A common resequencing-based genetic marker data set for global maize diversity

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.

Automated summary

Maize populations show vast diversity in both genetic and phenotypic traits. Resequencing strategies have been used to identify millions of genetic variants within and between maize populations, but inconsistencies in analytical pipelines, reference genome assemblies, and minor allele frequency filtering often limit the reuse and remixing of genetic diversity data for new research questions. This study utilized resequencing data from published and newly sequenced maize samples to create a unified marker set of over 366 million segregating variants, providing increased power to identify known flowering-time genes and track changes in allele frequency across the global distribution of maize.