Sequencing effort dictates gene discovery in marine microbial metagenomes

Massive metagenomic sequencing combined with gene prediction methods were previously used to compile the gene catalogue of the ocean and host-associated microbes. Global expeditions conducted over the past 15 years have sampled the ocean to build a catalogue of genes from pelagic microbes. Here we undertook a large sequencing effort of a perturbed Red Sea plankton community to uncover that the rate of gene discovery increases continuously with sequencing effort, with no indication that the retrieved 2.83 million non-redundant (complete) genes predicted from the experiment represented a nearly complete inventory of the genes present in the sampled community (i.e., no evidence of saturation). The underlying reason is the Pareto-like distribution of the abundance of genes in the plankton community, resulting in a very long tail of millions of genes present at remarkably low abundances, which can only be retrieved through massive sequencing. Microbial metagenomic projects retrieve a variable number of unique genes per Tera base-pair (Tbp), with a median value of 14.7 million unique genes per Tbp sequenced across projects. The increase in the rate of gene discovery in microbial metagenomes with sequencing effort implies that there is ample room for new gene discovery in further ocean and holobiont sequencing studies.     

Mating flight causes genome-wide transcriptional changes in sexually mature honeybee queens

In this study, we analyzed the gene and miRNA expression differences between the courted virgin queen (CVQ) and non-courted virgin queen (NCVQ) of Apis mellifera using a high-throughput sequencing method. Through Digital Gene Expression (DGE) sequencing, 452 genes were differentially expressed, out of which, 90 genes were up-regulated and 362 genes were down-regulated in CVQ compared with NCVQ. Through small RNA sequencing, 27 miRNAs showed significant expression difference between these two samples. Moreover, 9 of the differentially expressed genes are the targets of the 11 differentially expressed miRNAs. Besides, 47 novel miRNA candidates were predicted in these two samples. Our results provided valuable information for understanding the molecular mechanism of the transition to functional queens.     

Model-based identification of conditionally-essential genes from transposon-insertion sequencing data

The understanding of bacterial gene function has been greatly enhanced by recent advancements in the deep sequencing of microbial genomes. Transposon insertion sequencing methods combines next-generation sequencing techniques with transposon mutagenesis for the exploration of the essentiality of genes under different environmental conditions. We propose a model-based method that uses regularized negative binomial regression to estimate the change in transposon insertions attributable to gene-environment changes in this genetic interaction study without transformations or uniform normalization. An empirical Bayes model for estimating the local false discovery rate combines unique and total count information to test for genes that show a statistically significant change in transposon counts. When applied to RB-TnSeq (randomized barcode transposon sequencing) and Tn-seq (transposon sequencing) libraries made in strains of Caulobacter crescentus using both total and unique count data the model was able to identify a set of conditionally beneficial or conditionally detrimental genes for each target condition that shed light on their functions and roles during various stress conditions.     

降解组测序技术在植物miRNA研究中的应用

目前, 利用芯片技术和miRNA测序可快速、准确地检测到物种中所含有的miRNA。随着越来越多的miRNA被发现, miRNA靶基因的确定已成为研究miRNA生物学功能的关键。传统的miRNA靶基因的寻找主要依赖生物信息学预测、AGO蛋白免疫共沉淀和荧光素酶法等。随着高通量测序技术的持续革新, 出现了一种新的miRNA靶基因的检测方法, 即降解组测序(degradome sequencing)法, 该方法拥有高通量测序技术、生物信息学分析和RACE验证三者的优势, 并已成功应用于拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)和小立碗藓(Physcomitrella patens)等模式植物miRNA靶基因的检测。基于已发表的相关文献和联川生物降解组测序平台, 该文对降解组测序技术应用于植物miRNA靶基因的研究进展及其实验原理进行了综述, 同时对运用该技术可进行的更深入研究进行了讨论。     

Design considerations for massively parallel sequencing studies of complex human disease

