Genomic investigations provide insights into the mechanisms of resilience to heterogeneous habitats of the Indian Ocean in a pelagic fish

Abstract

The adaptive genetic variation in response to heterogeneous habitats of the Indian Ocean was investigated in the Indian oil sardine using ddRAD sequencing to understand the subpopulation structure, stock complexity, mechanisms of resilience, and vulnerability in the face of climate change. Samples were collected from different ecoregions of the Indian ocean and ddRAD sequencing was carried out. Population genetic analyses revealed that samples from the Gulf of Oman significantly diverged from other Indian Ocean samples. SNP allele-environment correlation revealed the presence of candidate loci correlated with the environmental variables like annual sea surface temperature, chlorophyll-a, and dissolved oxygen concentration which might represent genomic regions allegedly diverging as a result of local adaptation. Larval dispersal modelling along the southwest coast of India indicated a high dispersal rate. The two major subpopulations (Gulf of Oman and Indian) need to be managed regionally to ensure the preservation of genetic diversity, which is crucial for climatic resilience.

Restriction Site-Associated DNA Sequencing Reveals Local Adaptation Despite High Levels of Gene Flow in Sardinella lemuru (Bleeker, 1853) Along the Northern Coast of Mindanao, Philippines

“…Conversely, we found no association between the candidate outlier loci and the parameters that are often used as proxies for ocean primary productivity and food availability, namely chl-a and POC. This contrasts with the findings of Sebastian et al (2021) who reported that chl-a is among the environmental parameters that led to two adaptively divergent populations of S. longiceps in the Indian Ocean. While it is possible that chl-a and POC are not strong enough to drive adaptive divergence despite their differences between regions, it is more likely that loci associated with these parameters were neither genotyped nor screened with the outlier detection methods used.…”

“…Variability in primary productivity due to wind and ocean current was also hypothesized to influence recruitment success of S. lemuru along the coast of Western Australia (Gaughan and Mitchell, 2000). In this study, three unannotated loci that contributed greatly to the observed regional genetic differentiation correlated with SST, suggesting that this environmental parameter acts as a selective force putatively driving adaptive divergence on such genomic regions (Sebastian et al, 2021). Temperature is important for the proper functioning of proteins that affect physiological processes; it is therefore considered a primary selective agent involved in local adaptation in the marine environment, as was observed in many fishes (e.g., Hemmer-Hansen et al, 2007a;Dionne et al, 2008;Nielsen et al, 2009a,b;Limborg et al, 2012a,b;Sebastian et al, 2021).…”

“…In this study, three unannotated loci that contributed greatly to the observed regional genetic differentiation correlated with SST, suggesting that this environmental parameter acts as a selective force putatively driving adaptive divergence on such genomic regions (Sebastian et al, 2021). Temperature is important for the proper functioning of proteins that affect physiological processes; it is therefore considered a primary selective agent involved in local adaptation in the marine environment, as was observed in many fishes (e.g., Hemmer-Hansen et al, 2007a;Dionne et al, 2008;Nielsen et al, 2009a,b;Limborg et al, 2012a,b;Sebastian et al, 2021). Conversely, we found no association between the candidate outlier loci and the parameters that are often used as proxies for ocean primary productivity and food availability, namely chl-a and POC.…”

“…Meanwhile, putatively outlier SNPs revealed regional genetic differentiation, indicating that patterns of gene flow do not match patterns of adaptive divergence (Funk et al, 2012). The strong adaptive differentiation observed against a backdrop of high levels of gene flow indicates that the influence of natural selection overpowers genetic drift, a common occurrence in populations with large effective population size and inhabit heterogeneous environments (Hemmer-Hansen et al, 2007b;Funk et al, 2012;Limborg et al, 2012a,b;Moore et al, 2014;Sebastian et al, 2021). Remotely sensed parameters have shown that, at a temporal scale, the stronger signature of upwelling in NZP causes more pronounced fluctuation in SST, chl-a, and POC between monsoons, making it relatively more dynamic than NMR; meanwhile, at a spatial scale, NZP has, on average, cooler waters and higher concentrations of chl-a and POC than NMR.…”

“…Larvae that exhibit greater fitness to prevailing environmental conditions would have a higher likelihood of survival to sexual maturity, and will eventually contribute to the gene pool, thereby resulting in a spawning population carrying specific adaptive genetic variants (Willette et al, 2014). Signatures of genetic variation recovered using outlier loci have been reported for many fish species that exhibit high levels of gene flow, including S. longiceps (Sebastian et al, 2021), Gadus morhua (Westgaard and Fevolden, 2007;Nielsen et al, 2009b;Bradbury et al, 2010), Platichthys flesus (Hemmer-Hansen et al, 2007a,b), Caesio cuning (Ackiss et al, 2018), Clupea harengus (André et al, 2011;Lamichhaney et al, 2012;TABLE 4 | Spearman correlation (ρ) between putatively outlier loci and remotely sensed environmental parameters.…”