Genetic Load in Syntopic Populations of Two Species of Endangered Galápagos Land Iguanas with Divergent Demographic Histories

Small isolated populations represent unique opportunities to investigate how demographic histories influence the accumulation of deleterious mutations (genetic load). In this study, we focus on two syntopic populations of closely related Galápagos Land Iguanas, Conolophus subcristatus and C. marthae. While C. subcristatus remains relatively widespread across multiple islands, C. marthae is a Critically Endangered species represented by a single population occupying a very small area on the northern slopes of Isabela Island, marked by a history of long-term demographic decline. We generated low-coverage whole-genome resequencing data from 20 individuals of each species to investigate the relationship between demographic history and genetic load. Variant sites were categorized by predicted functional impact to estimate the relative abundance of deleterious mutations, and genetic load was compared between species. We found that the two syntopic populations are genetically isolated, confirming reproductive isolation between the species. Overall genetic diversity was lower in C. marthae than in C. subcristatus, reflecting its smaller historical population size. The number of deleterious alleles in C. marthae was significantly lower than in C. subcristatus. This pattern is consistent with genetic purging, a phenomenon whereby harmful recessive alleles are more likely to be exposed to selection and subsequently eliminated in small, inbred populations. Despite this indication of purifying selection, C. marthae remains at critical risk of extinction due to its extremely small population size and narrow geographic range. Further validation with highercoverage genomic data is currently underway and will be essential to confirm the observed trends and guide future conservation strategies. These preliminary findings highlight the importance of considering genetic load alongside demographic metrics in conservation genomics.