Anthropogenic and natural barriers affect genetic connectivity in an Alpine butterfly - Trense, Daronja; Schmidt, Tom; Yang, Qiong; Chung, Jessica; Hoffmann, Ary; Fischer, Klaus (Dryad, 2020)
Dispersal is a key biological process serving several functions including
connectivity among populations. Habitat fragmentation caused by natural or
anthropogenic structures may hamper dispersal, thereby disrupting genetic
connectivity. Investigating factors affecting dispersal and gene flow is
important in the current era of anthropogenic global change, as dispersal
comprises a vital part of a species’ resilience to environmental change.
Using fine-scale landscape genomics, we investigate gene flow and genetic
structure of the Sooty Copper butterfly (Lycaena tityrus) in the Alpine
Ötz valley system in Austria. We show surprisingly high levels of gene
flow in L. tityrus across the region. Nevertheless, ravines, forests and
roads had effects on genetic structure, although rivers did not. The
latter is surprising as roads and rivers have a similar width and run
largely in parallel in our study area, pointing towards a higher impact of
anthropogenic compared with natural linear structures. Additionally, we
detected eleven loci potentially under thermal selection, including ones
related to membranes, metabolism, and immune function. This study
demonstrates the usefulness of molecular approaches in obtaining estimates
of dispersal and population processes in the wild. Our results suggest
that, despite high gene flow in the Alpine valley system investigated, L.
tityrus nevertheless seems to be vulnerable to anthropogenically-driven
habitat fragmentation. With anthropogenic rather than natural linear
structures affecting gene flow, this may have important consequences for
the persistence of species such as the butterfly studied here in altered
landscapes.
SNPs were called using a de novo pipeline without a reference genome. We
used the process_radtags program within stacks version 2.3 (Catchen,
Hohenlohe, Bassham, Amores, & Cresko, 2013; Catchen, Amores,
Hohenlohe, Cresko, & Postlethwait, 2011) to demultiplex the
sequence data. This separated individuals by their unique barcode, removed
adapter sequences, trimmed the reads to 120 bp length, and discarded
low-quality reads (Phred score < 20). We then ran the stacks
denovo_map pipeline using one individual per outgroup and 26 individuals
from the Ötz valley system to generate a catalogue of loci. Each of the
186 individuals was then matched against this catalogue and SNPs were
subsequently called. We filtered the data to retain SNPs which were
present in more than 50% of the 186 individuals, and then retained the
first SNP in each ddRAD locus. Further filtering with the program vcftools
version 0.1.11 (Danecek et al., 2011) was done to retain loci that were at
Hardy-Weinberg equilibrium, had a minor allele count of > 2,
missing data of < 5%, and mean depth of 20-45. The final dataset
contained 12,806 SNPs for analyses of relatedness, genetic structure, and
outlier loci.