Association and genome analyses to propose putative candidate genes for malt quality traits

Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis

Improving barley grain quality is a major goal in barley breeding. In this study, a total of 35 papers focusing on quantitative trait loci (QTLs) mapping for barley quality traits published since 2000 were collected. Among the 454 QTLs identified in these studies, 349 of them were mapped onto high-density consensus maps, which were used for QTL meta-analysis. Through QTL meta-analysis, the initial QTLs were integrated into 41 meta-QTLs (MQTLs) with an average confidence interval (CI) of 1. 66 cM, which is 88.9% narrower than that of the initial QTLs. Among the 41 identified MQTLs, 25 were subsequently validated in publications using genome-wide association study (GWAS). From these 25 validated MQTLs, ten breeder's MQTLs were selected. Synteny analysis comparing barley and wheat MQTLs revealed orthologous relationships between eight breeder's MQTLs and 45 wheat MQTLs. Additionally, 17 barley homologs associated with rice quality traits were identified within the regions of the breeder's MQTLs through comparative analysis. The findings of this study provide valuable insights for molecular marker-assisted breeding and the identification of candidate genes related to quality traits in barley.

Identification of the Key Transcription Factors Regulating the Expression of the Genes Associated with Barley Malt Quality during Malting

Barley malt is produced through a malting process; it begins with steeping followed by germination and kilning, in which dramatic changes happen for a large number of physiological and biochemical traits in barley seeds. The objectives of this study were to comprehensively investigate the phenotypic changes during malting, and identify the key regulators that modulate the expression of genes associated with malt quality traits. The results showed that there was a significant positive correlation between gibberellic acid (GA) content and the activities of some hydrolytic enzymes, including α-amylases, β-amylases, and limit dextrinase (LD), and a significant negative correlation between GA and β-glucan content. Starch content had little change, but starch granules were pitted severely during malting. Weighted gene coexpression analysis (WGCNA) identified the genes associated with the greatest changes of the examined malt traits during malting. The correlation analysis and protein-protein interaction (PPI) analysis detected several key transcriptional factor (TF) regulating genes associated with malt quality. These genes and TFs regulating malting traits are potentially useful in barley breeding for malt quality improvement.

Selection of favorable alleles of genes controlling flowering and senescence improves malt barley quality

Malt barley (Hordeum vulgare L.) is an important cash crop with stringent grain quality standards. Timing of the switch from vegetative to reproductive growth and timing of whole-plant senescence and nutrient remobilization are critical for cereal grain yield and quality. Understanding the genetic variation in genes associated with these developmental traits can streamline genotypic selection of superior malt barley germplasm. Here, we determined the effects of allelic variation in three genes encoding a glycine-rich RNA-binding protein (HvGR-RBP1) and two NAC transcription factors (HvNAM1 and HvNAM2) on malt barley agronomics and quality using previously developed markers for HvGR-RBP1 and HvNAM1 and a novel marker for HvNAM2. Based on a single-nucleotide polymorphism (SNP) in the first intron, the utilized marker differentiates NAM2 alleles of low-grain protein variety 'Karl' and of higher protein variety 'Lewis'. We demonstrate that the selection of favorable alleles for each gene impacts heading date, senescence timing, grain size, grain protein concentration, and malt quality. Specifically, combining 'Karl' alleles for the two NAC genes with the 'Lewis' HvGR-RBP1 allele extends grain fill duration, increases the percentage of plump kernels, decreases grain protein, and provides malt quality stability. Molecular markers for these genes are therefore highly useful tools in malt barley breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01331-7.

Proteome Phenotypes Discriminate the Growing Location and Malting Traits in Field-Grown Barley

Barley is one of the key cereal grains for malting and brewing industries. However, climate variability and unprecedented weather events can impact barley yield and end-product quality. The genetic background and environmental conditions are key factors in defining the barley proteome content and malting characteristics. Here, we measure the barley proteome and malting characteristics of three barley lines grown in Western Australia, differing in genetic background and growing location, by applying liquid chromatography-mass spectrometry (LC-MS). Using data-dependent acquisition LC-MS, 1571 proteins were detected with high confidence. Quantitative data acquired using sequential window acquisition of all theoretical (SWATH) MS on barley samples resulted in quantitation of 920 proteins. Multivariate analyses revealed that the barley lines' genetics and their growing locations are strongly correlated between proteins and desired traits such as the malt yield. Linking meteorological data with proteomic measurements revealed how high-temperature stress in northern regions affects seed temperature tolerance during malting, resulting in a higher malt yield. Our results show the impact of environmental conditions on the barley proteome and malt characteristics; these findings have the potential to expedite breeding programs and malt quality prediction.

De novo transcriptome sequencing, assembly, and gene expression profiling of a salt-stressed halophyte (Salsola drummondii) from a saline habitat

Salsola drummondii is a perennial habitat-indifferent halophyte growing in saline and nonsaline habitats of the Arabian hyperarid deserts. It offers an invaluable opportunity to examine the molecular mechanisms of salt tolerance. The present study was conducted to elucidate these mechanisms through transcriptome profiling of seedlings grown from seeds collected in a saline habitat. The Illumina Hiseq 2500 platform was employed to sequence cDNA libraries prepared from shoots and roots of nonsaline-treated plants (controls) and plants treated with 1200 mM NaCl. Transcriptomic comparison between salt-treated and control samples resulted in 17,363 differentially expressed genes (DEGs), including 12,000 upregulated genes (7870 in roots, 4130 in shoots) and 5363 downregulated genes (4258 in roots and 1105 in shoots). The majority of identified DEGs are known to be involved in transcription regulation (79), signal transduction (82), defense metabolism (101), transportation (410), cell wall metabolism (27), regulatory processes (392), respiration (85), chaperoning (9), and ubiquitination (98) during salt tolerance. This study identified potential genes associated with the salt tolerance of S. drummondii and demonstrated that this tolerance may depend on the induction of certain genes in shoot and root tissues. These gene expressions were validated using reverse-transcription quantitative PCR, the results of which were consistent with transcriptomics results. To the best of our knowledge, this is the first study providing genetic information on salt tolerance mechanisms in S. drummondii.

CANDIDATE GENES IDENTIFICATION OF OIL PALM (Elaeis guineensis Jacq.) INTEREST CHARACTERS USING PUBLISHED DATABASE

Palm oil has supplied more than 30% of vegetable oil consumption worldwide. Rising demand has pushed oil palm plantations to increase the yield. It is well known that genetic has played a significant role in phenotypic performance. Moreover, in recent years, genomic data has emerged tremendously. Unfortunately on the gene related to oil palm yield. Therefore, a preliminary study to classify and select oil palm candidate genes associated with characteristic by scanning existing genes in oil palm or other in-silico species were conducted. Based on Blast2Go results, 22 genes related to oil biosynthesis, two specifically related to fruit number and fruit weight were analysed. Furthermore, 19 candidate genes were able to amplify.