Landscape of next-generation sequencing technologies

Synthetic DNA: the next generation of big data storage

With world wide data predicted to exceed 40 trillion gigabytes by 2020, big data storage is a very real and escalating problem. Herein, we discuss the utility of synthetic DNA as a robust and eco-friendly archival data storage solution of the future.

Loss of culturability of Salmonella enterica subsp. enterica serovar Typhimurium upon cell-cell contact with human fecal bacteria

Loss of culturability of Salmonella enterica subsp. enterica serovar Typhimurium has been observed in mixed cultures with anaerobic fecal bacteria under conditions that allow local interaction between cells, such as cell contact. A reduction of a population of culturable S. Typhimurium on the order of ∼10(4) to 10(5) CFU/ml was observed in batch anaerobic mixed cultures with fecal samples from different human donors. Culturability was not affected either in supernatants collected at several times from fecal cultures, when separated from fecal bacteria by a membrane of 0.45-μm pore size, or when in contact with inactivated fecal bacterial cells. Loss of culturability kinetics was characterized by a sharp reduction of several logarithmic units followed by a pronounced tail. A mathematical model was developed to describe the rate of loss of culturability as a function of the frequency of encounters between populations and the probability of inactivation after encounter. The model term F(S · F)(1/2) quantifies the effect of the concentration of both populations, fecal bacteria (F) and S. Typhimurium (S), on the loss of culturability of S. Typhimurium by cell contact with fecal bacteria. When the value of F(S · F)(1/2) decreased below ca. 10(15) (CFU/ml)(2), the frequency of encounters sharply decreased, leading to the deceleration of the inactivation rate and to the tailing off of the S. Typhimurium population. The probability of inactivation after encounter, P, was constant, with an estimated value of ∼10(-5) for all data sets. P might be characteristic of the mechanism of growth inhibition after a cell encounter.

Electrophoresis of deformable polyelectrolytes in a nanofluidic channel

The influence of the shape of a polyelectrolyte (PE) on its electrophoretic behavior in a nanofluidic channel is investigated by considering the translocation of a deformable ellipsoidal PE along the axis of a cylindrical nanochannel. A continuum model comprising a Poisson equation for the electric potential, Nernst-Planck equations for the ionic concentrations, and modified Stokes equations for the flow field is adopted. The effects of the PE shape, boundary, bulk ionic concentration, counterion condensation, electroosmotic retardation flow, and electroosmotic flow (EOF) on the PE mobility are discussed. Several interesting behaviors are observed. For example, if the nanochannel is uncharged and the double layer is thick, then the PE mobility increases (decreases) with increasing double-layer thickness for a smaller (larger) boundary, which has not been reported previously. If the nanochannel is negatively charged and the double layer is thick, then a negatively charged PE moves in the direction of the applied electric field. The results gathered provide necessary information for both the interpretation of experimental data and the design of nanochannel-based sensing devices.

Towards practical, high-capacity, low-maintenance information storage in synthesized DNA

Digital production, transmission and storage have revolutionized how we access and use information but have also made archiving an increasingly complex task that requires active, continuing maintenance of digital media. This challenge has focused some interest on DNA as an attractive target for information storage because of its capacity for high-density information encoding, longevity under easily achieved conditions and proven track record as an information bearer. Previous DNA-based information storage approaches have encoded only trivial amounts of information or were not amenable to scaling-up, and used no robust error-correction and lacked examination of their cost-efficiency for large-scale information archival. Here we describe a scalable method that can reliably store more information than has been handled before. We encoded computer files totalling 739 kilobytes of hard-disk storage and with an estimated Shannon information of 5.2 × 10(6) bits into a DNA code, synthesized this DNA, sequenced it and reconstructed the original files with 100% accuracy. Theoretical analysis indicates that our DNA-based storage scheme could be scaled far beyond current global information volumes and offers a realistic technology for large-scale, long-term and infrequently accessed digital archiving. In fact, current trends in technological advances are reducing DNA synthesis costs at a pace that should make our scheme cost-effective for sub-50-year archiving within a decade.

