Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics

Metagenomic approaches and opportunities in arid soil research

Arid soils present unique challenges and opportunities for studying microbial diversity and bioactive potential due to the extreme environmental conditions they bear. This review article investigates soil metagenomics as an emerging tool to explore complex microbial dynamics and unexplored bioactive potential in harsh environments. Utilizing advanced metagenomic techniques, diverse microbial populations that grow under extreme conditions such as high temperatures, salinity, high pH levels, and exposure to metals and radiation can be studied. The use of extremophiles to discover novel natural products and biocatalysts emphasizes the role of functional metagenomics in identifying enzymes and secondary metabolites for industrial and pharmaceutical purposes. Metagenomic sequencing uncovers a complex network of microbial diversity, offering significant potential for discovering new bioactive compounds. Functional metagenomics, connecting taxonomic diversity to genetic capabilities, provides a pathway to identify microbes' mechanisms to synthesize valuable secondary metabolites and other bioactive substances. Contrary to the common perception of desert soil as barren land, the metagenomic analysis reveals a rich diversity of life forms adept at extreme survival. It provides valuable findings into their resilience and potential applications in biotechnology. Moreover, the challenges associated with metagenomics in arid soils, such as low microbial biomass, high DNA degradation rates, and DNA extraction inhibitors and strategies to overcome these issues, outline the latest advancements in extraction methods, high-throughput sequencing, and bioinformatics. The importance of metagenomics for investigating diverse environments opens the way for future research to develop sustainable solutions in agriculture, industry, and medicine. Extensive studies are necessary to utilize the full potential of these powerful microbial communities. This research will significantly improve our understanding of microbial ecology and biotechnology in arid environments.

Analysis of Oral Microbiota in Elderly Thai Patients with Alzheimer's Disease and Mild Cognitive Impairment

Alzheimer's disease (AD) is a neurodegenerative disease that predominantly affects the older adult population. Neuroinflammation may be triggered by the migration of oral microbiota composition changes from the oral cavity to the brain. However, the relationship between oral microbiota composition and neurodegenerative diseases, such as AD, remains poorly understood. Therefore, we conducted a comprehensive comparison of the relative abundance and diversity of bacterial taxa present in saliva among older adults diagnosed with AD, those with mild cognitive impairment (MCI), and healthy controls. Saliva samples and clinical data were collected from 10 AD patients, 46 MCI patients, and 44 healthy older adults. AD patients had lower Clinical Dementia Rating, Montreal Cognitive Assessment, and Mini-mental Status Examination scores, and induced microbial diversity, than the MCI and control groups. Moreover, AD patients exhibited significantly higher levels of Fusobacteriota and Peptostreptococcaceae and lower levels of Veillonella than the MCI and control groups. In conclusion, a high abundance of Fusobacteria at various levels (i.e., phylum, class, family, and genus levels) may serve as a biomarker for AD. The analysis of oral microbiota dysbiosis biomarkers in older adults may be valuable for identifying individuals at risk for AD.

Crossing epigenetic frontiers: the intersection of novel histone modifications and diseases

Histone post-translational modifications (HPTMs), as one of the core mechanisms of epigenetic regulation, are garnering increasing attention due to their close association with the onset and progression of diseases and their potential as targeted therapeutic agents. Advances in high-throughput molecular tools and the abundance of bioinformatics data have led to the discovery of novel HPTMs which similarly affect gene expression, metabolism, and chromatin structure. Furthermore, a growing body of research has demonstrated that novel histone modifications also play crucial roles in the development and progression of various diseases, including various cancers, cardiovascular diseases, infectious diseases, psychiatric disorders, and reproductive system diseases. This review defines nine novel histone modifications: lactylation, citrullination, crotonylation, succinylation, SUMOylation, propionylation, butyrylation, 2-hydroxyisobutyrylation, and 2-hydroxybutyrylation. It comprehensively introduces the modification processes of these nine novel HPTMs, their roles in transcription, replication, DNA repair and recombination, metabolism, and chromatin structure, as well as their involvement in promoting the occurrence and development of various diseases and their clinical applications as therapeutic targets and potential biomarkers. Moreover, this review provides a detailed overview of novel HPTM inhibitors targeting various targets and their emerging strategies in the treatment of multiple diseases while offering insights into their future development prospects and challenges. Additionally, we briefly introduce novel epigenetic research techniques and their applications in the field of novel HPTM research.

mRNA Fragmentation Pattern Detected by SHAPE

The success of messenger RNA (mRNA) vaccines in controlling COVID-19 has warranted further developments in new technology. Currently, their quality control process largely relies on low-resolution electrophoresis for detecting chain breaks. Here, we present an approach using multi-primer reverse transcription sequencing (MPRT-seq) to identify degradation fragments in mRNA products. Using this in-house-made mRNA containing two antigens and untranslated regions (UTRs), we analyzed the mRNA completeness and degradation pattern at a nucleotide resolution. We then analyzed the sensitive base sequence and its correlation with the secondary structure. Our MPRT-seq mapping shows that certain sequences on the 5' of bulge-stem-loop structures can result in preferential chain breaks. Our results agree with commonly used capillary electrophoresis (CE) integrity analysis but at a much higher resolution, and can improve mRNA stability by providing information to remove sensitive structures or sequences in the mRNA sequence design.

