Isolation of High-Molecular-Weight DNA for Long-Read Sequencing Using a High-Salt Gel Electroelution Trap.

Long-read sequencing technologies require high-molecular-weight (HMW) DNA of sufficient purity and integrity, which can be difficult to obtain from complex biological samples. We propose a method for purifying HMW DNA that takes advantage of the fact that DNA's electrophoretic mobility decreases in a high-ionic-strength environment. The method begins with the separation of HMW DNA from various impurities by electrophoresis in an agarose gel-filled channel. After sufficient separation, a high-salt gel block is placed ahead of the DNA band of interest, leaving a gap between the separating gel and the high-salt gel that serves as a reservoir for sample collection. The DNA is then electroeluted from the separating gel into the reservoir, where its migration slows due to electrostatic shielding of the DNA's negative charge by excess counterions from the high-salt gel. As a result, the reservoir accumulates HMW DNA of high purity and integrity, which can be easily collected and used for long-read sequencing and other demanding applications without additional desalting. The method is simple and inexpensive, yields sequencing-grade HMW DNA even from difficult plant and soil samples, and has the potential for automation and scalability.

BIODICA: a computational environment for Independent Component Analysis of omics data.

SUMMARY: We developed BIODICA, an integrated computational environment for application of independent component analysis (ICA) to bulk and single-cell molecular profiles, interpretation of the results in terms of biological functions and correlation with metadata. The computational core is the novel Python package stabilized-ica which provides interface to several ICA algorithms, a stabilization procedure, meta-analysis and component interpretation tools. BIODICA is equipped with a user-friendly graphical user interface, allowing non-experienced users to perform the ICA-based omics data analysis. The results are provided in interactive ways, thus facilitating communication with biology experts. AVAILABILITY AND IMPLEMENTATION: BIODICA is implemented in Java, Python and JavaScript. The source code is freely available on GitHub under the MIT and the GNU LGPL licenses. BIODICA is supported on all major operating systems. URL: https://sysbio-curie.github.io/biodica-environment/.

Assessing reproducibility of matrix factorization methods in independent transcriptomes.

MOTIVATION: Matrix factorization (MF) methods are widely used in order to reduce dimensionality of transcriptomic datasets to the action of few hidden factors (metagenes). MF algorithms have never been compared based on the between-datasets reproducibility of their outputs in similar independent datasets. Lack of this knowledge might have a crucial impact when generalizing the predictions made in a study to others. RESULTS: We systematically test widely used MF methods on several transcriptomic datasets collected from the same cancer type (14 colorectal, 8 breast and 4 ovarian cancer transcriptomic datasets). Inspired by concepts of evolutionary bioinformatics, we design a novel framework based on Reciprocally Best Hit (RBH) graphs in order to benchmark the MF methods for their ability to produce generalizable components. We show that a particular protocol of application of independent component analysis (ICA), accompanied by a stabilization procedure, leads to a significant increase in the between-datasets reproducibility. Moreover, we show that the signals detected through this method are systematically more interpretable than those of other standard methods. We developed a user-friendly tool for performing the Stabilized ICA-based RBH meta-analysis. We apply this methodology to the study of colorectal cancer (CRC) for which 14 independent transcriptomic datasets can be collected. The resulting RBH graph maps the landscape of interconnected factors associated to biological processes or to technological artifacts. These factors can be used as clinical biomarkers or robust and tumor-type specific transcriptomic signatures of tumoral cells or tumoral microenvironment. Their intensities in different samples shed light on the mechanistic basis of CRC molecular subtyping. AVAILABILITY AND IMPLEMENTATION: The RBH construction tool is available from http://goo.gl/DzpwYp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Independent Component Analysis for Unraveling the Complexity of Cancer Omics Datasets.

