Landscape of next-generation sequencing technologies

Storage-D: A user-friendly platform that enables practical and personalized DNA data storage

Deoxyribonucleic acid (DNA) has been suggested as a very promising medium for data storage in recent years. Although numerous studies have advocated for DNA data storage, its practical application remains obscure and there is a lack of a user-oriented platform. Here, we developed a DNA data storage platform, named Storage-D, which allows users to convert their data into DNA sequences of any length and vice versa by selecting algorithms, error-correction, random-access, and codec pin strategies in terms of their own choice. It incorporates a newly designed "Wukong" algorithm, which provides over 20 trillion codec pins for data privacy use. This algorithm can also control GC content to the selected standard, as well as adjust the homopolymer run length to a defined level, while maintaining a high coding potential of ~1.98 bis/nt, allowing it to outperform previous algorithms. By connecting to a commercial DNA synthesis and sequencing platform with "Storage-D," we successfully stored "Diagnosis and treatment protocol for COVID-19 patients" into 200 nt oligo pools in vitro, and 500 bp genes in vivo which replicated in both normal and extreme bacteria. Together, this platform allows for practical and personalized DNA data storage, potentially with a wide range of applications.

Quantifying transcriptome diversity: a review

Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.

Optical nanomaterial-based detection of biomarkers in liquid biopsy

Liquid biopsy, which is a minimally invasive procedure as an alternative to tissue biopsy, has been introduced as a new diagnostic/prognostic measure. By screening disease-related markers from the blood or other biofluids, it promises early diagnosis, timely prognostication, and effective treatment of the diseases. However, there will be a long way until its realization due to its conceptual and practical challenges. The biomarkers detected by liquid biopsy, such as circulating tumor cell (CTC) and circulating tumor DNA (ctDNA), are extraordinarily rare and often obscured by an abundance of normal cellular components, necessitating ultra-sensitive and accurate detection methods for the advancement of liquid biopsy techniques. Optical biosensors based on nanomaterials open an important opportunity in liquid biopsy because of their enhanced sensing performance with simple and practical properties. In this review article, we summarized recent innovations in optical nanomaterials to demonstrate the sensitive detection of protein, peptide, ctDNA, miRNA, exosome, and CTCs. Each study prepares the optical nanomaterials with a tailored design to enhance the sensing performance and to meet the requirements of each biomarker. The unique optical characteristics of metallic nanoparticles (NPs), quantum dots, upconversion NPs, silica NPs, polymeric NPs, and carbon nanomaterials are exploited for sensitive detection mechanisms. These recent advances in liquid biopsy using optical nanomaterials give us an opportunity to overcome challenging issues and provide a resource for understanding the unknown characteristics of the biomarkers as well as the mechanism of the disease.

A dual-rule encoding DNA storage system using chaotic mapping to control GC content

MOTIVATION

DNA as a novel storage medium is considered an effective solution to the world's growing demand for information due to its high density and long-lasting reliability. However, early coding schemes ignored the biologically constrained nature of DNA sequences in pursuit of high density, leading to DNA synthesis and sequencing difficulties. This article proposes a novel DNA storage coding scheme. The system encodes half of the binary data using each of the two GC-content complementary encoding rules to obtain a DNA sequence.

RESULTS

After simulating the encoding of representative document and image file formats, a DNA sequence strictly conforming to biological constraints was obtained, reaching a coding potential of 1.66 bit/nt. In the decoding process, a mechanism to prevent error propagation was introduced. The simulation results demonstrate that by adding Reed-Solomon code, 90% of the data can still be recovered after introducing a 2% error, proving that the proposed DNA storage scheme has high robustness and reliability. Availability and implementation: The source code for the codec scheme of this paper is available at https://github.com/Mooreniah/DNA-dual-rule-rotary-encoding-storage-system-DRRC.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Overview on century progress in research on mosaic disease of apple (Malus domestica Borkh) incited by apple mosaic virus/apple necrotic mosaic virus

Apple mosaic is widely distributed disease throughout the apple growing regions leading to the major adverse effects both qualitatively and quantitatively. Earlier the apple mosaic virus-ApMV was regarded as the only causal agent of the disease, but recently a novel virus apple necrotic mosaic virus-ApNMV have been reported as the causal pathogen from various apple growing countries. Accurate diagnosis of disease and detection of ApMV and ApNMV are of utmost importance, because without this ability we can neither understand nor control this disease. Both the viruses are mostly controlled through quarantine, isolation, sanitation and certification programs depending on sensitive and specific detection methods available. Here we review the 100-year progress in research on apple mosaic disease, which includes history, yield losses, causal agents, their genome organization, replication, traditional to recent detection methods, transmission, distribution and host range of associated viruses and management of the disease.

Sequence Alignment/Map format: a comprehensive review of approaches and applications

The Sequence Alignment/Map (SAM) format file is the text file used to record alignment information. Alignment is the core of sequencing analysis, and downstream tasks accept mapping results for further processing. Given the rapid development of the sequencing industry today, a comprehensive understanding of the SAM format and related tools is necessary to meet the challenges of data processing and analysis. This paper is devoted to retrieving knowledge in the broad field of SAM. First, the format of SAM is introduced to understand the overall process of the sequencing analysis. Then, existing work is systematically classified in accordance with generation, compression and application, and the involved SAM tools are specifically mined. Lastly, a summary and some thoughts on future directions are provided.

