Sequence information can be obtained from single DNA molecules

Advancing DNA Structural Analysis: A SERS Approach Free from Citrate Interference Combined with Machine Learning

Surface-enhanced Raman spectroscopy (SERS) has become an indispensable tool for biomolecular analysis, yet the detection of DNA signals remains hindered by spectral interference from citrate ions, which overlap with key DNA features. This study introduces an innovative, ultrasensitive SERS platform utilizing thiol-modified silver nanoparticles (Ag@SDCNPs) that overcomes this challenge by eliminating citrate interference. This platform enables direct, interference-free detection and structural characterization of a wide range of DNA conformations, including single-stranded DNA (ssDNA), double-stranded DNA (dsDNA), i-motif, hairpin, G-quadruplex, and triple-stranded DNA (tsDNA). Employing calcium ions as aggregating agents and deuterated methanol as an internal standard, the system achieved high spectral quality and reproducibility. Machine learning (ML) techniques, such as linear discriminant analysis (LDA) and t-distributed stochastic neighbor embedding (t-SNE), were utilized for spectral classification, alongside support vector machines (SVM) for predictive modeling, yielding accuracies above 99%. These findings establish a robust and versatile platform for DNA structural analysis, offering transformative potential for applications in clinical diagnostics and biomedical research.

Should AI-Powered Whole-Genome Sequencing Be Used Routinely for Personalized Decision Support in Surgical Oncology—A Scoping Review

In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments.

Viral genome sequencing methods: benefits and pitfalls of current approaches

Whole genome sequencing of viruses provides high-resolution molecular insights, enhancing our understanding of viral genome function and phylogeny. Beyond fundamental research, viral sequencing is increasingly vital for pathogen surveillance, epidemiology, and clinical applications. As sequencing methods rapidly evolve, the diversity of viral genomics applications and catalogued genomes continues to expand. Advances in long-read, single molecule, real-time sequencing methodologies present opportunities to sequence contiguous, haplotype resolved viral genomes in a range of research and applied settings. Here we present an overview of nucleic acid sequencing methods and their applications in studying viral genomes. We emphasise the advantages of different viral sequencing approaches, with a particular focus on the benefits of third-generation sequencing technologies in elucidating viral evolution, transmission networks, and pathogenesis.

Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications

Background

Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field.

Methods

We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field.

Results

3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field.

Conclusion

Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.

Sequential sequencing by synthesis and the next-generation sequencing revolution

The impact of next-generation sequencing (NGS) cannot be overestimated. The technology has transformed the field of life science, contributing to a dramatic expansion in our understanding of human health and disease and our understanding of biology and ecology. The vast majority of the major NGS systems today are based on the concept of 'sequencing by synthesis' (SBS) with sequential detection of nucleotide incorporation using an engineered DNA polymerase. Based on this strategy, various alternative platforms have been developed, including the use of either native nucleotides or reversible terminators and different strategies for the attachment of DNA to a solid support. In this review, some of the key concepts leading to this remarkable development are discussed.

Connection of ssDNA to Silicon Substrate Based on a Mechano-Chemical Method

A novel fabrication process to connect single-stranded DNA (ssDNA)to a silicon substrate based on a mechano-chemical method is proposed. In this method, the single crystal silicon substrate was mechanically scribed in a diazonium solution of benzoic acid using a diamond tip which formed silicon free radicals. These combined covalently with organic molecules of diazonium benzoic acid contained in the solution to form self-assembled films (SAMs). The SAMs were characterized and analyzed by AFM, X-ray photoelectron spectroscopy and infrared spectroscopy. The results showed that the self-assembled films were covalently connected to the silicon substrate by Si-C. In this way, a nano-level benzoic acid coupling layer was self-assembled on the scribed area of the silicon substrate. The ssDNA was further covalently connected to the silicon surface by the coupling layer. Fluorescence microscopy showed that ssDNA had been connected, and the influence of ssDNA concentration on the fixation effect was studied. The fluorescence brightness gradually increased with the gradual increase in ssDNA concentration from 5 μmol/L to 15 μmol/L, indicating that the fixed amount of ssDNA increased. However, when the concentration of ssDNA increased from 15 μmol/L to 20 μmol/L, the detected fluorescence brightness decreased, indicating that the hybridization amount decreased. The reason may be related to the spatial arrangement of DNA and the electrostatic repulsion between DNA molecules. It was also found that ssDNA junctions on the silicon surface were not very uniform, which was related to many factors, such as the inhomogeneity of the self-assembled coupling layer, the multi-step experimental operation and the pH value of the fixation solution.

