The next-generation sequencing technology: a technology review and future perspective

A novel hierarchical network-based approach to unveil the complexity of functional microbial genome

Biological networks serve a crucial role in elucidating intricate biological processes. While interspecies environmental interactions have been extensively studied, the exploration of gene interactions within species, particularly among individual microorganisms, is less developed. The increasing amount of microbiome genomic data necessitates a more nuanced analysis of microbial genome structures and functions. In this context, we introduce a complex structure using higher-order network theory, "Solid Motif Structures (SMS)", via a hierarchical biological network analysis of genomes within the same genus, effectively linking microbial genome structure with its function. Leveraging 162 high-quality genomes of Microcystis, a key freshwater cyanobacterium within microbial ecosystems, we established a genome structure network. Employing deep learning techniques, such as adaptive graph encoder, we uncovered 27 critical functional subnetworks and their associated SMSs. Incorporating metagenomic data from seven geographically distinct lakes, we conducted an investigation into Microcystis' functional stability under varying environmental conditions, unveiling unique functional interaction models for each lake. Our work compiles these insights into an extensive resource repository, providing novel perspectives on the functional dynamics within Microcystis. This research offers a hierarchical network analysis framework for understanding interactions between microbial genome structures and functions within the same genus.

Recent Advances in Metagenomic Approaches, Applications, and Challenge

Advances in metagenomics analysis with the advent of next-generation sequencing have extended our knowledge of microbial communities as compared to conventional techniques providing advanced approach to identify novel and uncultivable microorganisms based on their genetic information derived from a particular environment. Shotgun metagenomics involves investigating the DNA of the entire community without the requirement of PCR amplification. It provides access to study all genes present in the sample. On the other hand, amplicon sequencing targets taxonomically important marker genes, the analysis of which is restricted to previously known DNA sequences. While sequence-based metagenomics is used to analyze DNA sequences directly from the environment without the requirement of library construction and with limited identification of novel genes and products that can be complemented by functional genomics, function-based metagenomics requires fragmentation and cloning of extracted metagenome DNA in a suitable host with subsequent functional screening and sequencing clone for detection of a novel gene. Although advances were made in metagenomics, different challenges arise. This review provides insight into advances in the metagenomic approaches combined with next-generation sequencing, their recent applications highlighting the emerging ones, such as in astrobiology, forensic sciences, and SARS-CoV-2 infection diagnosis, and the challenges associated. This review further discusses the different types of metagenomics and outlines advancements in bioinformatics tools and their significance in the analysis of metagenomic datasets.

Decoding the microbial universe with metagenomics: a brief insight

A major part of any biological system on earth involves microorganisms, of which the majority are yet to be cultured. The conventional methods of culturing microbes have given fruitful outcomes yet have limitations. The curiosity for better understanding has led to the development of culture-independent molecular methods that help push aside the roadblocks of earlier methods. Metagenomics unifies the scientific community in search of a better understanding of the functioning of the ecosystem and its component organisms. This approach has opened a new paradigm in advanced research. It has brought to light the vast diversity and novelty among microbial communities and their genomes. This review focuses on the development of this field over time, the techniques and analysis of data generated through sequencing platforms, and its prominent interpretation and representation.

A novel causative functional mutation in GATA6 gene is responsible for familial dilated cardiomyopathy as supported by in silico functional analysis

Dilated cardiomyopathy (DCM), one of the most common types of cardiomyopathies has a heterogeneous nature and can be seen in Mendelian forms. Next Generation Sequencing is a powerful tool for identifying novel variants in monogenic disorders. We used whole-exome sequencing (WES) and Sanger sequencing techniques to identify the causative mutation of DCM in an Iranian pedigree. We found a novel variant in the GATA6 gene, leading to substituting Histidine by Tyrosine at position 329, observed in all affected family members in the pedigree, whereas it was not established in any of the unaffected ones. We hypothesized that the H329Y mutation may be causative for the familial pattern of DCM in this family. The predicted models of GATA6 and H329Y showed the high quality according to PROCHECK and ERRAT. Nonetheless, simulation results revealed that the protein stability decreased after mutation, while the flexibility may have been increased. Hence, the mutation led to the increased compactness of GATA6. Overall, these data indicated that the mutation could affect the protein structure, which may be related to the functional impairment of GATA6 upon H329Y mutation, likewise their involvement in pathologies. Further functional investigations would help elucidating the exact mechanism.

