Data from: Phased Genotyping-by-Sequencing Enhances Analysis of Genetic Diversity and Reveals Divergent Copy Number Variants in Maize

Metadata Updated: November 10, 2020

High-throughput sequencing (HTS) of reduced representation genomic libraries has ushered in an era of genotyping-by-sequencing (GBS), where genome-wide genotype data can be obtained for nearly any species. However, there remains a need for imputation-free GBS methods for genotyping large samples taken from heterogeneous populations of heterozygous individuals. This requires that a number of issues encountered with GBS be considered, including the sequencing of nonoverlapping sets of loci across multiple GBS libraries, a common missing data problem that results in low call rates for markers per individual, and a tendency for applicability only in inbred line samples with sufficient linkage disequilibrium for accurate imputation. We addressed these issues while developing and validating a new, comprehensive platform for GBS. This study supports the notion that GBS can be tailored to particular aims, and using Zea mays our results indicate that large samples of unknown pedigree can be genotyped to obtain complete and accurate GBS data. Optimizing size selection to sequence a high proportion of shared loci among individuals in different libraries and using simple in silico filters, a GBS procedure was established that produces high call rates per marker (>85%) with accuracy exceeding 99.4%. Furthermore, by capitalizing on the sequence-read structure of GBS data (stacks of reads), a new tool for resolving local haplotypes and scoring phased genotypes was developed, a feature that is not available in many GBS pipelines. Using local haplotypes reduces the marker dimensionality of the genotype matrix while increasing the informativeness of the data. Phased GBS in maize also revealed the existence of reproducibly inaccurate (apparent accuracy) genotypes that were due to divergent copy number variants (CNVs) unobservable in the underlying single nucleotide polymorphism (SNP) data.

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Public: This dataset is intended for public access and use. License: Creative Commons CCZero

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Dates

Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 10, 2020
Metadata Updated Date November 10, 2020
Publisher Agricultural Research Service
Unique Identifier Unknown
Maintainer
Identifier cb1abf9f-7f76-45ee-8f1a-4cc5cc32922a
Data Last Modified 2019-08-05
Public Access Level public
Bureau Code 005:18
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
License https://creativecommons.org/publicdomain/zero/1.0/
Program Code 005:040
Source Datajson Identifier True
Source Hash 1c253e88504cb8e59eacb43a42bad20aa76ba69d
Source Schema Version 1.1

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