QTL mapping of agronomic traits in wheat using the UK Avalon × Cadenza reference mapping population grown in Kazakhstan

Identification of Quantitative Trait Loci Associated with Plant Adaptation Traits Using Nested Association Mapping Population

This study evaluated 290 recombinant inbred lines (RILs) of the nested association mapping (NAM) population from the UK. The population derived from 24 families, where a common parent was "Paragon," one of the UK's spring wheat cultivar standards. All genotypes were tested in two regions of Kazakhstan at the Kazakh Research Institute of Agriculture and Plant Industry (KRIAPI, Almaty region, Southeast Kazakhstan, 2019-2022 years) and Alexandr Barayev Scientific-Production Center for Grain Farming (SPCGF, Shortandy, Akmola region, Northern Kazakhstan, 2019-2022 years). The studied traits consisted of plant adaptation-related traits, including heading date (HD, days), seed maturation date (SMD, days), plant height (PH, cm), and peduncle length (PL, cm). In addition, the yield per m2 was analyzed in both regions. Based on a field evaluation of the population in northern and southeastern Kazakhstan and using 10,448 polymorphic SNP (single-nucleotide polymorphism) markers, the genome-wide association study (GWAS) allowed for detecting 74 QTLs in four studied agronomic traits (HD, SMD, PH, and PL). The literature survey suggested that 16 of the 74 QTLs identified in our study had also been detected in previous QTL mapping studies and GWASs for all studied traits. The results will be used for further studies related to the adaptation and productivity of wheat in breeding projects for higher grain productivity.

Rht12b, a widely used ancient allele of TaGA2oxA13, reduces plant height and enhances yield potential in wheat

KEY MESSAGE

We identified a new wheat dwarfing allele Rht12b conferring reduced height and higher grain yield, pinpointed its causal variations, developed a breeding-applicable marker, and traced its origin and worldwide distribution. Plant height control is essential to optimize lodging resistance and yield gain in crops. RHT12 is a reduced height (Rht) locus that is identified in a mutationally induced dwarfing mutant and encodes a gibberellin 2-oxidase TaGA2oxA13. However, the artificial dwarfing allele is not used in wheat breeding due to excessive height reduction. Here, we confirmed a stable Rht locus, overlapping with RHT12, in a panel of wheat cultivars and its dwarfing allele reduced plant height by 5.4-8.2 cm, equivalent to Rht12b, a new allele of RHT12. We validated the effect of Rht12b on plant height in a bi-parent mapping population. Importantly, wheat cultivars carrying Rht12b had higher grain yield than those with the contrasting Rht12a allele. Rht12b conferred higher expression level of TaGA2oxA13. Transient activation assays defined SNP-390(C/A) in the promoter of TaGA2oxA13 as the causal variation. An efficient kompetitive allele-specific PCR marker was developed to diagnose Rht12b. Conjoint analysis showed that Rht12b plus the widely used Rht-D1b, Rht8 and Rht24b was the predominant Rht combination and conferred a moderate plant height in tested wheat cultivars. Evolutionary tracking uncovered that RHT12 locus arose from a tandem duplication event with Rht12b firstly appearing in wild emmer. The frequency of Rht12b was approximately 70% (700/1005) in a worldwide wheat panel and comparable to or higher than those of other widely used Rht genes, suggesting it had been subjected to positive selection. These findings not only identify a valuable Rht gene for wheat improvement but also develop a functionally diagnostic tool for marker-assisted breeding.

Genome-wide association studies for phenological and agronomic traits in mungbean (Vigna radiata L. Wilczek)

