scholarly journals Using empirical datasets to quantify uncertainty in inferences of landscape genetic resistance due to variation of individual-based genetic distance metrics

2021 ◽  
Author(s):  
Joscha Beninde ◽  
Alain C. Frantz
Keyword(s):  
Gene Flow ◽  
Genetic Distance ◽  
Genetic Resistance ◽  
List Type ◽  
Distance Metrics ◽  
Factorial Correspondence Analysis ◽  
Landscape Resistance ◽  
Landscape Factors ◽  
Landscape Genetic ◽  
The Impact

AbstractEstimates of gene flow are commonly based on inferences of landscape resistance in ecological and evolutionary research and they frequently inform decision-making processes in conservation management. It is therefore imperative that inferences of a landscape factors relevance and its resistance are robust across approaches and reflect real-world gene flow instead of methodological artefacts. Here, we tested the impact of 160 different individual-based pairwise genetic metrics on consistency of landscape genetic inferences.We used three empirical datasets that adopted individual-based sampling schemes and varied in scale (35-25,000 km2) and total number of samples (184-790) and comprise the wild boar, Sus scrofa, the red fox, Vulpes vulpes and the common wall lizard, Podarcis muralis. We made use of a machine-learning algorithm implemented in ResistanceGA to optimally fit resistances of landscape factors to genetic distance metrics and ranked their importance. Employed for nine landscape factors this resulted in 4,320 unique combinations of dataset, landscape factor and genetic distance metric, which provides the basis for quantifying uncertainty in inferences of landscape resistance.Our results demonstrate that there are clear differences in Akaike information criteria (AICc)-based model support and marginal R2-based model fit between different genetic distance metrics. Metrics based on between 1-10 axes of eigenvector-based multivariate analyses (Factorial correspondence analysis, FCA; Principal component analysis, PCA) outperformed more widely used metrics, including the proportion of shared alleles (DPS), with AICc and marginal R2 values often an order of magnitude greater in the former. Across datasets, inferences of the directionality of a landscape factors influence on gene flow, e.g. facilitating or impeding it, changed across different genetic distance metrics. The directionality of the inferred resistance was largely consistent when considering metrics based on between 1-10 FCA/PCA axes.Inferences of landscape genetic resistance need to be corroborated using calculations of multiple individual-based pairwise genetic distance metrics. Our results call for the adoption of eigenvector-based quantifications of pairwise genetic distances. Specifically, a preliminary step of analysis should be incorporated, which explores model ranks across genetic distance metrics derived from FCA and PCA, and, contrary to findings of a simulation study, we demonstrate that it suffices to quantify these distances spanning the first ten axes only.

scholarly journals Simulating Pattern-Process Relationships to Validate Landscape Genetic Models

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
A. J. Shirk ◽  
S. A. Cushman ◽  
E. L. Landguth
Keyword(s):  
Gene Flow ◽  
Genetic Model ◽  
Strong Relationship ◽  
Genetic Isolation ◽  
Landscape Resistance ◽  
Oreamnos Americanus ◽  
Landscape Models ◽  
Genetic Pattern ◽  
Alternative Hypotheses ◽  
Landscape Genetic

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all plausible alternative hypotheses. In this paper, rather than infer the process of gene flow from an observed genetic pattern, we simulate gene flow and determine if the simulated genetic pattern is related to the observed empirical genetic pattern. This is a form of inverse modeling and can be used to independently validate a landscape genetic model. In this study, we used this approach to validate a model of landscape resistance based on elevation, landcover, and roads that was previously related to genetic isolation among mountain goats (Oreamnos americanus) inhabiting the Cascade Range, Washington (USA). The strong relationship between the empirical and simulated patterns of genetic isolation we observed provides independent validation of the resistance model and demonstrates the utility of this approach in supporting landscape genetic inferences.

