Alexandr Pozharskiy

Mountain ecosystems of the Northern Tian Shan harbor rare endemic plant species that are increasingly vulnerable to environmental change. This study assessed the ontogenetic stage composition, selected anatomical characteristics, and chloroplast genome features of Malus sieversii, Ribes janczewskii, and Ikonnikovia kaufmanniana. Field surveys included five populations and 971 recorded individuals: two populations of M. sieversii, one population of R. janczewskii, and two populations of I. kaufmanniana. Individuals were assigned to juvenile, immature, vegetative adult, and generative stages. The proportion of juvenile and immature individuals varied from 23.78% to 41.89% among populations, indicating substantial differences in the representation of early ontogenetic stages. Comparative anatomical analysis identified structural traits associated with adaptation to local environmental conditions. Complete chloroplast genomes were assembled and annotated, with sizes of 160,192 bp (M. sieversii), 157,432 bp (R. janczewskii), and 162,624 bp (I. kaufmanniana). All plastomes exhibited a conserved quadripartite structure and contained 131–132 genes and SSR loci with species-specific composition. Phylogenomic analysis placed M. sieversii within a well-supported wild apple clade, confirmed the distinct lineage of R. janczewskii, and supported the separation of I. kaufmanniana from Limonium. These findings provide new data and lay a basis for further studies to better understand the evolutionary distinctiveness and conservation relevance of endemic plant species in the Northern Tian Shan.

Fire blight, caused by Erwinia amylovora , is one of the most important diseases of cultivated apple ( Malus domestica ) worldwide. Since 2008, this pathogen became widespread in Kazakhstan, a global centre of origin for apple. Genomic data on Central Asian populations of this pathogen remain limited. This study aimed to isolate, characterize and assess the pathogenicity and genomic diversity of E. amylovora isolates from the Almaty region. Seven isolates were obtained from symptomatic apple trees and confirmed using loop‐mediated isothermal amplification (LAMP) and real‐time quantitative PCR assays. Pathogenicity tests on apple saplings and immature pear fruits demonstrated variable virulence among isolates, depending on host and tissue type. Whole‐genome sequencing generated high‐quality draft genomes of approximately 3.7–3.8 Mb, each comprising a chromosome and the pEA29 plasmid, with an average sequencing depth of 525.8×. Comparative analysis identified 389 high‐confidence genetic variants, including 337 SNPs and 52 indels, with several impact mutations with predicted impacts detected in genes associated with virulence, stress response and cellular processes. The overall genomic similarity was extremely high (average nucleotide identity of 99.99%), confirming the low intraspecific diversity of the pathogen. Phylogenetic analysis involving 326 global genomes placed seven Kazakh isolates within a regional lineage closely related to strains from Kazakhstan, Kyrgyzstan and China. CRISPR typing classified all isolates into the (A,t,α) CRISPR haplotype typical for the Almaty region. These findings expand genomic data on E. amylovora in Central Asia and provide a foundation for improved surveillance, epidemiological tracking and disease management to protect cultivated and wild apple resources.

This study presents the results of mapping the distribution of economically important and quarantine weed species in southern Kazakhstan. Field surveys were conducted in the Almaty, Zhetysu, Zhambyl, and Turkestan regions, covering agricultural lands, roadside habitats, fallow fields, and irrigated areas. Georeferenced sampling was carried out to determine the current distribution range and infestation level of major weed species. A total of 1,078 specimens of Rhaponticum repens (Russian knapweed), 1,153 specimens of Ambrosia artemisiifolia (common ragweed), and 1,027 specimens of Cuscuta campestris (field dodder) were collected and analyzed. Weed distribution mapping was performed using QGIS 3.28, while geographic coordinates were processed with the Lat Lon Tools plugin. The resulting thematic maps enabled visualization of infestation hotspots and distribution patterns across the study area. The results showed that transportation corridors, irrigated agroecosystems, and intensively managed agricultural landscapes represent major pathways for weed dispersal. R. repens was primarily associated with arid and foothill environments, C. campestris was mainly distributed in irrigated croplands and roadside habitats, whereas A. artemisiifolia exhibited a fragmented but expanding distribution near urbanized and highly disturbed areas. The study demonstrates the value of GIS-based mapping as an effective tool for monitoring quarantine weeds, assessing phytosanitary risks, and supporting weed management strategies in southern Kazakhstan.

