A Pre-Vaccination Baseline of SARS-CoV-2 Genetic Surveillance and Diversity in the United States

COVID-19 vaccines were first administered on 15 December 2020, marking an important transition point for the spread of SARS-CoV-2 in the United States (U.S.). Prior to this point in time, the virus spread to an almost completely immunologically naïve population, whereas subsequently, vaccine-induced immune pressure and prior infections might be expected to influence viral evolution. Accordingly, we conducted a study to characterize the spread of SARS-CoV-2 in the U.S. pre-vaccination, investigate the depth and uniformity of genetic surveillance during this period, and measure and otherwise characterize changing viral genetic diversity, including by comparison with more recently emergent variants of concern (VOCs). In 2020, SARS-CoV-2 spread across the U.S. in three phases distinguishable by peaks in the numbers of infections and shifting geographical distributions. Virus was genetically sampled during this period at an overall rate of ~1.2%, though there was a substantial mismatch between case rates and genetic sampling nationwide. Viral genetic diversity tripled over this period but remained low in comparison to other widespread RNA virus pathogens, and although 54 amino acid changes were detected at frequencies exceeding 5%, linkage among them was not observed. Based on our collective observations, our analysis supports a targeted strategy for worldwide genetic surveillance as perhaps the most sensitive and efficient means of detecting new VOCs.

Estimating red fox density using non-invasive genetic sampling and spatial capture–recapture modelling

Spatial capture–recapture modelling (SCR) is a powerful tool for estimating density, population size, and space use of elusive animals. Here, we applied SCR modelling to non-invasive genetic sampling (NGS) data to estimate red fox (Vulpes vulpes) densities in two areas of boreal forest in central (2016–2018) and southern Norway (2017–2018). Estimated densities were overall lower in the central study area (mean = 0.04 foxes per km2 in 2016, 0.10 in 2017, and 0.06 in 2018) compared to the southern study area (0.16 in 2017 and 0.09 in 2018). We found a positive effect of forest cover on density in the central, but not the southern study area. The absence of an effect in the southern area may reflect a paucity of evidence caused by low variation in forest cover. Estimated mean home-range size in the central study area was 45 km2 [95%CI 34–60] for females and 88 km2 [69–113] for males. Mean home-range sizes were smaller in the southern study area (26 km2 [16–42] for females and 56 km2 [35–91] for males). In both study areas, detection probability was session-dependent and affected by sampling effort. This study highlights how SCR modelling in combination with NGS can be used to efficiently monitor red fox populations, and simultaneously incorporate ecological factors and estimate their effects on population density and space use.

Evidence for the Widespread Occurrence of Bacteria Implicated in Acute Oak Decline from Incidental Genetic Sampling

Acute Oak Decline (AOD) is complex syndrome affecting Britain’s keystone native oak species, (Quercus robur L. and Q. petraea L. (Matt.) Liebl.), in some cases causing mortality within five years of symptom development. The most distinguishable symptom is weeping stem lesions, from which four species of bacteria have been isolated: Brenneria goodwinii, Gibbsiella quercinecans, Lonsdalea britannica and Rahnella victoriana. We do not yet know where else these bacteria exist, and little is known about the relationship of the wider oak leaf microbiome (phyllosphere) to acute oak decline. Here we investigate whether incidental evidence from a large oak genome re-sequencing dataset could be used to detect these bacteria in oak foliage, and whether bacterial incidence co-varied with AOD status or location. Oak leaves and buds were sampled from 421 trees at five sites in England. Whole genomic DNA from these samples was shot-gun sequenced with short reads. Non-oak reads were extracted from these data and queried to microbial databases. Reads uniquely matching AOD-associated bacterial genomes were found to be present on trees from all five sites and included trees with active lesions, trees with historic lesions and trees without AOD symptoms. The abundance of the AOD-associated bacteria did not differ between tree health categories but did differ among sites. We conclude that the AOD-associated bacteria may be members of the normal oak microbiome, whose presence on a tree is not sufficient to cause AOD symptoms.

