Development of mapping populations (MP) of any crop, including wheat, with its high-density genetics map is a crucial initial step in breeding programs aimed towards identification of quantitative trait loci for complex traits, such as yield. Current study is related to the field observations of hexaploid common wheat MP derived from a cross between the cultivars Pamyati Azieva (Russian Federation) and Paragon (UK). MP consisted of 98 recombinant inbred lines (RILs). It is the first mapping population to be constructed using one of the registered commercial cultivars in Kazakhstan. All 98 RILs were tested for four consecutive years (2015-2018) in the field conditions of the Kazakh Research Institute of Agriculture and Plant growing (KAZNIIZR). Field study suggests that the MP is a highly suitable genetic resource for wheat breeding projects, as the developed RILs showed a wide range of variation in yield related traits, including plant height (PH), number of fertile spikes (NFS), number of kernels per spike (NKS), and thousand kernel weight (TKW). The analysis of weight of kernels per plant (WKP) indicated that in total 40 RILs, including these five RILs: RIL48, RIL36, RIL83, RIL01, and RIL46, outperformed the local parent cultivar Pamyati Azieva. They showed averaged best yield values over the indicated period, which is highly correlated with PH, NFS, NKS, and TKW, as indicated by the Pearson correlation index. Individuals with favorable values for all yield-related traits were identified for their incorporation into the breeding studies. The GGE Biplot analysis allowed the separation of four trials to two mega-environments, possibly reflecting the amount of precipitation around flowering time and seed maturation time, which are crucial phases of wheat plant growth and development. These observations will be used to inform further studies related to genetic mapping of quantitative trait loci of yield components in common wheat.
Leaf rust (LR) and stem rust (SR) are harmful fungal diseases of bread wheat (Triticum aestivum L.). The purpose of this study was to identify QTLs for resistance to LR and SR that are effective in two wheat-growing regions of Kazakhstan. To accomplish this task, a population of recombinant inbred lines (RILs) of ‘Pamyati Azieva × Paragon’ was grown in the northern and southeastern parts of Kazakhstan, phenotyped for LR/SR severities, and analyzed for key yield components. The study revealed a negative correlation between disease severity and plant productivity in both areas. The mapping population was genotyped using a 20,000 Illumina SNP array. A total of 4595 polymorphic SNP markers were further selected for linkage analysis after filtering based on missing data percentage and segregation distortion. Windows QTL Cartographer was applied to identify QTLs associated with LR and SR resistances in the RIL mapping population studied. Two QTLs for LR resistance and eight for SR resistance were found in the north, and the genetic positions of eight of them have matched the positions of the known Lr and Sr genes, while two QTLs for SR were novel. In the southeast, eight QTLs for LR and one for SR were identified in total. The study is an initial step of the genetic mapping of LR and SR resistance loci of bread wheat in Kazakhstan. Field trials in two areas of the country and the genotyping of the selected mapping population have allowed identification of key QTLs that will be effective in regional breeding projects for better bread wheat productivity.
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.
Background The success of wheat production is largely dependent on local breeding projects that focus on the development of high-yielding cultivars with the use of novel molecular tools. One strategy for improving wheat productivity involves the deployment of diverse germplasms with a high potential yield. An important factor for achieving success involves the dissection of quantitative trait loci (QTLs) for complex agronomic traits, such as grain yield components, in targeted environments for wheat growth. Methods In this study, we tested the United Kingdom (UK) spring set of the doubled haploid (DH) reference population derived from the cross between two British cultivars, Avalon (winter wheat) and Cadenza (spring wheat), in the Northern, Central, and Southern regions (Karabalyk, Karaganda, Kyzylorda) of Kazakhstan over three years (2013–2015). The DH population has previously been genotyped by UK scientists using 3647 polymorphic DNA markers. The list of tested traits includes the heading time, seed maturation time, plant height, spike length, productive tillering, number of kernels per spike, number of kernels per meter, thousand kernel weight, and yield per square meter. Windows QTL Cartographer was applied for QTL mapping using the composite interval mapping method. Results In total, 83 out of 232 QTLs were identified as stable QTLs from at least two environments. A literature survey suggests that 40 QTLs had previously been reported elsewhere, indicating that this study identified 43 QTLs that are presumably novel marker-trait associations (MTA) for these environments. Hence, the phenotyping of the DH population in new environments led to the discovery of novel MTAs. The identified SNP markers associated with agronomic traits in the DH population could be successfully used in local Kazakh breeding projects for the improvement of wheat productivity.
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