Michael G. Sovic

Venomics of new world pit vipers: genus-wide comparisons of venom proteomes across Agkistrodon

UNLABELLED We report a genus-wide comparison of venom proteome variation across New World pit vipers in the genus Agkistrodon. Despite the wide variety of habitats occupied by this genus and that all its taxa feed on diverse species of vertebrates and invertebrate prey, the venom proteomes of copperheads, cottonmouths, and cantils are remarkably similar, both in the type and relative abundance of their different toxin families. The venoms from all the eleven species and subspecies sampled showed relatively similar proteolytic and PLA2 activities. In contrast, quantitative differences were observed in hemorrhagic and myotoxic activities in mice. The highest myotoxic activity was observed with the venoms of A. b. bilineatus, followed by A. p. piscivorus, whereas the venoms of A. c. contortrix and A. p. leucostoma induced the lowest myotoxic activity. The venoms of Agkistrodon bilineatus subspecies showed the highest hemorrhagic activity and A. c. contortrix the lowest. Compositional and toxicological analyses agree with clinical observations of envenomations by Agkistrodon in the USA and Central America. A comparative analysis of Agkistrodon shows that venom divergence tracks phylogeny of this genus to a greater extent than in Sistrurus rattlesnakes, suggesting that the distinct natural histories of Agkistrodon and Sistrurus clades may have played a key role in molding the patterns of evolution of their venom protein genes. BIOLOGICAL SIGNIFICANCE A deep understanding of the structural and functional profiles of venoms and of the principles governing the evolution of venomous systems is a goal of venomics. Isolated proteomics analyses have been conducted on venoms from many species of vipers and pit vipers. However, making sense of these large inventories of data requires the integration of this information across multiple species to identify evolutionary and ecological trends. Our genus-wide venomics study provides a comprehensive overview of the toxic arsenal across Agkistrodon and a ground for understanding the natural histories of, and clinical observations of envenomations by, species of this genus.

Phylogeny-based comparative analysis of venom proteome variation in a clade of rattlesnakes (Sistrurus sp.).

A long-standing question in evolutionary studies of snake venoms is the extent to which phylogenetic divergence and diet can account for between-species differences in venom composition. Here we apply phylogeny-based comparative methods to address this question. We use data on venom variation generated using proteomic techniques for all members of a small clade of rattlesnakes (Sistrurus sp.) and two outgroups for which phylogenetic and diet information is available. We first complete the characterization of venom variation for all members of this clade with a “venomic” analysis of pooled venoms from two members of this genus, S. milarius streckeri and S. m. milarius. These venoms exhibit the same general classes of proteins as those found in other Sistrurus species but differ in their relative abundances of specific protein families. We then test whether there is significant phylogenetic signal in the relative abundances of major venom proteins across species and if diet (measured as percent mammals and lizards among all prey consumed) covaries with venom composition after phylogenetic divergence is accounted for. We found no evidence for significant phylogenetic signal in venom variation: K values for seven snake venom proteins and two composite venom variables [PC 1 and 2]) were all nonsignificant and lower (mean = 0.11+0.06 sd) than mean K values (>0.35) previously reported for a wide range of morphological, life history, physiological and behavioral traits from other species. Finally, analyses based on Phylogenetic Generalized Least Squares (PGLS) methods reveal that variation in abundance of some venom proteins, most strongly CRISP is significantly related to snake diet. Our results demonstrate that venom variation in these snakes is evolutionarily a highly labile trait even among very closely-related taxa and that natural selection acting through diet variation may play a role in molding the relative abundance of specific venom proteins.