Genetic Structure and Gene Flow in Eastern Grey Kangaroos in an Isolated Conservation Reserve

Dispersal is a key process for population persistence, particularly in fragmented landscapes. Connectivity between habitat fragments can be easily estimated by quantifying gene flow among subpopulations. However, the focus in ecological research has been on endangered species, typically excluding species that are not of current conservation concern. Consequently, our current understanding of the behaviour and persistence of many species is incomplete. A case in point is the eastern grey kangaroo (Macropus giganteus), an Australian herbivore that is subjected to considerable harvesting and population control efforts. In this study, we used non-invasive genetic sampling of eastern grey kangaroos within and outside of the Mourachan Conservation Property to assess functional connectivity. In total, we genotyped 232 samples collected from 17 locations at 20 microsatellite loci. The clustering algorithm indicated the presence of two clusters, with some overlap between the groups within and outside of the reserve. This genetic assessment should be repeated in 10–15 years to observe changes in population structure and gene flow over time, monitoring the potential impact of the planned exclusion fencing around the reserve.

Noninvasive Genetic Assessment Is an Effective Wildlife Research Tool When Compared with Other Approaches

Wildlife research has been indispensable for increasing our insight into ecosystem functioning as well as for designing effective conservation measures under the currently high rates of biodiversity loss. Genetic and genomic analyses might be able to yield the same information on, e.g., population size, health, or diet composition as other wildlife research methods, and even provide additional data that would not be possible to obtain by alternative means. Moreover, if DNA is collected non-invasively, this technique has only minimal or no impact on animal welfare. Nevertheless, the implementation rate of noninvasive genetic assessment in wildlife studies has been rather low. This might be caused by the perceived inefficiency of DNA material obtained non-invasively in comparison with DNA obtained from blood or tissues, or poorer performance in comparison with other approaches used in wildlife research. Therefore, the aim of this review was to evaluate the performance of noninvasive genetic assessment in comparison with other methods across different types of wildlife studies. Through a search of three scientific databases, 113 relevant studies were identified, published between the years 1997 and 2020. Overall, most of the studies (94%) reported equivalent or superior performance of noninvasive genetic assessment when compared with either invasive genetic sampling or another research method. It might be also cheaper and more time-efficient than other techniques. In conclusion, noninvasive genetic assessment is a highly effective research approach, whose efficacy and performance are likely to improve even further in the future with the development of optimized protocols.

Evidence for the Widespread Occurrence of Bacteria Implicated in Acute Oak Decline from Incidental Genetic Sampling

Acute Oak Decline (AOD) is complex syndrome affecting Britain’s keystone native oak species, (Quercus robur L. and Q. petraea L. (Matt.) Liebl.), in some cases causing mortality within five years of symptom development. The most distinguishable symptom is weeping stem lesions, from which four species of bacteria have been isolated: Brenneria goodwinii, Gibbsiella quercinecans, Lonsdalea britannica and Rahnella victoriana. We do not yet know where else these bacteria exist, and little is known about the relationship of the wider oak leaf microbiome (phyllosphere) to acute oak decline. Here we investigate whether incidental evidence from a large oak genome re-sequencing dataset could be used to detect these bacteria in oak foliage, and whether bacterial incidence co-varied with AOD status or location. Oak leaves and buds were sampled from 421 trees at five sites in England. Whole genomic DNA from these samples was shot-gun sequenced with short reads. Non-oak reads were extracted from these data and queried to microbial databases. Reads uniquely matching AOD-associated bacterial genomes were found to be present on trees from all five sites and included trees with active lesions, trees with historic lesions and trees without AOD symptoms. The abundance of the AOD-associated bacteria did not differ between tree health categories but did differ among sites. We conclude that the AOD-associated bacteria may be members of the normal oak microbiome, whose presence on a tree is not sufficient to cause AOD symptoms.

