Simulating the spread of selection-driven genotypes using landscape resistance models for desert bighorn sheep

Landscape genomics analysis provides insights into future climate change-driven risk in rhesus macaque

Climate change significantly affects the suitability of wildlife habitats. Thus, understanding how animals adapt ecologically and genetically to climate change is important for targeted species protection. Rhesus macaques (Macaca mulatta) are widely distributed and multi-climatically adapted primates. This study explored how rhesus macaques adapt to climate change by integrating ecological and genetic methods and applying species distribution models (SDMs) and a gradient forest (GF) model. The findings suggested that temperature seasonality primarily affects habitat suitability and indicated that climate change will have a dramatic impact on macaque populations in the future. We also applied genotype-environment association (GEA) analyses and selection signature analyses to identify genes associated with climate change and provide possible explanations for the adaptation of rhesus macaques to climatic environments. The population genomics analyses suggested that the Taihang population has the highest genomic vulnerability with inbreeding and low heterozygosity. Combined with the higher ecological vulnerability, additional conservation strategies are required for this population under higher risk of climate change. Our work measured the impact of climate change and enabled the identification of populations that exhibit high vulnerability to severe climate change. Such information is useful for selecting populations of rhesus macaques as subject of long-term monitoring or evolutionary rescue under future climate change.

Population connectivity patterns of genetic diversity, immune responses and exposure to infectious pneumonia in a metapopulation of desert bighorn sheep

Habitat fragmentation is an important driver of biodiversity loss and can be remediated through management actions aimed at maintenance of natural connectivity in metapopulations. Connectivity may protect populations from infectious diseases by preserving immunogenetic diversity and disease resistance. However, connectivity could exacerbate the risk of infectious disease spread across vulnerable populations. We tracked the spread of a novel strain of Mycoplasma ovipneumoniae in a metapopulation of desert bighorn sheep Ovis canadensis nelsoni in the Mojave Desert to investigate how variation in connectivity among populations influenced disease outcomes. M. ovipneumoniae was detected throughout the metapopulation, indicating that the relative isolation of many of these populations did not protect them from pathogen invasion. However, we show that connectivity among bighorn sheep populations was correlated with higher immunogenetic diversity, a protective immune response and lower disease prevalence. Variation in protective immunity predicted infection risk in individual bighorn sheep and was associated with heterozygosity at genetic loci linked to adaptive and innate immune signalling. Together, these findings may indicate that population connectivity maintains immunogenetic diversity in bighorn sheep populations in this system and has direct effects on immune responses in individual bighorn sheep and their susceptibility to infection by a deadly pathogen. Our study suggests that the genetic benefits of population connectivity could outweigh the risk of infectious disease spread and supports conservation management that maintains natural connectivity in metapopulations.

Building a bridge between adaptive capacity and adaptive potential to understand responses to environmental change

Adaptive capacity is a topic at the forefront of environmental change research with roots in both social, ecological, and evolutionary science. It is closely related to the evolutionary biology concept of adaptive potential. In this systematic literature review, we: (1) summarize the history of these topics and related fields; (2) assess relationship(s) between the concepts among disciplines and the use of the terms in climate change research, and evaluate methodologies, metrics, taxa biases, and the geographic scale of studies; and (3) provide a synthetic conceptual framework to clarify concepts. Bibliometric analyses revealed the terms have been used most frequently in conservation and evolutionary biology journals, respectively. There has been a greater growth in studies of adaptive potential than adaptive capacity since 2001, but a greater geographical extent of adaptive capacity studies. Few studies include both, and use is often superficial. Our synthesis considers adaptive potential as one process contributing to adaptive capacity of complex systems, notes "sociological" adaptive capacity definitions include actions aimed at desired outcome (i.e., policies) as a system driver whereas "biological" definitions exclude such drivers, and suggests models of adaptive capacity require integration of evolutionary and social-ecological system components.

Genome-wide SNP analysis reveals an increase in adaptive genetic variation through selective breeding of coral

Marine heat waves are increasing in magnitude, duration, and frequency as a result of climate change and are the principal global driver of mortality in reef-building corals. Resilience-based genetic management may increase coral heat tolerance, but it is unclear how temperature responses are regulated at the genome level and thus how corals may adapt to warming naturally or through selective breeding. Here we combine phenotypic, pedigree, and genomic marker data from colonies sourced from a warm reef on the Great Barrier Reef reproductively crossed with conspecific colonies from a cooler reef to produce combinations of warm purebreds and warm-cool hybrid larvae and juveniles. Interpopulation breeding created significantly greater genetic diversity across the coral genome compared to breeding between populations and maintained diversity in key regions associated with heat tolerance and fitness. High-density genome-wide scans of single nucleotide polymorphisms (SNPs) identified alleles significantly associated with larval families reared at 27.5°C (87-2,224 loci), including loci putatively associated with proteins involved in responses to heat stress (cell membrane formation, metabolism, and immune responses). Underlying genetics of these families explained 43% of PCoA multilocus variation in survival, growth, and bleaching responses at 27.5°C and 31°C at the juvenile stage. Genetic marker contribution to total variation in fitness traits (narrow-sense heritability) was high for survival but not for growth and bleaching in juveniles, with heritability of these traits being higher at 31°C relative to 27.5°C. While based on only a limited number of crosses, the mechanistic understanding presented here demonstrates that allele frequencies are affected by one generation of selective breeding, key information for the assessments of genetic intervention feasibility and modelling of reef futures.

