Successful seedling establishment depends on the optimum depth of seed placement especially in drought-prone conditions, providing an opportunity to exploit subsoil water and increase winter survival in winter wheat. Coleoptile length is a key determinant for the appropriate depth at which seed can be sown. Thus, understanding the genetic basis of coleoptile length is necessary and important for wheat breeding. We conducted a genome-wide association study (GWAS) using a diverse panel of 298 winter wheat genotypes to dissect the genetic architecture of coleoptile length. We identified nine genomic regions associated with the coleoptile length on seven different chromosomes. Of the nine genomic regions, five have been previously reported in various studies, including one mapped to previously known Rht-B1 region. Three novel quantitative trait loci (QTLs), QCL.sdsu-2AS, QCL.sdsu-4BL, and QCL.sdsu-5BL were identified in our study. QCL.sdsu-5BL has a large substitution effect which is comparable to Rht-B1's effect and could be used to compensate for the negative effect of Rht-B1 on coleoptile length. In total, the nine QTLs explained 59% of the total phenotypic variation. Cultivars 'Agate' and 'MT06103' have the longest coleoptile length and interestingly, have favorable alleles at nine and eight coleoptile loci, respectively. These lines could be a valuable germplasm for longer coleoptile breeding. Gene annotations in the candidate regions revealed several putative proteins of specific interest including cytochrome P450-like, expansins, and phytochrome A. The QTLs for coleoptile length linked to single-nucleotide polymorphism (SNP) markers reported in this study could be employed in marker-assisted breeding for longer coleoptile in wheat. Thus, our study provides valuable insights into the genetic and molecular regulation of the coleoptile length in winter wheat.

Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models remains a challenge in the successful implementation of this approach. Multivariate models have shown promise when evaluated using diverse panels of unrelated accessions; however, limited information is available on their performance in advanced breeding trials. Here, we used multivariate GP models to predict multiple agronomic traits using 314 advanced and elite breeding lines of winter wheat evaluated in 10 site-year environments. We evaluated a multi-trait (MT) model with two cross-validation schemes representing different breeding scenarios (CV1, prediction of completely unphenotyped lines; and CV2, prediction of partially phenotyped lines for correlated traits). Moreover, extensive data from multi-environment trials (METs) were used to cross-validate a Bayesian multi-trait multi-environment (MTME) model that integrates the analysis of multiple-traits, such as G × E interaction. The MT-CV2 model outperformed all the other models for predicting grain yield with significant improvement in PA over the single-trait (ST-CV1) model. The MTME model performed better for all traits, with average improvement over the ST-CV1 reaching up to 19, 71, 17, 48, and 51% for grain yield, grain protein content, test weight, plant height, and days to heading, respectively. Overall, the empirical analyses elucidate the potential of both the MT-CV2 and MTME models when advanced breeding lines are used as a training population to predict related preliminary breeding lines. Further, we evaluated the practical application of the MTME model in the breeding program to reduce phenotyping cost using a sparse testing design. This showed that complementing METs with GP can substantially enhance resource efficiency. Our results demonstrate that multivariate GS models have a great potential in implementing GS in breeding programs.

Allopolyploidy greatly expands the range of possible regulatory interactions among functionally redundant homoeologous genes. However, connection between the emerging regulatory complexity and expression and phenotypic diversity in polyploid crops remains elusive. Here, we use diverse wheat accessions to map expression quantitative trait loci (eQTL) and evaluate their effects on the population-scale variation in homoeolog expression dosage. The relative contribution of cis- and trans-eQTL to homoeolog expression variation is strongly affected by both selection and demographic events. Though trans-acting effects play major role in expression regulation, the expression dosage of homoeologs is largely influenced by cis-acting variants, which appear to be subjected to selection. The frequency and expression of homoeologous gene alleles showing strong expression dosage bias are predictive of variation in yield-related traits, and have likely been impacted by breeding for increased productivity. Our study highlights the importance of genomic variants affecting homoeolog expression dosage in shaping agronomic phenotypes and points at their potential utility for improving yield in polyploid crops.

Breeding for salinity tolerance using Bangladeshi rice landraces and understand genetic diversity has been limited by the complex and polygenic nature of salt tolerance in rice genotypes. A genetic diversity and association mapping analysis was conducted using 96 germplasm accessions with variable response to salt stress at the seedling stage. These included 86 landraces and 10 indica varieties and lines including Nona Bokra, from southern Bangladesh. A total of 220 alleles were detected at 58 Simple Sequence Repeat (SSR) marker loci randomly distributed on all 12 rice chromosomes and 8 Sequence Tagged Site (STS) markers developed for genes SKC1, DST, and SalT. The average gene diversity was 0.5075 and polymorphism information content value was 0.4426, respectively. Cluster analysis revealed that 68 and 21 accessions were clustered into 2 distinct groups, possibly corresponding to indica and japonica groups, respectively and the remaining 7 landraces were classified as an admixed group. In addition to Wn11463, the STS marker for SKC1, RM22418 on Chr. 8 was significantly associated with salinity tolerance, at the location of a QTL detected in previous studies. Our findings of favorable alleles associated with salinity tolerance in Bangladeshi rice landraces, as well as the development of STS markers for salt tolerance genes, will be helpful in future efforts to breed salinity tolerance in rice.

Background: In the late 1920s, A. E. Watkins collected about 7000 landrace cultivars (LCs) of bread wheat (Triticum aestivum L.) from 32 different countries around the world. Among which 826 LCs remain viable and could be a valuable source of superior/favorable alleles to enhance disease resistance in wheat. In the present study, a core set of 121 LCs, which captures the majority of the genetic diversity of Watkins collection, was evaluated for identifying novel sources of resistance against tan spot, Stagonospora nodorum blotch (SNB), and Fusarium Head Blight (FHB). Results: A diverse response was observed in 121 LCs for all three diseases. The majority of LCs were moderately susceptible to susceptible to tan spot Ptr race 1 (84%) and FHB (96%) whereas a large number of LCs were resistant or moderately resistant against tan spot Ptr race 5 (95%) and SNB (54%). Thirteen LCs were identified in this study could be a valuable source for multiple resistance to tan spot Ptr races 1 and 5, and SNB, and another five LCs could be a potential source for FHB resistance. GWAS analysis was carried out using disease phenotyping score and 8807 SNPs data of 118 LCs, which identified 30 significant marker-trait associations (MTAs) with-log10 (p-value) > 3.0. Ten, five, and five genomic regions were found to be associated with resistance to tan spot Ptr race 1, race 5, and SNB, respectively in this study. In addition to Tsn1, several novel genomic regions Q.Ts1.sdsu-4BS and Q.Ts1.sdsu-5BS (tan spot Ptr race 1) and Q.Ts5.sdsu-1BL, Q.Ts5.sdsu-2DL, Q.Ts5.sdsu-3AL, and Q.Ts5.sdsu-6BL (tan spot Ptr race 5) were also identified. Our results indicate that these putative genomic regions contain several genes that play an important role in plant defense mechanisms. Conclusion: Our results suggest the existence of valuable resistant alleles against leaf spot diseases in Watkins LCs. The single-nucleotide polymorphism (SNP) markers linked to the quantitative trait loci (QTLs) for tan spot and SNB resistance along with LCs harboring multiple disease resistance could be useful for future wheat breeding.