2,162 research outputs found
Data from: No evidence for sibling or parent-offspring coadaptation in a wild population of blue tits, despite high power
No full textFour files: Chick data (both weights and survival); Adult data (both fecundity and survival); Pedigree data; Analysis scriptsParent and offspring behaviours are expected to act as both the agents and targets of selection. This may generate parent-offspring coadaptation in which parent and offspring behaviours become genetically correlated in a way that increases inclusive fitness. Cross-fostering has been used to study parent-offspring coadaptation, with the prediction that offspring raised by non-relatives, or parents raising non-relatives, should suffer fitness costs. Using long-term data from more than 400 partially crossed broods of blue tits (Cyanistes caeruleus) we show there is no difference in mass or survival between crossed and non-crossed chicks. However, previous studies for which the evidence for parent-offspring coadaptation is strongest compare chicks from fully crossed broods with those from non-crossed broods. When parent-offspring coadaptation acts at the level of the brood then partial cross-fostering experiments are not expected to show evidence of coadaptation. To test this, we performed an additional cross-fostering experiment (163 broods) in which clutches were either fully crossed, non-crossed, or partiallycrossed. In agreement with the long-term data, there was no evidence for parent-offspring coadaptationon offspring fitness depsite high power. In addition there was no evidence of effects on parental fitness, nor evidnce of sibling coadaptation, although the power of these tests was more modest.When using this data, please cite the original publication: Thomson CE, Hadfield JD (2018) No evidence for sibling or parent-offspring coadaptation in a wild population of blue tits, despite high power. Evolution, online in advance of print. https://doi.org/10.1111/evo.13642 Additionally, please cite the Dryad data package: Thomson C, Hadfield JD (2018) Data from: No evidence for sibling or parent-offspring coadaptation in a wild population of blue tits, despite high power. Dryad Digital Repository. https://doi.org/10.5061/dryad.845825
Consideration of Interference Correlation Properties in a JD-CDMA Mobile Radio System with Coherent Receiver Antenna Diversity
No full textIn code division multiple access (CDMA) mobile radio systems, both intersymbol interference and multiple access interference arise which can be combatted by using Joint Detection (JD) techniques, to reduce the degradation in performance resulting from time variance, coherent receiver antenna diversity (CRAD) can be used. The application of JD techniques offers the possibility to exploit the knowledge of noise covariances at the receiver. If only intercell (cochannel) interference is considered, the noise covariances in the uplink receiver of a multiple receiver antenna CDMA mobile radio system depend mainly on the directions of arrival (DOAs) of the interfering signals and the receiver antenna placement. Therefore, if the interferer DOAs are known at the base station, these covariances could be estimated. In this thesis, a realistic model of the uplink of a JD CDMA mobile radio system with CRAD is described in which the above mentioned interference cancelling method is used. Simulation results according to this model are given and evaluated.Applied SciencesElectrical EngineeringTelecommunications and Traffic Control Systems Grou
Dairy farmers’ perceptions toward the implementation of on-farm Johne’s disease prevention and control strategies
No full textmplementation of specific management strategies on dairy farms is currently the most effective way to reduce the prevalence of Johne’s disease (JD), an infectious chronic enteritis of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). However, dairy farmers often fail to implement recommended strategies. The objective of this study was to assess perceptions of farmers participating in a JD prevention and control program toward recommended practices, and explore factors that influence whether or not a farmer adopts risk-reducing measures for MAP transmission. Semi-structured interviews were conducted with 25 dairy farmers enrolled in a voluntary JD control program in Alberta, Canada. Principles of classical grounded theory were used for participant selection, interviewing, and data analysis. Additionally, demographic data and MAP infection status were collected and analyzed using quantitative questionnaires and the JD control program database. Farmers’ perceptions were distinguished according to 2 main categories: first, their belief in the importance of JD, and second, their belief in recommended JD prevention and control strategies. Based on these categories, farmers were classified into 4 groups: proactivists, disillusionists, deniers, and unconcerned. The first 2 groups believed in the importance of JD, and proactivists and unconcerned believed in proposed JD prevention and control measures. Groups that regarded JD as important had better knowledge about best strategies to reduce MAP transmission and had more JD risk assessments conducted on their farm. Although not quantified, it also appeared that these groups had more JD prevention and control practices in place. However, often JD was not perceived as a problem in the herd and generally farmers did not regard JD control as a “hot topic” in communications with their herd veterinarian and other farmers. Recommendations regarding how to communicate with farmers and motivate various groups of farmers according to their specific perceptions were provided to optimize adoption of JD prevention and control measures and thereby increase success of voluntary JD control programs
Estimating evolutionary parameters when viability selection is operating.