Disentangling associated genomes

The recovery and assembly of genome sequences from samples containing communities of organisms pose several challenges. Because it is rarely possible to disassociate the resident organisms prior to sequencing, a major obstacle is the assignment of sequences to a single genome that can be fully assembled. This chapter delineates many of the decisions, methodologies, and approaches that can lead to the generation of complete or nearly complete microbial genome sequences from heterogeneous samples-that is, the procedures that allow us to turn metagenomes into genomes.

Chip in a lab: Microfluidics for next generation life science research

Microfluidic circuits are characterized by fluidic channels and chambers with a linear dimension on the order of tens to hundreds of micrometers. Components of this size enable lab-on-a-chip technology that has much promise, for example, in the development of point-of-care diagnostics. Micro-scale fluidic circuits also yield practical, physical, and technological advantages for studying biological systems, enhancing the ability of researchers to make more precise quantitative measurements. Microfluidic technology has thus become a powerful tool in the life science research laboratory over the past decade. Here we focus on chip-in-a-lab applications of microfluidics and survey some examples of how small fluidic components have provided researchers with new tools for life science research.

Merging multiple omics datasets in silico: statistical analyses and data interpretation

By the combinations of high-throughput analytical technologies in the fields of transcriptomics, proteomics, and metabolomics, we are now able to gain comprehensive and quantitative snapshots of the intracellular processes. Dynamic intracellular activities and their regulations can be elucidated by systematic observation of these multi-omics data. On the other hand, careful statistical analysis is necessary for such integration, since each of the omics layers as well as the specific analytical methodologies harbor different levels of noise and variations. Moreover, interpretation of such multitude of data requires an intuitive pathway context. Here we describe such statistical methods for the integration and comparison of multi-omics data, as well as the computational methods for pathway reconstruction, ID conversion, mapping, and visualization that play key roles for the efficient study of multi-omics information.

Discovery of posttranscriptional regulatory RNAs using next generation sequencing technologies

Next generation sequencing (NGS) has revolutionized the way by which we engineer metabolism by radically altering the path to genome-wide inquiries. This is due to the fact that NGS approaches offer several powerful advantages over traditional methods that include the ability to fully sequence hundreds to thousands of genes in a single experiment and simultaneously detect homozygous and heterozygous deletions, alterations in gene copy number, insertions, translocations, and exome-wide substitutions that include "hot-spot mutations." This chapter describes the use of these technologies as a sequencing technique for transcriptome analysis and discovery of regulatory RNA elements in the context of three main platforms: Illumina HiSeq, 454 pyrosequencing, and SOLiD sequencing. Specifically, this chapter focuses on the use of Illumina HiSeq, since it is the most widely used platform for RNA discovery and transcriptome analysis. Regulatory RNAs have now been found in all branches of life. In bacteria, noncoding small RNAs (sRNAs) are involved in highly sophisticated regulatory circuits that include quorum sensing, carbon metabolism, stress responses, and virulence (Gorke and Vogel, Gene Dev 22:2914-2925, 2008; Gottesman, Trends Genet 21:399-404, 2005; Romby et al., Curr Opin Microbiol 9:229-236, 2006). Further characterization of the underlying regulation of gene expression remains poorly understood given that it is estimated that over 60% of all predicted genes remain hypothetical and the 5' and 3' untranslated regions are unknown for more than 90% of the genes (Siegel et al., Trends Parasitol 27:434-441, 2011). Importantly, manipulation of the posttranscriptional regulation that occurs at the level of RNA stability and export, trans-splicing, polyadenylation, protein translation, and protein stability via untranslated regions (Clayton, EMBO J 21:1881-1888, 2002; Haile and Papadopoulou, Curr Opin Microbiol 10:569-577, 2007) could be highly beneficial to metabolic engineering.

