These are processed datasets of historical maize yield trials conducted in 1934-2014 in Illinois, Iowa, Kansas, and Nebraska with associated data on time exposed to different temperatures and total precipitation derived from public climate data sources. Coefficients and performance statistics for predictive models of historical maize yields based on these data are included. Additional processed climate data is provided for five models from the CMIP6 ensemble run under historical and three different climate forcing scenarios. Maize yields predicted using the historical models and simulated climate data are also provided.

These are processed datasets of historical maize yield trials conducted in 1934-2014 in Illinois, Iowa, Kansas, and Nebraska with associated data on time exposed to different temperatures and total precipitation derived from public climate data sources. Coefficients and performance statistics for predictive models of historical maize yields based on these data are included. Additional processed climate data is provided for five models from the CMIP6 ensemble run under historical and three different climate forcing scenarios. Maize yields predicted using the historical models and simulated climate data are also provided.

Data from hybrid maize yeild trails conducted by the University of Illinois at Urbana-Champaign, Iowa State University, Kansas State University, and the University of Nebraska-Lincoln between 1934 and 2014. This digitized data was orginally published in Agricultural Experiment Station and Cooperative Extension Service reports and bulletins distributed in paper and, in later years, as Excel files. The data set includes brand and hybrid names, trial location, and yield (bushels per acre) for all trials and years. Additional data on agronomic phenotypes, soil type, and average weather is included when reported in the orginal publications. Details about the orginal publications, data processing, etc. can be found in the included readme file. A GitHub repositiry containing the R code used to munge the data is also publically available and linked as a reference.

Data from hybrid maize yeild trails conducted by the University of Illinois at Urbana-Champaign, Iowa State University, Kansas State University, and the University of Nebraska-Lincoln between 1934 and 2014. This digitized data was orginally published in Agricultural Experiment Station and Cooperative Extension Service reports and bulletins distributed in paper and, in later years, as Excel files. The data set includes brand and hybrid names, trial location, and yield (bushels per acre) for all trials and years. Additional data on agronomic phenotypes, soil type, and average weather is included when reported in the orginal publications. Details about the orginal publications, data processing, etc. can be found in the included readme file. A GitHub repositiry containing the R code used to munge the data is also publically available and linked as a reference.

Imputed and phased single nucleotide polymorphisms (SNPs) for 5022 maize recombinant inbred lines from the nested association mapping (NAM) panel. SNPs were derived from maize HapMap1, HapMap2, and RNA-seq. SNPs are in VCF4.1 format. A CSV file contains genetic map information for the SNPs.

Imputed and phased single nucleotide polymorphisms (SNPs) for 5022 maize recombinant inbred lines from the nested association mapping (NAM) panel. SNPs were derived from maize HapMap1, HapMap2, and RNA-seq. SNPs are in VCF4.1 format. A CSV file contains genetic map information for the SNPs.

This study demonstrates GBS based SNP-typing in 11 early-backcross introgression populations of rice (at BC1F5), comprising a set of 564 diverse introgression lines and 12 parents. Sequencing using 10 Ion Proton runs generated a total of ~943.4 million raw reads, out of which ~881.6 million reads remained after trimming for low-quality bases. After alignment, 794,297 polymorphic SNPs were identified, and filtering resulted in LMD50 SNPs (low missing data, with each SNP, genotyped in at least 50% of the samples) for each sub-population. Every data point was supported by actual sequencing data without any imputation, eliminating imputation-induced errors in SNP-calling. Genotyping substantiated the impacts of novel breeding strategy revealing: (a) the donor introgression pattern in ILs were characteristic with variable introgression frequency in different genomic regions, attributed mainly to stringent selection under abiotic stress (b) considerably lower heterozygosity was observed in the ILs. Functional annotation revealed 426 non-synonymous deleterious SNPs present in 102 loci with a range of 1 to 4 SNPs per locus and 120 novel SNPs. SNP-typing this diversity panel will further assist in the development of markers supporting genomic applications in molecular breeding programs.Raw sequencing data is available at the NCBI SRA PRJNA479931.