Massively Parallel Sequencing (MPS) allows sequencing of entire exomes and genomes to now be done at reasonable cost, and its utility for identifying genes responsible for rare Mendelian disorders has been demonstrated. However, for a complex disease, study designs need to accommodate substantial degrees of locus, allelic, and phenotypic heterogeneity, as well as complex relationships between genotype and phenotype. Such considerations include careful selection of samples for sequencing and a well-developed strategy for identifying the few "true" disease susceptibility genes from among the many irrelevant genes that will be found to harbor rare variants. To examine these issues we have performed simulation-based analyses in order to compare several strategies for MPS sequencing in complex disease. Factors examined include genetic architecture, sample size, number and relationship of individuals selected for sequencing, and a variety of filters based on variant type, multiple observations of genes and concordance of genetic variants within pedigrees. A two-stage design was assumed where genes from the MPS analysis of high-risk families are evaluated in a secondary screening phase of a larger set of probands with more modest family histories. Designs were evaluated using a cost function that assumes the cost of sequencing the whole exome is 400 times that of sequencing a single candidate gene. Results indicate that while requiring variants to be identified in multiple pedigrees and/or in multiple individuals in the same pedigree are effective strategies for reducing false positives, there is a danger of over-filtering so that most true susceptibility genes are missed. In most cases, sequencing more than two individuals per pedigree results in reduced power without any benefit in terms of reduced overall cost. Further, our results suggest that although no single strategy is optimal, simulations can provide important guidelines for study design.     

Molecular diagnosis of usher syndrome: application of two different next generation sequencing-based procedures

Usher syndrome (USH) is a clinically and genetically heterogeneous disorder characterized by visual and hearing impairments. Clinically, it is subdivided into three subclasses with nine genes identified so far. In the present study, we investigated whether the currently available Next Generation Sequencing (NGS) technologies are already suitable for molecular diagnostics of USH. We analyzed a total of 12 patients, most of which were negative for previously described mutations in known USH genes upon primer extension-based microarray genotyping. We enriched the NGS template either by whole exome capture or by Long-PCR of the known USH genes. The main NGS sequencing platforms were used: SOLiD for whole exome sequencing, Illumina (Genome Analyzer II) and Roche 454 (GS FLX) for the Long-PCR sequencing. Long-PCR targeting was more efficient with up to 94% of USH gene regions displaying an overall coverage higher than 25×, whereas whole exome sequencing yielded a similar coverage for only 50% of those regions. Overall this integrated analysis led to the identification of 11 novel sequence variations in USH genes (2 homozygous and 9 heterozygous) out of 18 detected. However, at least two cases were not genetically solved. Our result highlights the current limitations in the diagnostic use of NGS for USH patients. The limit for whole exome sequencing is linked to the need of a strong coverage and to the correct interpretation of sequence variations with a non obvious, pathogenic role, whereas the targeted approach suffers from the high genetic heterogeneity of USH that may be also caused by the presence of additional causative genes yet to be identified.     

Direct sequencing of PCR products for mutation detection in osteogenesis imperfecta

This work present a short and simple method for mutation detection in type I collagen genes, based on the direct sequencing of single-stranded DNA. The sequencing of type I collagen genes is complicated and difficult because of their large size and highly repetitive and GC-rich coding regions. Although many techniques have been developed for mutation screening in osteogenesis imperfecta (OI), they represent different degrees of sensitivity and are difficult to reproduce and too expensive for application in each laboratory. The method described here is short, easy and especially useful for sequencing of collagen genes in OI cases, in which the region with a suspected structural defect is localized by collagen analysis.     

