Central Asia is an important region for the growth of winter wheat, with a cultivation area of more than 15 million hectares (ha). However, the average yield is approximately 3 tons per ha, which is significantly lower than that in developed countries. Therefore, the development of new competitive high-yielding cultivars, including those based on the application of modern molecular genetics tools, is a key priority in winter wheat breeding projects. One of these tools is the result of the identification of new genes and quantitative trait loci (QTLs) for agronomic traits using diverse germplasm panels and genome-wide association studies (GWAS). In this work, a panel of winter wheat accessions was assembled using 115 accessions from Central Asia and 162 samples from other regions of the world. The GWAS, based on a two-year field evaluation of the collection in Kazakhstan’s southern and southeastern regions and 10,481 polymorphic SNP (single-nucleotide polymorphism) markers, allowed for the detection of 173 stable QTLs in nine studied agronomic traits. A survey of the published scientific literature suggests that 23 of these 173 stable QTLs have locations similar to those of previously reported QTLs, supporting the robustness of the research. In addition, 221 and 162 accessions surpassed local standards for grain yield at Kazakhstan’s southern and southeastern stations, respectively. Therefore, this study is an additional contribution to the identification of new QTLs for key agronomic traits and valuable genetic lines in winter wheat breeding projects.

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.

Despite the importance of winter wheat in Central Asian countries, there are limited reports describing their diversity within this region. In this study, the population structures of 115 modern winter wheat cultivars from four Central Asian countries were compared to germplasms from six other geographic origins using 10,746 polymorphic single-nucleotide polymorphism (SNP) markers. After applying the STRUCTURE package, we found that in terms of the most optimal K steps, samples from Kazakhstan and Kyrgyzstan were grouped together with samples from Russia, while samples from Tajikistan and Uzbekistan were grouped with samples from Afghanistan. The mean value of Nei’s genetic diversity index for the germplasm from four groups from Central Asia was 0.261, which is comparable to that of the six other groups studied: Europe, Australia, the USA, Afghanistan, Turkey, and Russia. The Principal Coordinate Analysis (PCoA) showed that samples from Kyrgyzstan, Tajikistan, and Uzbekistan were close to samples from Turkey, while Kazakh accessions were located near samples from Russia. The evaluation of 10,746 SNPs in Central Asian wheat suggested that 1006 markers had opposing allele frequencies. Further assessment of the physical positions of these 1006 SNPs in the Wheat Ensembl database indicated that most of these markers are constituents of genes associated with plant stress tolerance and adaptability. Therefore, the SNP markers identified can be effectively used in regional winter wheat breeding projects for facilitating plant adaptation and stress resistance.

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.

The main purposes of the study were (i) to develop a mapping population, (ii) to construct its genetic map for further identification of genes associated with important agronomic traits. To the best of our knowledge this is the first segregating population and genetic map developed for Kazakh bread wheat. The work is an example of how plant breeding programs in Kazakhstan have started successfully using next generation plant breeding methods to carry out systematic plant breeding to enhance final grain harvest. The KASP technology and SNP DNA-markers have been exploited to genotype and build a genetic map. The total length of the map was 1376 cM. A total 157, which spanned A, B and D subgenomes, out of the initial 178 SNP markers used formed 26 linkage groups leaving 1 duplicated and 20 unassigned markers. As threshold distance between markers was set ≤30 cM, two linkage groups were obtained for chromosomes such as 2А, 2В, 2D, 3A, 5A, 6B and 7A. Kosambi mapping function was employed to calculate recombination units. RILs were developed through SSD method up to F4 generation. Almost 97% of identified alleles were useful in evaluating the population’s genetic diversity; the remaining 3% showed no outcome. As a result, 77 DNA markers were mapped for A, 74 for B and 27 for D genomes. The mapping population will be genotyped using a high marker density array platform such as Illumina iSelect to obtain a genetic map with a relatively high coverage. Then, the population and high-resolution genetic map will be used to identify genes influencing wheat adaptation in Kazakhstan.

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.