高通量测序技术在遗传性耳聋研究中的应用及研究进展

耳聋是一种常见的严重出生缺陷,阐明遗传性耳聋的致病机理不仅能够在临床上辅助诊断,为遗传咨询及耳聋预防提供依据,而且能促进人们更深入地了解耳聋的致病机制,开发新的治疗方法。随着基因组研究技术不断创新,以全基因组测序、全外显子组测序、目标区域测序为代表的高通量测序技术在遗传性耳聋研究中已得到广泛应用。本文总结了近5年全外显子组测序和目标区域测序在遗传性耳聋致病基因研究及临床分子诊断中应用及研究进展,希望能够有助于我国临床耳聋基因诊断技术的发展及诊断水平的提升。     

Next-generation sequencing as a tool to quickly identify causative EMS-generated mutations

The advent of next generation sequencing has influenced every aspect of biological research. Many labs are now using whole genome sequencing in Arabidopsis thaliana as a means to quickly identify EMS-generated mutations present in isolated mutants. Following identification of these mutations, examination of T-DNA insertional alleles defective in candidate genes or complementation of the mutant phenotype with a wild type copy of candidate genes can be used to verify which mutation is causative for the phenotype of interest. Here, we discuss the benefits and pitfalls of using this method to identify mutations underlying phenotypes.     

新一代测序技术在遗传性耳聋基因研究及诊断中的应用

超过50%的耳聋由遗传基因缺陷所致,伴随着基因组学技术的发展,耳聋分子遗传学研究逐渐成为耳科学研究的前沿领域。新一代高通量测序技术的出现,提供了以数据为导向的新的遗传性疾病研究模式,革新了人们对遗传性疾病的认识过程,使得对遗传性疾病的研究策略也发生了重大转变。近年来新一代测序技术(Next generation sequencing,NGS)在耳聋研究中的应用,大大加快了耳聋基因发现的速度,并逐渐向临床应用方向转化。文章总结了遗传性耳聋的特点和研究现状,以及新一代测序技术在耳聋研究中的应用和前景,以及基于NGS技术的耳聋基因研究和临床耳聋基因诊断的发展方向。     

下一代半导体测序技术在遗传性心肌病分子诊断中的应用

遗传性心肌病(Inherited cardiomyopathy, ICM)是一种常见的遗传性心脏疾病,主要由基因突变所致,是青少年和年轻运动员猝死的最主要原因之一。到目前为止,已经发现约100个基因和其致病有关,这些基因相关的变异位点具有不同的致病机制。随着临床遗传检测在遗传疾病诊断中的应用,对遗传性心肌病的分子遗传学特性及其致病机制进行深入了解,是对该病遗传诊断的关键。下一代半导体测序仪在2010年底由美国Life Technologies公司发布,其以布满微孔的高密度半导体芯片为测序基础,具有快速、经济、灵敏性好、准确率高等特点,已经应用于遗传疾病的突变筛查。文章主要对遗传性心肌病的分子遗传学特性和下一代半导体测序技术在遗传性心肌病遗传检测中的应用以及面临的挑战进行了概括总结,有助于遗传性心肌病的诊断、预防和治疗。     

Next-generation sequencing for identifying new genes in rare genetic diseases: many challenges and a pinch of luck

A report on the European Society of Human Genetics conference, held in Paris, France, June 8-11, 2013.     

第三代测序技术在微生物研究中的应用

1977年Sanger发明的双末端终止法开启了测序之旅,而测序技术在30多年内不断革新。每种新技术的出现都有超过前代产品的独特之处,但也会不可避免的存在自身局限性,关键在于掌握每种技术的优缺点并加以合理应用。第三代测序技术是一种集高通量、快速度、长读长及低成本等多种优点于一身的新型测序技术,它的出现为基因组学、转录组学及DNA甲基化等研究注入了新活力。本文在介绍基本技术原理的基础上,着重概述了第三代测序技术在微生物研究中的应用,从而揭示了其广泛的应用前景。     

Characterization of the seminal bacterial microbiome of healthy,fertile stallions using next-generation sequencing

High-throughput sequencing studies have shown the important role microbial communities play in the male reproductive tract, indicating differences in the semen microbial composition between fertile and infertile males. Most of these studies were made on human beings but little is known regarding domestic animals. Seminal bacteria studies made in stallions mostly focus on pathogenic bacteria and on their impact on reproductive technology. However, little is known about stallion commensal seminal microflora. That ultimately hinders our capacity to associate specific bacteria to conditions or seminal quality. Therefore, the aim of this study was to characterize the seminal microbial composition of 12 healthy, fertile stallion using next-generation sequencing. Hypervariable region V3 was chosen for bacterial identification. A total of nine phyla was detected. The most abundant ones were Bacteroidetes (46.50%), Firmicutes (29.92%) and Actinobacteria (13.58%). At family level, we found 69 bacterial families, but only nine are common in all samples. Porphyromonadaceae (33.18%), Peptoniphilaceae (14.09%), Corynebacteriaceae (11.32%) and Prevotellaceae (9.05%) were the most representative ones, while the Firmicutes phylum displayed the highest number of families (23, a third of the total). Samples showed high inter-subject variability. Findings previously described in other species notably differ from our findings. Families found in human such as Lactobacillaceae, Staphylococcaceae and Streptococcaceae only represented a 0.00%, 0.17% and 0.22% abundance in our samples, respectively. In conclusion, Porphyromonadaceae, Prevotellaceae, Peptoniphilaceae and Corynebacteriaceae families are highly represented in the seminal microbiome of healthy, fertile stallions. A high variation among individuals is also observed.     

