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A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations

The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic...

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Autores principales: Adhikari, Laxman, Shrestha, Sandesh, Wu, Shuangye, Crain, Jared, Gao, Liangliang, Evers, Byron, Wilson, Duane, Ju, Yoonha, Koo, Dal-Hoe, Hucl, Pierre, Pozniak, Curtis, Walkowiak, Sean, Wang, Xiaoyun, Wu, Jing, Glaubitz, Jeffrey C., DeHaan, Lee, Friebe, Bernd, Poland, Jesse
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584886/
https://www.ncbi.nlm.nih.gov/pubmed/36266371
http://dx.doi.org/10.1038/s41598-022-19858-2
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author Adhikari, Laxman
Shrestha, Sandesh
Wu, Shuangye
Crain, Jared
Gao, Liangliang
Evers, Byron
Wilson, Duane
Ju, Yoonha
Koo, Dal-Hoe
Hucl, Pierre
Pozniak, Curtis
Walkowiak, Sean
Wang, Xiaoyun
Wu, Jing
Glaubitz, Jeffrey C.
DeHaan, Lee
Friebe, Bernd
Poland, Jesse
author_facet Adhikari, Laxman
Shrestha, Sandesh
Wu, Shuangye
Crain, Jared
Gao, Liangliang
Evers, Byron
Wilson, Duane
Ju, Yoonha
Koo, Dal-Hoe
Hucl, Pierre
Pozniak, Curtis
Walkowiak, Sean
Wang, Xiaoyun
Wu, Jing
Glaubitz, Jeffrey C.
DeHaan, Lee
Friebe, Bernd
Poland, Jesse
author_sort Adhikari, Laxman
collection PubMed
description The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines (Triticum aestivum, CDC Stanley x CDC Landmark), wheat-barley (T. aestivum x Hordeum vulgare) and wheat-wheatgrass (Triticum durum x Thinopyrum intermedium) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs.
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spelling pubmed-95848862022-10-22 A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations Adhikari, Laxman Shrestha, Sandesh Wu, Shuangye Crain, Jared Gao, Liangliang Evers, Byron Wilson, Duane Ju, Yoonha Koo, Dal-Hoe Hucl, Pierre Pozniak, Curtis Walkowiak, Sean Wang, Xiaoyun Wu, Jing Glaubitz, Jeffrey C. DeHaan, Lee Friebe, Bernd Poland, Jesse Sci Rep Article The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines (Triticum aestivum, CDC Stanley x CDC Landmark), wheat-barley (T. aestivum x Hordeum vulgare) and wheat-wheatgrass (Triticum durum x Thinopyrum intermedium) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs. Nature Publishing Group UK 2022-10-20 /pmc/articles/PMC9584886/ /pubmed/36266371 http://dx.doi.org/10.1038/s41598-022-19858-2 Text en © The Author(s) 2022, corrected publication 2023 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/) .
spellingShingle Article
Adhikari, Laxman
Shrestha, Sandesh
Wu, Shuangye
Crain, Jared
Gao, Liangliang
Evers, Byron
Wilson, Duane
Ju, Yoonha
Koo, Dal-Hoe
Hucl, Pierre
Pozniak, Curtis
Walkowiak, Sean
Wang, Xiaoyun
Wu, Jing
Glaubitz, Jeffrey C.
DeHaan, Lee
Friebe, Bernd
Poland, Jesse
A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title_full A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title_fullStr A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title_full_unstemmed A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title_short A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
title_sort high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584886/
https://www.ncbi.nlm.nih.gov/pubmed/36266371
http://dx.doi.org/10.1038/s41598-022-19858-2
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