Comparative evolution of molecular markers: An analysis of genetic variation within the blue marlin (Makaira nigricans)

Blue marlin diversity was assessed at mtDNA, scnDNA, microsatellite DNA, and allozyme molecular markers. Hierarchical analysis of molecular variance (AMOVA) revealed that most genetic variation was maintained within populations, with a non-significant fraction attributable to variation among temporal replicates and between locations within oceans. In contrast, inter-ocean divergence was highly significant for a majority of loci within each marker class. Previous studies of mitochondrial DNA (mtDNA; n = 104) genetic variation within the blue marlin revealed two distinct clades of haplotypes, one of which was present only in the Atlantic (the \u27Atlantic clade\u27), at a frequency of 40% &(F\sb{lcub}st{rcub}& = 0.39). ScnDNA and allozyme markers exhibited lower levels of diversity and inter-ocean divergence than mtDNA (average &F\sb{lcub}st{rcub}& = 0.08). Enhanced genetic drift among populations, due to the four-fold lower effective population size of mtDNA, was emphasized as causing the greater mtDNA inter-ocean divergence. The low mutation rate of nuclear markers, and greater male dispersal may have contributed to the difference detected. Microsatellite loci were hypervariable, and displayed a wide range of divergence estimates (average &F\sb{lcub}st{rcub}& = 0.14). A nuclear \u27Atlantic clade\u27 of alleles was detected at one locus, indicating that the historical forces that generated the mitochondrial Atlantic clade (Pleistocene allopatry) also strongly influenced the nuclear genome. Although some microsatellite loci were much more sensitive than scnDNA markers, on average, these differences were not significant, due to the wide range of microsatellite patterns detected. The mean and variance of inter-ocean divergence &(F)& estimates were not significantly different among marker classes, suggesting a minor influence of selection. Correlations between diversity and divergence within and among marker classes were non-significant, indicating that difference in mutation rate can not explain the lower nuclear divergence. The patterns of diversity obtained within and among marker classes is consistent with expected values under migration-drift equilibrium

Vision and Change Through the Genome Consortium for Active Teaching using Next-Generation Sequencing (GCAT-SEEK)

Development of the Genome Consortium on Active Teaching using Next Generation Sequencing (GCAT-SEEK) is described. Workshops, educational modules, assessment resources, data analysis software and computer hardware available for faculty are described

Filtering for sex-specific loci

The R script counts each samples' matches (matches.tsv) to the catalog (Batch_7.catalog.tags.tsv) and tabulates the depth of each locus in each individual. We then filtered for presence in all of one sex and none of the other sex. We identified loci present in all males and no females

batch_7.2.sumstats.tsv

Stacks1.04 populations output provides summary statistics for each locus containing SNPs. To identify sex markers, we split each species into male and female samples: S. chrysomelas males were assigned to Pop 1, S. chrysomelas females were assigned to Pop 2, S. carnatus males were assigned to Pop 3, and S. carnatus females were assigned to Pop 4. See the Stacks manual for headers

batch_7.catalog.tags.tsv

Stacks1.04 denovo_map.pl pipeline was used to construct a catalog of loci from ddRAD-seq reads of S. carnatus and S. chrysomelas samples. . We specified a minimum depth of coverage (m) of two, a maximum number of mismatches between stacks (alleles) within an individual (M) of two, and a maximum number of mismatches between individuals (n) of one to build the catalog. M and n allow for assembly of polymorphic loci within individuals and fixed differences among individuals at a locus, respectively. See the Stacks manual for headers

matches.tsv

Samples' stacks are matched to the catalog to create a matches.tsv file for each sample. We counted the matches to the catalog to find the depth of each locus in each individual sample. This file must be unzipped. See the Stacks manual for headers

Fixed differences

This R script was used to identify loci with SNPs that are differently fixed between males and females (ie all males are heterozygous, all females are homozygous). The loci identified are on the sex chromosomes, but given our parameters they have not diverged enough for Stacks to split them into separate loci. We tested the scrip on loci that mapped to select scaffolds where sex-specific markers were found, and then we applied the script to filter the entire sumstats.tsv file

Data from: Comparative population genetic analysis of bocaccio rockfish Sebastes paucispinis using anonymous and gene-associated simple sequence repeat loci

Comparative population genetic analyses of traditional and emergent molecular markers aid in determining appropriate use of new technologies. The bocaccio rockfish Sebastes paucispinis is a high-gene-flow marine species off the west coast of North America that experienced strong population decline over the past three decades. We used 18 anonymous and 13 gene associated simple sequence repeat loci (EST-SSRs) to characterize range-wide population structure with temporal replicates. No FST-outliers were detected using the LOSITAN program, suggesting that neither balancing nor divergent selection affected the loci surveyed. Consistent hierarchical structuring of populations by geography or year class was not detected regardless of marker class. The EST-SSRs were less variable than the anonymous SSRs, but no correlation between FST and variation or marker class was observed. General Linear Model analysis showed that low EST-SSR variation was attributable to low mean repeat number. Comparative genomic analysis with Gasterosteus aculeatus, Takifugu rubripes, and Oryzias latipes showed consistently lower repeat number in EST-SSRs than SSR loci that were not in ESTs. Purifying selection likely imposed functional constraints on EST-SSRs resulting in low repeat numbers that affected diversity estimates, but did not affect the observed pattern of population structure

allinRpts

GENEPOP data file for 27 loci with alleles recoded into repeat units. Population and locus names follow the manuscript