Next-generation Sequencing Technologies Research Articles

Special clinical features with a novel mutation site of CHN1 gene in a Chinese family with Duane retraction syndrome

ABSTRACT Purpose This study is to describe the special clinical and genotypic features of a Chinese family with variant types of Duane retraction syndrome and to present our experience on managing these cases. Methods Four individuals from one family were reviewed by ophthalmologic examinations, in which two affected and two unaffected individuals were revealed. MRI scans were performed on the two patients. Relevant gene mutations were screened by the next-generation sequencing technology and confirmed by Sanger sequencing technology. Results The six-year-old proband presented with special clinical features of severe horizontal gaze dysfunction, exotropia and mild scoliosis. His mother showed significantly limited binocular abductions, with retraction of eyeballs in adduction. From MRI scans, abducens nerves were not observed in both patients and the oculomotor nerve was slightly thin in the proband. The proband and his mother shared the same CHN1 gene mutation site (c. 62A>G; p.Y21C). Strabismus surgery was performed on the proband to correct the primary gaze exotropia. (NM_001822: exon3 or NM_001025201: exon4: c. 62A>G; p.Y21C) Conclusions A novel CHN1 gene mutation was revealed from a Chinese family with Duane retraction syndrome. Remarkably, the proband and his mother presented different clinical features of ocular motility disorder. Strabismus correction surgery and amblyopia training helped to improve the appearance and visual function of the proband.

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation.

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, scaling to large sample sizes, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting 2 large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

The complete chloroplast genome sequence of Malus × adstringens Zabel ‘Hopa’ (Rosaceae)

Malus × adstringens Zabel ‘Hopa’ is an important crabapple cultivar with significant ornamental value. Here, we assembled its complete chloroplast (cp) genome using the next-generation sequencing technology to clarify the phylogenetic relationships in Malus. The total length of the complete chloroplast genome was 160,230 base pairs (bp) with a GC content of 36.50%, consisting of a large single-copy (LSC) region with a sequence length of 88,310 bp, a small single-copy (SSC) region with a sequence length of 19,196 bp, and a pair of inverted repeat (IR) regions of 26,362 bp. The complete chloroplast genome contained 128 genes, namely 84 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. In addition, 73 SSRs were found in the M. ‘Hopa’ cp genome. The phylogenetic relationship of M. ‘Hopa’ in Malus is closely related to M. spectabilis (Aiton) Borkh. and then to M. sieversii (Lebed.) M. Roem. Our results demonstrate that it is feasible to resolve the phylogenetic relationships of crabapple cultivars and identify their putative maternal lineages using cp genomic data.

Complete mitochondrial genome sequence of Butyriboletus hainanensis (Boletales, Basidiomycota)

Butyriboletus hainanensis, a macrofungus belonging to the Boletaceae family, is named after its collection location on Hainan Island, China. However, little is known about its mitochondrial genome and its phylogenetic relationship with other boletes. In this study, we utilized next-generation sequencing technology to sequence the mitochondrial genome of Bu. hainanensis. Our findings revealed that the mitochondrial genome of this species is presumably a circular DNA molecule spanning 36,592 bp. It consists of 15 protein-coding genes, 27 transfer RNA genes, and two ribosomal RNA genes. The base composition of the mitochondrial genome is as follows: A (36.64%), C (12.22%), G (11.73%), and T (39.41%), with a GC content of 23.95%. Additionally, a phylogenetic tree was constructed based on 22 mitochondrial genomes, which provided valuable insights into the phylogenetic relationships of Bu. hainanensis with other boletes for the first time.