An overview of recent technological developments in bovine genomics

Cattle are regarded as highly valuable animals because of their milk, beef, dung, fur, and ability to draft. The scientific community has tried a number of strategies to improve the genetic makeup of bovine germplasm. To ensure higher returns for the dairy and beef industries, researchers face their greatest challenge in improving commercially important traits. One of the biggest developments in the last few decades in the creation of instruments for cattle genetic improvement is the discovery of the genome. Breeding livestock is being revolutionized by genomic selection made possible by the availability of medium- and high-density single nucleotide polymorphism (SNP) arrays coupled with sophisticated statistical techniques. It is becoming easier to access high-dimensional genomic data in cattle. Continuously declining genotyping costs and an increase in services that use genomic data to increase return on investment have both made a significant contribution to this. The field of genomics has come a long way thanks to groundbreaking discoveries such as radiation-hybrid mapping, in situ hybridization, synteny analysis, somatic cell genetics, cytogenetic maps, molecular markers, association studies for quantitative trait loci, high-throughput SNP genotyping, whole-genome shotgun sequencing to whole-genome mapping, and genome editing. These advancements have had a significant positive impact on the field of cattle genomics. This manuscript aimed to review recent advances in genomic technologies for cattle breeding and future prospects in this field.

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data

With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devoted to those popular types such as m6A and pseudouridine. To address current limitations on studying the crucial regulator, m1A modification, we conceived this study. We have developed an integrated computational workflow designed for the detection of m1A modifications from direct RNA sequencing data. This workflow comprises a feature extractor responsible for capturing signal characteristics (such as mean, standard deviations, and length of electric signals), a single molecule-level m1A predictor trained with features extracted from the IVT dataset using classical machine learning algorithms, a confident m1A site selector employing the binomial test to identify statistically significant m1A sites, and an m1A modification rate estimator. Our model achieved accurate molecule-level prediction (Average AUC = 0.9689) and reliable m1A site detection and quantification. To show the feasibility of our workflow, we conducted a study on in vivo transcribed human HEK293 cell line, and the results were carefully annotated and compared with other techniques (i.e., Illumina sequencing-based techniques). We believed that this tool will enabling a comprehensive understanding of the m1A modification and its functional mechanisms within cells and organisms.

Infection and the microbiome in bronchiectasis

Bronchiectasis is marked by bronchial dilatation, recurrent infections and significant morbidity, underpinned by a complex interplay between microbial dysbiosis and immune dysregulation. The identification of distinct endophenotypes have refined our understanding of its pathogenesis, including its heterogeneous disease mechanisms that influence treatment and prognosis responses. Next-generation sequencing (NGS) has revolutionised the way we view airway microbiology, allowing insights into the "unculturable". Understanding the bronchiectasis microbiome through targeted amplicon sequencing and/or shotgun metagenomics has provided key information on the interplay of the microbiome and host immunity, a central feature of disease progression. The rapid increase in translational and clinical studies in bronchiectasis now provides scope for the application of precision medicine and a better understanding of the efficacy of interventions aimed at restoring microbial balance and/or modulating immune responses. Holistic integration of these insights is driving an evolving paradigm shift in our understanding of bronchiectasis, which includes the critical role of the microbiome and its unique interplay with clinical, inflammatory, immunological and metabolic factors. Here, we review the current state of infection and the microbiome in bronchiectasis and provide views on the future directions in this field.

Beef Cattle Genome Project: Advances in Genome Sequencing, Assembly, and Functional Genes Discovery

Beef is a major global source of protein, playing an essential role in the human diet. The worldwide production and consumption of beef continue to rise, reflecting a significant trend. However, despite the critical importance of beef cattle resources in agriculture, the diversity of cattle breeds faces severe challenges, with many breeds at risk of extinction. The initiation of the Beef Cattle Genome Project is crucial. By constructing a high-precision functional annotation map of their genome, it becomes possible to analyze the genetic mechanisms underlying important traits in beef cattle, laying a solid foundation for breeding more efficient and productive cattle breeds. This review details advances in genome sequencing and assembly technologies, iterative upgrades of the beef cattle reference genome, and its application in pan-genome research. Additionally, it summarizes relevant studies on the discovery of functional genes associated with key traits in beef cattle, such as growth, meat quality, reproduction, polled traits, disease resistance, and environmental adaptability. Finally, the review explores the potential of telomere-to-telomere (T2T) genome assembly, structural variations (SVs), and multi-omics techniques in future beef cattle genetic breeding. These advancements collectively offer promising avenues for enhancing beef cattle breeding and improving genetic traits.

Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Long-read sequencing for brain tumors

Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.

Bibliometric analysis of kinship analysis from 1960 to 2023: global trends and development

Kinship analysis is a crucial aspect of forensic genetics. This study analyzed 1,222 publications on kinship analysis from 1960 to 2023 using bibliometric analysis techniques, investigating the annual publication and citation patterns, most productive countries, organizations, authors and journals, most cited documents and co-occurrence of keywords. The initial publication in this field occurred in 1960. Since 2007, there has been a significant increase in publications, with over 30 published annually except for 2010. China had the most publications (n = 213, 17.43%), followed by the United States (n = 175, 14.32%) and Germany (n = 89, 7.28%). The United States also had the highest citation count. Sichuan University in China has the largest number of published articles. The University of Leipzig and the University of Cologne in Germany exhibit the highest total citation count and average citation, respectively. Budowle B was the most prolific author and Kayser M was the most cited author. In terms of publications, Forensic Science International- Genetics, Forensic Science International, and International Journal of Legal Medicine were the most prolific journals. Among them, Forensic Science International-Genetics boasted the highest h-index, citation count, and average citation rate. The most frequently cited publication was "Van Oven M, 2009, Hum Mutat", with a total of 1,361 citations. The most frequent co-occurrence keyword included "DNA", "Loci", "Paternity testing", "Population", "Markers", and "Identification", with recent interest focusing on "Kinship analysis", "SNP" and "Inference". The current research is centered around microhaplotypes, forensic genetic genealogy, and massively parallel sequencing. The field advanced with new DNA analysis methods, tools, and genetic markers. Collaborative research among nations, organizations, and authors benefits idea exchange, problem-solving efficiency, and high-quality results.