Mungbean (Vigna radiata L. Wilczek) is one of the important warm-season food legumes, contributing substantially to nutritional security and environmental sustainability. The genetic complexity of yield-associated agronomic traits in mungbean is not well understood. To dissect the genetic basis of phenological and agronomic traits, we evaluated 153 diverse mungbean genotypes for two phenological (days to heading and days to maturity) and eight agronomic traits (leaf nitrogen status using SPAD, plant height, number of primary branches, pod length, number of pods per plant, seeds per pod, 100-seed weight, and yield per plant) under two environmental conditions. A wide array of phenotypic variability was apparent among the studied genotypes for all the studied traits. The broad sense of heritability of traits ranged from 0.31 to 0.95 and 0.21 to 0.94 at the Delhi and Ludhiana locations, respectively. A total of 55,634 genome-wide single nucleotide polymorphisms (SNPs) were obtained by the genotyping-by-sequencing method, of which 15,926 SNPs were retained for genome-wide association studies (GWAS). GWAS with Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) model identified 50 SNPs significantly associated with phenological and agronomic traits. In total, 12 SNPs were found to be significantly associated with phenological traits across environments, explaining 7%-18.5% of phenotypic variability, and 38 SNPs were significantly associated with agronomic traits, explaining 4.7%-27.6% of the phenotypic variability. The maximum number of SNPs (15) were located on chromosome 1, followed by seven SNPs each on chromosomes 2 and 8. The BLAST search identified 19 putative candidate genes that were involved in light signaling, nitrogen responses, phosphorus (P) transport and remobilization, photosynthesis, respiration, metabolic pathways, and regulating growth and development. Digital expression analysis of 19 genes revealed significantly higher expression of 12 genes, viz. VRADI01G08170, VRADI11G09170, VRADI02G00450, VRADI01G00700, VRADI07G14240, VRADI03G06030, VRADI02G14230, VRADI08G01540, VRADI09G02590, VRADI08G00110, VRADI02G14240, and VRADI02G00430 in the roots, cotyledons, seeds, leaves, shoot apical meristems, and flowers. The identified SNPs and putative candidate genes provide valuable genetic information for fostering genomic studies and marker-assisted breeding programs that improve yield and agronomic traits in mungbean.

Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat

KEY MESSAGE

A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

Background

Although genome-wide association studies (GWAS) are an increasingly informative tool in the mining of new quantitative trait loci (QTLs), a classical biparental mapping approach is still a powerful, widely used method to search the unique genetic factors associated with important agronomic traits in bread wheat.

Methods

In this study, a newly constructed mapping population of Pamyati Azieva (Russian Federation) × Paragon (UK), consisting of 94 recombinant inbred lines (RILs), was tested in three different regions of Kazakhstan with the purpose of QTL identification for key agronomic traits. The RILs were tested in 11 environments of two northern breeding stations (Petropavlovsk, North Kazakhstan region, and Shortandy, Aqmola region) and one southeastern station (Almalybak, Almaty region). The following eight agronomic traits were studied: heading days, seed maturation days, plant height, spike length, number of productive spikes, number of kernels per spike, thousand kernel weight, and yield per square meter. The 94 RILs of the PAxP cross were genotyped using Illumina's iSelect 20K single nucleotide polymorphism (SNP) array and resulted in the identification of 4595 polymorphic SNP markers.

Results

The application of the QTL Cartographer statistical package allowed the identification of 53 stable QTLs for the studied traits. A survey of published studies related to common wheat QTL identification suggested that 28 of those 53 QTLs were presumably novel genetic factors. The SNP markers for the identified QTLs of the analyzed agronomic traits of common wheat can be efficiently applied in ongoing breeding activities in the wheat breeding community using a marker-assisted selection approach.

Genome-wide association study of yield components in spring wheat collection harvested under two water regimes in Northern Kazakhstan

Background

Bread wheat is the most important cereal in Kazakhstan, where it is grown on over 12 million hectares. One of the major constraints affecting wheat grain yield is drought due to the limited water supply. Hence, the development of drought-resistant cultivars is critical for ensuring food security in this country. Therefore, identifying quantitative trait loci (QTLs) associated with drought tolerance as an essential step in modern breeding activities, which rely on a marker-assisted selection approach.

Methods

A collection of 179 spring wheat accessions was tested under irrigated and rainfed conditions in Northern Kazakhstan over three years (2018, 2019, and 2020), during which data was collected on nine traits: heading date (HD), seed maturity date (SMD), plant height (PH), peduncle length (PL), number of productive spikes (NPS), spike length (SL), number of kernels per spike (NKS), thousand kernel weight (TKW), and kernels yield per m² (YM2). The collection was genotyped using a 20,000 (20K) Illumina iSelect SNP array, and 8,662 polymorphic SNP markers were selected for a genome-wide association study (GWAS) to identify QTLs for targeted agronomic traits.

Results

Out of the total of 237 discovered QTLs, 50 were identified as being stable QTLs for irrigated and rainfed conditions in the Akmola region, Northern Kazakhstan; the identified QTLs were associated with all the studied traits except PH. The results indicate that nine QTLs for HD and 11 QTLs for SMD are presumably novel genetic factors identified in the irrigated and rainfed conditions of Northern Kazakhstan. The identified SNP markers of the QTLs for targeted traits in rainfed conditions can be applied to develop new competitive spring wheat cultivars in arid zones using a marker-assisted selection approach.