Independent component analysis (ICA) is a matrix factorization approach where the signals captured by each individual matrix factors are optimized to become as mutually independent as possible. Initially suggested for solving source blind separation problems in various fields, ICA was shown to be successful in analyzing functional magnetic resonance imaging (fMRI) and other types of biomedical data. In the last twenty years, ICA became a part of the standard machine learning toolbox, together with other matrix factorization methods such as principal component analysis (PCA) and non-negative matrix factorization (NMF). Here, we review a number of recent works where ICA was shown to be a useful tool for unraveling the complexity of cancer biology from the analysis of different types of omics data, mainly collected for tumoral samples. Such works highlight the use of ICA in dimensionality reduction, deconvolution, data pre-processing, meta-analysis, and others applied to different data types (transcriptome, methylome, proteome, single-cell data). We particularly focus on the technical aspects of ICA application in omics studies such as using different protocols, determining the optimal number of components, assessing and improving reproducibility of the ICA results, and comparison with other popular matrix factorization techniques. We discuss the emerging ICA applications to the integrative analysis of multi-level omics datasets and introduce a conceptual view on ICA as a tool for defining functional subsystems of a complex biological system and their interactions under various conditions. Our review is accompanied by a Jupyter notebook which illustrates the discussed concepts and provides a practical tool for applying ICA to the analysis of cancer omics datasets.

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

BACKGROUND: Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. RESULTS: Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. CONCLUSIONS: We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

Cancer-related genes in the transcription signature of facioscapulohumeral dystrophy myoblasts and myotubes.

Muscular dystrophy is a condition potentially predisposing for cancer; however, currently, only Myotonic dystrophy patients are known to have a higher risk of cancer. Here, we have searched for a link between facioscapulohumeral dystrophy (FSHD) and cancer by comparing published transcriptome signatures of FSHD and various malignant tumours and have found a significant enrichment of cancer-related genes among the genes differentially expressed in FSHD. The analysis has shown that gene expression profiles of FSHD myoblasts and myotubes resemble that of Ewing's sarcoma more than that of other cancer types tested. This is the first study demonstrating a similarity between FSHD and cancer cell expression profiles, a finding that might indicate the existence of a common step in the pathogenesis of these two diseases.

Genome sequence and assembly of the amylolytic Bacillus licheniformis T5 strain isolated from Kazakhstan soil.

OBJECTIVES: The data presented in this study were collected with the aim of obtaining the complete genomes of specific strains of Bacillus bacteria, namely, Bacillus licheniformis T5. This strain was chosen based on its enzymatic activities, particularly amylolytic activity. In this study, nanopore sequencing technology was employed to obtain the genome sequences of this strain. It is important to note that these data represent a focused objective within a larger research context, which involves exploring the biochemical features of promising Bacilli strains and investigating the relationship between enzymatic activity, phenotypic features, and the microorganism's genome. DATA DESCRIPTION: In this study, the whole-genome sequence was obtained from one Bacillus strain, Bacillus licheniformis T5, isolated from soil samples in Kazakhstan. Sample preparation and genomic DNA library construction were performed according to the Ligation sequencing gDNA kit (SQK-LSK109) protocol and NEBNext module. The prepared library was sequenced on a MinION instrument (Oxford Nanopore Technologies nanopore sequencer with a maximum throughput of up to 30 billion nucleotides per run and no limit on read length), using a flow cell for nanopore sequencing FLO-MIN106D. The genome de novo assembly was performed using the long sequencing reads generated by MinION Oxford Nanopore platform. Finally, one circular contig was obtained harboring a length of 4,247,430 bp with 46.16% G + C content and the mean contig 428X coverage. B. licheniformis T5 genome assembly annotation revealed 5391 protein-coding sequences, 81 tRNAs, 51 repeat regions, 24 rRNAs, 3 virulence factors and 53 antibiotic resistance genes. This sequence encompasses the complete genetic information of the strain, including genes, regulatory elements, and noncoding regions. The data reveal important insights into the genetic characteristics, phenotypic traits, and enzymatic activity of this Bacillus strain. The findings of this study have particular value to researchers interested in microbial biology, biotechnology, and antimicrobial studies. The genomic sequence offers a foundation for understanding the genetic basis of traits such as endospore formation, alkaline tolerance, temperature range for growth, nutrient utilization, and enzymatic activities. These insights can contribute to the development of novel biotechnological applications, such as the production of enzymes for industrial purposes. Overall, this study provides valuable insights into the genetic characteristics, phenotypic traits, and enzymatic activities of the Bacillus licheniformis T5 strain. The acquired genomic sequences contribute to a better understanding of this strain and have implications for various research fields, such as microbiology, biotechnology, and antimicrobial studies.