IAVCP (Influenza A Virus Consensus and Phylogeny): Automatic Identification of the Genomic Sequence of the Influenza A Virus from High-Throughput Sequencing Data

Recently, high-throughput sequencing of influenza A viruses has become a routine test. It should be noted that the extremely high diversity of the influenza A virus complicates the task of determining the sequences of all eight genome segments. For a fast and accurate analysis, it is necessary to select the most suitable reference for each segment. At the same time, there is no standardized method in the field of decoding sequencing results that allows the user to update the sequence databases to which the reads obtained by virus sequencing are compared. The IAVCP (influenza A virus consensus and phylogeny) was developed with the goal of automatically analyzing high-throughput sequencing data of influenza A viruses. Its goals include the extraction of a consensus genome directly from paired raw reads. In addition, the pipeline enables the identification of potential reassortment events in the evolutionary history of the virus of interest by analyzing the topological structure of phylogenetic trees that are automatically reconstructed.

Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals

Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene-environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals.

Can long-read sequencing tackle the barriers, which the next-generation could not? A review

The large-scale heterogeneity of genetic diseases necessitated the deeper examination of nucleotide sequence alterations enhancing the discovery of new targeted drug attack points. The appearance of new sequencing techniques was essential to get more interpretable genomic data. In contrast to the previous short-reads, longer lengths can provide a better insight into the potential health threatening genetic abnormalities. Long-reads offer more accurate variant identification and genome assembly methods, indicating advances in nucleotide deflect-related studies. In this review, we introduce the historical background of sequencing technologies and show their benefits and limits, as well. Furthermore, we highlight the differences between short- and long-read approaches, including their unique advances and difficulties in methodologies and evaluation. Additionally, we provide a detailed description of the corresponding bioinformatics and the current applications.

Comparative characterization of supragingival plaque microbiomes in malocclusion adult female patients undergoing orthodontic treatment with removable aligners or fixed appliances: a descriptive cross-sectional study

Objectives

This study aimed to explore the effects of removable aligners and fixed appliances on the supragingival bacterial communities in adult female patients undergoing orthodontic treatment.

Methods

Supragingival plaque samples from 48 female individuals underwent microbiome analysis (16S rRNA gene sequencing) using PacBio Sequel sequencing. The study included 13 adults without orthodontic treatment needs as the control group (Group C), and 35 patients with comparable initial orthodontic conditions who received treatment at a university clinic in Beijing, China. The treatment involved either traditional fixed brackets (Group B, n = 17) or Invisalign® aligners (Group AT, n = 18). Bioinformatics methods were used for data analysis.

Results

From the 48 plaque samples, a total of 334,961 valid reads were obtained, averaging 6,978 sequences per sample. The 16S rDNA sequences were classified into 25,727 amplicon sequence variants (ASVs). Significant variances in alpha and beta diversity among the groups were noted. Group B microbiome exhibited an increased presence of Gram-negative bacteria. At the phylum level, Actinobacteriota was significantly more prevalent in Group C samples, while Bacteroidota was enriched in Group B samples. Family-level relative abundance analysis showed a notable increase in Saccharibacteria (formerly TM7) and Prevotellaceae in Group B. Genus-level analysis revealed a significant rise in Lautropia in Group AT. Fixed orthodontic appliances were linked to oral microbiome changes, notably an enhanced relative abundance of anaerobes, including periodontal pathogens.

Conclusion

The observation points to the impact of orthodontic appliance on the oral microbial community, highlighting the difference between traditional braces (Group B) and clear aligners (Group AT)in terms of the predominance of anaerobic and gram negative bacteria. This emphasizes the importance of considering the microbiological effects when choosing orthodontic appliance and underscores the need for tailored oral hygiene practices for individuals undergoing these treatments. This research might provide insights that could assist in the development of innovative cleaning techniques and antibacterial materials.

The Third-Generation Sequencing Challenge: Novel Insights for the Omic Sciences

The understanding of the human genome has been greatly improved by the advent of next-generation sequencing technologies (NGS). Despite the undeniable advantages responsible for their widespread diffusion, these methods have some constraints, mainly related to short read length and the need for PCR amplification. As a consequence, long-read sequencers, called third-generation sequencing (TGS), have been developed, promising to overcome NGS. Starting from the first prototype, TGS has progressively ameliorated its chemistries by improving both read length and base-calling accuracy, as well as simultaneously reducing the costs/base. Based on these premises, TGS is showing its potential in many fields, including the analysis of difficult-to-sequence genomic regions, structural variations detection, RNA expression profiling, DNA methylation study, and metagenomic analyses. Protocol standardization and the development of easy-to-use pipelines for data analysis will enhance TGS use, also opening the way for their routine applications in diagnostic contexts.

Dominance of transposable element-related satDNAs results in great complexity of "satDNA library" and invokes the extension towards "repetitive DNA library"

Research on bivalves is fast-growing, including genome-wide analyses and genome sequencing. Several characteristics qualify oysters as a valuable model to explore repetitive DNA sequences and their genome organization. Here we characterize the satellitomes of five species in the family Ostreidae (Crassostrea angulata, C. virginica, C. hongkongensis, C. ariakensis, Ostrea edulis), revealing a substantial number of satellite DNAs (satDNAs) per genome (ranging between 33 and 61) and peculiarities in the composition of their satellitomes. Numerous satDNAs were either associated to or derived from transposable elements, displaying a scarcity of transposable element-unrelated satDNAs in these genomes. Due to the non-conventional satellitome constitution and dominance of Helitron-associated satDNAs, comparative satellitomics demanded more in-depth analyses than standardly employed. Comparative analyses (including C. gigas, the first bivalve species with a defined satellitome) revealed that 13 satDNAs occur in all six oyster genomes, with Cg170/HindIII satDNA being the most abundant in all of them. Evaluating the "satDNA library model" highlighted the necessity to adjust this term when studying tandem repeat evolution in organisms with such satellitomes. When repetitive sequences with potential variation in the organizational form and repeat-type affiliation are examined across related species, the introduction of the terms "TE library" and "repetitive DNA library" becomes essential.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-024-00218-0.