Current Advances in Nanotechnology for the Next Generation of Sequencing (NGS)

This communication aims at discussing strategies based on developments from nanotechnology focused on the next generation of sequencing (NGS). In this regard, it should be noted that even in the advanced current situation of many techniques and methods accompanied with developments of technology, there are still existing challenges and needs focused on real samples and low concentrations of genomic materials. The approaches discussed/described adopt spectroscopical techniques and new optical setups. PCR bases are introduced to understand the role of non-covalent interactions by discussing about Nobel prizes related to genomic material detection. The review also discusses colorimetric methods, polymeric transducers, fluorescence detection methods, enhanced plasmonic techniques such as metal-enhanced fluorescence (MEF), semiconductors, and developments in metamaterials. In addition, nano-optics, challenges linked to signal transductions, and how the limitations reported in each technique could be overcome are considered in real samples. Accordingly, this study shows developments where optical active nanoplatforms generate signal detection and transduction with enhanced performances and, in many cases, enhanced signaling from single double-stranded deoxyribonucleic acid (DNA) interactions. Future perspectives on miniaturized instrumentation, chips, and devices aimed at detecting genomic material are analyzed. However, the main concept in this report derives from gained insights into nanochemistry and nano-optics. Such concepts could be incorporated into other higher-sized substrates and experimental and optical setups.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Conventional and Omics Approaches for Understanding the Abiotic Stress Response in Cereal Crops-An Updated Overview

Cereals have evolved various tolerance mechanisms to cope with abiotic stress. Understanding the abiotic stress response mechanism of cereal crops at the molecular level offers a path to high-yielding and stress-tolerant cultivars to sustain food and nutritional security. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. Omics approaches generate a massive amount of data, and adequate advancements in computational tools have been achieved for effective analysis. The combination of integrated omics and bioinformatics approaches has been recognized as vital to generating insights into genome-wide stress-regulation mechanisms. In this review, we have described the self-driven drought, heat, and salt stress-responsive mechanisms that are highlighted by the integration of stress-manipulating components, including transcription factors, co-expressed genes, proteins, etc. This review also provides a comprehensive catalog of available online omics resources for cereal crops and their effective utilization. Thus, the details provided in the review will enable us to choose the appropriate tools and techniques to reduce the negative impacts and limit the failures in the intensive crop improvement study.

DNA sequencing based on electronic tunneling in a gold nanogap: a first-principles study

Deoxyribonucleic acid (DNA) sequencing has found wide applications in medicine including treatment of diseases, diagnosis and genetics studies. Rapid and cost-effective DNA sequencing has been achieved by measuring the transverse electronic conductance as a single-stranded DNA is driven through a nanojunction. With the aim of improving the accuracy and sensitivity of DNA sequencing, we investigate the electron transport properties of DNA nucleobases within gold nanogaps based on first-principles quantum transport simulations. Considering the fact that the DNA bases can rotate within the nanogap during measurements, different nucleobase orientations and their corresponding residence time within the nanogap are explicitly taken into account based on their energetics. This allows us to obtain an average current that can be compared directly to experimental measurements. Our results indicate that bare gold electrodes show low distinguishability among the four DNA nucleobases while the distinguishability can be substantially enhanced with sulfur atom decorated electrodes. We further optimized the size of the nanogap by maximizing the residence time of the desired orientation.

Chloroplast Genes Are Involved in The Male-Sterility of K-Type CMS in Wheat

The utilization of crop heterosis can greatly improve crop yield. The sterile line is vital for the heterosis utilization of wheat (Triticum aestivum L.). The chloroplast genomes of two sterile lines and one maintainer were sequenced using second-generation high-throughput technology and assembled. The nonsynonymous mutated genes among the three varieties were identified, the expressed difference was further analyzed by qPCR, and finally, the function of the differentially expressed genes was analyzed by the barley stripe mosaic virus-induced gene silencing (BSMV-VIGS) method. A total of 16 genes containing 31 nonsynonymous mutations between K519A and 519B were identified. There were no base mutations in the protein-encoding genes between K519A and YS3038. The chloroplast genomes of 519B and K519A were closely related to the Triticum genus and Aegilops genus, respectively. The gene expression levels of the six selected genes with nonsynonymous mutation sites for K519A compared to 519B were mostly downregulated at the binucleate and trinucleate stages of pollen development. The seed setting rates of atpB-silenced or ndhH-silenced 519B plants by BSMV-VIGS method were significantly reduced. It can be concluded that atpB and the ndhH are likely to be involved in the reproductive transformation of 519B.

AI applications in functional genomics

We review the current applications of artificial intelligence (AI) in functional genomics. The recent explosion of AI follows the remarkable achievements made possible by "deep learning", along with a burst of "big data" that can meet its hunger. Biology is about to overthrow astronomy as the paradigmatic representative of big data producer. This has been made possible by huge advancements in the field of high throughput technologies, applied to determine how the individual components of a biological system work together to accomplish different processes. The disciplines contributing to this bulk of data are collectively known as functional genomics. They consist in studies of: i) the information contained in the DNA (genomics); ii) the modifications that DNA can reversibly undergo (epigenomics); iii) the RNA transcripts originated by a genome (transcriptomics); iv) the ensemble of chemical modifications decorating different types of RNA transcripts (epitranscriptomics); v) the products of protein-coding transcripts (proteomics); and vi) the small molecules produced from cell metabolism (metabolomics) present in an organism or system at a given time, in physiological or pathological conditions. After reviewing main applications of AI in functional genomics, we discuss important accompanying issues, including ethical, legal and economic issues and the importance of explainability.

