Author Identifiers
Nicole Said’s ORCID record 
Ankje Frouws’s ORCID record Kathryn McMahon’s ORCID record
Publication Date
2026
Document Type
Dataset
Publisher
Edith Cowan University
School or Research Centre
School of Science / Centre for Marine Ecosystems Research (CMER) / Centre for People Place and Planet
Funders
This research was supported through the Western Australian Marine Science Institute, Westport Marine Science Program and an Australian Research Council grant.
Grant Number
ARC Number: DP210101932
Grant Link
https://wamsi.org.au/research_themes/benthic-communities-and-habitats/ https://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP210101932
Description
Seagrasses are flowering plants commonly found along coastal waters, globally, where they provide important ecosystem services such as habitat provision, sequestering carbon, and sediment stabilization. They can reproduce both clonally and sexually where sexual reproduction can result in new, potentially adaptive, variants and the existence of both reproductive methods means that meadows can be highly variable in clonal diversity. The temperate seagrass, Posidonia sinuosa, occurs across a latitudinal gradient along the Western Australian coastline. Some meadows have experienced significant decline as a result of industrialisation and urbanisation of coastal areas. We investigated spatial genetic diversity, structure, and local adaptation using genomic markers through ddRAD-seq. Thirty Posidonia sinuosa meadows were sampled across its latitudinal range on the west coast of Australia between Geraldton and Geographe Bay. Sites were selected to cover a temperature and depth range and where long-term monitoring of seagrass condition has occurred. The data set contains 7,777 SNPS for 287 individuals across 28 seagrass meadows after bioinformatic filtering. All meadows had similarly low levels of genetic diversity, with high levels of inbreeding. Weak genetic structure across the latitudinal gradient was consistent with genetic connectivity, enabled by sea-surface seed dispersal. Approximately 6.1% of markers were identified as putatively adaptive and most were associated with temperature variables. Allelic turnover was associated with a < 1.4 C temperature change, suggesting plants may be sensitive to small temperature changes. Meadows are currently growing in temperatures below their thermal optima, suggesting they may be able to tolerate future projected temperatures up to a point. They are unlikely to tolerate current projections for 2100, which equate to +3.2 C, in addition to extreme heatwave events. Conservation of fragmented, northern, warmer-adapted meadows will be important to assist recovery and persistence of damaged meadows into the future, as translocation of putatively warmer-adapted genotypes between meadows that have exhibited historic connectivity may be a viable strategy for restoration of impacted higher latitude meadows.
Research Activity Title
WAMSI Project 2.2. Pressure-response relationships, building resilience and future proofing seagrass
Research Activity Description
This study focused on understanding genetic diversity and connectivity in the Posidonia sinuosa seagrass populations along the west coast of Western Australia, as part of Project 2.2 ‘Building Resilience and Future Proofing Seagrass Meadows’. Seagrass meadows were sampled across the latitudinal gradient from Geraldton (northern range edge) to Geographe Bay (southernmost meadows on the west coast) between May and December 2022. Sampling was clustered in three geographic areas (northern, central, southern) and included long term seagrass monitoring sites, with greater intensity of sampling conducted within the Cockburn Sound area at a range of depths (1.2 - 11.8 m). A population genomics approach was undertaken to assess levels of diversity within meadows (including clonal diversity), patterns of genetic structure among meadows (admixture and gene flow), and discovery of putative adaptive variants associated with local environmental conditions (local adaptation). These data will provide important baseline information for understanding patterns of genetic diversity in natural P. sinuosa meadows along the west coast, as well as enable informed decisions for incorporating resilience into future seagrass restoration activities.
Methodology
13-26 seagrass shoots were collected on SCUBA from 30 P. sinuosa meadows. Genomic DNA was extracted from frozen shoot meristems using a Qiagen DNeasy Plant Pro Kit and processed through double digest restriction-site associated sequencing (ddRAD-seq) by AGRF and ran through a bioinformatics pipeline for genome assembly, resulting in the raw dataset. Subsequently, raw data was filtered based on loci quality and percentage missing data through an additional pipeline, resulting in the final dataset used for analyses. Both the raw and filtered datasets are provided here.
Start of data collection time period
2022
End of data collection time period
2022
Research Project Links
https://wamsi.org.au/research_themes/benthic-communities-and-habitats/
Codes
File: METADATA.csv File Format: Excel Description: Metadata for raw and filtered datafiles (e.g. sample labels, location of populations, environmental data).
