Digital repository of Slovenian research organisations

Search the repository
A+ | A- | Help | SLO | ENG

Query: search in
search in
search in
search in

Options:
  Reset


Query: "keywords" (NGS) .

1 - 6 / 6
First pagePrevious page1Next pageLast page
1.
Bioinformatic challenges in metagenomic next generation sequencing data analysis while unravelling a case of uncommon campylobacteriosis
Rok Kogoj, Martin Bosilj, Andraž Celar Šturm, Miša Korva, Katja Strašek Smrdel, Eva Kvas, Mateja Pirš, Lidija Lepen, Tina Triglav, 2025, original scientific article

Abstract: Objective: This study aimed to employ advanced bioinformatics and modern sequencing approaches to solve a diagnostic problem of persistent Campylobacter spp. molecular detection yet negative culture results from four consecutive stool samples of a previously healthy patient with newly diagnosed selective IgA deficiency and prolonged diarrhoea. Methods: Metagenomic next-generation sequencing (mNGS) based on short-paired end reads with basic bioinformatic read classification analysis was used at first. Due to ambiguous results, advanced bioinformatics involving contigs construction and classification, reference genome mappings and reads filtering with BBSplit, additionally coupled with metagenomic long-reads sequencing and Full-length 16S rRNA metabarcoding were employed to further elucidate the results. Virulence factors were analysed using the Prokka Genome Annotation tool. Modified classical bacteriology methods were finally used for further clarification. Results: Short-pair end reads analysis identified several Campylobacter species in all four samples. After advanced bioinformatic approaches were applied, candidatus C. infans was suspected as the putative pathogen. This result was further supported by metagenomic long-reads sequencing and Full-length 16S rRNA metabarcoding. Nevertheless, after modifying the culture conditions based on mNGS results, a mixed culture of candidatus C. infans and C.ureolyticus was obtained. Sequencing of the mixed culture resulted in an 87.48% and 73.47% genome coverage of candidatus C. infans and C. ureolyticus, respectively. In the candidatus C. infans genome more virulence factors hits were found than in the C. ureolyticus genome thus supporting the first as the most probable cause of symptoms. Conclusion: This study shows the pivotal role and strengths of mNGS in unravelling an unusual case of diarrhoea and demonstrates how mNGS can guide established microbiological methods to improve on current limitations. However, it also emphasises the need for careful interpretation of sequencing data, particularly for closely related bacterial species from clinical samples that are known to support complex microbial communities.
Keywords: 16S rRNA metabarcoding, bioinformatics, campylobacter, metagenomics, NGS
Published in DiRROS: 15.04.2026; Views: 111; Downloads: 93
.pdf Full text (563,47 KB)
This document has many files! More...

2.
Unraveling the complexity of skeletal dysplasias in the national health system
Dorra Najjar, Aleš Maver, Ana Marija Peterlin, Helena Jaklič, Borut Peterlin, 2025, original scientific article

Abstract: Introduction: Skeletal dysplasia (SD) is a large and heterogeneous group of rare genetic disorders that affects bone and cartilage growth. These disorders are diagnosed based on radiographic, clinical, and molecular criteria. However, the diagnostics is challenging due to clinical and genetic heterogeneity. We present the experience of systematic use of comprehensive genetic testing in the national health system and the molecular epidemiology of SD in Slovenia. Methods: We retrospectively reviewed 470 patients with clinical features of SD, including prenatal, childhood, and adult patients referred for diagnostic genetic evaluation to the national genetic reference center over ten years. In 262 patients, whole exome or whole genome sequencing was performed, while direct gene sequencing was performed in 208 patients with a specific clinical diagnosis. Results: A definitive genetic diagnosis using NGS was achieved in 50% (n=131) of patients. Among the positive cases, 49.61% initially presented with a nonspecific diagnosis of SD, and genetic testing contributed to establishing the diagnosis. Moreover, we demonstrated high genetic heterogeneity in our SD cohort with 66 distinct causative genes, resulting in different types of SD. In detail, we detected 132 causative variants, of which 29 were novel, which expanded the mutational spectrum of SD. Furthermore, pathogenic copy number variants (CNVs) were identified in 4.55% of the total number of variants, highlighting the importance of CNV analysis in expanding the yield of molecular diagnosis of SD. Conclusion: With the systematic use of WES and WGS, we have significantly improved the diagnostic yield of SD in the national health system and access to genetic testing. Moreover, we found significant genetic heterogeneity, and we report the genetic epidemiology of SD in the Slovenian population.
Keywords: CNV, copy number variants, NGS, next-generation sequencing, diagnostic yield, molecular pathology, prenatal diagnosis, rare genetic diseases, skeletal dysplasia
Published in DiRROS: 10.11.2025; Views: 531; Downloads: 262
.pdf Full text (1,11 MB)
This document has many files! More...

