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Background Mitochondrial DNA is remarkably polymorphic. This is why animal geneticists survey mitochondrial genomes variations for fundamental and applied purposes. We present here an approach to sequence whole mitochondrial genomes using nanopore long-read sequencing. Our method relies on the selective elimination of nuclear DNA using an exonuclease treatment and on the amplification of circular mitochondrial DNA using a multiple displacement amplification step. Results We optimized each preparative step to obtain a 100 million-fold enrichment of horse mitochondrial DNA relative to nuclear DNA. We sequenced these amplified mitochondrial DNA using nanopore sequencing technology and obtained mitochondrial DNA reads that represented up to half of the sequencing output. The sequence reads were 2.3 kb of mean length and provided an even coverage of the mitochondrial genome. Long-reads spanning half or more of the whole mtDNA provided a coverage that varied between 118X and 488X. We evaluated SNPs identified using these long-reads by Sanger sequencing as ground truth and found a precision of 100.0%; a recall of 93.1% and a F1-score of 0.964 using the Twilight horse mtDNA reference. The choice of the mtDNA reference impacted variant calling efficiency with F1-scores varying between 0.947 and 0.964. Conclusions Our method to amplify mtDNA and to sequence it using the nanopore technology is usable for mitochondrial DNA variant analysis. With minor modifications, this approach could easily be applied to other large circular DNA molecules.

Background The low cost and rapidity of microsatellite analysis have led to the development of several markers for many species. Because in non-invasive genetics it is recommended to genotype individuals using few loci, generally a subset of markers is selected. The choice of different marker panels by different research groups studying the same population can cause problems and bias in data analysis. A priority issue in conservation genetics is the comparability of data produced by different labs with different methods. Here, we compared data from previous and ongoing studies to identify a panel of microsatellite loci efficient for the long-term monitoring of Apennine brown bears ( Ursus arctos marsicanus ), aiming at reducing genotyping uncertainty and allowing reliable individual identifications overtimes. Results We examined all microsatellite markers used up to now and identified 19 candidate loci. We evaluated the efficacy of 13 of the most commonly used loci analyzing 194 DNA samples belonging to 113 distinct bears selected from the Italian national biobank. We compared data from 4 different marker subsets on the basis of genotyping errors, allelic patterns, observed and expected heterozygosity, discriminatory powers, number of mismatching pairs, and probability of identity. The optimal marker set was selected evaluating the low molecular weight, the high discriminatory power, and the low occurrence of genotyping errors of each primer. We calibrated allele calls and verified matches among genotypes obtained in previous studies using the complete set of 13 STRs (Short Tandem Repeats), analyzing six invasive DNA samples from distinct individuals. Differences in allele-sizing between labs were consistent, showing a substantial overlap of the individual genotyping. Conclusions The proposed marker set comprises 11 Ursus specific markers with the addition of cxx20, the canid-locus less prone to genotyping errors, in order to prevent underestimation (maximizing the discriminatory power) and overestimation (minimizing the genotyping errors) of the number of Apennine brown bears. The selected markers allow saving time and costs with the amplification in multiplex of all loci thanks to the same annealing temperature. Our work optimizes the available resources by identifying a shared panel and a uniform methodology capable of improving comparisons between past and future studies.

Political scientists are making increasing use of the methodologies of behavior genetics in an attempt to uncover whether or not political behavior is heritable, as well as the specific genotypes that might act as predisposing factors for—or predictors of—political “phenotypes.” Noteworthy among the latter are a series of candidate gene association studies in which researchers claim to have discovered one or two common genetic variants that predict such behaviors as voting and political orientation. We critically examine the candidate gene association study methodology by considering, as a representative example, the recent study by Fowler and Dawes according to which “two genes predict voter turnout.” In addition to demonstrating, on the basis of the data set employed by Fowler and Dawes, that two genes do not predict voter turnout, we consider a number of difficulties, both methodological and genetic, that beset the use of gene association studies, both candidate and genome-wide, in the social and behavioral sciences.

Population genetic data underpin many studies of behavioral, ecological, and evolutionary processes in wild populations and contribute to effective conservation management. However, collecting genetic samples can be challenging when working with endangered, invasive, or cryptic species. Environmental DNA (eDNA) offers a way to sample genetic material non-invasively without requiring visual observation. While eDNA has been trialed extensively as a biodiversity and biosecurity monitoring tool with a strong taxonomic focus, it has yet to be fully explored as a means for obtaining population genetic information. Here, we review current research that employs eDNA approaches for the study of populations. We outline challenges facing eDNA-based population genetic methodologies, and suggest avenues of research for future developments. We advocate that with further optimizations, this emergent field holds great potential as part of the population genetics toolkit.