Application of Next-Generation Sequencing Technology in Southeast Asia: A Practical Framework for Advancing Wildlife Conservation

Next-generation sequencing (NGS) has transformed genomics, presenting significant potential for advancing wildlife conservation. NGS technology offers opportunities and challenges for addressing scientific questions in wildlife management. Unfortunately, there is a lack of comprehensive records on NGS implementation in Southeast Asia, particularly concerning wildlife conservation. To address this gap, we analyzed NGS studies focused on wildlife monitoring in Southeast Asia and introduced a practical framework for implementing NGS technologies in global wildlife conservation, especially in Southeast Asia. We systematically reviewed NGS studies in wildlife monitoring from the SCOPUS database. We identified 137 relevant publications from 11 countries, with Malaysia contributing 36% of the studies. The included studies were categorized into five themes: species identification, dietary assessment, health monitoring, taxonomic resolution, and whole-genome sequencing, with the majority focusing on 38 publications related to wildlife health. The framework developed in this study help the researchers and conservation practitioners with insights on NGS technology application in conservation while also addressing the benefits, limitations, and ethical considerations associated with NGS use. This review offers a brief overview of NGS usage and provides guidelines for embracing NGS as a valuable tool for effective wildlife conservation strategies in our rapidly changing world.

Collagen of ancient bones gives an indication of endogenous DNA preservation based on next-generation sequencing technology

Collagen of ancient bones gives an indication of endogenous DNA preservation based on next-generation sequencing technology

Single-Cell Proteomics by Barcoded Phage-Displayed Screening via an Integrated Microfluidic Chip.

Recent advancements in the profiling of proteomes at the single-cell level necessitate the development of quantitative and versatile platforms, particularly for analyzing rare cells like circulating tumor cells (CTCs). In this chapter, we present an integrated microfluidic chip that utilizes magnetic nanoparticles to capture single tumor cells with exceptional efficiency. This chip enables on-chip incubation and facilitates in situ analysis of cell-surface protein expression. By combining phage-based barcoding with next-generation sequencing technology, we successfully monitored changes in the expression of multiple surface markers induced by CTC adherence. This innovative platform holds significant potential for comprehensive screening of multiple surface antigens simultaneously in rare cells, offering single-cell resolution. Consequently, it will contribute valuable insights into biological heterogeneity and human disease.

Update on functional analysis of long non-coding RNAs in common crops.

With the rapid advances in next-generation sequencing technology, numerous non-protein-coding transcripts have been identified, including long noncoding RNAs (lncRNAs), which are functional RNAs comprising more than 200 nucleotides. Although lncRNA-mediated regulatory processes have been extensively investigated in animals, there has been considerably less research on plant lncRNAs. Nevertheless, multiple studies on major crops showed lncRNAs are involved in crucial processes, including growth and development, reproduction, and stress responses. This review summarizes the progress in the research on lncRNA roles in several major crops, presents key strategies for exploring lncRNAs in crops, and discusses current challenges and future prospects. The insights provided in this review will enhance our comprehension of lncRNA functions in crops, with potential implications for improving crop genetics and breeding.

Current state of genetic analysis in multiple myeloma and future perspectives

Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells. Recent advances in next-generation sequencing technologies have facilitated in-depth genetic exploration of MM, unveiling a more comprehensive genomic landscape that extends beyond classical chromosomal alterations, such as IGH translocations and hyperdiploidy. These studies have elucidated recurrent mutations across various functional pathways including those involving MAPK, NF-κB, cell cycle regulation, and epigenetic modulation. With respect to clinical utility, studies have shown that the number of genetic alterations and biallelic events in TP53 are associated with worse prognosis, and CRBN mutations with resistance to immunomodulatory drugs. We recently analyzed the full landscape of genetic alterations in relapsed and refractory MM using circulating tumor DNA (ctDNA), revealing TP53 mutations as the most frequent driver mutation. Notably, more than half of TP53 mutations were present in only ctDNA, suggesting a subclonal origin. Mutations in six genes, including KRAS and TP53, were associated with poor progression-free survival. In addition, the number of ctDNA mutations was identified as a prognostic factor independent of IGH translocations and clinical factors. Here we summarize recent progress in genetic analysis of MM, focusing on clinical relevance.

