3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Ghost Lineages Highly Influence the Interpretation of Introgression Tests

      research-article
      , ,
      Systematic Biology
      Oxford University Press

      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

          Most species are extinct, those that are not are often unknown. Sequenced and sampled species are often a minority of known ones. Past evolutionary events involving horizontal gene flow, such as horizontal gene transfer, hybridization, introgression, and admixture, are therefore likely to involve “ghosts,” that is extinct, unknown, or unsampled lineages. The existence of these ghost lineages is widely acknowledged, but their possible impact on the detection of gene flow and on the identification of the species involved is largely overlooked. It is generally considered as a possible source of error that, with reasonable approximation, can be ignored. We explore the possible influence of absent species on an evolutionary study by quantifying the effect of ghost lineages on introgression as detected by the popular D-statistic method. We show from simulated data that under certain frequently encountered conditions, the donors and recipients of horizontal gene flow can be wrongly identified if ghost lineages are not taken into account. In particular, having a distant outgroup, which is usually recommended, leads to an increase in the error probability and to false interpretations in most cases. We conclude that introgression from ghost lineages should be systematically considered as an alternative possible, even probable, scenario. [ABBA–BABA; D-statistic; gene flow; ghost lineage; introgression; simulation.]

          Related collections

          Most cited references72

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

          Inference of Population Structure Using Multilocus Genotype Data

          We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The complete genome sequence of a Neandertal from the Altai Mountains

            We present a high-quality genome sequence of a Neandertal woman from Siberia. We show that her parents were related at the level of half siblings and that mating among close relatives was common among her recent ancestors. We also sequenced the genome of a Neandertal from the Caucasus to low coverage. An analysis of the relationships and population history of available archaic genomes and 25 present-day human genomes shows that several gene flow events occurred among Neandertals, Denisovans and early modern humans, possibly including gene flow into Denisovans from an unknown archaic group. Thus, interbreeding, albeit of low magnitude, occurred among many hominin groups in the Late Pleistocene. In addition, the high quality Neandertal genome allows us to establish a definitive list of substitutions that became fixed in modern humans after their separation from the ancestors of Neandertals and Denisovans.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A high-coverage genome sequence from an archaic Denisovan individual.

              We present a DNA library preparation method that has allowed us to reconstruct a high-coverage (30×) genome sequence of a Denisovan, an extinct relative of Neandertals. The quality of this genome allows a direct estimation of Denisovan heterozygosity indicating that genetic diversity in these archaic hominins was extremely low. It also allows tentative dating of the specimen on the basis of "missing evolution" in its genome, detailed measurements of Denisovan and Neandertal admixture into present-day human populations, and the generation of a near-complete catalog of genetic changes that swept to high frequency in modern humans since their divergence from Denisovans.
                Bookmark

                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Syst Biol
                Syst Biol
                sysbio
                Systematic Biology
                Oxford University Press
                1063-5157
                1076-836X
                September 2022
                16 February 2022
                16 February 2022
                : 71
                : 5
                : 1147-1158
                Affiliations
                Laboratoire de Biométrie et Biologie Évolutive UMR5558 , Univ Lyon, Université Lyon 1, CNRS, F-69622 Villeurbanne, France
                Laboratoire de Biométrie et Biologie Évolutive UMR5558 , Univ Lyon, Université Lyon 1, CNRS, F-69622 Villeurbanne, France
                Inria, Centre de Recherche de Lyon , F-69603 Villeurbanne, France
                Laboratoire de Biométrie et Biologie Évolutive UMR5558 , Univ Lyon, Université Lyon 1, CNRS, F-69622 Villeurbanne, France
                Author notes
                Correspondence to be sent to: CNRS Université Claude Bernard Lyon 1, Laboratoire de Biométrie et Biologie Évolutive (LBBE), Bâtiment Mendel, 43 boulevard du 11 Novembre 1918, Villeurbanne, 69622 Cedex, France; E-mail: t.tricou@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-4432-2680
                https://orcid.org/0000-0001-9532-5251
                Article
                syac011
                10.1093/sysbio/syac011
                9366450
                35169846
                7a56fb86-b94f-423c-81df-0d439b540826
                © The Author(s) 2022. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 01 April 2021
                : 01 February 2021
                : 08 February 2022
                : 21 March 2022
                Page count
                Pages: 12
                Funding
                Funded by: French National Research Agency, DOI 10.13039/501100001665;
                Award ID: ANR-19-CE45-0010
                Categories
                Regular Articles
                AcademicSubjects/SCI01130

                Animal science & Zoology
                Animal science & Zoology

                Comments

                Comment on this article