Next-generation sequencing technologies: An overview

Comparison of nine extraction methods for bacterial identification using the ONT MinION sequencer

The Anthrax mailings bioterrorism attack in 2001 revealed the need for universal and rapid microbial forensic analyses on unknown biological evidence. However, the gold standard for bacterial identification includes culturing isolates, which is laborious. Molecular approaches for bacterial identification revolve around 16S ribosomal gene sequencing using Sanger or next generation sequencing (NGS) platforms, but these techniques are laboratory-based and can also be time-consuming. The Oxford Nanopore Technologies (ONT) MinION sequencer can generate long read lengths that span the entire bacterial 16S rRNA gene and accurately identify the species level. This platform can be used in the field, allowing on-site evidence analysis. However, it requires higher quantities of pure DNA compared to other sequencing platforms; thus, the extraction method for bacterial DNA is critical for downstream analysis, which to date are tailored toward a priori knowledge of the species' taxonomic grouping. During an attack, the investigative team may not know what species they are handling; therefore, identifying an extraction method that can handle all bacterial groups and generate clean DNA for the MinION is useful for microbial forensic analysis. The purpose of this study was to identify a "universal" extraction method that can be coupled with ONT MinION sequencing for use in forensic situations for rapid identification. It also evaluated the cloud-based data analysis software provided by ONT, EPI2ME. No "universal" extraction method was identified as optimal for downstream MinION sequencing. However, the DNeasy PowerSoil Kit and Noda et al. Chelex-100 method gave comparable sequencing results and could be used as rapid extraction techniques. This study showed that the ONT 16S Barcoding Kit 1-24 coupled with the 16S FASTQ workflow might not be the best for use in forensic situations where species-level identification needs to be obtained, as most alignments were approximately 89% accurate. In all seven test organisms and nine extraction methods, accurate species identification was only obtained in 63% of the cases.

Rapid diagnosis of Aspergillus fumigatus endocarditis using mNGS assay: A case report and review of the literature

Fungal endocarditis is caused mainly by Candida albicans and Aspergillus spp. and was first reported in the 1950s. Natural-valve endocarditis caused by Aspergillus is relatively uncommon. In this case, a 56-year-old male patient was admitted to the hospital on account of a cough accompanied by chills and fever and ineffective self-medication. Infective endocarditis was initially suspected based on echocardiography (indicating right atrial growth) and clinical manifestations. However, routine pathogen detections were always negative. The patient's condition was identified as Aspergillus fumigatus endocarditis (AFE) and was treated with targeted therapy, considering the detection of significant AFE sequences in the blood through metagenomic next-generation sequencing (mNGS). On this basis, the paper further summarizes the clinical manifestations, diagnosis, treatments, and outcomes of AFE endocarditis cases reported in recent years, aiming to provide a reference to better understand this rare infective disease and guide medical practitioners in choosing the right diagnostic and therapeutic strategy.

Dynamic changes in the gut microbiota after bismuth quadruple therapy and high-dose dual therapy for Helicobacter pylori eradication

BACKGROUND

A novel regimen with high-dose dual therapy (HDDT) has emerged, but its impact on the gut microbiota is not well understood. This study aimed to evaluate the impact of HDDT on the gut microbiota and compare it with that of bismuth quadruple therapy (BQT).

METHODS

We enrolled outpatients (18-70 years) diagnosed with Helicobacter pylori infection by either histology or a positive 13C-urea breath test (13C-UBT) and randomly assigned to either the BQT or HDDT group. Subjects consented to provide fecal samples which were collected at baseline, Week 2, and Week 14. Amplification of the V1 and V9 regions of the 16S rRNA was conducted followed by high-throughput sequencing.

RESULTS

Ultimately, 78 patients (41 patients in the HDDT group and 37 in the BQT group) were enrolled in this study. Eradication therapy significantly altered the diversity of the gut microbiota. However, the alpha diversity rebounded only in the HDDT group at 12 weeks post-eradication. Immediately following eradication, the predominance of Proteobacteria, replacing commensal Firmicutes and Bacteroidetes, did not recover after 12 weeks. Species-level analysis showed that the relative abundances of Klebsiella pneumoniae and Escherichia fergusonii significantly increased in both groups at Week 2. Enterococcus faecium and Enterococcus faecalis significantly increased in the BQT group, with no significant difference observed in the HDDT group. After 12 weeks of treatment, the relative abundance of more species in the HDDT group returned to baseline levels.

CONCLUSION

Eradication of H. pylori can lead to an imbalance in gut microbiota. Compared to BQT, the HDDT is a regimen with milder impact on gut microbiota.

The diagnosis of central nervous system infections in resource-limited settings and the use of novel and molecular diagnostic platforms to improve diagnosis

INTRODUCTION

Central nervous system infections (CNSI) disproportionately affect individuals in low-resource settings where diagnosis is challenging; large proportions of patients never receive a confirmed microbiological diagnosis resulting in inadequate management and high mortality. The epidemiology of CNSI varies globally and conventional diagnostics deployed in resource-limited settings have significant limitations, with an urgent need for improved diagnostic strategies.

AREAS COVERED

This review describes molecular platforms and other novel diagnostics used in the diagnosis of CNSI that are applicable to resource-limited settings. An extensive literature search of Medline and PubMed was performed. The emphasis is on investigations targeting infections of relevance to resource-limited settings either due to variation in regional CNSI epidemiology or due to increased prevalence in patients with immunosuppression. This includes commercially available multiplex PCR platforms, mycobacterial PCR platforms, and rapid diagnostics tests. To offer a framework for the optimal implementation in clinical settings, existing evidence highlighting the advantages and limitations of available platforms is reviewed.

EXPERT OPINION

The implementation of molecular platforms and other novel diagnostics has the potential to transform CNSI diagnosis in resource-limited settings, with several examples of successful rollout of novel diagnostics such as Xpert MTB/RIF Ultra and cryptococcal antigen testing.

One-pot DTECT enables rapid and efficient capture of genetic signatures for precision genome editing and clinical diagnostics

The detection of genomic sequences and their alterations is crucial for basic research and clinical diagnostics. However, current methodologies are costly and time-consuming and require outsourcing sample preparation, processing, and analysis to genomic companies. Here, we establish One-pot DTECT, a platform that expedites the detection of genetic signatures, only requiring a short incubation of a PCR product in an optimized one-pot mixture. One-pot DTECT enables qualitative, quantitative, and visual detection of biologically relevant variants, such as cancer mutations, and nucleotide changes introduced by prime editing and base editing into cancer cells and human primary T cells. Notably, One-pot DTECT achieves quantification accuracy for targeted genetic signatures comparable with Sanger and next-generation sequencing. Furthermore, its effectiveness as a diagnostic platform is demonstrated by successfully detecting sickle cell variants in blood and saliva samples. Altogether, One-pot DTECT offers an efficient, versatile, adaptable, and cost-effective alternative to traditional methods for detecting genomic signatures.

