Data from: Genetic dissection of grain iron and zinc, and thousand kernel weight in wheat (Triticum aestivum L.) using genome-wide association study

The study material in GWAS panel with 280 common bread wheat genotypes was
selected from All India Coordinated Research Project on Wheat and Barley
to map the genomic regions responsible for enhanced Grain Zinc Content
(GZnC), Grain Iron Content (GZnC) and Thousand Kernel weight (TKW).
Phenotypic data: The GWAS panel was evaluated at five different
environments: E1-University of Agricultural Sciences, research farm,
Dharwad (15°29'20.71"N, 74°59'3.35"E, 750m AMSL),
E2-ICAR- Indian Agricultural Research Institute, New Delhi (28°38′30.5″N,
77°09′58.2″E, 228 m AMSL), E3-Indian Agricultural Research Institute,
Jharkhand (24°16'58.4"N, 85°21'16.1"E, 651m AMSL),
E4-ICAR-Indian Institute of Wheat and Barley, Karnal
(29°41'8.2644''N,
76°59'25.9692''E,  250m AMSL), and
E5-Punjab Agricultural University, Ludhiana (30o54' N, 75o48'E,
247m AMSL). Around 20 g of grain sample from each genotype were used for
phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray
Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments
plc, Abingdon, United Kingdom) calibrated with glass beads-based values.
To record TKW, the Numigral grain counter was used to count the grain
number, the reading was set at 1000 grains and the weight of the grains
was recorded in grams with an electronic balance. The GFeC, GZnC were
expressed as milligram per kilogram (mg/kg), GPC in percentage (%), TKW in
grams (gms). Genotypic data: Genomic DNA of the GWAS panel was extracted
from the leaves of 21 days-old seedlings by Cetyl Trimethyl Ammonium
Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder’s
Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143
genome-wide SNPs. The monomorphic, markers with minor allele frequency
(MAF) of <5%, missing data of >20%, and heterozygote
frequency >25% were removed from the analysis. The remaining set of
14,790 high-quality SNPs was used in GWAS analysis. The detailed
information of the methods and software used, data analysis and GWAS is
available at DOI: 10.1038/s41598-022-15992-z.