Linking plant functional genes to rhizosphere microbes: a review

The importance of rhizomicrobiome in plant development, nutrition acquisition and stress tolerance is unquestionable. Relevant plant genes corresponding to the above functions also regulate rhizomicrobiome construction. Deciphering the molecular regulatory network of plant-microbe interactions could substantially contribute to improving crop yield and quality. Here, the plant gene-related nutrient uptake, biotic and abiotic stress resistance, which may influence the composition and function of microbial communities, are discussed in this review. In turn, the influence of microbes on the expression of functional plant genes, and thereby plant growth and immunity, is also reviewed. Moreover, we have specifically paid attention to techniques and methods used to link plant functional genes and rhizomicrobiome. Finally, we propose to further explore the molecular mechanisms and signalling pathways of microbe-host gene interactions, which could potentially be used for managing plant health in agricultural systems.

Full-Length Transcriptome of the Great Himalayan Leaf-Nosed Bats (Hipposideros armiger) Optimized Genome Annotation and Revealed the Expression of Novel Genes

The Great Himalayan Leaf-nosed bat (Hipposideros armiger) is one of the most representative species of all echolocating bats and is an ideal model for studying the echolocation system of bats. An incomplete reference genome and limited availability of full-length cDNAs have hindered the identification of alternatively spliced transcripts, which slowed down related basic studies on bats' echolocation and evolution. In this study, we analyzed five organs from H. armiger for the first time using PacBio single-molecule real-time sequencing (SMRT). There were 120 GB of subreads generated, including 1,472,058 full-length non-chimeric (FLNC) sequences. A total of 34,611 alternative splicing (AS) events and 66,010 Alternative Polyadenylation (APA) sites were detected by transcriptome structural analysis. Moreover, a total of 110,611 isoforms were identified, consisting of 52% new isoforms of known genes and 5% of novel gene loci, as well as 2112 novel genes that have not been annotated before in the current reference genome of H. armiger. Furthermore, several key novel genes, including Pol, RAS, NFKB1, and CAMK4, were identified as being associated with nervous, signal transduction, and immune system processes, which may be involved in regulating the auditory nervous perception and immune system that helps bats to regulate in echolocation. In conclusion, the full-length transcriptome results optimized and replenished existing H. armiger genome annotation in multiple ways and offer advantages for newly discovered or previously unrecognized protein-coding genes and isoforms, which can be used as a reference resource.

Highly reliable and efficient encoding systems for hexadecimal polypeptide-based data storage

Polypeptides consisting of amino acid (AA) sequences are suitable for high-density information storage. However, the lack of suitable encoding systems, which accommodate the characteristics of polypeptide synthesis, storage and sequencing, impedes the application of polypeptides for large-scale digital data storage. To address this, two reliable and highly efficient encoding systems, i.e. RaptorQ-Arithmetic-Base64-Shuffle-RS (RABSR) and RaptorQ-Arithmetic-Huffman-Rotary-Shuffle-RS (RAHRSR) systems, are developed for polypeptide data storage. The two encoding systems realized the advantages of compressing data, correcting errors of AA chain loss, correcting errors within AA chains, eliminating homopolymers, and pseudo-randomized encrypting. The coding efficiency without arithmetic compression and error correction of audios, pictures and texts by the RABSR system was 3.20, 3.12 and 3.53 Bits/AA, respectively. While that using the RAHRSR system reached 4.89, 4.80 and 6.84 Bits/AA, respectively. When implemented with redundancy for error correction and arithmetic compression to reduce redundancy, the coding efficiency of audios, pictures and texts by the RABSR system was 4.43, 4.36 and 5.22 Bits/AA, respectively. This efficiency further increased to 7.24, 7.11 and 9.82 Bits/AA by the RAHRSR system, respectively. Therefore, the developed hexadecimal polypeptide-based systems may provide a new scenario for highly reliable and highly efficient data storage.

Specific-Locus Amplified Fragment Sequencing (SLAF-Seq)

Specific length amplified fragment sequencing (SLAF-seq) technology is a simplified genome sequencing technology based on next-generation sequencing. SLAF-seq technology has several distinguishing characteristics: 1. Deep sequencing to ensure accuracy of genotyping; 2. Effectively reduce sequencing costs; 3. Pre-designed simplified representation scheme to optimize marker efficiency; 4. Doubled barcode system for large populations. The advantages and technical process of SLAF-seq are described briefly with summarized results for the application of SLAF-seq in development of molecular markers, construction of high-density genetic map and gene mapping in ornamental plants. Finally, the difficulties and prospects of this method are discussed in application.