scholarly journals Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Isobel Routledge ◽  
H. Juliette T. Unwin ◽  
Samir Bhatt
Keyword(s):  
Genetic Distance ◽  
Malaria Transmission ◽  
Spatial Scale ◽  
Model Comparison ◽  
Spatial Information ◽  
Onset Time ◽  
Distance Metrics ◽  
Individual Level ◽  
Reproduction Numbers ◽  
The Impact

AbstractIndividual-level geographic information about malaria cases, such as the GPS coordinates of residence or health facility, is often collected as part of surveillance in near-elimination settings, but could be more effectively utilised to infer transmission dynamics, in conjunction with additional information such as symptom onset time and genetic distance. However, in the absence of data about the flow of parasites between populations, the spatial scale of malaria transmission is often not clear. As a result, it is important to understand the impact of varying assumptions about the spatial scale of transmission on key metrics of malaria transmission, such as reproduction numbers. We developed a method which allows the flexible integration of distance metrics (such as Euclidian distance, genetic distance or accessibility matrices) with temporal information into a single inference framework to infer malaria reproduction numbers. Twelve scenarios were defined, representing different assumptions about the likelihood of transmission occurring over different geographic distances and likelihood of missing infections (as well as high and low amounts of uncertainty in this estimate). These scenarios were applied to four individual level datasets from malaria eliminating contexts to estimate individual reproduction numbers and how they varied over space and time. Model comparison suggested that including spatial information improved models as measured by second order AIC (ΔAICc), compared to time only results. Across scenarios and across datasets, including spatial information tended to increase the seasonality of temporal patterns in reproduction numbers and reduced noise in the temporal distribution of reproduction numbers. The best performing parameterisations assumed long-range transmission (> 200 km) was possible. Our approach is flexible and provides the potential to incorporate other sources of information which can be converted into distance or adjacency matrices such as travel times or molecular markers.

scholarly journals High dispersal capacity of Culicoides obsoletus (Diptera: Ceratopogonidae), vector of bluetongue and Schmallenberg viruses, revealed by landscape genetic analyses

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Antoine Mignotte ◽  
Claire Garros ◽  
Simon Dellicour ◽  
Maude Jacquot ◽  
Marius Gilbert ◽  
...  
Keyword(s):  
Gene Flow ◽  
Environmental Factors ◽  
Isolation By Distance ◽  
Genetic Distances ◽  
Dispersal Capacity ◽  
Culicoides Obsoletus ◽  
High Dispersal ◽  
Western Palearctic ◽  
Landscape Genetic ◽  
The Impact

Abstract Background In the last two decades, recurrent epizootics of bluetongue virus and Schmallenberg virus have been reported in the western Palearctic region. These viruses affect domestic cattle, sheep, goats and wild ruminants and are transmitted by native hematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae). Culicoides dispersal is known to be stratified, i.e. due to a combination of dispersal processes occurring actively at short distances and passively or semi-actively at long distances, allowing individuals to jump hundreds of kilometers. Methods Here, we aim to identify the environmental factors that promote or limit gene flow of Culicoides obsoletus, an abundant and widespread vector species in Europe, using an innovative framework integrating spatial, population genetics and statistical approaches. A total of 348 individuals were sampled in 46 sites in France and were genotyped using 13 newly designed microsatellite markers. Results We found low genetic differentiation and a weak population structure for C. obsoletus across the country. Using three complementary inter-individual genetic distances, we did not detect any significant isolation by distance, but did detect significant anisotropic isolation by distance on a north-south axis. We employed a multiple regression on distance matrices approach to investigate the correlation between genetic and environmental distances. Among all the environmental factors that were tested, only cattle density seems to have an impact on C. obsoletus gene flow. Conclusions The high dispersal capacity of C. obsoletus over land found in the present study calls for a re-evaluation of the impact of Culicoides on virus dispersal, and highlights the urgent need to better integrate molecular, spatial and statistical information to guide vector-borne disease control.

