22
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Maternal Effects on Anogenital Distance in a Wild Marmot Population

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In mammals, prenatal exposure to sex steroid hormones may have profound effects on later behavior and fitness and have been reported under both laboratory and field conditions. Anogenital distance is a non-invasive measure of prenatal exposure to sex steroid hormones. While we know that intra-uterine position and litter sex ratio influence anogenital distance, there are other, heretofore unstudied, factors that could influence anogenital distance, including maternal effects. We capitalized on a long-term study of wild yellow-bellied marmots ( Marmota flaviventris) to study the importance of maternal effects on explaining variation in anogenital distance and found significant effects. The strength of these effects varied annually. Taken together, our data highlights the strong variability due to environmental effects, and illustrates the importance of additive genetic and maternal genetic effects on neonatal anogenital distance. We suspect that, as others apply recently popularised quantitative genetic techniques to study free-living populations, such effects will be identified in other systems.

          Related collections

          Most cited references25

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            How to separate genetic and environmental causes of similarity between relatives.

            Related individuals often have similar phenotypes, but this similarity may be due to the effects of shared environments as much as to the effects of shared genes. We consider here alternative approaches to separating the relative contributions of these two sources to phenotypic covariances, comparing experimental approaches such as cross-fostering, traditional statistical techniques and more complex statistical models, specifically the 'animal model'. Using both simulation studies and empirical data from wild populations, we demonstrate the ability of the animal model to reduce bias due to shared environment effects such as maternal or brood effects, especially where pedigrees contain multiple generations and immigration rates are low. However, where common environment effects are strong, a combination of both cross-fostering and an animal model provides the best way to avoid bias. We illustrate ways of partitioning phenotypic variance into components of additive genetic, maternal genetic, maternal environment, common environment, permanent environment and temporal effects, but also show how substantial confounding between these different effects may occur. Whilst the flexibility of the mixed model approach is extremely useful for incorporating the spatial, temporal and social heterogeneity typical of natural populations, the advantages will inevitably be restricted by the quality of pedigree information and care needs to be taken in specifying models that are appropriate to the data.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The Relationship between Anogenital Distance, Fatherhood, and Fertility in Adult Men

              Background Anogenital distance (AGD), a sexually dimorphic measure of genital development, is a marker for endocrine disruption in animal studies and may be shorter in infant males with genital anomalies. Given the correlation between anogenital distance and genital development, we sought to determine if anogenital distance varied in fertile compared to infertile adult men. Methods A cross sectional study of consecutive men being evaluated for infertility and men with proven fertility was recruited from an andrology clinic. Anogenital distance (the distance from the posterior aspect of the scrotum to the anal verge) and penile length (PL) were measured using digital calipers. ANOVA and linear regression were used to determine correlations between AGD, fatherhood status, and semen analysis parameters (sperm density, motility, and total motile sperm count). Findings A total of 117 infertile men (mean age: 35.3±17.4) and 56 fertile men (mean age: 44.8±9.7) were recruited. The infertile men possessed significantly shorter mean AGD and PL compared to the fertile controls (AGD: 31.8 vs 44.6 mm, PL: 107.1 vs 119.5 mm, p<0.01). The difference in AGD persisted even after accounting for ethnic and anthropomorphic differences. In addition to fatherhood, on both unadjusted and adjusted linear regression, AGD was significantly correlated with sperm density and total motile sperm count. After adjusting for demographic and reproductive variables, for each 1 cm increase in a man's AGD, the sperm density increases by 4.3 million sperm per mL (95% CI 0.53, 8.09, p = 0.03) and the total motile sperm count increases by 6.0 million sperm (95% CI 1.34, 10.58, p = 0.01). On adjusted analyses, no correlation was seen between penile length and semen parameters. Conclusion A longer anogenital distance is associated with fatherhood and may predict normal male reproductive potential. Thus, AGD may provide a novel metric to assess reproductive potential in men.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                20 March 2014
                : 9
                : 3
                : e92718
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America
                [2 ]Département de Biologie, École Normale Supeérieure de Lyon, Lyon, France
                [3 ]The Rocky Mountain Biological Laboratory, Crested Butte, Colorado, United States of America
                [4 ]Departamento de Biología, Universidad Autónoma de Madrid, Madrid, Spain
                [5 ]School of Biological Sciences, University of Aberdeen, Aberdeen, United Kingdom
                University of Barcelona, Faculty of Biology, Spain
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JGAM. Performed the experiments: TDF DTB RM JGAM. Analyzed the data: TDF DTB RM JGAM. Wrote the paper: TDF DTB RM JGAM.

                Article
                PONE-D-13-51049
                10.1371/journal.pone.0092718
                3961422
                24651864
                be931b8d-6202-4c62-b7f1-d5d8732d8eee
                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
                : 4 December 2013
                : 25 February 2014
                Page count
                Pages: 5
                Funding
                DTB was supported by the National Geographic Society, UCLA (Faculty Senate and the Division of Life Sciences), a Rocky Mountain Biological Laboratory research fellowship, and by the NSF (IDBR-0754247 and DEB-1119660 to DTB, as well as DBI 0242960 and 0731346 to the Rocky Mountain Biological Laboratory). RM was supported by postdoctoral fellowships from the Spanish Ministerio de Innovación y Ciencia and the Fulbright program. JGAM was supported by a FRQNT postdoctoral fellowship and the NSF. 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
                Anatomy
                Reproductive System
                Genital Anatomy
                Digestive System
                Developmental Biology
                Morphogenesis
                Evolutionary Biology
                Genetics
                Population Biology
                Veterinary Science
                Animal Types
                Wildlife
                Zoology
                Mammalogy

                Uncategorized
                Uncategorized

                Comments

                Comment on this article