Diversity Analysis of Intestinal Bifidobacteria in the Hohhot Population

(1) Background: Bifidobacterium plays a pivotal role within the gut microbiota, significantly affecting host health through its abundance and composition in the intestine. Factors such as age, gender, and living environment exert considerable influence on the gut microbiota, yet scant attention has been directed towards understanding the specific effects of these factors on the Bifidobacterium population. Therefore, this study focused on 98 adult fecal samples to conduct absolute and relative quantitative analyses of bifidobacteria. (2) Methods: Using droplet digital PCR and the PacBio Sequel II sequencing platform, this study sought to determine the influence of various factors, including living environment, age, and BMI, on the absolute content and biodiversity of intestinal bifidobacteria. (3) Results: Quantitative results indicated that the bifidobacteria content in the intestinal tract ranged from 106 to 109 CFU/g. Notably, the number of bifidobacteria in the intestinal tract of the school population surpassed that of the off-campus population significantly (p = 0.003). Additionally, the group of young people exhibited a significantly higher count of bifidobacteria than the middle-aged and elderly groups (p = 0.041). The normal-weight group displayed a significantly higher bifidobacteria count than the obese group (p = 0.027). Further analysis of the relative abundance of bifidobacteria under different influencing factors revealed that the living environment emerged as the primary factor affecting the intestinal bifidobacteria structure (p = 0.046, R2 = 2.411). Moreover, the diversity of bifidobacteria in the intestinal tract of college students surpassed that in the out-of-school population (p = 0.034). This was characterized by a notable increase in 11 strains, including B. longum, B. bifidum, and B. pseudolongum, in the intestinal tract of college students, forming a more intricate intestinal bifidobacteria interaction network. (4) Conclusions: In summary, this study elucidated the principal factors affecting intestinal bifidobacteria and delineated their characteristics of intestinal bifidobacteria in diverse populations. By enriching the theory surrounding gut microbiota and health, this study provides essential data support for further investigations into the intricate dynamics of the gut microbiota.

Gut microbiota in relationship to diabetes mellitus and its late complications with a focus on diabetic foot syndrome: A review

Diabetes mellitus is a chronic disease affecting glucose metabolism. The pathophysiological reactions underpinning the disease can lead to the development of late diabetes complications. The gut microbiota plays important roles in weight regulation and the maintenance of a healthy digestive system. Obesity, diabetes mellitus, diabetic retinopathy, diabetic nephropathy and diabetic neuropathy are all associated with a microbial imbalance in the gut. Modern technical equipment and advanced diagnostic procedures, including xmolecular methods, are commonly used to detect both quantitative and qualitative changes in the gut microbiota. This review summarises collective knowledge on the role of the gut microbiota in both types of diabetes mellitus and their late complications, with a particular focus on diabetic foot syndrome.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Optimized MLPA workflow for spinal muscular atrophy diagnosis: identification of a novel variant, NC_000005.10:g.(70919941_70927324)del in isolated exon 1 of SMN1 gene through long-range PCR

BACKGROUND

Spinal muscular atrophy (SMA) is a rare autosomal recessive hereditary neuromuscular disease caused by survival motor neuron 1 (SMN1) gene deletion or mutation. Homozygous deletions of exon 7 in SMN1 result in 95% of SMA cases, while the remaining 5% are caused by other pathogenic variants of SMN1.

METHODS

We analyzed two SMA-suspected cases that were collected, with no SMN1 gene deletion and point mutation in whole-exome sequencing. Exon 1 deletion of the SMN gene was detected using Multiplex ligation-dependent probe amplification (MLPA) P021. We used long-range polymerase chain reaction (PCR) to isolate the SMN1 template, optimized-MLPA P021 for copy number variation (CNV) analysis within SMN1 only, and validated the findings via third-generation sequencing.

RESULTS

Two unrelated families shared a genotype with one copy of exon 7 and a novel variant, g.70919941_70927324del, in isolated exon 1 of the SMN1 gene. Case F1-II.1 demonstrated no exon 1 but retained other exons, whereas F2-II.1 had an exon 1 deletion in a single SMN1 gene. The read coverage in the third-generation sequencing results of both F1-II.1 and F2-II.1 revealed a deletion of approximately 7.3 kb in the 5' region of SMN1. The first nucleotide in the sequence data aligned to the 7385 bp of NG_008691.1.

CONCLUSION

Remarkably, two proband families demonstrated identical SMN1 exon 1 breakpoint sites, hinting at a potential novel mutation hotspot in Chinese SMA, expanding the variation spectrum of the SMN1 gene and corroborating the specificity of isolated exon 1 deletion in SMA pathogenesis. The optimized-MLPA P021 determined a novel variant (g.70919941_70927324del) in isolated exon 1 of the SMN1 gene based on long-range PCR, enabling efficient and affordable detection of SMN gene variations in patients with SMA, providing new insight into SMA diagnosis to SMN1 deficiency and an optimized workflow for single exon CNV testing of the SMN gene.

Long read sequencing on its way to the routine diagnostics of genetic diseases

The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.

Advancements in HLA Typing Techniques and Their Impact on Transplantation Medicine

HLA typing serves as a standard practice in hematopoietic stem cell transplantation to ensure compatibility between donors and recipients, preventing the occurrence of allograft rejection and graft-versus-host disease. Conventional laboratory methods that have been widely employed in the past few years, including sequence-specific primer PCR and sequencing-based typing (SBT), currently face the risk of becoming obsolete. This risk stems not only from the extensive diversity within HLA genes but also from the rapid advancement of next-generation sequencing and third-generation sequencing technologies. Third-generation sequencing systems like single-molecule real-time (SMRT) sequencing and Oxford Nanopore (ONT) sequencing have the capability to analyze long-read sequences that span entire intronic-exonic regions of HLA genes, effectively addressing challenges related to HLA ambiguity and the phasing of multiple short-read fragments. The growing dominance of these advanced sequencers in HLA typing is expected to solidify further through ongoing refinements, cost reduction, and error rate minimization. This review focuses on hematopoietic stem cell transplantation (HSCT) and explores prospective advancements and application of HLA DNA typing techniques. It explores how the adoption of third-generation sequencing technologies can revolutionize the field by offering improved accuracy, reduced ambiguity, and enhanced assessment of compatibility in HSCT. Embracing these cutting-edge technologies is essential to advancing the success rates and outcomes of hematopoietic stem cell transplantation. This review underscores the importance of staying at the forefront of HLA typing techniques to ensure the best possible outcomes for patients undergoing HSCT.

