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Rht18, derived from Triticum durum (tetraploid) wheat, is classified as a gibberellic acid (GA)-responsive dwarfing gene. Prior to this study, the responses of Rht18 to exogenous GA on agronomic traits in hexaploid wheat were still unknown. The response of Rht18 to exogenous GA 3 on coleoptile length, plant height, yield components and other agronomic traits were investigated using F 4:5 and F 5:6 hexaploid dwarf lines with Rht18 derived from two crosses between the tetraploid donor Icaro and tall Chinese winter wheat cultivars, Xifeng 20 and Jinmai 47. Applications of exogenous GA 3 significantly increased coleoptile length in both lines and their tall parents. Plant height was significantly increased by 21.3 and 10.7% in the GA 3 -treated dwarf lines of Xifeng 20 and Jinmai 47, respectively. Compared to the untreated dwarf lines, the partitioning of dry matter to ears at anthesis was significantly decreased while the partitioning of dry matter to stems was significantly increased in the GA 3 -treated dwarf lines. There were no obvious changes in plant height and dry matter partitioning in the GA 3 -treated tall parents. Exogenous GA 3 significantly decreased grain number spike -1 while it increased 1000-kernel weight in both the dwarf lines and tall parents. Thus, applications of exogenous GA 3 restored plant height and other agronomic traits of Rht18 dwarf lines to the levels of the tall parents. This study indicated that Rht18 dwarf mutants are GA-deficient lines with impaired GA biosynthesis.

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Notwithstanding the rapid development of high‐throughput genotyping platforms in recent years, several plant research programs find themselves in a dilemma of which marker system to use while conducting genome‐wide association studies (GWAS) and genomic selection. To gain insight into this, we genotyped an elite spring wheat (Triticum aestivum L.) association mapping initiative (WAMI, 287 lines) panel with various array‐based platforms—(i) Diversity Arrays Technology (DArT), (ii) Illumina Infinium BeadChip wheat 9K iSelect (I9K), and (iii) wheat 90K iSelect (I90K)—and sequencing‐based platform DArTseq. The raw markers refined using a common set of protocols after the bioinformatics analysis were compared by performing a series of genetic analyses: estimates of genetic diversity through nucleotide diversity (π), population structure and familial relatedness, marker‐trait associations (MTAs), and genomic prediction. Results indicated that genetic data from DArTseq consisted of a high proportion of rare allele markers (1% < minor allele frequency < 5%). The nucleotide diversity statistic (π) was higher for the array‐based single nucleotide polymorphisms (SNPs) than sequencing‐based SNPs. The I9K detected population structure caused by the variety ‘Kauz’ and grouped the population into two subgroups, whereas I90K, DArT, and DArTseq detected five subgroups driven by key pedigrees. The I90K with the highest marker density identified a high number of significant MTAs. Genomic prediction accuracy varied among traits; DArTseq and I90K produced similar prediction accuracies. Among the marker platforms compared, I90K was the best genotyping platform for GWAS, and DArTseq—given the low cost per SNP—was the best platform for genomic prediction in spring wheat.

Seri/Babax spring wheat linkage mapping population was developed to minimize the confounding effect of phenology in the genetic dissection of abiotic stress traits. An existing linkage map (< 500 markers) was updated with 6,470 polymorphic Illumina iSelect 90K array and DArTseq SNPs to a genetic map of 5576.5 cM with 1748 non-redundant markers (1165 90K SNPs, 207 DArTseq SNPs, 183 AFLP, 111 DArT array, and 82 SSR) assigned to 31 linkage groups. We conducted QTL mapping for yield and related traits phenotyped in seven major wheat growing areas from Egypt, Sudan, Iran and India, and nine environments (heat, drought, heat plus drought, and yield potential) in Obregon, Mexico. The current study confirmed QTLs from previous studies and identified novel QTLs. QTL analysis identified