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      Distribution extension of a vent scale worm Branchinotoglumabipapillata (Polychaeta, Polynoidae) in the Indian Ocean

      research-article
      1 , 2 , 1 , 3 ,
      ZooKeys
      Pensoft Publishers
      16S rRNA, 18S rRNA, CO1, deep-sea, hydrothermal vent, northern Central Indian Ridge, polynoids

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          Abstract

          Branchinotogluma Pettibone, 1985 is the most species-rich genus within the subfamily Lepidonotopodinae Pettibone, 1983, comprising 18 valid species from chemosynthesis-based ecosystems in the Pacific and Indian Oceans. Here, we report a new distributional record of Branchinotogluma bipapillata Zhou, Wang, Zhang & Wang, 2018, at the hydrothermal vent sites on the northern Central Indian Ridge (nCIR). This record represents the northernmost occurrence of B. bipapillata in the Indian Ocean. We conducted a comparative study of the nCIR population and other documented populations using distributional information, morphological traits, and genetic markers (two mitochondrial [ COI, 16S rRNA] and one nuclear [ 18S rRNA] genes). While most morphological characters of B. bipapillata were consistent with those found in the Southwest Indian Ridge (SWIR), variations were noted in the segment with the last branchiae. Molecular data revealed that all populations of B. bipapillata form a single clade, indicating a wide distribution from the SWIR to nCIR, covering ~4,000 km across various ridges in the Indian Ocean. This study presents extensive distribution of a vent species with well-connected populations throughout the Indian Ocean, distinguishing it from many other vent species affected by the dispersal barrier in the Indian Ocean.

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          MEGA11: Molecular Evolutionary Genetics Analysis Version 11

          The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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            jModelTest 2: more models, new heuristics and parallel computing.

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              Gene flow and the geographic structure of natural populations

              M Slatkin (1987)
              There is abundant geographic variation in both morphology and gene frequency in most species. The extent of geographic variation results from a balance of forces tending to produce local genetic differentiation and forces tending to produce genetic homogeneity. Mutation, genetic drift due to finite population size, and natural selection favoring adaptations to local environmental conditions will all lead to the genetic differentiation of local populations, and the movement of gametes, individuals, and even entire populations--collectively called gene flow--will oppose that differentiation. Gene flow may either constrain evolution by preventing adaptation to local conditions or promote evolution by spreading new genes and combinations of genes throughout a species' range. Several methods are available for estimating the amount of gene flow. Direct methods monitor ongoing gene flow, and indirect methods use spatial distributions of gene frequencies to infer past gene flow. Applications of these methods show that species differ widely in the gene flow that they experience. Of particular interest are those species for which direct methods indicate little current gene flow but indirect methods indicate much higher levels of gene flow in the recent past. Such species probably have undergone large-scale demographic changes relatively frequently.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Writing - original draftRole: Writing - review and editingRole: Formal analysisRole: Visualization
                Role: ConceptualizationRole: Writing - review and editingRole: Funding acquisitionRole: Supervision
                Journal
                Zookeys
                Zookeys
                2
                urn:lsid:arphahub.com:pub:45048D35-BB1D-5CE8-9668-537E44BD4C7E
                urn:lsid:zoobank.org:pub:91BD42D4-90F1-4B45-9350-EEF175B1727A
                ZooKeys
                Pensoft Publishers
                1313-2989
                1313-2970
                2024
                14 October 2024
                : 1215
                : 139-149
                Affiliations
                [1 ] Division of Biomedical Research, Korea Research Institute Bioscience and Biotechnology, Daejeon 34141, Republic of Korea Division of Biomedical Research, Korea Research Institute Bioscience and Biotechnology Daejeon Republic of Korea
                [2 ] Division of EcoScience, Ewha Womans University, Seoul 03760, Republic of Korea Ewha Womans University Seoul Republic of Korea
                [3 ] KRIBB School, University of Science and Technology, Daejeon, 34113, Republic of Korea University of Science and Technology Daejeon Republic of Korea
                Author notes
                Corresponding author: Se-Joo Kim ( biosejoo@ 123456kribb.re.kr )

                Academic editor: Andrew Davinack

                Author information
                https://orcid.org/0000-0001-7283-298X
                https://orcid.org/0000-0003-1653-072X
                Article
                129623
                10.3897/zookeys.1215.129623
                11494209
                39440028
                3480378c-7565-466c-ac2e-6b0ad6bc6920
                Won-Kyung Lee, Se-Joo Kim

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 June 2024
                : 02 September 2024
                Funding
                Funded by: National Research Foundation of Korea 501100003725 http://doi.org/10.13039/501100003725
                Ministry of Education of Korea Ministry of Oceans and Fisheries, Korea Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program
                Categories
                Research Article
                Phyllodocida
                Polynoidae
                Faunistics & Distribution
                Identification key
                Phylogeny
                Taxonomy
                Cenozoic
                Indian Ocean
                Oceans

                Animal science & Zoology
                16s rrna,18s rrna,co1,deep-sea,hydrothermal vent,northern central indian ridge,polynoids

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