A genetic linkage map for the saltwater crocodile (Crocodylus porosus)

<p>Abstract</p> <p>Background</p> <p>Genome elucidation is now in high gear for many organisms, and whilst genetic maps have been developed for a broad array of species, surprisingly, no such maps exist for a crocodilian, or indeed any other non-avian member of the Class Reptilia. Genetic linkage maps are essential tools for the mapping and dissection of complex quantitative trait loci (QTL), and in order to permit systematic genome scans for the identification of genes affecting economically important traits in farmed crocodilians, a comprehensive genetic linage map will be necessary.</p> <p>Results</p> <p>A first-generation genetic linkage map for the saltwater crocodile (<it>Crocodylus porosus</it>) was constructed using 203 microsatellite markers amplified across a two-generation pedigree comprising ten full-sib families from a commercial population at Darwin Crocodile Farm, Northern Territory, Australia. Linkage analyses identified fourteen linkage groups comprising a total of 180 loci, with 23 loci remaining unlinked. Markers were ordered within linkage groups employing a heuristic approach using CRIMAP v3.0 software. The estimated female and male recombination map lengths were 1824.1 and 319.0 centimorgans (cM) respectively, revealing an uncommonly large disparity in recombination map lengths between sexes (ratio of 5.7:1).</p> <p>Conclusion</p> <p>We have generated the first genetic linkage map for a crocodilian, or indeed any other non-avian reptile. The uncommonly large disparity in recombination map lengths confirms previous preliminary evidence of major differences in sex-specific recombination rates in a species that exhibits temperature-dependent sex determination (TSD). However, at this point the reason for this disparity in saltwater crocodiles remains unclear.</p> <p>This map will be a valuable resource for crocodilian researchers, facilitating the systematic genome scans necessary for identifying genes affecting complex traits of economic importance in the crocodile industry. In addition, since many of the markers placed on this genetic map have been evaluated in up to 18 other extant species of crocodilian, this map will be of intrinsic value to comparative mapping efforts aimed at understanding genome content and organization among crocodilians, as well as the molecular evolution of reptilian and other amniote genomes. As researchers continue to work towards elucidation of the crocodilian genome, this first generation map lays the groundwork for more detailed mapping investigations, as well as providing a valuable scaffold for future genome sequence assembly.</p

Development and characterization of 16 microsatellite markers for the Louisiana pine snake, Pituophis ruthveni, and two congeners of conservation concern

We isolated and characterized 16 microsatellite loci from the Louisiana pine snake, Pituophis ruthveni. Loci were screened in 24 individuals from locations throughout its distribution in Louisiana and Texas. The number of alleles per locus ranged from 4 to 12, observed heterozygosity ranged from 0.200 to 0.875, and the probability of identity ranged from 0.043 to 0.298. We examined cross-species amplification at these loci in P. catenifer (bullsnakes and gopher snakes) and P. melanoleucus (pine snakes). These new markers provide tools for examining the conservation genetics of this species complex. Louisiana pine snakes face numerous threats: population densities are extremely low and their natural habitat has been severely altered and fragmented. In southern Canada, P. catenifer is at the northern extreme of its range and limited by the availability of suitable over-wintering sites. Hence, for these two species reduction of heterozygosity, potential for inbreeding, and increased effects of genetic drift are all of considerable conservation concern

Invasion ecology of wild pigs (Sus scrofa) in Florida, USA: the role of humans in the expansion and colonization of an invasive wild ungulate

Wild pigs (Sus scrofa) are the most widely distributed invasive wild ungulate in the United States, yet the factors that influence wild pig dispersal and colonization at the regional level are poorly understood. Our objective was to use a population genetic approach to describe patterns of dispersal and colonization among populations to gain a greater understanding of the invasion process contributing to the expansion of this species. We used 52 microsatellite loci to produce individual genotypes for 482 swine sampled at 39 locations between 2014 and 2016. Our data revealed the existence of genetically distinct subpopulations (FST = 0.1170, p\0.05). We found evidence of both fine-scale subdivision among the sampling locations, as well as evidence of long term genetic isolation. Several locations exhibited significant admixture (interbreeding) suggesting frequent mixing of individuals among locations; up to 14% of animals were immigrants from other populations. This pattern of admixture suggested successive rounds of human-assisted translocation and subsequent expansion across Florida. We also found evidence of genetically distinct populations that were isolated from nearby populations, suggesting recent introduction by humans. In addition, proximity to wild pig holding facilities was associated with higher migration rates and admixture, likely due to the escape or release of animals. Taken together, these results suggest that human-assisted movement plays a major role in the ecology and rapid population growth of wild pigs in Florida

