Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.

When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power...
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Autor*in:	Drew J Duckett [verfasserIn] Kailee Calder [verfasserIn] Jack Sullivan [verfasserIn] David C Tank [verfasserIn] Bryan C Carstens [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 18(2023), 11, p e0291941
Übergeordnetes Werk:	volume:18 ; year:2023 ; number:11, p e0291941

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0291941

Katalog-ID:	DOAJ096063017

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allfields	10.1371/journal.pone.0291941 doi (DE-627)DOAJ096063017 (DE-599)DOAJ6eda98ce06ef4cc98566f7154a0b6f9b DE-627 ger DE-627 rakwb eng Drew J Duckett verfasserin aut Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses. 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample. Medicine R Science Q Kailee Calder verfasserin aut Jack Sullivan verfasserin aut David C Tank verfasserin aut Bryan C Carstens verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 18(2023), 11, p e0291941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:18 year:2023 number:11, p e0291941 https://doi.org/10.1371/journal.pone.0291941 kostenfrei https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b kostenfrei https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2023 11, p e0291941
spelling	10.1371/journal.pone.0291941 doi (DE-627)DOAJ096063017 (DE-599)DOAJ6eda98ce06ef4cc98566f7154a0b6f9b DE-627 ger DE-627 rakwb eng Drew J Duckett verfasserin aut Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses. 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample. Medicine R Science Q Kailee Calder verfasserin aut Jack Sullivan verfasserin aut David C Tank verfasserin aut Bryan C Carstens verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 18(2023), 11, p e0291941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:18 year:2023 number:11, p e0291941 https://doi.org/10.1371/journal.pone.0291941 kostenfrei https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b kostenfrei https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2023 11, p e0291941
allfields_unstemmed	10.1371/journal.pone.0291941 doi (DE-627)DOAJ096063017 (DE-599)DOAJ6eda98ce06ef4cc98566f7154a0b6f9b DE-627 ger DE-627 rakwb eng Drew J Duckett verfasserin aut Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses. 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample. Medicine R Science Q Kailee Calder verfasserin aut Jack Sullivan verfasserin aut David C Tank verfasserin aut Bryan C Carstens verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 18(2023), 11, p e0291941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:18 year:2023 number:11, p e0291941 https://doi.org/10.1371/journal.pone.0291941 kostenfrei https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b kostenfrei https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2023 11, p e0291941
allfieldsGer	10.1371/journal.pone.0291941 doi (DE-627)DOAJ096063017 (DE-599)DOAJ6eda98ce06ef4cc98566f7154a0b6f9b DE-627 ger DE-627 rakwb eng Drew J Duckett verfasserin aut Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses. 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample. Medicine R Science Q Kailee Calder verfasserin aut Jack Sullivan verfasserin aut David C Tank verfasserin aut Bryan C Carstens verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 18(2023), 11, p e0291941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:18 year:2023 number:11, p e0291941 https://doi.org/10.1371/journal.pone.0291941 kostenfrei https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b kostenfrei https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2023 11, p e0291941
allfieldsSound	10.1371/journal.pone.0291941 doi (DE-627)DOAJ096063017 (DE-599)DOAJ6eda98ce06ef4cc98566f7154a0b6f9b DE-627 ger DE-627 rakwb eng Drew J Duckett verfasserin aut Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses. 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample. Medicine R Science Q Kailee Calder verfasserin aut Jack Sullivan verfasserin aut David C Tank verfasserin aut Bryan C Carstens verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 18(2023), 11, p e0291941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:18 year:2023 number:11, p e0291941 https://doi.org/10.1371/journal.pone.0291941 kostenfrei https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b kostenfrei https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2023 11, p e0291941
language	English
source	In PLoS ONE 18(2023), 11, p e0291941 volume:18 year:2023 number:11, p e0291941
sourceStr	In PLoS ONE 18(2023), 11, p e0291941 volume:18 year:2023 number:11, p e0291941
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authorswithroles_txt_mv	Drew J Duckett @@aut@@ Kailee Calder @@aut@@ Jack Sullivan @@aut@@ David C Tank @@aut@@ Bryan C Carstens @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
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author	Drew J Duckett
spellingShingle	Drew J Duckett misc Medicine misc R misc Science misc Q Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.
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topic_title	Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses
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title	Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.
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title_full	Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses
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title_sort	reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses
title_auth	Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.
abstract	When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample.
abstractGer	When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample.
abstract_unstemmed	When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample.
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container_issue	11, p e0291941
title_short	Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.
url	https://doi.org/10.1371/journal.pone.0291941 https://doaj.org/article/6eda98ce06ef4cc98566f7154a0b6f9b https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291941&type=printable https://doaj.org/toc/1932-6203
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Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.

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