The spongy moth (Lymantria dispar) is a significant defoliator of broadleaf forests and fruit trees, but its population genetic structure in Central Asia remains poorly defined. We analyzed 153 specimens collected from ten populations across Kazakhstan between 2023 and 2024, using a combination of diagnostic real-time PCR, RAPD genotyping, and mitochondrial COI sequencing. Subspecies identification and Asian introgression were initially assessed with the COI/FS1 TaqMan assay. All samples carried the European mitochondrial type L. dispar dispar, while the nuclear FS1 locus indicated Asian introgression in 92.8% of specimens, including eleven heterozygotes for the Asian allele. RAPD amplification with five polymorphic primers produced 107 variable bands, which we converted into a presence/absence matrix for population genetics analysis. Principal coordinate analysis showed weak but detectable population structure, and Bayesian clustering (STRUCTURE) supported the presence of two primary nuclear clusters. Populations from Ketpentau, Sumbe, Kazachka, Butakovka, and Pavlodar were assigned predominantly to one cluster, whereas most individuals from Almaty, Ile-Alatau, Koksu, North Kazakhstan, and Tekeli were assigned predominantly to the other, with limited admixture in several localities. COI sequences formed a single, minimally differentiated L. dispar clade, with no evidence of distinct mitochondrial lineages. Overall, these findings reveal extensive Asian nuclear introgression in populations retaining European mitochondrial haplotypes, supporting the interpretation of Kazakhstan as part of a broad contact zone within the larger dispar–asiatica gradient. The observed mito-nuclear discordance has important implications for quarantine diagnostics and highlights the need for multilocus molecular assays in regional biosurveillance.

Emerging and re-emerging plant diseases are becoming more frequent and severe due to climate change, agricultural intensification, crop genetic uniformity, and the expanding global movement of planting materials. These drivers have altered host-pathogen-environment interactions, facilitating pathogen range expansion, host shifts, and erosion of resistance, thereby increasing the risk of epidemics and pandemics in major crops. In this context, genetic and genomic approaches have become central to modern plant pathology, providing high-resolution tools to investigate disease emergence, spread, and adaptation. This review summarizes recent advances in genomic surveillance, high-throughput sequencing-based diagnostics, pathogen pangenomes, and data-driven prediction as interconnected components of an integrated framework for studying emerging and re-emerging plant diseases. Genome-scale analyses have improved outbreak reconstruction and population-level inference, while unbiased sequencing and metagenomic approaches have expanded diagnostic capacity to include complex, latent, and previously undetected infections. Pangenomic studies further demonstrate that virulence evolution is frequently driven by gene content variation, structural rearrangements, and demographic processes, challenging reference-centric models of pathogen adaptation. Predictive and risk assessment approaches increasingly integrate genomic information with environmental, epidemiological, and pathway data to support proactive surveillance and management. Taken together, the evidence indicates that plant disease emergence results from interacting evolutionary, ecological, and anthropogenic processes. Genetic and genomic tools, when embedded within coordinated surveillance systems and supported by standardized data practices, provide a robust foundation for early warning, improved outbreak interpretation, and risk-informed plant health management under accelerating global change.

Cross-ecosystem transmission of plant pathogens from crops to natural forests is increasingly recognized as a key factor in disease emergence and biodiversity loss. Agricultural systems serve as major sources of inoculum, with landscape interfaces—such as crop–forest edges, riparian zones, abandoned orchards, and nursery–wildland transitions—acting as active epidemiological gateways. Biological vectors, abiotic dispersal, and human activities collectively enable pathogen movement across these boundaries. Host-range expansion, recombination, and hybridization allow pathogens to infect both cultivated and wild hosts, leading to generalist and recombinant lineages that survive across diverse habitats. In natural ecosystems, such introductions can alter community composition, decrease resilience, and intensify the impacts of climate-driven stress. Advances in molecular diagnostics, genomic surveillance, environmental DNA, and remote sensing–GIS (Geographic Information System) approaches now enable high-resolution detection of pathogen flow across landscapes. Incorporating these tools into interface-focused monitoring frameworks offers a pathway to earlier detection, better risk assessment, and more effective mitigation. A One Health, landscape-based approach that treats agro–wild interfaces as key control points is essential for reducing spillover risk and safeguarding both agricultural productivity and the health of natural forest ecosystems.

Fire blight, caused by Erwinia amylovora, is one of the most damaging bacterial diseases affecting apple production and the safety of wild Malus sieversii populations in Central Asia. Effective monitoring relies on accurate molecular diagnostics; however, comparative data on commonly used detection methods remain limited for the region. In this study, we evaluated the performance of three molecular assays—LAMP, real-time PCR, and targeted nanopore sequencing of a 16S rRNA gene fragment—using 124 plant samples exhibiting fire blight symptoms collected from 30 sites across Southern Kazakhstan and Kyrgyzstan. The results of LAMP, real-time PCR, and the amplification of 16S sequences were highly consistent with each other. Targeted 16S nanopore sequencing reliably identified E. amylovora in all PCR-positive samples, yielding high read counts and consistent species-level classification, although the analyzed 16S region provided limited resolution for intraspecies variation. Across sampling locations, abandoned orchards represented major reservoirs of infection compared to maintained orchards and wild populations. Our results confirm that all three approaches are robust tools for detecting E. amylovora. These findings support the importance of different molecular diagnostic methods to assist fire blight surveillance in the region.