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

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

Whole-genome sequence of multi-drug resistant Pseudomonas aeruginosa strains UY1PSABAL and UY1PSABAL2 isolated from human broncho-alveolar lavage, Yaoundé, Cameroon

Pseudomonas aeruginosa has been implicated in a wide range of post-operation wound and lung infections. A wide range of acquired resistance and virulence markers indicate surviving strategy of P. aeruginosa. Complete-genome analysis has been identified as efficient approach towards understanding the pathogenicity of this organism. This study was designed to sequence the entire genome of P. aeruginosa UY1PSABAL and UY1PSABAL2; determine drug-resistance profiles and virulence factors of the isolates; assess factors that contribute toward stability of the genomes; and thereafter determine evolutionary relationships between the strains and other isolates from similar sources. The genomes of the MDR P. aeruginosa UY1PSABAL and UY1PSABAL2 were sequenced on the Illumina Miseq platform. The raw sequenced reads were assessed for quality using FastQC v.0.11.5 and filtered for low quality reads and adapter regions using Trimmomatic v.0.36. The de novo genome assembly was made with SPAdes v.3.13 and annotated using Prokka v.2.1.1 annotation pipeline; Rapid Annotation using Subsytems Technology (RAST) server v.2.0; and PATRIC annotation tool v.3.6.2. Antimicrobial resistance genes and virulence determinants were searched through the functional annotation data generated from Prokka, RAST and PATRIC annotation pipelines; In addition to ResFinder and Comprehensive Antibiotic Resistance Database (CARD) which were employed to determine resistance genes. The PHAge Search Tool Enhanced Release (PHASTER) web server was used for the rapid identification and annotation of prophage sequences within bacterial genome. Predictive secondary metabolites were identified with AntiSMASH v.5.0. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and cas genes regions were also investigated with the CRISPRone and CRISPRFinder server. The genome sizes of 7.0 and 6.4 Mb were determined for UY1PSABAL and UY1PSABAL2 strains with G+C contents of 66.1% and 66.48% respectively. β-lactamines resistance genes blaPAO, aminoglycoside phosphorylating enzymes genes aph(3')-IIb, fosfomycine resistance gene fosA, vancomycin vanW and tetracycline tetA were among identified resistance genes harboured in both isolates. UY1PSABAL bore additional aph(6)-Id, aph(3'')-Ib, ciprofloxacin-modifying enzyme crpP and ribosomal methylation enzyme rmtB. Both isolates were found harbouring virulence markers such as flagella and type IV pili; and also present various type III secretion systems such as exoA, exoS, exoU, exoT. Secondary metabolites such as pyochelin and pyoverdine with iron uptake activity were found within the genomes as well as quorum-sensing systems, and various fragments for prophages and insertion sequences. Only the UY1PSABAL2 contains CRISPR-Cas system. The phylogeny revealed a very close evolutionary relationship between UY1PSABAL and the similar strain isolated from Malaysia; the same trend was observed between UY1PSABAL2 and the strain from Chinese origin. Complete analyses of the entire genomes provide a wide range of information towards understanding pathogenicity of the pathogens in question.