A comprehensive review on Gossypium hirsutum resistance against cotton leaf curl virus

Cotton (Gossypium hirsutum L.) is a significant fiber crop. Being a major contributor to the textile industry requires continuous care and attention. Cotton is subjected to various biotic and abiotic constraints. Among these, biotic factors including cotton leaf curl virus (CLCuV) are dominant. CLCuV is a notorious disease of cotton and is acquired, carried, and transmitted by the whitefly (Bemisia tabaci). A cotton plant affected with CLCuV may show a wide range of symptoms such as yellowing of leaves, thickening of veins, upward or downward curling, formation of enations, and stunted growth. Though there are many efforts to protect the crop from CLCuV, long-term results are not yet obtained as CLCuV strains are capable of mutating and overcoming plant resistance. However, systemic-induced resistance using a gene-based approach remained effective until new virulent strains of CLCuV (like Cotton Leaf Curl Burewala Virus and others) came into existence. Disease control by biological means and the development of CLCuV-resistant cotton varieties are in progress. In this review, we first discussed in detail the evolution of cotton and CLCuV strains, the transmission mechanism of CLCuV, the genetic architecture of CLCuV vectors, and the use of pathogen and nonpathogen-based approaches to control CLCuD. Next, we delineate the uses of cutting-edge technologies like genome editing (with a special focus on CRISPR-Cas), next-generation technologies, and their application in cotton genomics and speed breeding to develop CLCuD resistant cotton germplasm in a short time. Finally, we delve into the current obstacles related to cotton genome editing and explore forthcoming pathways for enhancing precision in genome editing through the utilization of advanced genome editing technologies. These endeavors aim to enhance cotton's resilience against CLCuD.

Genomics landscape of mitochondrial DNA variations in patients from South Italy affected by mitochondriopathies

Mitochondrial DNA (mtDNA) is a 16,569 base pairs, double-stranded, circular molecule that contains 37 genes coding for 13 subunits of the respiratory chain plus 2 rRNAs and 22 tRNAs. Mutations in these genes have been identified in patients with a variety of disorders affecting every system in the body. The advent of next generation sequencing technologies has provided the possibility to perform the whole mitochondrial DNA sequencing, allowing the identification of disease-causing pathogenic variants in a single platform. In this study, the whole mtDNA of 100 patients from South Italy affected by mitochondrial diseases was analyzed by using an amplicon-based approach and then the enriched libraries were deeply sequenced on the ION Torrent platform (Thermofisher Scientific Waltham, MA, USA). After bioinformatics analysis and filtering, we were able to find 26 nonsynonymous variants with a MAF <1% that were associated with different pathological phenotypes, expanding the mutational spectrum of these diseases. Moreover, among the new mutations found, we have also analyzed the 3D structure of the MT-ATP6 A200T gene variation in order to confirm suspected functional alterations. This work brings light on new variants possibly associated with several mitochondriopathies in patients from South Italy and confirms that deep sequencing approach, compared to the standard methods, is a reliable and time-cost reducing strategy to detect all the variants present in the mitogenome, making the possibility to create a genomics landscape of mitochondrial DNA variations in human diseases.

"Evaluating the Benefits and Limits of Multiple Displacement Amplification with Whole-Genome Oxford Nanopore Sequencing"

Multiple Displacement Amplification (MDA) outperforms conventional PCR in long fragment and whole genome amplification which makes it attractive to couple with long-read sequencing of samples with limited quantities of DNA to obtain improved genome assemblies. Here, we explore the efficacy and limits of MDA for genome sequence assembly using Oxford Nanopore Technologies (ONT) rapid library preparations and minION sequencing. We successfully generated almost complete genome sequences for all organisms examined, including Cryptosporidium meleagridis, Staphylococcus aureus, Enterococcus faecium, and Escherichia coli, with the ability to generate high-quality data from samples starting with only 0.025 ng of total DNA. Controlled sheared DNA samples exhibited a distinct pattern of size-increase after MDA, which may be associated with the amplification of long, low-abundance fragments present in the assay, as well as generating concatemeric sequences during amplification. To address concatemers, we developed a computational pipeline (CADECT: Concatemer Detection Tool) to identify and remove putative concatemeric sequences. This study highlights the efficacy of MDA in generating high-quality genome assemblies from limited amounts of input DNA. Also, the CADECT pipeline effectively mitigated the impact of concatemeric sequences, enabling the assembly of contiguous sequences even in cases where the input genomic DNA was degraded. These results have significant implications for the study of organisms that are challenging to culture in vitro, such as Cryptosporidium, and for expediting critical results in clinical settings with limited quantities of available genomic DNA.

The application of high-throughput sequencing technology in corneal diseases

High-throughput sequencing technology, also known as next-generation sequencing technology, can explore new biomarkers and specific gene mutations. It has a pivotal role in promoting the gene research, which can limit the detection area, lessen the time needed for sequencing. Also, it can quickly screen out the suspected pathogenic genes of patients, gain the necessary genetic data, and provide the basis for clinical diagnosis and genetic counseling. In the research of corneal diseases, through the DNA sequencing of patients' diseased cells, it can provide a deeper understanding of corneal diseases and improve the diagnosis, classification and treatment alternatives of various corneal diseases. This article will introduce the application progress of high-throughput sequencing technology in corneal diseases, which will help to understand the application of this technology in various corneal diseases.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Comparative analysis of chloroplast genomes of seven Juniperus species from Kazakhstan

Juniperus species are shrubs or trees in the family Cupressaceae that play an important role in forest ecosystems. In this study, we report the complete sequences of the plastid (pt) genomes of five Juniperus species collected in Kazakhstan (J. communis, J. sibirica, J. pseudosabina, J. semiglobosa, and J. davurica). The sequences of the pt genomes of the five species were annotated in addition to two full pt genome sequences from J. sabina and J. seravschanica, which we have previously reported. The pt genome sequences of these seven species were compared to the pt genomes of Juniperus species available in the public NCBI database. The total length of the pt genomes of Juniperus species, including previously published pt genome data, ranged from 127,469 bp (J. semiglobosa) to 128,097 bp (J. communis). Each Juniperus plastome consisted of 119 genes, including 82 protein-coding genes, 33 transfer RNA and 4 ribosomal RNA genes. Among the identified genes, 16 contained one or two introns, and 2 tRNA genes were duplicated. A comparative assessment of pt genome sequences suggested the identification of 1145 simple sequence repeat markers. A phylogenetic tree of 26 Juniperus species based on the 82 protein-coding genes separated the Juniperus samples into two major clades, corresponding to the Juniperus and Sabina sections. The analysis of pt genome sequences indicated that accD and ycf2 were the two most polymorphic genes. The phylogenetic evaluation of 26 Juniperus species using these two genes confirmed that they can be efficiently used as DNA barcodes for phylogenetic analyses in the genus. The sequenced plastomes of these Juniperus species have provided a large amount of genetic data that will be valuable for future genomic studies of this genus.

