Abstract
SUMMARY Macroalgae thrive in extreme environments, yet the genomic basis of their tolerance remains poorly resolved. We describe nine Arabian Gulf macroalgae and integrate them with 117 published genomes (126 total; 70 Rhodophyta, 43 Ochrophyta, 13 Chlorophyta) to test genome–environment associations. Google Earth Engine (GEE) for broad-scale oceanography and 10-meter resolution AlphaEarth Foundations (AEF) embeddings for fine-scale habitat heterogeneity. We identified 157 significant (FDR q < 0.05) correlations with global GEE variables—including a strong negative temperature association with DUF3570—while AEF embeddings uncovered over 1,000 lineage-specific signals within Rhodophyta and identified climate-driven Pfam modules. The von Willebrand factor type-A domain emerged as uniquely robust across all frameworks and enriched in Arabian Gulf species. In the Arabian Gulf, enrichment of this domain is consistent with selection for adhesion mechanisms capable of withstanding chronic hydrodynamic stress compounded by high temperature and salinity. These results demonstrate that converging remote sensing with deep learning identifies conserved and lineage-specific genomic signatures of ecological differentiation across diverse macroalgal lineages.
Full text
1,537 characters
· extracted from
oa-doi-fallback
· click to expand
SUMMARY
Macroalgae thrive in extreme environments, yet the genomic basis of their tolerance remains poorly resolved. We describe nine Arabian Gulf macroalgae and integrate them with 117 published genomes (126 total; 70 Rhodophyta, 43 Ochrophyta, 13 Chlorophyta) to test genome–environment associations. Google Earth Engine (GEE) for broad-scale oceanography and 10-meter resolution AlphaEarth Foundations (AEF) embeddings for fine-scale habitat heterogeneity. We identified 157 significant (FDR q < 0.05) correlations with global GEE variables—including a strong negative temperature association with DUF3570—while AEF embeddings uncovered over 1,000 lineage-specific signals within Rhodophyta and identified climate-driven Pfam modules. The von Willebrand factor type-A domain emerged as uniquely robust across all frameworks and enriched in Arabian Gulf species. In the Arabian Gulf, enrichment of this domain is consistent with selection for adhesion mechanisms capable of withstanding chronic hydrodynamic stress compounded by high temperature and salinity. These results demonstrate that converging remote sensing with deep learning identifies conserved and lineage-specific genomic signatures of ecological differentiation across diverse macroalgal lineages.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵7 Lead contact: Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Kourosh Salehi-Ashtiani (ksa3{at}nyu.edu).
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.