High-throughput molecular technologies for unraveling the mystery of soil microbial community: challenges and future prospects

Soil microbial communities play a crucial role in soil fertility, sustainability, and plant health. However, intensive agriculture with increasing chemical inputs and changing environments have influenced native soil microbial communities. Approaches have been developed to study the structure, diversity, and activity of soil microbes to better understand the biology and plant-microbe interactions in soils. Unfortunately, a good understanding of soil microbial community remains a challenge due to the complexity of community composition, interactions of the soil environment, and limitations of technologies, especially related to the functionality of some taxa rarely detected using conventional techniques. Culture-based methods have been shown unable and sometimes are biased for assessing soil microbial communities. To gain further knowledge, culture-independent methods relying on direct analysis of nucleic acids, proteins, and lipids are worth exploring. In recent years, metagenomics, metaproteomics, metatranscriptomics, and proteogenomics have been increasingly used in studying microbial ecology. In this review, we examined the importance of microbial community to soil quality, the mystery of rhizosphere and plant-microbe interactions, and the biodiversity and multi-trophic interactions that influence the soil structure and functionality. The impact of the cropping system and climate change on the soil microbial community was also explored. Importantly, progresses in molecular biology, especially in the development of high-throughput biotechnological tools, were extensively assessed for potential uses to decipher the diversity and dynamics of soil microbial communities, with the highlighted advantages/limitations.

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.

Preparation of Mammalian Nascent RNA for Long Read Sequencing

Long read sequencing technologies now allow high-quality sequencing of RNAs (or their cDNAs) that are hundreds to thousands of nucleotides long. Long read sequences of nascent RNA provide single-nucleotide-resolution information about co-transcriptional RNA processing events-e.g., splicing, folding, and base modifications. Here, we describe how to isolate nascent RNA from mammalian cells through subcellular fractionation of chromatin-associated RNA, as well as how to deplete poly(A)+ RNA and rRNA, and, finally, how to generate a full-length cDNA library for use on long read sequencing platforms. This approach allows for an understanding of coordinated splicing status across multi-intron transcripts by revealing patterns of splicing or other RNA processing events that cannot be gained from traditional short read RNA sequencing. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Subcellular fractionation Basic Protocol 2: Nascent RNA isolation and adapter ligation Basic Protocol 3: cDNA amplicon preparation.

Next-Generation Sequencing at High Sequencing Depth as a Tool to Study the Evolution of Metastasis Driven by Genetic Change Events of Lung Squamous Cell Carcinoma

Background: The aim of this study is to report tumoral genetic mutations observed at high sequencing depth in a lung squamous cell carcinoma (SqCC) sample. We describe the findings and differences in genetic mutations that were studied by deep next-generation sequencing methods on the primary tumor and liver metastasis samples. In this report, we also discuss how these differences may be involved in determining the tumor progression leading to the metastasis stage.

Methods: We followed one lung SqCC patient who underwent FDG-PET scan imaging, before and after three months of treatment. We sequenced 26 well-known cancer-related genes, at an average of ~6,000 × sequencing coverage, in two spatially distinct regions, one from a primary lung tumor metastasis and the other from a distal liver metastasis, which was present before the treatment.

Results: A total of 3,922,196 read pairs were obtained across all two samples' sequenced locations. Merged mapped reads showed several variants, from which we selected 36 with high confidence call. While we found 83% of genetic concordance between the distal metastasis and primary tumor, six variants presented substantial discordance. In the liver metastasis sample, we observed three de novo genetic changes, two on the FGFR3 gene and one on the CDKN2A gene, and the frequency of one variant found on the FGFR2 gene has been increased. Two genetic variants in the HRAS gene, which were present initially in the primary tumor, have been completely lost in the liver tumor. The discordant variants have coding consequences as follows: FGFR3 (c.746C>G, p. Ser249Cys), CDKN2A (c.47_50delTGGC, p. Leu16Profs^*9), and HRAS (c.182A>C, p. Gln61Pro). The pathogenicity prediction scores for the acquired variants, assessed using several databases, reported these variants as pathogenic, with a gain of function for FGFR3 and a loss of function for CDKN2A. The patient follow-up using imaging with 18F-FDG PET/CT before and after four cycles of treatment shows discordant tumor progression in metastatic liver compared to primary lung tumor.

Conclusions: Our results report the occurrence of several genetic changes between primary tumor and distant liver metastasis in lung SqCC, among which non-silent mutations may be associated with tumor evolution during metastasis.

Impact of Nucleic Acid Sequencing on Viroid Biology

The early 1970s marked two breakthroughs in the field of biology: (i) The development of nucleotide sequencing technology; and, (ii) the discovery of the viroids. The first DNA sequences were obtained by two-dimensional chromatography which was later replaced by sequencing using electrophoresis technique. The subsequent development of fluorescence-based sequencing method which made DNA sequencing not only easier, but many orders of magnitude faster. The knowledge of DNA sequences has become an indispensable tool for both basic and applied research. It has shed light biology of viroids, the highly structured, circular, single-stranded non-coding RNA molecules that infect numerous economically important plants. Our understanding of viroid molecular biology and biochemistry has been intimately associated with the evolution of nucleic acid sequencing technologies. With the development of the next-generation sequence method, viroid research exponentially progressed, notably in the areas of the molecular mechanisms of viroids and viroid diseases, viroid pathogenesis, viroid quasi-species, viroid adaptability, and viroid–host interactions, to name a few examples. In this review, the progress in the understanding of viroid biology in conjunction with the improvements in nucleotide sequencing technology is summarized. The future of viroid research with respect to the use of third-generation sequencing technology is also briefly envisaged.

