Computational and bioinformatics frameworks for next-generation whole exome and genome sequencing

KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data

BACKGROUND

Non-Invasive Prenatal Testing (NIPT) is a technique that allows pregnant women to screen for chromosomal abnormalities in their developing fetus without the need for invasive procedures like amniocentesis or chorionic villus sampling. However, current methods to detect anomaly from maternal cell-free DNAs (cfDNAs) that are based on the sequence read counts calculating z-scores face challenges with false positives and negatives. To address these challenges, we aimed to develop a novel NIPT algorithm named KF-NIPT, which is derived from the initials of k-mer and fetal fraction used in its development with the goal of significantly improving accuracy.

RESULTS

We developed a KF-NIPT, a new algorithm that estimate chromosomal anomaly by calculating K-mer-based sequence depth and fetal fraction from the whole genome sequencing (WGS) data. Moreover, we implemented a modified preprocessing pipeline for the WGS data, correcting the biases of the genomic mapping quality and the GC contents. The performance of our method was evaluated using publicly available NIPT data. We could demonstrate that our method has better accuracy and sensitivity compared to those of the previous methods.

CONCLUSIONS

We found that using k-mer and fetal fraction reduces errors in NIPT and have integrated this into a pipeline, showing that the traditional read count-based z-score method can be improved. KF-NIPT is implemented in the R and Python environment. The source code is available at https://github.com/eastbrain/KF-NIPT . KF-NIPT has been tested on Ubuntu Linux-64 server and Linux-64 on Windows using a WSL (Windows Subsystem for Linux).

Identification and whole-genome sequencing analysis of Vibrio vulnificus strains causing pearl gentian grouper disease in China

Vibrio vulnificus is a pathogenic bacterium that causes disease in marine fish, affecting fish farming and human health worldwide. In May 2021, in the Bohai Bay region, a disease broke out in commercially farmed pearl gentian grouper (♀Epinephelus fuscoguttatus × ♂Epinephelus lanceolatus), causing huge economic losses. The diseased fish had skin lesions, water accumulation in their abdomens, and showed tissue and organ damage. V. vulnificus biotype 2 has been reported in eels and other marine fish, but it is less reported in pearl gentian grouper. In this study, the pathogenic strain isolated from diseased fish was identified as V. vulnificus EPL 0201 biotype 2 on the basis of physiological and biochemical characteristics and the results of 16S rRNA gene and gyrB sequencing, virulence gene detection, and recursive infection experiments. To gain a comprehensive understanding of the pathogenicity and drug resistance of this strain, whole-genome sequencing was performed. Whole-genome analysis showed that the gene map of this strain was complete. The Virulence Factor Database annotation results showed that this strain had the key virulence factor genes vvhA and rtxA, which cause host disease. In addition, this strain had genes conferring resistance against cephalosporins, aminoglycosides, tetracyclines, and sulfonamides. Antimicrobial susceptibility testing confirmed the presence of these resistance genes identified in the genome. The results of this study show that V. vulnificus EPL 0201 biotype 2 is a multi-drug resistant strain with high pathogenicity.

Advancements in Genomic and Behavioral Neuroscience Analysis for the Study of Normal and Pathological Brain Function

Psychiatric and neurological disorders are influenced by an undetermined number of genes and molecular pathways that may differ among afflicted individuals. Functionally testing and characterizing biological systems is essential to discovering the interrelationship among candidate genes and understanding the neurobiology of behavior. Recent advancements in genetic, genomic, and behavioral approaches are revolutionizing modern neuroscience. Although these tools are often used separately for independent experiments, combining these areas of research will provide a viable avenue for multidimensional studies on the brain. Herein we will briefly review some of the available tools that have been developed for characterizing novel cellular and animal models of human disease. A major challenge will be openly sharing resources and datasets to effectively integrate seemingly disparate types of information and how these systems impact human disorders. However, as these emerging technologies continue to be developed and adopted by the scientific community, they will bring about unprecedented opportunities in our understanding of molecular neuroscience and behavior.