Single DNA Translocation and Electrical Characterization Based on Atomic Force Microscopy and Nanoelectrodes

Precision DNA translocation control is critical for achieving high accuracy in single molecule-based DNA sequencing. In this report, we describe an atomic force microscopy (AFM) based method to linearize a double-stranded DNA strand during the translocation process and characterize the electrical properties of the moving DNA using a platinum (Pt) nanoelectrode gap. In this method, λDNAs were first deposited on a charged mica substrate surface and topographically scanned. A single DNA suitable for translocation was then identified and electrostatically attached to an AFM probe by pressing the probe tip down onto one end of the DNA strand without chemical functionalizations. Next, the DNA strand was lifted off the mica surface by the probe tip. The pulling force required to completely lift off the DNA agreed well with the theoretical DNA adhesion force to a charged mica surface. After liftoff, the captured DNA was translocated at varied speeds across the substrate and ultimately across the Pt nanoelectrode gap for electrical characterizations. Finally, finite element analysis of the effect of the translocating DNA on the conductivity of the nanoelectrode gap was conducted, validating the range of the gap current measured experimentally during the DNA translocation process.

Characterization of somatic structural variations in 528 Chinese individuals with Esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) demonstrates high genome instability. Here, we analyze 528 whole genomes to investigate structural variations' mechanisms and biological functions. SVs show multi-mode distributions in size, indicating distinct mutational processes. We develop a tool and define five types of complex rearrangements with templated insertions. We highlight a type of fold-back inversion, which is associated with poor outcomes. Distinct rearrangement signatures demonstrate variable genomic metrics such as replicating time, spatial proximity, and chromatin accessibility. Specifically, fold-back inversion tends to occur near the centrosome; TD-c2 (Tandem duplication-cluster2) is significantly enriched in chromatin-accessibility and early-replication region compared to other signatures. Analyses of TD-c2 signature reveal 9 TD hotspots, of which we identify a hotspot consisting of a super-enhancer of PTHLH. We confirm the oncogenic effect of the PTHLH gene and its interaction with enhancers through functional experiments. Finally, extrachromosomal circular DNAs (ecDNAs) are present in 14% of ESCCs and have strong selective advantages to driver genes.

Gut Microbiota in Nutrition and Health with a Special Focus on Specific Bacterial Clusters

Health is influenced by how the gut microbiome develops as a result of external and internal factors, such as nutrition, the environment, medication use, age, sex, and genetics. Alpha and beta diversity metrics and (enterotype) clustering methods are commonly employed to perform population studies and to analyse the effects of various treatments, yet, with the continuous development of (new) sequencing technologies, and as various omics fields as a result become more accessible for investigation, increasingly sophisticated methodologies are needed and indeed being developed in order to disentangle the complex ways in which the gut microbiome and health are intertwined. Diseases of affluence, such as type 2 diabetes (T2D) and cardiovascular diseases (CVD), are commonly linked to species associated with the Bacteroides enterotype(s) and a decline of various (beneficial) complex microbial trophic networks, which are in turn linked to the aforementioned factors. In this review, we (1) explore the effects that some of the most common internal and external factors have on the gut microbiome composition and how these in turn relate to T2D and CVD, and (2) discuss research opportunities enabled by and the limitations of some of the latest technical developments in the microbiome sector, including the use of artificial intelligence (AI), strain tracking, and peak to trough ratios.

A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

Background

Next-generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies.

Objective

The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now.

Results

The proposed study, based on previous studies and manufacturers' descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position.

Conclusion

The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory- and time-saving algorithms and databases need to be developed to analyze data produced by the 3rd- and 4th-generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.

Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules

In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed in vitro, involving biochemical operations such as synthesis, amplification and sequencing. Because errors may occur with specific sequence patterns or experimental instruments, these biochemical operations are not completely reliable. Modeling errors in these biochemical procedures is an interesting research topic. For example, researchers have proposed several methods to avoid the known vulnerable sequence patterns in the study of storing binary information in DNA molecules. However, there are few end-to-end methods to evaluate these biochemical errors with regard to the DNA sequences. In this article, based on the data generated by a DNA storage research, we use artificial neural networks to predict whether a DNA sequence tends to cause errors in biochemical operations. Through comparative experiments and hyperparameter optimization, we analyze the known and potential problems in the research process. As a result, an end-to-end method to model the biochemical errors of DNA molecules in vitro through a computer system is proposed.

Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases

Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.

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.

A Review of Next Generation Sequencing Methods and its Applications in Laboratory Diagnosis

Next-generation sequencing (NGS) is a new technology used to detect the sequence of DNA and RNA and to detect mutations or variations of significance. NGS generates large quantities of sequence data within a short time duration. The various types of sequencing includes Sanger Sequencing, Pyrosequencing, Sequencing by Synthesis (Illumina), Ligation (SoLID), Single molecule Fluorescent Sequencing (Helicos), Single molecule Real time Sequencing (Pacbio), Semiconductor sequencing (Ion torrent technology), Nanopore sequencing and fourth generation sequencing. These methods of sequencing have been modified and improved over the years such that it has become cost effective and accessible to diagnostic laboratories. Management of Outbreaks, rapid identification of bacteria, molecular case finding, taxonomy, detection of the zoonotic agents and guiding prevention strategies in HIV outbreaks are just a few of the many applications of Next Generation sequencing in clinical microbiology.

Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade

Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data.

