Cadmium (Cd) contamination in wheat farmland is increasing at an alarming rate, posing threats to food security and public health.  Breeding and utilizing wheat varieties characterized by low Cd accumulation levels constitute an effective strategy in the battle against wheat Cd contamination.  The adoption of molecular marker-assisted approaches can greatly expedite the selection and enhancement of wheat varieties with low Cd accumulation.  Nonetheless, research concerning the genes associated with wheat cadmium accumulation remains scarce.  In this study, a high-density 660K SNP array was employed for conducting a genome-wide association study (GWAS) on the grain Cd concentration (GCdC), bioconcentration factor (BCF) and translocation factor (TF) in 175 wheat germplasms.  The findings revealed 401 significant SNPs identified across three diverse environments.  Linkage disequilibrium analysis revealed 30 core quantitative trait loci (QTLs) capable of reliably modulating wheat Cd accumulation phenotypes.  Through gene annotation, transcriptomics, and gene molecular features, four candidate genes (TraesCS7B02G000200, TraesCS4A02G035900, TraesCS4A02G040900, and TraesCS5D02G564000) were identified as potential constituents in the biological process of wheat Cd accumulation.  Furthermore, six wheat germplasms exhibiting low grain Cd accumulation were isolated, and two kompetitive allele specific PCR (KASP) markers conducive to breeding selection were developed.  These findings provide valuable genetic resources for cultivating wheat with low Cd accumulation and establish a foundation for understanding the molecular mechanisms underlying low Cd accumulation in wheat.  The candidate genes and KASP markers elucidated in this research have potential for effective use in genetic enhancement and marker-assisted selection in the breeding of wheat with low Cd accumulation.

Protein content (PC) in maize kernels is a key determinant of their nutritional quality, however, its genetic basis remains largely unexplored.  In this study, we conducted a genome-wide association study (GWAS) using 264 maize inbred lines and 1.25 million single nucleotide polymorphisms (SNPs), applying six GWAS models: BLINK, FarmCPU, MLM, MLMM, SUPER, and 3VmrMLM. Kernel PC exhibited substantial variation, ranging from 9.26 to 20.94%, with a broad-sense heritability of 0.56.  A total of 473 significant quantitative trait nucleotides (QTNs) were detected, each explaining 0.08 to 7.10% of the phenotypic variance.  Among them, 115 QTNs were consistently detected across different models, environments and analytical methods.  Notably, 3VmrMLM model identified 59 most significant QTNs, with 38 were QEIs, and the MLM model identified the fewest significant QTNs (8).  We further identified 35 candidate genes located within or adjacent to the significant QTNs.  Among these, four genes - Zm00001d033805, Zm00001d037565, Zm00001d052164 and Zm00001d031535 - were strongly associated with PC.  These genes are implicated in critical biological pathways, including nitrogen metabolism, photosynthesis, and the tricarboxylic acid (TCA) cycle.  Notably, Zm00001d037565, encoding a gibberellin 2-oxidase, plays a role in seed development and is likely involved in regulating protein accumulation in kernels.  Haplotype analysis revealed that the HapA of Zm00001d037565 is significantly associated with higher PC.  Selective sweep analysis indicated that this gene underwent selection during maize domestication from teosinte (Zea mays ssp. mexicana and Zea mays ssp. parviglumis), its adaptation from tropical/subtropical to temperate regions, and throughout modern breeding programs.  Overall, this study advances our understanding of the genetic architecture of maize kernel PC and provides valuable candidate genes and haplotypes for marker-assisted selection, offering new targets for developing high-protein maize varieties.