3.
Graph Convolutional Networks for Predicting Cancer Outcomes and Stage : a focus on cGAS-STING pathway activation
Mateo Sokač, Borna Skračić, Danijel Kučak, Leo Mršić, 2024, original scientific article

Abstract: The study presented in this paper evaluated gene expression profiles from The Cancer Genome Atlas (TCGA). To reduce complexity, we focused on genes in the cGAS–STING pathway, crucial for cytosolic DNA detection and immune response. The study analyzes three clinical variables: disease-specific survival (DSS), overall survival (OS), and tumor stage. To effectively utilize the high-dimensional gene expression data, we needed to find a way to project these data meaningfully. Since gene pathways can be represented as graphs, a novel method of presenting genomics data using graph data structure was employed, rather than the conventional tabular format. To leverage the gene expression data represented as graphs, we utilized a graph convolutional network (GCN) machine learning model in conjunction with the genetic algorithm optimization technique. This allowed for obtaining an optimal graph representation topology and capturing important activations within the pathway for each use case, enabling a more insightful analysis of the cGAS–STING pathway and its activations across different cancer types and clinical variables. To tackle the problem of unexplainable AI, graph visualization alongside the integrated gradients method was employed to explain the GCN model’s decision-making process, identifying key nodes (genes) in the cGAS–STING pathway. This approach revealed distinct molecular mechanisms, enhancing interpretability. This study demonstrates the potential of GCNs combined with explainable AI to analyze gene expression, providing insights into cancer progression. Further research with more data is needed to validate these findings.
Keywords: cGAS–STING, graph-convolutional-network, graphs, cancer, pan-cancer, machine learning, NGS
Published in DiRROS: 09.09.2025; Views: 634; Downloads: 341
.pdf Full text (2,05 MB)
This document has many files! More...

4.
A native insect on a non-native plant : the phylogeography of the Leafminer Phyllonorycter populifoliella (Lepidoptera: Gracillariidae) attacking the North American Balsam Poplar in North Asia
Natalia I. Kirichenko, Maria A. Ryazanova, Evgeny Akulov, Svetlana V. Baryshnikova, Anton A. Efremenko, Konstantin V. Krutovsky, Victor Ya. Kuzevanov, Andrei V. Selikhovkin, Pathour R. Shashank, Sergey Yu. Sinev, 2025, original scientific article

Abstract: The trans-Palearctic moth Phyllonorycter populifoliella (Lepidoptera: Gracillariidae) is a major pest of the North American Populus balsamifera and its hybrids widely planted as ornamentals in North Asia (i.e., the Asian part of Russia). We DNA barcoded Ph. populifoliella from distant geographical populations in Russia and analyzed them together with the data from eight European countries and India to estimate intraspecific variability and the haplotype richness in the Palearctic, and specifically in North Asia. Furthermore, using next-generation sequencing (NGS, Sequel platform, PacBio), we investigated larval and pupal remnants found in an old herbarium from the Nearctic, where P. balsamifera occurs naturally, to verify if any events of the moth introduction to this biogeographic zone happened in the past. Relatively high intraspecific variability in the COI gene of mtDNA, reaching 3.73%, was recorded in Ph. populifoliella. Overall, 30 COI haplotypes were defined in 83 specimens from the Palearctic, with a noticeable richness in North Asia (21 haplotypes). Using NGS, the remnants of 14 Phyllonorycter specimens dissected from up to 174-year-old herbaria from the Palearctic and Nearctic were sequenced, and four moth species were identified. Among them, there were three Palearctic species, Ph. populifoliella, Ph. pastorella (Zeller), and Ph. apparella (Herrich-Schäffer), and one Nearctic, Ph. nipigon (Freeman). No evidence of Ph. populifoliella introduction to North America was documented based on the examination of the herbarium dated 1850–1974. Three specimens of Ph. populifoliella identified from herbaria from Austria and Poland (dated 1879–1931) represented one haplotype (H7) known from the recent time. Overall, our study clarifies the modern range, provides insights into phylogeography, and defines the haplotype richness of the native leafminer outbreaking on the alien host. Furthermore, it underlines the use of old herbaria to explore the historical distribution of endophagous insect species.
Keywords: leafmining moth, alien host plant, DNA barcoding, NGS, intraspecific genetic variability, haplotypes, old herbaria, Asian part of Russia, Palearctic, Nearctic
Published in DiRROS: 18.02.2025; Views: 926; Downloads: 600
.pdf Full text (12,29 MB)
This document has many files! More...

