DOI: 10.5061/dryad.rn8pk0pkv
title: SNP data set of Peruvian highland maize races

description: Peruvian maize exhibits significant morphological diversity, with
 landraces cultivated from sea level up to 3,500 meters above sea level.
 Previous research based on morphological descriptors identified at least
 52 Peruvian maize races, but their genetic diversity and population
 structure remain largely unknown. In this study, we used
 genotyping-by-sequencing (GBS) to infer the genetic structure and
 diversity of 423 maize accessions from the Genebank of La Molina National
 Agrarian University (UNALM). These accessions represent nine races and one
 sub-race, along with 15 open-pollinated lines (purple corn) and two yellow
 maize hybrids. We obtained 14,235 high-quality SNPs distributed along the
 10 maize chromosomes. Gene diversity ranged from 0.33 (Pachia) to 0.362
 (Ancashino), with Cusco showing the lowest inbreeding coefficient (0.205)
 and Ancashino the highest (0.274) among the landraces. Population
 divergence (FST) was very low (mean = 0.017), indicating extensive
 interbreeding among Peruvian maize varieties. Population structure
 analysis revealed that these 423 distinct genotypes could be grouped into
 10 clusters, with some maize races clustering together. Peruvian maize
 races did not form monophyletic groups; instead, our phylogenetic tree
 identified two clades corresponding to the chronological classification of
 Peruvian maize races: Anciently Derived or Primary Races (ADPR)
 and Lately Derived or Secondary Races (LDSR). These clades also align with
 the geographic origins of the maize races, reflecting their mixed
 evolutionary backgrounds. Further investigation of Peruvian maize
 germplasm using modern technologies is essential to enhance their use in
 breeding programs, particularly in the Andean region of Peru.
description: # SNP data set of Peruvian highland maize races We examined (i) 406
 accessions of nine races and one sub-race of Peruvian maize that are
 currently cultivated in 10 Andean geographic departments of Peru, (ii) 15
 open-pollinated (OP) purple maize lines and (iii) two yellow maize hybrids
 (423 individuals in total). Genotyping by sequencing libraries was created
 following Elshire et al. (2011) protocol. Genomic DNA was digested with
 the *ApeKI* enzyme and fragments were ligated to Illumina sequencing
 adapters and also with sequence barcodes that are unique to each sample,
 which allows the recovery of sample identity for each sequenced DNA
 fragment after multiplexing. The pooled samples were sequenced on the
 Illumina NovaSeq 600 platform from which 100 bp single-end sequences reads
 were obtained. Quality of the raw data was examined with FastQC v0.11.7
 software (Andrews, 2010), then we employed the TASSEL v5.2.42
 bioinformatic pipeline (Bradbury et al., 2007; Glaubitz et al., 2014) for
 SNPs calling with maize Zm-B73-REFERENCE-NAM-5.0 (Hufford et al., 2021) as
 the reference genome. Parameters employed in this pipeline were the same
 as in the study of Huaringa et al (2023). Data curation was performed
 using software VCFtools v0.1.16 (Danecek et al., 2011) with the following
 criteria of retention: (i) minimum minor allele frequency of 0.1, (ii)
 number of alleles less than or equal to two, and (iv) maximum missing data
 of 0.1. Additional filtering was conducted by removing SNPs in linkage
 disequilibrium (LD) at a threshold of r2 = 0.2 with function
 *snpgdsLDpruning* of SNPRelate package (Zheng et al., 2012) in R v4.2.233
 program. Finally, TASSEL software was employed to convert the .vcf file to
 PHYLIP format with argument *-exportType* Phylip_Inter. Elshire, R. J. *et
 al.* A robust, simple genotyping-by-sequencing (GBS) approach for high
 diversity species. *PLoS One* **6**, (2011). Andrews, S. FastQC: A Quality
 Control Tool for High Throughput Sequence Data.
 [http://www.bioinformatics.babraham.ac.uk/projects/fastqc/](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) (2010). Bradbury, P. J. *et al.* TASSEL: Software for association mapping of complex traits in diverse samples. *Bioinformatics* **23**, 2633–2635 (2007). Glaubitz, J. C. *et al.* TASSEL-GBS: A high capacity genotyping by sequencing analysis pipeline. *PLoS One* **9**, (2014). Hufford, M. B. *et al.* De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. *Science* **373**, 655–662 (2021). Huaringa-Joaquin, A. *et al.* Assessment of the genetic diversity and population structure of the Peruvian Andean legume, Tarwi (*Lupinus mutabilis*), with high quality SNPs. *Diversity* **15**, (2023). Danecek, P. *et al.* The variant call format and VCFtools. *Bioinformatics* **27**, 2156–2158 (2011). Zheng, X. *et al.* A high-performance computing toolset for relatedness and principal component analysis of SNP data. *Bioinformatics* **28**, 3326–3328 (2012). R Core Team. R: A language and environment for statistical computing. [https://www.R-project.org/](https://www.R-project.org/) (2022).