No full textSome individuals die before a trait is measured or expressed (the invisible fraction), and some relevant traits are not measured in any individual (missing traits). This paper discusses how these concepts can be cast in terms of missing data problems from statistics. Using missing data theory, I show formally the conditions under which a valid evolutionary inference is possible when the invisible fraction and/or missing traits are ignored. These conditions are restrictive and unlikely to be met in even the most comprehensive long-term studies. When these conditions are not met, many selection and quantitative genetic parameters cannot be estimated accurately unless the missing data process is explicitly modelled. Surprisingly, this does not seem to have been attempted in evolutionary biology. In the case of the invisible fraction, viability selection and the missing data process are often intimately linked. In such cases, models used in survival analysis can be extended to provide a flexible and justified model of the missing data mechanism. Although missing traits pose a more difficult problem, important biological parameters can still be estimated without bias when appropriate techniques are used. This is in contrast to current methods which have large biases and poor precision. Generally, the quantitative genetic approach is shown to be superior to phenotypic studies of selection when invisible fractions or missing traits exist because part of the missing information can be recovered from relatives
Natural and sexual selection on MHC genes in Soay sheep
No full textThe major histocompatibility complex (MHC) is one of the most variable gene
families in vertebrates. MHC molecules can recognize antigens from pathogens and
signal immune cells to invoke an adaptive immune response. Pathogen-mediated
selection is believed to be the main force maintaining diversity at MHC genes and
three main hypothesis have been proposed including heterozygote advantage,
negative frequency-dependent selection and fluctuating selection. However, it has
proven hard to demonstrate the exact selection regime that maintains variation in
natural populations. An effective method to examine contemporary selection on MHC
genes is to test for association between MHC genetic variation and fitness. However,
many previous studies suffer from poor genetic tools, low sample size, short time
scale and inappropriate statistical approaches. Also, a critical question, which is
rarely studied, is whether the associations between MHC variation and fitness are
consistent with associations between MHC variation and phenotypic traits that
predict fitness.
Besides the paradigm of pathogen-mediated selection, sexual selection may also
contribute to the maintenance of MHC diversity. MHC-dependent sexual selection
could also occur via three mechanisms including selection for specific alleles or
haplotypes, selection for heterozygosity and selection for compatibility. However, at
present there is no consensus as to which of these mechanisms are involved and
their importance. Previous studies have often suffered from limited genetic and
behavioural data and small sample size, and were rarely able to examine all the
mechanisms together, determine whether signatures of MHC-based non-random
mating are independent of genomic effects or distinguish whether MHC-dependent
sexual selection takes place at the pre- or post-copulatory stage.
For more than three decades, Soay sheep living in the island of Hirta, St Kilda
archipelago have been followed from birth, through all breeding attempts, to death.
With a genetically-inferred multigenerational pedigree, individual fitness of Soay
sheep can be measured directly. In addition, genomic pairwise relatedness and a
genomic measure of individual inbreeding is available for most individuals. Recently,
using genotyping-by-sequencing, a total of eight MHC class IIa haplotypes have
been identified in the study population and 5349 sheep alive between 1985 and 2012
have been diplotyped. This data, together with accurate fitness measurements and a
large number of phenotypic observations makes the Soay sheep a good system to
study selection on MHC class IIa genes. In addition, the availability of a large
number of consort and parentage records enabled us to test for MHC-dependent
sexual selection in Soay sheep more thoroughly than previous studies. Therefore, in
this thesis, taking advantage of this high quality dataset, I study natural and sexual
selection on MHC genes in Soay sheep.
