Quantifying the Impact of Population Size on Natural Selection Across the Genome Lucas D. Baker1 Vikram E. Chhatre2 Hayley C. Lanier1 1Zoology & Physiology, University of Wyoming at Casper 2Wyoming INBRE Bioinformatics Core, University of Wyoming

Why Anthropogenic; adjective created by people or caused by human activity: anthropogenic pollution In a world in which humans are having an impact on our environment, as scientists it is important for us to better understand the effect and response nature is taking.

Arctic ground squirrel Mammals of the Alaskan alpine Alaska & Chugach ranges All five species are south of the Yukon river Brooks Range Only three occur north Yukon River collared pika hoary marmot singing vole Arctic ground squirrel brown lemming least most habitat specificity

animals/ha 0.62-7.2 0.6-7.8 1.5-6 5-50 50-200 ground squirrel collared pika hoary marmot singing vole brown lemming 0.62-7.2 0.6-7.8 1.5-6 5-50 50-200 animals/ha

Impact of genetic drift Death by chance Death by chance collared pika hoary marmot singing vole ground squirrel brown lemming 0.62-7.2 0.6-7.8 1.5-6 5-50 50-200

Genetic Drift Death by Chance (will not pass on genes) Population In this project, we looked to examine how mechanisms of evolution respond to an animals population size. Especially important was genetic drift. Population

What is the impact of genetic drift on different size populations of Alaskan mammals?

Samples for sequencing collected from co-distributed populations throughout Alaska

Genomic data collection Restriction digest genomic DNA Ligate adaptors and barcodes Pool samples, size select, PCR enrich Illumina paired-end sequencing Reads filtered and assembled in STACKS RADseq We used an approach called RADseq, which yields a reduced-representation genome For many questions you don’t need a full genome, and by randomly targeting a subset of the genome we can develop a strong understanding of evolutionary processes Briefly, this approach consists of… 169 million reads 3,035,160 ± 1,271,412 per individual Lanier et al. 2015, Mol. Ecol.

Single Nucleotide Polymorphism (SNP) STACKS Stacks (v1.44) variant discovery and analysis pipeline (Catchen et al. 20xx) to identify Single Nucleotide Polymorphisms (SNPs) in [ADD NUMBER] individuals from [ADD NUMBER] populations belonging to the five species.  Nucleotide diversity was estimated for all species and compared with population size.  Using genetic simulations over 50 generations, we applied strong selection pressure (s=0.2) on populations of varying sizes to see the effect of drift.    We used an approach called RADseq, which yields a reduced-representation genome For many questions you don’t need a full genome, and by randomly targeting a subset of the genome we can develop a strong understanding of evolutionary processes Briefly, this approach consists of… 169 million reads 3,035,160 ± 1,271,412 per individual

What the simulations tell us Species with larger population sizes have greater nucleotide diversity selection coefficient (s) = 0.2 Small populations more likely to lose alleles due to genetic drift. Selection works more effectively in large populations. collared pika hoary marmot ground squirrel singing vole brown lemming

What the genomic data tell us The number of polymorphic loci also differs by species. Species with larger population sizes show more genomic variation

What the genomic data tell us Species with larger population sizes have greater nucleotide diversity Species with larger population sizes show more genomic variation

Rapid shift in climate Can adaptation keep up? years before today (0 = 1950) Vostok ice core data/J.R. Petit et al.; NOAA Mauna Loa CO2 record)

Conservation & Monitoring incorporating this information hoary marmot ground squirrel singing vole brown lemming collared pika Selection works more effectively in large populations. Small populations more likely to lose alleles due to genetic drift.

Acknowledgments Wyoming INBRE Dr. Hayley Lanier Dr. Vikram Chhatre Lewis Hein Isaac Anderson Haley Tolbert Laura Diesburg Shane Dodge University of Wyoming’s Advanced Research Computing Center (ARCC)