The third generation sequencing: the advanced approach to genetic diseases

Detection of hemophilia a genetic variants using third-generation long-read sequencing

BACKGROUND

Hemophilia A (HA) is an X-linked recessive genetic disorder caused by pathogenic variations of the factor VIII -encoding gene, F8 gene. Due to the large size and diverse types of variations in the F8 gene, causative mutations in F8 cannot be simultaneously detected in one step by traditional molecular analysis, and genetic molecular diagnosis and prenatal screening of HA still face significant difficulties and challenges in clinical practice. Therefore, we aimed to develop and validate an efficient, accurate, and time-saving method for the genetic detection of HA.

METHODS

A comprehensive analysis of hemophilia A (CAHEA) method based on long-range PCR and long-read sequencing (LRS) was used to detect F8 gene mutations in 14 clinical HA samples. The LRS results were compared with those of the conventional methods to evaluate the accuracy and sensitivity of the proposed approach.

RESULTS

The CAHEA method successfully identified 14 F8 variants in all probands, including 3 small insertion deletions, 4 single nucleotide variants, and 7 intron 22 inversions in a "one-step" manner, of which 2 small deletions have not been reported previously. Moreover, this method provided an opportunity to analyze the mechanism of rearrangement and the pathogenicity of F8 variants. The LRS results were validated and found to be in 100% agreement with those obtained using the conventional method.

CONCLUSION

Our proposed LRS-based F8 gene detection method is an accurate and reproducible genetic screening and diagnostic method with significant clinical value. It provides efficient, comprehensive, and accurate genetic screening and diagnostic services for individuals at high risk of HA as well as for premarital and prenatal populations.

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.

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.

Clinical applications of metagenomics next-generation sequencing in infectious diseases

Infectious diseases are a great threat to human health. Rapid and accurate detection of pathogens is important in the diagnosis and treatment of infectious diseases. Metagenomics next-generation sequencing (mNGS) is an unbiased and comprehensive approach for detecting all RNA and DNA in a sample. With the development of sequencing and bioinformatics technologies, mNGS is moving from research to clinical application, which opens a new avenue for pathogen detection. Numerous studies have revealed good potential for the clinical application of mNGS in infectious diseases, especially in difficult-to-detect, rare, and novel pathogens. However, there are several hurdles in the clinical application of mNGS, such as: (1) lack of universal workflow validation and quality assurance; (2) insensitivity to high-host background and low-biomass samples; and (3) lack of standardized instructions for mass data analysis and report interpretation. Therefore, a complete understanding of this new technology will help promote the clinical application of mNGS to infectious diseases. This review briefly introduces the history of next-generation sequencing, mainstream sequencing platforms, and mNGS workflow, and discusses the clinical applications of mNGS to infectious diseases and its advantages and disadvantages.

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

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

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.

Third-generation sequencing identified a novel complex variant in a patient with rare alpha-thalassemia

BACKGROUND

Thalassemias represent some of the most common monogenic diseases worldwide and are caused by variations in human hemoglobin genes which disrupt the balance of synthesis between the alpha and beta globin chains. Thalassemia gene detection technology is the gold standard to achieve accurate detection of thalassemia, but in clinical practice, most of the tests are only for common genotypes, which can easily lead to missing or misdiagnosis of rare thalassemia genotypes.

CASE PRESENTATION

We present the case of an 18-year-old Chinese female with abnormal values of routine hematological indices who was admitted for genetic screening for thalassemia. Genomic DNA was extracted and used for the genetic assays. Gap polymerase chain reaction and agarose gel electrophoresis were performed to detect HBA gene deletions, while PCR-reverse dot blot hybridization was used to detect point mutations in the HBA and HBB genes. Next-generation sequencing and third-generation sequencing (TGS) were used to identify known and potentially novel genotypes of thalassemia. We identified a novel complex variant αHb WestmeadαHb Westmeadαanti3.7/-α3.7 in a patient with rare alpha-thalassemia.

CONCLUSIONS

Our study identified a novel complex variant that expands the thalassemia gene variants spectrum. Meanwhile, the study suggests that TGS could effectively improve the specificity of thalassemia gene detection, and has promising potential for the discovery of novel thalassemia genotypes, which could also improve the accuracy of genetic counseling. Couples who are thalassemia carriers have the opportunity to reduce their risk of having a child with thalassemia.

Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

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

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

Neonatal X-linked myotubular myopathy with a de novo mutation: A case report and literature review

X-linked myotubular myopathy (XLMTM) is a rare congenital myopathy. In February 2021, a male neonate was admitted to the West China Second University Hospital, Sichuan University, with clinical manifestations of hypotonia, accompanied by distinctive facial features, and requiring continuous ventilatory support. He was born prematurely at 36+2 weeks gestation and developed respiratory distress postnatally, followed by difficulty in weaning from mechanical ventilation. Additional clinical features included hypotonia of the limbs, swallowing dysfunction, and specific facial characteristics (elongated limbs, narrow face, high-arched palate, wrist drop, empty scrotum, elongated fingers/toes). Genetic testing confirmed the diagnosis of XLMTM. Whole-exome sequencing analysis of the family revealed no mutations in the father, paternal grandfather, or paternal grandmother, while the mother had a heterozygous mutation. The pathogenic mutation was identified as MTM1 gene (OMIM: 300415), chromosome position chrX-150649714, with a nucleotide change of c.868-2A>C. The patient exhibited typical facial features. Genetic testing is crucial for accurate diagnosis of XLMTM in infants presenting with abnormal muscle tone and distinctive facial features.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus

Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration

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

Identification of a novel 91.5 kb-deletion (αα)FJ in the α-globin gene cluster using single-molecule real-time (SMRT) sequencing

OBJECTIVES

To present a novel 91.5-kb deletion of the α-globin gene cluster (αα)FJ identified by genetic assay and prenatal diagnosis in a Chinese family.

SUBJECTS AND METHODS

The proband was a 34-year-old G3P1 (Gravida 3, Para 1) female at the gestational age of 21+ weeks with a history of an edematous fetus. A routine genetic assay (reverse dot blot hybridization, RDB) was performed to detect common thalassemia mutations. Multiplex ligation-dependent probe amplification (MLPA) and single-molecule real-time technology (SMRT) were used to detect rare thalassemia mutations.

RESULTS

The hematological phenotypes of the proband, her mother, elder sister, husband, daughter, and nephew were consistent with the phenotype of α-thalassemia trait. No mutations were found in these family members by RDB, except for the proband's husband who carried an α-globin gene deletion --SEA/αα. MLPA results showed that the proband and other α-thalassemia-suspected relatives had heterozygous deletions around the POLR3K-3-463nt, HS40-178nt, and HBA-HS40-382nt probes. The 5'-breakpoint was out of probe scope and could not be determined. SMRT was performed and a 91.5-kb deletion (NC_000016.10: g.39268_130758del) in the α-globin gene cluster (αα)FJ was identified in the proband and other suspected relatives, which could explain their phenotypes. At the proband's gestational age of 22+ weeks, an amniotic fluid sample was collected and analyzed. As only the 91.5-kb deletion (αα)FJ was identified in the fetus with RDB, MLPA, and SMRT. The proband was suggested to continue the pregnancy.

CONCLUSION

We first reported a 91.5-kb deletion (NC_000016.10: g.hg38-chr16:39268-_130758del) of the HS-40 region in the α-globin gene cluster (αα)FJ identified in a Chinese family. Since the HS-40 loss of heterozygosity in combination with the heterozygous deletion --SEA might result in Hb Bart's hydrops fetalis, routine genetic assay, and SMRT were recommended to individuals at risk for prenatal diagnosis.

Estimating genome-wide DNA methylation heterogeneity with methylation patterns

BACKGROUND

In a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment.

RESULTS

Here, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection.

CONCLUSIONS

We adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.

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.

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.

An Overview of Deep Generative Models in Functional and Evolutionary Genomics

Following the widespread use of deep learning for genomics, deep generative modeling is also becoming a viable methodology for the broad field. Deep generative models (DGMs) can learn the complex structure of genomic data and allow researchers to generate novel genomic instances that retain the real characteristics of the original dataset. Aside from data generation, DGMs can also be used for dimensionality reduction by mapping the data space to a latent space, as well as for prediction tasks via exploitation of this learned mapping or supervised/semi-supervised DGM designs. In this review, we briefly introduce generative modeling and two currently prevailing architectures, we present conceptual applications along with notable examples in functional and evolutionary genomics, and we provide our perspective on potential challenges and future directions.

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

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

Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases

Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs.

Screening of marine sediment-derived microorganisms and their bioactive metabolites: a review

Marine sediments are one of the largest habitats on Earth, and their unique ecology, such as high salinity, high pressure, and hypoxia, may activate certain silent genes in marine microbes, resulting in microbes, enzymes, active products, and specific metabolic pathways that can adapt to these specific ecological environments. Marine sediment-derived microorganisms and their bioactive metabolites are of great significance and have potential commercial development prospects for food, pharmaceutical, chemical industries, agriculture, environmental protection and human nutrition and health. In recent years, although there have been numerous scientific reports surrounding marine sediment-derived microorganisms and their bioactive metabolites, a comprehensive review of their research progress is lacking. This paper presents the development and renewal of traditional culture-dependent and omics analysis techniques and their application to the screening of marine sediment-derived microorganisms producing bioactive substances. It also highlights recent research advances in the last five years surrounding the types, functional properties and potential applications of bioactive metabolites produced by marine sediment-derived microorganisms. These bioactive metabolites mainly include antibiotics, enzymes, enzyme inhibitors, sugars, proteins, peptides, and some other small molecule metabolites. In addition, the review ends with concluding remarks on the challenges and future directions for marine sediment-derived microorganisms and their bioactive metabolites. The review report not only helps to deepen the understanding of marine sediment-derived microorganisms and their bioactive metabolites, but also provides some useful information for the exploitation and utilization of marine microbial resources and the mining of new compounds with potential functional properties.