Utilizing Massively Parallel Sequencing (MPS) of Human Leukocyte Antigen (HLA) Gene Polymorphism to Assess Relatedness in Deficiency Parentage Testing

In the realm of DNA testing with legal implications, the reliability and precision of genetic markers play a pivotal role in confirming or negating paternity claims. This study aimed to assess the potential utility of human leukocyte antigen (HLA) gene polymorphism through massively parallel sequencing (MPS) technology as robust forensic markers for parentage testing involving genetic deficiencies. It sought to redefine the significance of HLA genes in this context. Data on autosomal short tandem repeat (aSTR) mutational events across 18 paternity cases involving 16 commonly employed microsatellite loci were presented. In instances where traditional aSTR analysis failed to establish statistical certainty, kinship determination was pursued via HLA genotyping, encompassing the amplification of 17 linked HLA loci. Within the framework of this investigation, phase-resolved genotypes for HLA genes were meticulously generated, resulting in the definition of 34 inherited HLA haplotypes. An impressive total of 274 unique HLA alleles, which were classified at either the field 3 or 4 level, were identified, including the discovery of four novel HLA alleles. Likelihood ratio (LR) values, which indicated the likelihood of the observed data under a true biological relationship versus no relationship, were subsequently calculated. The analysis of the LR values demonstrated that the HLA genes significantly enhanced kinship determination compared with the aSTR analysis. Combining LR values from aSTR markers and HLA loci yielded conclusive outcomes in duo paternity cases, showcasing the potential of HLA genes and MPS technology for deeper insights and diversity in genetic testing. Comprehensive reference databases and high-resolution HLA typing across diverse populations are essential. Reintegrating HLA alleles into forensic identification complements existing markers, creating a potent method for future forensic analysis.

Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

Genomic features of lung cancer patients in Indonesia's national cancer center

INTRODUCTION

Advances in molecular biology bring advantages to lung cancer management. Moreover, high-throughput molecular tests are currently useful for revealing genetic variations among lung cancer patients. We investigated the genomics profile of the lung cancer patients at the National Cancer Centre of Indonesia.

METHODS

A retrospective study enrolled 627 tissue biopsy samples using real time polymerase chain reaction (RT-PCR) and 80 circulating tumour DNA (ctDNA) liquid biopsy samples using next-generation sequencing (NGS) from lung cancer patients admitted to the Dharmais Cancer Hospital from January 2018 to December 2022. Data were obtained from medical records. Data statistically analysed with p < 0.05 is considered significant.

RESULT

The EGFR test results revealed by RT-PCR were wild type (51.5%), single variant (38.8%), double variant (8.3%), and triple variant (1.4%), with 18.66% L85R, 18.22% Ex19del, and 11.08% L861Q variant. Liquid biopsy ctDNA using NGS showed only 2.5% EGFR wild type, 62.5% single variant and 35% co-variant, with EGFR/TP53 and EGFR/PIK3CA as the highest.

CONCLUSION

EGFR variants are the most found in our centre. Liquid biopsy with ctDNA using NGS examination could detect broad variants and co-variants that will influence the treatment planning.

Comparison of capture-based mtDNA sequencing performance between MGI and illumina sequencing platforms in various sample types

BACKGROUND

Mitochondrial genome abnormalities can lead to mitochondrial dysfunction, which in turn affects cellular biology and is closely associated with the development of various diseases. The demand for mitochondrial DNA (mtDNA) sequencing has been increasing, and Illumina and MGI are two commonly used sequencing platforms for capture-based mtDNA sequencing. However, there is currently no systematic comparison of mtDNA sequencing performance between these two platforms. To address this gap, we compared the performance of capture-based mtDNA sequencing between Illumina's NovaSeq 6000 and MGI's DNBSEQ-T7 using tissue, peripheral blood mononuclear cell (PBMC), formalin-fixed paraffin-embedded (FFPE) tissue, plasma, and urine samples.

RESULTS

Our analysis indicated a high degree of consistency between the two platforms in terms of sequencing quality, GC content, and coverage. In terms of data output, DNBSEQ-T7 showed higher rates of clean data and duplication compared to NovaSeq 6000. Conversely, the amount of mtDNA data obtained by per gigabyte sequencing data was significantly lower in DNBSEQ-T7 compared to NovaSeq 6000. In terms of detection mtDNA copy number, both platforms exhibited good consistency in all sample types. When it comes to detection of mtDNA mutations in tissue, FFPE, and PBMC samples, the two platforms also showed good consistency. However, when detecting mtDNA mutations in plasma and urine samples, significant differenceof themutation number detected was observed between the two platforms. For mtDNA sequencing of plasma and urine samples, a wider range of DNA fragment size distribution was found in NovaSeq 6000 when compared to DNBSEQ-T7. Additionally, two platforms exhibited different characteristics of mtDNA fragment end preference.

CONCLUSIONS

In summary, the two platforms generally showed good consistency in capture-based mtDNA sequencing. However, it is necessary to consider the data preferences generated by two sequencing platforms when plasma and urine samples were analyzed.

A qualitative assessment of using ChatGPT as large language model for scientific workflow development

BACKGROUND

Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on large compute clusters. However, implementing workflows is difficult due to the involvement of many black-box tools and the deep infrastructure stack necessary for their execution. Simultaneously, user-supporting tools are rare, and the number of available examples is much lower than in classical programming languages.

RESULTS

To address these challenges, we investigate the efficiency of large language models (LLMs), specifically ChatGPT, to support users when dealing with scientific workflows. We performed 3 user studies in 2 scientific domains to evaluate ChatGPT for comprehending, adapting, and extending workflows. Our results indicate that LLMs efficiently interpret workflows but achieve lower performance for exchanging components or purposeful workflow extensions. We characterize their limitations in these challenging scenarios and suggest future research directions.

