Cryptic variation fuels plant phenotypic change through hierarchical epistasis

Sophia G. Zebell, Carlos Martí-Gómez, Blaine Fitzgerald, Camila P. Cunha, Michael Lach, Brooke M. Seman, Anat Hendelman, Simon Sretenovic, Yiping Qi, Madelaine Bartlett, Yuval Eshed (), David M. McCandlish () and Zachary B. Lippman ()
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Sophia G. Zebell: Cold Spring Harbor Laboratory
Carlos Martí-Gómez: Cold Spring Harbor Laboratory
Blaine Fitzgerald: Cold Spring Harbor Laboratory
Camila P. Cunha: Weizmann Institute of Science
Michael Lach: Weizmann Institute of Science
Brooke M. Seman: Cold Spring Harbor Laboratory
Anat Hendelman: Cold Spring Harbor Laboratory
Simon Sretenovic: University of Maryland
Yiping Qi: University of Maryland
Madelaine Bartlett: Sainsbury Laboratory Cambridge University (SLCU)
Yuval Eshed: Weizmann Institute of Science
David M. McCandlish: Cold Spring Harbor Laboratory
Zachary B. Lippman: Cold Spring Harbor Laboratory

Nature, 2025, vol. 644, issue 8078, 984-992

Abstract: Abstract Cryptic genetic variants exert minimal phenotypic effects alone but are hypothesized to form a vast reservoir of genetic diversity driving trait evolvability through epistatic interactions1–3. This classical theory has been reinvigorated by pan-genomics, which is revealing pervasive variation within gene families, cis-regulatory regions and regulatory networks4–6. Testing the ability of cryptic variation to fuel phenotypic diversification has been hindered by intractable genetics, limited allelic diversity and inadequate phenotypic resolution. Here, guided by natural and engineered cis-regulatory cryptic variants in a paralogous gene pair, we identified additional redundant trans regulators, establishing a regulatory network controlling tomato inflorescence architecture. By combining coding mutations with cis-regulatory alleles in populations segregating for all four network genes, we generated 216 genotypes spanning a wide spectrum of inflorescence complexity and quantified branching in over 35,000 inflorescences. Analysis of this high-resolution genotype–phenotype map using a hierarchical model of epistasis revealed a layer of dose-dependent interactions within paralogue pairs enhancing branching, culminating in strong, synergistic effects. However, we also identified a layer of antagonism between paralogue pairs, whereby accumulating mutations in one pair progressively diminished the effects of mutations in the other. Our results demonstrate how gene regulatory network architecture and complex dosage effects from paralogue diversification converge to shape phenotypic space, producing the potential for both strongly buffered phenotypes and sudden bursts of phenotypic change.

Date: 2025
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DOI: 10.1038/s41586-025-09243-0

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