# Evidence of a genomic basis for growth rate variation in a natural kelp population

## TL;DR

This study shows that genetic differences can predict growth rates in a natural kelp population, offering insights into their ecological and breeding potential.

## Contribution

The study identifies specific genetic loci strongly associated with growth rate variation in a natural kelp population.

## Key findings

- Approximately half of the growth rate variation in kelp is predicted by 18 genetic loci.
- Most of these loci are expressed or linked to putative genes, though many genes have unknown functions.
- The findings suggest a genomic basis for growth rate variation with implications for kelp forest dynamics and aquaculture.

## Abstract

Understanding the genetic architecture of functional traits can provide key insights into the ecological dynamics and adaptive potential of species. We investigated whether genetic data can predict growth rate variation in a natural population of the widespread kelp, Ecklonia radiata. We tagged kelps and tracked their growth in situ over spring when growth is maximal. Individual kelps were then genotyped using reduced representation sequencing (ddRAD) and we employed multiple approaches to assess whether genetic variation corresponded with growth rate variation. Despite a limited sample size, we found evidence that growth rate can be strongly predicted from genetic variation, with approximately half of the variation in growth rate predicted by only 18 loci (R2 = 0.499). Leveraging published transcriptomic data, we confirm that most of these loci are expressed or are linked to expressed putative genes. However, many of these genes are of unknown function and do not match well-known gene families. These findings have important implications for understanding natural kelp forest dynamics and for applied approaches such as selective breeding and aquaculture. While our study offers an important first assessment of the possible genomic architecture underlying growth rate in E. radiata, future work is needed to confirm this apparent link between genetic and functional variation.

The online version contains supplementary material available at 10.1038/s41598-026-36286-8.