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      Genetic and Phenotypic Divergence in a Dung Beetle 50 Years After Its Introduction to Australia

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          ABSTRACT

          Species translocations are increasingly being used in conservation and for biological control. The success of a translocation can be strongly influenced by the evolutionary processes occurring during the early phase of the introduction and the subsequent spread to new regions. In this study, morphological variation and population genetic structure were assessed in the African dung beetle Digitonthophagus gazella, a species that was intentionally introduced to Australia for biological control in 1968 and subsequently spread widely across the northern part of the continent. A dataset based on 1594 neutral single nucleotide polymorphism (SNP) loci that were genotyped in 187 individuals from 12 sites revealed significant genetic divergences between sites (global F ST = 0.118) and provides evidence of restricted gene flow among established populations at small to moderate spatial scales (74–500 km). Geometric morphometric analyses revealed significant divergence among populations in the shape of the foretibia, a trait ecologically important for tunnelling in soil and dung. Moreover, phenotypic divergence in this trait for both sexes was significantly higher than genetic differentiation at selectively neutral loci ( P ST >  F ST), suggesting that directional selection is contributing to the phenotypic divergences among populations. Our study shows how population structure can establish quickly in an introduced species and highlights the importance of considering local adaptation when performing translocations on established populations.

          Abstract

          Species translocations for conservation and biological control can be influenced by evolutionary processes occurring during the initial introduction and subsequent spread. This study assessed the morphological variation and population genetic structure of the African dung beetle, Digitonthophagus gazella, introduced to Australia in 1968, using data from 1594 SNP loci genotyped in 187 individuals from 12 sites. The findings revealed significant genetic divergence and restricted gene flow among populations, as well as significant phenotypic divergence in a key morphological trait due to directional selection, emphasising the importance of local adaptation in translocation efforts.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                boikhutso.rapalai@research.uwa.edu.au
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                10 November 2024
                November 2024
                : 14
                : 11 ( doiID: 10.1002/ece3.v14.11 )
                : e70536
                Affiliations
                [ 1 ] Centre for Evolutionary Biology The University of Western Australia Crawley Western Australia Australia
                [ 2 ] School of Biological Sciences The University of Western Australia Crawley Western Australia Australia
                Author notes
                [*] [* ] Correspondence:

                Boikhutso Lerato Rapalai ( boikhutso.rapalai@ 123456research.uwa.edu.au )

                Author information
                https://orcid.org/0000-0002-3773-779X
                https://orcid.org/0000-0003-0562-1474
                Article
                ECE370536 ECE-2024-06-01236.R2
                10.1002/ece3.70536
                11550911
                840dd16d-76e3-426d-bc6a-f6c9c5d313ed
                © 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 October 2024
                : 20 June 2024
                : 24 October 2024
                Page count
                Figures: 13, Tables: 6, Pages: 21, Words: 13400
                Funding
                Funded by: Australian Government, Department of Agriculture, Fisheries and Forestry, Rural Research and Development for Profit Program , doi 10.13039/100015539;
                Award ID: 16‐03‐016
                Categories
                Evolutionary Ecology
                Research Article
                Research Article
                Custom metadata
                2.0
                November 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.5.1 mode:remove_FC converted:10.11.2024

                Evolutionary Biology
                digitonthophagus gazella,introduced species,phenotypic adaptation,population structure,single nucleotide polymorphisms

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