Apple scab, caused by the fungus Venturia inaequalis, is one of the most widespread and economically significant diseases of apple orchards, leading to reduced photosynthesis, fruit damage, and yield losses of up to 70%. In this study, a survey of 30 wild and cultivated apple populations in Kazakhstan and Kyrgyzstan was conducted, encompassing 302 samples. The pathogen was detected in 8 populations (48 samples), corresponding to an infection rate of 16%. Molecular identification using the EF-1α marker and ITS region sequencing definitively confirmed the presence of V. inaequalis in all positive samples. Phylogenetic analysis showed clear population structuring: isolates from Kyrgyzstan formed a distinct clade close to international lineages, while Kazakh isolates showed high genetic variation. These findings highlight the ongoing presence of V. inaequalis in Central Asia and emphasize the importance of combining morphological, molecular, and phylogenetic methods for effective pathogen monitoring and control.

Grapevine viroids are the smallest pathogens affecting viticulture. Infected grapevines may show symptoms such as leaf yellowing, mottling, stunted growth, reduced fruit quality, and overall vine decline. Asymptomatic viroid infections in grapevines can still decrease grapevine productivity, thereby posing a hidden economic threat to viticulture (Wolpert et al., 1996; Wu et al., 2023). This study aimed to detect three widely distributed viroid species of the Pospiviroidae family: Grapevine yellow speckle viroid 1 (GYSVd-1), Grapevine yellow speckle viroid 2 (GYSVd-2), and Hop stunt viroid (HSVd). The study focused on grapevine (Vitis vinifera) cultivars 'Saperavi' and 'Rkatsiteli' cultivated in Kazakhstan. Three fields in Shirin village and one field in Tyulkubas village (each about 600 ha) in Almaty region were tested for the presence of viroids due to a decline in yield observed despite the negative tests for common viruses (past 3 years). Symptoms typical for viral infections were observed sporadically without a consistent pattern of infection. Total 17 samples from Shirin (July 2023) and 14 from Tyulkubas (June 2024) with visible symptoms were collected randomly. Validated primers were used to identify GYSVd-1 (mF/mR1, 250 bp) (Hajizadeh et al. 2012) GYSVd-2 (P1/P2, 375 bp) (Jiang et al. 2009) and HSVd (78P/83M, 312 bp) (Sano et al. 2001) using conventional RT-PCR. Among the analyzed samples, in Shirin village, 6 samples tested positive for GYSVd-1, 15 for GYSVd-2, and 15 for HSVd, including 2 positive for both HSVd and GYSVd-1. In Tyulkubas village, 2 samples were positive for GYSVd-1 and 12 for HSVd; GYSVd-1 positive samples als were positive for HSVd, including 8 positive for both HSVd and GYSVd-2 and 6 positive for three viroids. Amplicons for each viroid were further sequenced using the Sanger's method on ABI 3500 Genetic Analyser with BigDye v.3.1 kit and using MinION sequencer with the Rapid Barcoding Kit 96 V14 (Oxford Nanopore Technologies) according to the manufacturer's protocol. The obtained reads were mapped to reference sequences from GenBank-GYSVd-1 NC_001920.1, HSVd NC_001351.1, and GYSVd-2 MG780425.1-using Minimap v.2.2.0 with default parameters in Geneious software. Sequencing produced total 2253 reads for GYSVd-1 (average length 159 bp, range 42-296), 2095 for GYSVd-2 (203.6 bp, 49-578), and 1235 for HSVd (218.5 bp, 53-440). Of these, 947 (42.0%) were been mapped to GYSVd-1, 1778 (84.9%) to GYSVd-2, and 678 (54.9%) to HSVd. Genome coverage was 62.3% (GYSVd-1), 98.1% (GYSVd-2), and 73.8% (HSVd), with mean depths of 889X, 1282X, and 659X, respectively. Each viroid resulted a single contig corresponding to the target amplicon. No reads corresponding to other viral or bacterial agents have been identified. NCBI BLASTn search resulted total 141 hits with coverage 59-68% and identity 98.69-99.35% for GYSVd-1; 128 hits with coverage 82-100% and identity 97.59-100% for GYSVd-2; 157 hits with coverage 99-100% and identity 95.49-97.29%; no not-specific matches were identified for three viroids. The assembled viroid sequences obtained using nanopore sequencing have been uploaded into NCBI database (accessions PV341024-PV341026). Viroids GYSVd-1,2 and HSVd have been detected for the first time in Kazakhstan. The results indicate the need for further studies to estimate impact of these viroids on viticulture and lay a basis for their monitoring in the country.