BackgroundSand rice (Agriophyllum squarrosum (L.) Moq.) is an annual shrub-like plant adapted to the mobile sand dunes in desert and semi-desert regions of Asia. It has a balanced nutrient composition with relatively high concentration of lipids and proteins, which results in its nutrition being similar to legumes. Sand rice’s proteins contain the full range of essential amino acids. However, calories content is more similar to wheat. These features together with desert stress resistance make sand rice a potential food crop resilient to ongoing climate change. It is also an important fodder crop (on young stages of growth) for cattle in arid regions of Kazakhstan. In our work, sand rice samples were collected from two distant regions of Kazakhstan as a part of the nation-wide project to determine genetic variation of the native flora.ResultsSamples were collected in western and southeastern parts of Kazakhstan separated by distances of up to 1300 km. Sequences of the nuclear ribosomal DNA ITS1-5.8S-ITS2 region and the chloroplast matK gene confirmed the identity of species defined by morphological traits. Comparison with GenBank sequences revealed polymorphic sequence positions among Kazakh populations and GenBank references, and suggested a distinction among local populations of sand rice. The phylogenetic analysis of nucleotide sequences showed a clear partition of A. squarrosum (L.) Moq. from Agriophyllum minus Fisch. & C.A. Mey, which grows in the same sand dunes environment.ConclusionsDNA barcoding analyses of ITS and matK sequences showed a segregation of A. squarrosum from A. minus into separate clades in Maximum-Likelhood dendrograms. ITS analysis can be successfully used to characterize A. squarrosum populations growing quite distant from each other. The data obtained in this work provide the basis for further investigations on A. squarrosum population structure and may play a role in the screening of sand rice plants growing in desert and semi-desert environments of Central Asia and China.

BackgroundSpring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS.ResultsField trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits.ConclusionsField evaluation of foreign germplasm revealed its poor yield performance in Northern Kazakhstan, which is the main wheat growing region in the country. However, it was found that EU and CIMMYT germplasm has high breeding potential to improve yield performance in Central and Southern regions. The use of Principal Coordinate analysis clearly separated the panel into three distinct groups according to their breeding origin. GWAS based on use of the TASSEL 5.0 package allowed the identification of 114 MTAs for twelve agronomic traits. The study identifies a network of key genes for improvement of yield productivity in wheat growing regions of Kazakhstan.

BackgroundIn recent years soybean is becoming one of the most important oilseed crops in Kazakhstan. Only within the last ten years (2006–2016), the area under soybean is expanded from 45 thousand hectares (ha) in 2006 to 120 thousand ha in 2016. The general trend of soybean expansion is from south-eastern to eastern and northern regions of the country, where average temperatures are lower and growing seasons are shorter. These new soybean growing territories were poorly examined in terms of general effects on productivity level among the diverse sample of soybean accessions. In this study, phenotypic data were collected in three separate regions of Kazakhstan and entire soybean sample was genotyped for identification of marker-trait associations (MTA).ResultsIn this study, the collection of 113 accessions representing five different regions of the World was planted in 2015–2016 in northern, eastern, and south-eastern regions of Kazakhstan. It was observed that North American accessions showed the highest yield in four out of six trials especially in Northern Kazakhstan in both years. The entire sample was genotyped with 6 K SNP Illumina array. 4442 SNPs found to be polymorphic and were used for whole genome genotyping purposes. Obtained SNP markers data and field data were used for GWAS (genome-wide association study). 30 SNPs appear to be very significant in 42 MTAs in six studied environments.ConclusionsThe study confirms the efficiency of GWAS for the identification of molecular markers which tag important agronomic traits. Overall thirty SNP markers associated with time to flowering and maturation, plant height, number of fertile nodes, seeds per plant and yield were identified. Physical locations of 32 identified out of 42 total MTAs coincide well with positions of known analogous QTLs. This result indicates importance of revealed MTAs for soybean growing regions in Kazakhstan. Obtained results would serve as required prerequisite for forming and realization of specific breeding programs towards effective adaptation and increased productivity of soybean in three different regions of Kazakhstan.