Mixed Infection of Cytomegalovirus and Pulmonary Nocardiosis Caused by Nocardia elegans Diagnosed Using Nanopore Sequencing Technology

A 69-year-old woman who had undergone renal transplantation and was receiving sulfamethoxazole/trimethoprim (ST) developed pulmonary nocardiosis. To our knowledge, this is the first report of the identification of Nocardia elegans using nanopore sequencing, supported by 16S rDNA capillary sequencing findings. Chest computed tomography performed after ST initiation revealed significant improvement of the pulmonary shadows compared to previous findings. We herein report the value of nanopore sequencing for rapid identification of rare pathogens, such as Nocardia elegans. Furthermore, our findings suggest that Nocardia may infect even patients receiving ST, which is currently the most effective prophylactic drug.

Melting of confined DNA: static and dynamic properties

We study dsDNA (double strand DNA) melting in detail within varying strip-like confinement in a two-dimensional lattice model. The interplay between reduced configurational entropy and attractive base-pairing energy results in a non-monotonic melting profile of DNA. Structural transitions associated with confined DNA melting reveal a stretched or extended state for very strong confinement. By using the exact enumeration method, we investigate the emergence of a local denatured zone e.g. bubbles during DNA melting. The survival time of a single bubble within varying strip width is studied from the Fokker-Planck formalism by considering the bubble size as a reaction co-ordinate. We show that a simple lattice model can capture the sequence heterogeneity effect on DNA melting and bubble dynamics within the strip. Different time scales of bubble zipping for different DNA sequences are found, which may have potential applications in denaturation mapping.

Towards practical and robust DNA-based data archiving using the yin-yang codec system

DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense of introducing biocompatibility challenges or decoding failure. Here we propose a robust transcoding algorithm named the yin-yang codec, using two rules to encode two binary bits into one nucleotide, to generate DNA sequences that are highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200 nt oligo pools and in vivo as a ~54 kbps DNA fragment in yeast cells. Sequencing results show that the yin-yang codec exhibits high robustness and reliability for a wide variety of data types, with an average recovery rate of 99.9% above 104 molecule copies and an achieved recovery rate of 87.53% at ≤102 copies. Additionally, the in vivo storage demonstration achieved an experimentally measured physical density close to the theoretical maximum.

DNA-Based Concatenated Encoding System for High-Reliability and High-Density Data Storage

Information storage based on DNA molecules provides a promising solution with advantages of low-energy consumption, high storage efficiency, and long lifespan. However, there are only four natural nucleotides and DNA storage is thus limited by 2 bits per nucleotide. Here, artificial nucleotides into DNA data storage to achieve higher coding efficiency than 2 bits per nucleotide is introduced. To accommodate the characteristics of DNA synthesis and sequencing, two high-reliability encoding systems suitable for four, six, and eight nucleotides, i.e., the RaptorQ-Arithmetic-LZW-RS (RALR) and RaptorQ-Arithmetic-Base64-RS (RABR) systems, are developed. The two concatenated encoding systems realize the advantages of correcting DNA sequence losses, correcting errors within DNA sequences, reducing homopolymers, and controlling specific nucleotide contents. The average coding efficiencies with error correction and without arithmetic compression by the RALR system using four, six, and eight nucleotides reach 1.27, 1.61, and 1.85 bits per nucleotide, respectively. While the average coding efficiencies by the RABR system are up to 1.50, 2.00, and 2.35 bits per nucleotide, respectively. The coding efficiency, versatility, and tunability of the developed artificial DNA systems might provide significant guidance for high-reliability and high-density data storage.

Nanopore sequencing approach for variation detection of a live attenuated Newcastle disease virus vaccine

Live attenuated Newcastle disease virus (NDV) vaccines have been used widely to protect chickens against Newcastle disease. However, the vaccine issues caused by genome mutations can seriously affect poultry health. In this study, the authors demonstrate the use of nanopore sequencing technology for rapid genome determination and variation analysis from a live attenuated NDV vaccine. NDV-specific reads were detected immediately after sequencing, and 24× genome coverage was obtained within 10 min. Variation analysis revealed 19 variant sites across the vaccine genome compared to the NDV clone 30 reference sequence . The sequencing and data analysis workflow employed enables all basic molecular biology laboratories to perform detailed genome sequencing in live attenuated vaccine, providing an effective means of quality control for vaccine production.

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world’s population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. “Multi-omics” strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of “omics” approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

Plant PhysioSpace: a robust tool to compare stress response across plant species

Generalization of transcriptomics results can be achieved by comparison across experiments. This generalization is based on integration of interrelated transcriptomics studies into a compendium. Such a focus on the bigger picture enables both characterizations of the fate of an organism and distinction between generic and specific responses. Numerous methods for analyzing transcriptomics datasets exist. Yet, most of these methods focus on gene-wise dimension reduction to obtain marker genes and gene sets for, for example, pathway analysis. Relying only on isolated biological modules might result in missing important confounders and relevant contexts. We developed a method called Plant PhysioSpace, which enables researchers to compute experimental conditions across species and platforms without a priori reducing the reference information to specific gene sets. Plant PhysioSpace extracts physiologically relevant signatures from a reference dataset (i.e. a collection of public datasets) by integrating and transforming heterogeneous reference gene expression data into a set of physiology-specific patterns. New experimental data can be mapped to these patterns, resulting in similarity scores between the acquired data and the extracted compendium. Because of its robustness against platform bias and noise, Plant PhysioSpace can function as an inter-species or cross-platform similarity measure. We have demonstrated its success in translating stress responses between different species and platforms, including single-cell technologies. We have also implemented two R packages, one software and one data package, and a Shiny web application to facilitate access to our method and precomputed models.