5.
A framework for the evaluation of biosecurity, commercial, regulatory, and scientific impacts of plant viruses and viroids identified by NGS technologies
Sébastien Massart, Thierry Candresse, José Gil, Christophe Lacomme, Lukas Predajna, Maja Ravnikar, Jean-Sébastien Reynard, Artemis Rumbou, Pasquale Saldarelli, Dijana Škorić, Eeva J. Vainio, Jari P. T. Valkonen, Hervé Vanderschuren, Christina Varveri, Thierry Wetzel, 2017, original scientific article

Abstract: Recent advances in high-throughput sequencing technologies and bioinformatics have generated huge new opportunities for discovering and diagnosing plant viruses and viroids. Plant virology has undoubtedly benefited from these new methodologies, but at the same time, faces now substantial bottlenecks, namely the biological characterization of the newly discovered viruses and the analysis of their impact at the biosecurity, commercial, regulatory, and scientific levels. This paper proposes a scaled and progressive scientific framework for efficient biological characterization and risk assessment when a previously known or a new plant virus is detected by next generation sequencing (NGS) technologies. Four case studies are also presented to illustrate the need for such a framework, and to discuss the scenarios.
Keywords: NGS, pest risk analysis, virus diseases, biological characterization, plant health, regulatory agencies
Published in DiRROS: 25.07.2024; Views: 1235; Downloads: 758
.pdf Full text (760,13 KB)
This document has many files! More...

6.
Extreme environments simplify reassembly of communities of arbuscular mycorrhizal fungi
Nataša Šibanc, Dave R. Clark, Thorunn Helgason, Alex J. Dumbrell, Irena Maček, 2024, original scientific article

Abstract: The ecological impacts of long-term (press) disturbance on mechanisms regulating the relative abundance (i.e., commonness or rarity) and temporal dynamics of species within a community remain largely unknown. This is particularly true for the functionally important arbuscular mycorrhizal (AM) fungi; obligate plant-root endosymbionts that colonize more than two-thirds of terrestrial plant species. Here, we use high-resolution amplicon sequencing to examine how AM fungal communities in a specific extreme ecosystem—mofettes or natural CO2 springs caused by geological CO2 exhalations—are affected by long-term stress. We found that in mofettes, specific and temporally stable communities form as a subset of the local metacommunity. These communities are less diverse and dominated by adapted, “stress tolerant” taxa. Those taxa are rare in control locations and more benign environments worldwide, but show a stable temporal pattern in the extreme sites, consistently dominating the communities in grassland mofettes. This pattern of lower diversity and high dominance of specific taxa has been confirmed as relatively stable over several sampling years and is independently observed across multiple geographic locations (mofettes in different countries). This study implies that the response of soil microbial community composition to long-term stress is relatively predictable, which can also reflect the community response to other anthropogenic stressors (e.g., heavy metal pollution or land use change). Moreover, as AM fungi are functionally differentiated, with different taxa providing different benefits to host plants, changes in community structure in response to long-term environmental change have the potential to impact terrestrial plant communities and their productivity
Keywords: arbuscular mycorrhiza, elevated CO2, long-term experiments, soil biodiversity, soil hypoxia, next-generation sequencing, NGS
Published in DiRROS: 28.02.2024; Views: 1591; Downloads: 1030
.pdf Full text (1,45 MB)
This document has many files! More...

Search done in 0.31 sec.
Back to top