Long-read sequencing unveils novel somatic variants and methylation patterns in the genetic information system of early lung cancer

Lung cancer poses a global health challenge, necessitating advanced diagnostics for improved outcomes. Intensive efforts are ongoing to pinpoint early detection biomarkers, such as genomic variations and DNA methylation, to elevate diagnostic precision. We conducted long-read sequencing on cancerous and adjacent non-cancerous tissues from a patient with lung adenocarcinoma. We identified somatic structural variations (SVs) specific to lung cancer by integrating data from various SV calling methods and differentially methylated regions (DMRs) that were distinct between these two tissue samples, revealing a unique methylation pattern associated with lung cancer. This study discovered over 40,000 somatic SVs and over 180,000 DMRs linked to lung cancer. We identified approximately 700 genes of significant relevance through comprehensive analysis, including genes intricately associated with many lung cancers, such as NOTCH1, SMOC2, CSMD2, and others. Furthermore, we observed that somatic SVs and DMRs were substantially enriched in several pathways, such as axon guidance signaling pathways, which suggests a comprehensive multi-omics impact on lung cancer progression across various biological investigation levels. These datasets can potentially serve as biomarkers for early lung cancer detection and may hold significant value in clinical diagnosis and treatment applications.

Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration

Gastric cancer (GC) is a heterogeneous disease, often diagnosed at advanced stages, with a 5-year survival rate of approximately 20%. Despite notable technological advancements in cancer research over the past decades, their impact on GC management and outcomes has been limited. Numerous molecular alterations have been identified in GC, leading to various molecular classifications, such as those developed by The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG). Other authors have proposed alternative perspectives, including immune, proteomic, or epigenetic-based classifications. However, molecular stratification has not yet transitioned into clinical practice for GC, and little attention has been paid to alternative molecular classifications. In this review, we explore diverse molecular classifications in GC from a practical point of view, emphasizing their relationships with clinicopathological factors, prognosis, and therapeutic approaches. We have focused on classifications beyond those of TCGA and the ACRG, which have been less extensively reviewed previously. Additionally, we discuss the challenges that must be overcome to ensure their impact on patient treatment and prognosis. This review aims to serve as a practical framework to understand the molecular landscape of GC, facilitate the development of consensus molecular categories, and guide the design of innovative molecular studies in the field.

Climate Change-The Rise of Climate-Resilient Crops

Climate change disrupts food production in many regions of the world. The accompanying extreme weather events, such as droughts, floods, heat waves, and cold snaps, pose threats to crops. The concentration of carbon dioxide also increases in the atmosphere. The United Nations is implementing the climate-smart agriculture initiative to ensure food security. An element of this project involves the breeding of climate-resilient crops or plant cultivars with enhanced resistance to unfavorable environmental conditions. Modern agriculture, which is currently homogeneous, needs to diversify the species and cultivars of cultivated plants. Plant breeding programs should extensively incorporate new molecular technologies, supported by the development of field phenotyping techniques. Breeders should closely cooperate with scientists from various fields of science.

Tolerogenic Nano-/Microparticle Vaccines for Immunotherapy

Autoimmune diseases, allergies, transplant rejections, generation of antidrug antibodies, and chronic inflammatory diseases have impacted a large group of people across the globe. Conventional treatments and therapies often use systemic or broad immunosuppression with serious efficacy and safety issues. Tolerogenic vaccines represent a concept that has been extended from their traditional immune-modulating function to induction of antigen-specific tolerance through the generation of regulatory T cells. Without impairing immune homeostasis, tolerogenic vaccines dampen inflammation and induce tolerogenic regulation. However, achieving the desired potency of tolerogenic vaccines as preventive and therapeutic modalities calls for precise manipulation of the immune microenvironment and control over the tolerogenic responses against the autoantigens, allergens, and/or alloantigens. Engineered nano-/microparticles possess desirable design features that can bolster targeted immune regulation and enhance the induction of antigen-specific tolerance. Thus, particle-based tolerogenic vaccines hold great promise in clinical translation for future treatment of aforementioned immune disorders. In this review, we highlight the main strategies to employ particles as exciting tolerogenic vaccines, with a focus on the particles' role in facilitating the induction of antigen-specific tolerance. We describe the particle design features that facilitate their usage and discuss the challenges and opportunities for designing next-generation particle-based tolerogenic vaccines with robust efficacy to promote antigen-specific tolerance for immunotherapy.

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.

The Evolution, Assembly, and Dynamics of Marine Holobionts

The holobiont concept (i.e., multiple living beings in close symbiosis with one another and functioning as a unit) is revolutionizing our understanding of biology, especially in marine systems. The earliest marine holobiont was likely a syntrophic partnership of at least two prokaryotic members. Since then, symbiosis has enabled marine organisms to conquer all ocean habitats through the formation of holobionts with a wide spectrum of complexities. However, most scientific inquiries have focused on isolated organisms and their adaptations to specific environments. In this review, we attempt to illustrate why a holobiont perspective-specifically, the study of how numerous organisms form a discrete ecological unit through symbiosis-will be a more impactful strategy to advance our understanding of the ecology and evolution of marine life. We argue that this approach is instrumental in addressing the threats to marine biodiversity posed by the current global environmental crisis.