FragGeneScan: predicting genes in short and error-prone reads

The advances of next-generation sequencing technology have facilitated metagenomics research that attempts to determine directly the whole collection of genetic material within an environmental sample (i.e. the metagenome). Identification of genes directly from short reads has become an important yet challenging problem in annotating metagenomes, since the assembly of metagenomes is often not available. Gene predictors developed for whole genomes (e.g. Glimmer) and recently developed for metagenomic sequences (e.g. MetaGene) show a significant decrease in performance as the sequencing error rates increase, or as reads get shorter. We have developed a novel gene prediction method FragGeneScan, which combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads. The performance of FragGeneScan was comparable to Glimmer and MetaGene for complete genomes. But for short reads, FragGeneScan consistently outperformed MetaGene (accuracy improved ∼62% for reads of 400 bases with 1% sequencing errors, and ∼18% for short reads of 100 bases that are error free). When applied to metagenomes, FragGeneScan recovered substantially more genes than MetaGene predicted (>90% of the genes identified by homology search), and many novel genes with no homologs in current protein sequence database.     

In-solution hybrid capture of bisulfite-converted DNA for targeted bisulfite sequencing of 174 ADME genes

DNA methylation is one of the most important epigenetic alterations involved in the control of gene expression. Bisulfite sequencing of genomic DNA is currently the only method to study DNA methylation patterns at single-nucleotide resolution. Hence, next-generation sequencing of bisulfite-converted DNA is the method of choice to investigate DNA methylation profiles at the genome-wide scale. Nevertheless, whole genome sequencing for analysis of human methylomes is expensive, and a method for targeted gene analysis would provide a good alternative in many cases where the primary interest is restricted to a set of genes.Here, we report the successful use of a custom Agilent SureSelect Target Enrichment system for the hybrid capture of bisulfite-converted DNA. We prepared bisulfite-converted next-generation sequencing libraries, which are enriched for the coding and regulatory regions of 174 ADME genes (i.e. genes involved in the metabolism and distribution of drugs). Sequencing of these libraries on Illumina’s HiSeq2000 revealed that the method allows a reliable quantification of methylation levels of CpG sites in the selected genes, and validation of the method using pyrosequencing and the Illumina 450K methylation BeadChips revealed good concordance.     

Exomdiagnostik ver?ndert die Sicht auf Mitochondriopathien

With molecular-genetic diagnostics of large sets of genes (gene panels, exome sequencing) becoming less expensive, it is expected that they will be increasingly used in clinical practice. This will especially affect those monogenic diseases which are heterogenic, that is, in which mutations of many different genes result in phenotypes that are clinically difficult to distinguish from each other. Respiratory chain defects are an example of such disorders. Exome sequencing allows for rapid, simultaneous screening of all genes that come into question.     

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing(NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters(XMETs). The genetic variants in XMET genes are critical to predicate interindividual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.     

New mutations in chronic lymphocytic leukemia identified by target enrichment and deep sequencing

Chronic lymphocytic leukemia (CLL) is a heterogeneous disease without a well-defined genetic alteration responsible for the onset of the disease. Several lines of evidence coincide in identifying stimulatory and growth signals delivered by B-cell receptor (BCR), and co-receptors together with NFkB pathway, as being the driving force in B-cell survival in CLL. However, the molecular mechanism responsible for this activation has not been identified. Based on the hypothesis that BCR activation may depend on somatic mutations of the BCR and related pathways we have performed a complete mutational screening of 301 selected genes associated with BCR signaling and related pathways using massive parallel sequencing technology in 10 CLL cases. Four mutated genes in coding regions (KRAS, SMARCA2, NFKBIE and PRKD3) have been confirmed by capillary sequencing. In conclusion, this study identifies new genes mutated in CLL, all of them in cases with progressive disease, and demonstrates that next-generation sequencing technologies applied to selected genes or pathways of interest are powerful tools for identifying novel mutational changes.     