Deep transcriptome profiling of ovarian cancer cells using next-generation sequencing approach

The next-generation sequencing technology allows identification and cataloging of almost all mRNAs, even those with only one or a few transcripts per cell. To understand the chemotherapy response program in ovarian cancer cells at deep transcript sequencing levels, we applied two next-generation sequencing technologies to study two ovarian chemotherapy response models: the in vitro acquired cisplatin-resistant cell line model (IGROV-1-CP and IGROV1) and the in vivo ovarian cancer tissue resistant model. We identified 3,422 signatures (2,957 genes) that are significantly differentially expressed between IGROV1 and IGROV-1-CP cells (P < .001). Our database offers the first comprehensive view of the digital transcriptomes of ovarian cancer cell lines and tissues with different chemotherapy response phenotypes.

Genetic association studies in lumbar disc degeneration: a systematic review

Objective

Low back pain is associated with lumbar disc degeneration, which is mainly due to genetic predisposition. The objective of this study was to perform a systematic review to evaluate genetic association studies in lumbar disc degeneration as defined on magnetic resonance imaging (MRI) in humans.

Methods

A systematic literature search was conducted in MEDLINE, MEDLINE In-Process, SCOPUS, ISI Web of Science, The Genetic Association Database and The Human Genome Epidemiology Network for information published between 1990–2011 addressing genes and lumbar disc degeneration. Two investigators independently identified studies to determine inclusion, after which they performed data extraction and analysis. The level of cumulative genetic association evidence was analyzed according to The HuGENet Working Group guidelines.

Results

Fifty-two studies were included for review. Forty-eight studies reported at least one positive association between a genetic marker and lumbar disc degeneration. The phenotype definition of lumbar disc degeneration was highly variable between the studies and replications were inconsistent. Most of the associations presented with a weak level of evidence. The level of evidence was moderate for ASPN (D-repeat), COL11A1 (rs1676486), GDF5 (rs143383), SKT (rs16924573), THBS2 (rs9406328) and MMP9 (rs17576).

Conclusions

Based on this first extensive systematic review on the topic, the credibility of reported genetic associations is mostly weak. Clear definition of lumbar disc degeneration phenotypes and large population-based cohorts are needed. An international consortium is needed to standardize genetic association studies in relation to disc degeneration.

Methods, Challenges and Potentials of Single Cell RNA-seq

RNA-sequencing (RNA-seq) has become the tool of choice for transcriptomics. Several recent studies demonstrate its successful adaption to single cell analysis. This allows new biological insights into cell differentiation, cell-to-cell variation and gene regulation, and how these aspects depend on each other. Here, I review the current single cell RNA-seq (scRNA-seq) efforts and discuss experimental protocols, challenges and potentials.

Targeted transcript profiling by sequencing

In this work we present a targeted gene expression strategy employing trinucleotide threading (TnT) amplification and massive parallel sequencing. We have previously shown that TnT combined with array readout accurately monitors expression levels. However, with this detection strategy spurious products go undetected. Accordingly, we adapted the TnT protocol to massive parallel sequencing to acquire an unbiased view of the entire TnT-generated product population. In this manner we investigated the identity of undesired products, their extent at different oligonucleotide:RNA ratios and their effect on the expression levels. We demonstrate that TnT gene expression profiling with massive sequencing readout renders reliable expression data from as low as 3.5 ng of total RNA. Moreover, using 350 ng of total RNA results in only 0.7% to 1.1% undesired products. When lowering the amount of input material, the undesired product fraction increases but this does not influence the expression profiles.