GIP: an open-source computational pipeline for mapping genomic instability from protists to cancer cells

Genome instability has been recognized as a key driver for microbial and cancer adaptation and thus plays a central role in many diseases. Genome instability encompasses different types of genomic alterations, yet most available genome analysis software are limited to just one type of mutation. To overcome this limitation and better understand the role of genetic changes in enhancing pathogenicity we established GIP, a novel, powerful bioinformatic pipeline for comparative genome analysis. Here, we show its application to whole genome sequencing datasets of Leishmania, Plasmodium, Candida and cancer. Applying GIP on available data sets validated our pipeline and demonstrated the power of our tool to drive biological discovery. Applied to Plasmodium vivax genomes, our pipeline uncovered the convergent amplification of erythrocyte binding proteins and identified a nullisomic strain. Re-analyzing genomes of drug adapted Candida albicans strains revealed correlated copy number variations of functionally related genes, strongly supporting a mechanism of epistatic adaptation through interacting gene-dosage changes. Our results illustrate how GIP can be used for the identification of aneuploidy, gene copy number variations, changes in nucleic acid sequences, and chromosomal rearrangements. Altogether, GIP can shed light on the genetic bases of cell adaptation and drive disease biomarker discovery.

Emerging roles of rare and low-frequency genetic variants in type 1 diabetes mellitus

Type 1 diabetes mellitus (T1DM) is defined as an autoimmune disorder and has enormous complexity and heterogeneity. Although its precise pathogenic mechanisms are obscure, this disease is widely acknowledged to be precipitated by environmental factors in individuals with genetic susceptibility. To date, the known susceptibility loci, which have mostly been identified by genome-wide association studies, can explain 80%–85% of the heritability of T1DM. Researchers believe that at least a part of its missing genetic component is caused by undetected rare and low-frequency variants. Most common variants have only small to modest effect sizes, which increases the difficulty of dissecting their functions and restricts their potential clinical application. Intriguingly, many studies have indicated that rare and low-frequency variants have larger effect sizes and play more significant roles in susceptibility to common diseases, including T1DM, than common variants do. Therefore, better recognition of rare and low-frequency variants is beneficial for revealing the genetic architecture of T1DM and for providing new and potent therapeutic targets for this disease. Here, we will discuss existing challenges as well as the great significance of this field and review current knowledge of the contributions of rare and low-frequency variants to T1DM.

Next-generation sequencing technologies: An overview

Since the days of Sanger sequencing, next-generation sequencing technologies have significantly evolved to provide increased data output, efficiencies, and applications. These next generations of technologies can be categorized based on read length. This review provides an overview of these technologies as two paradigms: short-read, or "second-generation," technologies, and long-read, or "third-generation," technologies. Herein, short-read sequencing approaches are represented by the most prevalent technologies, Illumina and Ion Torrent, and long-read sequencing approaches are represented by Pacific Biosciences and Oxford Nanopore technologies. All technologies are reviewed along with reported advantages and disadvantages. Until recently, short-read sequencing was thought to provide high accuracy limited by read-length, while long-read technologies afforded much longer read-lengths at the expense of accuracy. Emerging developments for third-generation technologies hold promise for the next wave of sequencing evolution, with the co-existence of longer read lengths and high accuracy.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

Identification of a de novo FOXP1 mutation and incidental discovery of inherited genetic variants contributing to a case of autism spectrum disorder and epilepsy

Background

Autism spectrum disorder is commonly co‐diagnosed intellectual disability, language disorder, anxiety, and epilepsy, however, symptom management is difficult due to the complex genetic nature of ASD.

Methods

We present a next‐generation sequencing‐based case study with both de novo and inherited genetic variants and highlight the impact of structural variants on post‐translational regulation of protein expression. Since management of symptoms has classically been through pharmaceutical therapies, a pharmacogenomics screen was also utilized to determine possible drug/gene interactions.

Results

A de novo variant was identified within the FOXP1 3′ untranslated regulatory region using exome sequencing. Additionally, inherited variants that likely contribute to the current and potential future traits were identified within the COMT, SLC6A4, CYP2C19, and CYP2D6 genes.

Conclusion

This study aims to elucidate how a collection of variant genotypes could potentially impact neural development resulting in a unique phenotype including ASD and epilepsy. Each gene's contribution to neural development is assessed, and the interplay of these genotypes is discussed. The results highlight the utility of exome sequencing in conjunction with pharmacogenomics screening when evaluating possible causes of and therapeutic treatments for ASD‐related symptoms.

Ma Huang Tang ameliorates bronchial asthma symptoms through the TLR9 pathway

CONTEXT

Ma Huang Tang (MHT) has been used to treat influenza, fever, bronchial asthma, etc. as a traditional Chinese medication. However, the anti-inflammation mechanism of MHT remains unclear.