Detailed evaluation of cancer sequencing pipelines in different microenvironments and heterogeneity levels

The importance of next generation sequencing (NGS) rises in cancer research as accessing this key technology becomes easier for researchers. The sequence data created by NGS technologies must be processed by various bioinformatics algorithms within a pipeline in order to convert raw data to meaningful information. Mapping and variant calling are the two main steps of these analysis pipelines, and many algorithms are available for these steps. Therefore, detailed benchmarking of these algorithms in different scenarios is crucial for the efficient utilization of sequencing technologies. In this study, we compared the performance of twelve pipelines (three mapping and four variant discovery algorithms) with recommended settings to capture single nucleotide variants. We observed significant discrepancy in variant calls among tested pipelines for different heterogeneity levels in real and simulated samples with overall high specificity and low sensitivity. Additional to the individual evaluation of pipelines, we also constructed and tested the performance of pipeline combinations. In these analyses, we observed that certain pipelines complement each other much better than others and display superior performance than individual pipelines. This suggests that adhering to a single pipeline is not optimal for cancer sequencing analysis and sample heterogeneity should be considered in algorithm optimization.     

A progeroid syndrome with neonatal presentation and long survival maps to 19p13.3p13.2

We report on a Palestinian family with three affected individuals exhibiting progeroid syndrome characterized by intrauterine growth retardation, a progeroid appearance, failure to thrive, short stature, and hypotonia. The progeroid features were evident at birth. All the affected members of this family have survived beyond the neonatal period and one of them is currently a 27‐year‐old adult. As parental consanguinity suggested an autosomal recessive mode of inheritance, we employed homozygosity mapping using single nucleotide polymorphism arrays followed by next generation whole exome sequencing to identify the disease‐causing gene. We were able to identify a single block of homozygosity shared between all the affected members of the studied family spanning 2.3 Mb on chromosome 19p13.3p13.2. However, Sanger sequencing of known genes and whole exome sequencing of the three affected sibs did not reveal a convincing causal mutation. These findings are anticipated to open the way for the identification of the molecular causes underlying this syndrome. Birth Defects Research (Part A) 97:456–462, 2013. © 2013 Wiley Periodicals, Inc.     

宏基因组学二代测序技术在感染性呼吸系统疾病病原体诊断中的应用进展

呼吸系统感染发病率高,早期明确感染的病原体是提高治愈率、降低死亡率的关键.目前病原体培养仍是临床病原学诊断的主要方式,但其敏感性低、耗时较长,不利于早期诊断和治疗.宏基因组学测序技术具有覆盖病原体广泛、快速、无偏倚、无需特异性扩增的优势,在鉴定罕见、混合感染、免疫抑制患者感染和常规检测方法难以检测到病原体的诊断中有较高...     

Molecular Profiling of Tumor Tissue in Mexican Patients with Colorectal Cancer

Colorectal cancer is a heterogeneous disease with multiple genomic changes that influence the clinical management of patients; thus, the search for new molecular targets remains necessary. The aim of this study was to identify genetic variants in tumor tissues from Mexican patients with colorectal cancer, using massive parallel sequencing. A total of 4813 genes were analyzed in tumoral DNA from colorectal cancer patients, using the TruSight One Sequencing panel. From these, 192 variants with clinical associations were found distributed in 168 different genes, of which 46 variants had not been previous reported in the literature or databases, although genes harboring those variants had already been described in colorectal cancer. Enrichment analysis of the affected genes was performed using Reactome software; pathway over-representation showed significance for disease, signal transduction, and immune system subsets in all patients, while exclusive subsets such as DNA repair, autophagy, and RNA metabolism were also found. Those characteristics, whether individual or shared, could give tumors specific capabilities for survival, aggressiveness, or response to treatment. Our results can be useful for future investigations targeting specific characteristics of tumors in colorectal cancer patients. The identification of exclusive or common pathways in colorectal cancer patients could be important for better diagnosis and personalized cancer treatment.     

