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      Phylogeographic Analysis Suggests a Recent Population Bottleneck in the Rare Red Sea Tridacna squamosina

      , , , ,
      Frontiers in Marine Science
      Frontiers Media SA

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          Abstract

          Giant clams are an important ecological component of coral reefs in the Red Sea, as they enhance the reef’s productivity and provide habitat that can increase diversity. Three species of giant clams, namely Tridacna maxima, T. squamosa, and T. squamosina have been described within the Red Sea. However, due to its scarcity, information about the distribution and ecology of T. squamosina in the Saudi Arabian Red Sea is still lacking. This study used DNA barcoding to confirm the identity of the rare T. squamosina in the Farasan Banks. Six mtCOI fragments (500 bp) of T. squamosina were successfully amplified using the SQUA-primers for the first time. We used our data along with 18 reference sequences (16S) from the online database to assess the genetic diversity and population structure of T. squamosina. Low genetic diversity among the T. squamosina populations inferred from the 16S sequences implies a recent bottleneck for this species, which is supported by their historically higher diversity based on the coalescent-based estimator. Given the small population abundance and limited genetic variation of T. squamosina, it may warrant immediate local protections such as biobanking and fertility preservation programs as well as effective integrated coastal zone management plans.

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          Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

          We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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            On the number of segregating sites in genetical models without recombination

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              Evolutionary relationship of DNA sequences in finite populations.

              F Tajima (1983)
              With the aim of analyzing and interpreting data on DNA polymorphism obtained by DNA sequencing or restriction enzyme technique, a mathematical theory on the expected evolutionary relationship among DNA sequences (nucleons) sampled is developed under the assumption that the evolutionary change of nucleons is determined solely by mutation and random genetic drift. The statistical property of the number of nucleotide differences between randomly chosen nucleons and that of heterozygosity or nucleon diversity is investigated using this theory. These studies indicate that the estimates of the average number of nucleotide differences and nucleon diversity have a large variance, and a large part of this variance is due to stochastic factors. Therefore, increasing sample size does not help reduce the variance significantly The distribution of sample allele (nucleomorph) frequencies is also studied, and it is shown that a small number of samples are sufficient in order to know the distribution pattern.
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                Author and article information

                Journal
                Frontiers in Marine Science
                Front. Mar. Sci.
                Frontiers Media SA
                2296-7745
                February 10 2021
                February 10 2021
                : 8
                Article
                10.3389/fmars.2021.628142
                acb82fd2-eca1-4a37-8dcf-a85f47573a23
                © 2021

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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