Identification and characterization of unconventional membrane protein trafficking regulators in Arabidopsis: A genetic approach

Proper trafficking and subcellular localization of membrane proteins are essential for plant growth and development. The plant endomembrane system contains several membrane-bound organelles with distinct functions including the endoplasmic reticulum (ER), Golgi apparatus, trans-Golgi network (TGN) or early endosome, prevacuolar compartment (PVC) or multivesicular body (MVB) and vacuole. Multiple approaches have been successfully used to identify and study the regulators and components important for signal transduction, growth and development, as well as membrane trafficking in the endomembrane system in plants. These include the homologous characterization of the counterparts in mammals or yeast employing both reverse genetic as well as the forward genetic screen approaches. However, the deletion or mutation of membrane trafficking related proteins usually leads to seedling lethality due to their essential roles in plant development and organelle biogenesis. To overcome the limitation of lethal phenotype of the target proteins, we used DEX-inducible RNAi knock-down lines to study their function in plants. More recently, we developed and used both RNAi knock-down and T-DNA insertional lines as starting materials to screen for mutations that could suppress and rescue the lethal phenotype, or a suppressor screening. Further characterization of the newly identified suppressor mutants has resulted in the identification of novel negative regulators in mediating membrane trafficking and organelle biogenesis in plants. In this review, we summarize the current approaches in studying protein trafficking in the endomembrane system. We then describe three examples of suppressor screening with distinct starting materials (i.e. FREE1, MON1, and SH3P2 that are regulators of MVB, vacuole, and autophagosomes, respectively) to discuss the rationale, procedures, advantages and disadvantages, and possible outcomes of such a suppressor screening. We finally propose that these novel screening approaches will lead to the identification of new unconventional players in regulating protein trafficking and organelle biogenesis in plants and discuss their impact on plant cell biology research.

Effect of vitamin D3 on the immunomodulation of head kidney after Edwardsiella ictaluri challenge in yellow catfish (Pelteobagrus fulvidraco)

Edwardsiella ictaluri (E. ictaluri) causes severe infections in yellow catfish (Pelteobagrus fulvidraco), which leads to a massive loss in the aquaculture industry especially in catfish commercial production. Previous studies have confirmed that vitamin D₃ is essential in immune regulation in mammals. Based on next-generation sequencing, this study explored the immunomodulatory effects of dietary vitamin D₃ on the head kidney of yellow catfish after E. ictaluri challenge. Current results showed that increasing the content of dietary vitamin D₃ within the experimental concentration range (1120IU/kg-16600IU/kg) could reduce the mortality of the yellow catfish after E. ictaluri challenge. Results of the next-generation sequencing showed that dietary vitamin D₃ regulates the immune mechanism of the head kidney mainly through three pathways i.e. negative regulation of interferon-β production, negative regulation of interleukin-6 production and neutrophil chemotaxis. Proteins HSPA8, MAP4K4 and MRC1 may be involved in vitamin D₃-mediated immunoregulation in the head kidney. qPCR results showed that increasing the content of dietary vitamin D₃ can improve the immune function of the yellow catfish by down-regulating ifn-β and pro-inflammatory factors tnf-α, il1-β, il-6, il-8 and up-regulating the anti-inflammatory factor il-10. The above results indicated that dietary addition of vitamin D₃ regulated the immune response in head kidney of yellow catfish and helped the fish to resist the negative effects of infection by E. ictaluri in a dose-dependent manner.

A novel variant in LPL gene is associated with familial combined hyperlipidemia

Familial combined hyperlipidemia (FCHL) is a common genetic disorder characterized by increased fasted serum cholesterol, triglycerides, and apolipoprotein B-100. Molecular genetic techniques such as next generation sequencing have been very successful methods for rare variants finding with a moderate-to large effect. In this study, we characterized a large pedigree from MASHAD study in northeast Iran with coinheritance of FCHL and early-onset coronary heart disease. In this family, we used whole-exome sequencing and Sanger sequencing to determine the disease-associated gene. We identified a novel variant in the LPL gene, leading to a substitution of an asparagine for aspartic acid at position 151. The D151N substitution cosegregated with these characters in all affected family members in the pedigree but it was absent in all unaffected members in this family. We speculated that the mutation D151N in LPL gene might be associated with FCHL and early-onset coronary heart disease in this family. However, the substantial mechanism requires further investigation.

