Next-generation sequencing technologies: An overview

A survey of k-mer methods and applications in bioinformatics

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer

Colorectal cancer (CRC) is the third most diagnosed cancer and the second deadliest cancer worldwide representing a major public health problem. In recent years, increasing evidence has shown that microRNA (miRNA) can control the expression of targeted human messenger RNA (mRNA) by reducing their abundance or translation, acting as oncogenes or tumor suppressors in various cancers, including CRC. Due to the significant up-regulation of oncogenic miRNAs in CRC, elucidating the underlying mechanism and identifying dysregulated miRNA targets may provide a basis for improving current therapeutic interventions. In this paper, we proposed Gra-CRC-miRTar, a pre-trained nucleotide-to-graph neural network framework, for identifying potential miRNA targets in CRC. Different from previous studies, we constructed two pre-trained models to encode RNA sequences and transformed them into de Bruijn graphs. We employed different graph neural networks to learn the latent representations. The embeddings generated from de Bruijn graphs were then fed into a Multilayer Perceptron (MLP) to perform the prediction tasks. Our extensive experiments show that Gra-CRC-miRTar achieves better performance than other deep learning algorithms and existing predictors. In addition, our analyses also successfully revealed 172 out of 201 functional interactions through experimentally validated miRNA-mRNA pairs in CRC. Collectively, our effort provides an accurate and efficient framework to identify potential miRNA targets in CRC, which can also be used to reveal miRNA target interactions in other malignancies, facilitating the development of novel therapeutics. The Gra-CRC-miRTar web server can be found at: http://gra-crc-mirtar.com/.

Lipid nanoparticle technology-mediated therapeutic gene manipulation in the eyes

Millions of people worldwide have hereditary genetic disorders, trauma, infectious diseases, or cancer of the eyes, and many of these eye diseases lead to irreversible blindness, which is a major public health burden. The eye is a relatively small and immune-privileged organ. The use of nucleic acid-based drugs to manipulate malfunctioning genes that target the root of ocular diseases is regarded as a therapeutic approach with great promise. However, there are still some challenges for utilizing nucleic acid therapeutics in vivo because of certain unfavorable characteristics, such as instability, biological carrier-dependent cellular uptake, short pharmacokinetic profiles in vivo (RNA), and on-target and off-target side effects (DNA). The development of lipid nanoparticles (LNPs) as gene vehicles is revolutionary progress that has contributed the clinical application of nucleic acid therapeutics. LNPs have the capability to entrap and transport various genetic materials such as small interfering RNA, mRNA, DNA, and gene editing complexes. This opens up avenues for addressing ocular diseases through the suppression of pathogenic genes, the expression of therapeutic proteins, or the correction of genetic defects. Here, we delve into the cutting-edge LNP technology for ocular gene therapy, encompassing formulation designs, preclinical development, and clinical translation.

Adapted molecular methods to unravel the recalcitrant mycorrhizal associations of Aucoumea klaineana Pierre

Understanding the role of root microbiota is crucial in sustainable forest management but remains challenging, especially for tropical trees. We developed an efficient and low-toxicity method to extract and amplify the fungal DNA associated with Aucoumea klaineana Pierre fine roots. To improve DNA quality, we optimized a commercial extraction kit by incorporating activated charcoal and modifying incubation periods. This enhanced protocol, combined with bovine serum albumin during PCR, effectively mitigated inhibitors present in A. klaineana tree root samples. This approach opens new perspectives for studying the microbiota of tropical trees.

Sustainability implications and relevance of using omics sciences to investigate cheeses with protected designation of origin

Cheese, a fundamental component of the human diet and a cornerstone of the global food economy, has a significance beyond its role as a commodity, playing a crucial part in the cultural identity of various communities. The intricate natural aging process known as maturation involves a series of reactions that induce changes in the cheese's physical, biochemical, microbiological, and particularly sensory characteristics, making it a complex aspect of cheese production. Recently, the adoption of omics sciences (e.g., metagenomics, metabolomics, proteomics) has emerged as a new trend in studies related to protected designation of origin (PDO) cheese. This mini-summary aims to outline the relationship between omics studies in these food matrices and all the sustainability facets of the production chain in general, and to discuss and recognize that the importance of these studies goes beyond comprehending the cheese biome and extends to fostering and ensuring the sustainability of the production chain. In this context, numerous studies in recent years have linked the identification of intrinsic characteristics of PDO cheeses through omics sciences to crucial sustainability themes such as territoriality, biodiversity, and the preservation of product authenticity. The trajectory suggests that, increasingly, multidisciplinary studies spanning various omics sciences will not only contribute to the characterization of these products but will also address sustainability aspects directly related to the production chain (e.g., authenticity, microbial biodiversity, functionality). This expansion underscores the multidisciplinary nature of these studies, broadening their social impact beyond the academic realm. Consequently, these pivotal studies play a crucial role in advancing discussions on PDO products and sustainability. © 2024 Society of Chemical Industry.

A comprehensive adsorption and desorption study on the interaction of DNA oligonucleotides with TiO2 nanolayers

