An accurate assignment test for extremely low-coverage whole-genome sequence data
Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. Yet, assignment tests often rely on moderate- to high-coverage sequence data that can be difficult to obtain for fields such as molecular ecology and ancient DNA. We have de...
Published in: | Molecular Ecology Resources |
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Online Access: | https://hdl.handle.net/11250/2977423 https://doi.org/10.1111/1755-0998.13551 |
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2977423 2023-05-15T15:27:35+02:00 An accurate assignment test for extremely low-coverage whole-genome sequence data Ferrari, Giada Atmore, Lane Margaret Jentoft, Sissel Jakobsen, Kjetill Sigurd Makowiecki, Daniel Barrett, James Star, Bastiaan 2021 application/pdf https://hdl.handle.net/11250/2977423 https://doi.org/10.1111/1755-0998.13551 eng eng Wiley Norges forskningsråd: 221734 Norges forskningsråd: 262777 EU – Horisont Europa (EC/HEU): 813383 Molecular Ecology Resources. 2021, 1-15. urn:issn:1755-098X https://hdl.handle.net/11250/2977423 https://doi.org/10.1111/1755-0998.13551 cristin:1959570 Navngivelse-Ikkekommersiell 4.0 Internasjonal http://creativecommons.org/licenses/by-nc/4.0/deed.no CC-BY-NC 1-15 Molecular Ecology Resources Journal article Peer reviewed 2021 ftntnutrondheimi https://doi.org/10.1111/1755-0998.13551 2022-02-09T23:38:20Z Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. Yet, assignment tests often rely on moderate- to high-coverage sequence data that can be difficult to obtain for fields such as molecular ecology and ancient DNA. We have developed a novel approach that efficiently assigns biologically relevant information (i.e., population identity or structural variants such as inversions) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic single nucleotide polymorphisms (SNPs) associated with a biological characteristic. Low-coverage alignment files are subsequently compared to these databases to ascertain allelic state, yielding a joint probability for each association. To assess the efficacy of this approach, we assigned haplotypes and population identity in Heliconius butterflies, Atlantic herring, and Atlantic cod using chromosomal inversion sites and whole-genome data. We scored both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient Atlantic herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage data (as low as 0.0001x) based on genome-wide SNPs. This approach will therefore increase the number of samples in evolutionary, ecological and archaeological research for which relevant biological information can be obtained. publishedVersion Article in Journal/Newspaper atlantic cod NTNU Open Archive (Norwegian University of Science and Technology) Molecular Ecology Resources 22 4 1330 1344 |
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Open Polar |
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NTNU Open Archive (Norwegian University of Science and Technology) |
op_collection_id |
ftntnutrondheimi |
language |
English |
description |
Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. Yet, assignment tests often rely on moderate- to high-coverage sequence data that can be difficult to obtain for fields such as molecular ecology and ancient DNA. We have developed a novel approach that efficiently assigns biologically relevant information (i.e., population identity or structural variants such as inversions) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic single nucleotide polymorphisms (SNPs) associated with a biological characteristic. Low-coverage alignment files are subsequently compared to these databases to ascertain allelic state, yielding a joint probability for each association. To assess the efficacy of this approach, we assigned haplotypes and population identity in Heliconius butterflies, Atlantic herring, and Atlantic cod using chromosomal inversion sites and whole-genome data. We scored both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient Atlantic herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage data (as low as 0.0001x) based on genome-wide SNPs. This approach will therefore increase the number of samples in evolutionary, ecological and archaeological research for which relevant biological information can be obtained. publishedVersion |
format |
Article in Journal/Newspaper |
author |
Ferrari, Giada Atmore, Lane Margaret Jentoft, Sissel Jakobsen, Kjetill Sigurd Makowiecki, Daniel Barrett, James Star, Bastiaan |
spellingShingle |
Ferrari, Giada Atmore, Lane Margaret Jentoft, Sissel Jakobsen, Kjetill Sigurd Makowiecki, Daniel Barrett, James Star, Bastiaan An accurate assignment test for extremely low-coverage whole-genome sequence data |
author_facet |
Ferrari, Giada Atmore, Lane Margaret Jentoft, Sissel Jakobsen, Kjetill Sigurd Makowiecki, Daniel Barrett, James Star, Bastiaan |
author_sort |
Ferrari, Giada |
title |
An accurate assignment test for extremely low-coverage whole-genome sequence data |
title_short |
An accurate assignment test for extremely low-coverage whole-genome sequence data |
title_full |
An accurate assignment test for extremely low-coverage whole-genome sequence data |
title_fullStr |
An accurate assignment test for extremely low-coverage whole-genome sequence data |
title_full_unstemmed |
An accurate assignment test for extremely low-coverage whole-genome sequence data |
title_sort |
accurate assignment test for extremely low-coverage whole-genome sequence data |
publisher |
Wiley |
publishDate |
2021 |
url |
https://hdl.handle.net/11250/2977423 https://doi.org/10.1111/1755-0998.13551 |
genre |
atlantic cod |
genre_facet |
atlantic cod |
op_source |
1-15 Molecular Ecology Resources |
op_relation |
Norges forskningsråd: 221734 Norges forskningsråd: 262777 EU – Horisont Europa (EC/HEU): 813383 Molecular Ecology Resources. 2021, 1-15. urn:issn:1755-098X https://hdl.handle.net/11250/2977423 https://doi.org/10.1111/1755-0998.13551 cristin:1959570 |
op_rights |
Navngivelse-Ikkekommersiell 4.0 Internasjonal http://creativecommons.org/licenses/by-nc/4.0/deed.no |
op_rightsnorm |
CC-BY-NC |
op_doi |
https://doi.org/10.1111/1755-0998.13551 |
container_title |
Molecular Ecology Resources |
container_volume |
22 |
container_issue |
4 |
container_start_page |
1330 |
op_container_end_page |
1344 |
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1766358007738793984 |