Signature of Gut Microbiome by Conventional and Advanced Analysis Techniques: Advantages and Disadvantages

Gut microbiota is considered as a human organ with its own specific functions and complexity. Development of novel techniques such as shut gun sequencing, metagenomics, and next-generation sequencing (NGS) has enabled bypassing the traditional culturedependent bias and has significantly expanded our understanding of the composition, diversity, and roles of the gut microbiota in human health and diseases. Although amplicon sequencing characterizes the taxonomic composition of the gut microbiome, it is impossible to cover the direct evidence of the microbial biological functions related to the gut microbial community. Hence, the critical next step for gut microbiome studies is shifting from gene/ genome-centric analysis to mechanism-centric techniques by integrating omics data with experimental results. Realizing gut microbial diversity and their bioactive metabolites function will provide insight into the clinical application of gut microbiota in diagnoses and treatments of several diseases. In this review, we focused on explaining the conventional and advanced microbiome analysis techniques regarding gut microbiota investigation with considering the advantages and disadvantages of the platforms.

Associations between sleep bruxism and (peri-) implant complications: a prospective cohort study

Objectives/Aims:

To describe the protocol of a prospective cohort study designed to answer the question: ‘Is sleep bruxism a risk factor for (peri-)implant complications?’.

Materials and Methods:

Our study is a single-centre, double-blind, prospective cohort study with a follow-up time of 2 years. Ninety-eight participants fulfilling inclusion criteria (planned treatment with implant-supported fixed suprastructure(s) and age 18 years or older) will be included. Sleep bruxism will be monitored at several time points as masticatory muscle activity during sleep by means of a portable single-channel electromyographic device. Our main outcomes are biological complications (i.e., related to peri-implant bleeding, probing depth, marginal bone height, quality of submucosal biofilm and loss of osseointegration) and technical complications (i.e., suprastructure, abutment, implant body or other).

Results:

The study is currently ongoing, and data are being gathered.

Discussion:

The results of this prospective cohort study will provide important information for clinicians treating bruxing patients with dental implants. Furthermore, it will contribute to the body of evidence related to the behaviour of dental implants and their complications under conditions of high mechanical loadings that result from sleep bruxism activity.

Conclusion:

The protocol of a prospective cohort study designed to investigate possible associations between sleep bruxism and (peri-) implant complications was presented.

A real-time decoding sequencing technology—new possibility for high throughput sequencing

The challenges and corresponding solutions for a decoding sequencing to be compatible with high throughput sequencing (HTS) technologies are provided.

Jellyfish Bioactive Compounds: Methods for Wet-Lab Work

The study of bioactive compounds from marine animals has provided, over time, an endless source of interesting molecules. Jellyfish are commonly targets of study due to their toxic proteins. However, there is a gap in reviewing successful wet-lab methods employed in these animals, which compromises the fast progress in the detection of related biomolecules. Here, we provide a compilation of the most effective wet-lab methodologies for jellyfish venom extraction prior to proteomic analysis-separation, identification and toxicity assays. This includes SDS-PAGE, 2DE, gel chromatography, HPLC, DEAE, LC-MS, MALDI, Western blot, hemolytic assay, antimicrobial assay and protease activity assay. For a more comprehensive approach, jellyfish toxicity studies should further consider transcriptome sequencing. We reviewed such methodologies and other genomic techniques used prior to the deep sequencing of transcripts, including RNA extraction, construction of cDNA libraries and RACE. Overall, we provide an overview of the most promising methods and their successful implementation for optimizing time and effort when studying jellyfish.

