Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations

Abstract Background Historically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contrib...

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Autores principales:	Anne-Katrin Emde, Amanda Phipps-Green, Murray Cadzow, C. Scott Gallagher, Tanya J. Major, Marilyn E. Merriman, Ruth K. Topless, Riku Takei, Nicola Dalbeth, Rinki Murphy, Lisa K. Stamp, Janak de Zoysa, Philip L. Wilcox, Keolu Fox, Kaja A. Wasik, Tony R. Merriman, Stephane E. Castel
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Biotechnology TP248.13-248.65 Genetics QH426-470
Acceso en línea:	https://doaj.org/article/295efebb8290477c8a164ca0f7d5bfec
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spelling	oai:doaj.org-article:295efebb8290477c8a164ca0f7d5bfec2021-11-08T10:57:36ZMid-pass whole genome sequencing enables biomedical genetic studies of diverse populations10.1186/s12864-021-07949-91471-2164https://doaj.org/article/295efebb8290477c8a164ca0f7d5bfec2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12864-021-07949-9https://doaj.org/toc/1471-2164Abstract Background Historically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contributed to deepening global health disparities. Whole genome sequencing (WGS) better captures genetic variation but remains prohibitively expensive. Thus, we explored WGS at “mid-pass” 1-7x coverage. Results Here, we developed and benchmarked methods for mid-pass sequencing. When applied to a population without an existing genomic reference panel, 4x mid-pass performed consistently well across ethnicities, with high recall (98%) and precision (97.5%). Conclusion Compared to array data imputed into 1000 Genomes, mid-pass performed better across all metrics and identified novel population-specific variants with potential disease relevance. We hope our work will reduce financial barriers for geneticists from underrepresented populations to characterize their genomes prior to biomedical genetic applications.Anne-Katrin EmdeAmanda Phipps-GreenMurray CadzowC. Scott GallagherTanya J. MajorMarilyn E. MerrimanRuth K. ToplessRiku TakeiNicola DalbethRinki MurphyLisa K. StampJanak de ZoysaPhilip L. WilcoxKeolu FoxKaja A. WasikTony R. MerrimanStephane E. CastelBMCarticleBiotechnologyTP248.13-248.65GeneticsQH426-470ENBMC Genomics, Vol 22, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biotechnology TP248.13-248.65 Genetics QH426-470
spellingShingle	Biotechnology TP248.13-248.65 Genetics QH426-470 Anne-Katrin Emde Amanda Phipps-Green Murray Cadzow C. Scott Gallagher Tanya J. Major Marilyn E. Merriman Ruth K. Topless Riku Takei Nicola Dalbeth Rinki Murphy Lisa K. Stamp Janak de Zoysa Philip L. Wilcox Keolu Fox Kaja A. Wasik Tony R. Merriman Stephane E. Castel Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
description	Abstract Background Historically, geneticists have relied on genotyping arrays and imputation to study human genetic variation. However, an underrepresentation of diverse populations has resulted in arrays that poorly capture global genetic variation, and a lack of reference panels. This has contributed to deepening global health disparities. Whole genome sequencing (WGS) better captures genetic variation but remains prohibitively expensive. Thus, we explored WGS at “mid-pass” 1-7x coverage. Results Here, we developed and benchmarked methods for mid-pass sequencing. When applied to a population without an existing genomic reference panel, 4x mid-pass performed consistently well across ethnicities, with high recall (98%) and precision (97.5%). Conclusion Compared to array data imputed into 1000 Genomes, mid-pass performed better across all metrics and identified novel population-specific variants with potential disease relevance. We hope our work will reduce financial barriers for geneticists from underrepresented populations to characterize their genomes prior to biomedical genetic applications.
format	article
author	Anne-Katrin Emde Amanda Phipps-Green Murray Cadzow C. Scott Gallagher Tanya J. Major Marilyn E. Merriman Ruth K. Topless Riku Takei Nicola Dalbeth Rinki Murphy Lisa K. Stamp Janak de Zoysa Philip L. Wilcox Keolu Fox Kaja A. Wasik Tony R. Merriman Stephane E. Castel
author_facet	Anne-Katrin Emde Amanda Phipps-Green Murray Cadzow C. Scott Gallagher Tanya J. Major Marilyn E. Merriman Ruth K. Topless Riku Takei Nicola Dalbeth Rinki Murphy Lisa K. Stamp Janak de Zoysa Philip L. Wilcox Keolu Fox Kaja A. Wasik Tony R. Merriman Stephane E. Castel
author_sort	Anne-Katrin Emde
title	Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
title_short	Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
title_full	Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
title_fullStr	Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
title_full_unstemmed	Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
title_sort	mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations
publisher	BMC
publishDate	2021
url	https://doaj.org/article/295efebb8290477c8a164ca0f7d5bfec
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Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations

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