Intra-Host Co-Existing Strains of SARS-CoV-2 Reference Genome Uncovered by Exhaustive Computational Search

The COVID-19 pandemic caused by SARS-CoV-2 has had a severe impact on people worldwide. The reference genome of the virus has been widely used as a template for designing mRNA vaccines to combat the disease. In this study, we present a computational method aimed at identifying co-existing intra-host strains of the virus from RNA-sequencing data of short reads that were used to assemble the original reference genome. Our method consisted of five key steps: extraction of relevant reads, error correction for the reads, identification of within-host diversity, phylogenetic study, and protein binding affinity analysis. Our study revealed that multiple strains of SARS-CoV-2 can coexist in both the viral sample used to produce the reference sequence and a wastewater sample from California. Additionally, our workflow demonstrated its capability to identify within-host diversity in foot-and-mouth disease virus (FMDV). Through our research, we were able to shed light on the binding affinity and phylogenetic relationships of these strains with the published SARS-CoV-2 reference genome, SARS-CoV, variants of concern (VOC) of SARS-CoV-2, and some closely related coronaviruses. These insights have important implications for future research efforts aimed at identifying within-host diversity, understanding the evolution and spread of these viruses, as well as the development of effective treatments and vaccines against them.

Retinitis Pigmentosa: Current Clinical Management and Emerging Therapies

Retinitis pigmentosa (RP) comprises a group of inherited retinal dystrophies characterized by the degeneration of rod photoreceptors, followed by the degeneration of cone photoreceptors. As a result of photoreceptor degeneration, affected individuals experience gradual loss of visual function, with primary symptoms of progressive nyctalopia, constricted visual fields and, ultimately, central vision loss. The onset, severity and clinical course of RP shows great variability and unpredictability, with most patients already experiencing some degree of visual disability in childhood. While RP is currently untreatable for the majority of patients, significant efforts have been made in the development of genetic therapies, which offer new hope for treatment for patients affected by inherited retinal dystrophies. In this exciting era of emerging gene therapies, it remains imperative to continue supporting patients with RP using all available options to manage their condition. Patients with RP experience a wide variety of physical, mental and social-emotional difficulties during their lifetime, of which some require timely intervention. This review aims to familiarize readers with clinical management options that are currently available for patients with RP.

Translational Bioinformatics Applied to the Study of Complex Diseases

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: "How does TBI provide a scientific understanding of complex diseases?" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

Next generation sequencing technologies to explore the diversity of germplasm resources: achievements and trends in tomato

Tomato is one of the major vegetable crops grown worldwide and a model species for genetic and biological research. Progress in genomic technologies made possible the development of forefront methods for high-scale sequencing, providing comprehensive insight into the genetic architecture of germplasm resources. This review revisits next-generation sequencing strategies and applications to investigate the diversity of tomato, describing the common platforms used for SNP genotyping of large collections, de novo sequencing, and whole genome resequencing. Significant findings in evolutionary history are outlined, thus discussing how genomics has provided new hints about the processes behind domestication. Finally, achievement and perspectives on pan-genome construction and graphical pan-genome development toward precise mining of the natural variation to be exploited for breeding purposes are presented.

DNA methylation episignatures: insight into copy number variation

In this review we discuss epigenetic disorders that result from aberrations in genes linked to epigenetic regulation. We describe current testing methods for the detection of copy number variants (CNVs) in Mendelian disorders, dosage sensitivity, reciprocal phenotypes and the challenges of test selection and overlapping clinical features in genetic diagnosis. We discuss aberrations of DNA methylation and propose a role for episignatures as a novel clinical testing method in CNV disorders. Finally, we postulate that episignature mapping in CNV disorders may provide novel insights into the molecular mechanisms of disease and unlock key findings of the genome-wide impact on disease gene networks.