Vitamin D Status, VDR, and TLR Polymorphisms and Pulmonary Tuberculosis Epidemiology in Kazakhstan.

BACKGROUND: Tuberculosis (TB) and vitamin D deficiency remain major public health problems in Kazakhstan. Due to the high incidence of pulmonary tuberculosis in the country and based on the importance of vitamin D in the modulation of the immune response and the association of its deficiency with many health conditions, the aim of our research was to study the vitamin D status, VDR and TLR gene polymorphisms, and pulmonary tuberculosis epidemiology in Kazakhstan. METHODS: A case-control study included 411 individuals diagnosed with pulmonary TB and 686 controls with no family history of pulmonary tuberculosis. Concentrations of serum vitamin D (25-(OH)D) levels were measured by electrochemiluminescence immunoassay. The gene polymorphisms were determined by real-time polymerase chain reaction (PCR) allelic discrimination assay using TaqMan probes. The association between the risk of pulmonary TB and polymorphisms was evaluated using multimodal logistic regression and assessed with the ORs, corresponding to 95% Cis, and the significance level was determined as p < 0.05. RESULTS: 1097 individuals were recruited from 3 different regions of Kazakhstan. Biochemical data showed vitamin D deficiency (25-(OH)D < 20 ng/mL) was present in both groups, with the case group accounting for almost 95% and 43.7% in controls. Epidemiological data revealed that socioeconomic factors such as BMI < 25 kg/m2 (p < 0.001), employment (p < 0.001), diabetes (p < 0.001), and vitamin D deficiency (p < 0.001) were statistically different between case and control groups. Logistic regression analysis, adjusted by sex, age, BMI, residence, employment, smoking, alcohol consumption, and diabetes, showed that T/T polymorphism of the VDR gene (rs1544410, OR = 1.97, 95% CI: 1.04-3.72, p = 0.03) and A/A polymorphism of the TLR8 gene (rs3764880, OR = 2.44, 95% CI: 1.20-4.98, p = 0.01) were associated with a high risk of developing pulmonary tuberculosis. CONCLUSIONS: Vitamin D deficiency remains prevalent in our study cohort and is associated with TB progression. Socioeconomic determinants such as unemployment, BMI under 25 kg/m2, and diabetes are the main risk factors for the development of pulmonary TB in our study. A/A polymorphism of TLR8 (rs3764880) and T/T polymorphism (BsmI, rs1544410) of VDR genes may act as biomarkers for pulmonary tuberculosis in the Kazakh population.

Pulmonary tuberculosis epidemiology and genetics in Kazakhstan.

Background: Tuberculosis (TB) is a major public health emergency in many countries, including Kazakhstan. Despite the decline in the incidence rate and having one of the highest treatment effectiveness in the world, the incidence rate of TB remains high in Kazakhstan. Social and environmental factors along with host genetics contribute to pulmonary tuberculosis (PTB) incidence. Due to the high incidence rate of TB in Kazakhstan, our research aimed to study the epidemiology and genetics of PTB in Kazakhstan. Materials and methods: 1,555 participants were recruited to the case-control study. The epidemiology data was taken during an interview. Polymorphisms of selected genes were determined by real-time PCR using pre-designed TaqMan probes. Results: Epidemiological risk factors like diabetes (χ2 = 57.71, p < 0.001), unemployment (χ2 = 81.1, p < 0.001), and underweight-ranged BMI (<18.49, χ2 = 206.39, p < 0.001) were significantly associated with PTB. VDR FokI (rs2228570) and VDR BsmI (rs1544410) polymorphisms were associated with an increased risk of PTB. A/A genotype of the TLR8 gene (rs3764880) showed a significant association with an increased risk of PTB in Asians and Asian males. The G allele of the rs2278589 polymorphism of the MARCO gene increases PTB susceptibility in Asians and Asian females. VDR BsmI (rs1544410) polymorphism was significantly associated with PTB in Asian females. A significant association between VDR ApaI polymorphism and PTB susceptibility in the Caucasian population of Kazakhstan was found. Conclusion: This is the first study that evaluated the epidemiology and genetics of PTB in Kazakhstan on a relatively large cohort. Social and environmental risk factors play a crucial role in TB incidence in Kazakhstan. Underweight BMI (<18.49 kg/m2), diabetes, and unemployment showed a statistically significant association with PTB in our study group. FokI (rs2228570) and BsmI (rs1544410) polymorphisms of the VDR gene can be used as possible biomarkers of PTB in Asian males. rs2278589 polymorphism of the MARCO gene may act as a potential biomarker of PTB in Kazakhs. BsmI polymorphism of the VDR gene and rs2278589 polymorphism of the MARCO gene can be used as possible biomarkers of PTB risk in Asian females as well as VDR ApaI polymorphism in Caucasians.

