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Additional file 1 Supplementary tables and genotype differences at shared SNPs panel figures: Table S1. Number of SNPs and population metrics for Manila clam (Ruditapes philippinarum) samples (N = 110, four localities). Table S2. Number of SNPs and population metrics for common edible cockle (Cerastoderma edule) samples (N = 120, four localities). Table S3. Number of SNPs and population metrics for brown trout (Salmo trutta) samples (N = 52, three localities). Table S4. Number of SNPs and population metrics for silver catfish (Rhamdia quelen) samples (N = 21, two localities). Table S5. Number of SNPs and population metrics for small-spotted catshark (Scyliorhinus canicula) samples (N = 28, two localities). Table S6. Geographical coordinates of sampling localities for the five species used in this study. Table S7. Building-loci pipelines options selected for process_radtags (A), STACKS 2 (B), and Meyer’s 2b-RAD v2.1 (C). Supplementary figures: Figure S1. Differences in genotyping between common SNPs (COM panel) from both building-loci pipelines in each species. Figure S2. Differences in genotyping between common SNPs from reference genome and de novo approach comparisons (i.e. RG-STA and RG-ALT) in Manila clam and brown trout. Figure S3. Type of genotype differences between common SNPs (COM panel) from both building-loci pipelines in each species. Figure S4. Type of genotype differences between common SNPs from reference genome and de novo approach comparisons (i.e. RG-STA and RG-ALT) in Manila clam and brown trout.

Additional file 2 CLUMPAK and DAPC output comparisons for all species: Figure S5. Comparison between CLUMPAK and DAPC outputs for Manila clam (Ruditapes philippinarum) samples (N = 110). Figure S6. Comparison between CLUMPAK and DAPC outputs for common edible cockle (Cerastoderma edule) samples (N = 120). Figure S7. Comparison between CLUMPAK and DAPC outputs for brown trout (Salmo trutta) samples (N = 52). Figure S8. . Comparison between CLUMPAK and DAPC outputs for silver catfish (Rhamdia quelen) samples (N = 21). Figure S9. Comparison between CLUMPAK and DAPC outputs for small-spotted catshark (Scyliorhinus canicula) samples (N = 28).

Additional file 3. Description of the information included within GitHub website ( https://github.com/abhortas/USC-RAD-seq-scripts ) where custom Perl scripts and file examples to obtain shared SNPs and compare genotypes from the two building-loci pipelines used in the present study are available.

During the last century, most species across the globe have experienced the effects of global change and other types of human impact such as exploitation. Genetic analyses of historical collections from museums and other repositories represent a unique resource for tracking demographic and evolutionary effects of climate change and other humaninduced stressors. This research focuses on a large shark, the tiger shark (Galeocerdo cuvier), for which there is a striking lack of genomic resources, despite the strong public and commercial interest in the species, including human shark interactions, conservation and management. The ability of elasmobranchs, as many other species, to react to a rapidly changing environment is still poorly understood. Therefore, the use of genomic data to comprehend present and past evolutionary responses to the environment represents a key to predict the impact of ongoing changes and the resilience of a species to future changes. It is timely we advance our understanding of these events to inform a sustainable use of resources, both in the eye of the economic and social consequences this will have on the future of many communities, but also for protection of global biodiversity as a legacy for future generations. In this study, I have highlighted the importance, and provided an example, of calibrating microsatellite data. I have demonstrated the utility of the resulting genetic database to improve inferences on global population structure by including abundant archival specimens, through identification of basin of origin for samples of unknown provenance (Manuscript I). Through genomic scale SNP analyses from contemporary and archived jaw samples I have provided an improved understanding of the spatiotemporal scale of population structuring in tiger sharks. I found clear evidence of temporal genetic changes in tiger sharks from the Australian east coast. The changes were most likely affiliated with the disappearance of a cryptic population, which was likely reduced/extirpated due to local direct and indirect exploitation (Manuscript II). By employing SNPs derived from the tiger shark transcriptome, I analysed worldwide contemporary and archived samples in order to elucidate the global population structure of the species. Both SNP and mtDNA data confirmed the deep genetic split between Atlantic and Indo-Pacific populations of tiger sharks and highlighted that it is based on a high number of genome-wide SNPs, suggesting primarily neutral evolutionary processes. However, the presence of loci with very high FST values also suggests adaptive divergence (Manuscript III). More importantly, the study showed for the first time extensive population structuring within both the Atlantic and Indo-Pacific oceans, suggesting population structure on a hithertoundetected geographical scale. The findings have large implications for local and global management of tiger sharks as well as other large sharks.

Background: The irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control. Results: Despite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons. Conclusions: Tested building-loci pipelines for selection of SNP panels seem to have low influence on population genetics inference across the diverse case-study scenarios here studied. However, preliminary trials with different bioinformatic pipelines are suggested to evaluate their influence on population parameters according with the specific goals of each study The work undertaken in this project was funded by Xunta de Galicia Autonomous Government (GRC2014/010), Interreg Atlantic Area (Cockles project, EAPA_458/2016) and Girona University (MPCUdG2016/060) projects. Adrián Casanova was a Xunta de Galicia fellowship (ED481A-2017/091) SI