The utilization of TiO2 nanolayers that possess excellent biocompatibility and physical properties in DNA sensing and sequencing remains largely to be explored. To examine their applicability in gene sequencing, a comprehensive study on the interaction of DNA oligonucleotides with TiO2 nanolayers was performed through adsorption and desorption experiments. TiO2 nanolayers with 10 nm thickness were fabricated via magnetron sputtering onto a 6-inch silicon wafer. A simple chip block method, validated via quartz crystal microbalance experiments with dissipation monitoring (QCM-D), was proposed to study the adsorption behaviors and interaction mechanisms under a variety of critical influencing factors, including DNA concentration, length, and type, adsorption time, pH, and metal ions. It is determined that the adsorption takes 2 h to reach saturation in the MES solution and the adsorption capacity is significantly enhanced by lowering the pH due to the isoelectric point being pH = 6 for TiO2. The adsorption percentages of nucleobases are largely similar in the MES solution while following 5T = 5G > 5C > 5A in HEPES buffer for an adsorption duration of 2.5 h. Through pre-adsorption experiments, it is deduced that DNA oligonucleotides are horizontally adsorbed on the nanolayer. This further demonstrates that mono-, di-, and tri-valent metal ions promote the adsorption, whereas Zn2+ has strong adsorption by inducing DNA condensation. Based on the desorption experiments, it is revealed that electrostatic force dominates the adsorption over van der Waals force and hydrogen bonds. The phosphate group is the main functional group for adsorption, and the adsorption strength increases with the length of the oligonucleotide. This study provides comprehensive data on the adsorption of DNA oligonucleotides onto TiO2 nanolayers and clarifies the interaction mechanisms therein, which will be valuable for applications of TiO2 in DNA-related applications.

Chromosome-contiguous genome for the Haecon-5 strain of Haemonchus contortus reveals marked genetic variability and enables the discovery of essential gene candidates

Millions of livestock animals worldwide are infected with the haematophagous barber's pole worm, Haemonchus contortus, the aetiological agent of haemonchosis. Despite the major significance of this parasite worldwide and its widespread resistance to current treatments, the lack of a high-quality genome for the well-defined strain of this parasite from Australia, called Haecon-5, has constrained research in a number of areas including host-parasite interactions, drug discovery and population genetics. To enable research in these areas, we report here a chromosome-contiguous genome (∼280 Mb) for Haecon-5 with high-quality models for 19,234 protein-coding genes. Comparative genomic analyses show significant genomic similarity (synteny) with a UK strain of H. contortus, called MHco3(ISE).N1 (abbreviated as "ISE"), but we also discover marked differences in genomic structure/gene arrangements, distribution of nucleotide variability (single nucleotide polymorphisms (SNPs) and indels) and orthology between Haecon-5 and ISE. We used the genome and extensive transcriptomic resources for Haecon-5 to predict a subset of essential single-copy genes employing a "cross-species" machine learning (ML) approach using a range of features from nucleotide/protein sequences, protein orthology, subcellular localisation, single-cell RNA-seq and/or histone methylation data available for the model organisms Caenorhabditis elegans and Drosophila melanogaster. From a set of 1,464 conserved single copy genes, transcribed in key life-cycle stages of H. contortus, we identified 232 genes whose homologs have critical functions in C. elegans and/or D. melanogaster, and prioritised 10 of them for further characterisation; nine of the 10 genes likely play roles in neurophysiological processes, germline, hypodermis and/or respiration, and one is an unknown (orphan) gene for which no detailed functional information exists. Future studies of these genes/gene products are warranted to elucidate their roles in parasite biology, host-parasite interplay and/or disease. Clearly, the present Haecon-5 reference genome and associated resources now underpin a broad range of fundamental investigations of H. contortus and could assist in accelerating the discovery of novel intervention targets and drug candidates to combat haemonchosis.

A novel hierarchical network-based approach to unveil the complexity of functional microbial genome

Biological networks serve a crucial role in elucidating intricate biological processes. While interspecies environmental interactions have been extensively studied, the exploration of gene interactions within species, particularly among individual microorganisms, is less developed. The increasing amount of microbiome genomic data necessitates a more nuanced analysis of microbial genome structures and functions. In this context, we introduce a complex structure using higher-order network theory, "Solid Motif Structures (SMS)", via a hierarchical biological network analysis of genomes within the same genus, effectively linking microbial genome structure with its function. Leveraging 162 high-quality genomes of Microcystis, a key freshwater cyanobacterium within microbial ecosystems, we established a genome structure network. Employing deep learning techniques, such as adaptive graph encoder, we uncovered 27 critical functional subnetworks and their associated SMSs. Incorporating metagenomic data from seven geographically distinct lakes, we conducted an investigation into Microcystis' functional stability under varying environmental conditions, unveiling unique functional interaction models for each lake. Our work compiles these insights into an extensive resource repository, providing novel perspectives on the functional dynamics within Microcystis. This research offers a hierarchical network analysis framework for understanding interactions between microbial genome structures and functions within the same genus.

Advancing quantitative PCR with color cycle multiplex amplification

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.

Taking advantage of reference-guided assembly in a slowly-evolving lineage: Application to Testudo graeca

BACKGROUND

Obtaining de novo chromosome-level genome assemblies greatly enhances conservation and evolutionary biology studies. For many research teams, long-read sequencing technologies (that produce highly contiguous assemblies) remain unaffordable or unpractical. For the groups that display high synteny conservation, these limitations can be overcome by a reference-guided assembly using a close relative genome. Among chelonians, tortoises (Testudinidae) are considered one of the most endangered taxa, which calls for more genomic resources. Here we make the most of high synteny conservation in chelonians to produce the first chromosome-level genome assembly of the genus Testudo with one of the most iconic tortoise species in the Mediterranean basin: Testudo graeca.

RESULTS

We used high-quality, paired-end Illumina sequences to build a reference-guided assembly with the chromosome-level reference of Gopherus evgoodei. We reconstructed a 2.29 Gb haploid genome with a scaffold N50 of 107.598 Mb and 5.37% gaps. We sequenced 25,998 protein-coding genes, and identified 41.2% of the assembly as repeats. Demographic history reconstruction based on the genome revealed two events (population decline and recovery) that were consistent with previously suggested phylogeographic patterns for the species. This outlines the value of such reference-guided assemblies for phylogeographic studies.

CONCLUSIONS

Our results highlight the value of using close relatives to produce de novo draft assemblies in species where such resources are unavailable. Our annotated genome of T. graeca paves the way to delve deeper into the species' evolutionary history and provides a valuable resource to enhance direct conservation efforts on their threatened populations.