Genome sequence assembly algorithms and misassembly identification methods

The sequence assembly algorithms have rapidly evolved with the vigorous growth of genome sequencing technology over the past two decades. Assembly mainly uses the iterative expansion of overlap relationships between sequences to construct the target genome. The assembly algorithms can be typically classified into several categories, such as the Greedy strategy, Overlap-Layout-Consensus (OLC) strategy, and de Bruijn graph (DBG) strategy. In particular, due to the rapid development of third-generation sequencing (TGS) technology, some prevalent assembly algorithms have been proposed to generate high-quality chromosome-level assemblies. However, due to the genome complexity, the length of short reads, and the high error rate of long reads, contigs produced by assembly may contain misassemblies adversely affecting downstream data analysis. Therefore, several read-based and reference-based methods for misassembly identification have been developed to improve assembly quality. This work primarily reviewed the development of DNA sequencing technologies and summarized sequencing data simulation methods, sequencing error correction methods, various mainstream sequence assembly algorithms, and misassembly identification methods. A large amount of computation makes the sequence assembly problem more challenging, and therefore, it is necessary to develop more efficient and accurate assembly algorithms and alternative algorithms.

Case Report: The third-generation sequencing confirmed a novel 7.2 Kb deletion at β-globin gene in a patient with rare β-thalassemia

Background: Thalassemia was the most common monogenic diseases worldwide, which was caused by mutations, deletions or duplications in human globin genes which disturbed the synthesis balance between α- and β-globin chains of hemoglobin. There were many classics methods to diagnose thalassemia, but all of them had limitations. Although variations in the human β-globin gene cluster were mainly point mutations, novel large deletions had been described in recent years along with the development of DNA sequencing technology.

Case report: We present a case of 32-year-old male with abnormal hematological results. However, 23 genotypes of the most common thalassemia were not detected by two independent conventional platforms. Finally, using multiplex ligation-dependent probe amplification (MLPA), third-generation sequencing (TGS) and Gap PCR detection methods, we first confirmed the case with a novel 7.2 Kb deletion (Chr11:5222800-5230034, hg38) located at HBB gene.

Conclusion: Our results showed that TGS technology was a powerful tool for thalassemia breakpoint detection, had promising potentiality in genetic screening of novel thalassemia, especially for the novel deletions in globin genes.

Application of the Single-Molecule Real-Time Technology (SMRT) for Identification of HKαα Thalassemia Allele

OBJECTIVE

Single-molecule real-time technology (SMRT) is a sequencing technology using the DNA polymerases and fluorescently tagged nucleotides to accurately sequence DNA strands. The purpose of this study was to evaluate the detection accuracy of SMRT for identification of the Hong Kongαα (HKαα) thalassemia allele.

METHODS

We conducted a blinded study of 33 samples of known HKαα alleles. These alleles were detected using SMRT to evaluate accuracy.

RESULTS

We conducted a blinded study of 33 known HKαα samples and found all HKαα variants detected by SMRT to be concordant with those independently assigned by gap-polymerase chain reaction (gap-PCR), reverse dot blot hybridization, and 2-round nested PCR. In addition, SMRT detected 2 β-thalassemia variants that were missed by conventional techniques.

CONCLUSION

The results demonstrate that SMRT offers a higher detection accuracy of thalassemia rare and new loci. It is an efficient, reliable, and broad-spectrum test that can be widely used for thalassemia screening in the clinic.

Listeria monocytogenes in foods-From culture identification to whole-genome characteristics

Listeria monocytogenes is an important foodborne pathogen, which is able to persist in the food production environments. The presence of these bacteria in different niches makes them a potential threat for public health. In the present review, the current information on the classical and alternative methods used for isolation and identification of L. monocytogenes in food have been described. Although these techniques are usually simple, standardized, inexpensive, and are routinely used in many food testing laboratories, several alternative molecular-based approaches for the bacteria detection in food and food production environments have been developed. They are characterized by the high sample throughput, a short time of analysis, and cost-effectiveness. However, these methods are important for the routine testing toward the presence and number of L. monocytogenes, but are not suitable for characteristics and typing of the bacterial isolates, which are crucial in the study of listeriosis infections. For these purposes, novel approaches, with a high discriminatory power to genetically distinguish the strains during epidemiological studies, have been developed, e.g., whole-genome sequence-based techniques such as NGS which provide an opportunity to perform comparison between strains of the same species. In the present review, we have shown a short description of the principles of microbiological, alternative, and modern methods of detection of L. monocytogenes in foods and characterization of the isolates for epidemiological purposes. According to our knowledge, similar comprehensive papers on such subject have not been recently published, and we hope that the current review may be interesting for research communities.

Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing

Nanopore sequencing has brought the technology to the next generation in the science of sequencing. This is achieved through research advancing on: pore efficiency, creating mechanisms to control DNA translocation, enhancing signal-to-noise ratio, and expanding to long-read ranges. Heterogeneity regarding epigenetics would be broad as mutations in the epigenome are sensitive to cause new challenges in cancer research. Epigenetic enzymes which catalyze DNA methylation and histone modification are dysregulated in cancer cells and cause numerous heterogeneous clones to evolve. Detection of this heterogeneity in these clones plays an indispensable role in the treatment of various cancer types. With single-cell profiling, the nanopore sequencing technology could provide a simple sequence at long reads and is expected to be used soon at the bedside or doctor's office. Here, we review the advancements of nanopore sequencing and its use in the detection of epigenetic heterogeneity in cancer.

Advances and Trends in Omics Technology Development

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to the concept of “omics” and methodological advancement in systematically interrogating a cellular system. Yet, the ever-growing types of molecules and regulatory mechanisms being discovered have been persistently transforming our understandings on the cellular machinery. This renders cell omics seemingly, like the universe, expand with no limit and our goal toward the complete harness of the cellular system merely impossible. Therefore, it is imperative to review what has been done and is being done to predict what can be done toward the translation of omics information to disease control with minimal cell perturbation. With a focus on the “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies of these omics together with their epiomics and interactomics, and review technologies developed for interrogation. We predict, among others, redoxomics as an emerging omics layer that views cell decision toward the physiological or pathological state as a fine-tuned redox balance.

Compilation of parasitic immunogenic proteins from 30 years of published research using machine learning and natural language processing

The World Health Organisation reported in 2020 that six of the top 10 sources of death in low-income countries are parasites. Parasites are microorganisms in a relationship with a larger organism, the host. They acquire all benefits at the host’s expense. A disease develops if the parasitic infection disrupts normal functioning of the host. This disruption can range from mild to severe, including death. Humans and livestock continue to be challenged by established and emerging infectious disease threats. Vaccination is the most efficient tool for preventing current and future threats. Immunogenic proteins sourced from the disease-causing parasite are worthwhile vaccine components (subunits) due to reliable safety and manufacturing capacity. Publications with ‘subunit vaccine’ in their title have accumulated to thousands over the last three decades. However, there are possibly thousands more reporting immunogenicity results without mentioning ‘subunit’ and/or ‘vaccine’. The exact number is unclear given the non-standardised keywords in publications. The study aim is to identify parasite proteins that induce a protective response in an animal model as reported in the scientific literature within the last 30 years using machine learning and natural language processing. Source code to fulfil this aim and the vaccine candidate list obtained is made available.

SMRT Sequencing Reveals Candidate Genes and Pathways With Medicinal Value in Cipangopaludina chinensis

Cipangopaludina chinensis is an economically important aquatic snail with high medicinal value. However, molecular biology research on C. chinensis is limited by the lack of a reference genome, so the analysis of its transcripts is an important step to study the regulatory genes of various substances in C. chinensis. Herein, we conducted the first full-length transcriptome analysis of C. chinensis using PacBio single-molecule real-time (SMRT) sequencing technology. We identified a total of 26,312 unigenes with an average length of 2,572 bp, of which the largest number of zf-c2h2 transcription factor families (120,18.24%) were found, and also observed that the majority of the 8,058 SSRs contained 4-7 repeat units, which provided data for subsequent work on snail genetics Subsequently, 91.86% (24,169) of the genes were successfully annotated to the four major databases, while the highest homology was observed with Pomacea canaliculata. Functional annotation revealed that the majority of transcripts were enriched in metabolism, signal transduction and Immune-related pathways, and several candidate genes involved in drug metabolism and immune response were identified (e.g., CYP1A1, CYP2J, CYP2U1, GST, ,PIK3, PDE3A, PRKAG). This study lays a foundation for future molecular biology research and provides a reference for studying genes associated with the medicinal value of C. chinensis.

Paving the Way: Contributions of Big Data to Apicomplexan and Kinetoplastid Research

In the age of big data an important question is how to ensure we make the most out of the resources we generate. In this review, we discuss the major methods used in Apicomplexan and Kinetoplastid research to produce big datasets and advance our understanding of Plasmodium, Toxoplasma, Cryptosporidium, Trypanosoma and Leishmania biology. We debate the benefits and limitations of the current technologies, and propose future advancements that may be key to improving our use of these techniques. Finally, we consider the difficulties the field faces when trying to make the most of the abundance of data that has already been, and will continue to be, generated.

Microbiome: A forgotten target of environmental micro(nano)plastics?