Genomic impact of cigarette smoke, with application to three smoking-related diseases

There is considerable evidence that inhaled toxicants such as cigarette smoke can cause both irreversible changes to the genetic material (DNA mutations) and putatively reversible changes to the epigenetic landscape (changes in the DNA methylation and chromatin modification state). The diseases that are believed to involve genetic and epigenetic perturbations include lung cancer, chronic obstructive pulmonary disease (COPD), and cardiovascular disease (CVD), all of which are strongly linked epidemiologically to cigarette smoking. In this review, we highlight the significance of genomics and epigenomics in these major smoking-related diseases. We also summarize the in vitro and in vivo findings on the specific perturbations that smoke and its constituent compounds can inflict upon the genome, particularly on the pulmonary system. Finally, we review state-of-the-art genomics and new techniques such as high-throughput sequencing and genome-wide chromatin assays, rapidly evolving techniques which have allowed epigenetic changes to be characterized at the genome level. These techniques have the potential to significantly improve our understanding of the specific mechanisms by which exposure to environmental chemicals causes disease. Such mechanistic knowledge provides a variety of opportunities for enhanced product safety assessment and the discovery of novel therapeutic interventions.

A genetic linkage map of Brassica carinata constructed with a doubled haploid population

Brassica carinata is an important oilseed crop with unique favourable traits that are desirable for other Brassica crops. However, given the limited research into genetic resources in B. carinata, knowledge of the genetic structure of this species is relatively poor. Nine homozygous, genetically distinct accessions of B. carinata were obtained via microspore culture, from which two divergent doubled haploid (DH) lines were used to develop a DH mapping population that consisted of 183 lines. The mapping population showed segregation of multiple traits of interest. A genetic map was constructed with PCR-based markers, and a total of 212 loci, which covered 1,703 cM, were assigned to eight linkage groups in the B genome and nine linkage groups in the C genome, which allowed comparison with genetic maps of other important Brassica species that contain the B/C genome(s). Loci for two Mendelian-inherited traits related to pigmentation (petal and anther tip colour) and one quantitative trait (seed coat colour) were identified using the linkage map. The significance of the mapping population in the context of genetic improvement of Brassica crops is discussed.

Genotyping-by-Sequencing in Plants

The advent of next-generation DNA sequencing (NGS) technologies has led to the development of rapid genome-wide Single Nucleotide Polymorphism (SNP) detection applications in various plant species. Recent improvements in sequencing throughput combined with an overall decrease in costs per gigabase of sequence is allowing NGS to be applied to not only the evaluation of small subsets of parental inbred lines, but also the mapping and characterization of traits of interest in much larger populations. Such an approach, where sequences are used simultaneously to detect and score SNPs, therefore bypassing the entire marker assay development stage, is known as genotyping-by-sequencing (GBS). This review will summarize the current state of GBS in plants and the promises it holds as a genome-wide genotyping application.

Why assembling plant genome sequences is so challenging

In spite of the biological and economic importance of plants, relatively few plant species have been sequenced. Only the genome sequence of plants with relatively small genomes, most of them angiosperms, in particular eudicots, has been determined. The arrival of next-generation sequencing technologies has allowed the rapid and efficient development of new genomic resources for non-model or orphan plant species. But the sequencing pace of plants is far from that of animals and microorganisms. This review focuses on the typical challenges of plant genomes that can explain why plant genomics is less developed than animal genomics. Explanations about the impact of some confounding factors emerging from the nature of plant genomes are given. As a result of these challenges and confounding factors, the correct assembly and annotation of plant genomes is hindered, genome drafts are produced, and advances in plant genomics are delayed.

Application of metatranscriptomics to soil environments

The activities of soil microbial communities are of critical importance to terrestrial ecosystem functioning. The mechanisms that determine the interactions between soil microorganisms, their environment and neighbouring organisms, however, are poorly understood. Due to advances in sequencing technologies, an increasing number of metagenomics studies are being conducted on samples from diverse environments including soils. This information has not only increased our awareness of the functional potential of soil microbial communities, but also constitutes powerful reference material for soil metatranscriptomics studies. Metatranscriptomics provides a snapshot of transcriptional profiles that correspond to discrete populations within a microbial community at the time of sampling. This information can indicate the potential activities of complex microbial communities and the mechanisms that regulate them. Here we summarise the technical challenges for metatranscriptomics applied to soil environments and discuss approaches for gaining biologically meaningful insight into these datasets.