LUCS: a high-resolution nucleic acid sequencing tool for accurate long-read analysis of individual DNA molecules

Nucleic acid sequence analyses are fundamental to all aspects of biological research, spanning aging, mitochondrial DNA (mtDNA) and cancer, as well as microbial and viral evolution. Over the past several years, significant improvements in DNA sequencing, including consensus sequence analysis, have proven invaluable for high-throughput studies. However, all current DNA sequencing platforms have limited utility for studies of complex mixtures or of individual long molecules, the latter of which is crucial to understanding evolution and consequences of single nucleotide variants and their combinations. Here we report a new technology termed LUCS (Long-molecule UMI-driven Consensus Sequencing), in which reads from third-generation sequencing are aggregated by unique molecular identifiers (UMIs) specific for each individual DNA molecule. This enables in-silico reconstruction of highly accurate consensus reads of each DNA molecule independent of other molecules in the sample. Additionally, use of two UMIs enables detection of artificial recombinants (chimeras). As proof of concept, we show that application of LUCS to assessment of mitochondrial genomes in complex mixtures from single cells was associated with an error rate of 1X10^-4 errors/nucleotide. Thus, LUCS represents a major step forward in DNA sequencing that offers high-throughput capacity and high-accuracy reads in studies of long DNA templates and nucleotide variants in heterogenous samples.

Detecting sequence variants in clinically important protozoan parasites

Second and third generation sequencing methods are crucial for population genetic studies, and variant detection is a popular approach for exploiting this sequence data. While mini- and microsatellites are historically useful markers for studying important Protozoa such as Toxoplasma and Plasmodium spp., detecting non-repetitive variants such as those found in genes can be fundamental to investigating a pathogen's biology. These variants, namely single nucleotide polymorphisms and insertions and deletions, can help elucidate the genetic basis of an organism's pathogenicity, identify selective pressures, and resolve phylogenetic relationships. They also have the added benefit of possessing a comparatively low mutation rate, which contributes to their stability. However, there is a plethora of variant analysis tools with nuanced pipelines and conflicting recommendations for best practise, which can be confounding. This lack of standardisation means that variant analysis requires careful parameter optimisation, an understanding of its limitations, and the availability of high quality data. This review explores the value of variant detection when applied to non-model organisms such as clinically important protozoan pathogens. The limitations of current methods are discussed, including special considerations that require the end-users' attention to ensure that the results generated are reproducible, and the biological conclusions drawn are valid.

Long walk to genomics: History and current approaches to genome sequencing and assembly

Genomes represent the starting point of genetic studies. Since the discovery of DNA structure, scientists have devoted great efforts to determine their sequence in an exact way. In this review we provide a comprehensive historical background of the improvements in DNA sequencing technologies that have accompanied the major milestones in genome sequencing and assembly, ranging from early sequencing methods to Next-Generation Sequencing platforms. We then focus on the advantages and challenges of the current technologies and approaches, collectively known as Third Generation Sequencing. As these technical advancements have been accompanied by progress in analytical methods, we also review the bioinformatic tools currently employed in de novo genome assembly, as well as some applications of Third Generation Sequencing technologies and high-quality reference genomes.

Direct Approach toward Label-Free DNA Detection by Surface-Enhanced Raman Spectroscopy: Discrimination of a Single-Base Mutation in 50 Base-Paired Double Helixes

Surface-enhanced Raman spectroscopy (SERS) has exhibited great potential in label-free DNA detection. Owing to the limitation in chain length, it is however still challenging for SERS as a routine method to explore the intrinsic structural information on unmodified DNA. Here, we develop a universal SERS-based approach toward quantification of A/G in single-stranded DNAs (12 up to 28 bases) by introducing a novel interfacial agent, dichloromethane. DNA hybridization is successfully probed as evidenced by the typical SERS bands attributed to hydrogen bonds in a hairpin structure. More importantly, enlarged space of "hot spots" in SERS enables discrimination of single-base mutation in double-stranded DNA with 100 bases, which as a proof-of-concept study will pave a new avenue for highly sensitive DNA detection in clinical applications.

High Throughput Sequencing For Plant Virus Detection and Discovery

Over the last decade, virologists have discovered an unprecedented number of viruses using high throughput sequencing (HTS), which led to the advancement of our knowledge on the diversity of viruses in nature, particularly unraveling the virome of many agricultural crops. However, these new virus discoveries have often widened the gaps in our understanding of virus biology; the forefront of which is the actual role of a new virus in disease, if any. Yet, when used critically in etiological studies, HTS is a powerful tool to establish disease causality between the virus and its host. Conversely, with globalization, movement of plant material is increasingly more common and often a point of dispute between countries. HTS could potentially resolve these issues given its capacity to detect and discover. Although many pipelines are available for plant virus discovery, all share a common backbone. A description of the process of plant virus detection and discovery from HTS data are presented, providing a summary of the different pipelines available for scientists' utility in their research.

