Data from: Co-inheritance of sea age at maturity and iteroparity in the Atlantic salmon vgll3 genomic region
Aykanat, Tutku et al. (2019), Data from: Co-inheritance of sea age at maturity and iteroparity in the Atlantic salmon vgll3 genomic region, Dryad, Dataset, https://doi.org/10.5061/dryad.7nt676d
Co-inheritance in life history traits may result in unpredictable evolutionary trajectories if not accounted for in life-history models. Iteroparity (the reproductive strategy of reproducing more than once) in Atlantic salmon (Salmo salar) is a fitness trait with substantial variation within and among populations. In the Teno River in northern Europe, iteroparous individuals constitute an important component of many populations and have experienced a sharp increase in abundance in the last 20 years, partly overlapping with a general decrease in age structure. The physiological basis of iteroparity bears similarities to that of age at first maturity, another life history trait with substantial fitness effects in salmon. Sea age at maturity in Atlantic salmon is controlled by a major locus around the vgll3 gene, and we used this opportunity demonstrate that these two traits are co-inherited around this genome region. The odds ratio of survival until second reproduction was up to 2.4 (1.8-3.5 90% CI) times higher for fish with the early-maturing vgll3 genotype (EE) compared to fish with the late-maturing genotype (LL). The L allele was dominant in individuals remaining only one year at sea before maturation, but the dominance was reversed, with the E allele being dominant in individuals maturing after two or more years at sea. Post hoc analysis indicated that iteroparous fish with the EE genotype had accelerated growth prior to first reproduction compared to first-time spawners, across all age groups, while this effect was not detected in fish with the LL genotype. These results broaden the functional link around the vgll3 genome region and help us understand constraints in the evolution of life history variation in salmon. Our results further highlight the need to account for genetic correlations between fitness traits when predicting demographic changes in changing environments.