8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Range-wide neutral and adaptive genetic structure of an endemic herb from Amazonian Savannas

      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

          Conserving genetic diversity in rare and narrowly distributed endemic species is essential to maintain their evolutionary potential and minimize extinction risk under future environmental change. In this study we assess neutral and adaptive genetic structure and genetic diversity in Brasilianthus carajensis (Melastomataceae), an endemic herb from Amazonian Savannas. Using RAD sequencing we identified a total of 9365 SNPs in 150 individuals collected across the species’ entire distribution range. Relying on assumption-free genetic clustering methods and environmental association tests we then compared neutral with adaptive genetic structure. We found three neutral and six adaptive genetic clusters, which could be considered management units (MU) and adaptive units (AU), respectively. Pairwise genetic differentiation ( F ST) ranged between 0.024 and 0.048, and even though effective population sizes were below 100, no significant inbreeding was found in any inferred cluster. Nearly 10 % of all analysed sequences contained loci associated with temperature and precipitation, from which only 25 sequences contained annotated proteins, with some of them being very relevant for physiological processes in plants. Our findings provide a detailed insight into genetic diversity, neutral and adaptive genetic structure in a rare endemic herb, which can help guide conservation and management actions to avoid the loss of unique genetic variation.

          Abstract

          Rare and narrowly distributed plants are particularly sensitive to the loss and fragmentation of their natural habitats, which ultimately result in reduced genetic diversity and a weakened ability to adapt to changing environments. In this study we evaluated the genetic health of a narrowly distributed herb from Amazonian Savannas. Relying on Next-Generation Sequencing technologies we were able to take a detailed glance at a representative portion of the plant’s whole genome, assessing genetic diversity, genetic composition and adaptations to local environmental conditions. Our results provide clear guidance on how to avoid the loss of unique genetic variation in this unique plant.

          Related collections

          Most cited references57

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

          Between a rock and a hard place: evaluating the relative risks of inbreeding and outbreeding for conservation and management.

          As populations become increasingly fragmented, managers are often faced with the dilemma that intentional hybridization might save a population from inbreeding depression but it might also induce outbreeding depression. While empirical evidence for inbreeding depression is vastly greater than that for outbreeding depression, the available data suggest that risks of outbreeding, particularly in the second generation, are on par with the risks of inbreeding. Predicting the relative risks in any particular situation is complicated by variation among taxa, characters being measured, level of divergence between hybridizing populations, mating history, environmental conditions and the potential for inbreeding and outbreeding effects to be occurring simultaneously. Further work on consequences of interpopulation hybridization is sorely needed with particular emphasis on the taxonomic scope, the duration of fitness problems and the joint effects of inbreeding and outbreeding. Meanwhile, managers can minimize the risks of both inbreeding and outbreeding by using intentional hybridization only for populations clearly suffering from inbreeding depression, maximizing the genetic and adaptive similarity between populations, and testing the effects of hybridization for at least two generations whenever possible.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Extinction debt of high-mountain plants under twenty-first-century climate change

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

              Revealing cryptic spatial patterns in genetic variability by a new multivariate method.

              Increasing attention is being devoted to taking landscape information into account in genetic studies. Among landscape variables, space is often considered as one of the most important. To reveal spatial patterns, a statistical method should be spatially explicit, that is, it should directly take spatial information into account as a component of the adjusted model or of the optimized criterion. In this paper we propose a new spatially explicit multivariate method, spatial principal component analysis (sPCA), to investigate the spatial pattern of genetic variability using allelic frequency data of individuals or populations. This analysis does not require data to meet Hardy-Weinberg expectations or linkage equilibrium to exist between loci. The sPCA yields scores summarizing both the genetic variability and the spatial structure among individuals (or populations). Global structures (patches, clines and intermediates) are disentangled from local ones (strong genetic differences between neighbors) and from random noise. Two statistical tests are proposed to detect the existence of both types of patterns. As an illustration, the results of principal component analysis (PCA) and sPCA are compared using simulated datasets and real georeferenced microsatellite data of Scandinavian brown bear individuals (Ursus arctos). sPCA performed better than PCA to reveal spatial genetic patterns. The proposed methodology is implemented in the adegenet package of the free software R.
                Bookmark

                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                AoB Plants
                AoB Plants
                aobpla
                AoB Plants
                Oxford University Press (US )
                2041-2851
                February 2020
                31 January 2020
                31 January 2020
                : 12
                : 1
                : plaa003
                Affiliations
                [1 ] Universidade Federal Rural da Amazônia/Museu Paraense Emílio Goeldi, Programa de Pós-graduação em Ciências Biológicas - Botânica Tropical , Belém-PA, Brazil
                [2 ] Museu Paraense Emílio Goeldi, Programa de Capacitação Institucional (PCI) , Belém-PA, Brazil
                [3 ] Instituto Tecnológico Vale, Desenvolvimento Sustentável , Belém-PA, Brazil
                [4 ] Universidade Federal do Pará, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Genética e Biologia Molecular , Belém-PA, Brazil
                [5 ] Universidade de São Paulo, Departamento de Ecologia , São Paulo-SP, Brazil
                Author notes
                Corresponding author’s email address: r.jaffe@ 123456ib.usp.br
                Article
                plaa003
                10.1093/aobpla/plaa003
                7043808
                7a55b0fc-5d50-4072-b7b1-91395112e42e
                © The Author(s) 2020. Published by Oxford University Press on behalf of the Annals of Botany Company.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 August 2019
                : 21 January 2020
                : 28 January 2020
                : 26 February 2020
                Page count
                Pages: 11
                Funding
                Funded by: Instituto Tecnológico Vale, National Council for Scientific and Technological Development
                Award ID: 300652/2019-4
                Award ID: 300714/2017-3
                Award ID: 316067/2018-0
                Award ID: 301616/2017-5
                Funded by: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 10.13039/501100002322
                Award ID: 88887.156652/2017-00
                Award ID: 88882.347930/2019-01
                Categories
                Special Issue: The Ecology and Genetics of Population Differentiation in Plants

                Plant science & Botany
                brasilianthus carajensis,conservation genomics,environmental association tests (eat),evolutionary significant unit,genotype–environment association (gea),single nucleotide polymorphism (snp)

                Comments

                Comment on this article