Bordetella avium-associated endophthalmitis: case report

Background

Bordetella avium, an aerobic bacterium that rarely causes infection in humans, is a species of Bordetella that generally inhabits the respiratory tracts of turkeys and other birds. It causes a highly contagious bordetellosis. Few reports describe B. avium as a causative agent of eye-related infections.

Case presentation

We report a case of acute infectious endophthalmitis associated with infection by B. avium after open trauma. After emergency vitrectomy and subsequent broad-spectrum antibiotic treatment, the infection was controlled successfully, and the patient’s vision improved.

Conclusions

B. avium can cause infection in the human eye, which can manifest as acute purulent endophthalmitis. Nanopore targeted sequencing technology can quickly identify this organism. Emergency vitrectomy combined with lens removal and silicone oil tamponade and the early application of broad-spectrum antibiotics are key for successful treatment.

Application of NGS Technology in Understanding the Pathology of Autoimmune Diseases

NGS technologies have transformed clinical diagnostics and broadly used from neonatal emergencies to adult conditions where the diagnosis cannot be made based on clinical symptoms. Autoimmune diseases reveal complicate molecular background and traditional methods could not fully capture them. Certainly, NGS technologies meet the needs of modern exploratory research, diagnostic and pharmacotherapy. Therefore, the main purpose of this review was to briefly present the application of NGS technology used in recent years in the understanding of autoimmune diseases paying particular attention to autoimmune connective tissue diseases. The main issues are presented in four parts: (a) panels, whole-genome and -exome sequencing (WGS and WES) in diagnostic, (b) Human leukocyte antigens (HLA) as a diagnostic tool, (c) RNAseq, (d) microRNA and (f) microbiome. Although all these areas of research are extensive, it seems that epigenetic impact on the development of systemic autoimmune diseases will set trends for future studies on this area.

Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction and genotyping

Over the last few decades, genomics is leading toward audacious future, and has been changing our views about conducting biomedical research, studying diseases, and understanding diversity in our society across the human species. The whole genome and exome sequencing (WGS/WES) are two of the most popular next-generation sequencing (NGS) methodologies that are currently being used to detect genetic variations of clinical significance. Investigating WGS/WES data for the variant discovery and genotyping is based on the nexus of different data analytic applications. Although several bioinformatics applications have been developed, and many of those are freely available and published. Timely finding and interpreting genetic variants are still challenging tasks among diagnostic laboratories and clinicians. In this study, we are interested in understanding, evaluating, and reporting the current state of solutions available to process the NGS data of variable lengths and types for the identification of variants, alleles, and haplotypes. Residing within the scope, we consulted high quality peer reviewed literature published in last 10 years. We were focused on the standalone and networked bioinformatics applications proposed to efficiently process WGS and WES data, and support downstream analysis for gene-variant discovery, annotation, prediction, and interpretation. We have discussed our findings in this manuscript, which include but not are limited to the set of operations, workflow, data handling, involved tools, technologies and algorithms and limitations of the assessed applications.

Coronavirus Disease 2019 (COVID-19) Diagnostic Tools: A Focus on Detection Technologies and Limitations

The ongoing coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a severe threat to human health and the global economy and has resulted in overwhelming stress on health care systems worldwide. Despite the global health catastrophe, especially in the number of infections and fatalities, the COVID-19 pandemic has also revolutionized research and discovery with remarkable success in diagnostics, treatments, and vaccine development. The use of many diagnostic methods has helped establish public health guidelines to mitigate the spread of COVID-19. However, limited information has been shared about these methods, and there is a need for the scientific community to learn about these technologies, in addition to their sensitivity, specificity, and limitations. This review article is focused on providing insights into the major methods used for SARS-CoV-2 detection. We describe in detail the core principle of each method, including molecular and serological approaches, along with reported claims about the rates of false negatives and false positives, the types of specimens needed, and the level of technology and the time required to perform each test. Although this study will not rank or prioritize these methods, the information will help in the development of guidelines and diagnostic protocols in clinical settings and reference laboratories.

Fast, Scalable, and Practical: An Alkaline DNA Extraction Pipeline for Emergency Microbiomics Biosurveillance

Pandemics and environmental crises evident from the first two decades of the 21st century call for methods innovation in biosurveillance and early detection of risk signals in planetary ecosystems. In crises conditions, conventional methods in public health, biosecurity, and environmental surveillance do not work well. In addition, the standard laboratory amenities and procedures may become unavailable, irrelevant, or simply not feasible, for example, owing to disruptions in logistics and process supply chains. The COVID-19 pandemic has been a wakeup call in this sense to reintroduce point-of-need diagnostics with an eye to limited resource settings and biosurveillance solutions. We report here a methodology innovation, a fast, scalable, and alkaline DNA extraction pipeline for emergency microbiomics biosurveillance. We believe that the presented methodology is well poised for effective, resilient, and anticipatory responses to future pandemics and ecological crises while contributing to microbiome science and point-of-need diagnostics in nonelective emergency contexts. The alkaline DNA extraction pipeline can usefully expand the throughput in emergencies by deployment or to allow backup in case of instrumentation failure in vital facilities. The need for distributed public health genomics surveillance is increasingly evident in the 21st century. This study makes a contribution to these ends broadly, and for future pandemic preparedness in particular. We call for innovation in biosurveillance methods that remain important existentially on a planet under pressure from unchecked human growth and breach of the boundaries between human and nonhuman animal habitats.

