ALBERT

Description: To improve the methylation estimates in our study, we corrected for SNPs, which could have led to a wrong methylation call. The excluded positions were derived with custom written perl scripts from C-to-T and G-to-A-SNPs with genotype quality of 20 and a minimum allele frequency of 0.005 from the 96 wild caught three-spined sticklebacks with a combination of custom written Perl and R-scripts using packages from methylkit and GenomicRanges. This BED-file contains the C-to-T SNPs, in which the first field is the name of the chromosome; the second describes the start position and the third the end position of the feature in standard chromosomal coordinates.

Description: This vcf file is generated from genomic data of three-spined sticklebacks from Kiel (KIE), Germany and Nynäshamn (NYN), Sweden. The individuals from Kiel are S3, S4, S19, S20, S33, S34, S47, S48, S49, S50, S63, S64, S77, S78, S89, S90. The individuals from NYN are S5, S6, S21, S22, S35, S36, S37, S38, S51, S52, S65, S66, S79, S80, S85, S86. It contains high quality biallelic positions (GQ=20) and is filtered for minor allele frequencies of maf = 0.05, allows 40 % of missing data (13 individuals) and a read depth of 〉=5. Further this vcf file is subset to the inducible differentially methylated sites (DMS) (198sites) in decreasing PSU (_6PSU) with 5 kilobases (kb) before and after DMS. With this file further calculations were performed to estimate the genetic differentiation (i.e. Fst) between the different populations (see manuscript indicated below).

Description: This vcf file is generated from genomic data of three-spined sticklebacks from Kiel (KIE) and Sylt (SYL), Germany. The individuals from Kiel are S3, S4, S19, S20, S33, S34, S47, S48, S49, S50, S63, S64, S77, S78, S89, S90. The individuals from SYL are S9, S10, S17, S18, S31, S32, S45, S46, S59, S60, S61, S62, S73, S74, S87, S88. It contains high quality biallelic positions (GQ=20) and is filtered for minor allele frequencies of maf = 0.05, allows 40 % of missing data (13 individuals) and a read depth of 〉=5. Further this vcf file is subset to the inducible differentially methylated sites (DMS) (148sites) in increasing PSU (_33PSU) with 5 kilobases (kb) before and after DMS. With this file further calculations were performed to estimate the genetic differentiation (i.e. Fst) between the different populations (see manuscript indicated below).

Description: The provided file archive contains genotype data from mid-Atlantic hydrothermal vent mussels (genus Bathymodiolus) at 18 SNP loci and the mitochondrial ND4 gene (BMAR_Baz_Bpu_genotypes.txt). The subfolders denote statistical programs used in the multilocus genotyping study and contain input files and scripts that were used in the respective analyses. Our analyses indicate that B. azoricus and B. puteoserpentis hybridize introgressively across a large geographic area without evidence for general hybrid incompatibilities. While these findings shed new light onto the genetic structure of this hybrid zone, many aspects about its nature still remain obscure. Our study sets a baseline for further research that should primarily focus on the acquisition of additional mussel samples and environmental data, a detailed exploration of vent areas and hidden populations as well as genomic analyses in both mussel hosts and their bacterial symbionts.

Description: To assess the phenotypic effects of transgenerational salinity change in sticklebacks, offspring were sampled as eggs, freshly hatched larvae, as well as 12, 30 and 90 days post hatch (dph). We measured egg size, yolk-sac size to length ratio of fish larvae from pictures taken under a stereomicroscope. At 12, 30 and 90 days post hatch we measured length and weight of the larvae. Additionally, dissections were performed at 30 and 90 dph to assess the hepatosomatic index (HSI) of juveniles. Mortality was monitored throughout the experiment to account for possible non-random mortality.

Description: Cells in multicellular organisms are genetically heterogeneous owing to somatic mutations. The accumulation of somatic genetic variation in species undergoing asexual (or clonal) reproduction (termed modular species) may lead to phenotypic heterogeneity among modules. However, abundance and dynamics of somatic genetic variation under clonal growth, a widespread life history in nature, remain poorly understood. Here we show that branching events in a seagrass clone or genet leads to population bottlenecks at the cellular level and hence the evolution of genetically differentiated modules. Studying inter-module somatic genetic variation, we uncovered thousands of SNPs that segregated among modules. The strength of purifying selection on mosaic genetic variation was greater at the intra-module comparing with the inter-module level. Our study provides evidence for the operation of selection at multiple levels, of cell population and modules. Somatic genetic drift leads to the emergence of genetically unique modules; hence, modules in long-lived clonal species constitute an appropriate elementary level of selection and individuality.

Description: Four marine fish species are among the most important on the world market: cod, salmon, tuna, and sea bass. While the supply of North American and European markets for two of these species - Atlantic salmon and European sea bass - mainly comes from fish farming, Atlantic cod and tunas are mainly caught from wild stocks. We address the question what will be the status of these wild stocks in the midterm future, in the year 2048, to be specific. Whereas the effects of climate change and ecological driving forces on fish stocks have already gained much attention, our prime interest is in studying the effects of changing economic drivers, as well as the impact of variable management effectiveness. Using a process-based ecological-economic multispecies optimization model, we assess the future stock status under different scenarios of change. We simulate (i) technological progress in fishing, (ii) increasing demand for fish, and (iii) increasing supply of farmed fish, as well as the interplay of these driving forces under different sce- narios of (limited) fishery management effectiveness. We find that economic change has a substantial effect on fish populations. Increasing aquaculture production can dampen the fishing pressure on wild stocks, but this effect is likely to be overwhelmed by increasing demand and technological progress, both increasing fishing pressure. The only solution to avoid collapse of the majority of stocks is institutional change to improve management effectiveness significantly above the current state. We conclude that full recognition of economic drivers of change will be needed to successfully develop an integrated ecosystem management and to sustain the wild fish stocks until 2048 and beyond.