scholarly journals Introgression of a block of genome under infinitesimal selection

2017 ◽  
Author(s):  
Himani Sachdeva ◽  
Nicholas H. Barton
Keyword(s):  
Genetic Variability ◽  
Infinite Number ◽  
Branching Process ◽  
Directional Selection ◽  
Native Population ◽  
Adaptive Introgression ◽  
Long Run ◽  
Number Of Genes ◽  
Polygenic Selection ◽  
Process Approximation

AbstractAdaptive introgression is common in nature and can be driven by selection acting on multiple, linked genes. We explore the effects of polygenic selection on introgression under the infinitesimal model with linkage. This model assumes that the introgressing block has an effectively infinite number of genes, each with an infinitesimal effect on the trait under selection. The block is assumed to introgress under directional selection within a native population that is genetically homogeneous. We use individual-based simulations and a branching process approximation to compute various statistics of the introgressing block, and explore how these depend on parameters such as the map length and initial trait value associated with the introgressing block, the genetic variability along the block, and the strength of selection. Our results show that the introgression dynamics of a block under infinitesimal selection is qualitatively different from the dynamics of neutral introgression. We also find that in the long run, surviving descendant blocks are likely to have intermediate lengths, and clarify how the length is shaped by the interplay between linkage and infinitesimal selection. Our results suggest that it may be difficult to distinguish introgression of single loci from that of genomic blocks with multiple, tightly linked and weakly selected loci.

The asymptotic final size distribution of multitype chain-binomial epidemic processes

1999 ◽  
Vol 31 (01) ◽  
pp. 220-234 ◽  
Author(s):  
Mikael Andersson
Keyword(s):  
Branching Process ◽  
Counting Process ◽  
Contact Structure ◽  
Finite Population ◽  
Convergence Result ◽  
System Of Equations ◽  
Final Size ◽  
Linear System Of Equations ◽  
Non Linear System ◽  
Process Approximation

A multitype chain-binomial epidemic process is defined for a closed finite population by sampling a simple multidimensional counting process at certain points. The final size of the epidemic is then characterized, given the counting process, as the smallest root of a non-linear system of equations. By letting the population grow, this characterization is used, in combination with a branching process approximation and a weak convergence result for the counting process, to derive the asymptotic distribution of the final size. This is done for processes with an irreducible contact structure both when the initial infection increases at the same rate as the population and when it stays fixed.

scholarly journals An epidemic model with exposure-dependent severities

2005 ◽  
Vol 42 (04) ◽  
pp. 932-949 ◽  
Author(s):  
Frank Ball ◽  
Tom Britton
Keyword(s):  
Branching Process ◽  
Large Population ◽  
Final Outcome ◽  
Model Parameters ◽  
Final Size ◽  
Strong Law ◽  
Sir Epidemic ◽  
Major Outbreak ◽  
Infectious State ◽  
Process Approximation

We consider a stochastic model for the spread of a susceptible–infective–removed (SIR) epidemic among a closed, finite population, in which there are two types of severity of infectious individuals, namely mild and severe. The type of severity depends on the amount of infectious exposure an individual receives, in that infectives are always initially mild but may become severe if additionally exposed. Large-population properties of the model are derived. In particular, a coupling argument is used to provide a rigorous branching process approximation to the early stages of an epidemic, and an embedding argument is used to derive a strong law and an associated central limit theorem for the final outcome of an epidemic in the event of a major outbreak. The basic reproduction number, which determines whether or not a major outbreak can occur given few initial infectives, depends only on parameters of the mild infectious state, whereas the final outcome in the event of a major outbreak depends also on parameters of the severe state. Moreover, the limiting final size proportions need not even be continuous in the model parameters.

Range expansion of Brewer's blackbird: phenetics of a new population

1971 ◽  
Vol 49 (2) ◽  
pp. 175-183 ◽  
Author(s):  
Dennis M. Power
Keyword(s):  
United States ◽  
Genetic Variability ◽  
Range Expansion ◽  
Founder Effect ◽  
The United States ◽  
Directional Selection ◽  
Population Variability ◽  
Two Samples ◽  
Stable Part ◽  
Made In

The Brewer's blackbird (Euphagus cyanocephalus) is rapidly expanding its range eastward across Ontario and parts of the United States. This study was to determine if phenetic changes have taken place during or immediately after expansion. A sample was collected in 1968 in the vicinity of McKerrow, Ontario, near the periphery of the zone of expansion and where breeding was first recorded in 1962. For comparison, a second collection was made in the stable part of the range near Winnipeg, Manitoba. Statistical comparisons for 37 skin and skeletal characters were made between the two samples for both sexes. Tests for differences in character means suggest that strong directional selection, different from that in the stable part of the range, is not operating in the newly occupied area. Likewise, differences in population variability seem slight and do not show alterations in genetic variability that would be expected during a Carsonian population flush or that would be expected because of a partial founder effect.

