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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 engineeredcis-regulatory cryptic variants in a paralogous gene pair, we identified additional redundanttransregulators, establishing a regulatory network controlling tomato inflorescence architecture. By combining coding mutations withcis-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.
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This content will become publicly available on February 25, 2026
Cryptic variation fuels plant phenotypic change through hierarchical epistasis
ABSTRACT Cryptic genetic variants exert minimal or no phenotypic effects alone but have long been hypothesized to form a vast, hidden reservoir of genetic diversity that drives trait evolvability through epistatic interactions. This classical theory has been reinvigorated by pan-genome sequencing, which has revealed pervasive variation within gene families and regulatory networks, including extensive cis-regulatory changes, gene duplication, and divergence between paralogs. Nevertheless, empirical testing of cryptic variation’s capacity 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 recently evolved paralogous gene pair, we identified an additional pair of redundant trans regulators, establishing a regulatory network that controls tomato inflorescence architecture. By combining coding mutations with a cis-regulatory allelic series in populations segregating for all four network genes, we systematically constructed a collection of 216 genotypes spanning the full spectrum of inflorescence complexity and quantified branching in over 27,000 inflorescences. Analysis of the resulting high-resolution genotype-phenotype map revealed a layer of dose-dependent interactions within paralog pairs that enhances branching, culminating in strong, synergistic effects. However, we also uncovered an unexpected layer of antagonism between paralog pairs, where 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 paralog diversification converge to shape phenotypic space under a hierarchical model of epistatic interactions. Given the prevalence of paralog evolution in genomes, we propose that paralogous cryptic variation within regulatory networks elicits hierarchies of epistatic interactions, catalyzing bursts of phenotypic change. Keyword:cryptic mutations, paralogs, redundancy, cis-regulatory, tomato, inflorescence, gene regulatory network, modeling, epistasis
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- Award ID(s):
- 2216612
- PAR ID:
- 10590909
- Publisher / Repository:
- bioRxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- bioRxiv
- Sponsoring Org:
- National Science Foundation
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