AftrRAD: a pipeline for accurate and efficient de novo assembly of RADseq data

An increase in studies using restriction site‐associated DNA sequencing (RADseq) methods has led to a need for both the development and assessment of novel bioinformatic tools that aid in the generation and analysis of these data. Here, we report the availability of AftrRAD, a bioinformatic pipeline that efficiently assembles and genotypes RADseq data, and outputs these data in various formats for downstream analyses. We use simulated and experimental data sets to evaluate AftrRADs ability to perform accurate de novo assembly of loci, and we compare its performance with two other commonly used programs, stacks and pyrad. We demonstrate that AftrRAD is able to accurately assemble loci, while accounting for indel variation among alleles, in a more computationally efficient manner than currently available programs. AftrRAD run times are not strongly affected by the number of samples in the data set, making this program a useful tool when multicore systems are not available for parallel processing, or when data sets include large numbers of samples.

Genetic diversity in migratory bats: Results from RADseq data for three tree bat species at an Ohio windfarm

Genetic analyses can identify the scale at which wildlife species are impacted by human activities, and provide demographic information useful for management. Here, we use thousands of nuclear DNA genetic loci to assess whether genetic structure occurs within Lasiurus cinereus (Hoary Bat), L. borealis (Red Bat), and Lasionycteris noctivagans (Silver-Haired Bat) bats found at a wind turbine site in Ohio, and to also estimate demographic parameters in each of these three groups. Our specific goals are to: 1) demonstrate the feasibility of isolating RADseq loci from these tree bat species, 2) test for genetic structure within each species, including any structure that may be associated with time (migration period), and 3) use coalescent-based modeling approaches to estimate genetically-effective population sizes and patterns of population size changes over evolutionary timescales. Thousands of loci were successfully genotyped for each species, demonstrating the value of RADseq for generating polymorphic loci for population genetic analyses in these bats. There was no evidence for genetic differentiation between groups of samples collected at different times throughout spring and fall migration, suggesting that individuals from each species found at the wind facility are from single panmictic populations. Estimates of present-day effective population sizes varied across species, but were consistently large, on the order of 10(5)-10(6). All populations show evidence of expansions that date to the Pleistocene. These results, along with recent work also suggesting limited genetic structure in bats across North America, argue that additional biomarker systems such as stable-isotopes or trace elements should be investigated as alternative and/or complementary approaches to genetics for sourcing individuals collected at single wind farm sites.

Within-group relatedness is correlated with colony-level social structure and reproductive sharing in a social fish

In group‐living species, the degree of relatedness among group members often governs the extent of reproductive sharing, cooperation and conflict within a group. Kinship among group members can be shaped by the presence and location of neighbouring groups, as these provide dispersal or mating opportunities that can dilute kinship among current group members. Here, we assessed how within‐group relatedness varies with the density and position of neighbouring social groups in Neolamprologus pulcher, a colonial and group‐living cichlid fish. We used restriction site‐associated DNA sequencing (RADseq) methods to generate thousands of polymorphic SNPs. Relative to microsatellite data, RADseq data provided much tighter confidence intervals around our relatedness estimates. These data allowed us to document novel patterns of relatedness in relation to colony‐level social structure. First, the density of neighbouring groups was negatively correlated with relatedness between subordinates and dominant females within a group, but no such patterns were observed between subordinates and dominant males. Second, subordinates at the colony edge were less related to dominant males in their group than subordinates in the colony centre, suggesting a shorter breeding tenure for dominant males at the colony edge. Finally, subordinates who were closely related to their same‐sex dominant were more likely to reproduce, supporting some restraint models of reproductive skew. Collectively, these results demonstrate that within‐group relatedness is influenced by the broader social context, and variation between groups in the degree of relatedness between dominants and subordinates can be explained by both patterns of reproductive sharing and the nature of the social landscape.

