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Updated: May 28, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
Published on: August 21, 2016
Genome-wide polymorphisms show unexpected targets of natural selection
Melissa H Pespeni1, David A Garfield, Mollie K Manier
1Department of Biology, Hopkins Marine Station, Stanford University, Oceanview Boulevard, Pacific Grove, CA 93950, USA. mpespeni@stanford.edu
Abstract:
Natural selection can act on all the expressed genes of an individual, leaving signatures of genetic differentiation or diversity at many loci across the genome. New power to assay these genome-wide effects of selection comes from associating multi-locus patterns of polymorphism with gene expression and function. Here, we performed one of the first genome-wide surveys in a marine species, comparing purple sea urchins, Strongylocentrotus purpuratus, from two distant locations along the species' wide latitudinal range. We examined 9112 polymorphic loci from upstream non-coding and coding regions of genes for signatures of selection with respect to gene function and tissue- and ontogenetic gene expression. We found that genetic differentiation (F(ST)) varied significantly across functional gene classes. The strongest enrichment occurred in the upstream regions of E3 ligase genes, enzymes known to regulate protein abundance during development and environmental stress. We found enrichment for high heterozygosity in genes directly involved in immune response, particularly NALP genes, which mediate pro-inflammatory signals during bacterial infection. We also found higher heterozygosity in immune genes in the southern population, where disease incidence and pathogen diversity are greater. Similar to the major histocompatibility complex in mammals, balancing selection may enhance genetic diversity in the innate immune system genes of this invertebrate. Overall, our results show that how genome-wide polymorphism data coupled with growing databases on gene function and expression can combine to detect otherwise hidden signals of selection in natural populations.
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