Deciphering the genetic basis of phytoplankton traits through genome-wide association studies
Abstract
Abstract While marine genomic databases are rapidly expanding through large-scale sequencing programs, the functional characterization of these genomes progresses slowly and remains a major scientific challenge. In this study, we applied a Genome-Wide Association Study (GWAS) approach to identify and investigate genomic loci without a priori assumptions. The microalga Tisochrysis lutea was selected as a case study due to its economic importance and the extensive knowledge accumulated over the years. Particular attention was paid to pigment and lipid metabolism due to their high commercial value. To implement the GWAS approach, a collection of 100 algal lineages was established from 15 available polyclonal strains. This collection was then phenotyped under two different culture conditions. Of the 31 phenotypic traits investigated, 18 met the requirements for GWAS analysis. Concurrently, each algal lineage was genotyped by whole-genome sequencing to inventory all genetic polymorphisms. A mixed model was applied, revealing 13 significant associations between phenotypic traits and alleles. These associations highlight previously unsuspected genomic loci that play a major role in pigment or lipid content. The candidate genes identified at these loci may have a direct or indirect role in these metabolic pathways. Nevertheless, elucidating the precise molecular mechanisms of the associated genes remains limited without the implementation of functional approaches. Despite the complexity of the process, we conclude that the GWAS approach is an effective strategy for exploring phytoplankton genomes, particularly for quantitative traits of interest. Ideally, this approach should be combined with other functional methods to progressively characterize marine genomes.
Fields of Study & Subjects
Genetic Mapping and Diversity in Plants and Animals
Genetic and phenotypic traits in livestock
Algal biology and biofuel production
Publication details
- Journal / source
- bioRxiv (Cold Spring Harbor Laboratory)
- Publication date
- 27 February 2026
- Language
- EN
- Document type
- Preprint