PET/CT Recognition of Costal Cartilage Infection After Breast Implant Surgery

BACKGROUND

Postoperative infection of breast implants can lead to implant removal and other complications. This study aimed to investigate the presence of costal cartilage infection following breast implant surgery and the diagnostic role of PET/CT in identifying this rare complication.

PATIENTS AND METHODS

A retrospective study included 16 patients with persistent infections after breast implant removal surgery. Patients underwent PET/CT scans before surgery, and surgical plans were made based on PET/CT findings. Surgical procedures were guided by PET/CT, and specimens were collected for pathological examination and microbiological culture. Follow-up assessments were performed at 1, 3, and 12 months postoperatively.

RESULTS

Among the 16 patients, 11 were diagnosed with costal cartilage infection, whereas 5 had subcutaneous soft tissue infections. PET/CT accurately identified costal cartilage infection in all cases and localized the infected costal cartilage in the majority of cases. Microbiological culture results showed various pathogens. All patients were cured with one or staged surgery.

CONCLUSION

Costal cartilage infection following breast implant surgery is a significant concern. PET/CT plays a crucial role in the accurate diagnosis and localization of infected costal cartilage, aiding in appropriate surgical management. Patients should be closely monitored for the possibility of costal cartilage infection when experiencing persistent symptoms after breast implant surgery.

Cryptographic approaches to authenticating synthetic DNA sequences

In a bioeconomy that relies on synthetic DNA sequences, the ability to ensure their authenticity is critical. DNA watermarks can encode identifying data in short sequences and can be combined with error correction and encryption protocols to ensure that sequences are robust to errors and securely communicated. New digital signature techniques allow for public verification that a sequence has not been modified and can contain sufficient information for synthetic DNA to be self-documenting. In translating these techniques from bacteria to more complex genetically modified organisms (GMOs), special considerations must be made to allow for public verification of these products. We argue that these approaches should be widely implemented to assert authorship, increase the traceability, and detect the unauthorized use of synthetic DNA.

Detection of four isomers of the human cytomegalovirus genome using nanopore long-read sequencing

Human cytomegalovirus has a linear DNA genome with a total length of approximately 235 kb. This large genome is divided into two domains, "Long" and "Short". There are four isomers of the cytomegalovirus genome with different orientations of each domain. To confirm the presence of four types of isomers, it is necessary to identify the sequence of the junction between the domains. However, due to the presence of repeat sequences, it is difficult to determine the junction sequences by next-generation sequencing analysis. To solve this problem, long-read sequencing was performed using the Oxford Nanopore sequencer and the junctions were successfully identified in four isomers in strain Merin and ATCC-2011-3. Nanopore sequencing also revealed the presence of multiple copies of the "a" sequence (a-seq) in the junctions, indicating the diversity of the junction sequences. These results strongly suggest that long-read sequencing using the nanopore sequencer would be beneficial for identifying the complex structure of the cytomegalovirus genome.

Phage display technology and its impact in the discovery of novel protein-based drugs

INTRODUCTION

Phage display technology is a well-established versatile in vitro display technology that has been used for over 35 years to identify peptides and antibodies for use as reagents and therapeutics, as well as exploring the diversity of alternative scaffolds as another option to conventional therapeutic antibody discovery. Such successes have been responsible for spawning a range of biotechnology companies, as well as many complementary technologies devised to expedite the drug discovery process and resolve bottlenecks in the discovery workflow.

AREAS COVERED

In this perspective, the authors summarize the application of phage display for drug discovery and provide examples of protein-based drugs that have either been approved or are being developed in the clinic. The amenability of phage display to generate functional protein molecules to challenging targets and recent developments of strategies and techniques designed to harness the power of sampling diverse repertoires are highlighted.

EXPERT OPINION

Phage display is now routinely combined with cutting-edge technologies to deep-mine antibody-based repertoires, peptide, or alternative scaffold libraries generating a wealth of data that can be leveraged, e.g. via artificial intelligence, to enable the potential for clinical success in the discovery and development of protein-based therapeutics.

Applications of Nanopore sequencing in precision cancer medicine

Oxford Nanopore Technologies sequencing, also referred to as Nanopore sequencing, stands at the forefront of a revolution in clinical genetics, offering the potential for rapid, long read, and real-time DNA and RNA sequencing. This technology is currently making sequencing more accessible and affordable. In this comprehensive review, we explore its potential regarding precision cancer diagnostics and treatment. We encompass a critical analysis of clinical cases where Nanopore sequencing was successfully applied to identify point mutations, splice variants, gene fusions, epigenetic modifications, non-coding RNAs, and other pivotal biomarkers that defined subsequent treatment strategies. Additionally, we address the challenges of clinical applications of Nanopore sequencing and discuss the current efforts to overcome them.

Hereditary Amyloidosis: Insights Into a Fibrinogen A Variant Protein

Amyloidosis are a group of diseases in which soluble proteins aggregate and deposit in fibrillar conformation extracellularly in tissues. The effectiveness of therapeutic strategies depends on the specific protein involved, being crucial to accurately determine its nature. Moreover, following the diagnosis, the search for the mutation within relatives allows the clinical advice. Here we report the precise diagnosis and explored the possible reasons of the structural pathogenicity for a renal amyloidosis related to a fibrinogen Aα-chain variant. Whole-exome sequencing and GATK calling pipeline were leveraged to characterize the protein variant present in a patient with kidney failure. Bioinformatics strategies were applied to suggest potential explanations of the variants aggregation. Our pipeline allowed the identification of a single-point variant of fibrinogen Aα-chain, which opened the possibility of curative transplantation. In silico structural analysis suggested that the pathogenicity of the variant may be attributed to a heightened susceptibility to yield a peptide prone to deposit as an oligomer with a β-sheet structure. Exploiting the comprehensive coverage of whole-genome sequencing, we managed to fill a vacant stage in the diagnosis of hereditary amyloidosis and to stimulate the advancement in biomedicine.