Transcriptome profiling and analysis of patients with esophageal squamous cell carcinoma from Kazakhstan.

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal cancer in Central Asia, often diagnosed at advanced stages. Understanding population-specific patterns of ESCC is crucial for tailored treatments. This study aimed to unravel ESCC's genetic basis in Kazakhstani patients and identify potential biomarkers for early diagnosis and targeted therapies. ESCC patients from Kazakhstan were studied. We analyzed histological subtypes and conducted in-depth transcriptome sequencing. Differential gene expression analysis was performed, and significantly dysregulated pathways were identified using KEGG pathway analysis (p-value < 0.05). Protein-protein interaction networks were constructed to elucidate key modules and their functions. Among Kazakhstani patients, ESCC with moderate dysplasia was the most prevalent subtype. We identified 42 significantly upregulated and two significantly downregulated KEGG pathways, highlighting molecular mechanisms driving ESCC pathogenesis. Immune-related pathways, such as viral protein interaction with cytokines, rheumatoid arthritis, and oxidative phosphorylation, were elevated, suggesting immune system involvement. Conversely, downregulated pathways were associated with extracellular matrix degradation, crucial in cancer invasion and metastasis. Protein-protein interaction network analysis revealed four distinct modules with specific functions, implicating pathways in esophageal cancer development. High-throughput transcriptome sequencing elucidated critical molecular pathways underlying esophageal carcinogenesis in Kazakhstani patients. Insights into dysregulated pathways offer potential for early diagnosis and precision treatment strategies for ESCC. Understanding population-specific patterns is essential for personalized approaches to ESCC management.

Blind source separation methods for deconvolution of complex signals in cancer biology.

Two blind source separation methods (Independent Component Analysis and Non-negative Matrix Factorization), developed initially for signal processing in engineering, found recently a number of applications in analysis of large-scale data in molecular biology. In this short review, we present the common idea behind these methods, describe ways of implementing and applying them and point out to the advantages compared to more traditional statistical approaches. We focus more specifically on the analysis of gene expression in cancer. The review is finalized by listing available software implementations for the methods described.

Whole-Genome Sequence-Based Characterization of Pre-XDR M. tuberculosis Clinical Isolates Collected in Kazakhstan.

BACKGROUND: Kazakhstan has a high burden of multidrug-resistant tuberculosis in the Central Asian region. This study aimed to perform genomic characterization of Mycobacterium tuberculosis strains obtained from Kazakhstani patients with pre-extensively drug-resistant tuberculosis diagnosed in Kazakhstan. METHODS: Whole-genome sequencing was performed on 10 pre-extensively drug-resistant M. tuberculosis strains from different regions of Kazakhstan. All strains had high-confidence resistance mutations according to the resistance grading system previously established by the World Health Organization. The genome analysis was performed using TB-Profiler, Mykrobe, CASTB, and ResFinder. RESULTS: Valuable information for understanding the genetic diversity of tuberculosis in Kazakhstan can also be obtained from whole-genome sequencing. The results from the Phenotypic Drug Susceptibility Testing (DST) of bacterial strains were found to be consistent with the drug resistance information obtained from genomic data that characterized all isolates as pre-XDR. This information can help in developing targeted prevention and control strategies based on the local epidemiology of tuberculosis. Furthermore, the data obtained from whole-genome sequencing can help in tracing the transmission pathways of tuberculosis and facilitating early detection of outbreaks. CONCLUSIONS: The results from whole-genome sequencing of tuberculosis clinical samples in Kazakhstan provide important insights into the drug resistance patterns and genetic diversity of tuberculosis in the country. These results can contribute to the improvement of tuberculosis control and management programs in Kazakhstan.

