Cryptic variation fuels plant phenotypic change through hierarchical epistasis

Area of Science:

• Genetics
• Evolutionary Biology
• Plant Biology

Background:

• Cryptic genetic variants are hypothesized to be a reservoir for trait evolvability via epistasis.
• Pan-genome sequencing reveals extensive variation in gene families and regulatory networks, including paralogs.
• Empirical testing of cryptic variation has been limited by genetic complexity and phenotypic resolution.

Purpose of the Study:

• To investigate the role of cryptic variation in paralogous gene pairs in controlling phenotypic complexity.
• To establish a gene regulatory network controlling tomato inflorescence architecture using natural and engineered variants.
• To systematically analyze genotype-phenotype relationships across a spectrum of inflorescence complexity.

Main Methods:

• Identification of redundant trans regulators forming a network with paralogous cis-regulatory variants.
• Construction of 216 genotypes combining coding mutations and cis-regulatory allelic series.
• Quantification of inflorescence branching in over 27,000 inflorescences to build a high-resolution map.

Main Results:

• Discovered dose-dependent, synergistic interactions within paralog pairs enhancing branching.
• Uncovered antagonistic interactions between paralog pairs, where mutations in one pair reduced the effects of the other.
• Demonstrated how gene regulatory network architecture and paralog diversification shape phenotypic space through hierarchical epistasis.

Conclusions:

• Paralogous cryptic variation within regulatory networks can drive phenotypic change through hierarchical epistasis.
• Gene regulatory network architecture and complex dosage effects from paralog diversification are key to shaping phenotypic space.
• This model provides insight into how hidden genetic variation can catalyze bursts of phenotypic evolution, particularly given the prevalence of paralog evolution.