CONCLUSIONS

Our results show a high accuracy for comprehending and explaining scientific workflows while achieving a reduced performance for modifying and extending workflow descriptions. These findings clearly illustrate the need for further research in this area.

Methods of Detection and Mechanisms of Origin of Complex Structural Genome Variations

Based on classical karyotyping, structural genome variations (SVs) have generally been considered to be either "simple" (with one or two breakpoints) or "complex" (with more than two breakpoints). Studying the breakpoints of SVs at nucleotide resolution revealed additional, subtle structural variations, such that even "simple" SVs turned out to be "complex." Genome-wide sequencing methods, such as fosmid and paired-end mapping, short-read and long-read whole genome sequencing, and single-molecule optical mapping, also indicated that the number of SVs per individual was considerably larger than expected from karyotyping and high-resolution chromosomal array-based studies. Interestingly, SVs were detected in studies of cohorts of individuals without clinical phenotypes. The common denominator of all SVs appears to be a failure to accurately repair DNA double-strand breaks (DSBs) or to halt cell cycle progression if DSBs persist. This review discusses the various DSB response mechanisms during the mitotic cell cycle and during meiosis and their regulation. Emphasis is given to the molecular mechanisms involved in the formation of translocations, deletions, duplications, and inversions during or shortly after meiosis I. Recently, CRISPR-Cas9 studies have provided unexpected insights into the formation of translocations and chromothripsis by both breakage-fusion-bridge and micronucleus-dependent mechanisms.

Analyzing RNA posttranscriptional modifications to decipher the epitranscriptomic code

The discovery of RNA silencing has revealed that non-protein-coding sequences (ncRNAs) can cover essential roles in regulatory networks and their malfunction may result in severe consequences on human health. These findings have prompted a general reassessment of the significance of RNA as a key player in cellular processes. This reassessment, however, will not be complete without a greater understanding of the distribution and function of the over 170 variants of the canonical ribonucleotides, which contribute to the breathtaking structural diversity of natural RNA. This review surveys the analytical approaches employed for the identification, characterization, and detection of RNA posttranscriptional modifications (rPTMs). The merits of analyzing individual units after exhaustive hydrolysis of the initial biopolymer are outlined together with those of identifying their position in the sequence of parent strands. Approaches based on next generation sequencing and mass spectrometry technologies are covered in depth to provide a comprehensive view of their respective merits. Deciphering the epitranscriptomic code will require not only mapping the location of rPTMs in the various classes of RNAs, but also assessing the variations of expression levels under different experimental conditions. The fact that no individual platform is currently capable of meeting all such demands implies that it will be essential to capitalize on complementary approaches to obtain the desired information. For this reason, the review strived to cover the broadest possible range of techniques to provide readers with the fundamental elements necessary to make informed choices and design the most effective possible strategy to accomplish the task at hand.

Sequencing by avidity enables high accuracy with low reagent consumption

We present avidity sequencing, a sequencing chemistry that separately optimizes the processes of stepping along a DNA template and that of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase-polymer-nucleotide complexes bound to clonal copies of DNA targets. These polymer-nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar and yield negligible dissociation rates. Avidity sequencing achieves high accuracy, with 96.2% and 85.4% of base calls having an average of one error per 1,000 and 10,000 base pairs, respectively. We show that the average error rate of avidity sequencing remained stable following a long homopolymer.

Loop-Mediated Isothermal Amplification of DNA (LAMP) as an Alternative Method for Determining Bacteria in Wound Infections

The increasing number of patients with chronic wounds requires the development of quick and accurate diagnostics methods. One of the key and challenging aspects of treating ulcers is to control wound infection. Early detection of infection is essential for the application of suitable treatment methods, such as systemic antibiotics or other antimicrobial agents. Clinically, the most frequently used method for detecting microorganisms in wounds is through a swab and culture on appropriate media. This test has major limitations, such as the long bacterial growth time and the selectivity of bacterial growth. This article presents an overview of molecular methods for detecting bacteria in wounds, including real-time polymerase chain reaction (rtPCR), quantitative polymerase chain reaction (qPCR), genotyping, next-generation sequencing (NGS), and loop-mediated isothermal amplification (LAMP). We focus on the LAMP method, which has not yet been widely used to detect bacteria in wounds, but it is an interesting alternative to conventional detection methods. LAMP does not require additional complicated equipment and provides the fastest detection time for microorganisms (approx. 30 min reaction). It also allows the use of many pairs of primers in one reaction and determination of up to 15 organisms in one sample. Isothermal amplification of DNA is currently the easiest and most economical method for microbial detection in wound infection. Direct visualization of the reaction with dyes, along with omitting DNA isolation, has increased the potential use of this method.

Oxford Nanopore Technology and its Application in Liquid Biopsies

Advanced medical technologies are transforming the future of healthcare, in particular, the screening and detection of molecular-genetic changes in patients suspected of having a neoplasm. They are based on the assumption that neoplasms release small amounts  of  various  neoplasm-specific molecules, such as tumor DNA, called circulating DNA (cirDNA), into the extracellular space and subsequently into the blood. The detection of tumor-specific molecules and specific molecular changes in body fluids in a noninvasive or minimally invasive approach is known as "liquid biopsy." The aim of this review is to summarize the current knowledge of the application of ONT for analyzing circulating DNA in the field of liquid biopsies among cancer patients. Databases were searched using the keywords "nanopore" and "liquid biopsy" and by applying strict inclusion criteria. This technique can be used for the detection of neoplastic disease, including metastases, guiding precision therapy, and monitoring its effects. There are many challenges, however, for the successful implementation of this technology into the clinical practice. The first one is the low amount of tumor-specific molecules in the body fluids. Secondly, a tumor molecular signature should be discriminated from benign conditions like clonal hematopoiesis of unknown significance. Oxford Nanopore Technology (ONT) is a third-generation sequencing technology that seems particularly promising to complete these tasks. It offers rapid sequencing thanks to its ability to detect changes in the density of the electric current passing through nanopores. Even though ONT still needs validation technology, it is a promising approach for early diagnosis, therapy guidance, and monitoring of different neoplasms based on analyzing the cirDNA.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

Muscle Transcriptome Sequencing Revealed Thermal Stress-Responsive Regulatory Genes in Farmed Rohu, Labeo rohita (Hamilton, 1822)