Simultaneous high throughput genotyping of 36 blood group systems using NGS based on probe capture technology

Human blood group antigen has important biological functions, and transfusion of incompatible blood can cause alloimmunization and may lead to serious hemolytic reactions. Currently, serological methods are most commonly used in blood group typing. However, this technique has certain limitations and cannot fully meet the increasing demand for the identification of blood group antigens. This study describes a next-generation sequencing (NGS) technology platform based on exon and flanking region capture probes to detect full coding exon and flanking intron regions of the 36 blood group systems, providing a new high-throughput method for the identification of blood group antigens. The 871 capture probes were designed for the exon and flanking intron sequences of 36 blood group system genes, and synchronization analysis for 36 blood groups was developed. The library for NGS was tested using the MiSeq Sequencing Reagent Kit (v2, 300 cycles) by Illumina NovaSeq, and the data were analyzed by the CLC Genomics Workbench 21.0 software. A total of 199 blood specimens have been sequenced for the 41 genes from 36 blood groups. Among them, heterozygote genotypes were found in the ABO, Rh, MNS, Lewis, Duffy, Kidd, Diego, Gerbich, Dombrock, Globoside, JR, LAN, and Landsteiner-Wiene blood group systems. Only the homozygous genotype was found in the remaining 22 blood group systems. The obtained data in the NGS method shows a good correlation (99.98 %) with those of the polymerase chain reaction-sequence-based typing. An NGS technology platform for 36 blood group systems genotyping was successfully established, which has the characteristics of high accuracy, high throughput, and wide coverage.

A Wright-Fisher graph model and the impact of directional selection on genetic variation

We introduce a multi-allele Wright-Fisher model with mutation and selection such that allele frequencies at a single locus are traced by the path of a hybrid jump-diffusion process. The state space of the process is given by the vertices and edges of a topological graph, i.e. edges are unit intervals. Vertices represent monomorphic population states and positions on the edges mark the biallelic proportions of ancestral and derived alleles during polymorphic segments. In this setting, mutations can only occur at monomorphic loci. We derive the stationary distribution in mutation-selection-drift equilibrium and obtain the expected allele frequency spectrum under large population size scaling. For the extended model with multiple independent loci we derive rigorous upper bounds for a wide class of associated measures of genetic variation. Within this framework we present mathematically precise arguments to conclude that the presence of directional selection reduces the magnitude of genetic variation, as constrained by the bounds for neutral evolution.

Local read haplotagging enables accurate long-read small variant calling

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant.

Comparative Analysis of Gut Microbiota between Captive and Wild Long-Tailed Gorals for Ex Situ Conservation

The long-tailed goral is close to extinction, and ex situ conservation is essential to prevent this phenomenon. Studies on the gut microbiome of the long-tailed goral are important for understanding the ecology of this species. We amplified DNA from the 16S rRNA regions and compared the microbiomes of wild long-tailed gorals and two types of captive long-tailed gorals. Our findings revealed that the gut microbiome diversity of wild long-tailed gorals is greatly reduced when they are reared in captivity. A comparison of the two types of captive long-tailed gorals confirmed that animals with a more diverse diet exhibit greater gut microbiome diversity. Redundancy analysis confirmed that wild long-tailed gorals are distributed throughout the highlands, midlands, and lowlands. For the first time, it was revealed that the long-tailed goral are divided into three groups depending on the height of their habitat, and that the gut bacterial community changes significantly when long-tailed gorals are raised through ex situ conservation. This provides for the first time a perspective on the diversity of food plants associated with mountain height that will be available to long-tailed goral in the future.

HapKled: a haplotype-aware structural variant calling approach for Oxford nanopore sequencing data

Introduction: Structural Variants (SVs) are a type of variation that can significantly influence phenotypes and cause diseases. Thus, the accurate detection of SVs is a vital part of modern genetic analysis. The advent of long-read sequencing technology ushers in a new era of more accurate and comprehensive SV calling, and many tools have been developed to call SVs using long-read data. Haplotype-tagging is a procedure that can tag haplotype information on reads and can thus potentially improve the SV detection; nevertheless, few methods make use of this information. In this article, we introduce HapKled, a new SV detection tool that can accurately detect SVs from Oxford Nanopore Technologies (ONT) long-read alignment data. Methods: HapKled utilizes haplotype information underlying alignment data by conducting haplotype-tagging using Whatshap on the reads to improve the detection performance, with three unique calling mechanics including altering clustering conditions according to haplotype information of signatures, determination of similar SVs based on haplotype information, and slack filtering conditions based on haplotype quality. Results: In our evaluations, HapKled outperformed state-of-the-art tools and can deliver better SV detection results on both simulated and real sequencing data. The code and experiments of HapKled can be obtained from https://github.com/CoREse/HapKled. Discussion: With the superb SV detection performance that HapKled can deliver, HapKled could be useful in bioinformatics research, clinical diagnosis, and medical research and development.

Enhanced Genomic and Transcriptomic Resources for Trichinella pseudospiralis and T. spiralis to Underpin the Discovery of Molecular Differences between Stages and Species

Nematodes of the genus Trichinella are important pathogens of humans and animals. This study aimed to enhance the genomic and transcriptomic resources for T. pseudospiralis (non-encapsulated phenotype) and T. spiralis (encapsulated phenotype) and to explore transcriptional profiles. First, we improved the assemblies of the genomes of T. pseudospiralis (code ISS13) and T. spiralis (code ISS534), achieving genome sizes of 56.6 Mb (320 scaffolds, and an N50 of 1.02 Mb) and 63.5 Mb (568 scaffolds, and an N50 value of 0.44 Mb), respectively. Then, for each species, we produced RNA sequence data for three key developmental stages (first-stage muscle larvae [L1s], adults, and newborn larvae [NBLs]; three replicates for each stage), analysed differential transcription between stages, and explored enriched pathways and processes between species. Stage-specific upregulation was linked to cellular processes, metabolism, and host-parasite interactions, and pathway enrichment analysis showed distinctive biological processes and cellular localisations between species. Indeed, the secreted molecules calmodulin, calreticulin, and calsyntenin-with possible roles in modulating host immune responses and facilitating parasite survival-were unique to T. pseudospiralis and not detected in T. spiralis. These insights into the molecular mechanisms of Trichinella-host interactions might offer possible avenues for developing new interventions against trichinellosis.