In chapter 2, I investigate natural selection on MHC genes by examining
associations between MHC class IIa variation and fitness measurements including
total fitness and five fitness components using data for from 1080 to 3400 Soay
sheep depending on the measurement. I found haplotypes C and D were associated
with decreased and increased male total fitness respectively. In terms of fitness
components, juvenile survival was positively associated with haplotype divergence
while the above haplotype C and F were associated with adult male breeding
success and adult female lifespan respectively. Consistent with the increased male
total fitness, the rarest haplotype D has increased in frequency throughout the study
period more than expected under neutral expectations. My results suggest that
contemporary selection is acting on MHC class II genes in Soay sheep and that
fitness components may show a different mode of selection to total fitness.
In chapter 3, I test associations between MHC class IIa variation and five
representative phenotypic traits that are associated with fitness: weight, strongyle
faecal egg count, and IgA, IgE and IgG immunoglobulin titres against the
gastrointestinal nematode parasite Teladorsagia circumcincta all collected in Soay
sheep caught in August. I found no association between MHC class IIa genes and
August weight or strongyle faecal egg count. I did, however, find age-, isotype- and
sex-dependent associations between MHC class II genes and immunoglobulin
levels. These results suggest associations between MHC variation and phenotypic
traits are more likely to be found for traits more closely associated with parasite
defence than integrative traits such as body weight and highlight the association
between MHC variation and antibodies in wild populations.
In chapter 4, I use Monte Carlo simulation to investigate evidence for non-random
MHC-dependent mating patterns by all three mechanisms in a free-living population
of Soay sheep. Using 1710 sheep diplotyped at the MHC class IIa region and
genome-wide single-nucleotide polymorphisms (SNPs), together with field
observations of consorts, I found sexual selection against haplotype C in males at
the pre-copulatory stage and sexual selection against female MHC heterozygosity
during the rut. I also found MHC-dependent disassortative mating at the post-copulatory stage, along with strong evidence of inbreeding avoidance at both stages.
Results from generalized linear mixed models suggest that the pattern of MHC-dependent disassortative mating could be a by-product of inbreeding avoidance. My
results therefore suggest that while multiple apparent mechanisms of non-random
mating with respect to the MHC may occur, some of them have alternative
explanations.
In chapter 5, I use 2459 parent-offspring trios to examine whether there was within-trio post-copulatory selection on MHC class IIa genes at both the haplotype and
diplotype levels. I found there was transmission ratio distortion of one of the eight
MHC class II haplotypes (E) which was transmitted less than expected by fathers,
and transmission ratio distortion of another haplotype (A) which was transmitted
more than expected by chance to male offspring. However, in both cases, these
deviations were not significant after correction for multiple tests. In addition, I did not
find any evidence of post-copulatory selection at the diplotype level. These results
imply that, given known parents, there is no strong within-trio post-copulatory
selection on MHC class II genes in this population
Knowledge gaps that hamper prevention and control of Mycobacterium avium subspecies paratuberculosis infection
No full textIn the last decades, many regional and country‐wide control programmes for Johne's disease (JD ) were developed due to associated economic losses, or because of a possible association with Crohn's disease. These control programmes were often not successful, partly because management protocols were not followed, including the introduction of infected replacement cattle, because tests to identify infected animals were unreliable, and uptake by farmers was not high enough because of a perceived low return on investment. In the absence of a cure or effective commercial vaccines, control of JD is currently primarily based on herd management strategies to avoid infection of cattle and restrict within‐farm and farm‐to‐farm transmission. Although JD control programmes have been implemented in most developed countries, lessons learned from JD prevention and control programmes are underreported. Also, JD control programmes are typically evaluated in a limited number of herds and the duration of the study is less than 5 year, making it difficult to adequately assess the efficacy of control programmes. In this manuscript, we identify the most important gaps in knowledge hampering JD prevention and control programmes, including vaccination and diagnostics. Secondly, we discuss directions that research should take to address those knowledge gaps
