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• W4318263083 abstract "Current genetic methods of population assessment in conservation biology have been challenged by genome-scale analyses due to their quantitatively novel insights. These analyses include assessments of runs-of-homozygosity (ROH), genomic evolutionary rate profiling (GERP), and mutational load. Here, we aim to elucidate the relationships between these measures using three divergent ungulates: white-tailed deer, caribou, and mountain goat. The white-tailed deer is currently expanding, while caribou are in the midst of a significant decline. Mountain goats remain stable, having suffered a large historical bottleneck. We assessed genome-wide signatures of inbreeding using the inbreeding coefficient F and %ROH (FROH ) and identified evolutionarily constrained regions with GERP. Mutational load was estimated by identifying mutations in highly constrained elements (CEs) and sorting intolerant from tolerant (SIFT) mutations. Our results showed that F and FROH are higher in mountain goats than in caribou and white-tailed deer. Given the extended bottleneck and low Ne of the mountain goat, this supports the idea that the genome-wide effects of demographic change take time to accrue. Similarly, we found that mountain goats possess more highly constrained CEs and the lowest dN/dS values, both of which are indicative of greater purifying selection; this is also reflected by fewer mutations in CEs and deleterious mutations identified by SIFT. In contrast, white-tailed deer presented the highest mutational load with both metrics, in addition to dN/dS, while caribou were intermediate. Our results demonstrate that extended bottlenecks may lead to reduced diversity and increased FROH in ungulates, but not necessarily an increase in mutational load, probably due to the purging of deleterious alleles in small populations." @default.
• W4318263083 created "2023-01-28" @default.
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• W4318263083 date "2023-02-08" @default.
• W4318263083 modified "2023-10-13" @default.
• W4318263083 title "Genomic health is dependent on long‐term population demographic history" @default.
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• W4318263083 doi "https://doi.org/10.1111/mec.16863" @default.
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• W4318263083 hasPublicationYear "2023" @default.
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