scholarly journals A landscape genetic analysis of swamp rabbits (Sylvilagus aquaticus) suggests forest canopy cover enhances gene flow in an agricultural matrix

2018 ◽  
Vol 96 (6) ◽  
pp. 622-632 ◽  
Author(s):  
Leah K. Berkman ◽  
Clayton K. Nielsen ◽  
Charlotte L. Roy ◽  
Edward J. Heist
Keyword(s):  
Gene Flow ◽  
Genetic Distance ◽  
Canopy Cover ◽  
Population Connectivity ◽  
Causal Modeling ◽  
Suitable Habitat ◽  
Southern Illinois ◽  
Landscape Features ◽  
Tree Canopy Cover ◽  
Landscape Genetic

Habitat loss and fragmentation pose a continued and immediate threat to wildlife and create a persistent need for ecological information at the landscape scale to guide conservation efforts. Landscape features influence population connectivity for many species and genetic analyses can be employed to determine which of these features are most important. Because population connectivity through dispersal is important to the persistence of swamp rabbits (Sylvilagus aquaticus (Bachman, 1837)) at the northern edge of their range, we used a landscape genetic approach to relate gene flow to landscape features that may impact dispersal success. We tested resistance values for attributes of land cover, watercourse corridors, canopy cover, and roads and used causal modeling and redundancy analysis to relate these representations of landscapes to genetic distance for swamp rabbits in southern Illinois, USA. Models that included canopy cover had the strongest correlations with genetic distance and were supported by our methods whereas other models were not. We concluded that high tree canopy cover enhances gene flow and landscape connectivity for swamp rabbits in southern Illinois. Our study provides important empirical evidence that landscape variables may impact the habitat connectivity of swamp rabbits. Preserving dispersal routes for swamp rabbits should focus on improving canopy cover, in both bottomland and upland, to connect suitable habitat.

scholarly journals Fine-Scale Genetic Diversity of the Brazilian Pantaneiro Horse Breed Adapted To Flooded Regions

2021 ◽  
Author(s):  
Marcelo Bchara Nogueira ◽  
Concepta M Pimentel ◽  
Danielle Assis de Faria ◽  
Sandra Aparecida Oliveria Santos ◽  
Patrícia Ianella ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Gene Flow ◽  
Genetic Variability ◽  
Genetic Distance ◽  
Animal Species ◽  
Principal Component ◽  
Mantel Test ◽  
Sampling Location ◽  
Sampling Strategies ◽  
The Impact

Abstract Among the animal species first introduced in Brazil during the country's discovery, horses (Equus caballus) stand out because of their evolutionary history and relationship with humans. Among the Brazilian horse breeds, the Pantaneiro draws attention due to its adaptative traits. Blood samples of 116 Pantaneiro horses were divided into six populations based on their sampling location, aiming to identify the existence of genetic structure and quantify genetic diversity within and between them. Populations were compared to elucidate genetic variability and differentiation better and assess the impact of Pantanal's natural geographic barriers on gene flow between populations. Data from the GGP Equine BeadChip (Geneseek-Neogen, 65.157 SNPs) was used to assess basic diversity parameters, genetic distance (FST), Principal Component Analysis (PCA) and population structure (ADMIXTURE) for the sampled animals. Mantel Test was also performed to investigate the correlation between the populations' genetic and geographic distances. Results showed high genetic variability in all populations, with elevated levels of admixture in their structure. High levels of admixture make it challenging to establish a racial pattern and, consequently, populations within the breed, being that only one of the populations differentiated itself from the others. No significant correlations between genetic and geographic distances were observed, indicating that environmental barriers did not hinder gene flow between populations. and neither farmers selection practices might have change breed genetic composition signficantly Low genetic distance and similar heterozygosity values were observed among populations, suggesting strong genetic proximity and low differentiation. Thereby, the Pantaneiro breed does not exhibit genetic subpopulations and could be considered, for conservation purposes, a single big population in the Panatnal region. This study will support sampling strategies for National genebank.