Optical detection of infectious SARS-CoV-2 virions by counting spikes

Existing methods for the mass detection of viruses are limited to the registration of small amounts of a viral genome or specific protein markers. In spite of high sensitivity, the applied methods cannot distinguish between virulent viral particles and non-infectious viral particle debris. We report an approach to solve this long-standing challenge using the SARS-CoV-2 virus as an example. We show that wide-field optical microscopy with the state-of-the-art mesoscopic fluorescent labels, formed by a core-shell plasmonic nanoparticle with fluorescent dye molecules in the core-shell that are strongly coupled to the plasmonic nanoparticle, not only rapidly, i.e. in less than 20 minutes after sampling, detects SARS-CoV-2 virions directly in a patient sample without a pre-concentration step, but can also distinguish between infectious and non-infectious virus strains by counting the spikes on the lipid envelope of individual viral particles.

First Chromosome-Level Genome Assembly of a Ribbon Worm from the Hoplonemertea Clade, Emplectonema gracile, and Its Structural Annotation

Genome-wide information has so far been unavailable for ribbon worms of the clade Hoplonemertea, the most species-rich class within the phylum Nemertea. While species within Pilidiophora, the sister clade of Hoplonemertea, possess a pilidium larval stage and lack stylets on their proboscis, Hoplonemertea species have a planuliform larva and are armed with stylets employed for the injection of toxins into their prey. To further compare these developmental, physiological, and behavioral differences from a genomic perspective, the availability of a reference genome for a Hoplonemertea species is crucial. Such data will be highly useful for future investigations toward a better understanding of molecular ecology, venom evolution, and regeneration not only in Nemertea but also in other marine invertebrate phyla. To this end, we herein present the annotated chromosome-level genome assembly for Emplectonema gracile (Nemertea; Hoplonemertea; Monostilifera; Emplectonematidae), an easily collected nemertean well suited for laboratory experimentation. The genome has an assembly size of 157.9 Mb. Hi-C scaffolding yielded chromosome-level scaffolds, with a scaffold N50 of 10.0 Mb and a score of 95.1% for complete BUSCO genes found as a single copy. Annotation predicted 20,684 protein-coding genes. The high-quality reference genome reaches an Earth BioGenome standard level of 7.C.Q50.

A narrative review of inherited arrhythmogenic syndromes in young population: role of genetic diagnosis in exercise recommendations

Sudden cardiac death is a rare but socially devastating event, especially if occurs in young people. Usually, this unexpected lethal event occurs during or just after exercise. One of the leading causes of sudden cardiac death is inherited arrhythmogenic syndromes, a group of genetic entities characterised by incomplete penetrance and variable expressivity. Exercise can be the trigger for malignant arrhythmias and even syncope in population with a genetic predisposition, being sudden cardiac death as the first symptom. Due to genetic origin, family members must be clinically assessed and genetically analysed after diagnosis or suspected diagnosis of a cardiac channelopathy. Early identification and adoption of personalised preventive measures is crucial to reduce risk of arrhythmias and avoid new lethal episodes. Despite exercise being recommended by the global population due to its beneficial effects on health, particular recommendations for these patients should be adopted considering the sport practised, level of demand, age, gender, arrhythmogenic syndrome diagnosed but also genetic diagnosis. Our review focuses on the role of genetic background in sudden cardiac death during exercise in child and young population.

Oral microbial profiles of extrinsic black tooth stain in primary dentition: A literature review

The extrinsic black tooth stain (EBS) is commonly found in primary dentition. Patients cannot clean the EBS; this can only be done by professional scaling and debridement. It also has a tendency to reform, which significantly compromises children's aesthetics and even affects their quality of life. However, there is no conclusive evidence on the etiology of the EBS. The associations between the EBS and related oral microbial features is one of the research hot topics. No literature review summarized these research progresses in this area. Therefore, we reviewed the literature on the microbiology of the EBS since 1931 and reported as the following 5 aspects: molecular biotechnology, morphological structure and physiochemical characteristics, microbial etiology hypothesis and core microbial characteristics. The EBS is a special dental plaque mainly composed of Gram-positive bacilli and cocci with scattered calcium deposits that acquired salivary pellicle activates. Early studies showed that the Actinomyces was the main pathogenic bacteria. With advances in biological research techniques, the 'core microbiome' was proposed. The potential pathogenic genera were Actinomyces, Prevotella nigrescens, Pseudotropinibacterium, Leptotrichia, Neisseria and Rothia. However, the pathogenic species of the above genera were still unclear. Currently, it is believed that the EBS consists of iron compounds or black substances that oral bacterial metabolism produces or that the bacterial metabolites formed after chemical reactions in the micro-ecological environment.