Microplastics (MPs) and nanoplastics (NPs) are emerging pollutants in different environmental compartments (air, soil and water) and that may induce several ecotoxicological effects on organisms and their microbiota. A considerable number of studies has been addressing and highlighting the effects of MPs/NPs on biochemical, molecular and behavior effects of aquatic organisms. However, less attention has been focused on microbiota. Here, a critical overview of published studies focusing on microorganisms affected by MPs and NPs after in vitro or in vivo exposure is provided. Available studies regarding the properties of MPs/NPs, microbial phyla, experimental conditions, techniques employed, and effects are summarized. The link between microbiota disruption and other effects on other hosts (e.g., crustaceans, fish, and mammals) as also analyzed. Overall, the literature review shows that most studies with microorganisms were performed in vitro (MPs: 44.11%; NPs: 23.52%) in comparison with in vivo tests (MPs: 32.35%; NPs: 11.76%). The most studied MP/NPs were polystyrene particles, generally spheres, with sizes <50 μm and concentrations ranged between 100 and 1000 mg L^-1. The most studied main phyla were Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. MPs/NPs induced microbiome composition disruption, immune response (i.e., immune modulator release, immune cells activation and inflammatory response), enzyme activity changes (i.e., catalase, urease, dehydrogenase, alkaline phosphatase, and fluorescein diacetate hydrolase) and gene expression changes. The immune responses changes were related to microbiome disruption. Research gaps are highlighted and recommendations for future research indicated that microbiome is sensitive to MP/NPs and microbiome disruption can be a valuable tool to assess the risk of plastic particles to human and environmental health.

Innovative in Silico Approaches for Characterization of Genes and Proteins

Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.

Third-generation sequencing: A novel tool detects complex variants in the α-thalassemia gene

OBJECTIVE

Thalassemia is a monogenic disorder with a high carrier rate in the southern region of China. Most laboratories currently follow the protocol of testing hematologic indicators in individuals with positive hematologic indicators and then using the hot-spot mutation test kit. A novel thalassemia gene test is performed if there is a mismatch between the hematology and hot-spot mutation test results. However, due to the large population in southern China, some individuals carry complex α-globin gene cluster (CAGC) variants in NG_000006.1, which are difficult to detect using conventional thalassemia genetic analysis protocols, leading to missed or false genetic test results for individuals carrying these complex α-globin gene cluster variants. When an individual carries a complex α-thalassemia gene variant, and an individual carries a β- thalassemia gene variant, there may be clinical symptoms that might complicate clinical consultation and prenatal diagnosis if not accurately detected. Third-generation sequencing (TGS) enables long-read single-molecule sequencing with high detection accuracy, and long-length DNA chain reads in high-fidelity reads mode. TGS can be used to analyze high homology and rich GC DNA sequences.

RESULTS

Four samples that showed abnormalities in the thalassemia genetic test were studied using TGS, revealing that they carried genotypes with complex α-globin gene cluster variants, one of which was a complex variant αα anti3.7 α anti3.7 α 17.2.

CONCLUSIONS

TGS detects complex α-globin gene cluster variants. This study may provide a reference protocol for the use of TGS for the detection of complex α-globin gene cluster variants. TGS can reveal individuals with complex α-thalassemia genotypes in the population and improve the accuracy of genetic counseling and prenatal diagnosis.

Detecting structural variations with precise breakpoints using low-depth WGS data from a single oxford nanopore MinION flowcell

Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (specifically, 4×) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, particularly pathogenic SV for supporting clinical diagnosis. When using 4× ONT WGS data, existing SV calling software often fails to detect pathogenic SV, especially in the form of long deletion, terminal deletion, duplication, and unbalanced translocation. Our new SV calling software SENSV can achieve high sensitivity for all types of SV and a breakpoint precision typically ± 100 bp; both features are important for clinical concerns. The improvement achieved by SENSV stems from several new algorithms. We evaluated SENSV and other software using both real and simulated data. The former was based on 24 patient samples, each diagnosed with a genetic disorder. SENSV found the pathogenic SV in 22 out of 24 cases (all heterozygous, size from hundreds of kbp to a few Mbp), reporting breakpoints within 100 bp of the true answers. On the other hand, no existing software can detect the pathogenic SV in more than 10 out of 24 cases, even when the breakpoint requirement is relaxed to ± 2000 bp.

Next-Generation Sequencing for Confronting Virus Pandemics

Virus pandemics have happened, are happening and will happen again. In recent decades, the rate of zoonotic viral spillover into humans has accelerated, mirroring the expansion of our global footprint and travel network, including the expansion of viral vectors and the destruction of natural spaces, bringing humans closer to wild animals. Once viral cross-species transmission to humans occurs, transmission cannot be stopped by cement walls but by developing barriers based on knowledge that can prevent or reduce the effects of any pandemic. Controlling a local transmission affecting few individuals is more efficient that confronting a community outbreak in which infections cannot be traced. Genetic detection, identification, and characterization of infectious agents using next-generation sequencing (NGS) has been proven to be a powerful tool allowing for the development of fast PCR-based molecular assays, the rapid development of vaccines based on mRNA and DNA, the identification of outbreaks, transmission dynamics and spill-over events, the detection of new variants and treatment of vaccine resistance mutations, the development of direct-acting antiviral drugs, the discovery of relevant minority variants to improve knowledge of the viral life cycle, strengths and weaknesses, the potential for becoming dominant to take appropriate preventive measures, and the discovery of new routes of viral transmission.