100 Years of evolving gene-disease complexities and scientific debutants

It's been over 100 years since the word `gene' is around and progressively evolving in several scientific directions. Time-to-time technological advancements have heavily revolutionized the field of genomics, especially when it's about, e.g. triple code development, gene number proposition, genetic mapping, data banks, gene-disease maps, catalogs of human genes and genetic disorders, CRISPR/Cas9, big data and next generation sequencing, etc. In this manuscript, we present the progress of genomics from pea plant genetics to the human genome project and highlight the molecular, technical and computational developments. Studying genome and epigenome led to the fundamentals of development and progression of human diseases, which includes chromosomal, monogenic, multifactorial and mitochondrial diseases. World Health Organization has classified, standardized and maintained all human diseases, when many academic and commercial online systems are sharing information about genes and linking to associated diseases. To efficiently fathom the wealth of this biological data, there is a crucial need to generate appropriate gene annotation repositories and resources. Our focus has been how many gene-disease databases are available worldwide and which sources are authentic, timely updated and recommended for research and clinical purposes. In this manuscript, we have discussed and compared 43 such databases and bioinformatics applications, which enable users to connect, explore and, if possible, download gene-disease data.

A theoretical analysis of single molecule protein sequencing via weak binding spectra

We propose and theoretically study an approach to massively parallel single molecule peptide sequencing, based on single molecule measurement of the kinetics of probe binding (Havranek, et al., 2013) to the N-termini of immobilized peptides. Unlike previous proposals, this method is robust to both weak and non-specific probe-target affinities, which we demonstrate by applying the method to a range of randomized affinity matrices consisting of relatively low-quality binders. This suggests a novel principle for proteomic measurement whereby highly non-optimized sets of low-affinity binders could be applicable for protein sequencing, thus shifting the burden of amino acid identification from biomolecular design to readout. Measurement of probe occupancy times, or of time-averaged fluorescence, should allow high-accuracy determination of N-terminal amino acid identity for realistic probe sets. The time-averaged fluorescence method scales well to weakly-binding probes with dissociation constants of tens or hundreds of micromolar, and bypasses photobleaching limitations associated with other fluorescence-based approaches to protein sequencing. We argue that this method could lead to an approach with single amino acid resolution and the ability to distinguish many canonical and modified amino acids, even using highly non-optimized probe sets. This readout method should expand the design space for single molecule peptide sequencing by removing constraints on the properties of the fluorescent binding probes.

Microfluidic Devices Containing ZnO Nanorods with Tunable Surface Chemistry and Wetting-Independent Water Mobility

Interest in polydimethylsiloxane (PDMS) microfluidic devices has grown dramatically in recent years, particularly in the context of improved performance lab-on-a-chip devices with decreasing channel size enabling more devices on ever smaller chips. As channels become smaller, the resistance to flow increases and the device structure must be able to withstand higher internal pressures. We report herein the fabrication of microstructured surfaces that promote water mobility independent of surface static wetting properties. The key tool in this approach is the growth of ZnO nanorods on the bottom face of the microfluidic device. We show that water flow in these devices is similar whether the textured nanorod-bearing surface is hydrophilic or superhydrophobic; that is, the device tolerates a wide range of surface wetting properties without changing the water flow within the device. This is not the case for smooth surfaces with different wetting properties, wherein hydrophilic surfaces result in slower flow rates. The ability to create monolayer-coated ZnO nanorods in a PDMS microfluidic device also allows for a variety of surface modifications within standard mass-produced devices. The inorganic ZnO nanorods can be coated with alkyl phosphonate monolayers. These monolayers can be used to convert hydrophilic surfaces into hydrophobic and even superhydrophobic surfaces that provide a platform for further surface modification. We also report photopatterned biomolecule immobilization within the channels on the monolayer-coated ZnO rods.

Exploring the Human Microbiome: The Potential Future Role of Next-Generation Sequencing in Disease Diagnosis and Treatment

The interaction between the human microbiome and immune system has an effect on several human metabolic functions and impacts our well-being. Additionally, the interaction between humans and microbes can also play a key role in determining the wellness or disease status of the human body. Dysbiosis is related to a plethora of diseases, including skin, inflammatory, metabolic, and neurological disorders. A better understanding of the host-microbe interaction is essential for determining the diagnosis and appropriate treatment of these ailments. The significance of the microbiome on host health has led to the emergence of new therapeutic approaches focused on the prescribed manipulation of the host microbiome, either by removing harmful taxa or reinstating missing beneficial taxa and the functional roles they perform. Culturing large numbers of microbial taxa in the laboratory is problematic at best, if not impossible. Consequently, this makes it very difficult to comprehensively catalog the individual members comprising a specific microbiome, as well as understanding how microbial communities function and influence host-pathogen interactions. Recent advances in sequencing technologies and computational tools have allowed an increasing number of metagenomic studies to be performed. These studies have provided key insights into the human microbiome and a host of other microbial communities in other environments. In the present review, the role of the microbiome as a therapeutic agent and its significance in human health and disease is discussed. Advances in high-throughput sequencing technologies for surveying host-microbe interactions are also discussed. Additionally, the correlation between the composition of the microbiome and infectious diseases as described in previously reported studies is covered as well. Lastly, recent advances in state-of-the-art bioinformatics software, workflows, and applications for analysing metagenomic data are summarized.