Development of a screening system of gene sets for estimating the time of early skeletal muscle injury based on second-generation sequencing technology

The present study is aimed to address the challenge of wound age estimation in forensic science by identifying reliable genetic markers using low-cost and high-precision second-generation sequencing technology. A total of 54 Sprague-Dawley rats were randomly assigned to a control group or injury groups, with injury groups being further divided into time points (4 h, 8 h, 12 h, 16 h, 20 h, 24 h, 28 h, and 32 h after injury, n = 6) to establish rat skeletal muscle contusion models. Gene expression data were obtained using second-generation sequencing technology, and differential gene expression analysis, weighted gene co-expression network analysis (WGCNA) and time-dependent expression trend analysis were performed. A total of six sets of biomarkers were obtained: differentially expressed genes at adjacent time points (127 genes), co-expressed genes most associated with wound age (213 genes), hub genes exhibiting time-dependent expression (264 genes), and sets of transcription factors (TF) corresponding to the above sets of genes (74, 87, and 99 genes, respectively). Then, random forest (RF), support vector machine (SVM) and multilayer perceptron (MLP), were constructed for wound age estimation from the above gene sets. The results estimated by transcription factors were all superior to the corresponding hub genes, with the transcription factor group of WGCNA performed the best, with average accuracy rates of 96% for three models' internal testing, and 91.7% for the highest external validation. This study demonstrates the advantages of the indicator screening system based on second-generation sequencing technology and transcription factor level for wound age estimation.

Effects of different assembly strategies on gene annotation in activated sludge

Activated sludge comprises diverse bacteria, fungi, and other microorganisms, featuring a rich repertoire of genes involved in antibiotic resistance, pollutant degradation, and elemental cycling. In this regard, hybrid assembly technology can revolutionize metagenomics by detecting greater gene diversity in environmental samples. Nonetheless, the optimal utilization and comparability of genomic information between hybrid assembly and short- or long-read technology remain unclear. To address this gap, we compared the performance of the hybrid assembly, short- and long-read technologies, abundance and diversity of annotated genes, and taxonomic diversity by analysing 46, 161, and 45 activated sludge metagenomic datasets, respectively. The results revealed that hybrid assembly technology exhibited the best performance, generating the most contiguous and longest contigs but with a lower proportion of high-quality metagenome-assembled genomes than short-read technology. Compared with short- or long-read technologies, hybrid assembly technology can detect a greater diversity of microbiota and antibiotic resistance genes, as well as a wider range of potential hosts. However, this approach may yield lower gene abundance and pathogen detection. Our study revealed the specific advantages and disadvantages of hybrid assembly and short- and long-read applications in wastewater treatment plants, and our approach could serve as a blueprint to be extended to terrestrial environments.

GWAS advancements to investigate disease associations and biological mechanisms

Genome-wide association studies (GWAS) have been instrumental in elucidating the genetic architecture of various traits and diseases. Despite the success of GWAS, inherent limitations such as identifying rare and ultra-rare variants, the potential for spurious associations, and in pinpointing causative agents can undermine diagnostic capabilities. This review provides an overview of GWAS and highlights recent advances in genetics that employ a range of methodologies, including Whole Genome Sequencing (WGS), Mendelian Randomization (MR), the Pangenome's high-quality T2T-CHM13 panel, and the Human BioMolecular Atlas Program (HuBMAP), as potential enablers of current and future GWAS research. State of the literature demonstrate the capabilities of these techniques in enhancing the statistical power of GWAS. WGS, with its comprehensive approach, captures the entire genome, surpassing the capabilities of the traditional GWAS technique focused on predefined Single Nucleotide Polymorphism (SNP) sites. The Pangenome's T2T-CHM13 panel, with its holistic approach, aids in the analysis of regions with high sequence identity, such as segmental duplications (SDs). Mendelian Randomization has advanced causative inference, improving clinical diagnostics and facilitating definitive conclusions. Furthermore, spatial biology techniques like HuBMAP, enable 3D molecular mapping of tissues at single-cell resolution, offering insights into pathology of complex traits. This study aims to elucidate and advocate for the increased application of these technologies, highlighting their potential to shape the future of GWAS research.

A reproducible workflow for assembling the mitochondrial genome of Acheta domesticus (Orthoptera: Gryllidae)

In this study, we report the assembly and annotation of the mitochondrial genome (mitogenome) of Acheta domesticus from breeding facility, a species commonly known as the house cricket. This species is considered to be an important edible cricket. The mitogenome was assembled using a reproducible protocol implemented on the Galaxy Europe Server, which involved uploading paired-end fastq reads for bioinformatic analysis. The resulting mitogenome is 15,784 base pairs in length and has a GC content of 29.05%. The nucleotide composition of this mitogenome is similar to that of other insect mitogenomes, with A, T, C, and G nucleotides comprising 39.2%, 31.7%, 19.6%, and 9.5% of the mitogenome, respectively. The gene organization of the A. domesticus mitogenome is identical to that of other cricket species. The mitogenome consists of 37 genes, including 13 protein-coding genes, 22 tRNA genes, and two rRNA genes. The congruence between PCA and Bayesian evolutionary tree analysis in clustering the divergent A. domesticus sequences highlights these genomes as candidates for further study to elucidate their distinct features and evolutionary history.

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.

Deciphering Autoimmune Diseases: Unveiling the Diagnostic, Therapeutic, and Prognostic Potential of Immune Repertoire Sequencing

Autoimmune diseases (AIDs) are immune system disorders where the body exhibits an immune response to its own antigens, causing damage to its own tissues and organs. The pathogenesis of AIDs is incompletely understood. However, recent advances in immune repertoire sequencing (IR-seq) technology have opened-up a new avenue to study the IR. These studies have revealed the prevalence in IR alterations, potentially inducing AIDs by disrupting immune tolerance and thereby contributing to our comprehension of AIDs. IR-seq harbors significant potential for the clinical diagnosis, personalized treatment, and prognosis of AIDs. This article reviews the application and progress of IR-seq in diseases, such as multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, and type 1 diabetes, to enhance our understanding of the pathogenesis of AIDs and offer valuable references for the diagnosis and treatment of AIDs.