OBJECTIVE

The study identifies the possible mechanisms of MHT on ovalbumin (OVA)-induced acute bronchial asthma in mice.

MATERIALS AND METHODS

First, an asthma-related protein-protein interaction (PPI) network was constructed. And then, the acute bronchial asthma mice models were established by exposing to aerosolized 1% ovalbumin for 30 min/day for 1 week, and the mice were administered 2.0, 4.0, or 8.0 g/kg of MHT daily. To evaluate therapeutic effect, sensitization time, abdominal breathing time, eosinophils in bronchoalveolar lavage fluid, and tissue and trachea pathology were examined. Related genes were measured using RNA sequencing (RNA-seq). The expression levels of TLR9 in lung and trachea tissues were determined by immunohistochemical staining.

RESULTS

MHT had a LD₅₀ = 19.2 g/kg against asthma, while MHT at high doses (8 g/kg) effectively extended the sensitization time and abdominal breathing time and alleviated OVA-induced eosinophilic airway inflammation and mitigated pathological changes. The RNA-seq assay showed that the high-dose MHT resulted in a significant decrease in the levels of TLR9, TRAF6, TAB2, etc. in the lung tissue. Immunohistochemical assay confirmed the down-regulated of TLR9. Molecular docking revealed that six MHT compounds potentially mediated the TLR9 signaling pathway.

DISCUSSION AND CONCLUSIONS

MHT could mitigate the pathological changes of acute asthma-like syndrome through inhibition of the TLR9 pathway. Results of this study may provide a reference for the development of a novel therapy for patients with allergic asthma.

Challenges in the introduction of next-generation sequencing (NGS) for diagnostics of myeloid malignancies into clinical routine use

Given the vast phenotypic and genetic heterogeneity of acute and chronic myeloid malignancies, hematologists have eagerly awaited the introduction of next-generation sequencing (NGS) into the routine diagnostic armamentarium to enable a more differentiated disease classification, risk stratification, and improved therapeutic decisions. At present, an increasing number of hematologic laboratories are in the process of integrating NGS procedures into the diagnostic algorithms of patients with acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs). Inevitably accompanying such developments, physicians and molecular biologists are facing unexpected challenges regarding the interpretation and implementation of molecular genetic results derived from NGS in myeloid malignancies. This article summarizes typical challenges that may arise in the context of NGS-based analyses at diagnosis and during follow-up of myeloid malignancies.

Next generation sequencing: implications in personalized medicine and pharmacogenomics

A breakthrough in next generation sequencing (NGS) in the last decade provided an unprecedented opportunity to investigate genetic variations in humans and their roles in health and disease. NGS offers regional genomic sequencing such as whole exome sequencing of coding regions of all genes, as well as whole genome sequencing. RNA-seq offers sequencing of the entire transcriptome and ChIP-seq allows for sequencing the epigenetic architecture of the genome. Identifying genetic variations in individuals can be used to predict disease risk, with the potential to halt or retard disease progression. NGS can also be used to predict the response to or adverse effects of drugs or to calculate appropriate drug dosage. Such a personalized medicine also provides the possibility to treat diseases based on the genetic makeup of the patient. Here, we review the basics of NGS technologies and their application in human diseases to foster human healthcare and personalized medicine.

Contribution of Next-Generation Sequencing to Aquatic and Fish Virology

The recent technological advances in nucleic acid sequencing, called next-generation sequencing (NGS), have revolutionized the field of genomics and have also influenced viral research. Aquatic viruses, and especially those infecting fish, have also greatly benefited from NGS technologies, which provide a huge amount of molecular information at a low cost in a relatively short period of time. Here, we review the use of the current high-throughput sequencing platforms with a special focus on the associated challenges (regarding sample preparation and bioinformatics) in their applications to the field of aquatic virology, especially for: (i) discovering novel viruses that may be associated with fish mortalities, (ii) elucidating the mechanisms of pathogenesis, and finally (iii) studying the molecular epidemiology of these pathogens.