Rohu, Labeo rohita, is one of the most important aquaculture species in the Indian subcontinent. Understanding the molecular-level physiological responses to thermal stress or climate change is essential. In the present work, transcriptome sequencing was carried out in the muscle tissue of the rohu in response to heat stress (35 °C) in comparison with the control (28 °C). A total of 125 Gb of sequence data was generated, and the raw-reads were filtered and trimmed, which resulted in 484 million quality reads. Reference-based assembly of reads was performed using L. rohita genome, and a total of 90.17% of reads were successfully mapped. A total of 37,462 contigs were assembled with an N50 value of 1854. The differential expression analysis revealed a total of 107 differentially expressed genes (DEGs) (15 up-, 37 down-, and 55 neutrally regulated) as compared to the control group (Log2FC > 2, P < 0.05). Gene enrichment analysis of DEGs indicates that transcripts were associated with molecular, biological, and cellular activities. The randomly selected differentially expressed transcripts were validated by RT-qPCR and found consistent expression patterns in line with the RNA-seq data. Several transcripts such as SERPINE1(HSP47), HSP70, HSP90alpha, Rano class II histocompatibility A beta, PGC-1 and ERR-induced regulator, proto-oncogene c-Fos, myozenin2, alpha-crystallin B chain-like protein, angiopoietin-like protein 8, and acetyl-CoA carboxylases have been identified in muscle tissue of rohu that are associated with stress/immunity. This study identified the key biomarker SERPINE1 (HSP47), which showed significant upregulation (~ 2- to threefold) in muscle tissue of rohu exposed to high temperature. This study can pave a path for the identification of stress-responsive biomarkers linked with thermal adaptations in the farmed carps.

Experimental and Computational Approaches to Measure Telomere Length: Recent Advances and Future Directions

PURPOSE OF REVIEW

The length of telomeres, protective structures at the chromosome ends, is a well-established biomarker for pathological conditions including multisystemic syndromes called telomere biology disorders. Approaches to measure telomere length (TL) differ on whether they estimate average, distribution, or chromosome-specific TL, and each presents their own advantages and limitations.

RECENT FINDINGS

The development of long-read sequencing and publication of the telomere-to-telomere human genome reference has allowed for scalable and high-resolution TL estimation in pre-existing sequencing datasets but is still impractical as a dedicated TL test. As sequencing costs continue to fall and strategies for selectively enriching telomere regions prior to sequencing improve, these approaches may become a promising alternative to classic methods. Measurement methods rely on probe hybridization, qPCR or more recently, computational methods using sequencing data. Refinements of existing techniques and new approaches have been recently developed but a test that is accurate, simple, and scalable is still lacking.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Patchwork: Alignment-Based Retrieval and Concatenation of Phylogenetic Markers from Genomic Data

Low-coverage whole-genome sequencing (also known as "genome skimming") is becoming an increasingly affordable approach to large-scale phylogenetic analyses. While already routinely used to recover organellar genomes, genome skimming is rather rarely utilized for recovering single-copy nuclear markers. One reason might be that only few tools exist to work with this data type within a phylogenomic context, especially to deal with fragmented genome assemblies. We here present a new software tool called Patchwork for mining phylogenetic markers from highly fragmented short-read assemblies as well as directly from sequence reads. Patchwork is an alignment-based tool that utilizes the sequence aligner DIAMOND and is written in the programming language Julia. Homologous regions are obtained via a sequence similarity search, followed by a "hit stitching" phase, in which adjacent or overlapping regions are merged into a single unit. The novel sliding window algorithm trims away any noncoding regions from the resulting sequence. We demonstrate the utility of Patchwork by recovering near-universal single-copy orthologs within a benchmarking study, and we additionally assess the performance of Patchwork in comparison with other programs. We find that Patchwork allows for accurate retrieval of (putatively) single-copy genes from genome skimming data sets at different sequencing depths with high computational speed, outperforming existing software targeting similar tasks. Patchwork is released under the GNU General Public License version 3. Installation instructions, additional documentation, and the source code itself are all available via GitHub at https://github.com/fethalen/Patchwork.

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.

Towards a Long-Read Sequencing Approach for the Molecular Diagnosis of RPGRORF15 Genetic Variants

Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGRORF15, aiding in the correct annotation of genetic variants in online databases.

Oligo-Metastatic Disease in Oncology: Exploring the Limits and the Potential of Genetic Assessment

Oligo-metastatic disease (OMD) in the field of oncology denotes a distinct subset of metastatic tumors characterized by less aggressive biological behavior and extended survival times in comparison to their widely metastatic counterparts. While there is a general consensus regarding the existence of OMD, there remains a lack of widely accepted criteria for its a priori identification at the time of presentation. This review delves into the concept of OMD, placing a particular emphasis on the significance of understanding the limitations and potential of genetic assessments. It explores how these aspects are crucial in advancing our comprehension of this phenomenon. In a rapidly advancing era of precision medicine, understanding the intricacies of OMD opens up exciting possibilities for tailored treatment approaches. By elucidating the genetic underpinnings and dynamic nature of this condition, we stand to improve patient outcomes and potentially shift the paradigm of metastatic cancer management.

Contrasting new and available reference genomes to highlight uncertainties in assemblies and areas for future improvement: an example with monodontid species

BACKGROUND

Reference genomes provide a foundational framework for evolutionary investigations, ecological analysis, and conservation science, yet uncertainties in the assembly of reference genomes are difficult to assess, and by extension rarely quantified. Reference genomes for monodontid cetaceans span a wide spectrum of data types and analytical approaches, providing the context to derive broader insights related to discrepancies and regions of uncertainty in reference genome assembly. We generated three beluga (Delphinapterus leucas) and one narwhal (Monodon monoceros) reference genomes and contrasted these with published chromosomal scale assemblies for each species to quantify discrepancies associated with genome assemblies.

RESULTS

The new reference genomes achieved chromosomal scale assembly using a combination of PacBio long reads, Illumina short reads, and Hi-C scaffolding data. For beluga, we identified discrepancies in the order and orientation of contigs in 2.2-3.7% of the total genome depending on the pairwise comparison of references. In addition, unsupported higher order scaffolding was identified in published reference genomes. In contrast, we estimated 8.2% of the compared narwhal genomes featured discrepancies, with inversions being notably abundant (5.3%). Discrepancies were linked to repetitive elements in both species.

CONCLUSIONS

We provide several new reference genomes for beluga (Delphinapterus leucas), while highlighting potential avenues for improvements. In particular, additional layers of data providing information on ultra-long genomic distances are needed to resolve persistent errors in reference genome construction. The comparative analyses of monodontid reference genomes suggested that the three new reference genomes for beluga are more accurate compared to the currently published reference genome, but that the new narwhal genome is less accurate than one published. We also present a conceptual summary for improving the accuracy of reference genomes with relevance to end-user needs and how they relate to levels of assembly quality and uncertainty.

