Rapid diversification of gray mangroves (Avicennia marina) driven by geographic isolation and extreme environmental conditions in the Arabian Peninsula
Data files
Jan 08, 2024 version files 92.79 MB
Abstract
Biological systems occurring in ecologically heterogeneous and spatially discontinuous habitats provide an ideal opportunity to investigate the relative roles of neutral and selective factors in driving lineage diversification. The gray mangroves (Avicennia marina) of Arabia occur at the northern edge of the species’ range and are subject to variable, often extreme, environmental conditions, as well as to historic large fluctuations in habitat availability and connectivity resulting from Quaternary glacial cycles. Here, we analyze fully sequenced genomes sampled from 20 locations across the Red Sea, the Arabian Sea, and the Persian/Arabian Gulf (PAG) to reconstruct the evolutionary history of the species in the region and to identify adaptive mechanisms of lineage diversification. Population structure and phylogenetic analyses revealed marked genetic structure and highly supported clades among and within the seas surrounding the Arabian Peninsula. Demographic modeling showed times of divergence consistent with recent periods of geographic isolation and low marine connectivity during glaciations, revealing the presence of (cryptic) glacial refugia in the Red Sea and the PAG. Significant migration was detected within the Red Sea and the PAG, and across the Strait of Hormuz to the Arabian Sea, suggesting gene flow upon secondary contact among Arabian mangrove populations. Genetic‐environment association analyses revealed high levels of adaptive divergence and detected signs of multi-loci local adaptation driven by temperature extremes and hypersalinity. These results support a process of rapid diversification resulting from the combined effects of historical factors and ecological selection and reveal mangrove peripheral environments as relevant drivers of lineage diversity.
README: Datasets and Supplementary Materials for the article: “Rapid diversification of gray mangroves (Avicennia marina) driven by geographic isolation and extreme environmental conditions in the Arabian Peninsula”
Deposited in DRYAD DOI: 10.5061/dryad.d51c5b05s
Here we report all the necessary datasets to reproduce the phylogenomics, population genomics, demographic and genotype-environment association analyses carried out in the article ‘Rapid diversification of gray mangroves (Avicennia marina) driven by geographic isolation and extreme environmental conditions in the Arabian Peninsula’, published in Molecular Ecology. For details on data generation please refer to the article.
Article DOI:10.1111/mec.17260
Last updated: January 4, 2024
Description of the data and file structure:
The data is structured in two subdirectories.
- RDA_Datasets: Data files used in genotype-environment association studies with redundancy analysis:
- MangSamples170_coords.txt: Population and geographic coordinates for each mangrove individual.
- Mang_ClimCoords.txt: georeferenced environmental data for each sample analyzed in the article.
- GEA_EcologicalVariables: Description of Ecological variables present in the file 'Mang_ClimCoords.txt'
- 012 and indv files: Alternative allele count files and sample lists used in the RDA.
- GOdatabase_32CHROM.txt: Annotated list of genes and genomic coordinates for candidate gene identification (check or genome report for more details on the reference and annotation): https://academic.oup.com/g3journal/article/11/1/jkaa025/6026961
- Empty cells indicates missing values.
2.fastsimcoal: Site frequency spectra, .est and .tpl input files for the eight demographic models tested with fastsimcoal2.
Sharing/Access information:
Resequencing raw data is deposited in the SRA database, accession BioProject: PRJNA629068. NCBI biosample accession numbers are provided in Table S1 of the article (Supporting Information).
Code/Software:
R script for redundancy analysis (RDA) conducted in the article: The R script is provided separately as related software. R analyses were carried out in RStudio v 1.1.463 (R Studio Team, 2015) with R v3.5.3 (R Core Team, 2019).
*Used Packages:
sdmpredictors
sp
raster
maptools
rgdal
rJava
psych
caret
RPMG
factoextra
curl
vroom
pcadapt
qvalue
vegan
qqman
robust
gdata
fields
Methods
Details in the corresponding mansucript and the README file.