Pathogenic bacteria and fungi in bioaerosols from specialized hospitals in Shandong province, East China

Bacteria and fungi are abundant and ubiquitous in bioaerosols in hospital environments. Understanding the distribution and diversity of microbial communities within bioaerosols is critical for mitigating their detrimental effects. Our knowledge on the composition of bacteria or fungi in bioaerosols is limited, especially the potential pathogens present in fine particulate matter (PM2.5) from specialized hospitals. Thirty p.m.2.5 filter samples were collected from five hospitals (i.e., oral, dermatology, chest, eye, and general hospitals) in Shandong Province, East China. The diversity of bacteria and fungi was analyzed at the species level using single-molecule real-time sequencing of the 16 S and internal transcribed spacer 1 (ITS) ribosomal genes, respectively. Significant differences were detected across sampling sites in terms of microbial diversity and community composition in PM2.5 as well as pollution concentrations. The range of PM2.5 concentrations observed in hospital halls was higher, ranging from 39.0 to 46.2 μg/m3, compared to the wards where the concentrations ranged from 10.7 to 25.2 μg/m3. Furthermore, microbial variations in PM2.5 bioaerosols were associated with hospital type. The most dominant pathogens identified were Vibrio metschnikovii, Staphylococcus epidermidis, Staphylococcus haemolyticus, Fusarium pseudensiforme, and Aspergillus ruber. Among these, A. ruber was identified as an opportunistic fungus in a hospital setting for the first time. Nine potentially novel strains of F. pseudensiforme, showing 84.5%-92.0% ITS sequence similarity to known Fusarium isolates, were identified in PM2.5 samples from all hospitals (excluding an eye hospital). This study highlights the importance of hospital environments in shaping microbial aerosol communities. To the best of our knowledge, this is the first study to provide insights into the bacterial and fungal biodiversity of PM2.5 in specialized hospitals, enriching research in healthcare environmental microbiology and carrying significant public health implications.

Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPSeq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPSeq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

Application of functional genomics for domestication of novel non-model microbes

With the expansion of domesticated microbes producing biomaterials and chemicals to support a growing circular bioeconomy, the variety of waste and sustainable substrates that can support microbial growth and production will also continue to expand. The diversity of these microbes also requires a range of compatible genetic tools to engineer improved robustness and economic viability. As we still do not fully understand the function of many genes in even highly studied model microbes, engineering improved microbial performance requires introducing genome-scale genetic modifications followed by screening or selecting mutants that enhance growth under prohibitive conditions encountered during production. These approaches include adaptive laboratory evolution, random or directed mutagenesis, transposon-mediated gene disruption, or CRISPR interference (CRISPRi). Although any of these approaches may be applicable for identifying engineering targets, here we focus on using CRISPRi to reduce the time required to engineer more robust microbes for industrial applications.

ONE-SENTENCE SUMMARY

The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

Direct Determination of the Structure of Single Biopolymer Molecules Using Nanopore Sequencing

This review highlights operational principles, features, and modern aspects of the development of third-generation sequencing technology of biopolymers focusing on the nucleic acids analysis, namely the nanopore sequencing system. Basics of the method and technical solutions used for its realization are considered, from the first works showing the possibility of creation of these systems to the easy-to-handle procedure developed by Oxford Nanopore Technologies company. Moreover, this review focuses on applications, which were developed and realized using equipment developed by the Oxford Nanopore Technologies, including assembly of whole genomes, methagenomics, direct analysis of the presence of modified bases.

The undiscovered biosynthetic potential of the Greenland Ice Sheet microbiome

The Greenland Ice Sheet is a biome which is mainly microbially driven. Several different niches can be found within the glacial biome for those microbes able to withstand the harsh conditions, e.g., low temperatures, low nutrient conditions, high UV radiation in summer, and contrasting long and dark winters. Eukaryotic algae can form blooms during the summer on the ice surface, interacting with communities of bacteria, fungi, and viruses. Cryoconite holes and snow are also habitats with their own microbial community. Nevertheless, the microbiome of supraglacial habitats remains poorly studied, leading to a lack of representative genomes from these environments. Under-investigated extremophiles, like those living on the Greenland Ice Sheet, may provide an untapped reservoir of chemical diversity that is yet to be discovered. In this study, an inventory of the biosynthetic potential of these organisms is made, through cataloging the presence of biosynthetic gene clusters in their genomes. There were 133 high-quality metagenome-assembled genomes (MAGs) and 28 whole genomes of bacteria obtained from samples of the ice sheet surface, cryoconite, biofilm, and snow using culturing-dependent and -independent approaches. AntiSMASH and BiG-SCAPE were used to mine these genomes and subsequently analyze the resulting predicted gene clusters. Extensive sets of predicted Biosynthetic Gene Clusters (BGCs) were collected from the genome collection, with limited overlap between isolates and MAGs. Additionally, little overlap was found in the biosynthetic potential among different environments, suggesting specialization of organisms in specific habitats. The median number of BGCs per genome was significantly higher for the isolates compared to the MAGs. The most talented producers were found among Proteobacteria. We found evidence for the capacity of these microbes to produce antimicrobials, carotenoid pigments, siderophores, and osmoprotectants, indicating potential survival mechanisms to cope with extreme conditions. The majority of identified BGCs, including those in the most prevalent gene cluster families, have unknown functions, presenting a substantial potential for bioprospecting. This study underscores the diverse biosynthetic potential in Greenland Ice Sheet genomes, revealing insights into survival strategies and highlighting the need for further exploration and characterization of these untapped resources.

Unraveling the Concealed Transcriptomic Landscape of PTEN in Human Malignancies

Background

Phosphatase and tensin homolog, widely known as PTEN, is a major negative regulator of the PI3K/AKT/mTOR signaling pathway, involved in the regulation of a variety of important cellular processes, including cell proliferation, growth, survival, and metabolism. Since most of the molecules involved in this biological pathway have been described as key regulators in cancer, the study of the corresponding genes at several levels is crucial.

