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      Natural Selection on Individual Variation in Tolerance of Gastrointestinal Nematode Infection

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          Abstract

          A 25-year study of wild sheep shows that individuals vary in how quickly they lose weight as parasite infections increase, and that those who lose the least weight when heavily infected produce more offspring.

          Abstract

          Hosts may mitigate the impact of parasites by two broad strategies: resistance, which limits parasite burden, and tolerance, which limits the fitness or health cost of increasing parasite burden. The degree and causes of variation in both resistance and tolerance are expected to influence host–parasite evolutionary and epidemiological dynamics and inform disease management, yet very little empirical work has addressed tolerance in wild vertebrates. Here, we applied random regression models to longitudinal data from an unmanaged population of Soay sheep to estimate individual tolerance, defined as the rate of decline in body weight with increasing burden of highly prevalent gastrointestinal nematode parasites. On average, individuals lost weight as parasite burden increased, but whereas some lost weight slowly as burden increased (exhibiting high tolerance), other individuals lost weight significantly more rapidly (exhibiting low tolerance). We then investigated associations between tolerance and fitness using selection gradients that accounted for selection on correlated traits, including body weight. We found evidence for positive phenotypic selection on tolerance: on average, individuals who lost weight more slowly with increasing parasite burden had higher lifetime breeding success. This variation did not have an additive genetic basis. These results reveal that selection on tolerance operates under natural conditions. They also support theoretical predictions for the erosion of additive genetic variance of traits under strong directional selection and fixation of genes conferring tolerance. Our findings provide the first evidence of selection on individual tolerance of infection in animals and suggest practical applications in animal and human disease management in the face of highly prevalent parasites.

          Author Summary

          Animals can defend themselves against parasites through either resistance (reducing parasite numbers, for example, by killing them) or tolerance (maintaining health as infections levels increase, for example, by repairing damage). Resistance has been well-studied in wild animals, but tolerance has been less so. We analysed data on body weight collected over 25 years on a natural population of Soay sheep, infected with parasitic gut worms. As parasite burden increased, sheep lost weight. Crucially, there was variation among individuals: some lost weight rapidly with increasing infections (i.e., showed “low tolerance”), whereas others lost weight slowly (i.e., showed “high tolerance”). The least tolerant individuals lost 4.5 kg of body weight across the range of parasite burdens that we saw, whereas the most tolerant lost only around 0.36 kg. However, variation in tolerance did not have a heritable genetic basis, so that although tolerance varied between individuals, this was not due to genetic differences. Further analysis revealed that there was natural selection on tolerance. Individuals who were more tolerant of infection produced more offspring over the course of their lives. This study shows that natural selection can act upon resistance and tolerance simultaneously in nature, a result that has implications for both human health and livestock management.

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          Best linear unbiased estimation and prediction under a selection model.

          Mixed linear models are assumed in most animal breeding applications. Convenient methods for computing BLUE of the estimable linear functions of the fixed elements of the model and for computing best linear unbiased predictions of the random elements of the model have been available. Most data available to animal breeders, however, do not meet the usual requirements of random sampling, the problem being that the data arise either from selection experiments or from breeders' herds which are undergoing selection. Consequently, the usual methods are likely to yield biased estimates and predictions. Methods for dealing with such data are presented in this paper.
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            The strength of phenotypic selection in natural populations.

            How strong is phenotypic selection on quantitative traits in the wild? We reviewed the literature from 1984 through 1997 for studies that estimated the strength of linear and quadratic selection in terms of standardized selection gradients or differentials on natural variation in quantitative traits for field populations. We tabulated 63 published studies of 62 species that reported over 2,500 estimates of linear or quadratic selection. More than 80% of the estimates were for morphological traits; there is very little data for behavioral or physiological traits. Most published selection studies were unreplicated and had sample sizes below 135 individuals, resulting in low statistical power to detect selection of the magnitude typically reported for natural populations. The absolute values of linear selection gradients |beta| were exponentially distributed with an overall median of 0.16, suggesting that strong directional selection was uncommon. The values of |beta| for selection on morphological and on life-history/phenological traits were significantly different: on average, selection on morphology was stronger than selection on phenology/life history. Similarly, the values of |beta| for selection via aspects of survival, fecundity, and mating success were significantly different: on average, selection on mating success was stronger than on survival. Comparisons of estimated linear selection gradients and differentials suggest that indirect components of phenotypic selection were usually modest relative to direct components. The absolute values of quadratic selection gradients |gamma| were exponentially distributed with an overall median of only 0.10, suggesting that quadratic selection is typically quite weak. The distribution of gamma values was symmetric about 0, providing no evidence that stabilizing selection is stronger or more common than disruptive selection in nature.
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              An ecologist's guide to the animal model.

              1. Efforts to understand the links between evolutionary and ecological dynamics hinge on our ability to measure and understand how genes influence phenotypes, fitness and population dynamics. Quantitative genetics provides a range of theoretical and empirical tools with which to achieve this when the relatedness between individuals within a population is known. 2. A number of recent studies have used a type of mixed-effects model, known as the animal model, to estimate the genetic component of phenotypic variation using data collected in the field. Here, we provide a practical guide for ecologists interested in exploring the potential to apply this quantitative genetic method in their research. 3. We begin by outlining, in simple terms, key concepts in quantitative genetics and how an animal model estimates relevant quantitative genetic parameters, such as heritabilities or genetic correlations. 4. We then provide three detailed example tutorials, for implementation in a variety of software packages, for some basic applications of the animal model. We discuss several important statistical issues relating to best practice when fitting different kinds of mixed models. 5. We conclude by briefly summarizing more complex applications of the animal model, and by highlighting key pitfalls and dangers for the researcher wanting to begin using quantitative genetic tools to address ecological and evolutionary questions.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                July 2014
                29 July 2014
                : 12
                : 7
                : e1001917
                Affiliations
                [1 ]Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom
                [2 ]Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
                [3 ]Institute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
                [4 ]Centre for Immunity, Infection and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
                [5 ]Centre for Ecology and Conservation, University of Exeter, Cornwall Campus, Penryn, Cornwall, United Kingdom
                [6 ]Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
                Stanford University, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: ADH DHN ALG. Analyzed the data: ADH DHN AJW. Contributed reagents/materials/analysis tools: JMP CB. Contributed to the writing of the manuscript: ADH DHN AJW CB KAW JMP ALG. Conducted fieldwork: JGP.

                [¤]

                Current address: Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom

                Article
                PBIOLOGY-D-14-00948
                10.1371/journal.pbio.1001917
                4114752
                25072883
                00216c39-dadb-416f-a9fa-9e2726db6c9c
                Copyright @ 2014

                This 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.

                History
                : 14 March 2014
                : 19 June 2014
                Page count
                Pages: 13
                Funding
                This study was funded by Natural Environment Research Council ( http://www.nerc.ac.uk/) Standard Grant no. NE/G004854/1 and European Research Council ( http://erc.europa.eu/) Large Grant no. 250098 to JMP. ADH is supported by European Research Council grant no. R/120448-11-1 to V. Lummaa; DHN is supported by Biotechnology and Biological Sciences Research Council ( http://www.bbsrc.ac.uk/) David Phillips Fellowship no. BB/H021686/1; AJW is supported by BBSRC David Phillips Fellowship no. BB/G022976/1; ALG is supported by Princeton University and the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directorate, U.S. Department of Homeland Security, and the Fogarty International Center of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Evolutionary Ecology
                Evolutionary Biology
                Parasitology
                Intestinal Parasites
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

                Life sciences
                Life sciences

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