Landscape Connectivity and Genetic Structure in a Mainstem and a Tributary Stonefly (Plecoptera) Species Using a Novel Reference Genome

Rachel L. Malison, Brian K. Hand, Emily Winter, J. Joseph Giersch, Stephen J. Amish, Diane Whited, Jack A. Stanford, Gordon Luikart

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding how environmental variation influences population genetic structure can help predict how environmental change influences population connectivity, genetic diversity, and evolutionary potential. We used riverscape genomics modeling to investigate how climatic and habitat variables relate to patterns of genetic variation in 2 stonefly species, one from mainstem river habitats (Sweltsa coloradensis) and one from tributaries (Sweltsa fidelis) in 40 sites in northwest Montana, USA. We produced a draft genome assembly for S. coloradensis (N50 = 0.251 Mbp, BUSCO > 95% using "insecta_ob9"reference genes). We genotyped 1930 SNPs in 372 individuals for S. coloradensis and 520 SNPs in 153 individuals for S. fidelis. We found higher genetic diversity for S. coloradensis compared to S. fidelis, but nearly identical genetic differentiation among sites within each species (both had global loci median FST= 0.000), despite differences in stream network location. For landscape genomics and testing for selection, we produced a less stringently filtered data set (3454 and 1070 SNPs for S. coloradensis and S. fidelis, respectively). Environmental variables (mean summer precipitation, slope, aspect, mean June stream temperature, land cover type) were correlated with 19 putative adaptive loci for S. coloradensis, but there was only one putative adaptive locus for S. fidelis (correlated with aspect). Interestingly, we also detected potential hybridization between multiple Sweltsa species which has never been previously detected. Studies like ours, that test for adaptive variation in multiple related species are needed to help assess landscape connectivity and the vulnerability of populations and communities to environmental change.

Original languageEnglish
Pages (from-to)453-471
Number of pages19
JournalJournal of Heredity
Volume113
Issue number4
DOIs
StatePublished - Jul 1 2022

Keywords

  • RAD sequencing
  • adaptive gene flow
  • climate change
  • landscape genomics
  • local adaptation

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