Noninvasive genetic sampling of two flying fox species provides a high rate of genotyping success and a low error rate during amplification

Noninvasive genetic sampling techniques are useful tools for providing genetic data that are crucially needed for determining suitable conservation actions. Yet these methods may be highly unreliable in certain situations for instance, when working with faecal samples of frugivorous species in tropical areas. In this study, we tested the applicability of noninvasive genetic sampling on two Comoro Islands flying fox species: Pteropus livingstonii and P.seychellensis comorensis in order to optimize the sampling and laboratory process. Both mitochondrial (mtDNA) and microsatellite markers were tested using two common faeces conservation protocols (ethanol and silica gel), and the polymerase chain reaction (PCR) success and genotyping error rates were assessed. The average proportion of mtDNA PCRs positive results was 55% for P.livingstonii and 38% for P.s.comorensis, and higher amplification success was obtained for samples preserved in ethanol as compared to silica gel. The average genotyping success rate was high (74% for P.livingstonii and 95% for P.s.comorensis) and the genotyping error rate was low for both species. Despite our results confirm the effectiveness of using noninvasive genetic sampling methods to study flying fox species, the protocol we used can be optimized to provide higher efficiency. Some recommendations related to field sampling protocols and laboratory methods are proposed in order to optimize amplification rate and minimize genotyping errors.

Use of an enclosed elk population to assess two non-invasive methods for estimating population size

Non-invasive genetic sampling and spatially explicit capture-recapture (SCR) models are used increasingly to estimate abundance of wildlife populations, but have not been adequately tested on gregarious animals such as elk (Cervus canadensis), for which correlated space use and movements violate model assumptions of independence. To evaluate the robustness and accuracy of SCR, and to assess the utility of an alternative non-invasive method for estimating density of gregarious ungulates, we utilized a tule elk (Cervus canadensis nannodes) population of known size within a fenced enclosure on the San Luis National Wildlife Refuge in central California. We evaluated fecal genetic SCR to camera trap-based random encounter model (REM) approaches to density estimation based on comparison to the true abundance. We also subsampled the dataset to explore the effects of varying search effort and elk density on the precision and accuracy of results. We found that SCR outperformed REM methods in the full datasets, and reliably provided accurate (relative bias <10%) and reasonably precise (relative standard error ≤20%) estimates of density at moderately low to high densities (6-17 elk/km2), when the subsampling scenarios yielded a minimum average of 20 recaptures. We also found that the number of samples used to construct detection histories was a reliable predictor of precision, and could be used to establish minimum sampling requirements in future population surveys of elk. Although field-testing in free-ranging populations is needed, our results suggest that non-invasive genetic SCR is a promising tool for future population studies and monitoring of elk and potentially other gregarious ungulates. In contrast, the REM estimate of density was highly inaccurate, imprecise, and highly sensitive to camera parameters.

Estimating Red Fox Density Using Non-Invasive Genetic Sampling and Spatial Capture-Recapture Modeling

Spatial capture-recapture modelling (SCR) is a powerful tool for estimating densities, population size and space use of elusive animals. Here, we applied SCR modeling to non-invasive genetic sampling (NGS) data to estimate red fox (Vulpes vulpes) densities in two areas of boreal forest in central (2016 - 2018) and southern Norway (2017 - 2018). Estimated densities were overall lower in the northern study area (mean = 0.04 foxes per km2 [95%CI: 0.02-0.09] in 2016, 0.09 [0.05-0.18] in 2017 and 0.07 [0.04-0.13] in 2018) compared to the southern study area (0.16 [0.09-0.26] in 2017 and 0.10 [0.07-0.16] in 2018). We found a positive effect of forest cover on density in the northern, but not the southern study area. The absence of an effect in the southern area may reflect a paucity of evidence caused by low variation in forest cover, but could also be due to climatic differences (e.g., winter severity) between the two areas. Estimated mean home range size in the northern study area was 45 km2 [34-60] for females and 88 km2 [69-113] for males. Mean home range sizes were smaller in the southern study area (26 km2 [16-42] for females and 56 km2 [35-91] for males). In both study areas, detection probability was session-dependent and affected by sampling effort. This study highlights how SCR modeling in combination with NGS can be used to efficiently monitor red fox populations, and simultaneously incorporate ecological factors and estimate their effects on population density and space-use.