Genomic Consequences of Long-Term Population Decline in Brown Eared Pheasant

Population genetic theory and empirical evidence indicate that deleterious alleles can be purged in small populations. However, this viewpoint remains controversial. It is unclear whether natural selection is powerful enough to purge deleterious mutations when wild populations continue to decline. Pheasants are terrestrial birds facing a long-term risk of extinction as a result of anthropogenic perturbations and exploitation. Nevertheless, there are scant genomics resources available for conservation management and planning. Here, we analyzed comparative population genomic data for the three extant isolated populations of Brown eared pheasant (Crossoptilon mantchuricum) in China. We showed that C. mantchuricum has low genome-wide diversity and a contracting effective population size because of persistent declines over the past 100,000 years. We compared genome-wide variation in C. mantchuricum with that of its closely related sister species, the Blue eared pheasant (C. auritum) for which the conservation concern is low. There were detrimental genetic consequences across all C. mantchuricum genomes including extended runs of homozygous sequences, slow rates of linkage disequilibrium decay, excessive loss-of-function mutations, and loss of adaptive genetic diversity at the major histocompatibility complex region. To the best of our knowledge, this study is the first to perform a comprehensive conservation genomic analysis on this threatened pheasant species. Moreover, we demonstrated that natural selection may not suffice to purge deleterious mutations in wild populations undergoing long-term decline. The findings of this study could facilitate conservation planning for threatened species and help recover their population size.     

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression‐based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression‐like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.     

Reconstructing cranial evolution in an extinct hominin

Homo erectus is the first hominin species with a truly cosmopolitan distribution and resembles recent humans in its broad spatial distribution. The microevolutionary events associated with dispersal and local adaptation may have produced similar population structure in both species. Understanding the evolutionary population dynamics of H. erectus has larger implications for the emergence of later Homo lineages in the Middle Pleistocene. Quantitative genetics models provide a means of interrogating aspects of long-standing H. erectus population history narratives. For the current study, cranial fossils were sorted into six major palaeodemes from sites across Africa and Asia spanning 1.8–0.1 Ma. Three-dimensional shape data from the occipital and frontal bones were used to compare intraspecific variation and test evolutionary hypotheses. Results indicate that H. erectus had higher individual and group variation than Homo sapiens, probably reflecting different levels of genetic diversity and population history in these spatially disperse species. This study also revealed distinct evolutionary histories for frontal and occipital bone shape in H. erectus, with a larger role for natural selection in the former. One scenario consistent with these findings is climate-driven facial adaptation in H. erectus, which is reflected in the frontal bone through integration with the orbits.     

Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed

Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).     

Landscape Features Fail to Explain Spatial Genetic Structure in White-Tailed Deer Across Ohio,USA

Landscape features influence wildlife movements across spatial scales and have the potential to influence the spread of disease. Chronic wasting disease (CWD) is a fatal prion disease affecting members of the family Cervidae, particularly white-tailed deer (Odocoileus virginianus), and the first positive CWD case in a wild deer in Ohio, USA, was recorded in 2020. Landscape genetics approaches are increasingly used to better understand potential pathways for CWD spread in white-tailed deer, but little is known about genetic structure of white-tailed deer in Ohio. The objectives of our study were to evaluate spatial genetic structure in white-tailed deer across Ohio and compare the support for isolation by distance (IBD) and isolation by landscape resistance (IBR) models in explaining this structure. We collected genetic data from 619 individual deer from 24 counties across Ohio during 2007–2009. We used microsatellite genotypes from 619 individuals genotyped at 11 loci and haplotypes from a 547-base pair fragment of the mitochondrial DNA control region. We used spatial and non-spatial genetic clustering tests to evaluate genetic structure in both types of genetic data and empirically optimized landscape resistance surfaces to compare IBD and IBR using microsatellite data. Non-spatial genetic clustering tests failed to detect spatial genetic structure, whereas spatial genetic clustering tests indicated subtle spatial genetic structure. The IBD model consistently outperformed IBR models that included land cover, traffic volume, and streams. Our results indicated widespread genetic connectivity of white-tailed deer across Ohio and negligible effects of landscape features. These patterns likely reflect some combination of minimal resistive effects of landscape features on white-tail deer movement in Ohio and the effects of regional recolonization or translocation. We encourage continued CWD surveillance in Ohio, particularly in the proximity of confirmed cases. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.     

A review of mycotoxin biosynthetic pathways: associated genes and their expressions under the influence of climatic factors

Fungal contamination of agricultural commodities, particularly by mycotoxigenic fungi, represents an enormous concern for global food security in terms of feeding the world's growing population with sufficient and safe food. Not only do they reduce crop yield and quality, but they also produce substantial numbers of mycotoxins, which pose serious adverse health effects in human and animals. As the genome of most mycotoxigenic species have been sequenced, the gene clusters involved in the biosynthesis of agriculturally important mycotoxins including aflatoxins, fumonisins, ochratoxins, zearalenone and trichothecenes, have been largely identified and characterised, with their roles elucidated by researchers. This review provides a comprehensive overview of the current knowledge of genes involved in the biosynthetic pathways of mycotoxins. In addition, the influence of climatic factors including water, temperature and carbon dioxide on differential mycotoxin gene expressions have been highlighted. Overall, the relationship between the relative expression of key regulatory and structural genes under different environmental conditions is significantly correlated with mycotoxins production. This indicates that mycotoxin gene induction can be used as a reliable indicator or marker to monitor mycotoxin production pre-and-post harvest. Furthermore, current strategies to manage mycotoxin risks still require improvement. Thus, an accurate understanding of the molecular mechanisms of mycotoxin biosynthesis in mycotoxigenic species could help to develop an innovative, robust targeted control strategy. This could include the exploitation of novel compounds, which can inhibit biosynthetic genes, to minimise mycotoxin risks.