50
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Understanding and using quantitative genetic variation

      review-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

          Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.

          Related collections

          Most cited references51

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

          Marker-assisted selection: an approach for precision plant breeding in the twenty-first century.

          DNA markers have enormous potential to improve the efficiency and precision of conventional plant breeding via marker-assisted selection (MAS). The large number of quantitative trait loci (QTLs) mapping studies for diverse crops species have provided an abundance of DNA marker-trait associations. In this review, we present an overview of the advantages of MAS and its most widely used applications in plant breeding, providing examples from cereal crops. We also consider reasons why MAS has had only a small impact on plant breeding so far and suggest ways in which the potential of MAS can be realized. Finally, we discuss reasons why the greater adoption of MAS in the future is inevitable, although the extent of its use will depend on available resources, especially for orphan crops, and may be delayed in less-developed countries. Achieving a substantial impact on crop improvement by MAS represents the great challenge for agricultural scientists in the next few decades.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

            The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              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.
                Bookmark

                Author and article information

                Journal
                Philos Trans R Soc Lond B Biol Sci
                RSTB
                royptb
                Philosophical Transactions of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8436
                1471-2970
                12 January 2010
                12 January 2010
                : 365
                : 1537 , Theme Issue 'Personal perspectives in the life sciences for the Royal Society's 350th anniversary' compiled and edited by Georgina Mace
                : 73-85
                Affiliations
                simpleInstitute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh , West Mains Road, Edinburgh EH9 3JT, UK
                Author notes
                Article
                rstb20090203
                10.1098/rstb.2009.0203
                2842708
                20008387
                ce3e090d-545e-45d1-811f-92735b09bcee
                © 2010 The Royal Society

                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 work is properly cited.

                History
                Categories
                1001
                70
                Articles

                Philosophy of science
                genetics,quantitative genetics,animal breeding,heritability
                Philosophy of science
                genetics, quantitative genetics, animal breeding, heritability

                Comments

                Comment on this article