how different reproductive barrier loci interact across the genome.
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@article{Field2026Genome,
title = {Genome-wide cline analysis identifies new locus contributing to a barrier to gene flow across an Antirrhinum hybrid zone},
author = {David L. Field and Sean Stankowski and Taylor Reiter and Jitka Polechová and Desmond Bradley and Daniel R. Richardson and Arka Pal and Daria Shipilina and Louis Boell and Melinda Pickup and Yongbiao Xue and Enrico Coen and Nick Barton},
journal = {PLoS Genetics},
year = {2026},
doi = {10.1371/journal.pgen.1012173},
url = {https://doi.org/10.1371/journal.pgen.1012173}
}
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