Evaluation of an alternative method of herd classification for infection with paratuberculosis in cattle herds in the United States
No full textObjective - To develop a better system for classification of herd infection status for paratuberculosis (Johne's disease JD]) in US cattle herds on the basis of the risk of potential transmission of Mycobacterium avium subsp paratubeculosis. Sample - Simulated data for herd size and within-herd prevalence; sensitivity and specificity for test methods obtained from consensus-based estimates. Procedures - Interrelationships among variables influencing interpretation and classification of herd infection status for JD were evaluated by use of simulated data for various herd sizes, true within-herd prevalences, and sampling and testing methods. The probability of finding ≥1 infected animal in herds was estimated for various testing methods and sample sizes by use of hypergeometric random sampling. Results - 2 main components were required for the new herd JD classification system: the probability of detection of infection determined on the basis of test results from a sample of animals and the maximum detected number of animals with positive test results. Tables were constructed of the estimated probability of detection of infection, and the maximum number of cattle with positive test results or fecal pools with positive culture results with 95% confidence for classification of herd JD infection status were plotted. Herd risk for JD was categorized on the basis of 95% confidence that the true within-herd prevalence was ≤15%, ≤10%, ≤5%, or ≤2%. Conclusions and Clinical Relevance - Analysis of the findings indicated that a scientifically rigorous and transparent herd classification system for JD in cattle is feasible.Source type: Electronic(1
Environmental and Parental Influences on Offspring Health and Growth in Great Tits (Parus major)
No full textPMCID: PMC3728352This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Factors associated with participation of Alberta dairy farmers in a voluntary, management-based Johne’s disease control program
No full textThe Alberta Johne's Disease Initiative (AJDI) is a voluntary, management-based prevention and control program for Johne's disease (JD), a wasting disease in ruminants that causes substantial economic losses to the cattle industry. Despite extensive communication about the program's benefits and low cost to participating producers, approximately 35% of Alberta dairy farmers have not enrolled in the AJDI. Therefore, the objective was to identify differences between AJDI nonparticipants and participants that may influence enrollment. Standardized questionnaires were conducted in person on 163 farms not participating and 61 farms participating in the AJDI. Data collected included demographic characteristics, internal factors (e.g., attitudes and beliefs of the farmer toward JD and the AJDI), external factors (e.g., farmers' JD knowledge and on-farm goals and constraints), as well as farmers' use and influence of various information sources. Nonparticipants and participants differed in at least some aspects of all studied categories. Based on logistic regression, participating farms had larger herds, higher self-assessed knowledge of JD, better understanding of AJDI details before participation, and used their veterinarian more often to get information about new management practices and technologies when compared with nonparticipants. In contrast, nonparticipants indicated that time was a major on-farm constraint and that participation in the AJDI would take too much time. They also indicated that they preferred to wait and see how the program worked on other farms before they participated
MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package
No full textGeneralized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form. Markov chain Monte Carlo methods solve this problem by sampling from a series of simpler conditional distributions that can be evaluated. The R package MCMCglmm implements such an algorithm for a range of model fitting problems. More than one response variable can be analyzed simultaneously, and these variables are allowed to follow Gaussian, Poisson, multi(bi)nominal, exponential, zero-inflated and censored distributions. A range of variance structures are permitted for the random effects, including interactions with categorical or continuous variables (i.e., random regression), and more complicated variance structures that arise through shared ancestry, either through a pedigree or through a phylogeny. Missing values are permitted in the response variable(s) and data can be known up to some level of measurement error as in meta-analysis. All simu- lation is done in C/ C++ using the CSparse library for sparse linear systems
- …