[Omics to serve myology]

Despite efforts in biomedical research, pathophysiological mechanisms and therapeutic targets of diseases remain difficult to identify. The development of high-throughput techniques led to the advent of innovatve technologies called omics. They aim at characterizing as exhaustively as possible a set of molecules: genes, RNAs, proteins, metabolites, etc. These a priori methods allow a precise molecular characterization of diseases and a better understanding of complex pathophysiological mechanisms. In this paper, we will review most omics approaches, their integration and their applications in the context of myology.

Comparative analysis of PacBio and ONT RNA sequencing methods for Nemopilema Nomurai venom identification

Recent studies on marine organisms have made use of third-generation sequencing technologies such as Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT). While these specialized bioinformatics tools have different algorithmic designs and performance capabilities, they offer scalability and can be applied to various datasets. We investigated the effectiveness of PacBio and ONT RNA sequencing methods in identifying the venom of the jellyfish species Nemopilema nomurai. We conducted a detailed analysis of the sequencing data from both methods, focusing on key characteristics such as CD, alternative splicing, long-chain noncoding RNA, simple sequence repeat, transcription factor, and functional transcript annotation. Our findings indicate that ONT generally produced higher raw data quality in the transcriptome analysis, while PacBio generated longer read lengths. PacBio was found to be superior in identifying CDs and long-chain noncoding RNA, whereas ONT was more cost-effective for predicting alternative splicing events, simple sequence repeats, and transcription factors. Based on these results, we conclude that PacBio is the most specific and sensitive method for identifying venom components, while ONT is the most cost-effective method for studying venogenesis, cnidocyst (venom gland) development, and transcription of virulence genes in jellyfish. Our study has implications for future sequencing technologies in marine jellyfish, and highlights the power of full-length transcriptome analysis in discovering potential therapeutic targets for jellyfish dermatitis.

RNA isoform expression landscape of the human dorsal root ganglion (DRG) generated from long read sequencing

Splicing is a post-transcriptional RNA processing mechanism that enhances genomic complexity by creating multiple isoforms from the same gene. Diversity in splicing in the mammalian nervous system is associated with neuronal development, synaptic function and plasticity, and is also associated with diseases of the nervous system ranging from neurodegeneration to chronic pain. 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 (LRS) to document isoform expression in the human dorsal root ganglia (hDRG) from 3 organ donors. Isoforms were validated in silico by confirming expression in hDRG short read sequencing (SRS) data from 3 independent organ donors. 19,547 isoforms of protein-coding genes were detected using LRS and validated with SRS and strict expression cutoffs. 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 ~35% of the 5'UTR was excised. In contrast, a novel splice-junction was utilized 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 utilized previously unannotated splice-sites to both excise exon 14 and include a sequence in the 5' end of exon 13. The insertion and deletion in the coding region was predicted to excise a serine-phosphorylation site favored by cdc2, and replace it with 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 hDRG obtained using LRS. Using this work as a foundation, an important next step will be to use LRS on hDRG tissues recovered from people with a history of chronic pain. This should enable identification of new drug targets and a better understanding of chronic pain that may involve aberrant splicing events.

Third-generation sequencing for genetic disease

Third-generation sequencing (TGS) has led to a brave new revolution in detecting genetic diseases over the last few years. TGS has been rapidly developed for genetic disease applications owing to its significant advantages such as long read length, rapid detection, and precise detection of complex and rare structural variants. This approach greatly improves the efficiency of disease diagnosis and complements the shortcomings of short-read sequencing. In this paper, we first briefly introduce the working mechanism of one of the most important representatives of TGS, single-molecule real-time (SMRT) sequencing by Pacific Bioscience (PacBio), followed by a review and comparison of the advantages and disadvantages of different sequencing technologies. Finally, we focused on the progress of SMRT sequencing applications in genetic disease detection. Future perspectives on the applications of TGS in other fields were also presented. With the continuous innovation of the SMRT technologies and the expansion of their fields of application, SMRT sequencing has broad clinical application prospects in genetic diseases detection, and is expected to become an important tool for the molecular diagnosis of other diseases.

Full-length transcriptome sequencing provides new insights into the complexity of flavonoid biosynthesis in Glechoma longituba

Glechoma longituba has been frequently used in treating urolithiasis and cholelithiasis due to the presence of flavonoids, which are its major bioactive constituents. However, research on the molecular background of flavonoid biosynthesis in G. longituba is limited. In this study, we used single-molecule real-time combined with next-generation sequencing technologies to construct the complete transcriptome of G. longituba. We identified 404,648 non-redundant transcripts, including 249,697 coding sequences, 197,811 simple sequence repeats, 174,846 long noncoding RNA, and 176,554 coding RNA. Moreover, we functionally annotated 346,218 isoforms (85.56%) and identified 86,528 differentially expressed genes. We also identified 55 non-redundant full-length isoforms related to the flavonoid biosynthetic pathway. Pearson correlation analysis revealed that the expression levels of some key genes of the flavonoid biosynthesis pathway were significantly positively correlated with the flavonoid metabolites. Furthermore, we performed bioinformatics analysis (sequence and structural) of isoform_47029 (encoding flavanone 3-hydroxylase) and isoform_53692 (encoding flavonol synthase) to evaluate their potential biological functions. Finally, we validated gene expression levels of 12 flavonoid-related key enzyme genes using quantitative real-time PCR. Overall, this study provides full-length transcriptome information on G. longituba for the first time and valuable molecular resources for further research on the medicinal properties of this plant.