Seasonal Succession of Bacterial Communities in Three Eutrophic Freshwater Lakes

Urban freshwater lakes play an indispensable role in maintaining the urban environment and are suffering great threats of eutrophication. Until now, little has been known about the seasonal bacterial communities of the surface water of adjacent freshwater urban lakes. This study reported the bacterial communities of three adjacent freshwater lakes (i.e., Tangxun Lake, Yezhi Lake and Nan Lake) during the alternation of seasons. Nan Lake had the best water quality among the three lakes as reflected by the bacterial eutrophic index (BEI), bacterial indicator (Luteolibacter) and functional prediction analysis. It was found that Alphaproteobacteria had the lowest abundance in summer and the highest abundance in winter. Bacteroidetes had the lowest abundance in winter, while Planctomycetes had the highest abundance in summer. N/P ratio appeared to have some relationships with eutrophication. Tangxun Lake and Nan Lake with higher average N/P ratios (e.g., N/P = 20) tended to have a higher BEI in summer at a water temperature of 27 °C, while Yezhi Lake with a relatively lower average N/P ratio (e.g., N/P = 14) tended to have a higher BEI in spring and autumn at a water temperature of 9-20 °C. BEI and water temperature were identified as the key parameters in determining the bacterial communities of lake water. Phosphorus seemed to have slightly more impact on the bacterial communities than nitrogen. It is expected that this study will help to gain more knowledge on urban lake eutrophication.

Hardware Acceleration of Genomics Data Analysis: Challenges and Opportunities

The significant decline in the cost of genome sequencing has dramatically changed the typical bioinformatics pipeline for analysing sequencing data. Where traditionally, the computational challenge of sequencing is now secondary to genomic data analysis. Short read alignment (SRA) is a ubiquitous process within every modern bioinformatics pipeline in the field of genomics and is often regarded as the principal computational bottleneck. Many hardware and software approaches have been provided to solve the challenge of acceleration. However, previous attempts to increase throughput using many-core processing strategies have enjoyed limited success, mainly due to a dependence on global memory for each computational block. The limited scalability and high energy costs of many-core SRA implementations pose a significant constraint in maintaining acceleration. The Networks-On-Chip (NoC) hardware interconnect mechanism has advanced the scalability of many-core computing systems and, more recently, has demonstrated potential in SRA implementations by integrating multiple computational blocks such as pre-alignment filtering and sequence alignment efficiently, while minimising memory latency and global memory access. This paper provides a state of the art review on current hardware acceleration strategies for genomic data analysis, and it establishes the challenges and opportunities of utilising NoCs as a critical building block in next-generation sequencing (NGS) technologies for advancing the speed of analysis.

Application of the conventional and novel methods in testing EGFR variants for NSCLC patients in the last 10 years through different regions: a systematic review

Variants in the epidermal growth factor receptor (EGFR) gene are recognized as predictors of therapy response and are correlated with progression-free and overall survival in non-small cell lung cancer (NSCLC) patients. Molecularly guided therapy needs precise and cost-effective molecular tests. This review focused primarily on screening or target methods for the EGFR variants detection with diagnostic and prognostic potential in the clinical research published papers. Concerning the inclusion and exclusion criteria, the search interval comprised available articles published from 2010 until 2020 in three electronic databases, ISI Web of Science, Pub Med, and Scopus. The analysis of eligible studies started with 5647 and obtained the final 987 full-text articles analyzed as clinical research. The regions comprised were Africa, America, Australia, Asia, Euro-Asia, Europe, or a consortium of different countries. All of the tested methods were applied prevalently in Asia. In clinical research, the polymerase chain reaction (PCR), followed by sequencing methods have been involved mostly over the years. The identified high-through output approaches evolved to improve the survival and quality of the NSCLC patient's life becoming more sensitive, specific, and cost-effective.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content

In this study, six bacterial isolates with variable GC, including Escherichia coli as mesophilic reference strain, were selected to compare hybrid assembly strategies based on next-generation sequencing (NGS) of short reads, single-tube long-fragment reads (stLFR) sequencing, and Oxford Nanopore Technologies (ONT) sequencing platforms. We obtained the complete genomes using the hybrid assembler Unicycler based on the NGS and ONT reads; others were de novo assembled using NGS, stLFR, and ONT reads by using different strategies. The contiguity, accuracy, completeness, sequencing costs, and DNA material requirements of the investigated strategies were compared systematically. Although all sequencing data could be assembled into accurate whole-genome sequences, the stLFR sequencing data yield a scaffold with more contiguity with more completeness of gene function than NGS sequencing assemblies. Our research provides a low-cost chromosome-level genome assembly strategy for large-scale sequencing of extremophile genomes with different GC contents.