Understanding variation in salamander ionomes: A nutrient balance approach

Ecological stoichiometry uses information on a few key biological elements (C, N, and P) to explain complex ecological patterns. Although factors driving variation in these elements are well-established, expanding stoichiometric principles to explore dynamics of the many other essential elements comprising biological tissues (i.e., the ionome) is needed to determine their metabolic relationships and better understand biological control of elemental flows through ecosystems. 2. In this paper, we report observations of ionomic variation in two species of salamander (Ambystoma opacum and A. talpoideum) across ontogenic stages using specimens from biological collections of two wetlands sampled over a 30-year period. This unique data set allowed us to explore the extent of ionomic variation between species, among ontogenic stages, between sites, and through time. 3. We found species- and to a lesser extent site-specific differences in C, N, and P along with 13 other elements forming salamander ionomes but saw no evidence of temporal changes. Salamander ionomic composition was most strongly related to ontogeny with relatively higher concentrations of many elements in adult males (i.e., Ca, P, S, Mg, Zn, and Cu) compared to metamorphic juveniles, which had greater amounts of C, Fe, and Mn. 4. In addition to patterns of individual elements, covariance among elements was used to construct multi-elemental nutrient balances, which revealed differences in salamander elemental composition between species and sites and changes in elemental proportions across ontogenic development. These multi-elemental balances distinguished among species-site-ontogenic stage groups better than using only C, N, and P. 5. Overall, this study highlights the responsiveness of consumer ionomes to life-history and environmental variation while reflecting underlying relationships among elements tied to biological function. As such, ionomic studies can provide important insights into factors shaping consumer elemental composition and for predicting how these changes might affect higher-order ecological processes

Rapid Microsatellite Identification from Illumina Paired-End Genomic Sequencing in Two Birds and a Snake

Identification of microsatellites, or simple sequence repeats (SSRs), can be a time-consuming and costly investment requiring enrichment, cloning, and sequencing of candidate loci. Recently, however, high throughput sequencing (with or without prior enrichment for specific SSR loci) has been utilized to identify SSR loci. The direct “Seq-to-SSR” approach has an advantage over enrichment-based strategies in that it does not require a priori selection of particular motifs, or prior knowledge of genomic SSR content. It has been more expensive per SSR locus recovered, however, particularly for genomes with few SSR loci, such as bird genomes. The longer but relatively more expensive 454 reads have been preferred over less expensive Illumina reads. Here, we use Illumina paired-end sequence data to identify potentially amplifiable SSR loci (PALs) from a snake (the Burmese python, Python molurus bivittatus), and directly compare these results to those from 454 data. We also compare the python results to results from Illumina sequencing of two bird genomes (Gunnison Sage-grouse, Centrocercus minimus, and Clark's Nutcracker, Nucifraga columbiana), which have considerably fewer SSRs than the python. We show that direct Illumina Seq-to-SSR can identify and characterize thousands of potentially amplifiable SSR loci for as little as $10 per sample – a fraction of the cost of 454 sequencing. Given that Illumina Seq-to-SSR is effective, inexpensive, and reliable even for species such as birds that have few SSR loci, it seems that there are now few situations for which prior hybridization is justifiable

Density and Dichotomous Family History Measures of Alcohol Use Disorder as Predictors of Behavioral and Neural Phenotypes: A Comparative Study Across Gender and Race/Ethnicity

Background: Family history (FH) is an important risk factor for the development of alcohol use disorder (AUD). A variety of dichotomous and density measures of FH have been used to predict alcohol outcomes; yet, a systematic comparison of these FH measures is lacking. We compared 4 density and 4 commonly used dichotomous FH measures and examined variations by gender and race/ethnicity in their associations with age of onset of regular drinking, parietal P3 amplitude to visual target, and likelihood of developing AUD. Methods: Data from the Collaborative Study on the Genetics of Alcoholism (COGA) were utilized to compute the density and dichotomous measures. Only subjects and their family members with DSM-5 AUD diagnostic information obtained through direct interviews using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) were included in the study. Area under receiver operating characteristic curves were used to compare the diagnostic accuracy of FH measures at classifying DSM-5 AUD diagnosis. Logistic and linear regression models were used to examine associations of FH measures with alcohol outcomes. Results: Density measures had greater diagnostic accuracy at classifying AUD diagnosis, whereas dichotomous measures presented diagnostic accuracy closer to random chance. Both dichotomous and density measures were significantly associated with likelihood of AUD, early onset of regular drinking, and low parietal P3 amplitude, but density measures presented consistently more robust associations. Further, variations in these associations were observed such that among males (vs. females) and Whites (vs. Blacks), associations of alcohol outcomes with density (vs. dichotomous) measures were greater in magnitude. Conclusions: Density (vs. dichotomous) measures seem to present more robust associations with alcohol outcomes. However, associations of dichotomous and density FH measures with different alcohol outcomes (behavioral vs. neural) varied across gender and race/ethnicity. These findings have great applicability for alcohol research examining FH of AUD

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development

Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission

Sequencing three crocodilian genomes to illuminate the evolution of archosaurs and amniotes

The International Crocodilian Genomes Working Group (ICGWG) will sequence and assemble the American alligator (Alligator mississippiensis), saltwater crocodile (Crocodylus porosus) and Indian gharial (Gavialis gangeticus) genomes. The status of these projects and our planned analyses are described

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]