scholarly journals Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

2016 ◽  
Vol 6 (12) ◽  
pp. 4115-4128 ◽  
Author(s):  
Katherine A. Zeller ◽  
Tyler G. Creech ◽  
Katie L. Millette ◽  
Rachel S. Crowhurst ◽  
Robert A. Long ◽  
...  
Keyword(s):  
Gene Flow ◽  
Landscape Resistance

scholarly journals Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling

2021 ◽  
Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe
Keyword(s):  
Satellite Data ◽  
Meteorological Data ◽  
Atmospheric Composition ◽  
Chemical Detection ◽  
List Type ◽  
Data Types ◽  
Wide Range ◽  
Future Technologies ◽  
The Impact ◽  
Near Future

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field

scholarly journals Does agricultural intensification cause tipping points in ecosystem services?

2021 ◽  
Author(s):  
Stephen C. L. Watson ◽  
Adrian C. Newton ◽  
Lucy E. Ridding ◽  
Paul M. Evans ◽  
Steven Brand ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Agricultural Intensification ◽  
Spatial Dynamics ◽  
Policy Option ◽  
List Type ◽  
Tipping Points ◽  
Software Models ◽  
Non Linear ◽  
Study Interval ◽  
The Impact

Abstract Context Agricultural intensification is being widely pursued as a policy option to improve food security and human development. Yet, there is a need to understand the impact of agricultural intensification on the provision of multiple ecosystem services, and to evaluate the possible occurrence of tipping points. Objectives To quantify and assess the long-term spatial dynamics of ecosystem service (ES) provision in a landscape undergoing agricultural intensification at four time points 1930, 1950, 1980 and 2015. Determine if thresholds or tipping points in ES provision may have occurred and if there are any detectable impacts on economic development and employment. Methods We used the InVEST suite of software models together with a time series of historical land cover maps and an Input–Output model to evaluate these dynamics over an 85-year period in the county of Dorset, southern England. Results Results indicated that trends in ES were often non-linear, highlighting the potential for abrupt changes in ES provision to occur in response to slight changes in underlying drivers. Despite the fluctuations in provision of different ES, overall economic activity increased almost linearly during the study interval, in line with the increase in agricultural productivity. Conclusions Such non-linear thresholds in ES will need to be avoided in the future by approaches aiming to deliver sustainable agricultural intensification. A number of positive feedback mechanisms are identified that suggest these thresholds could be considered as tipping points. However, further research into these feedbacks is required to fully determine the occurrence of tipping points in agricultural systems.

128 Development of an M1-polarized, non-viral chimeric antigen receptor macrophage (CAR-M) platform for cancer immunotherapy

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A141-A141
Author(s):  
Yumi Ohtani ◽  
Kayleigh Ross ◽  
Aditya Dandekar ◽  
Rashid Gabbasov ◽  
Michael Klichinsky
Keyword(s):  
Cancer Immunotherapy ◽  
Chimeric Antigen Receptor ◽  
Scale Up ◽  
Antigen Receptor ◽  
Innate Immune ◽  
List Type ◽  
M1 Phenotype ◽  
The Impact ◽  
Anti Tumor Activity ◽  
Immunosuppressive Factors