Systematic characterization and comparison of the CYP2C9 variability of the Orang Asli in Malaysia with 12 populations

We conducted a systematic characterization of CYP2C9 variants in 61 Orang Asli and 96 Singaporean Malays using the whole genome sequences data and compared the variants with the other 11 HapMap populations. The frequency of rs1057910 (CYP2C9*3) is the highest in the Orang Asli compared to other populations. Three alleles with clinical implication were detected in the Orang Asli while 2 were found in the Singaporean Malays. Large numbers of the Orang Asli are predicted to have reduced metabolic capacity and therefore they would require a lower dose of drugs which are metabolized by CYP2C9. They are also at increased risks of adverse effects and therapeutic failures. A large number of CYP2C9 variants in the Orang Asli were not in the Hardy Weinberg Equilibrium which could be due to small sample size or mutations that disrupt the equilibrium of allele frequencies. In conclusion, different polymorphism patterns, allele frequencies, genotype frequencies and LD blocks are observed between the Orang Asli, the Singaporean Malays and the other populations. The study provided new information on the genetic polymorphism of CYP2C9 which is important for the implementation of precision medicine for the Orang Asli.

The long tail and rare disease research: the impact of next-generation sequencing for rare Mendelian disorders

There are an estimated 6000-8000 rare Mendelian diseases that collectively affect 30 million individuals in the United States. The low incidence and prevalence of these diseases present significant challenges to improving diagnostics and treatments. Next-generation sequencing (NGS) technologies have revolutionized research of rare diseases. This article will first comment on the effectiveness of NGS through the lens of long-tailed economics. We then provide an overview of recent developments and challenges of NGS-based research on rare diseases. As the quality of NGS studies improve and the cost of sequencing decreases, NGS will continue to make a significant impact on the study of rare diseases moving forward.

The promise of omics-based approaches to cancer prevention

Cancer is a complex category of diseases caused in large part by genetic or genomic, transcriptomic, and epigenetic or epigenomic alterations in affected cells and the surrounding microenvironment. Carcinogenesis reflects the clonal expansion of cells that progressively acquire these genetic and epigenetic alterations-changes that, in turn, lead to modifications at the RNA level. Gradually advancing technology and most recently, the advent of next-generation sequencing (NGS), combined with bioinformatics analytic tools, have revolutionized our ability to interrogate cancer cells. The ultimate goal is to apply these high-throughput technologies to the various aspects of clinical cancer care: cancer-risk assessment, diagnosis, as well as target identification for treatment and prevention. In this article, we emphasize how the knowledge gained through large-scale omics-oriented approaches, with a focus on variations at the level of nucleic acids, can inform the field of chemoprevention.

Rare variant association studies: considerations, challenges and opportunities

Genome-wide association studies (GWASs) have successfully uncovered thousands of robust associations between common variants and complex traits and diseases. Despite these successes, much of the heritability of these traits remains unexplained. Because low-frequency and rare variants are not tagged by conventional genome-wide genotyping arrays, they may represent an important and understudied component of complex trait genetics. In contrast to common variant GWASs, there are many different types of study designs, assays and analytic techniques that can be utilized for rare variant association studies (RVASs). In this review, we briefly present the different technologies available to identify rare genetic variants, including novel exome arrays. We also compare the different study designs for RVASs and argue that the best design will likely be phenotype-dependent. We discuss the main analytical issues relevant to RVASs, including the different statistical methods that can be used to test genetic associations with rare variants and the various bioinformatic approaches to predicting in silico biological functions for variants. Finally, we describe recent rare variant association findings, highlighting the unexpected conclusion that most rare variants have modest-to-small effect sizes on phenotypic variation. This observation has major implications for our understanding of the genetic architecture of complex traits in the context of the unexplained heritability challenge.

YMAP: a pipeline for visualization of copy number variation and loss of heterozygosity in eukaryotic pathogens

The design of effective antimicrobial therapies for serious eukaryotic pathogens requires a clear understanding of their highly variable genomes. To facilitate analysis of copy number variations, single nucleotide polymorphisms and loss of heterozygosity events in these pathogens, we developed a pipeline for analyzing diverse genome-scale datasets from microarray, deep sequencing, and restriction site associated DNA sequence experiments for clinical and laboratory strains of Candida albicans, the most prevalent human fungal pathogen. The Y_MAP pipeline (http://lovelace.cs.umn.edu/Ymap/) automatically illustrates genome-wide information in a single intuitive figure and is readily modified for the analysis of other pathogens with small genomes.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

Bioinformatics in otolaryngology research. Part one: concepts in DNA sequencing and gene expression analysis

BACKGROUND

Advances in high-throughput molecular biology, genomics and epigenetics, coupled with exponential increases in computing power and data storage, have led to a new era in biological research and information. Bioinformatics, the discipline devoted to storing, analysing and interpreting large volumes of biological data, has become a crucial component of modern biomedical research. Research in otolaryngology has evolved along with these advances.

