DOI: 10.5061/dryad.8gtht76s9
title: Seascape genetics in a polychaete worm: Disentangling the roles of a biogeographic barrier and environmental factors

description: Aim: Seascape genomics studies aim to understand how environmental
 variables shape species diversity through genotype-environment
 associations. Identifying these effects on lecithotrophic larval species
 that live in intertidal zones is particularly challenging because they are
 subject to environmental heterogeneity and anthropogenic events. Here, we
 evaluate how biotic and abiotic features in the Southwest Atlantic
 littoral zone can affect a high dispersal species’ present and historical
 demographic. Taxon: Perinereis ponteni. Methods: We investigated
 population genetic diversity, connectivity, and past dynamics using 23,300
 SNPs generated using Genotyping by sequencing. We tested whether
 environmental abiotic variables could explain the variance found in
 genotype frequencies using isolation-by-environment (IBE) and landscape
 association approaches. These data, combined with paleodistribution
 simulations and oceanic circulation modeling, were used to infer species
 demographic history and connectivity patterns. Results: Along with high
 levels of connectivity detected, we found a genetic boundary in the
 southeastern region of Brazil around Cabo Frio (Rio de Janeiro) and a
 cline trend for some loci. The paleodistribution simulations reveal a
 spatial refuge in the southeast during the Last Glacial Maximum (21 kya),
 with the expansion of the northern region. We identified 1,421 SNPs with
 frequencies associated with eight environmental variables, most of which
 were related to temperature - the main environmental factor determining
 IBE. Main conclusions: Perinereis ponteni, a polychaete with high gene
 flow capability responds to biogeographic barriers, highlighting the
 importance of biotic and abiotic factors in shaping population
 connectivity. Furthermore, the effect of temperature indicates that future
 climate change and ocean warming can hugely impact this species.
description: Genomic DNA was extracted from 61
 specimens of <em>Perinereis ponteni</em> using the protocol by
 Doyle and Doyle (1987). DNA quality and concentration were assessed by gel
 electrophoresis, spectrometry (NanoDrop Lite spectrophotometer; Thermo
 Fisher Scientific), and fluorometry (Qubit 3.0 Fluorometer; Invitrogen).
 Approximately 100 ng of the extracted DNA per sample were sent to EcoMol
 Consultoria e Projetos Ltda (Piracicaba, Brazil), where GBS libraries were
 prepared according to the protocol described by Elshire, Glaubitz, Sun,
 Poland, Kawamoto, Buckler & Mitchell (2011) and modified by Nunes,
 Liu, Pértille, Perazza, Villela, de Almeida-Val ... & Coutinho
 (2017). The libraries were sequenced in 100 bp single-end fragments using
 the Illumina HiSeq 2500 platform at the Centro de Genômica Funcional
 ESALQ-USP. Sequenced
 fragments were first filtered using Seqyclean v1.10.09 (Zhbannikov,
 Hunter, Foster & Settles, 2017), removing sequences with an
 average Phred quality score ≤ 20, contaminants, and adapters. After
 filtering, Ipyrad v0.7.30 was used for demultiplexing, quality and size
 filtering, fragment clustering, and SNP prospection. Reads with more than
 five Ns or shorter than 35 bp were discarded. The minimum read depth was
 set to six for calling consensus sequences within the samples, and the
 maximum depth was set to 10,000. The clustering threshold was set to 90%,
 and the maximum number of SNPs per locus was set to 30. A locus had to be
 present in 50% or more of the samples in order to be retained in the final
 dataset. All other parameters were maintained at their default values.
 SNPs were first visualized as an occupancy matrix using the divergent
 option in the Matrix Condenser tool; samples with ≥ 40% missing data were
 removed. The resulting variant call format (VCF) files were used as input
 to VCF tools v.0.1.16, with the option max-missing 0.5, followed by the
 PLINK software, which filtered SNPs for missing data (geno &lt; 0.45),
 rare alleles (MAF &gt; 0.01), and linkage disequilibrium
 (indep-pairwise 50 5 0.5). The resulting files were converted to specific
 program formats using PGDSpider v.2.1.1.5.
description: The files included are text files, ready for the analyses. You
 could open using vim at the terminal or any text editor.