BackgroundWe have previously developed CAR-M as a novel cell therapy approach for the treatment of solid tumors.1 CAR-M have the potential to overcome key challenges that cell therapies face in the solid tumor setting – tumor infiltration, immunosuppression, lymphocyte exclusion – and can induce epitope spreading to overcome target antigen heterogeneity. While macrophages transduced with the adenoviral vector Ad5f35 (Ad CAR-M) traffic to tumors, provide robust anti-tumor activity, and recruit and activate T cells, we sought to identify a robust non-viral method of macrophage engineering in order to reduce the cost of goods, manufacturing complexity, and potential immunogenicity associated with viral vectors.MethodsAs innate immune cells, macrophages detect exogenous nucleic acids and respond with inflammatory and apoptotic programs. Thus, we sought to identify a means of mRNA delivery that avoids recognition by innate immune sensors. We screened a broad panel of mRNA encoding an anti-HER2 CAR comprising multiplexed 5’Cap and base modifications using an optimized and scalable electroporation approach and evaluated the impact of interferon-β priming on CAR-M phenotype and function.ResultsWe identified the optimal multiplexed mRNA modifications that led to maximal macrophage viability, transfection efficiency, intensity of CAR expression, and duration of expression. Non-viral HER2 CAR-M phagocytosed and killed human HER2+ tumor cells. Unlike Ad CAR-M, mRNA CAR-M were not skewed toward an M1 state by mRNA electroporation. Priming non-viral CAR-M with IFN-β induced a durable M1 phenotype, as shown by stable upregulation of numerous M1 markers and pathways. IFN-β priming significantly enhanced the anti-tumor activity of CAR but not control macrophages. IFN-β primed mRNA CAR-M were resistant to M2 conversion, maintaining an M1 phenotype despite challenge with various immunosuppressive factors, and converted bystander M2 macrophages toward M1. Interestingly, priming mRNA CAR-M with IFN-β significantly enhanced the persistence of CAR expression, overcoming the known issue of rapid mRNA turnover. RNA-seq analysis revealed that IFN-β priming affected pathways involved in increasing translation and decreasing RNA degradation in human macrophages.ConclusionsWe have established a novel, optimized non-viral CAR-M platform based on chemically modified mRNA and IFN-β priming. IFN-β priming induced a durable M1 phenotype, improved CAR expression, improved CAR persistence, led to enhanced anti-tumor function, and rendered resistance to immunosuppressive factors. This novel platform is amenable to scale-up, GMP manufacturing, and represents an advance in the development of CAR-M.ReferenceKlichinsky M, Ruella M, Shestova O, et al. Human chimeric antigen receptor macrophages for cancer immunotherapy. Nat Biotechnol 2020;38(8):947–953.

scholarly journals Research on the impact of ship traffic flow on the restricted channel segment of the middle Yangtze River based on traffic wave theory

2021 ◽  
Vol 3 (8) ◽  
Author(s):  
Ting Liu ◽  
Gabriel Lodewijks
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Flow Simulation ◽  
Wave Theory ◽  
Flow Density ◽  
List Type ◽  
Ship Traffic ◽  
Traffic Wave ◽  
The Impact ◽  
Channel Segment

Abstract Abstract On the basis of the influence of dry season on ship traffic flow, the gathering and dissipating process of ship traffic flow was researched with Greenshields linear flow—density relationship model, the intrinsic relationship between the ship traffic congestion state and traffic wave in the unclosed restricted channel segment was emphatically explored when the ship traffic flow in a tributary channel inflows, and the influence law of multiple traffic waves on the ship traffic flow characteristics in unclosed restricted segment is revealed. On this basis, the expressions of traffic wave speed and direction, dissipation time of queued ships and the number of ships affected were provided, and combined with Monte Carlo method, the ship traffic flow simulation model in the restricted channel segment was built. The simulation results show that in closed restricted channel segment the dissipation time of ships queued is mainly related to the ship traffic flow rate of segments A and C, and the total number of ships affected to the ship traffic flow rate of segment A. And in unclosed restricted channel segment, the dissipation time and the total number of ships affected are also determined by the meeting time of the traffic waves in addition to the ship traffic flow rate of segments. The research results can provide the theoretical support for further studying the ship traffic flow in unclosed restricted channel segment with multiple tributaries Article Highlights The inflow of tributaries' ship traffic flows has an obvious impact on the traffic conditions in the unenclosed restricted channel segment. The interaction and influence between multiple ship traffic waves and the mechanism of generating new traffic waves are explained. The expression of both dissipation time of queued ships and the total number of ships affected in the closed and unclosed restricted channel segment are given.

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