ECNano: A cost-effective workflow for target enrichment sequencing and accurate variant calling on 4800 clinically significant genes using a single MinION flowcell

BACKGROUND

The application of long-read sequencing using the Oxford Nanopore Technologies (ONT) MinION sequencer is getting more diverse in the medical field. Having a high sequencing error of ONT and limited throughput from a single MinION flowcell, however, limits its applicability for accurate variant detection. Medical exome sequencing (MES) targets clinically significant exon regions, allowing rapid and comprehensive screening of pathogenic variants. By applying MES with MinION sequencing, the technology can achieve a more uniform capture of the target regions, shorter turnaround time, and lower sequencing cost per sample.

METHOD

We introduced a cost-effective optimized workflow, ECNano, comprising a wet-lab protocol and bioinformatics analysis, for accurate variant detection at 4800 clinically important genes and regions using a single MinION flowcell. The ECNano wet-lab protocol was optimized to perform long-read target enrichment and ONT library preparation to stably generate high-quality MES data with adequate coverage. The subsequent variant-calling workflow, Clair-ensemble, adopted a fast RNN-based variant caller, Clair, and was optimized for target enrichment data. To evaluate its performance and practicality, ECNano was tested on both reference DNA samples and patient samples.

RESULTS

ECNano achieved deep on-target depth of coverage (DoC) at average > 100× and > 98% uniformity using one MinION flowcell. For accurate ONT variant calling, the generated reads sufficiently covered 98.9% of pathogenic positions listed in ClinVar, with 98.96% having at least 30× DoC. ECNano obtained an average read length of 1000 bp. The long reads of ECNano also covered the adjacent splice sites well, with 98.5% of positions having ≥ 30× DoC. Clair-ensemble achieved > 99% recall and accuracy for SNV calling. The whole workflow from wet-lab protocol to variant detection was completed within three days.

CONCLUSION

We presented ECNano, an out-of-the-box workflow comprising (1) a wet-lab protocol for ONT target enrichment sequencing and (2) a downstream variant detection workflow, Clair-ensemble. The workflow is cost-effective, with a short turnaround time for high accuracy variant calling in 4800 clinically significant genes and regions using a single MinION flowcell. The long-read exon captured data has potential for further development, promoting the application of long-read sequencing in personalized disease treatment and risk prediction.

Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species

Pangenomes are a rich resource to examine the genomic variation observed within a species or genera, supporting population genetics studies, with applications for the improvement of crop traits. Major crop species such as maize (Zea mays), rice (Oryza sativa), Brassica (Brassica spp.), and soybean (Glycine max) have had pangenomes constructed and released, and this has led to the discovery of valuable genes associated with disease resistance and yield components. However, pangenome data are not available for many less prominent crop species that are currently under-utilised. Despite many under-utilised species being important food sources in regional populations, the scarcity of genomic data for these species hinders their improvement. Here, we assess several under-utilised crops and review the pangenome approaches that could be used to build resources for their improvement. Many of these under-utilised crops are cultivated in arid or semi-arid environments, suggesting that novel genes related to drought tolerance may be identified and used for introgression into related major crop species. In addition, we discuss how previously collected data could be used to enrich pangenome functional analysis in genome-wide association studies (GWAS) based on studies in major crops. Considering the technological advances in genome sequencing, pangenome references for under-utilised species are becoming more obtainable, offering the opportunity to identify novel genes related to agro-morphological traits in these species.

Advancements in detection and removal of antibiotic resistance genes in sludge digestion: A state-of-art review

Sludge from wastewater treatment plants can act as a repository and crucial environmental provider of antibiotic resistance genes (ARGs). Over the past few years, people's knowledge regarding the occurrence and removal of ARGs in sludge has broadened remarkably with advancements in molecular biological techniques. Anaerobic and aerobic digestion were found to effectively achieve sludge reduction and ARGs removal. This review summarized advanced detection and removal techniques of ARGs, in the last decade, in the sludge digestion field. The fate of ARGs due to different sludge digestion strategies (i.e., anaerobic and aerobic digestion under mesophilic or thermophilic conditions, and in combination with relevant pretreatment technologies (e.g., thermal hydrolysis pretreatment, microwave pretreatment and alkaline pretreatment) and additives (e.g., ferric chloride and zero-valent iron) were systematically summarized and compared in this review. To date, this is the first review that provides a comprehensive assessment of the state-of-the-art technologies and future recommendations.