BackgroundIn recent years soybean is becoming one of the most important oilseed crops in Kazakhstan. Only within the last ten years (2006–2016), the area under soybean is expanded from 45 thousand hectares (ha) in 2006 to 120 thousand ha in 2016. The general trend of soybean expansion is from south-eastern to eastern and northern regions of the country, where average temperatures are lower and growing seasons are shorter. These new soybean growing territories were poorly examined in terms of general effects on productivity level among the diverse sample of soybean accessions. In this study, phenotypic data were collected in three separate regions of Kazakhstan and entire soybean sample was genotyped for identification of marker-trait associations (MTA).ResultsIn this study, the collection of 113 accessions representing five different regions of the World was planted in 2015–2016 in northern, eastern, and south-eastern regions of Kazakhstan. It was observed that North American accessions showed the highest yield in four out of six trials especially in Northern Kazakhstan in both years. The entire sample was genotyped with 6 K SNP Illumina array. 4442 SNPs found to be polymorphic and were used for whole genome genotyping purposes. Obtained SNP markers data and field data were used for GWAS (genome-wide association study). 30 SNPs appear to be very significant in 42 MTAs in six studied environments.ConclusionsThe study confirms the efficiency of GWAS for the identification of molecular markers which tag important agronomic traits. Overall thirty SNP markers associated with time to flowering and maturation, plant height, number of fertile nodes, seeds per plant and yield were identified. Physical locations of 32 identified out of 42 total MTAs coincide well with positions of known analogous QTLs. This result indicates importance of revealed MTAs for soybean growing regions in Kazakhstan. Obtained results would serve as required prerequisite for forming and realization of specific breeding programs towards effective adaptation and increased productivity of soybean in three different regions of Kazakhstan.

BackgroundAs part of nation-wide project to infer the genetic variation of the native flora in Kazakhstan, a study was attempted to assess phylogenetic relationships of endemic and rare Allium species. In total, 20 Allium species were collected in field trips in five different regions of Kazakhstan during 2015–2016. Most species (9) were collected in the southern part of the country along of Karatau mountains, followed by Altai mountains (5) in eastern Kazakhstan. The ITS and matK DNA regions were applied in order to assess the taxonomic relationships among species. The major goal of the study was to assess the taxonomic position of five endemic and rare species from Allium subgenus Reticulatobulbosa collected in Karatau mountains of Southern Kazakhstan.ResultsThe 20 collected Allium species were assessed using morphological traits and a DNA barcoding approach. The morphological analyses of four different species in subgenus Reticulatobulbosa inferred similarities of A. inconspicuum and A. barszchewskii (both from section Companulata) that were separated from A. oreoscordum and A. oreoprasoides (section Nigrimontana) by several traits, including form of bulbs and leaves, presence of bracts, shape of perianth lobes and style. The Neighbor-Joining method was applied to generate ITS and matK phylogenetic trees for two groups of populations: 1) 20 Allium species collected within the project, and 2) 50 Allium worldwide species.ConclusionsThe analyses of nucleotide sequences of ITS and matK robustly confirmed the monophyletic origin of the Allium species. The variability in 20 local Allium species in ITS was 6.6 higher than in matK, therefore the topology of the ITS tree was better resolved. The taxonomy of Allium species largely coincided with a recent classification of this genus. Analyses of both ITS and matK suggest that A. oreoscordum is genetically close to A. oreoprasoides in section Nigrimontana of subgenus Reticulatobulbosa. This result was also confirmed using morphological description of individual plants of four species in subgenus Reticulatobulbosa. The study is another contribution to taxonomy clarification in Allium.

BackgroundSand rice (Agriophyllum squarrosum (L.) Moq.) is an annual shrub-like plant adapted to the mobile sand dunes in desert and semi-desert regions of Asia. It has a balanced nutrient composition with relatively high concentration of lipids and proteins, which results in its nutrition being similar to legumes. Sand rice’s proteins contain the full range of essential amino acids. However, calories content is more similar to wheat. These features together with desert stress resistance make sand rice a potential food crop resilient to ongoing climate change. It is also an important fodder crop (on young stages of growth) for cattle in arid regions of Kazakhstan. In our work, sand rice samples were collected from two distant regions of Kazakhstan as a part of the nation-wide project to determine genetic variation of the native flora.ResultsSamples were collected in western and southeastern parts of Kazakhstan separated by distances of up to 1300 km. Sequences of the nuclear ribosomal DNA ITS1-5.8S-ITS2 region and the chloroplast matK gene confirmed the identity of species defined by morphological traits. Comparison with GenBank sequences revealed polymorphic sequence positions among Kazakh populations and GenBank references, and suggested a distinction among local populations of sand rice. The phylogenetic analysis of nucleotide sequences showed a clear partition of A. squarrosum (L.) Moq. from Agriophyllum minus Fisch. & C.A. Mey, which grows in the same sand dunes environment.ConclusionsDNA barcoding analyses of ITS and matK sequences showed a segregation of A. squarrosum from A. minus into separate clades in Maximum-Likelhood dendrograms. ITS analysis can be successfully used to characterize A. squarrosum populations growing quite distant from each other. The data obtained in this work provide the basis for further investigations on A. squarrosum population structure and may play a role in the screening of sand rice plants growing in desert and semi-desert environments of Central Asia and China.