The effects of locus number, genetic divergence, and genotyping error on the utility of dominant markers for hybrid identification

In surveys of hybrid zones, dominant genetic markers are often used to identify individuals of hybrid origin and assign these individuals to one of several potential hybrid classes. Quantitative analyses that address the statistical power of dominant markers in such inference are scarce. In this study, dominant genotype data were simulated to evaluate the effects of, first, the number of loci analyzed, second, the magnitude of differentiation between the markers scored in the groups that are hybridizing, and third, the level of genotyping error associated with the data when assigning individuals to various parental and hybrid categories. The overall performance of the assignment methods was relatively modest at the lowest level of divergence examined (Fst ˜ 0.4), but improved substantially at higher levels of differentiation (Fst ˜ 0.67 or 0.8). The effect of genotyping error was dependent on the level of divergence between parental taxa, with larger divergences tempering the effects of genotyping error. These results highlight the importance of considering the effects of each of the variables when assigning individuals to various parental and hybrid categories, and can help guide decisions regarding the number of loci employed in future hybridization studies to achieve the power and level of resolution desired.

The Use of Fluorescent Randomly Amplified Polymorphic DNA Markers to Identify Hybrids: A Case Study Evaluating the Origins of Saugeye following the Cessation of Stocking in an Ohio Reservoir

Abstract Hybridization and introgression continue to gain recognition as important issues in the management and conservation of native fishes. It is often necessary to identify hybrids in natural populations and to distinguish among individuals of various hybrid categories. Molecular methods are important for these purposes, and it is valuable if researchers have a range of molecular methods to apply, since each method has unique advantages and disadvantages. The determination of the best class of marker for a particular study depends on various factors, including the goals of the study, the resolution required, and the genomic and marker information already available for the taxa of interest. We modified a protocol to generate fluorescent randomly amplified polymorphic DNA (FRAPD) markers for hybridization studies. To our knowledge, this type of marker has not previously been used for hybrid identification. To demonstrate the utility of the modified methods, FRAPD markers were used to evaluate potential ...

gwasurvivr: an R package for genome wide survival analysis

Summary To address the limited software options for performing survival analyses with millions of SNPs, we developed gwasurvivr, an R/Bioconductor package with a simple interface for conducting genome wide survival analyses using VCF (outputted from Michigan or Sanger imputation servers) and IMPUTE2 files. To decrease the number of iterations needed for convergence when optimizing the parameter estimates in the Cox model we modified the R package survival such that the covariates in the model are first fit without the SNP, and those parameter estimates are used as initial points. We benchmarked gwasurvivr with other GWAS software capable of conducting genome wide survival analysis (genipe, SurvivalGWAS_SV, and GWASTools). gwasurvivr is significantly faster and shows better scalability as sample size and number of SNPs increase. Availability and implementation gwasurvivr, including source code, documentation, and vignette are available at: https://github.com/suchestoncampbelllab/gwasurvivr Contact Abbas Rizvi, Rizvi.33@osu.edu; Lara E Sucheston-Campbell, sucheston-campbell.1@osu.edu Supplementary information Supplementary data are available at https://github.com/suchestoncampbelllab/gwasurvivr_manuscript

assignPOP: An R package for population assignment using genetic, non-genetic, or integrated data in a machine-learning framework

Summary 1.The use of biomarkers (e.g., genetic, microchemical, and morphometric characteristics) to discriminate among and assign individuals to a population can benefit species conservation and management by facilitating our ability to understand population structure and demography. 2.Tools that can evaluate the reliability of large genomic datasets for population discrimination and assignment, as well as allow their integration with non-genetic markers for the same purpose, are lacking. Our R package, assignPOP, provides both functions in a supervised machine-learning framework. 3.assignPOP uses Monte-Carlo and K-fold cross-validation procedures, as well as principal component analysis (PCA), to estimate assignment accuracy and membership probabilities, using training (i.e., baseline source population) and test (i.e., validation) datasets that are independent. A user then can build a specified predictive model based on the relative sizes of these datasets and classification functions, including linear discriminant analysis, support vector machine, naive Bayes, decision tree, and random forest. 4.assignPOP can benefit any researcher who seeks to use genetic or non-genetic data to infer population structure and membership of individuals. assignPOP is a freely available R package under the GPL license, and can be downloaded from CRAN or at https://github.com/alexkychen/assignPOP. A comprehensive tutorial can also be found at https://alexkychen.github.io/assignPOP/. This article is protected by copyright. All rights reserved.