Assessing graphene nanopores for sequencing DNA

Using all-atom molecular dynamics and atomic-resolution Brownian dynamics, we simulate the translocation of single-stranded DNA through graphene nanopores and characterize the ionic current blockades produced by DNA nucleotides. We find that transport of single DNA strands through graphene nanopores may occur in single nucleotide steps. For certain pore geometries, hydrophobic interactions with the graphene membrane lead to a dramatic reduction in the conformational fluctuations of the nucleotides in the nanopores. Furthermore, we show that ionic current blockades produced by different DNA nucleotides are, in general, indicative of the nucleotide type, but very sensitive to the orientation of the nucleotides in the nanopore. Taken together, our simulations suggest that strand sequencing of DNA by measuring the ionic current blockades in graphene nanopores may be possible, given that the conformation of DNA nucleotides in the nanopore can be controlled through precise engineering of the nanopore surface.

The cervical microbiome over 7 years and a comparison of methodologies for its characterization

BACKGROUND

The rapidly expanding field of microbiome studies offers investigators a large choice of methods for each step in the process of determining the microorganisms in a sample. The human cervicovaginal microbiome affects female reproductive health, susceptibility to and natural history of many sexually transmitted infections, including human papillomavirus (HPV). At present, long-term behavior of the cervical microbiome in early sexual life is poorly understood.

METHODS

The V6 and V6-V9 regions of the 16S ribosomal RNA gene were amplified from DNA isolated from exfoliated cervical cells. Specimens from 10 women participating in the Natural History Study of HPV in Guanacaste, Costa Rica were sampled successively over a period of 5-7 years. We sequenced amplicons using 3 different platforms (Sanger, Roche 454, and Illumina HiSeq 2000) and analyzed sequences using pipelines based on 3 different classification algorithms (usearch, RDP Classifier, and pplacer).

RESULTS

Usearch and pplacer provided consistent microbiome classifications for all sequencing methods, whereas RDP Classifier deviated significantly when characterizing Illumina reads. Comparing across sequencing platforms indicated 7%-41% of the reads were reclassified, while comparing across software pipelines reclassified up to 32% of the reads. Variability in classification was shown not to be due to a difference in read lengths. Six cervical microbiome community types were observed and are characterized by a predominance of either G. vaginalis or Lactobacillus spp. Over the 5-7 year period, subjects displayed fluctuation between community types. A PERMANOVA analysis on pairwise Kantorovich-Rubinstein distances between the microbiota of all samples yielded an F-test ratio of 2.86 (p<0.01), indicating a significant difference comparing within and between subjects' microbiota.

CONCLUSIONS

Amplification and sequencing methods affected the characterization of the microbiome more than classification algorithms. Pplacer and usearch performed consistently with all sequencing methods. The analyses identified 6 community types consistent with those previously reported. The long-term behavior of the cervical microbiome indicated that fluctuations were subject dependent.

AdapterRemoval: easy cleaning of next-generation sequencing reads

BACKGROUND

With the advent of next-generation sequencing there is an increased demand for tools to pre-process and handle the vast amounts of data generated. One recurring problem is adapter contamination in the reads, i.e. the partial or complete sequencing of adapter sequences. These adapter sequences have to be removed as they can hinder correct mapping of the reads and influence SNP calling and other downstream analyses.

FINDINGS

We present a tool called AdapterRemoval which is able to pre-process both single and paired-end data. The program locates and removes adapter residues from the reads, it is able to combine paired reads if they overlap, and it can optionally trim low-quality nucleotides. Furthermore, it can look for adapter sequence in both the 5' and 3' ends of the reads. This is a flexible tool that can be tuned to accommodate different experimental settings and sequencing platforms producing FASTQ files. AdapterRemoval is shown to be good at trimming adapters from both single-end and paired-end data.