Application of high-throughput sequencing in understanding human oral microbiome related with health and disease

The oral microbiome is one of most diversity habitat in the human body and they are closely related with oral health and disease. As the technique developing, high-throughput sequencing has become a popular approach applied for oral microbial analysis. Oral bacterial profiles have been studied to explore the relationship between microbial diversity and oral diseases such as caries and periodontal disease. This review describes the application of high-throughput sequencing for characterization of oral microbiota and analyzing the changes of the microbiome in the states of health or disease. Deep understanding the knowledge of microbiota will pave the way for more effective prevent dentistry and contribute to the development of personalized dental medicine.

Metatranscriptome analysis of fungal strains Penicillium camemberti and Geotrichum candidum reveal cheese matrix breakdown and potential development of sensory properties of ripened Camembert-type cheese

BACKGROUND

Camembert-type cheese ripening is driven mainly by fungal microflora including Geotrichum candidum and Penicillium camemberti. These species are major contributors to the texture and flavour of typical bloomy rind cheeses. Biochemical studies showed that G. candidum reduces bitterness, enhances sulphur flavors through amino acid catabolism and has an impact on rind texture, firmness and thickness, while P. camemberti is responsible for the white and bloomy aspect of the rind, and produces enzymes involved in proteolysis and lipolysis activities. However, very little is known about the genetic determinants that code for these activities and their expression profile over time during the ripening process.

RESULTS

The metatranscriptome of an industrial Canadian Camembert-type cheese was studied at seven different sampling days over 77 days of ripening. A database called CamemBank01 was generated, containing a total of 1,060,019 sequence tags (reads) assembled in 7916 contigs. Sequence analysis revealed that 57% of the contigs could be affiliated to molds, 16% originated from yeasts, and 27% could not be identified. According to the functional annotation performed, the predominant processes during Camembert ripening include gene expression, energy-, carbohydrate-, organic acid-, lipid- and protein- metabolic processes, cell growth, and response to different stresses. Relative expression data showed that these functions occurred mostly in the first two weeks of the ripening period.

CONCLUSIONS

These data provide further advances in our knowledge about the biological activities of the dominant ripening microflora of Camembert cheese and will help select biological markers to improve cheese quality assessment.

Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis

BACKGROUND

Schizophrenia (SCZ) and type 2 diabetes mellitus (T2D) are both complex diseases. Accumulated studies indicate that schizophrenia patients are prone to present the type 2 diabetes symptoms, but the potential mechanisms behind their association remain unknown. Here we explored the pathogenetic association between SCZ and T2D based on pathway analysis and protein-protein interaction.

RESULTS

With sets of prioritized susceptibility genes for SCZ and T2D, we identified significant pathways (with adjusted p-value < 0.05) specific for SCZ or T2D and for both diseases based on pathway enrichment analysis. We also constructed a network to explore the crosstalk among those significant pathways. Our results revealed that some pathways are shared by both SCZ and T2D diseases through a number of susceptibility genes. With 382 unique susceptibility proteins for SCZ and T2D, we further built a protein-protein interaction network by extracting their nearest interacting neighbours. Among 2,104 retrieved proteins, 364 of them were found simultaneously interacted with susceptibility proteins of both SCZ and T2D, and proposed as new candidate risk factors for both diseases. Literature mining supported the potential association of partial new candidate proteins with both SCZ and T2D. Moreover, some proteins were hub proteins with high connectivity and interacted with multiple proteins involved in both diseases, implying their pleiotropic effects for the pathogenic association. Some of these hub proteins are the components of our identified enriched pathways, including calcium signaling, g-secretase mediated ErbB4 signaling, adipocytokine signaling, insulin signaling, AKT signaling and type II diabetes mellitus pathways. Through the integration of multiple lines of information, we proposed that those signaling pathways, which contain susceptibility genes for both diseases, could be the key pathways to bridge SCZ and T2D. AKT could be one of the important shared components and may play a pivotal role to link both of the pathogenetic processes.