Next-Generation Sequencing and Its Application: Empowering in Public Health Beyond Reality

Next-generation sequencing has the ability to revolutionize almost all fields of biological science. It has drastically reduced the cost of sequencing. This allows us to study the whole genome or part of the genome to understand how the cellular functions are governed by the genetic code. The data obtained in huge quantity from sequencing upon analysis gives an insight to understand the mechanism of pathogen biology, virulence, and phenomenon of bacterial resistance, which helps in investigating the outbreak. This ultimately helps in the development of therapies for public health welfare against human pathogen and diagnostic reagents for the screening. This chapter includes the basic of Sanger’s method of DNA sequencing and next-generation sequencing, different available platforms for sequencing with their advantages, and limitations and their chemistry with an overview of downstream data analysis. Furthermore, the breadth of applications of high-throughput NGS technology for human health has been discussed.

Massively parallel sequencing techniques for forensics: A review

DNA sequencing, starting with Sanger's chain termination method in 1977 and evolving into the next generation sequencing (NGS) techniques of today that employ massively parallel sequencing (MPS), has become essential in application areas such as biotechnology, virology, and medical diagnostics. Reflected by the growing number of articles published over the last 2-3 years, these techniques have also gained attention in the forensic field. This review contains a brief description of first, second, and third generation sequencing techniques, and focuses on the recent developments in human DNA analysis applicable in the forensic field. Relevance to the forensic analysis is that besides generation of standard STR-profiles, DNA repeats can also be sequenced to look for polymorphisms. Furthermore, additional SNPs can be sequenced to acquire information on ancestry, paternity or phenotype. The current MPS systems are also very helpful in cases where only a limited amount of DNA or highly degraded DNA has been secured from a crime scene. If enough autosomal DNA is not present, mitochondrial DNA can be sequenced for maternal lineage analysis. These developments clearly demonstrate that the use of NGS will grow into an indispensable tool for forensic science.

Paving the way to single-molecule protein sequencing

Proteins are major building blocks of life. The protein content of a cell and an organism provides key information for the understanding of biological processes and disease. Despite the importance of protein analysis, only a handful of techniques are available to determine protein sequences, and these methods face limitations, for example, requiring a sizable amount of sample. Single-molecule techniques would revolutionize proteomics research, providing ultimate sensitivity for the detection of low-abundance proteins and the realization of single-cell proteomics. In recent years, novel single-molecule protein sequencing schemes that use fluorescence, tunnelling currents and nanopores have been proposed. Here, we present a review of these approaches, together with the first experimental efforts towards their realization. We discuss their advantages and drawbacks, and present our perspective on the development of single-molecule protein sequencing techniques.

Design of polymer particle dispersions (latexes) in the course of radical heterophase polymerization for biomedical applications

Dispersions of polymer particle (DPPs) are increasingly being exploited both as biomolecule carriers, and as markers in various DPP biomedical applications related to cell and molecular biology, enzymology, immunology, diagnostics, in vitro and in vivo visualization, bioseparation, etc. Their potential to reduce reaction scales, lower costs, improve the rate, sensitivity, selectivity, stability and reproducibility of assays governs the diversity of their bioapplications. This review focuses on the design of DPPs with innovative special properties in the course of free radical heterophase polymerization that provides careful control of both macromolecular and colloidal properties. We demonstrate approaches that, according to the polymerization technique, regulate the particle size, shape, particle size distribution, morphology, surface chemistry and functionality, as well as the formation of organic-inorganic hybrid DPPs. The production of bioreagents based on DPPs and their use in bioassay are also reviewed.

Next generation sequencing applications for cardiovascular disease

The Human Genome Project (HGP), as the primary sequencing of the human genome, lasted more than one decade to be completed using the traditional Sanger's method. At present, next-generation sequencing (NGS) technology could provide the genome sequence data in hours. NGS has also decreased the expense of sequencing; therefore, nowadays it is possible to carry out both whole-genome (WGS) and whole-exome sequencing (WES) for the variations detection in patients with rare genetic diseases as well as complex disorders such as common cardiovascular diseases (CVDs). Finding new variants may contribute to establishing a risk profile for the pathology process of diseases. Here, recent applications of NGS in cardiovascular medicine are discussed; both Mendelian disorders of the cardiovascular system and complex genetic CVDs including inherited cardiomyopathy, channelopathies, stroke, coronary artery disease (CAD) and are considered. We also state some future use of NGS in clinical practice for increasing our information about the CVDs genetics and the limitations of this new technology. Key messages Traditional Sanger's method was the mainstay for Human Genome Project (HGP); Sanger sequencing has high fidelity but is slow and costly as compared to next generation methods. Within cardiovascular medicine, NGS has been shown to be successful in identifying novel causative mutations and in the diagnosis of Mendelian diseases which are caused by a single variant in a single gene. NGS has provided the opportunity to perform parallel analysis of a great number of genes in an unbiased approach (i.e. without knowing the underlying biological mechanism) which probably contribute to advance our knowledge regarding the pathology of complex diseases such as CVD.

Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing

The transcriptome encompasses a range of species including messenger RNA, and other noncoding RNA such as rRNA, tRNA, and short and long noncoding RNAs. Due to the huge role played by mRNA in development and disease, several methods have been developed to sequence and characterize mRNA, with RNA sequencing (RNA-Seq) emerging as the current method of choice particularly for large high-throughput studies. Short-read RNA-Seq which involves sequencing of short cDNA fragments and computationally assembling them to reconstruct the transcriptome, or aligning them to a reference is the most widely used approach. However, due to inherent limitations of this approach in de novo transcriptome assembly and isoform quantification, long-read RNA-Seq approaches, which also happen to be single molecule sequencing approaches, are increasingly becoming the standard for de novo transcriptome assembly and isoform quantification. In this chapter, we review the technical aspects of the current methods of RNA-Seq, both short and long-read approaches, and data analysis methods available. We discuss recent advances in single-cell RNA-Seq and direct RNA-Seq approaches, which perhaps will dominate the future of RNA-Seq.

Single molecule sequencing of the M13 virus genome without amplification

Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.

Electrostatic confinement and manipulation of DNA molecules for genome analysis

Repeated sequences make up approximately two-thirds of the human genome, which become fully accountable when very large DNA molecules are analyzed. Long, single DNA molecules are problematic using common experimental techniques and fluidic devices because of mechanical considerations that include breakage, dealing with the massive size of these coils, or the huge length of stretched DNAs. Accordingly, we harness analyte “issues” as exploitable advantages by invention and characterization of the “molecular gate,” which controls and synchronizes formation of stretched molecules as DNA dumbbells within nanoslit geometries that may also offer new routes to separation. This was accomplished by theoretical studies and experiments leveraging a series of electrical forces acting on DNA molecules, device walls, and the fluid flows within our devices.

Very large DNA molecules enable comprehensive analysis of complex genomes, such as human, cancer, and plants because they span across sequence repeats and complex somatic events. When physically manipulated, or analyzed as single molecules, long polyelectrolytes are problematic because of mechanical considerations that include shear-mediated breakage, dealing with the massive size of these coils, or the length of stretched DNAs using common experimental techniques and fluidic devices. Accordingly, we harness analyte “issues” as exploitable advantages by our invention and characterization of the “molecular gate,” which controls and synchronizes formation of stretched DNA molecules as DNA dumbbells within nanoslit geometries. Molecular gate geometries comprise micro- and nanoscale features designed to synergize very low ionic strength conditions in ways we show effectively create an “electrostatic bottle.” This effect greatly enhances molecular confinement within large slit geometries and supports facile, synchronized electrokinetic loading of nanoslits, even without dumbbell formation. Device geometries were considered at the molecular and continuum scales through computer simulations, which also guided our efforts to optimize design and functionalities. In addition, we show that the molecular gate may govern DNA separations because DNA molecules can be electrokinetically triggered, by varying applied voltage, to enter slits in a size-dependent manner. Lastly, mapping the Mesoplasmaflorum genome, via synchronized dumbbell formation, validates our nascent approach as a viable starting point for advanced development that will build an integrated system capable of large-scale genome analysis.

Systems biology approach in plant abiotic stresses

Plant abiotic stresses are the major constraint on plant growth and development, causing enormous crop losses across the world. Plants have unique features to defend themselves against these challenging adverse stress conditions. They modulate their phenotypes upon changes in physiological, biochemical, molecular and genetic information, thus making them tolerant against abiotic stresses. It is of paramount importance to determine the stress-tolerant traits of a diverse range of genotypes of plant species and integrate those traits for crop improvement. Stress-tolerant traits can be identified by conducting genome-wide analysis of stress-tolerant genotypes through the highly advanced structural and functional genomics approach. Specifically, whole-genome sequencing, development of molecular markers, genome-wide association studies and comparative analysis of interaction networks between tolerant and susceptible crop varieties grown under stress conditions can greatly facilitate discovery of novel agronomic traits that protect plants against abiotic stresses.

Highly accurate fluorogenic DNA sequencing with information theory-based error correction

Eliminating errors in next-generation DNA sequencing has proved challenging. Here we present error-correction code (ECC) sequencing, a method to greatly improve sequencing accuracy by combining fluorogenic sequencing-by-synthesis (SBS) with an information theory-based error-correction algorithm. ECC embeds redundancy in sequencing reads by creating three orthogonal degenerate sequences, generated by alternate dual-base reactions. This is similar to encoding and decoding strategies that have proved effective in detecting and correcting errors in information communication and storage. We show that, when combined with a fluorogenic SBS chemistry with raw accuracy of 98.1%, ECC sequencing provides single-end, error-free sequences up to 200 bp. ECC approaches should enable accurate identification of extremely rare genomic variations in various applications in biology and medicine.