Genome-Resolved Metagenomics and Metatranscriptomics Reveal Insights into the Ecology and Metabolism of Anaerobic Microbial Communities in PCB-Contaminated Sediments

Growth of organohalide-respiring bacteria such as Dehalococcoides mccartyi on halogenated organics (e.g., polychlorinated biphenyls (PCBs)) at contaminated sites or in enrichment culture requires interaction and support from other microbial community members. To evaluate naturally occurring interactions between Dehalococcoides and key supporting microorganisms (e.g., production of H2, acetate, and corrinoids) in PCB-contaminated sediments, metagenomic and metatranscriptomic sequencing was conducted on DNA and RNA extracted from sediment microcosms, showing evidence of both Dehalococcoides growth and PCB dechlorination. Using a genome-resolved approach, 160 metagenome-assembled genomes (MAGs), including three Dehalococcoides MAGs, were recovered. A novel reductive dehalogenase gene, distantly related to the chlorophenol dehalogenase gene cprA (pairwise amino acid identity: 23.75%), was significantly expressed. Using MAG gene expression data, 112 MAGs were assigned functional roles (e.g., corrinoid producers, acetate/H2 producers, etc.). A network coexpression analysis of all 160 MAGs revealed correlations between 39 MAGs and the Dehalococcoides MAGs. The network analysis also showed that MAGs assigned with functional roles that support Dehalococcoides growth (e.g., corrinoid assembly, and production of intermediates required for corrinoid synthesis) displayed significant coexpression correlations with Dehalococcoides MAGs. This work demonstrates the power of genome-resolved metagenomic and metatranscriptomic analyses, which unify taxonomy and function, in investigating the ecology of dehalogenating microbial communities.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Yeast metagenomics: analytical challenges in the analysis of the eukaryotic microbiome

Even if their impact is often underestimated, yeasts and yeast-like fungi represent the most prevalent eukaryotic members of microbial communities on Earth. They play numerous roles in natural ecosystems and in association with their hosts. They are involved in the food industry and pharmaceutical production, but they can also cause diseases in other organisms, making the understanding of their biology mandatory. The ongoing loss of biodiversity due to overexploitation of environmental resources is a growing concern in many countries. Therefore, it becomes crucial to understand the ecology and evolutionary history of these organisms to systematically classify them. To achieve this, it is essential that our knowledge of the mycobiota reaches a level similar to that of the bacterial communities. To overcome the existing challenges in the study of fungal communities, the first step should be the establishment of standardized techniques for the correct identification of species, even from complex matrices, both in wet lab practices and in bioinformatic tools.

De novo genome assembly depicts the immune genomic characteristics of cattle

Immunogenomic loci remain poorly understood because of their genetic complexity and size. Here, we report the de novo assembly of a cattle genome and provide a detailed annotation of the immunogenomic loci. The assembled genome contains 143 contigs (N50 ~ 74.0 Mb). In contrast to the current reference genome (ARS-UCD1.2), 156 gaps are closed and 467 scaffolds are located in our assembly. Importantly, the immunogenomic regions, including three immunoglobulin (IG) loci, four T-cell receptor (TR) loci, and the major histocompatibility complex (MHC) locus, are seamlessly assembled and precisely annotated. With the characterization of 258 IG genes and 657 TR genes distributed across seven genomic loci, we present a detailed depiction of immune gene diversity in cattle. Moreover, the MHC gene structures are integrally revealed with properly phased haplotypes. Together, our work describes a more complete cattle genome, and provides a comprehensive view of its complex immune-genome.

Identification of Genetic Variants Associated with Severe Myocardial Bridging through Whole-Exome Sequencing

Myocardial bridging (MB) is a congenital coronary artery anomaly and an important cause of angina. The genetic basis of MB is currently unknown. This study used a whole-exome sequencing technique and analyzed genotypic differences. Eight coronary angiography-confirmed cases of severe MB and eight age- and sex-matched control patients were investigated. In total, 139 rare variants that are potentially pathogenic for severe MB were identified in 132 genes. Genes with multiple rare variants or co-predicted by ClinVar and CADD/REVEL for severe MB were collected, from which heart-specific genes were selected under the guidance of tissue expression levels. Functional annotation indicated significant genetic associations with abnormal skeletal muscle mass, cardiomyopathies, and transmembrane ion channels. Candidate genes were reviewed regarding the functions and locations of each individual gene product. Among the gene candidates for severe MB, rare variants in DMD, SGCA, and TTN were determined to be the most crucial. The results suggest that altered anchoring proteins on the cell membrane and intracellular sarcomere unit of cardiomyocytes play a role in the development of the missed trajectory of coronary vessels. Additional studies are required to support the diagnostic application of cardiac sarcoglycan and dystroglycan complexes in patients with severe MB.

Predictive Clinical and Biological Criteria for Gene Panel Positivity in Suspected Inherited Autoinflammatory Diseases: Insights from a Case-Control Study

In order to assess the clinical and biological criteria that predict gene panel positivity in patients with a suspected inherited genetic autoinflammatory disease, we conducted a case-control study. These new selection criteria could replace the national multidisciplinary staff approval before performing genetic testing that has been required since 2019. The study involved 119 positive gene panels matched by panel sizes to 119 randomly selected negative gene panels. The patients were referred to our laboratory for genetic testing between June 2012, and March 2023. The clinical and biological criteria were extracted from a prospectively filled database. We focused our evaluation on accuracy and the positive predictive value. Neonatal symptom onset and deafness had the highest accuracies among all criteria associated with the positivity panel, with 92.9% (88.6; 96.0) and 92.6% (88.5; 95.6), respectively. However, it is important to note that the associated Positive Predictive Values (PPVs) cannot exceed 50%. Despite finding a statistical association between clinical and biological criteria and panel positivity, the predictive values of these criteria were not sufficient to recommend Next-Generation Sequencing (NGS) gene panel testing without the national multidisciplinary staff evaluation.

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion

BACKGROUND

Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.

METHODS

Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.

RESULTS

There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.

CONCLUSIONS

We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Integrating Internal Fragments in the Interpretation of Top-Down Sequencing Data of Larger Oligonucleotides

In the context of direct top-down analysis or concerted bottom-up characterization of nucleic acid samples, the waning yield of terminal fragments as a function of precursor ion size poses a significant challenge to the gas-phase sequencing of progressively larger oligonucleotides. In this report, we examined the behavior of oligoribonucleotide samples ranging from 20 to 364 nt upon collision-induced dissociation (CID). The experimental data showed a progressive shift from terminal to internal fragments as a function of size. The systematic evaluation of experimental factors, such as collision energy, precursor charge, sample temperature, and the presence of chaotropic agents, showed that this trend could be modestly alleviated but not suppressed. This inexorable effect, which has been reported also for other activation techniques, prompted a re-examination of the features that have traditionally discouraged the utilization of internal fragments as a source of sequence information in data interpretation procedures. Our simulations highlighted the ability of internal fragments to produce self-consistent ladders with either end corresponding to each nucleotide in the sequence, which enables both proper alignment and correct recognition of intervening nucleotides. In turn, contiguous ladders display extensive overlaps with one another and with the ladders formed by terminal fragments, which unambiguously constrain their mutual placement within the analyte sequence. The experimental data borne out the predictions by showing ladders with extensive overlaps, which translated into uninterrupted "walks" covering the entire sequence with no gaps from end to end. More significantly, the results showed that combining the information afforded by internal and terminal ladders resulted in much a greater sequence coverage and nucleotide coverage depth than those achievable when either type of information was considered separately. The examination of a series of 58-mer oligonucleotides with high sequence homology showed that the assignment ambiguities engendered by internal fragments did not significantly exceed those afforded by the terminal ones. Therefore, the balance between potential benefits and perils of including the former makes a compelling argument for the development of integrated data interpretation strategies, which are better equipped for dealing with the changing fragmentation patterns obtained from progressively larger oligonucleotides.