Objective

Although previous studies have elucidated the physiological role of PTEN under normal conditions and its involvement in carcinogenesis and cancer progression, the transcriptional profile of PTEN has been poorly investigated.

Methods

In this study, instead of conducting the "gold-standard" direct RNA sequencing that fails to detect less abundant novel mRNAs due to the decreased sequencing depth, we designed and implemented a multiplexed PTEN-targeted sequencing approach that combined both short- and long-read sequencing.

Results

Our study has highlighted a broad spectrum of previously unknown PTEN mRNA transcripts and assessed their expression patterns in a wide range of human cancer and non-cancer cell lines, shedding light on the involvement of PTEN in cell cycle dysregulation and thus tumor development.

Conclusion

The identification of the described novel PTEN splice variants could have significant implications for understanding PTEN regulation and function, and provide new insights into PTEN biology, opening new avenues for monitoring PTEN-related diseases, including cancer.

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.

Application of long read sequencing in rare diseases: The longer, the better?

Rare diseases encompass a diverse group of genetic disorders that affect a small proportion of the population. Identifying the underlying genetic causes of these conditions presents significant challenges due to their genetic heterogeneity and complexity. Conventional short-read sequencing (SRS) techniques have been widely used in diagnosing and investigating of rare diseases, with limitations due to the nature of short-read lengths. In recent years, long read sequencing (LRS) technologies have emerged as a valuable tool in overcoming these limitations. This minireview provides a concise overview of the applications of LRS in rare disease research and diagnosis, including the identification of disease-causing tandem repeat expansions, structural variations, and comprehensive analysis of pathogenic variants with LRS.

Bioherbicidal potential of Bacillus altitudinis D30202 on Avena fatua L.: a whole-genome sequencing analysis

Avena fatua L. (wild oat) is one of the most harmful gramineous weeds that can affect the yield and quality of infiltrating crops. Bacillus altitudinis D30202 exhibits an excellent biocontrol activity against wild oat. To elucidate the biocontrol mechanisms of B. altitudinis D30202, the genome structure of this strain was assessed via whole-genome sequencing analysis. We predicted and analyzed secondary metabolite synthesis gene clusters to elucidate the mechanisms underlying the biocontrol of weeds. The whole-genome sequencing data indicated that B. altitudinis D30202 had the genome size and GC content of 3,777,154 bp and 41.32%, respectively, and 3809 coding genes were identified. Moreover, this strain could generate several compounds with bioherbicidal activity, including 4-hydroxy-3-methoxycinnamic acid and two indole derivatives. Bioinformatics prediction and comparative genomic analysis revealed that the strain had 6 secondary metabolite gene clusters. Furthermore, the taxonomic position of B. altitudinis D30202 was assessed, confirming its uniqueness and novelty within the Bacillus genus. Comparative genomic analysis showed differences in gene distribution, suggesting potential adaptations to different environments. In conclusion, B. altitudinis D30202 possesses a genome with unique characteristics, encoding enzymes and pathways related to herbicidal potential and biocontrol. This study provides a reference basis for understanding the molecular mechanisms of weed inhibition.

Multiomics tools for improved atherosclerotic cardiovascular disease management

Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.

Whole genome sequencing in the palm of your hand: how to implement a MinION Galaxy-based workflow in a food safety laboratory for rapid Salmonella spp. serotyping, virulence, and antimicrobial resistance gene identification

Introduction

Whole Genome Sequencing (WGS) implementation in food safety laboratories is a significant advancement in food pathogen control and outbreak tracking. However, the initial investment for acquiring next-generation sequencing platforms and the need for bioinformatic skills represented an obstacle for the widespread use of WGS. Long-reading technologies, such as the one developed by Oxford Nanopore Technologies, can be easily implemented with a minor initial investment and with simple protocols that can be performed with basic laboratory equipment.

Methods

Herein, we report a simple MinION Galaxy-based workflow with analysis parameters that allow its implementation in food safety laboratories with limited computer resources and without previous knowledge in bioinformatics for rapid Salmonella serotyping, virulence, and identification of antimicrobial resistance genes. For that purpose, the single use Flongle flow cells, along with the MinION Mk1B for WGS, and the community-driven web-based analysis platform Galaxy for bioinformatic analysis was used. Three strains belonging to three different serotypes, monophasic S. Typhimurium, S. Grancanaria, and S. Senftenberg, were sequenced.

Results

After 24 h of sequencing, enough coverage was achieved in order to perform de novo assembly in all three strains. After evaluating different tools, Flye de novo assemblies with medaka polishing were shown to be optimal for in silico Salmonella spp. serotyping with SISRT tool followed by antimicrobial and virulence gene identification with ABRicate.

Discussion

The implementation of the present workflow in food safety laboratories with limited computer resources allows a rapid characterization of Salmonella spp. isolates.

Discovery and Comprehensive Characterization of Novel Circular RNAs of the Apoptosis-Related BOK Gene in Human Ovarian and Prostate Cancer Cells, Using Nanopore Sequencing

CircRNAs have become a novel scientific research hotspot, and an increasing number of studies have shed light on their involvement in malignant progression. Prompted by the apparent scientific gap in circRNAs from apoptosis-related genes, such as BOK, we focused on the identification of novel BOK circRNAs in human ovarian and prostate cancer cells. Total RNA was extracted from ovarian and prostate cancer cell lines and reversely transcribed using random hexamer primers. A series of PCR assays utilizing gene-specific divergent primers were carried out. Next, third-generation sequencing based on nanopore technology followed by extensive bioinformatics analysis led to the discovery of 23 novel circRNAs. These novel circRNAs consist of both exonic and intronic regions of the BOK gene. Interestingly, the exons that form the back-splice junction were truncated in most circRNAs, and multiple back-splice sites were found for each BOK exon. Moreover, several BOK circRNAs are predicted to sponge microRNAs with a key role in reproductive cancers, while the presence of putative open reading frames indicates their translational potential. Overall, this study suggests that distinct alternative splicing events lead to the production of novel BOK circRNAs, which could come into play in the molecular landscape and clinical investigation of ovarian and prostate cancer.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