A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

Quantification of Rare Single-Molecule Species Based on Fluorescence Lifetime

Single-molecule tracking combined with fluorescence lifetime analysis can be a powerful tool for direct molecular quantification in solution. However, it is not clear what molecular identification accuracy and how many single-molecule tracks are required to achieve an accurate quantification of rare molecular species. Here we carry out calculations to answer these questions, based on experimentally obtained single-molecule lifetime data and an unbiased ratio estimator. Our results indicate that even at the molecular identification accuracy of 0.99999, 1.8 million tracks are still required in order to achieve 95% confidence level in rare-species quantification with relative error less than ±5%. Our work highlights the fundamental challenges that we are facing in accurate single-molecule identification and quantification without amplification.

Pardon the Interruption: A Modification of Fischer's Venerable Reaction for the Synthesis of Heterocycles and Natural Products

This account provides an overview of our laboratory's studies of an unusual variant of the Fischer indolization reaction. We describe the discovery of the so-called 'interrupted Fischer indolization' and the development of the reaction from a methodological standpoint. In addition, our efforts to evaluate and apply this methodology in the context of akuammiline alkaloid total synthesis are discussed.

"Marker of Self" CD47 on lentiviral vectors decreases macrophage-mediated clearance and increases delivery to SIRPA-expressing lung carcinoma tumors

Lentiviruses infect many cell types and are now widely used for gene delivery in vitro, but in vivo uptake of these foreign vectors by macrophages is a limitation. Lentivectors are produced here from packaging cells that overexpress "Marker of Self" CD47, which inhibits macrophage uptake of cells when prophagocytic factors are also displayed. Single particle analyses show "hCD47-Lenti" display properly oriented human-CD47 for interactions with the macrophage's inhibitory receptor SIRPA. Macrophages derived from human and NOD/SCID/Il2rg-/- (NSG) mice show a SIRPA-dependent decrease in transduction, i.e., transgene expression, by hCD47-Lenti compared to control Lenti. Consistent with known "Self" signaling pathways, macrophage transduction by control Lenti is decreased by drug inhibition of Myosin-II to the same levels as hCD47-Lenti. In contrast, human lung carcinoma cells express SIRPA and use it to enhance transduction by hCD47-Lenti- as illustrated by more efficient gene deletion using CRISPR/Cas9. Intravenous injection of hCD47-Lenti into NSG mice shows hCD47 prolongs circulation, unless a blocking anti-SIRPA is preinjected. In vivo transduction of spleen and liver macrophages also decreases for hCD47-Lenti while transduction of lung carcinoma xenografts increases. hCD47 could be useful when macrophage uptake is limiting on other viral vectors that are emerging in cancer treatments (e.g., Measles glycoprotein-pseudotyped lentivectors) and also in targeting various SIRPA-expressing tumors such as glioblastomas.

Analysis of tandem gene copies in maize chromosomal regions reconstructed from long sequence reads

Haplotype variation not only involves SNPs but also insertions and deletions, in particular gene copy number variations. However, comparisons of individual genomes have been difficult because traditional sequencing methods give too short reads to unambiguously reconstruct chromosomal regions containing repetitive DNA sequences. An example of such a case is the protein gene family in maize that acts as a sink for reduced nitrogen in the seed. Previously, 41-48 gene copies of the alpha zein gene family that spread over six loci spanning between 30- and 500-kb chromosomal regions have been described in two Iowa Stiff Stalk (SS) inbreds. Analyses of those regions were possible because of overlapping BAC clones, generated by an expensive and labor-intensive approach. Here we used single-molecule real-time (Pacific Biosciences) shotgun sequencing to assemble the six chromosomal regions from the Non-Stiff Stalk maize inbred W22 from a single DNA sequence dataset. To validate the reconstructed regions, we developed an optical map (BioNano genome map; BioNano Genomics) of W22 and found agreement between the two datasets. Using the sequences of full-length cDNAs from W22, we found that the error rate of PacBio sequencing seemed to be less than 0.1% after autocorrection and assembly. Expressed genes, some with premature stop codons, are interspersed with nonexpressed genes, giving rise to genotype-specific expression differences. Alignment of these regions with those from the previous analyzed regions of SS lines exhibits in part dramatic differences between these two heterotic groups.

Functional Studies of DNA-Protein Interactions Using FRET Techniques

Protein-DNA interactions underpin life and play key roles in all cellular processes and functions including DNA transcription, packaging, replication, and repair. Identifying and examining the nature of these interactions is therefore a crucial prerequisite to understand the molecular basis of how these fundamental processes take place. The application of fluorescence techniques and in particular fluorescence resonance energy transfer (FRET) to provide structural and kinetic information has experienced a stunning growth during the past decade. This has been mostly promoted by new advances in the preparation of dye-labeled nucleic acids and proteins and in optical sensitivity, where its implementation at the level of individual molecules has opened a new biophysical frontier. Nowadays, the application of FRET-based techniques to the analysis of protein-DNA interactions spans from the classical steady-state and time-resolved methods averaging over large ensembles to the analysis of distances, conformational changes, and enzymatic reactions in individual protein-DNA complexes. This chapter introduces the practical aspects of applying these methods for the study of protein-DNA interactions.