Genome analysis of the domestic dog (Korean Jindo) by massively parallel sequencing

Although pioneering sequencing projects have shed light on the boxer and poodle genomes, a number of challenges need to be met before the sequencing and annotation of the dog genome can be considered complete. Here, we present the DNA sequence of the Jindo dog genome, sequenced to 45-fold average coverage using Illumina massively parallel sequencing technology. A comparison of the sequence to the reference boxer genome led to the identification of 4 675 437 single nucleotide polymorphisms (SNPs, including 3 346 058 novel SNPs), 71 642 indels and 8131 structural variations. Of these, 339 non-synonymous SNPs and 3 indels are located within coding sequences (CDS). In particular, 3 non-synonymous SNPs and a 26-bp deletion occur in the TCOF1 locus, implying that the difference observed in cranial facial morphology between Jindo and boxer dogs might be influenced by those variations. Through the annotation of the Jindo olfactory receptor gene family, we found 2 unique olfactory receptor genes and 236 olfactory receptor genes harbouring non-synonymous homozygous SNPs that are likely to affect smelling capability. In addition, we determined the DNA sequence of the Jindo dog mitochondrial genome and identified Jindo dog-specific mtDNA genotypes. This Jindo genome data upgrade our understanding of dog genomic architecture and will be a very valuable resource for investigating not only dog genetics and genomics but also human and dog disease genetics and comparative genomics.     

PCR反应条件对16S rRNA基因扩增子测序准确性的影响

【背景】16S rRNA基因扩增子测序技术是一种不依赖培养而获得样本中细菌种群结构、相对丰度等信息的方法。高通量测序技术实验步骤较多,每一步骤细微的差别都可能在最终的测序结果中放大,并造成测序结果与实际情况的偏差。【目的】基于MiSeq测序平台,探讨PCR反应体系中扩增引物序列、退火温度、模板起始量、扩增循环数和变性时间等5个因素对16S rRNA基因测序结果的影响。【方法】对mock DNA的16S rRNA基因扩增子进行测序,分别分析不同的扩增引物、退火温度、模板起始量、循环数和变性时间对数据准确性的影响。【结果】不同的扩增引物对检测结果有较大的影响,采用的4组引物中,引物B (V3–V4,341F/806R)的准确性最好,引物A(V3–V4,341F/805R)次之。比较不同退火温度(52、55和60℃)对检测准确性的影响,退火温度60℃的结果最接近理论值。模板起始量(2、10和50 ng)的检测结果显示,mock DNA起始量为2ng的结果准确性最高。相较于其他3组(15+18、25+8和30+8),循环数为(20+8)的检测结果最接近mock DNA的理论值。不同变性时间(3...     

基于第二代测序技术的细菌基因组与转录组研究策略简介

随着基于第二代测序技术的细菌基因组与转录组研究越来越广泛,选择合适的研究策略变得越来越重要.就基于第二代测序技术的细菌基因组和转录组研究策略进行综述,并简要介绍细菌基因组和转录组研究中的机遇和挑战.综述细菌基因组与转录组研究的常规方法及步骤,并简要地介绍存在的问题.细菌基因组和转录组研究策略为大多数细菌的研究提供了一个...     

Genotyping‐by‐sequencing approaches to characterize crop genomes: choosing the right tool for the right application

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high‐throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping‐by‐sequencing (GBS) methods include over a dozen reduced‐representation sequencing (RRS) approaches and at least four whole‐genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best‐suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small‐ to moderate‐sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost‐effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost‐effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.     

Water mass-specificity of bacterial communities in the North Atlantic revealed by massively parallel sequencing

Bacterial assemblages from subsurface (100 m depth), meso- (200-1000 m depth) and bathy-pelagic (below 1000 m depth) zones at 10 stations along a North Atlantic Ocean transect from 60°N to 5°S were characterized using massively parallel pyrotag sequencing of the V6 region of the 16S rRNA gene (V6 pyrotags). In a dataset of more than 830,000 pyrotags, we identified 10,780 OTUs of which 52% were singletons. The singletons accounted for less than 2% of the OTU abundance, whereas the 100 and 1000 most abundant OTUs represented 80% and 96% respectively of all recovered OTUs. Non-metric Multi-Dimensional Scaling and Canonical Correspondence Analysis of all the OTUs excluding the singletons revealed a clear clustering of the bacterial communities according to the water masses. More than 80% of the 1000 most abundant OTUs corresponded to Proteobacteria of which 55% were Alphaproteobacteria, mostly composed of the SAR11 cluster. Gammaproteobacteria increased with depth and included a relatively large number of OTUs belonging to Alteromonadales and Oceanospirillales. The bathypelagic zone showed higher taxonomic evenness than the overlying waters, albeit bacterial diversity was remarkably variable. Both abundant and low-abundance OTUs were responsible for the distinct bacterial communities characterizing the major deep-water masses. Taken together, our results reveal that deep-water masses act as bio-oceanographic islands for bacterioplankton leading to water mass-specific bacterial communities in the deep waters of the Atlantic.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.