Exploiting next-generation sequencing in antibody selections - a simple PCR method to recover binders

Antibody discovery using invitro display technologies such as phage and/or yeast display has become acornerstone in many research and development projects, including the creation of new drugs for clinical use. Traditionally, after the selection phase, random clones are isolated for binding validation and Sanger sequencing. More recently, next-generation sequencing (NGS) technology has allowed deeper insight into the antibody population after aselection campaign, enabling the identification of many more specific binders. However, this approach only provides the DNA sequences of potential binders, the properties of which need to be fully elucidated by obtaining corresponding clones and expressing them for further validation. Here we present arapid novel method to harvest potential clones identified by NGS that uses asimple PCR and yeast recombination approach. The protocol was tested in selections against three different targets and was able to recover clones at an abundance level that would be impractical to identify using traditional methods.

Application of Next Generation Sequencing in Laboratory Medicine

The rapid development of next-generation sequencing (NGS) technology, including advances in sequencing chemistry, sequencing technologies, bioinformatics, and data interpretation, has facilitated its wide clinical application in precision medicine. This review describes current sequencing technologies, including short- and long-read sequencing technologies, and highlights the clinical application of NGS in inherited diseases, oncology, and infectious diseases. We review NGS approaches and clinical diagnosis for constitutional disorders; summarize the application of U.S. Food and Drug Administration-approved NGS panels, cancer biomarkers, minimal residual disease, and liquid biopsy in clinical oncology; and consider epidemiological surveillance, identification of pathogens, and the importance of host microbiome in infectious diseases. Finally, we discuss the challenges and future perspectives of clinical NGS tests.

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integrated analysis, the recent past has seen an influx of proteogenomic tools that perform various tasks, including mapping proteins to the genomic data, searching experimental MS spectra against a six-frame translation genome database, and automating the process of annotating genome sequences. To date, most of such tools have not focused on scalability issues that are inherent in proteogenomic data analysis where the size of the database is much larger than a typical protein database. These state-of-the-art tools can take more than half a month to process a small-scale dataset of one million spectra against a genome of 3 GB. In this article, we provide an up-to-date review of tools that can analyze proteogenomic datasets, providing a critical analysis of the techniques' relative merits and potential pitfalls. We also point out potential bottlenecks and recommendations that can be incorporated in the future design of these workflows to ensure scalability with the increasing size of proteogenomic data. Lastly, we make a case of how high-performance computing (HPC) solutions may be the best bet to ensure the scalability of future big data proteogenomic data analysis.

INDEL detection, the 'Achilles heel' of precise genome editing: a survey of methods for accurate profiling of gene editing induced indels

Advances in genome editing technologies have enabled manipulation of genomes at the single base level. These technologies are based on programmable nucleases (PNs) that include meganucleases, zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated 9 (Cas9) nucleases and have given researchers the ability to delete, insert or replace genomic DNA in cells, tissues and whole organisms. The great flexibility in re-designing the genomic target specificity of PNs has vastly expanded the scope of gene editing applications in life science, and shows great promise for development of the next generation gene therapies. PN technologies share the principle of inducing a DNA double-strand break (DSB) at a user-specified site in the genome, followed by cellular repair of the induced DSB. PN-elicited DSBs are mainly repaired by the non-homologous end joining (NHEJ) and the microhomology-mediated end joining (MMEJ) pathways, which can elicit a variety of small insertion or deletion (indel) mutations. If indels are elicited in a protein coding sequence and shift the reading frame, targeted gene knock out (KO) can readily be achieved using either of the available PNs. Despite the ease by which gene inactivation in principle can be achieved, in practice, successful KO is not only determined by the efficiency of NHEJ and MMEJ repair; it also depends on the design and properties of the PN utilized, delivery format chosen, the preferred indel repair outcomes at the targeted site, the chromatin state of the target site and the relative activities of the repair pathways in the edited cells. These variables preclude accurate prediction of the nature and frequency of PN induced indels. A key step of any gene KO experiment therefore becomes the detection, characterization and quantification of the indel(s) induced at the targeted genomic site in cells, tissues or whole organisms. In this survey, we briefly review naturally occurring indels and their detection. Next, we review the methods that have been developed for detection of PN-induced indels. We briefly outline the experimental steps and describe the pros and cons of the various methods to help users decide a suitable method for their editing application. We highlight recent advances that enable accurate and sensitive quantification of indel events in cells regardless of their genome complexity, turning a complex pool of different indel events into informative indel profiles. Finally, we review what has been learned about PN-elicited indel formation through the use of the new methods and how this insight is helping to further advance the genome editing field.

Nucleic Acids Analysis

Nucleic acids are natural biopolymers of nucleotides that store, encode, transmit and express genetic information, which play central roles in diverse cellular events and diseases in living things. The analysis of nucleic acids and nucleic acids-based analysis have been widely applied in biological studies, clinical diagnosis, environmental analysis, food safety and forensic analysis. During the past decades, the field of nucleic acids analysis has been rapidly advancing with many technological breakthroughs. In this review, we focus on the methods developed for analyzing nucleic acids, nucleic acids-based analysis, device for nucleic acids analysis, and applications of nucleic acids analysis. The representative strategies for the development of new nucleic acids analysis in this field are summarized, and key advantages and possible limitations are discussed. Finally, a brief perspective on existing challenges and further research development is provided.

