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A common resequencing-based genetic marker data set for global maize diversity.
Grzybowski, Marcin W; Mural, Ravi V; Xu, Gen; Turkus, Jonathan; Yang, Jinliang; Schnable, James C.
Afiliação
  • Grzybowski MW; Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
  • Mural RV; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
  • Xu G; Department of Plant Molecular Ecophysiology, Institute of Plant Experimental Biology and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland.
  • Turkus J; Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
  • Yang J; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
  • Schnable JC; Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Plant J ; 113(6): 1109-1121, 2023 03.
Article em En | MEDLINE | ID: mdl-36705476
ABSTRACT
Maize (Zea mays ssp. mays) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole-genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high-confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering-time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Zea mays / Melhoramento Vegetal Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Zea mays / Melhoramento Vegetal Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article