Mapping of agronomic traits, disease resistance and malting quality in a wide cross of two-row barley cultivars

Genome-wide screening of meta-QTL and candidate genes controlling yield and yield-related traits in barley (Hordeum vulgare L.)

Increasing yield is an important goal of barley breeding. In this study, 54 papers published from 2001-2022 on QTL mapping for yield and yield-related traits in barley were collected, which contained 1080 QTLs mapped to the barley high-density consensus map for QTL meta-analysis. These initial QTLs were integrated into 85 meta-QTLs (MQTL) with a mean confidence interval (CI) of 2.76 cM, which was 7.86-fold narrower than the CI of the initial QTL. Among these 85 MQTLs, 68 MQTLs were validated in GWAS studies, and 25 breeder's MQTLs were screened from them. Seventeen barley orthologs of yield-related genes in rice and maize were identified within the hcMQTL region based on comparative genomics strategy and were presumed to be reliable candidates for controlling yield-related traits. The results of this study provide useful information for molecular marker-assisted breeding and candidate gene mining of yield-related traits in barley.

The genotype of barley cultivars influences multiple aspects of their associated microbiota via differential root exudate secretion

Plant-associated microbes play vital roles in promoting plant growth and health, with plants secreting root exudates into the rhizosphere to attract beneficial microbes. Exudate composition defines the nature of microbial recruitment, with different plant species attracting distinct microbiota to enable optimal adaptation to the soil environment. To more closely examine the relationship between plant genotype and microbial recruitment, we analysed the rhizosphere microbiomes of landrace (Chevallier) and modern (NFC Tipple) barley (Hordeum vulgare) cultivars. Distinct differences were observed between the plant-associated microbiomes of the 2 cultivars, with the plant-growth promoting rhizobacterial genus Pseudomonas substantially more abundant in the Tipple rhizosphere. Striking differences were also observed between the phenotypes of recruited Pseudomonas populations, alongside distinct genotypic clustering by cultivar. Cultivar-driven Pseudomonas selection was driven by root exudate composition, with the greater abundance of hexose sugars secreted from Tipple roots attracting microbes better adapted to growth on these metabolites and vice versa. Cultivar-driven selection also operates at the molecular level, with both gene expression and the abundance of ecologically relevant loci differing between Tipple and Chevallier Pseudomonas isolates. Finally, cultivar-driven selection is important for plant health, with both cultivars showing a distinct preference for microbes selected by their genetic siblings in rhizosphere transplantation assays.

Bringing Barley Back: Analysis of Heritage Varieties for Use as Germplasm Sources to Improve Resistance against the Most Devastating, Contemporary Disease in Canada, Fusarium Head Blight (Fusarium graminearum)

Fusarium head blight (FHB), caused by Fusarium graminearum, is currently the most devastating disease for barley (Hordeum vulgare) in Canada. Associated mycotoxins can compromise grain quality, where deoxynivalenol (DON) is considered particularly damaging due to its frequency of detection. Breeding barley with a lower DON content is difficult, due to the poor adaptation and malt quality of resistance sources. A set of European-derived heritage varieties were screened in an FHB nursery in Charlottetown, PE, with selections tested at Brandon, MB, between 2018-2022. Genetic evaluation demonstrated a distinct clustering of Canadian varieties from the heritage set. At Brandon, 72% of the heritage varieties ranked lower for DON content than did the moderately resistant Canadian check 'AAC Goldman', but resistance was associated with later heading and taller stature. In contrast with Canadian modern malting variety 'AAC Synergy', general deficiencies were observed in yield, enzyme activity, and extract, along with higher protein content. Nonetheless, several resistant varieties were identified with reasonable a heading date and yield, including 'Chevallier Chile', 'Domen', 'Djugay', 'Hannchen', 'Heils Franken', 'Moravian Barley', 'Loosdorfer' with 'Golden Melon', 'Nutans Moskva', and 'Vellavia', these being some of the most promising varieties when malting quality characteristics were also considered. These heritage resources could be used as parents in breeding to develop FHB-resistant malting barley varieties.