CONCLUSIONS

Our study is the first network and pathway-based systematic analysis for SCZ and T2D, and provides the general pathway-based view of pathogenetic association between two diseases. Moreover, we identified a set of candidate genes potentially contributing to the linkage between these two diseases. This research offers new insights into the potential mechanisms underlying the co-occurrence of SCZ and T2D, and thus, could facilitate the inference of novel hypotheses for the co-morbidity of the two diseases. Some etiological factors that exert pleiotropic effects shared by the significant pathways of two diseases may have important implications for the diseases and could be therapeutic intervention targets.

The history and advances of reversible terminators used in new generations of sequencing technology

DNA sequencing using reversible terminators, as one sequencing by synthesis strategy, has garnered a great deal of interest due to its popular application in the second-generation high-throughput DNA sequencing technology. In this review, we provided its history of development, classification, and working mechanism of this technology. We also outlined the screening strategies for DNA polymerases to accommodate the reversible terminators as substrates during polymerization; particularly, we introduced the "REAP" method developed by us. At the end of this review, we discussed current limitations of this approach and provided potential solutions to extend its application.

Next-generation sequencing to assess HIV tropism

PURPOSE OF REVIEW

Deep sequencing of the V3 region of the HIV envelope gene can detect minority non-R5 variants in patients with high sensitivity and specificity. As next-generation sequencing approaches have matured, the clinical utility of deep sequencing for HIV tropism has entered the clinic. Accurate and sensitive tropism testing is essential for successful treatment with the CCR5 antagonist class of antiretrovirals.

RECENT FINDINGS

This review will focus on five aspects of next-generation sequencing for assessing HIV tropism: some background on the necessity of deep sequencing versus other tropism methods; the methodological process of 454 sequencing and analysis; other next-generation sequencing technologies; the diagnostic performance of deep sequencing relative to other tropism assays; and the use of deep sequencing in clinical practice.

SUMMARY

This method has emerged quickly as both a research and clinical tool because of its high concordance with commonly used phenotypic tropism assays and its ability to predict virological response to CCR5 antagonist-containing regimens.

Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics

The Human Genome Project (HGP) provided the initial draft of mankind's DNA sequence in 2001. The HGP was produced by 23 collaborating laboratories using Sanger sequencing of mapped regions as well as shotgun sequencing techniques in a process that occupied 13 years at a cost of ~$3 billion. Today, Next Generation Sequencing (NGS) techniques represent the next phase in the evolution of DNA sequencing technology at dramatically reduced cost compared to traditional Sanger sequencing. A single laboratory today can sequence the entire human genome in a few days for a few thousand dollars in reagents and staff time. Routine whole exome or even whole genome sequencing of clinical patients is well within the realm of affordability for many academic institutions across the country. This paper reviews current sequencing technology methods and upcoming advancements in sequencing technology as well as challenges associated with data generation, data manipulation and data storage. Implementation of routine NGS data in cancer genomics is discussed along with potential pitfalls in the interpretation of the NGS data. The overarching importance of bioinformatics in the clinical implementation of NGS is emphasized.[7] We also review the issue of physician education which also is an important consideration for the successful implementation of NGS in the clinical workplace. NGS technologies represent a golden opportunity for the next generation of pathologists to be at the leading edge of the personalized medicine approaches coming our way. Often under-emphasized issues of data access and control as well as potential ethical implications of whole genome NGS sequencing are also discussed. Despite some challenges, it's hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease in the near future.

Metagenomic analysis: the challenge of the data bonanza

Several thousand metagenomes have already been sequenced, and this number is set to grow rapidly in the forthcoming years as the uptake of high-throughput sequencing technologies continues. Hand-in-hand with this data bonanza comes the computationally overwhelming task of analysis. Herein, we describe some of the bioinformatic approaches currently used by metagenomics researchers to analyze their data, the issues they face and the steps that could be taken to help overcome these challenges.