Universal whole-genome Oxford nanopore sequencing of SARS-CoV-2 using tiled amplicons.

We developed a comprehensive multiplexed set of primers adapted for the Oxford Nanopore Rapid Barcoding library kit that allows universal SARS-CoV-2 genome sequencing. This primer set is designed to set up any variants of the primers pool for whole-genome sequencing of SARS-CoV-2 using single- or double-tiled amplicons from 1.2 to 4.8 kb with the Oxford Nanopore. This multiplexed set of primers is also applicable for tasks like targeted SARS-CoV-2 genome sequencing. We proposed here an optimized protocol to synthesize cDNA using Maxima H Minus Reverse Transcriptase with a set of SARS-CoV-2 specific primers, which has high yields of cDNA template for RNA and is capable of long-length cDNA synthesis from a wide range of RNA amounts and quality. The proposed protocol allows whole-genome sequencing of the SARS-CoV-2 virus with tiled amplicons up to 4.8 kb on low-titer virus samples and even where RNA degradation has occurred. This protocol reduces the time and cost from RNA to genome sequence compared to the Midnight multiplex PCR method for SARS-CoV-2 genome sequencing using the Oxford Nanopore.

Cardiological Functional Assessment of National Olympic Team of Kazakhstan.

Athletes carry an increased risk of cardiovascular (CV) conditions. Due to the relatively high loads and intensity of the training process, athletes' CV systems undergo various adaptations, which can combine in the future and provoke unexpected outcomes. Most CV screening protocols have several successive steps. The aim of our study was to perform a cardiological functional assessment of the National Olympic Team of Kazakhstan via several noninvasive protocols to close the gaps between the approaches and collect solid data for the prevention of sudden cardiac death (SCD) incidence among Kazakhstani athletes. METHODS: The methods used in this study were 12-lead resting electrocardiography (ECG), echocardiography, cardiointervalography, cardiopulmonary exercise testing (CPET), and HyperQ stress testing. RESULTS: One case was detected via 12-lead resting ECG. Another case of the slowdown of the heart rate (HR) recovery was detected via cardiointervalography with no clinical signs and normal ECG. The HyperQ stress testing of the women's basketball team detected a positive result in four leads in one athlete. CONCLUSION: Our results demonstrate that the CV systems of athletes require the implementation of several diagnostic methods in rest and stress conditions for more precise evaluation, with each of the methods fulfilling the whole picture for the prevention of such tragic events as sudden cardiac death and sudden cardiac arrest.

Whole-Genome Sequencing Among Kazakhstani Children with Early-Onset Epilepsy Revealed New Gene Variants and Phenotypic Variability.

In Kazakhstan, there is insufficient data on genetic epilepsy, which has its own clinical and management implications. Thus, this study aimed to use whole genome sequencing to identify and evaluate genetic variants and genetic structure of early onset epilepsy in the Kazakhstani pediatric population. In this study, for the first time in Kazakhstan, whole genome sequencing was carried out among epilepsy diagnosed children. The study involved 20 pediatric patients with early onset epilepsy and no established cause of the disease during the July-December, 2021. The average age at enrolment was 34.5 months, with a mean age at seizure onset of 6 months. Six patients (30%) were male, and 7 were familial cases. We identified pathogenic and likely pathogenic variants in 14 (70%) cases, among them, 6 novel disease gene variants (KCNQ2, CASK, WWOX, MT-CO3, GRIN2D, and SLC12A5). Other genes associated with the disease were SCN1A (x2), SLC2A1, ARX, CACNA1B, PCDH19, KCNT1, and CHRNA2. Identification of the genetic causes in 70% of cases confirms the general structure of the etiology of early onset epilepsy and the necessity of using NGS in diagnostics. Moreover, the study describes new genotype-phenotypic correlations in genetic epilepsy. Despite certain limitations of the study, it can be concluded that the genetic etiology of pediatric epilepsy in Kazakhstan is very broad and requires further research.