Copy number variant detection using next-generation sequencing in EYS-associated retinitis pigmentosa

Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy and a major cause of blindness. RP is caused by several variants of multiple genes, and genetic diagnosis by identifying these variants is important for optimizing treatment and estimating patient prognosis. Next-generation sequencing (NGS), which is currently widely used for diagnosis, is considered useful but is known to have limitations in detecting copy number variations (CNVs). In this study, we re-evaluated CNVs in EYS, the main causative gene of RP, identified via NGS using multiplex ligation-dependent probe amplification (MLPA). CNVs were identified in NGS samples of eight patients. To identify potential CNVs, MLPA was also performed on samples from 42 patients who were undiagnosed by NGS but carried one of the five major pathogenic variants reported in Japanese EYS-RP cases. All suspected CNVs based on NGS data in the eight patients were confirmed via MLPA. CNVs were found in 2 of the 42 NGS-undiagnosed RP cases. Furthermore, results showed that 121 of the 661 patients with RP had EYS as the causative gene, and 8.3% (10/121 patients with EYS-RP) had CNVs. Although NGS using the CNV calling criteria utilized in this study failed to identify CNVs in two cases, no false-positive results were detected. Collectively, these findings suggest that NGS is useful for CNV detection during clinical diagnosis of RP.

Genomic Analysis of Novel Sulfitobacter Bacterial Strains Isolated from Marine Biofilms

Bacteria from the genus Sulfitobacter are distributed across various marine habitats and play a significant role in sulfur cycling. However, the metabolic features of Sulfitobacter inhabiting marine biofilms are still not well understood. Here, complete genomes and paired metatranscriptomes of eight Sulfitobacter strains, isolated from biofilms on subtidal stones, have been analyzed to explore their central energy metabolism and potential of secondary metabolite biosynthesis. Based on average nucleotide identity and phylogenetic analysis, the eight strains were classified into six novel species and two novel strains. The reconstruction of the metabolic pathways indicated that all strains had a complete Entner-Doudoroff pathway, pentose phosphate pathway, and diverse pathways for amino acid metabolism, suggesting the presence of an optimized central carbon metabolism. Pangenome analysis further revealed the differences between the gene cluster distribution patterns among the eight strains, suggesting significant functional variation. Moreover, a total of 47 biosynthetic gene clusters were discovered, which were further classified into 37 gene cluster families that showed low similarity with previously documented clusters. Furthermore, metatranscriptomic analysis revealed the expressions of key functional genes involved in the biosynthesis of ribosomal peptides in in situ marine biofilms. Overall, this study sheds new light on the metabolic features, adaptive strategies, and value of genome mining in this group of biofilm-associated Sulfitobacter bacteria.

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).

Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval

Polymerase Chain Reaction (PCR) amplification is widely used for retrieving information from DNA storage. During the PCR amplification process, nonspecific pairing between the 3' end of the primer and the DNA sequence can cause cross-talk in the amplification reaction, leading to the generation of interfering sequences and reduced amplification accuracy. To address this issue, we propose an efficient coding algorithm for PCR amplification information retrieval (ECA-PCRAIR). This algorithm employs variable-length scanning and pruning optimization to construct a codebook that maximizes storage density while satisfying traditional biological constraints. Subsequently, a codeword search tree is constructed based on the primer library to optimize the codebook, and a variable-length interleaver is used for constraint detection and correction, thereby minimizing the likelihood of nonspecific pairing. Experimental results demonstrate that ECA-PCRAIR can reduce the probability of nonspecific pairing between the 3' end of the primer and the DNA sequence to 2-25%, enhancing the robustness of the DNA sequences. Additionally, ECA-PCRAIR achieves a storage density of 2.14-3.67 bits per nucleotide (bits/nt), significantly improving storage capacity.

Sequencing Strategy to Ensure Accurate Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

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.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Changes in the Transcriptome Profile in Young Chickens after Infection with LaSota Newcastle Disease Virus

Understanding gene expression changes in chicks after vaccination against Newcastle Disease (ND) can reveal vaccine biomarkers. There are limited data on chicks' early immune response after ND vaccination. Two trials focused on this knowledge gap. In experiment one, 42 13-day-old specific-pathogen-free (SPF) chicks were used. Harderian glands (Hgs) and tracheas (Tcs) from five birds per group were sampled at 12, 24, and 48 h post-vaccination (hpv) to evaluate the gene transcription levels by RNA sequencing (RNA-seq) and RT-qPCR. The results of RNA-seq were compared by glmFTest, while results of RT-qPCR were compared by t-test. With RNA-seq, a significant up-regulation of interferon-related genes along with JAK-STAT signaling pathway regulation was observed in the Hgs at 24 hpv. None of the differentially expressed genes (DEGs) identified by RNA-seq were positive for RT-qPCR. Experiment 2 used 112 SPF and commercial chickens that were 1 day old and 14 days old. Only the commercial birds had maternal antibodies for Newcastle Disease virus (NDV). By RNA-seq, 20 core DEGs associated with innate immunity and viral genome replication inhibition were identified. Genes previously unlinked to NDV response, such as USP41, were identified. This research present genes with potential as immunity biomarkers for vaccines, yet further investigation is needed to correlate the core gene expression with viral shedding post-vaccination.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of "big data" and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

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.

Transcriptional Regulation Analysis Provides Insight into the Function of GSK3β Gene in Diannan Small-Ear Pig Spermatogenesis

Glycogen synthase kinase-3β (GSK3β) not only plays a crucial role in regulating sperm maturation but also is pivotal in orchestrating the acrosome reaction. Here, we integrated single-molecule long-read and short-read sequencing to comprehensively examine GSK3β expression patterns in adult Diannan small-ear pig (DSE) testes. We identified the most important transcript ENSSSCT00000039364 of GSK3β, obtaining its full-length coding sequence (CDS) spanning 1263 bp. Gene structure analysis located GSK3β on pig chromosome 13 with 12 exons. Protein structure analysis reflected that GSK3β consisted of 420 amino acids containing PKc-like conserved domains. Phylogenetic analysis underscored the evolutionary conservation and homology of GSK3β across different mammalian species. The evaluation of the protein interaction network, KEGG, and GO pathways implied that GSK3β interacted with 50 proteins, predominantly involved in the Wnt signaling pathway, papillomavirus infection, hippo signaling pathway, hepatocellular carcinoma, gastric cancer, colorectal cancer, breast cancer, endometrial cancer, basal cell carcinoma, and Alzheimer's disease. Functional annotation identified that GSK3β was involved in thirteen GOs, including six molecular functions and seven biological processes. ceRNA network analysis suggested that DSE GSK3β was regulated by 11 miRNA targets. Furthermore, qPCR expression analysis across 15 tissues highlighted that GSK3β was highly expressed in the testis. Subcellular localization analysis indicated that the majority of the GSK3β protein was located in the cytoplasm of ST (swine testis) cells, with a small amount detected in the nucleus. Overall, our findings shed new light on GSK3β's role in DSE reproduction, providing a foundation for further functional studies of GSK3β function.