Genetic structure of Mycoplasma ovipneumoniae informs pathogen spillover dynamics between domestic and wild Caprinae in the western United States

Spillover diseases have significant consequences for human and animal health, as well as wildlife conservation. We examined spillover and transmission of the pneumonia-associated bacterium Mycoplasma ovipneumoniae in domestic sheep, domestic goats, bighorn sheep, and mountain goats across the western United States using 594 isolates, collected from 1984 to 2017. Our results indicate high genetic diversity of M. ovipneumoniae strains within domestic sheep, whereas only one or a few strains tend to circulate in most populations of bighorn sheep or mountain goats. These data suggest domestic sheep are a reservoir, while the few spillovers to bighorn sheep and mountain goats can persist for extended periods. Domestic goat strains form a distinct clade from those in domestic sheep, and strains from both clades are found in bighorn sheep. The genetic structure of domestic sheep strains could not be explained by geography, whereas some strains are spatially clustered and shared among proximate bighorn sheep populations, supporting pathogen establishment and spread following spillover. These data suggest that the ability to predict M. ovipneumoniae spillover into wildlife populations may remain a challenge given the high strain diversity in domestic sheep and need for more comprehensive pathogen surveillance.

The active spread of adaptive variation for reef resilience

The speed at which species adapt depends partly on the rates of beneficial adaptation generation and how quickly they spread within and among populations. Natural rates of adaptation of corals may not be able to keep pace with climate warming. Several interventions have been proposed to fast-track thermal adaptation, including the intentional translocation of warm-adapted adults or their offspring (assisted gene flow, AGF) and the ex situ crossing of warm-adapted corals with conspecifics from cooler reefs (hybridization or selective breeding) and field deployment of those offspring. The introgression of temperature tolerance loci into the genomic background of cooler-environment corals aims to facilitate adaptation to warming while maintaining fitness under local conditions. Here we use research on selective sweeps and connectivity to understand the spread of adaptive variants as it applies to AGF on the Great Barrier Reef (GBR), focusing on the genus Acropora. Using larval biophysical dispersal modeling, we estimate levels of natural connectivity in warm-adapted northern corals. We then model the spread of adaptive variants from single and multiple reefs and assess if the natural and assisted spread of adaptive variants will occur fast enough to prepare receiving central and southern populations given current rates of warming. We also estimate fixation rates and spatial extent of fixation under multiple release scenarios to inform intervention design. Our results suggest that thermal tolerance is unlikely to spread beyond northern reefs to the central and southern GBR without intervention, and if it does, 30+ generations are needed for adaptive gene variants to reach fixation even under multiple release scenarios. We argue that if translocation, breeding, and reseeding risks are managed, AGF using multiple release reefs can be beneficial for the restoration of coral populations. These interventions should be considered in addition to conventional management and accompanied by strong mitigation of CO2 emissions.

The role of dispersal, selection, and timing of sampling on the false discovery rate of loci under selection during geographic range expansion

Identifying adaptive loci is important to understand the evolutionary potential of species undergoing range expansion. However, in expanding populations, spatial demographic processes such as allele surfing can create spatial patterns of neutral genetic variation that appear similar to those generated through adaptive processes. As a result, the false discovery rate of adaptive loci may be inflated in landscape genomic analyses. Here, we take a simulation modelling approach to investigate how range expansion affects our ability to correctly distinguish between neutral and adaptive genetic variation, using the mountain pine beetle outbreak system as a motivating example. We simulated the demographic and population genetic dynamics of populations undergoing range expansion using an individual-based genetic model CDMetaPOP. We investigated how the false discovery rate of adaptive loci is affected by (i) dispersal capacity, (ii) timing of sampling, and (iii) the strength of selection on an adaptive reference locus. We found that a combination of weak dispersal, weak selection, and early sampling presents the greatest risk of misidentifying loci under selection. Expanding populations present unique challenges to the reliable identification of adaptive loci. We demonstrate that there is a need for further methodological development to account for directional demographic processes in landscape genomics.