De novo transcriptome assembly of RNA-Seq reads with different strategies

De novo transcriptome assembly is an important approach in RNA-Seq data analysis and it can help us to reconstruct the transcriptome and investigate gene expression profiles without reference genome sequences. We carried out transcriptome assemblies with two RNA-Seq datasets generated from human brain and cell line, respectively. We then determined an efficient way to yield an optimal overall assembly using three different strategies. We first assembled brain and cell line transcriptome using a single k-mer length. Next we tested a range of values of k-mer length and coverage cutoff in assembling. Lastly, we combined the assembled contigs from a range of k values to generate a final assembly. By comparing these assembly results, we found that using only one k-mer value for assembly is not enough to generate good assembly results, but combining the contigs from different k-mer values could yield longer contigs and greatly improve the overall assembly.

A pangenomic study of Bacillus thuringiensis

Bacillus thuringiensis (B. thuringiensis) is a soil-dwelling Gram-positive bacterium and its plasmid-encoded toxins (Cry) are commonly used as biological alternatives to pesticides. In a pangenomic study, we sequenced seven B. thuringiensis isolates in both high coverage and base-quality using the next-generation sequencing platform. The B. thuringiensis pangenome was extrapolated to have 4196 core genes and an asymptotic value of 558 unique genes when a new genome is added. Compared to the pangenomes of its closely related species of the same genus, B. thuringiensis pangenome shows an open characteristic, similar to B. cereus but not to B. anthracis; the latter has a closed pangenome. We also found extensive divergence among the seven B. thuringiensis genome assemblies, which harbor ample repeats and single nucleotide polymorphisms (SNPs). The identities among orthologous genes are greater than 84.5% and the hotspots for the genome variations were discovered in genomic regions of 2.3-2.8Mb and 5.0-5.6Mb. We concluded that high-coverage sequence assemblies from multiple strains, before all the gaps are closed, are very useful for pangenomic studies.

Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

BACKGROUND

The rapid evolution of 454 GS-FLX sequencing technology has not been accompanied by a reassessment of the quality and accuracy of the sequences obtained. Current strategies for decision-making and error-correction are based on an initial analysis by Huse et al. in 2007, for the older GS20 system based on experimental sequences. We analyze here the quality of 454 sequencing data and identify factors playing a role in sequencing error, through the use of an extensive dataset for Roche control DNA fragments.

RESULTS

We obtained a mean error rate for 454 sequences of 1.07%. More importantly, the error rate is not randomly distributed; it occasionally rose to more than 50% in certain positions, and its distribution was linked to several experimental variables. The main factors related to error are the presence of homopolymers, position in the sequence, size of the sequence and spatial localization in PT plates for insertion and deletion errors. These factors can be described by considering seven variables. No single variable can account for the error rate distribution, but most of the variation is explained by the combination of all seven variables.

CONCLUSIONS

The pattern identified here calls for the use of internal controls and error-correcting base callers, to correct for errors, when available (e.g. when sequencing amplicons). For shotgun libraries, the use of both sequencing primers and deep coverage, combined with the use of random sequencing primer sites should partly compensate for even high error rates, although it may prove more difficult than previous thought to distinguish between low-frequency alleles and errors.

Transcriptome analysis

Transcriptome analysis technologies are important systems-biology methods for the investigation and optimization of mammalian cell cultures concerning with regard to growth rates and productivity. For the production of recombinant proteins, knowledge of the expression conditions of the influencing genes is a major issue in the improvement of cell lines by means of genome engineering. This chapter presents two main techniques for transcriptome analysis: microarray technology and next-generation sequencing. Protein-based methods are also briefly outlined. Furthermore, the impact of these technologies on mammalian cell culture improvement is discussed.

The next-generation sequencing technology and application

As one of the key technologies in biomedical research, DNA sequencing has not only improved its productivity with an exponential growth rate but also been applied to new areas of application over the past few years. This is largely due to the advent of newer generations of sequencing platforms, offering ever-faster and cheaper ways to analyze sequences. In our previous review, we looked into technical characteristics of the next-generation sequencers and provided prospective insights into their future development. In this article, we present a brief overview of the advantages and shortcomings of key commercially available platforms with a focus on their suitability for a broad range of applications.