Genomics for Yield and Yield Components in Durum Wheat

Allelic Variations in Vernalization (Vrn) Genes in Triticum spp

Rapid climate changes, with higher warming rates during winter and spring seasons, dramatically affect the vernalization requirements, one of the most critical processes for the induction of wheat reproductive growth, with severe consequences on flowering time, grain filling, and grain yield. Specifically, the Vrn genes play a major role in the transition from vegetative to reproductive growth in wheat. Recent advances in wheat genomics have significantly improved the understanding of the molecular mechanisms of Vrn genes (Vrn-1, Vrn-2, Vrn-3, and Vrn-4), unveiling a diverse array of natural allelic variations. In this review, we have examined the current knowledge of Vrn genes from a functional and structural point of view, considering the studies conducted on Vrn alleles at different ploidy levels (diploid, tetraploid, and hexaploid). The molecular characterization of Vrn-1 alleles has been a focal point, revealing a diverse array of allelic forms with implications for flowering time. We have highlighted the structural complexity of the different allelic forms and the problems linked to the different nomenclature of some Vrn alleles. Addressing these issues will be crucial for harmonizing research efforts and enhancing our understanding of Vrn gene function and evolution. The increasing availability of genome and transcriptome sequences, along with the improvements in bioinformatics and computational biology, offers a versatile range of possibilities for enriching genomic regions surrounding the target sites of Vrn genes, paving the way for innovative approaches to manipulate flowering time and improve wheat productivity.

Simultaneous improvement of grain yield and grain protein concentration in durum wheat by using association tests and weighted GBLUP

KEY MESSAGE

Simultaneous improvement for GY and GPC by using GWAS and GBLUP suggested a significant application in durum wheat breeding. Despite the importance of grain protein concentration (GPC) in determining wheat quality, its negative correlation with grain yield (GY) is still one of the major challenges for breeders. Here, a durum wheat panel of 200 genotypes was evaluated for GY, GPC, and their derived indices (GPD and GYD), under eight different agronomic conditions. The plant material was genotyped with the Illumina 25 k iSelect array, and a genome-wide association study was performed. Two statistical models revealed dozens of marker-trait associations (MTAs), each explaining up to 30%. phenotypic variance. Two markers on chromosomes 2A and 6B were consistently identified by both models and were found to be significantly associated with GY and GPC. MTAs identified for phenological traits co-mapped to well-known genes (i.e., Ppd-1, Vrn-1). The significance values (p-values) that measure the strength of the association of each single nucleotide polymorphism marker with the target traits were used to perform genomic prediction by using a weighted genomic best linear unbiased prediction model. The trained models were ultimately used to predict the agronomic performances of an independent durum wheat panel, confirming the utility of genomic prediction, although environmental conditions and genetic backgrounds may still be a challenge to overcome. The results generated through our study confirmed the utility of GPD and GYD to mitigate the inverse GY and GPC relationship in wheat, provided novel markers for marker-assisted selection and opened new ways to develop cultivars through genomic prediction approaches.