File Format(s)
Raw Data: File: CAGRF221112879-3_consensus.fa; File Format: FASTA; File: CAGRF221112879-3_variants.vcf; File Format: VCF Filtered Data: File Name: genepopfile1.gen; File Format: Genepop/Genind file; File Name: Output_File1 (Sample x SNP).txt; File Format:Text file; File name: METADATA.csv; File Format: CSV file; File name: indmetafile.csv; File Format: CSV file; File name: new_ind_assignments.csv; File Format: CSV file; File name: new_ind_assignments1.csv; File Format: CSV file; File name: Psinuosa_Repository code.txt; File Format: Text file; File name: VCF Sequencing MetaData.csv; File Format: CSV file; File name: New Locus Names.csv; File Format: CSV file; File name: Population_Env.csv; File Format: CSV file
File Size
'Raw Data: File: CAGRF221112879-3_consensus.fa File Size: 8,980 KB File: CAGRF221112879-3_variants.vcf File Size: 598,057 KB Filtered Data: File Name: genepopfile1.gen File Size: 10,947 KB; File Name: Output_File1 (Sample x SNP).txt File Size: 5,245 KB; File name: METADATA.csv File Size: 4 KB; File name: indmetafile.csv File Size: 24 KB; File name: new_ind_assignments.csv File Size: 17 KB; File name: new_ind_assignments1.csv File Size: 11 KB; File name: Psinuosa_Repository code.txt File Size: 4 KB; File name: VCF Sequencing MetaData.csv File Size: 5,000 KB; File name: New Locus Names.csv File Size: 198 kB; File name: Population_Env.csv File Size: 4 KB
Viewing Instructions
Raw Data files:
1. File: CAGRF221112879-3_consensus.fa File Format: FASTA Program to Open: Text Editor Description: Consensus DNA sequences of all loci before filtering
2. File: CAGRF221112879-3_variants.vcf File Format: VCF Program to Open: R, vcftools or bcftools (both command line) Description: Genotype file of SNP calls provided from GBS method Filtered Data: 1. File Name: genepopfile1.gen File Type: Genepop/Genind file Contains: Scored alleles at each locus within the filtered dataset for each individual, will be 0101, 0102, 0202, or 0000. Program Use: File can either be opened in R/R Studio, or in a text editor (e.g. Notepad++ in Windows, BBEdit on a Mac). 2. File Name: Output_File1 (Sample x SNP).txt File Type: Text file Contains: Scored genotypes at each locus within the filtered dataset for each individual, will either be 0, 1, 2, or NA. Program Use: File can either be opened in R/R Studio, or in a text editor (e.g. Notepad++ in Windows, BBEdit on a Mac).
3. File name: METADATA.csv File Type: CSV file Contains: List of column headers and content for all csv files listed below. Program Use: File can be opened in Excel, or read into R/R Studio.
4. File name: indmetafile.csv File Type: CSV file Contains: Individual metadata for each individual within the dataset. See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
5. File name: new_ind_assignments.csv File Type: CSV file Contains: List of sample IDs, still containing duplicates. Samples can be removed from the dataset using this file (e.g. technical repeats, individuals with poor sequencing outputs, too few individuals within a population for appropriate analyses). See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
6. File name: new_ind_assignments1.csv File Type: CSV file Contains: List of sample IDs, duplicates have been manually removed. Samples can be removed from the dataset using this file (e.g. technical repeats, individuals with poor sequencing outputs, too few individuals within a population for appropriate analyses). See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
7. File name: Psinuosa_Repository code.txt File Type: Text file Contains: R script to be able to read vcf file, convert vcf file to genlight object, filter samples and read genepop file into R. Program Use: File can either be opened in R/R Studio, or in a text editor (e.g. Notepad++ in Windows, BBEdit on a Mac).
8. File name: VCF Sequencing MetaData.csv File Type: CSV file Contains: Sequencing metadata that allows for filtering loci and individuals of lower sequencing quality etc. See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
9. File name: New Locus Names.csv File Type: CSV file Contains: Renaming of locus names into concise character form (rather than numeric). First column contains the original locus name provided by AGRF, the second column the concise character format. See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
10. File name: Population_Env.csv File Type: CSV file Contains: Environmental data for each population. See METADATA.csv for column headers and description. Program Use: File can be opened in Excel, or read into R/R Studio.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Contact
Enquiries about the dataset may be sent to Kathryn McMahon: k.mcmahon@ecu.edu.au
Citation
Whale, J., Sinclair, E., Webster, C., Said, N., Frouws, A., Field, D., & McMahon, K. (2026). Population genomics data for the temperate seagrass Posidonia sinuosa. [Data set]. Edith Cowan University. https://doi.org/10.25958/444y-yr20