NMD targets experience deadenylation during their maturation and endonucleolytic cleavage during their decay

Premature stop codon-containing mRNAs can produce truncated and dominantly acting proteins that harm cells. Eukaryotic cells protect themselves by degrading such mRNAs via the Nonsense-Mediated mRNA Decay (NMD) pathway. The precise reactions by which cells attack NMD target mRNAs remain obscure, precluding a mechanistic understanding of NMD and hampering therapeutic efforts to control NMD. A key step in NMD is the decay of the mRNA, which is proposed to occur via several competing models including deadenylation, exonucleolytic decay, and/or endonucleolytic decay. We set out to clarify the relative contributions of these decay mechanisms to NMD, and to identify the role of key factors. Here, we modify and deploy single-molecule nanopore mRNA sequencing to capture full-length NMD targets and their degradation intermediates, and we obtain single-molecule measures of splicing isoform, cleavage state, and poly(A) tail length. We observe robust endonucleolytic cleavage of NMD targets in vivo that depends on the nuclease SMG-6 and we use the occurence of cleavages to identify several known NMD targets. We show that NMD target mRNAs experience deadenylation, but similar to the extent that normal mRNAs experience as they enter the translational pool. Furthermore, we show that a factor (SMG-5) that historically was ascribed a function in deadenylation, is in fact required for SMG-6-mediated cleavage. Our results support a model in which NMD factors act in concert to degrade NMD targets in animals via an endonucleolytic cleavage near the stop codon, and suggest that deadenylation is a normal part of mRNA (and NMD target) maturation rather than a facet unique to NMD. Our work clarifies the route by which NMD target mRNAs are attacked in an animal.

Microfluidic design in single-cell sequencing and application to cancer precision medicine

Single-cell sequencing (SCS) is a crucial tool to reveal the genetic and functional heterogeneity of tumors, providing unique insights into the clonal evolution, microenvironment, drug resistance, and metastatic progression of cancers. Microfluidics is a critical component of many SCS technologies and workflows, conferring advantages in throughput, economy, and automation. Here, we review the current landscape of microfluidic architectures and sequencing techniques for single-cell omics analysis and highlight how these have enabled recent applications in oncology research. We also discuss the challenges and the promise of microfluidics-based single-cell analysis in the future of precision oncology.

Comparison of de novo assembly using long-read shotgun metagenomic sequencing of viruses in fecal and serum samples from marine mammals

Introduction

Viral diseases of marine mammals are difficult to study, and this has led to a limited knowledge on emerging known and unknown viruses which are ongoing threats to animal health. Viruses are the leading cause of infectious disease-induced mass mortality events among marine mammals.

Methods

In this study, we performed viral metagenomics in stool and serum samples from California sea lions (Zalophus californianus) and bottlenose dolphins (Tursiops truncates) using long-read nanopore sequencing. Two widely used long-read de novo assemblers, Canu and Metaflye, were evaluated to assemble viral metagenomic sequencing reads from marine mammals.

Results

Both Metaflye and Canu assembled similar viral contigs of vertebrates, such as Parvoviridae, and Poxviridae. Metaflye assembled viral contigs that aligned with one viral family that was not reproduced by Canu, while Canu assembled viral contigs that aligned with seven viral families that was not reproduced by Metaflye. Only Canu assembled viral contigs from dolphin and sea lion fecal samples that matched both protein and nucleotide RefSeq viral databases using BLASTx and BLASTn for Anelloviridae, Parvoviridae and Circoviridae families. Viral contigs assembled with Canu aligned with torque teno viruses and anelloviruses from vertebrate hosts. Viruses associated with invertebrate hosts including densoviruses, Ambidensovirus, and various Circoviridae isolates were also aligned. Some of the invertebrate and vertebrate viruses reported here are known to potentially cause mortality events and/or disease in different seals, sea stars, fish, and bivalve species.

Discussion

Canu performed better by producing the most viral contigs as compared to Metaflye with assemblies aligning to both protein and nucleotide databases. This study suggests that marine mammals can be used as important sentinels to surveil marine viruses that can potentially cause diseases in vertebrate and invertebrate hosts.

Benchmarking multi-platform sequencing technologies for human genome assembly

Genome assembly is a computational technique that involves piecing together deoxyribonucleic acid (DNA) fragments generated by sequencing technologies to create a comprehensive and precise representation of the entire genome. Generating a high-quality human reference genome is a crucial prerequisite for comprehending human biology, and it is also vital for downstream genomic variation analysis. Many efforts have been made over the past few decades to create a complete and gapless reference genome for humans by using a diverse range of advanced sequencing technologies. Several available tools are aimed at enhancing the quality of haploid and diploid human genome assemblies, which include contig assembly, polishing of contig errors, scaffolding and variant phasing. Selecting the appropriate tools and technologies remains a daunting task despite several studies have investigated the pros and cons of different assembly strategies. The goal of this paper was to benchmark various strategies for human genome assembly by combining sequencing technologies and tools on two publicly available samples (NA12878 and NA24385) from Genome in a Bottle. We then compared their performances in terms of continuity, accuracy, completeness, variant calling and phasing. We observed that PacBio HiFi long-reads are the optimal choice for generating an assembly with low base errors. On the other hand, we were able to produce the most continuous contigs with Oxford Nanopore long-reads, but they may require further polishing to improve on quality. We recommend using short-reads rather than long-reads themselves to improve the base accuracy of contigs from Oxford Nanopore long-reads. Hi-C is the best choice for chromosome-level scaffolding because it can capture the longest-range DNA connectedness compared to 10× linked-reads and Bionano optical maps. However, a combination of multiple technologies can be used to further improve the quality and completeness of genome assembly. For diploid assembly, hifiasm is the best tool for human diploid genome assembly using PacBio HiFi and Hi-C data. Looking to the future, we expect that further advancements in human diploid assemblers will leverage the power of PacBio HiFi reads and other technologies with long-range DNA connectedness to enable the generation of high-quality, chromosome-level and haplotype-resolved human genome assemblies.