Genotyping by Sequencing Advancements in Barley

Barley is considered an ideal crop to study cereal genetics due to its close relationship with wheat and diploid ancestral genome. It plays a crucial role in reducing risks to global food security posed by climate change. Genetic variations in the traits of interest in crops are vital for their improvement. DNA markers have been widely used to estimate these variations in populations. With the advancements in next-generation sequencing, breeders could access different types of genetic variations within different lines, with single-nucleotide polymorphisms (SNPs) being the most common type. However, genotyping barley with whole genome sequencing (WGS) is challenged by the higher cost and computational demand caused by the large genome size (5.5GB) and a high proportion of repetitive sequences (80%). Genotyping-by-sequencing (GBS) protocols based on restriction enzymes and target enrichment allow a cost-effective SNP discovery by reducing the genome complexity. In general, GBS has opened up new horizons for plant breeding and genetics. Though considered a reliable alternative to WGS, GBS also presents various computational difficulties, but GBS-specific pipelines are designed to overcome these challenges. Moreover, a robust design for GBS can facilitate the imputation to the WGS level of crops with high linkage disequilibrium. The complete exploitation of GBS advancements will pave the way to a better understanding of crop genetics and offer opportunities for the successful improvement of barley and its close relatives.

Importance of Landraces in Cereal Breeding for Stress Tolerance

The renewed focus on cereal landraces is a response to some negative consequences of modern agriculture and conventional breeding which led to a reduction of genetic diversity. Cereal landraces are still cultivated on marginal lands due to their adaptability to unfavourable conditions, constituting an important source of genetic diversity usable in modern plant breeding to improve the adaptation to abiotic or biotic stresses, yield performance and quality traits in limiting environments. Traditional agricultural production systems have played an important role in the evolution and conservation of wide variability in gene pools within species. Today, on-farm and ex situ conservation in gene bank collections, together with data sharing among researchers and breeders, will greatly benefit cereal improvement. Many efforts are usually made to collect, organize and phenotypically and genotypically analyse cereal landrace collections, which also utilize genomic approaches. Their use in breeding programs based on genomic selection, and the discovery of beneficial untapped QTL/genes/alleles which could be introgressed into modern varieties by MAS, pyramiding or biotechnological tools, increase the potential for their better deployment and exploitation in breeding for a more sustainable agricultural production, particularly enhancing adaptation and productivity in stress-prone environments to cope with current climate changes.

[NGS sequencing in barley breeding and genetic studies]

Barley (Hordeum vulgare L.) is the one of the most important cereal species used as food and feed crops, as well as for malting and alcohol production. At the end of the last century, traditional breeding techniques were complemented by the use of DNA markers. Molecular markers have also been used extensively for molecular genetic mapping and QTL analysis. In 2012, the barley genome sequencing was completed, which provided a broad range of new opportunities - from a more efficient search for candidate genes controlling economically important traits to genomic selection. The review summarizes the results of the studies performed after barley genome sequencing, which discovered new areas of barley genetics and breeding with high throughput screening and genotyping methods. During this period, intensive studies aimed at identification of barley genomic loci associated with economically important traits have been carried out; online databases and tools for working with barley genomic data and their deposition have appeared and are being replenished. In recent years, GWAS analysis has been used for large-scale phenotypegenotype association studies, which has been widely used in barley since 2010 due to the developed SNP-arrays, as well as genotyping methods based on direct NGS sequencing of selected fractions of the genome. To date, more than 80 papers have been published that describe the results of the GWAS analysis in barley. SNP identification associated with economically important traits and their transformation into CAPS or KASP markers convenient for screening selection material significantly expands the possibilities of marker-assisted selection of barley. In addition, the currently available information on potential target genes and the quality of the whole barley genome sequence provides a good base for applying genome editing technologies to create material for the creation of varieties with desired properties.

Comparison of three boosting methods in parent-offspring trios for genotype imputation using simulation study

Background

Genotype imputation is an important process of predicting unknown genotypes, which uses reference population with dense genotypes to predict missing genotypes for both human and animal genetic variations at a low cost. Machine learning methods specially boosting methods have been used in genetic studies to explore the underlying genetic profile of disease and build models capable of predicting missing values of a marker.

Methods

In this study strategies and factors affecting the imputation accuracy of parent-offspring trios compared from lower-density SNP panels (5 K) to high density (10 K) SNP panel using three different Boosting methods namely TotalBoost (TB), LogitBoost (LB) and AdaBoost (AB). The methods employed using simulated data to impute the un-typed SNPs in parent-offspring trios. Four different datasets of G1 (100 trios with 5 k SNPs), G2 (100 trios with 10 k SNPs), G3 (500 trios with 5 k SNPs), and G4 (500 trio with 10 k SNPs) were simulated. In four datasets all parents were genotyped completely, and offspring genotyped with a lower density panel.

Results

Comparison of the three methods for imputation showed that the LB outperformed AB and TB for imputation accuracy. The time of computation were different between methods. The AB was the fastest algorithm. The higher SNP densities resulted the increase of the accuracy of imputation. Larger trios (i.e. 500) was better for performance of LB and TB.

Conclusions

The conclusion is that the three methods do well in terms of imputation accuracy also the dense chip is recommended for imputation of parent-offspring trios.