Role of Genetic Polymorphisms in the Development of Complications in Patients with Implanted Left Ventricular Assist Devices: HeartWare, HeartMate II, and HeartMate 3.

Left ventricular assist device (LVAD) implantation is one of the mechanical circulatory support (MCS) treatments for advanced heart failure (HF) patients. MCS has emerged as a lifesaving therapy that improves patients' quality of life. However, MCS remains limited by a paradoxical coagulopathy accompanied by thrombosis and bleeding. The mechanisms of MCS thrombosis are increasingly being defined, but MCS-related bleeding, which is related to shear-mediated alteration of platelet function, remains poorly understood. Complications might develop due to the high non-physiological shear stress in the device and as a consequence of individual variability in response to the antithrombotic therapy. Thromboelastography (TEG) and genotyping of gene polymorphisms that are involved in the coagulation cascade and in the metabolism of the antithrombotic therapy might be valuable sources of information for the reduction of complication development. The aim of the study was to identify genetic factors related to the development of device complications according to the implanted LVAD type. We compared the clinical and genetic data of HF patients (n = 98) with/without complications with three types of implanted devices: HeartWare HVAD (HW), HeartMate II (HMII), and HeartMate 3 (HM3). rs9923231 in VKORC1 (95%CI -6.28-0.22, p = 0.04) and rs5918 in ITGB3 genes (95%CI 0.003-4.36, p = 0.05) showed significant association with the TEG coagulation index parameter, which identified hyper- and hypo-coagulation states. The wild genotype of rs5918 in the ITGB3 gene prevailed in patients implanted with HM3 devices, which developed fewer complications than with HMII (p = 0.04). Individual genetic information could be useful in the management of patients with HF and the implantation of MCS to reduce the development of complications.

Designing Allele-Specific Competitive-Extension PCR-Based Assays for High-Throughput Genotyping and Gene Characterization.

Polymerase chain reaction (PCR) is a simple and rapid method that can detect nucleotide polymorphisms and sequence variation in basic research applications, agriculture, and medicine. Variants of PCR, collectively known as allele-specific PCR (AS-PCR), use a competitive reaction in the presence of allele-specific primers to preferentially amplify only certain alleles. This method, originally named by its developers as Kompetitive Allele Specific PCR (KASP), is an AS-PCR variant adapted for fluorescence-based detection of amplification results. We developed a bioinformatic tool for designing probe sequences for PCR-based genotyping assays. Probe sequences are designed in both directions, and both single nucleotide polymorphisms (SNPs) and insertion-deletions (InDels) may be targeted. In addition, the tool allows discrimination of up to four-allelic variants at a single SNP site. To increase both the reaction specificity and the discriminative power of SNP genotyping, each allele-specific primer is designed such that the penultimate base before the primer's 3' end base is positioned at the SNP site. The tool allows design of custom FRET cassette reporter systems for fluorescence-based assays. FastPCR is a user-friendly and powerful Java-based software that is freely available (http://primerdigital.com/tools/). Using the FastPCR environment and the tool for designing AS-PCR provides unparalleled flexibility for developing genotyping assays and specific and sensitive diagnostic PCR-based tests, which translates into a greater likelihood of research success.

Whole-Exome Sequencing Reveals Pathogenic SIRT1 Variant in Brain Arteriovenous Malformation: A Case Report.