Comprehensive Mutation Analysis for Congenital Muscular Dystrophy: A Clinical PCR-Based Enrichment and Next-Generation Sequencing Panel

The congenital muscular dystrophies (CMDs) comprise a heterogeneous group of heritable muscle disorders with often difficult to interpret muscle pathology, making them challenging to diagnose. Serial Sanger sequencing of suspected CMD genes, while the current molecular diagnostic method of choice, can be slow and expensive. A comprehensive panel test for simultaneous screening of mutations in all known CMD-associated genes would be a more effective diagnostic strategy. Thus, the CMDs are a model disorder group for development and validation of next-generation sequencing (NGS) strategies for diagnostic and clinical care applications. Using a highly multiplexed PCR-based target enrichment method (RainDance) in conjunction with NGS, we performed mutation detection in all CMD genes of 26 samples and compared the results with Sanger sequencing. The RainDance NGS panel showed great consistency in coverage depth, on-target efficiency, versatility of mutation detection, and genotype concordance with Sanger sequencing, demonstrating the test''s appropriateness for clinical use. Compared to single tests, a higher diagnostic yield was observed by panel implementation. The panel''s limitation is the amplification failure of select gene-specific exons which require Sanger sequencing for test completion. Successful validation and application of the CMD NGS panel to improve the diagnostic yield in a clinical laboratory was shown.     

Sequencing cucumber (Cucumis sativus L.) chloroplast genomes identifies differences between chilling-tolerant and -susceptible cucumber lines.

Chilling injury in cucumber (Cucumis sativus L.) is conditioned by maternal factors, and the sequencing of its chloroplast genome could lead to the identification of economically important candidate genes. Complete sequencing of cucumber chloroplast (cp)DNA was facilitated by the development of 414 consensus chloroplast sequencing primers (CCSPs) from conserved cpDNA sequences of Arabidopsis (Arabidopsis thaliana L.), spinach (Spinacia oleracea L.), and tobacco (Nicotiana tabacum L.) cpDNAs, using degenerative primer technologies. Genomic sequence analysis led to the construction of 301 CCSPs and 72 cucumber chloroplast-specific sequencing primers (CSSPs), which were used for the complete sequencing of cpDNA of Gy14 (155 525 bp) and 'Chipper' (155 524 bp) cucumber lines, which are, respectively, susceptible and tolerant to chilling injury (4 degrees C for 5.5 h) in the first leaf stage. Comparative cpDNA sequence analyses revealed that 1 sequence span (located between genes trnK and rps16) and 2 nucleotides (located in genes atpB and ycf1) differed between chilling-susceptible and -tolerant lines. These sequence differences correspond to previously reported maternally inherited differences in chilling response between reciprocal F1 progeny derived from these lines. Sequence differences at these 3 cpDNA sites were also detected in a genetically diverse array of cucumber germplasm with different chilling responses. These and previously reported results suggest that 1 or several of these sequences could be responsible for the observed response to chilling injury in cucumber. The comprehensive sequencing of cpDNA of cucumber by CCSPs and CSSPs indicates that these primers have immediate applications in the analysis of cpDNAs from other dicotyledonous species and the investigation of evolutionary relationships.     

Exome Analysis of Two Limb-Girdle Muscular Dystrophy Families: Mutations Identified and Challenges Encountered

The molecular diagnosis of muscle disorders is challenging: genetic heterogeneity (>100 causal genes for skeletal and cardiac muscle disease) precludes exhaustive clinical testing, prioritizing sequencing of specific genes is difficult due to the similarity of clinical presentation, and the number of variants returned through exome sequencing can make the identification of the disease-causing variant difficult. We have filtered variants found through exome sequencing by prioritizing variants in genes known to be involved in muscle disease while examining the quality and depth of coverage of those genes. We ascertained two families with autosomal dominant limb-girdle muscular dystrophy of unknown etiology. To identify the causal mutations in these families, we performed exome sequencing on five affected individuals using the Agilent SureSelect Human All Exon 50 Mb kit and the Illumina HiSeq 2000 (2×100 bp). We identified causative mutations in desmin (IVS3+3A>G) and filamin C (p.W2710X), and augmented the phenotype data for individuals with muscular dystrophy due to these mutations. We also discuss challenges encountered due to depth of coverage variability at specific sites and the annotation of a functionally proven splice site variant as an intronic variant.