High-throughput nanopore targeted sequencing for efficient drug resistance assay of Mycobacterium tuberculosis

Drug-resistant tuberculosis (TB), especially multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB), is one of the urgent clinical problems and public health challenges. Culture-based phenotypic drug susceptibility testing (pDST) is time-consuming, and PCR-based assays are limited to hotspot mutations. In this study, we developed and validated a convenient and efficient approach based on high-throughput nanopore sequencing technology combined with multiplex PCR, namely nanopore targeted sequencing (NTS), to simultaneously sequence 18 genes associated with antibiotic resistance in Mycobacterium tuberculosis (MTB). The analytical performance of NTS was evaluated, and 99 clinical samples were collected to assess its clinical performance. The NTS results showed that MTB and its drug resistance were successfully identified in approximately 7.5 h. Furthermore, compared to the pDST and Xpert MTB/RIF assays, NTS provided much more drug resistance information, covering 14 anti-TB drugs, and it identified 20 clinical cases of drug-resistant MTB. The mutations underlying these drug-resistant cases were all verified using Sanger sequencing. Our approach for this TB drug resistance assay offers several advantages, including being culture-free, efficient, high-throughput, and highly accurate, which would be very helpful for clinical patient management and TB infection control.

RNA isoform expression landscape of the human dorsal root ganglion generated from long-read sequencing

ABSTRACT

Splicing is a posttranscriptional RNA processing mechanism that enhances genomic complexity by creating multiple isoforms from the same gene. We aimed to characterize the isoforms expressed in the human peripheral nervous system, with the goal of creating a resource to identify novel isoforms of functionally relevant genes associated with somatosensation and nociception. We used long-read sequencing to document isoform expression in the human dorsal root ganglia from 3 organ donors and validated in silico by confirming expression in short-read sequencing from 3 independent organ donors. Nineteen thousand five hundred forty-seven isoforms of protein-coding genes were detected and validated. We identified 763 isoforms with at least one previously undescribed splice junction. Previously unannotated isoforms of multiple pain-associated genes, including ASIC3, MRGPRX1, and HNRNPK, were identified. In the novel isoforms of ASIC3, a region comprising approximately 35% of the 5'UTR was excised. By contrast, a novel splice junction was used in isoforms of MRGPRX1 to include an additional exon upstream of the start codon, consequently adding a region to the 5'UTR. Novel isoforms of HNRNPK were identified, which used previously unannotated splice sites to both excise exon 14 and include a sequence in the 3' end of exon 13. This novel insertion is predicted to introduce a tyrosine phosphorylation site potentially phosphorylated by SRC. We also independently confirm a recently reported DRG-specific splicing event in WNK1 that gives insight into how painless peripheral neuropathy occurs when this gene is mutated. Our findings give a clear overview of mRNA isoform diversity in the human dorsal root ganglia obtained using long-read sequencing.

miR-153 promotes neural differentiation by activating the cell adhesion/Ca2+ signaling pathway and targeting ion channel activity in HT-22 cells by bioinformatic analysis

MicroRNAs have been studied extensively in neurodegenerative diseases. In a previous study, miR-153 promoted neural differentiation and projection formation in mouse hippocampal HT-22 cells. However, the pathways and molecular mechanism underlying miR-153-induced neural differentiation remain unclear. To explore the molecular mechanism of miR-153 on neural differentiation, we performed RNA sequencing on miR-153-overexpressed HT-22 cells. Based on RNA sequencing, differentially expressed genes (DEGs) and pathways in miR-153-overexpressed cells were identified. The Database for Annotation, Visualization and Integrated Discovery and Gene Set Enrichment Analysis were used to perform functional annotation and enrichment analysis of DEGs. Targetscan predicted the targets of miR-153. The Search Tool for the Retrieval of Interacting Genes and Cytoscape, were used to construct protein-protein interaction networks and identify hub genes. Q-PCR was used to detect mRNA expression of the identified genes. The expression profiles of the identified genes were compared between embryonic days 9.5 (E9.5) and E11.5 in the embryotic mouse brain of the GDS3442 dataset. Cell Counting Kit-8 assay was used to determine cell proliferation and cellular susceptibility to amyloid β-protein (Aβ) toxicity in miR-153-overexpressed cells. The results indicated that miR-153 increased cell adhesion/Ca2+ (Cdh5, Nrcam, and P2rx4) and Bdnf/Ntrk2 neurotrophic signaling pathway, and decreased ion channel activity (Kcnc3, Kcna4, Clcn5, and Scn5a). The changes in the expression of the identified genes in miR-153-overexpressed cells were consistent with the expression profile of GDS3442 during neural differentiation. In addition, miR-153 overexpression decreased cellular susceptibility to Aβ toxicity in HT-22 cells. In conclusion, miR-153 overexpression may promote neural differentiation by inducing cell adhesion and the Bdnf/Ntrk2 pathway, and regulating electrophysiological maturity by targeting ion channels. MiR-153 may play an important role in neural differentiation; the findings provide a useful therapeutic direction for neurodegenerative diseases.

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.