An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods
Sampling impediments and paucity of suitable material for molecular analyses have precluded the study of speciation and radiation of deep-sea species in Antarctica. We analyzed barcodes together with genome-wide single nucleotide polymorphisms obtained from double digestion restriction site-associat...
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ftpubmed:oai:pubmedcentral.nih.gov:8055997 2023-05-15T13:33:23+02:00 An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods Moles, Juan Derkarabetian, Shahan Schiaparelli, Stefano Schrödl, Michael Troncoso, Jesús S. Wilson, Nerida G. Giribet, Gonzalo 2021-04-19 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055997/ http://www.ncbi.nlm.nih.gov/pubmed/33875688 https://doi.org/10.1038/s41598-021-87244-5 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055997/ http://www.ncbi.nlm.nih.gov/pubmed/33875688 http://dx.doi.org/10.1038/s41598-021-87244-5 © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . CC-BY Sci Rep Article Text 2021 ftpubmed https://doi.org/10.1038/s41598-021-87244-5 2021-04-25T00:37:07Z Sampling impediments and paucity of suitable material for molecular analyses have precluded the study of speciation and radiation of deep-sea species in Antarctica. We analyzed barcodes together with genome-wide single nucleotide polymorphisms obtained from double digestion restriction site-associated DNA sequencing (ddRADseq) for species in the family Antarctophilinidae. We also reevaluated the fossil record associated with this taxon to provide further insights into the origin of the group. Novel approaches to identify distinctive genetic lineages, including unsupervised machine learning variational autoencoder plots, were used to establish species hypothesis frameworks. In this sense, three undescribed species and a complex of cryptic species were identified, suggesting allopatric speciation connected to geographic or bathymetric isolation. We further observed that the shallow waters around the Scotia Arc and on the continental shelf in the Weddell Sea present high endemism and diversity. In contrast, likely due to the glacial pressure during the Cenozoic, a deep-sea group with fewer species emerged expanding over great areas in the South-Atlantic Antarctic Ridge. Our study agrees on how diachronic paleoclimatic and current environmental factors shaped Antarctic communities both at the shallow and deep-sea levels, promoting Antarctica as the center of origin for numerous taxa such as gastropod mollusks. Text Antarc* Antarctic Antarctica Weddell Sea PubMed Central (PMC) Antarctic Weddell Weddell Sea Scientific Reports 11 1 |
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Article Moles, Juan Derkarabetian, Shahan Schiaparelli, Stefano Schrödl, Michael Troncoso, Jesús S. Wilson, Nerida G. Giribet, Gonzalo An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
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Sampling impediments and paucity of suitable material for molecular analyses have precluded the study of speciation and radiation of deep-sea species in Antarctica. We analyzed barcodes together with genome-wide single nucleotide polymorphisms obtained from double digestion restriction site-associated DNA sequencing (ddRADseq) for species in the family Antarctophilinidae. We also reevaluated the fossil record associated with this taxon to provide further insights into the origin of the group. Novel approaches to identify distinctive genetic lineages, including unsupervised machine learning variational autoencoder plots, were used to establish species hypothesis frameworks. In this sense, three undescribed species and a complex of cryptic species were identified, suggesting allopatric speciation connected to geographic or bathymetric isolation. We further observed that the shallow waters around the Scotia Arc and on the continental shelf in the Weddell Sea present high endemism and diversity. In contrast, likely due to the glacial pressure during the Cenozoic, a deep-sea group with fewer species emerged expanding over great areas in the South-Atlantic Antarctic Ridge. Our study agrees on how diachronic paleoclimatic and current environmental factors shaped Antarctic communities both at the shallow and deep-sea levels, promoting Antarctica as the center of origin for numerous taxa such as gastropod mollusks. |
format |
Text |
author |
Moles, Juan Derkarabetian, Shahan Schiaparelli, Stefano Schrödl, Michael Troncoso, Jesús S. Wilson, Nerida G. Giribet, Gonzalo |
author_facet |
Moles, Juan Derkarabetian, Shahan Schiaparelli, Stefano Schrödl, Michael Troncoso, Jesús S. Wilson, Nerida G. Giribet, Gonzalo |
author_sort |
Moles, Juan |
title |
An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
title_short |
An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
title_full |
An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
title_fullStr |
An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
title_full_unstemmed |
An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods |
title_sort |
approach using ddradseq and machine learning for understanding speciation in antarctic antarctophilinidae gastropods |
publisher |
Nature Publishing Group UK |
publishDate |
2021 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055997/ http://www.ncbi.nlm.nih.gov/pubmed/33875688 https://doi.org/10.1038/s41598-021-87244-5 |
geographic |
Antarctic Weddell Weddell Sea |
geographic_facet |
Antarctic Weddell Weddell Sea |
genre |
Antarc* Antarctic Antarctica Weddell Sea |
genre_facet |
Antarc* Antarctic Antarctica Weddell Sea |
op_source |
Sci Rep |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055997/ http://www.ncbi.nlm.nih.gov/pubmed/33875688 http://dx.doi.org/10.1038/s41598-021-87244-5 |
op_rights |
© The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
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CC-BY |
op_doi |
https://doi.org/10.1038/s41598-021-87244-5 |
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Scientific Reports |
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11 |
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1766041766935396352 |