In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification with next-generation sequencing. We applied genotyping-by-sequencing, a recently developed method to identify single-nucleotide polymorphisms, in the genomes of 384 wheat (Triticum aestivum) genotypes that were field tested under three different water regimes in Mediterranean climatic conditions: rain-fed only, mild water stress, and fully irrigated. We identified 102,324 single-nucleotide polymorphisms in these genotypes, and the phenotypic data were used to train and test genomic selection models intended to predict yield, thousand-kernel weight, number of kernels per spike, and heading date. Phenotypic data showed marked spatial variation. Therefore, different models were tested to correct the trends observed in the field. A mixed-model using moving-means as a covariate was found to best fit the data. When we applied the genomic selection models, the accuracy of predicted traits increased with spatial adjustment. Multiple genomic selection models were tested, and a Gaussian kernel model was determined to give the highest accuracy. The best predictions between environments were obtained when data from different years were used to train the model. Our results confirm that genotyping-by-sequencing is an effective tool to obtain genome-wide information for crops with complex genomes, that these data are efficient for predicting traits, and that correction of spatial variation is a crucial ingredient to increase prediction accuracy in genomic selection models.

Changing climates and associated increased variability pose risks to alfalfa (Medicago sativa L.) cultivation, with the requirement to establish, survive, and maintain production under water stress. Crop wild relatives (CWR) of alfalfa include populations that have evolved to survive in a number of different, extreme environments, but until recently have had limited use in breeding programs. Here we report on the phenotypic diversity of alfalfa crop wild relatives that were selected to represent extremes in drought tolerance (by sourcing germplasm from environments with extremes in low rainfall, high temperature, shallow soils, and winter freezing) with the aim of providing germplasm with drought tolerance and improved forage yield traits for breeding programs in both warm and cool dry temperate environments. Newly formed hybrids created between M. sativa, M. arborea L. (a woody shrub), and M. truncatula Gaertn. (an annual species from the Mediterranean region) were developed or acquired to introduce new genetic diversity from the tertiary genepool. Preliminary characterization and evaluation was used for taxonomic classification, and to identify wild accessions and pre‐bred (hybrid) lines that offer new diversity for growth habit, seed size, fall dormancy, and forage yield. The accessions and pre‐breeding lines described have been donated to the Australian Pastures Genebank for conservation and distribution.

White clover ( Trifolium repens L.) is the most important grazing perennial forage legume in temperate climates. However, its limited capacity to survive and restore growth after low temperatures during winter constrains the productivity and wide adoption of the crop. Despite the importance of cold tolerance for white clover cultivar development, the genetic basis of this trait remains largely unknown. Hence, in this study, we performed the first genome‐wide association study (GWAS) analyses in white clover to identify quantitative trait loci (QTL) for cold‐tolerance‐related traits. Seeds from 192 divergent genotypes from six populations in the Patagonia region of South America were collected and seed‐derived plants were further clonally propagated. Clonal trials were established in three locations representing temperature gradient associated with elevation. Given the allotetraploid nature of the white clover genome, distinct genetic models (diploid and tetraploid) were tested. Only the tetraploid parameterization was able to detect the 53 loci associated with cold‐tolerance traits. Out of the 53 single nucleotide polymorphism (SNP) trait associations, 17 controlled more than one trait or were stable across multiple sites. This work represents the first report of QTL for cold‐tolerance‐related traits, providing insights into its genetic basis and candidate genomic regions for further functional validation studies.