Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus
Summary: The novel machine learning technique Random Forest (RF) was used to test if the genetic differentiation of populations of marine species may be related to any of the key environmental variables known to shape species distributions. The study was performed in North and Baltic Sea characteriz...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-01-01
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| Series: | Oceanologia |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0078323418300927 |
| _version_ | 1828395596475531264 |
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| author | Tomasz Kijewski Malgorzata Zbawicka Jakob Strand Hans Kautsky Jonne Kotta Merli Rätsep Roman Wenne |
| author_facet | Tomasz Kijewski Malgorzata Zbawicka Jakob Strand Hans Kautsky Jonne Kotta Merli Rätsep Roman Wenne |
| author_sort | Tomasz Kijewski |
| collection | DOAJ |
| description | Summary: The novel machine learning technique Random Forest (RF) was used to test if the genetic differentiation of populations of marine species may be related to any of the key environmental variables known to shape species distributions. The study was performed in North and Baltic Sea characterized by strong gradients of environmental factors and almost continuous distributions of Mytilus mussel populations. Assessment of the species identity was performed using four nuclear DNA markers, and previously published single nucleotide polymorphism (SNP) data. A general pattern of cline variation was observed with increasing Mytilus trossulus share towards the eastern Baltic Sea. Average allele share rose to 61% in Höga Kusten, Gulf of Bothnia. All Baltic Sea samples revealed a strong introgression of Mytilus edulis and a limited introgression of M. trossulus through the Danish Straits.The studied environmental variables described 67 and 68% of the variability in the allele frequencies of M. edulis and M. trossulus. Salinity defined over 50% of the variability in the gene frequencies of the studied Mytilus spp. populations. Changes along this environmental gradient were not gradual but instead a significant shift from gene dominance was found at a salinity of 12 PSU. Water temperature and the trophic status of the sea area had only moderate association with the gene frequencies. The obtained results showed that the novel machine learning technique can be successfully used for finding correlations between genetic differentiation of populations and environmental variables and for defining the functional form of these linkages. Keywords: Marine environment, Spatial distribution, Seascape genetics, Nuclear DNA markers EFbis, Glu-5′, ITS, M7 and Single Nucleotide Polymorphism, Baltic Sea |
| first_indexed | 2024-12-10T08:15:53Z |
| format | Article |
| id | doaj.art-32a760553f6c4f61b9cfb6c5aeae202d |
| institution | Directory Open Access Journal |
| issn | 0078-3234 |
| language | English |
| last_indexed | 2024-12-10T08:15:53Z |
| publishDate | 2019-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Oceanologia |
| spelling | doaj.art-32a760553f6c4f61b9cfb6c5aeae202d2022-12-22T01:56:28ZengElsevierOceanologia0078-32342019-01-01611131142Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels MytilusTomasz Kijewski0Malgorzata Zbawicka1Jakob Strand2Hans Kautsky3Jonne Kotta4Merli Rätsep5Roman Wenne6Institute of Oceanology, Polish Academy of Sciences, Sopot, PolandInstitute of Oceanology, Polish Academy of Sciences, Sopot, PolandArctic Research Centre, Department of Bioscience, Aarhus University, Aarhus, DenmarkDepartment of Ecology, Environment and Plant Sciences, Stockholm University, SwedenEstonian Marine Institute, University of Tartu, Tallinn, EstoniaEstonian Marine Institute, University of Tartu, Tallinn, EstoniaInstitute of Oceanology, Polish Academy of Sciences, Sopot, Poland; Corresponding author at: Institute of Oceanology, Polish Academy of Sciences, Powstańców Warszawy 55, 81-712 Sopot, Poland. Tel.: +48 58 7311763; fax: +48 58 5512130.Summary: The novel machine learning technique Random Forest (RF) was used to test if the genetic differentiation of populations of marine species may be related to any of the key environmental variables known to shape species distributions. The study was performed in North and Baltic Sea characterized by strong gradients of environmental factors and almost continuous distributions of Mytilus mussel populations. Assessment of the species identity was performed using four nuclear DNA markers, and previously published single nucleotide polymorphism (SNP) data. A general pattern of cline variation was observed with increasing Mytilus trossulus share towards the eastern Baltic Sea. Average allele share rose to 61% in Höga Kusten, Gulf of Bothnia. All Baltic Sea samples revealed a strong introgression of Mytilus edulis and a limited introgression of M. trossulus through the Danish Straits.The studied environmental variables described 67 and 68% of the variability in the allele frequencies of M. edulis and M. trossulus. Salinity defined over 50% of the variability in the gene frequencies of the studied Mytilus spp. populations. Changes along this environmental gradient were not gradual but instead a significant shift from gene dominance was found at a salinity of 12 PSU. Water temperature and the trophic status of the sea area had only moderate association with the gene frequencies. The obtained results showed that the novel machine learning technique can be successfully used for finding correlations between genetic differentiation of populations and environmental variables and for defining the functional form of these linkages. Keywords: Marine environment, Spatial distribution, Seascape genetics, Nuclear DNA markers EFbis, Glu-5′, ITS, M7 and Single Nucleotide Polymorphism, Baltic Seahttp://www.sciencedirect.com/science/article/pii/S0078323418300927 |
| spellingShingle | Tomasz Kijewski Malgorzata Zbawicka Jakob Strand Hans Kautsky Jonne Kotta Merli Rätsep Roman Wenne Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus Oceanologia |
| title | Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus |
| title_full | Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus |
| title_fullStr | Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus |
| title_full_unstemmed | Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus |
| title_short | Random forest assessment of correlation between environmental factors and genetic differentiation of populations: Case of marine mussels Mytilus |
| title_sort | random forest assessment of correlation between environmental factors and genetic differentiation of populations case of marine mussels mytilus |
| url | http://www.sciencedirect.com/science/article/pii/S0078323418300927 |
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