Insights on SNP types, detection methods and their utilization in Brassica species: Recent progress and future perspectives

The genus Brassica, family Brassicaceae (Cruciferae), comprises many important species of oil crops, vegetables and medicinal plants including B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, B. carinata. Genomic researches in Brassica species is constrained by polyploidization, mainly due to its complicated genomic structure. However, rapid development of methods for detecting single nucleotide polymorphisms (SNP), such as next generation sequencing and SNP microarray, has accelerated release of reference Brassica species genomes as well as discovery of large numbers and genome-wide SNPs, thus intensifying forward genetics in this genus. In this review, we summarize biological characteristics, classification and various methods for detecting SNPs, focusing on high-throughput techniques. Moreover, we describe the pivotal roles of SNPs in genetic diversity, linkage map construction and QTL mapping, comparative genomics, linkage disequilibrium and genome-wide association studies. These insights are expected to deepen our understanding and guide further advancements in Brassica species research.

History of DNA Sequencing

The nucleotides are the building blocks of nucleic acids and determining their sequential arrangement had always been an integral part of biological research. Since the past seven decades, researchers from multi-disciplinary fields has been working together to innovate the best sequencing methods. Various methods had been proposed, from some oligonucleotides to the whole genome sequencing, and the growth had gone through adolescence to the mature phase where it is now capable of sequencing the whole genome at a low cost and within a short time frame. DNA sequencing has become a key technology in every discipline of biology and medicine. This review aims to highlight the evolution of DNA sequencing techniques and the machines used, including their principles and key achievements.

Chemically tailoring nanopores for single-molecule sensing and glycomics

A nanopore can be fairly-but uncharitably-described as simply a nanofluidic channel through a thin membrane. Even this simple structural description holds utility and underpins a range of applications. Yet significant excitement for nanopore science is more readily ignited by the role of nanopores as enabling tools for biomedical science. Nanopore techniques offer single-molecule sensing without the need for chemical labelling, since in most nanopore implementations, matter is its own label through its size, charge, and chemical functionality. Nanopores have achieved considerable prominence for single-molecule DNA sequencing. The predominance of this application, though, can overshadow their established use for nanoparticle characterization and burgeoning use for protein analysis, among other application areas. Analyte scope continues to be expanded, and with increasing analyte complexity, success will increasingly hinge on control over nanopore surface chemistry to tune the nanopore, itself, and to moderate analyte transport. Carbohydrates are emerging as the latest high-profile target of nanopore science. Their tremendous chemical and structural complexity means that they challenge conventional chemical analysis methods and thus present a compelling target for unique nanopore characterization capabilities. Furthermore, they offer molecular diversity for probing nanopore operation and sensing mechanisms. This article thus focuses on two roles of chemistry in nanopore science: its use to provide exquisite control over nanopore performance, and how analyte properties can place stringent demands on nanopore chemistry. Expanding the horizons of nanopore science requires increasing consideration of the role of chemistry and increasing sophistication in the realm of chemical control over this nanoscale milieu.

Sequencing of Small DNA Fragments with Aggregated-Induced-Emission Molecule-Labeled Nucleotides

Sequencing by synthesis is a significant method for high-throughput DNA sequencing. Herein, we synthesized terminal aggregated-induced-emission luminogen (AIEgen) labeled nucleotides (dNTPs-HCAP) that could serve as substrates for some polymerases and applied them into the sequencing of small DNA fragments. In the process of DNA amplification, ratiometric AIEgens are released from dNTPs-HCAP and aggregate through the effects of phosphatase, which results in changes in the ratiometric fluorescent signals. With the AIEgen-labeled nucleotides, we accomplished the sequencing of small DNA fragments through double changes in fluorescence. In addition, we achieved the differentiation of single nucleotide polymorphisms through rolling circle amplification reactions without the addition of signal probes, which is fast and cost-effective. The introduction of ratiometric AIEgens into DNA synthesis makes the detection of DNA sequences more efficient and accurate. Therefore, the development of AIEgen-labeled nucleotides is meaningful for the study of DNA sequencing methods.

Big data management: from hard drives to DNA drives

Information Communication and Technology is transforming all aspects of modern life and in this digital era, there is a tremendous increase in the amount of data that is being generated every day. The current, conventional storage devices are unable to keep pace with this rapidly growing data. Thus, there is a need to look for alternative storage devices. DNA being exceptional in storage of biological information offers a promising storage capacity. With its unique abilities of dense storage and reliability, it may prove better than all conventional storage devices in near future. The nucleotide bases are present in DNA in a particular sequence representing the coded information. These are the equivalent of binary letters (0 &1). To store data in DNA, binary data is first converted to ternary or quaternary which is then translated into the nucleotide code comprising 4 nucleotide bases (A, C, G, T). A DNA strand is then synthesized as per the code developed. This may either be stored in pools or sequenced back. The nucleotide code is converted back into ternary and subsequently the binary code which is read just like digital data. DNA drives may have a wide variety of applications in information storage and DNA steganography.