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, whereas loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well.

This introduction to the topical collection on Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology, and life history provides an overview of conceptual, theoretical, methodological, and empirical progress in research on pace-of-life syndromes (POLSs) over the last decade. The topical collection has two main goals. First, we briefly describe the history of POLS research and provide a refined definition of POLS that is applicable to various key levels of variation (genetic, individual, population, species). Second, we summarise the main lessons learned from current POLS research included in this topical collection. Based on an assessment of the current state of the theoretical foundations and the empirical support of the POLS hypothesis, we propose (i) conceptual refinements of theory, particularly with respect to the role of ecology in the evolution of (sexual dimorphism in) POLS, and (ii) methodological and statistical approaches to the study of POLS at all major levels of variation. This topical collection further holds (iii) key empirical examples demonstrating how POLS structures may be studied in wild populations of (non)human animals, and (iv) a modelling paper predicting POLS under various ecological conditions. Future POLS research will profit from the development of more explicit theoretical models and stringent empirical tests of model assumptions and predictions, increased focus on how ecology shapes (sex-specific) POLS structures at multiple hierarchical levels, and the usage of appropriate statistical tests and study designs.

Poor mental health has consistently been associated with substance use (smoking, alcohol drinking, cannabis use, and consumption of caffeinated drinks). To properly inform public health policy it is crucial to understand the mechanisms underlying these associations, and most importantly, whether or not they are causal. In this pre-registered systematic review, we assessed the evidence for causal relationships between mental health and substance use from Mendelian randomization (MR) studies, following PRISMA. We rated the quality of included studies using a scoring system that incorporates important indices of quality, such as the quality of phenotype measurement, instrument strength, and use of sensitivity methods. Sixty-three studies were included for qualitative synthesis. The final quality rating was '-' for 16 studies, '- +' for 37 studies, and '+'for 10 studies. There was robust evidence that higher educational attainment decreases smoking and that there is a bi-directional, increasing relationship between smoking and (symptoms of) mental disorders. Another robust finding was that higher educational attainment increases alcohol use frequency, but decreases binge-drinking and alcohol use problems, and that mental disorders causally lead to more alcohol drinking without evidence for the reverse. The current MR literature increases our understanding of the relationship between mental health and substance use. Bi-directional causal relationships are indicated, especially for smoking, providing further incentive to strengthen public health efforts to decrease substance use. Future MR studies should make use of large(r) samples in combination with detailed phenotypes, a wide range of sensitivity methods, and triangulate with other research methods.

Social interactions among individuals are ubiquitous both in animals and in plants, and in natural as well as domestic populations. These interactions affect both the direction and the magnitude of responses to selection and are a key factor in evolutionary success of species and in the design of breeding schemes in agriculture. At present, however, very little is known of the contribution of social effects to heritable variance in trait values. Here we present estimates of the direct and social genetic variance in growth rate, feed intake, back fat thickness, and muscle depth in a population of 14,032 domestic pigs with known pedigree. Results show that social effects contribute the vast majority of heritable variance in growth rate and feed intake in this population. Total heritable variance expressed relative to phenotypic variance was 71% for growth rate and 70% for feed intake. These values clearly exceed the usual range of heritability for those traits. Back fat thickness and muscle depth showed no heritable variance due to social effects. Our results suggest that genetic improvement in agriculture can be substantially advanced by redirecting breeding schemes, so as to capture heritable variance due to social effects.

Although scores of experiments have examined the ecological consequences of transgenic Bacillus thuringiensis (Bt) crops, debates continue regarding the nontarget impacts of this technology. Quantitative reviews of existing studies are crucial for better gauging risks and improving future risk assessments. To encourage evidence-based risk analyses, we constructed a searchable database for nontarget effects of Bt crops. A meta-analysis of 42 field experiments indicates that nontarget invertebrates are generally more abundant in Bt cotton and Bt maize fields than in nontransgenic fields managed with insecticides. However, in comparison with insecticide-free control fields, certain nontarget taxa are less abundant in Bt fields.