Search

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.

WOS: 000442210300011, 30151043, Science Citation Index Expanded, Unraveling adaptive genetic variation represents, in addition to the estimate of population demographic parameters, a cornerstone for the management of aquatic natural living resources, which, in turn, represent the raw material for breeding programs. The turbot (Scophthalmus maximus) is a marine flatfish of high commercial value living on the European continental shelf. While wild populations are declining, aquaculture is flourishing in southern Europe. We evaluated the genetic structure of turbot throughout its natural distribution range (672 individuals; 20 populations) by analyzing allele frequency data from 755 single nucleotide polymorphism discovered and genotyped by double-digest RAD sequencing. The species was structured into four main regions: Baltic Sea, Atlantic Ocean, Adriatic Sea, and Black Sea, with subtle differentiation apparent at the distribution margins of the Atlantic region. Genetic diversity and effective population size estimates were highest in the Atlantic populations, the area of greatest occurrence, while turbot from other regions showed lower levels, reflecting geographical isolation and reduced abundance. Divergent selection was detected within and between the Atlantic Ocean and Baltic Sea regions, and also when comparing these two regions with the Black Sea. Evidence of parallel evolution was detected between the two low salinity regions, the Baltic and Black seas. Correlation between genetic and environmental variation indicated that temperature and salinity were probably the main environmental drivers of selection. Mining around the four genomic regions consistently inferred to be under selection identified candidate genes related to osmoregulation, growth, and resistance to diseases. The new insights are useful for the management of turbot fisheries and aquaculture by providing the baseline for evaluating the consequences of turbot releases from restocking and farming., 7th Framework Programme for research (FP7) under "Knowledge-Based Bio-Economy - KBBE", Theme 2: "Food, Agriculture and fisheries, and Biotechnologies" [FP7-KBBE-2012-6-singlestage, 311920]; Spanish Regional Government Xunta de Galicia [GRC2014/010], 7th Framework Programme for research (FP7) under "Knowledge-Based Bio-Economy - KBBE", Theme 2: "Food, Agriculture and fisheries, and Biotechnologies" Project identifier: FP7-KBBE-2012-6-singlestage, Grant/Award Number: 311920; Spanish Regional Government Xunta de Galicia, Grant/Award Number: GRC2014/010

The development of Genotyping-By-Sequencing (GBS) technologies enables cost-effective analysis of large numbers of Single Nucleotide Polymorphisms (SNPs), especially in “non-model” species. Nevertheless, as such technologies enter a mature phase, biases and errors inherent to GBS are becoming evident. Here, we evaluated the performance of double digest Restriction enzyme Associated DNA (ddRAD) sequencing in SNP genotyping studies including high number of samples. Datasets of sequence data were generated from three marine teleost species (>5500 samples, >2.5 × 1012 bases in total), using a standardized protocol. A common bioinformatics pipeline based on STACKS was established, with and without the use of a reference genome. We performed analyses throughout the production and analysis of ddRAD data in order to explore (i) the loss of information due to heterogeneous raw read number across samples; (ii) the discrepancy between expected and observed tag length and coverage; (iii) the performances of reference based vs. de novo approaches; (iv) the sources of potential genotyping errors of the library preparation/bioinformatics protocol, by comparing technical replicates. Our results showed use of a reference genome and a posteriori genotype correction improved genotyping precision. Individual read coverage was a key variable for reproducibility; variance in sequencing depth between loci in the same individual was also identified as an important factor and found to correlate to tag length. A comparison of downstream analysis carried out with ddRAD vs single SNP allele specific assay genotypes provided information about the levels of genotyping imprecision that can have a significant impact on allele frequency estimations and population assignment. The results and insights presented here will help to select and improve approaches to the analysis of large datasets based on RAD-like methodologies The research leading to these results has received funding from the European Community's Seventh Framework Programme under agreement no. KBBE-311920 (AquaTrace). Samples used in this study were collected by the AquaTrace partners: Laboratory of Biodiversity and Evolutionary Genomics (LBEG), University of Leuven (European sea bass); Departmento de Genética, Universidad de Santiago de Compostela (turbot); Sabina De Innocentiis, ISPRA (gilthead sea bream). JH benefited from a PhD scholarship from Flanders Innovation & Entrepreneurship (IWT). GK was funded by a PhD scholarship of Onassis Foundation SI

Overexploitation of natural food resources, among which marine resources, put in serious risk the survival of many species and its availability as human food. Reduction of harvest, restocking with farmed fish and farming as alternative source of product, are commonly used to grant high quality food in a sustainable way. Nevertheless, the last two solutions have potential side effects, among which the genetic impact on natural populations that are involved in restocking actions or escapees from fattening cages and farms. Study the genetic structure of the species in the wild and farming environment is a key aspect to understand the real risks related to aquaculture. At the same time, genetic tools developed in the process can be used to trace wild and farmed origin of fish product, which is an aspect that is gaining great interest among consumers. In the study presented in the thesis, genetic analysis based on RAD genotyping allowed the study of more than 1000 wild and farmed samples with 1216 SNP. The results obtained suggest a subdivision of natural samples in four genetically distinct groups: Atlantic, West Mediterranean, Ionian Sea and Aegean Sea. The analysis carried out on many European broodstocks revealed a higher genetic differentiation compared to wild groups, probably due to founder effects and genetic drift; broodstocks are characterized by lower genetic variability, that in some cases fell below the minimum threshold to avoid inbreeding; finally, some of the broodstocks showed genetic traits that could make offspring unfit to the natural environment they would find in case of restocking of escapees. Comparing wild and farmed groups stimulated a discussion on the potential impact of aquaculture on natural populations, considering the reduction in fitness and the loss of inter/intra groups genetic variability, that cause a loss in long-term adaptation potential. The analytical techniques used and the results obtained are important for the development of gilthead sea bream aquaculture in Europe and for the correct management and protection of natural populations from the areas involved in production.

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