Arteriovenous malformations of the brain (bAVMs) are plexuses of pathological arteries and veins that lack a normal capillary system between them. Intracranial hemorrhage (hemorrhagic stroke) is the most frequent clinical manifestation of AVM, leading to lethal outcomes that are especially high among children and young people. Recently, high-throughput genome sequencing methods have made a notable contribution to the research progress in this subject. In particular, whole-exome sequencing (WES) methods allow the identification of novel mutations. However, the genetic mechanism causing AVM is still unclear. Therefore, the aim of this study was to investigate the potential genetic mechanism underlying AVM. We analyzed the WES data of blood and tissue samples of a 30-year-old Central Asian male diagnosed with AVM. We identified 54 polymorphisms in 43 genes. After in-silica overrepresentation enrichment analysis of the polymorphisms, the SIRT1 gene variant (g.67884831C>T) indicated a possible molecular mechanism of bAVM. Further studies are required to evaluate the functional impact of SIRT1 g.67884831C>T, which may warrant further replication and biological investigations related to sporadic bAVM.

Whole-Genome Sequencing and Genomic Variant Analysis of Kazakh Individuals.

Kazakhstan, the ninth-largest country in the world, is located along the Great Silk Road and connects Europe with Asia. Historically, its territory has been inhabited by nomadic tribes, and modern-day Kazakhstan is a multiethnic country with a dominant Kazakh population. We sequenced and analyzed the genomes of five ethnic Kazakhs at high coverage using the Illumina HiSeq2000 next-generation sequencing platform. The five Kazakhs yielded a total number of base pairs ranging from 87,308,581,400 to 107,526,741,301. On average, 99.06% were properly mapped. Based on the Het/Hom and Ti/Tv ratios, the quality of the genomic data ranged from 1.35 to 1.49 and from 2.07 to 2.08, respectively. Genetic variants were identified and annotated. Functional analysis of the genetic variants identified several variants that were associated with higher risks of metabolic and neurogenerative diseases. The present study showed high levels of genetic admixture of Kazakhs that were comparable to those of other Central Asians. These whole-genome sequence data of healthy Kazakhs could contribute significantly to biomedical studies of common diseases as their findings could allow better insight into the genotype-phenotype relations at the population level.

A high scale SARS-CoV-2 profiling by its whole-genome sequencing using Oxford Nanopore Technology in Kazakhstan.

Severe acute respiratory syndrome (SARS-CoV-2) is responsible for the worldwide pandemic, COVID-19. The original viral whole-genome was sequenced by a high-throughput sequencing approach from the samples obtained from Wuhan, China. Real-time gene sequencing is the main parameter to manage viral outbreaks because it expands our understanding of virus proliferation, spread, and evolution. Whole-genome sequencing is critical for SARS-CoV-2 variant surveillance, the development of new vaccines and boosters, and the representation of epidemiological situations in the country. A significant increase in the number of COVID-19 cases confirmed in August 2021 in Kazakhstan facilitated a need to establish an effective and proficient system for further study of SARS-CoV-2 genetic variants and the development of future Kazakhstan's genomic surveillance program. The SARS-CoV-2 whole-genome was sequenced according to SARS-CoV-2 ARTIC protocol (EXP-MRT001) by Oxford Nanopore Technologies at the National Laboratory Astana, Kazakhstan to track viral variants circulating in the country. The 500 samples kindly provided by the Republican Diagnostic Center (UMC-NU) and private laboratory KDL "Olymp" were collected from individuals in Nur-Sultan city diagnosed with COVID-19 from August 2021 to May 2022 using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). All samples had a cycle threshold (Ct) value below 20 with an average Ct value of 17.03. The overall average value of sequencing depth coverage for samples is 244X. 341 whole-genome sequences that passed quality control were deposited in the Global initiative on sharing all influenza data (GISAID). The BA.1.1 (n = 189), BA.1 (n = 15), BA.2 (n = 3), BA.1.15 (n = 1), BA.1.17.2 (n = 1) omicron lineages, AY.122 (n = 119), B.1.617.2 (n = 8), AY.111 (n = 2), AY.126 (n = 1), AY.4 (n = 1) delta lineages, one sample B.1.1.7 (n = 1) belongs to alpha lineage, and one sample B.1.637 (n = 1) belongs to small sublineage were detected in this study. This is the first study of SARS-CoV-2 whole-genome sequencing by the ONT approach in Kazakhstan, which can be expanded for the investigation of other emerging viral or bacterial infections on the country level.