OBJECTIVES

This review highlights several modern high-throughput research methods, and focuses on the bioinformatics principles necessary to carry out such studies. Several examples from recent literature pertinent to otolaryngology are provided. The review is divided into two parts; this first part discusses the bioinformatics approaches applied in nucleotide sequencing and gene expression analysis.

CONCLUSION

This paper demonstrates how high-throughput nucleotide sequencing and transcriptomics are changing biology and medicine, and describes how these changes are affecting otorhinolaryngology. Sound bioinformatics approaches are required to obtain useful information from the vast new sources of data.

Rapid point of care diagnostic tests for viral and bacterial respiratory tract infections--needs, advances, and future prospects

Respiratory tract infections rank second as causes of adult and paediatric morbidity and mortality worldwide. Respiratory tract infections are caused by many different bacteria (including mycobacteria) and viruses, and rapid detection of pathogens in individual cases is crucial in achieving the best clinical management, public health surveillance, and control outcomes. Further challenges in improving management outcomes for respiratory tract infections exist: rapid identification of drug resistant pathogens; more widespread surveillance of infections, locally and internationally; and global responses to infections with pandemic potential. Developments in genome amplification have led to the discovery of several new respiratory pathogens, and sensitive PCR methods for the diagnostic work-up of these are available. Advances in technology have allowed for development of single and multiplexed PCR techniques that provide rapid detection of respiratory viruses in clinical specimens. Microarray-based multiplexing and nucleic-acid-based deep-sequencing methods allow simultaneous detection of pathogen nucleic acid and multiple antibiotic resistance, providing further hope in revolutionising rapid point of care respiratory tract infection diagnostics.

Automation of molecular-based analyses: a primer on massively parallel sequencing

Recent advances in genetics have been enabled by new genetic sequencing techniques called massively parallel sequencing (MPS) or next-generation sequencing. Through the ability to sequence in parallel hundreds of thousands to millions of DNA fragments, the cost and time required for sequencing has dramatically decreased. There are a number of different MPS platforms currently available and being used in Australia. Although they differ in the underlying technology involved, their overall processes are very similar: DNA fragmentation, adaptor ligation, immobilisation, amplification, sequencing reaction and data analysis. MPS is being used in research, translational and increasingly now also in clinical settings. Common applications include sequencing of whole genomes, whole exomes or targeted genes for disease-causing gene discovery, genetic diagnosis and targeted cancer therapy. Even though the revolution that is occurring with MPS is exciting due to its increasing use, improving and emerging technologies and new applications, significant challenges still exist. Particularly challenging issues are the bioinformatics required for data analysis, interpretation of results and the ethical dilemma of 'incidental findings'.

Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

Pathology informatics fellowship training: Focus on molecular pathology

Background:

Pathology informatics is both emerging as a distinct subspecialty and simultaneously becoming deeply integrated within the breadth of pathology practice. As specialists, pathology informaticians need a broad skill set, including aptitude with information fundamentals, information systems, workflow and process, and governance and management. Currently, many of those seeking training in pathology informatics additionally choose training in a second subspecialty. Combining pathology informatics training with molecular pathology is a natural extension, as molecular pathology is a subspecialty with high potential for application of modern biomedical informatics techniques.

Methods and Results:

Pathology informatics and molecular pathology fellows and faculty evaluated the current fellowship program's core curriculum topics and subtopics for relevance to molecular pathology. By focusing on the overlap between the two disciplines, a structured curriculum consisting of didactics, operational rotations, and research projects was developed for those fellows interested in both pathology informatics and molecular pathology.

Conclusions:

The scope of molecular diagnostics is expanding dramatically as technology advances and our understanding of disease extends to the genetic level. Here, we highlight many of the informatics challenges facing molecular pathology today, and outline specific informatics principles necessary for the training of future molecular pathologists.

Sequencing and computational approaches to identification and characterization of microbial organisms

The recent advances in sequencing technologies and computational approaches are propelling scientists ever closer towards complete understanding of human-microbial interactions. The powerful sequencing platforms are rapidly producing huge amounts of nucleotide sequence data which are compiled into huge databases. This sequence data can be retrieved, assembled, and analyzed for identification of microbial pathogens and diagnosis of diseases. In this article, we present a commentary on how the metagenomics incorporated with microarray and new sequencing techniques are helping microbial detection and characterization.