scholarly journals How migratory populations become resident

2020 ◽  
Vol 287 (1923) ◽  
pp. 20193011 ◽  
Author(s):  
Tiago de Zoeten ◽  
Francisco Pulido
Keyword(s):  
Environmental Changes ◽  
Threshold Model ◽  
Directional Selection ◽  
Migratory Behaviour ◽  
Migratory Activity ◽  
Threshold Trait ◽  
Evolutionary Response ◽  
Number Of Genes ◽  
In The Wild ◽  
Selection Number

Migratory behaviour is rapidly changing in response to recent environmental changes, yet it is difficult to predict how migration will evolve in the future. To understand what determines the rate of adaptive evolutionary change in migratory behaviour, we simulated the evolution of residency using an individual-based threshold model, which allows for variation in selection, number of genes, environmental effects and assortative mating. Our model indicates that the recent reduction in migratory activity found in a population of Eurasian blackcaps ( Sylvia atricapilla ) is only compatible with this trait being under strong directional selection, in which residents have the highest fitness and fitness declines exponentially with migration distance. All other factors had minor effects on the adaptive response. Under this form of selection, a completely migratory population will become partially migratory in 6 and completely resident in 98 generations, demonstrating the persistence of partial migration, even under strong directional selection. Resident populations will preserve large amounts of cryptic genetic variation, particularly if migration is controlled by a large number of genes with small effects. This model can be used to realistically simulate the evolution of any threshold trait, including semi-continuous traits like migration, for predicting evolutionary response to natural selection in the wild.

The asymptotic final size distribution of multitype chain-binomial epidemic processes

1999 ◽  
Vol 31 (1) ◽  
pp. 220-234 ◽  
Author(s):  
Mikael Andersson
Keyword(s):  
Branching Process ◽  
Counting Process ◽  
Contact Structure ◽  
Finite Population ◽  
Convergence Result ◽  
System Of Equations ◽  
Final Size ◽  
Linear System Of Equations ◽  
Non Linear System ◽  
Process Approximation

A multitype chain-binomial epidemic process is defined for a closed finite population by sampling a simple multidimensional counting process at certain points. The final size of the epidemic is then characterized, given the counting process, as the smallest root of a non-linear system of equations. By letting the population grow, this characterization is used, in combination with a branching process approximation and a weak convergence result for the counting process, to derive the asymptotic distribution of the final size. This is done for processes with an irreducible contact structure both when the initial infection increases at the same rate as the population and when it stays fixed.

scholarly journals An epidemic model with exposure-dependent severities

2005 ◽  
Vol 42 (4) ◽  
pp. 932-949 ◽  
Author(s):  
Frank Ball ◽  
Tom Britton
Keyword(s):  
Branching Process ◽  
Large Population ◽  
Final Outcome ◽  
Model Parameters ◽  
Final Size ◽  
Strong Law ◽  
Sir Epidemic ◽  
Major Outbreak ◽  
Infectious State ◽  
Process Approximation

We consider a stochastic model for the spread of a susceptible–infective–removed (SIR) epidemic among a closed, finite population, in which there are two types of severity of infectious individuals, namely mild and severe. The type of severity depends on the amount of infectious exposure an individual receives, in that infectives are always initially mild but may become severe if additionally exposed. Large-population properties of the model are derived. In particular, a coupling argument is used to provide a rigorous branching process approximation to the early stages of an epidemic, and an embedding argument is used to derive a strong law and an associated central limit theorem for the final outcome of an epidemic in the event of a major outbreak. The basic reproduction number, which determines whether or not a major outbreak can occur given few initial infectives, depends only on parameters of the mild infectious state, whereas the final outcome in the event of a major outbreak depends also on parameters of the severe state. Moreover, the limiting final size proportions need not even be continuous in the model parameters.

scholarly journals Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle

PLoS Genetics ◽  
2021 ◽  
Vol 17 (7) ◽  
pp. e1009652
Author(s):  
Troy N. Rowan ◽  
Harly J. Durbin ◽  
Christopher M. Seabury ◽  
Robert D. Schnabel ◽  
Jared E. Decker
Keyword(s):  
Local Adaptation ◽  
Complex Traits ◽  
Evolutionary Model ◽  
Directional Selection ◽  
Birth Date ◽  
Environmental Selection ◽  
Selective Forces ◽  
Candidate Loci ◽  
Stressful Environments ◽  
Polygenic Selection

Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal’s birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system’s possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.

scholarly journals Epidemics on Random Graphs with Tunable Clustering

2008 ◽  
Vol 45 (03) ◽  
pp. 743-756 ◽  
Author(s):  
Tom Britton ◽  
Maria Deijfen ◽  
Andreas N. Lagerås ◽  
Mathias Lindholm
Keyword(s):  
Random Graphs ◽  
Branching Process ◽  
Intersection Graph ◽  
Epidemic Threshold ◽  
Random Intersection Graph ◽  
Large Outbreak ◽  
Process Approximation

In this paper a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. We investigate how these quantities vary with the clustering in the graph and find that, as the clustering increases, the epidemic threshold decreases. The network is modeled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if there is at least one group that they are both members of.

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