bioRxivEvolutionary Biology
Extreme copy number variation at a tRNA ligase affecting phenology and fitness in yellow monkeyflowers
T. C. Nelson, P. Monnahan, M. McIntosh, F. Finseth, K. Anderson, E. Macarthur-Waltz, J. K. Kelly, L. Fishman
Abstract
Copy number variation (CNV) is a major part of the genetic diversity segregating within populations, but remains poorly understood relative to single nucleotide variation. Here, we report on a tRNA ligase gene (Migut.N02091; RLG1a) exhibiting unprecedented, and fitness-relevant, CNV within an annual population of the yellow monkeyflower Mimulus guttatus. RLG1a variation was associated with multiple traits in pooled population sequencing (PoolSeq) scans of phenotypic and phenological cohorts. Resequencing of inbred lines revealed intermediate frequency three-copy variants of RLG1a (trip+; 5/35 = 14%), and trip+ lines exhibited elevated RLG1a expression under multiple conditions. trip+ carriers, in addition to being over-represented in late-flowering and large-flowered PoolSeq populations, flowered later under stressful conditions in a greenhouse experiment (P < 0.05). In wild population samples, we discovered an additional rare RLG1a variant (high+) that carries 250-300 copies of RLG1a totaling [~]5.7Mb (20-40% of a chromosome). In the progeny of a high+ carrier, Mendelian segregation of diagnostic alleles and qPCR-based copy counts indicate that high+ is a single tandem array unlinked from the single copy RLG1a locus. In the wild, high+ carriers had highest fitness in two particularly dry and/or hot years (2015 and 2017; both p < 0.01), while single copy individuals were twice as fecund as either CNV type in a lush year (2016: p < 0.005). Our results demonstrate fluctuating selection on CNVs affecting phenological traits in a wild population, suggest that plant tRNA ligases mediate stress-responsive life-history traits, and introduce a novel system for investigating the molecular mechanisms of gene amplification.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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