Restriction-site associated DNA sequencing (RADseq) has become a powerful and useful approach for population genomics. Currently, no software exists that utilizes both paired-end reads from RADseq data to efficiently produce population-informative variant calls, especially for non-model organisms with large effective population sizes and high levels of genetic polymorphism. dDocent is an analysis pipeline with a user-friendly, command-line interface designed to process individually barcoded RADseq data (with double cut sites) into informative SNPs/Indels for population-level analyses. The pipeline, written in BASH, uses data reduction techniques and other stand-alone software packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, read mapping, SNP and Indel calling, and baseline data filtering. Double-digest RAD data from population pairings of three different marine fishes were used to compare dDocent with Stacks, the first generally available, widely used pipeline for analysis of RADseq data. dDocent consistently identified more SNPs shared across greater numbers of individuals and with higher levels of coverage. This is due to the fact that dDocent quality trims instead of filtering, incorporates both forward and reverse reads (including reads with INDEL polymorphisms) in assembly, mapping, and SNP calling. The pipeline and a comprehensive user guide can be found at .

14Restriction-site associated DNA sequencing (RADseq) has become a powerful and useful 15 approach for population genomics. Currently, no software exists that utilizes both paired-end 16 reads from RADseq data to efficiently produce population-informative variant calls, 17 especially for organisms with large effective population sizes and high levels of genetic 18 polymorphism but for which no genomic resources exist. dDocent is an analysis pipeline with 19 a user-friendly, command-line interface designed to process individually barcoded RADseq 20 data (with double cut sites) into informative SNPs/INDELs for population-level analyses. The 21 pipeline, written in BASH, uses data reduction techniques and other stand-alone software 22packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, 23 read mapping, SNP and INDEL calling, and baseline data filtering. Double-digest RAD data 24 from population pairings of three different marine fishes were used to compare dDocent with 25Stacks, the first generally available, widely used pipeline for analysis of RADseq data. 26 dDocent consistently identified more SNPs shared across greater numbers of individuals and 27 with higher levels of coverage. This is most likely due to the fact that dDocent quality trims 28 instead of filtering and incorporates both forward and reverse reads in assembly, mapping, 29 and SNP calling, thus enabling use of reads with INDEL polymorphisms. The pipeline and a 30 comprehensive user guide can be found at (http://dDocent.wordpress.com). 31 32PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.314v1 | CC-BY 4.0

Genetic variation was surveyed at nine microsatellite loci and the mitochondrial control region (868 bp) to test for the presence of genetic stock structure in young-of-the-year Atlantic bluefin tuna (Thunnus thynnus thynnus) from the Mediterranean Sea. Bluefin tuna were sampled over a period of 5 years from the Balearic and Tyrrhenian seas in the western basin of the Mediterranean Sea, and from the southern Ionian Sea in the eastern basin of the Mediterranean Sea. Analyses of multilocus microsatellite genotypes and mitochondrial control region sequences revealed no significant heterogeneity among collections taken from the same location in different years; however, significant spatial genetic heterogeneity was observed across all samples for both microsatellite markers and mitochondrial control region sequences (FST=0.0023, P=0.038 and PhiST=0.0233, P=0.000, respectively). Significant genetic differentiation between the Tyrrhenian and Ionian collections was found for both microsatellite and mitochondrial markers (FST=0.0087, P=0.015 and PhiST=0.0367, P=0.030, respectively). These results suggest the possibility of a genetically discrete population in the eastern basin of the Mediterranean Sea.

Improved methods for obtaining, preparing, and staining fish chromosomes are described.lncluded are procedures for resolving serial or G-type bands. A brief review of various metaphase banding procedures and their use in fishes is also presented.

Sex-biased dispersal is expected to homogenize nuclear genetic variation relative to variation in genetic material inherited through the philopatric sex. When site fidelity occurs across a heterogeneous environment, local selective regimes may alter this pattern. We assessed spatial patterns of variation in nuclear-encoded, single nucleotide polymorphisms (SNPs) and sequences of the mitochondrial control region in bonnethead sharks (Sphyrna tiburo), a species thought to exhibit female philopatry, collected from summer habitats used for gestation. Geographic patterns of mtDNA haplotypes and putatively neutral SNPs confirmed female philopatry and male-mediated gene flow along the northeastern coast of the Gulf of Mexico. A total of 30 outlier SNP loci were identified; alleles at over half of these loci exhibited signatures of latitude-associated selection. Our results indicate that in species with sex-biased dispersal, philopatry can facilitate sorting of locally adaptive variation, with the dispersing sex facilitating movement of potentially adaptive variation among locations and environments.

Next-generation sequencing of reduced-representation genomic libraries provides a powerful methodology for genotyping thousands of single-nucleotide polymorphisms (SNPs) among individuals of nonmodel species. Utilizing genotype data in the absence of a reference genome, however, presents a number of challenges. One major challenge is the trade-off between splitting alleles at a single locus into separate clusters (loci), creating inflated homozygosity, and lumping multiple loci into a single contig (locus), creating artefacts and inflated heterozygosity. This issue has been addressed primarily through the use of similarity cut-offs in sequence clustering. Here, two commonly employed, postclustering filtering methods (read depth and excess heterozygosity) used to identify incorrectly assembled loci are compared with haplotyping, another postclustering filtering approach. Simulated and empirical data sets were used to demonstrate that each of the three methods separately identified incorrectly assembled loci; more optimal results were achieved when the three methods were applied in combination. The results confirmed that including incorrectly assembled loci in population-genetic data sets inflates estimates of heterozygosity and deflates estimates of population divergence. Additionally, at low levels of population divergence, physical linkage between SNPs within a locus created artificial clustering in analyses that assume markers are independent. Haplotyping SNPs within a locus effectively neutralized the physical linkage issue without having to thin data to a single SNP per locus. We introduce a Perl script that haplotypes polymorphisms, using data from single or paired-end reads, and identifies potentially problematic loci.

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