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Both candidate gene and neutral genetic diversity correlate with parasite resistance in female Mediterranean mouflon

BACKGROUND

Parasite infections can have substantial impacts on population dynamics and are accordingly a key challenge for wild population management. Here we studied genetic mechanisms driving parasite resistance in a large herbivore through a comprehensive approach combining measurements of neutral (16 microsatellites) and adaptive (MHC DRB1 exon 2) genetic diversity and two types of gastrointestinal parasites (nematodes and coccidia).

RESULTS

While accounting for other extrinsic and intrinsic predictors known to impact parasite load, we show that both neutral genetic diversity and DRB1 are associated with resistance to gastrointestinal nematodes. Intermediate levels of multi-locus heterozygosity maximized nematodes resistance, suggesting that both in- and outbreeding depression might occur in the population. DRB1 heterozygosity and specific alleles effects were detected, suggesting the occurrence of heterozygote advantage, rare-allele effects and/or fluctuating selection. On the contrary, no association was detected between genetic diversity and resistance to coccidia, indicating that different parasite classes are impacted by different genetic drivers.

CONCLUSIONS

This study provides important insights for large herbivores and wild sheep pathogen management, and in particular suggests that factors likely to impact genetic diversity and allelic frequencies, including global changes, are also expected to impact parasite resistance.

Recent advances in conservation and population genomics data analysis

New computational methods and next‐generation sequencing (NGS) approaches have enabled the use of thousands or hundreds of thousands of genetic markers to address previously intractable questions. The methods and massive marker sets present both new data analysis challenges and opportunities to visualize, understand, and apply population and conservation genomic data in novel ways. The large scale and complexity of NGS data also increases the expertise and effort required to thoroughly and thoughtfully analyze and interpret data. To aid in this endeavor, a recent workshop entitled “Population Genomic Data Analysis,” also known as “ConGen 2017,” was held at the University of Montana. The ConGen workshop brought 15 instructors together with knowledge in a wide range of topics including NGS data filtering, genome assembly, genomic monitoring of effective population size, migration modeling, detecting adaptive genomic variation, genomewide association analysis, inbreeding depression, and landscape genomics. Here, we summarize the major themes of the workshop and the important take‐home points that were offered to students throughout. We emphasize increasing participation by women in population and conservation genomics as a vital step for the advancement of science. Some important themes that emerged during the workshop included the need for data visualization and its importance in finding problematic data, the effects of data filtering choices on downstream population genomic analyses, the increasing availability of whole‐genome sequencing, and the new challenges it presents. Our goal here is to help motivate and educate a worldwide audience to improve population genomic data analysis and interpretation, and thereby advance the contribution of genomics to molecular ecology, evolutionary biology, and especially to the conservation of biodiversity.

Laparoscopic ovarian biopsy pick-up method for goats

Biopsy pick-up (BPU) has been considered a safe method to harvest ovarian fragments from live animals. However, no studies have been reported on the use of BPU to collect in vivo ovarian tissue in goats. The goals of this study were: (i) to test different biopsy needle sizes to collect ovarian tissue in situ using the BPU method (Experiment 1), and (ii) to study ovarian tissue features such as preantral follicle density, morphology, class distribution, and stromal cell density in ovarian fragments obtained in vivo through a laparoscopic BPU method (Experiment 2). In Experiment 1, goat ovaries (n = 20) were collected in a slaughterhouse and subjected to in situ BPU. Three needles (16, 18, and 20G) were tested. In Experiment 2, the most efficient biopsy needle from Experiment 1 was used to perform laparoscopic BPU in goats (n = 8). In Experiment 1, the recovery rate was greater (P < 0.05; range 50-62%) with 16G and 18G needles than the 20G (17%) needle. The mean weight of ovarian fragments collected by the 16G needle was greater (P < 0.05) than the 18G and the 20G needle. In Experiment 2, 62 biopsy attempts were performed and 52 ovarian fragments were collected (90% success rate). Overall, 2054 preantral follicles were recorded in 5882 histological sections analyzed. Mean preantral follicular density was 28.4 ± 1.3 follicles per cm². The follicular density differed (P < 0.05) among animals and ovarian fragments within the same animal. The mean stromal cell density in the ovarian fragments was 37.1 ± 0.5 cells per 2500 μm², and differed (P < 0.05) among animals. Moreover, preantral follicle density and stromal cell density were associated (P < 0.001). The percentage of morphologically normal follicles was 70.1 ± 1.2, and differed (P < 0.05) among animals. The majority (79%) of the morphologically normal follicles was classified as primordial follicles, and differed (P < 0.05) among animals and between ovaries. In summary, a laparoscopic BPU method has been developed to harvest ovarian tissue in vivo with a satisfactory success rate in goats. Furthermore, this study described for the first time that goat ovarian biopsy fragments have a high heterogeneity in follicular density, morphology, class distribution, and stromal cell density.