Whole-Genome Bisulfite Sequencing Protocol for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and clinical questions. DNA methylation analysis bears the particular promise to supplement or replace biochemical and imaging-based tests for the next generation of personalized medicine. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here, we provide a detailed protocol based on a commercial kit for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. The protocol is based on the construction of sequencing libraries from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For analyses requiring a quantitative distinction between 5-methylcytosine and 5-hydroxymethylcytosines levels, an oxidation step is included in the same workflow to perform oxidative bisulfite sequencing (OxBs-Seq). In this case, two sequencing libraries will be generated and sequenced: a classic methylome following bisulfite conversion and analyzing modified cytosines (not distinguishing between methylated and hydroxymethylated cytosines) and a methylome analyzing only methylated cytosines, respectively. Hydroxymethylation levels are deduced from the differences between the two reactions. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human and plant samples and yields robust and reproducible results.

Aberrant mitochondrial dynamics in myeloid neoplasms

Age-related clonal hematopoiesis and myeloid malignancies arise from hematopoietic stem cells and progenitors with genetic abnormalities. Advances in next-generation sequencing technology have led to the identification of a wide variety of genetic alterations involved in disease onset. However, it remains unclear how diverse genetic alterations, lacking disease specificity, lead to the development of myeloid malignancies and the progression of clonal hematopoiesis. Mitochondrial abnormalities and their roles in various pathological conditions such as aging, inflammation, neurological diseases, cardiac diseases, and cancer have recently been revealed, and have garnered attention as new therapeutic targets. This review focuses on regulation of mitochondrial dynamics and outlines the role of mitochondria in myeloid malignancies and clonal hematopoiesis.

Genome-Wide Association Study of Preharvest Sprouting in Wheat.

Genome-wide association study (GWAS) is widely used to characterize genes or quantitative trait loci (QTLs) associated with preharvest sprouting and seed dormancy. GWAS can identify both previously discovered and novel QTLs across diverse genetic panels. The high-throughput SNP arrays or next-generation sequencing technologies have facilitated the identification of numerous genetic markers, thereby significantly enhancing the resolution of GWAS. Although various methods have been developed, the fundamental principles underlying these techniques remain constant. Here, we provide a basic technological flow to perform seed dormancy assay, followed by GWAS using population structure control, and compared itwith previous identified QTLs and genes.

Museomics allows comparative analyses of mitochondrial genomes in the family Gryllidae (Insecta, Orthoptera) and confirms its phylogenetic relationships.

Next-generation sequencing technology can now be used to sequence historical specimens from natural history collections, an approach referred to as museomics. The museomics allows obtaining molecular data from old museum-preserved specimens, a resource of biomolecules largely underexploited despite the fact that these specimens are often unique samples of nomenclatural types that can be crucial for resolving scientific questions. Despite recent technical progress, cricket mitogenomes are still scarce in the databases, with only a handful of new ones generated each year from freshly collected material. In this study, we used the genome skimming method to sequence and assemble three new complete mitogenomes representing two tribes of the cricket subfamily Eneopterinae: two were obtained from old, historical type material of Xenogryllus lamottei (68 years old) and X. maniema (80 years old), the third one from a freshly collected specimen of Nisitrus vittatus. We compared their genome organization and base composition, and reconstructed the molecular phylogeny of the family Gryllidae. Our study not only confirmed that the genome skimming method used by next generation sequencing allows us to efficiently obtain the whole mitogenome from dry-pinned historical specimens, but we also confirmed how promising it is for large-scale comparative studies of mitogenomes using resources from natural history collections. Used in a phylogenetic context the new mitogenomes attest that the mitogenomic data contain valuable information and also strongly support phylogenetic relationships at multiple time scales.

Evaluation of HLA typing content of next-generation sequencing datasets from family trios and individuals of arab ethnicity.

Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling.

Cancer treatment comes to age: from one-size-fits-all to next-generation sequencing (NGS) technologies.