CONCLUSIONS

AdapterRemoval is a comprehensive tool for analyzing next-generation sequencing data. It exhibits good performance both in terms of sensitivity and specificity. AdapterRemoval has already been used in various large projects and it is possible to extend it further to accommodate application-specific biases in the data.

Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak

BACKGROUND

Isolates of methicillin-resistant Staphylococcus aureus (MRSA) belonging to a single lineage are often indistinguishable by means of current typing techniques. Whole-genome sequencing may provide improved resolution to define transmission pathways and characterize outbreaks.

METHODS

We investigated a putative MRSA outbreak in a neonatal intensive care unit. By using rapid high-throughput sequencing technology with a clinically relevant turnaround time, we retrospectively sequenced the DNA from seven isolates associated with the outbreak and another seven MRSA isolates associated with carriage of MRSA or bacteremia in the same hospital.

RESULTS

We constructed a phylogenetic tree by comparing single-nucleotide polymorphisms (SNPs) in the core genome to a reference genome (an epidemic MRSA clone, EMRSA-15 [sequence type 22]). This revealed a distinct cluster of outbreak isolates and clear separation between these and the nonoutbreak isolates. A previously missed transmission event was detected between two patients with bacteremia who were not part of the outbreak. We created an artificial "resistome" of antibiotic-resistance genes and demonstrated concordance between it and the results of phenotypic susceptibility testing; we also created a "toxome" consisting of toxin genes. One outbreak isolate had a hypermutator phenotype with a higher number of SNPs than the other outbreak isolates, highlighting the difficulty of imposing a simple threshold for the number of SNPs between isolates to decide whether they are part of a recent transmission chain.

CONCLUSIONS

Whole-genome sequencing can provide clinically relevant data within a time frame that can influence patient care. The need for automated data interpretation and the provision of clinically meaningful reports represent hurdles to clinical implementation. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.).

Going beyond five bases in DNA sequencing

DNA sequencing has provided a wealth of information about biological systems, but thus far has focused on the four canonical bases, and 5-methylcytosine through comparison of the genomic DNA sequence to a transformed four-base sequence obtained after treatment with bisulfite. However, numerous other chemical modifications to the nucleotides are known to control fundamental life functions, influence virulence of pathogens, and are associated with many diseases. These modifications cannot be accessed with traditional sequencing methods. In this opinion, we highlight several emerging single-molecule sequencing techniques that have the potential to directly detect many types of DNA modifications as an integral part of the sequencing protocol.

Bacterial genomics in infectious disease and the clinical pathology laboratory

CONTEXT

Throughout history, technologic advancements have fueled the engine of innovation, which, in turn, has driven discovery. Accordingly, recent advancements in DNA sequencing technology are revolutionizing bacterial genomics.

OBJECTIVE

To review important developments from the literature. The current state of bacterial genomics, with an emphasis on human pathogens and the clinical pathology laboratory, will be discussed.

DATA SOURCES

A comprehensive review was performed of the relevant literature indexed in PubMed (National Library of Medicine) and referenced medical texts.

CONCLUSIONS

Many important discoveries bearing on infectious disease research and pathology laboratory practice have been achieved through whole-genome sequencing strategies. Bacterial genomics has improved our understanding of molecular pathogenesis, host-pathogen interactions, and antibiotic-resistance mechanisms. Bacterial genomics has also facilitated the study of population structures, epidemics and outbreaks, and newly identified pathogens. Many opportunities now exist for clinical pathologists to contribute to bacterial genomics, including in the design of new diagnostic tests, therapeutic agents, and vaccines.

