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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 April 3, 2026
Solanum pan-genetics reveals paralogues as contingencies in crop engineering
Abstract Pan-genomics and genome-editing technologies are revolutionizing breeding of global crops1,2. A transformative opportunity lies in exchanging genotype-to-phenotype knowledge between major crops (that is, those cultivated globally) and indigenous crops (that is, those locally cultivated within a circumscribed area)3–5to enhance our food system. However, species-specific genetic variants and their interactions with desirable natural or engineered mutations pose barriers to achieving predictable phenotypic effects, even between related crops6,7. Here, by establishing a pan-genome of the crop-rich genusSolanum8and integrating functional genomics and pan-genetics, we show that gene duplication and subsequent paralogue diversification are major obstacles to genotype-to-phenotype predictability. Despite broad conservation of gene macrosynteny among chromosome-scale references for 22 species, including 13 indigenous crops, thousands of gene duplications, particularly within key domestication gene families, exhibited dynamic trajectories in sequence, expression and function. By augmenting our pan-genome with African eggplant cultivars9and applying quantitative genetics and genome editing, we dissected an intricate history of paralogue evolution affecting fruit size. The loss of a redundant paralogue of the classical fruit size regulatorCLAVATA3(CLV3)10,11was compensated by a lineage-specific tandem duplication. Subsequent pseudogenization of the derived copy, followed by a large cultivar-specific deletion, created a single fusedCLV3allele that modulates fruit organ number alongside an enzymatic gene controlling the same trait. Our findings demonstrate that paralogue diversifications over short timescales are underexplored contingencies in trait evolvability. Exposing and navigating these contingencies is crucial for translating genotype-to-phenotype relationships across species.
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- Award ID(s):
- 2216612
- PAR ID:
- 10590903
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Nature
- Date Published:
- Journal Name:
- Nature
- Volume:
- 640
- Issue:
- 8057
- ISSN:
- 0028-0836
- Page Range / eLocation ID:
- 135 to 145
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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