A practical approach to genome assembly and annotation of Basidiomycota using the example of Armillaria

Technological advancements in genome sequencing, assembly and annotation platforms and algorithms that resulted in several genomic studies have created an opportunity to further our understanding of the biology of phytopathogens, including Armillaria species. Most Armillaria species are facultative necrotrophs that cause root- and stem-rot, usually on woody plants, significantly impacting agriculture and forestry worldwide. Genome sequencing, assembly and annotation in terms of samples used and methods applied in Armillaria genome projects are evaluated in this review. Infographic guidelines and a database of resources to facilitate future Armillaria genome projects were developed. Knowledge gained from genomic studies of Armillaria species is summarized and prospects for further research are provided. This guide can be applied to other diploid and dikaryotic fungal genomics.

Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Nanopore Sequencing of RAGE Gene Polymorphisms and Their Association with Type 2 Diabetes

The receptor for advanced glycation end products (RAGE) is a transmembrane protein that interacts with its ligands, advanced glycation end products (AGEs). AGEs are elevated in diabetes and diabetic complications, leading to increased oxidative stress and activation of pro-inflammatory pathways facilitated by AGE-RAGE signaling. Polymorphisms in the RAGE gene can potentially affect AGE-RAGE interaction and its downstream signaling, which plays a crucial role in the progression of diabetes and its complications. In this study, we used nanopore sequencing for genotyping of RAGE polymorphism and identified a maximum number of 33 polymorphisms, including two previously unreported novel mutations in a cohort of healthy, type 2 diabetics without nephropathy and type 2 diabetics with nephropathy in order to identify associations. Two novel RAGE polymorphisms in the intron 8 and 3'UTR region at genomic locations 32181834 and 32181132, respectively, were detected with a low frequency. For four previously reported polymorphisms, cross-validation by PCR-RFLP showed 99.75% concordance with nanopore sequencing. Analysis of genotype distribution and allele frequencies revealed that five single nucleotide polymorphisms, i.e., rs1800625, rs3131300, rs3134940, rs2070600, and rs9391855, were associated with an increased risk for type 2 diabetes.

Exploring biomarkers of premature ovarian insufficiency based on oxford nanopore transcriptional profile and machine learning

Premature ovarian insufficiency (POI) is a reproductive endocrine disorder characterized by infertility and perimenopausal syndrome, with a highly heterogeneous genetic etiology and its mechanism is not fully understood. Therefore, we utilized Oxford Nanopore Technology (ONT) for the first time to characterize the full-length transcript profile, and revealed biomarkers, pathway and molecular mechanisms for POI by bioinformatics analysis and machine learning. Ultimately, we identified 272 differentially expressed genes, 858 core genes, and 25 hub genes by analysis of differential expression, gene set enrichment, and protein-protein interactions. Seven candidate genes were identified based on the intersection features of the random forest and Boruta algorithm. qRT-PCR results indicated that COX5A, UQCRFS1, LCK, RPS2 and EIF5A exhibited consistent expression trends with sequencing data and have potential as biomarkers. Additionally, GSEA analysis revealed that the pathophysiology of POI is closely associated with inhibition of the PI3K-AKT pathway, oxidative phosphorylation and DNA damage repair, as well as activation of inflammatory and apoptotic pathways. Furthermore, we emphasize that downregulation of respiratory chain enzyme complex subunits and inhibition of oxidative phosphorylation pathways play crucial roles in the pathophysiology of POI. In conclusion, our utilization of long-read sequencing has refined the annotation information within the POI transcriptional profile. This valuable data provides novel insights for further exploration into molecular regulatory networks and potential biomarkers associated with POI.

Application of Nanopore Sequencing for High Throughput Genotyping in Horses

Nanopore sequencing is a third-generation biopolymer sequencing technique that relies on monitoring the changes in an electrical current that occur as nucleic acids are passed through a protein nanopore. Increasing quality of reads generated by nanopore sequencing systems encourages their application in genome-wide polymorphism detection and genotyping. In this study, we employed nanopore sequencing to identify genome-wide polymorphisms in the horse genome. To reduce the size and complexity of genome fragments for sequencing in a simple and cost-efficient manner, we amplified random DNA fragments using a modified DOP-PCR and sequenced the resulting products using the MinION system. After initial filtering, this generated 28,426 polymorphisms, which were validated at a 3% error rate. Upon further filtering for polymorphism and reproducibility, we identified 9495 SNPs that reflected the horse population structure. To conclude, the use of nanopore sequencing, in conjunction with a genome enrichment step, is a promising tool that can be practical in a variety of applications, including genotyping, population genomics, association studies, linkage mapping, and potentially genomic selection.

Nanopore sequencing technology for clinical diagnosis of infectious diseases where laboratory capacity is meager: A case report

In resource-limited settings, patients are often first presented to clinical settings when seriously ill and access to proper clinical microbial diagnostics is often very limited or non-existing. On February 16th, 2022 we were on a field trip to test a completely field-deployable metagenomics sequencing set-up, that includes DNA purification, sequencing, and bioinformatics analyses using bioinformatics tools installed on a laptop for water samples, just outside Moshi, Tanzania. On our way to the test site, we were contacted by the nearby Machame hospital regarding a child seriously ill with diarrhea and not responding to treatment. Within the same day, we conducted an onsite metagenomics examination of a fecal sample from the child, and Campylobacter jejuni was identified as the causative agent. The treatment was subsequently changed, with almost immediate improvement, and the child was discharged on February 21st.