Decrypting the complexity of the human malaria parasite biology through systems biology approaches

The human malaria parasite, Plasmodium falciparum, is a unicellular protozoan responsible for over half a million deaths annually. With a complex life cycle alternating between human and invertebrate hosts, this apicomplexan is notoriously adept at evading host immune responses and developing resistance to all clinically administered treatments. Advances in omics-based technologies, increased sensitivity of sequencing platforms and enhanced CRISPR based gene editing tools, have given researchers access to more in-depth and untapped information about this enigmatic micro-organism, a feat thought to be infeasible in the past decade. Here we discuss some of the most important scientific achievements made over the past few years with a focus on novel technologies and platforms that set the stage for subsequent discoveries. We also describe some of the systems-based methods applied to uncover gaps of knowledge left through single-omics applications with the hope that we will soon be able to overcome the spread of this life-threatening disease.

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

Although next-generation sequencing (NGS) technology revolutionized sequencing, offering a tremendous sequencing capacity with groundbreaking depth and accuracy, it continues to demonstrate serious limitations. In the early 2010s, the introduction of a novel set of sequencing methodologies, presented by two platforms, Pacific Biosciences (PacBio) and Oxford Nanopore Sequencing (ONT), gave birth to third-generation sequencing (TGS). The innovative long-read technologies turn genome sequencing into an ease-of-handle procedure by greatly reducing the average time of library construction workflows and simplifying the process of de novo genome assembly due to the generation of long reads. Long sequencing reads produced by both TGS methodologies have already facilitated the decipherment of transcriptional profiling since they enable the identification of full-length transcripts without the need for assembly or the use of sophisticated bioinformatics tools. Long-read technologies have also provided new insights into the field of epitranscriptomics, by allowing the direct detection of RNA modifications on native RNA molecules. This review highlights the advantageous features of the newly introduced TGS technologies, discusses their limitations and provides an in-depth comparison regarding their scientific background and available protocols as well as their potential utility in research and clinical applications.

Technological Approaches in the Analysis of Extracellular Vesicle Nucleotide Sequences

Together with metabolites, proteins, and lipid components, the EV cargo consists of DNA and RNA nucleotide sequence species, which are part of the intracellular communication network regulating specific cellular processes and provoking distinct target cell responses. The extracellular vesicle (EV) nucleotide sequence cargo molecules are often investigated in association with a particular pathology and may provide an insight into the physiological and pathological processes in hard-to-access organs and tissues. The diversity and biological function of EV nucleotide sequences are distinct regarding EV subgroups and differ in tissue- and cell-released EVs. EV DNA is present mainly in apoptotic bodies, while there are different species of EV RNAs in all subgroups of EVs. A limited sample volume of unique human liquid biopsy provides a small amount of EVs with limited isolated DNA and RNA, which can be a challenging factor for EV nucleotide sequence analysis, while the additional difficulty is technical variability of molecular nucleotide detection. Every EV study is challenged with its first step of the EV isolation procedure, which determines the EV's purity, yield, and diameter range and has an impact on the EV's downstream analysis with a significant impact on the final result. The gold standard EV isolation procedure with ultracentrifugation provides a low output and not highly pure isolated EVs, while modern techniques increase EV's yield and purity. Different EV DNA and RNA detection techniques include the PCR procedure for nucleotide sequence replication of the molecules of interest, which can undergo a small-input EV DNA or RNA material. The nucleotide sequence detection approaches with their advantages and disadvantages should be considered to appropriately address the study problem and to extract specific EV nucleotide sequence information with the detection using qPCR or next-generation sequencing. Advanced next-generation sequencing techniques allow the detection of total EV genomic or transcriptomic data even at the single-molecule resolution and thus, offering a sensitive and accurate EV DNA or RNA biomarker detection. Additionally, with the processes where the EV genomic or transcriptomic data profiles are compared to identify characteristic EV differences in specific conditions, novel biomarkers could be discovered. Therefore, a suitable differential expression analysis is crucial to define the EV DNA or RNA differences between conditions under investigation. Further bioinformatics analysis can predict molecular cell targets and identify targeted and affected cellular pathways. The prediction target tools with functional studies are essential to help specify the role of the investigated EV-targeted nucleotide sequences in health and disease and support further development of EV-related therapeutics. This review will discuss the biological diversity of human liquid biopsy-obtained EV nucleotide sequences DNA and RNA species reported as potential biomarkers in health and disease and methodological principles of their detection, from human liquid biopsy EV isolation, EV nucleotide sequence extraction, techniques for their detection, and their cell target prediction.