Cancer is one of the leading causes of death worldwide and one of the greatest challenges in extending life expectancy. The paradigm of one-size-fits-all medicine has already given way to the stratification of patients by disease subtypes, clinical characteristics, and biomarkers (stratified medicine). The introduction of next-generation sequencing (NGS) in clinical oncology has made it possible to tailor cancer patient therapy to their molecular profiles. NGS is expected to lead the transition to precision medicine (PM), where the right therapeutic approach is chosen for each patient based on their characteristics and mutations. Here, we highlight how the NGS technology facilitates cancer treatment. In this regard, first, precision medicine and NGS technology are reviewed, and then, the NGS revolution in precision medicine is described. In the sequel, the role of NGS in oncology and the existing limitations are discussed. The available databases and bioinformatics tools and online servers used in NGS data analysis are also reviewed. The review ends with concluding remarks.

Multi-omics Resources for Understanding Gene Regulation in Response to ER Stress in Plants.

Proteotoxic stress of the endoplasmic reticulum (ER) is a potentially lethal condition that ensues when the biosynthetic capacity of the ER is overwhelmed. A sophisticated and largely conserved signaling, known as the unfolded protein response (UPR), is designed to monitor and alleviate ER stress. In plants, the emerging picture of gene regulation by the UPR now appears to be more complex than ever before, requiring multi-omics-enabled network-level approaches to be untangled. In the past decade, with an increasing access and decreasing costs of next-generation sequencing (NGS) and high-throughput protein-DNA interaction (PDI) screening technologies, multitudes of global molecular measurements, known as omics, have been generated and analyzed by the research community to investigate the complex gene regulation of plant UPR. In this chapter, we present a comprehensive catalog of omics resources at different molecular levels (transcriptomes, protein-DNA interactomes, and networks) along with the introduction of key concepts in experimental and computational tools in data generation and analyses. This chapter will serve as a starting point for both experimentalists and bioinformaticians to explore diverse omics datasets for their biological questions in the plant UPR, with likely applications also in other species for conserved mechanisms.

Techniques, procedures, and applications in host genetic analysis.

This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

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.

Microbial Formation on Different Biomedia Surface for Wastewater Treatment

Even though commercial plastic media such as Cosmoball successfully treated municipal wastewater without clogging, its inadequate surface area prevents its use for high biofilm growth rates. This study compares microbial formation on the activated carbon (AC)-coated and non-coated Cosmoball media by submerging four activated carbon AC-coated Cosmo balls and non-coated Cosmo balls in five-liter beakers containing municipal wastewater. The researchers then analyzed the surface morphology of the biofilms on the coated and non-coated surfaces and applied the next-generation sequencing (NGS) technology to the ecology of microbial-mediated processes. By Day 11, the AC-coated media showed a biofilm coverage of 95%, whereas the non-coated media had a biofilm coverage of about 70%. The research has demonstrated that the coated media has a four times higher surface area, thus saving as much as 50% of the aeration tank volume.

Study on advancement in bioinformatics for crop improvement: integrating genomics, phenomics, and machine learning

Bioinformatics has emerged as a vital tool in agriculture, performing an important role in crop improvement and precision agriculture. This review study explores the applications of bioinformatics in these areas, highlighting the importance of next-generation sequencing (NGS) and third-generation sequencing technologies like PacBio and ONT. The integration of bioinformatics and genomics has revolutionized crop improvement strategies, facilitating the creation of crop varieties that are more suitable for evolving climates. The review emphasizes the creation of integrated crop databases for managing large-scale genotype and phenotype data and discusses the role of bioinformatics in precision agriculture for optimizing resource usage and minimizing environmental impact. Multiomics technologies are highlighted for gaining insights into plant biology and facilitating informed decisions in crop improvement. Machine learning algorithms play a prominent role in interpreting diverse and complex datasets generated by imaging or sequencing, aiding in efficient plant phenotyping and the identification of associations between DNA sequences and traits. The review concludes by emphasizing the importance of collaboration, data integration, and the potential of bioinformatics in advancing agriculture.