Intraspecific divergence in sperm morphology of the green sea urchin, <Emphasis Type="Italic">Strongylocentrotus droebachiensis</Emphasis>: implications for selection in broadcast spawners

Background  

Sperm morphology can be highly variable among species, but less is known about patterns of population differentiation within species. Most studies of sperm morphometric variation are done in species with internal fertilization, where sexual selection can be mediated by complex mating behavior and the environment of the female reproductive tract. Far less is known about patterns of sperm evolution in broadcast spawners, where reproductive dynamics are largely carried out at the gametic level. We investigated variation in sperm morphology of a broadcast spawner, the green sea urchin (Strongylocentrotus droebachiensis), within and among spawnings of an individual, among individuals within a population, and among populations. We also examined population-level variation between two reproductive seasons for one population. We then compared among-population quantitative genetic divergence (Q _ST) for sperm characters to divergence at neutral microsatellite markers (F _ST).     

Identification of substituted pyrazolo[1,5-a]quinazolin-5(4H)-one as potent poly(ADP-ribose)polymerase-1 (PARP-1) inhibitors

A novel series of pyrazolo[1,5-a]quinazolin-5(4H)-one derivatives proved to be a potent class of PARP-1 inhibitors. An extensive SAR around the 3-position of pyrazole in the scaffold led to the discovery of amides derivatives as low nanomolar PARP-1 inhibitors.     

Genetic Structure Among 50 Species of the Northeastern Pacific Rocky Intertidal Community

Comparing many species'' population genetic patterns across the same seascape can identify species with different levels of structure, and suggest hypotheses about the processes that cause such variation for species in the same ecosystem. This comparative approach helps focus on geographic barriers and selective or demographic processes that define genetic connectivity on an ecosystem scale, the understanding of which is particularly important for large-scale management efforts. Moreover, a multispecies dataset has great statistical advantages over single-species studies, lending explanatory power in an effort to uncover the mechanisms driving population structure. Here, we analyze a 50-species dataset of Pacific nearshore invertebrates with the aim of discovering the most influential structuring factors along the Pacific coast of North America. We collected cytochrome c oxidase I (COI) mtDNA data from populations of 34 species of marine invertebrates sampled coarsely at four coastal locations in California, Oregon, and Alaska, and added published data from 16 additional species. All nine species with non-pelagic development have strong genetic structure. For the 41 species with pelagic development, 13 show significant genetic differentiation, nine of which show striking F_ST levels of 0.1–0.6. Finer scale geographic investigations show unexpected regional patterns of genetic change near Cape Mendocino in northern California for five of the six species tested. The region between Oregon and Alaska is a second focus of intraspecific genetic change, showing differentiation in half the species tested. Across regions, strong genetic subdivision occurs more often than expected in mid-to-high intertidal species, a result that may reflect reduced gene flow due to natural selection along coastal environmental gradients. Finally, the results highlight the importance of making primary research accessible to policymakers, as unexpected barriers to marine dispersal break the coast into separate demographic zones that may require their own management plans.     

Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod

Little is known about how quickly natural populations adapt to changes in their environment and how temporal and spatial variation in selection pressures interact to shape patterns of genetic diversity. We here address these issues with a series of genome scans in four overfished populations of Atlantic cod (Gadus morhua) studied over an 80‐year period. Screening of >1000 gene‐associated single‐nucleotide polymorphisms (SNPs) identified 77 loci that showed highly elevated levels of differentiation, likely as an effect of directional selection, in either time, space or both. Exploratory analysis suggested that temporal allele frequency shifts at certain loci may correlate with local temperature variation and with life history changes suggested to be fisheries induced. Interestingly, however, largely nonoverlapping sets of loci were temporal outliers in the different populations and outliers from the 1928 to 1960 period showed almost complete stability during later decades. The contrasting microevolutionary trajectories among populations resulted in sequential shifts in spatial outliers, with no locus maintaining elevated spatial differentiation throughout the study period. Simulations of migration coupled with observations of temporally stable spatial structure at neutral loci suggest that population replacement or gene flow alone could not explain all the observed allele frequency variation. Thus, the genetic changes are likely to at least partly be driven by highly dynamic temporally and spatially varying selection. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider all dimensions of biocomplexity for evolutionarily sustainable management.     

SNP genotyping and population genomics from expressed sequences – current advances and future possibilities

With the rapid increase in production of genetic data from new sequencing technologies, a myriad of new ways to study genomic patterns in nonmodel organisms are currently possible. Because genome assembly still remains a complicated procedure, and because the functional role of much of the genome is unclear, focusing on SNP genotyping from expressed sequences provides a cost‐effective way to reduce complexity while still retaining functionally relevant information. This review summarizes current methods, identifies ways that using expressed sequence data benefits population genomic inference and explores how current practitioners evaluate and overcome challenges that are commonly encountered. We focus particularly on the additional power of functional analysis provided by expressed sequence data and how these analyses push beyond allele pattern data available from nonfunction genomic approaches. The massive data sets generated by these approaches create opportunities and problems as well – especially false positives. We discuss methods available to validate results from expressed SNP genotyping assays, new approaches that sidestep use of mRNA and review follow‐up experiments that can focus on evolutionary mechanisms acting across the genome.     

Rates of molecular evolution and the fraction of nucleotide positions free to vary

Summary Selective constraints on DNA sequence change were incorporated into a model of DNA divergence by restricting substitutions to a subset of nucleotide positions. A simple model showed that both mutation rate and the fraction of nucleotide positions free to vary are strong determinants of DNA divergence over time.When divergence between two species approaches the fraction of positions free to vary, standard methods that correct for multiple mutations yield severe underestimates of the number of substitutions per site. A modified method appropriate for use with DNA sequence, restriction site, or thermal renaturation data is derived taking this fraction into account. The model also showed that the ratio of divergence in two gene classes (e.g., nuclear and mitochondrial) may vary widely over time even if the ratio of mutation rates remains constant.DNA sequence divergence data are used increasingly to detect differences in rates of molecular evolution. Often, variation in divergence rate is assumed to represent variation in mutation rate. The present model suggests that differing divergence rates among comparisons (either among gene classes or taxa) should be interpreted cautiously. Differences in the fraction of nucleotide positions free to vary can serve as an important alternative hypothesis to explain differences in DNA divergence rates.