Resolution limit for DNA barcodes in the Odijk regime

We develop an approximation for the probability of optically resolving two fluorescent labels on the backbone of a DNA molecule confined in a nanochannel in the Odijk regime as a function of the fluorescence wavelength, channel size, and the properties of the DNA (persistence length and effective width). The theoretical predictions agree well with equivalent data produced by Monte Carlo simulations of a touching wormlike bead model of DNA in a high ionic strength buffer. Although the theory is only strictly valid in the limit where the effective width of the nanochannel is small compared with the persistence length of the DNA, simulations indicate that the theoretical predictions are reasonably accurate for channel widths up to two-thirds of the persistence length. Our results quantify the conjecture that DNA barcoding has kilobase pair resolution-provided the nanochannel lies in the Odijk regime.

Nanosensors lost in space. A random walk study of single molecule detection with single-nanopore sensors

Nanopores by providing single molecule detection and manipulation are lately in the forefront of life science and nanotechnology research. While single nanopore sensors can detect the residence of even one molecule or nanoparticle within the nanopore, the analytical significance of this process is often misunderstood. A fundamental problem of nanosensors is that their sensing zone is generally infinitesimal with respect of the probed sample volume. Consequently, the probability to have in extremely diluted solutions target molecules or nanoparticles encountering the nanosensor is low. Thus, even though the sensor by itself has single molecule detection capability the average time frame in which this occurs is by far not irrelevant for the analysis. In this paper we report on random walk simulations to determine the average time (encounter time) needed by a single molecule to encounter a single nanopore sensor. By assigning the simulation environment with real space and time values a semi-empirical equation for expressing the average encounter time in purely diffusive systems is provided. We also show that random walk simulations can be adapted to evaluate the encounter time in the presence of an external force field acting on the target molecule. As practically relevant application the case of electrophoretically driving DNA strands towards the nanopore sensor is presented and a semi-empirical equation for the encounter time is provided.

Next generation sequencing: chemistry, technology and applications

High-throughput next generation sequencing (NGS) has been quickly adapted into many aspects of biomedical research and begun to engage with the clinical practice. The latter aspect will enable the application of genomic knowledge into clinical practice in this and next decades and will profoundly change the diagnosis, prognosis and treatment of many human diseases. It will further demand both philosophical and medical curriculum reforms in the training of our future physicians. However, significant huddles need to be overcome before an ultimate application of NGS in genomic medicine can be practical and fruitful.

Metagenomic approaches to the discovery of cellulases

Most of the microorganisms responsible for nutrient cycling in the environment have yet to be cultivated, and this could include those species responsible for the degradation of cellulose. Known cellulases are well defined at the protein sequence level, but gene variants are difficult to amplify from environmental DNA. The identification of novel cellulase genes independent of DNA amplification is made possible by adopting a direct metagenome sequencing approach to provide genes that can be cloned, expressed, and characterized prior to potential exploitation, all in the absence of any information on the species from which they originated. In this chapter, emerging strategies and methods that will enable the identification of novel cellulase genes and provide an unbiased perspective on gene expression in situ are presented.

Detection of pathogens in water: from phylochips to qPCR to pyrosequencing

Waterborne pathogens pose a significant threat to human health and a proper assessment of microbial water quality is important for decision making regarding water infrastructure and treatment investments and eventually to provide early warning of disease, particularly given increasing global disasters associated with severe public health risks. Microbial water quality monitoring has undergone tremendous transition in recent years, with novel molecular tools beginning to offer rapid, high-throughput, sensitive and specific detection of a wide spectrum of microbial pathogens that challenge traditional culture-based techniques. High-density microarrays, quantitative real-time PCR (qPCR) and pyrosequencing which are considered to be breakthrough technologies borne out of the ‘molecular revolution’ are at present emerging rapidly as tools of pathogen detection and discovery. Future challenges lie in integrating these molecular tools with concentration techniques and bioinformatics platforms for unbiased guide of pathogen surveillance in water and developing standardized protocols.

Next generation quantitative genetics in plants

Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.