采用高通量测序技术分析尾病毒目噬菌体基因组末端序列特点

证明噬菌体高通量测序中高频出现的序列即是噬菌体基因组的末端序列。在T3噬菌体基因组末端连接特异性序列接头,然后进行高通量测序,同时将不加接头的T3基因组也进行高通量测序,对测序结果进行生物信息学比较分析。采用类似高通量测序技术分析N4样噬菌体的全基因组序列。加接头的序列与无接头序列中的高频序列完全一致,证明了高通量测序过程中得到的高频序列就是加接头的基因组末端序列,同时证明T4样噬菌体的末端具有序列特异性而非完全随机,此外我们还发现N4样噬菌体基因组左侧末端具有唯一序列,而其基因组右侧末端不均一。高通量测序技术方便快捷,可用于噬菌体基因组末端和全基因组序列的同时测定。     

四种常用的生物序列比对软件比较

随着高通量测序技术的快速发展,下一代测序技术也迅速发展为生物领域中的主流技术,而理解下一代测序数据最重要的一步是比对。比对是进行后续生物信息分析的基石,也因此催生了很多比对软件。本文主要选取了四种常用的比对软件Bowtie2、BWA、MAQ和SOAP2,对这四种软件及算法进行综述,并通过实际测序数据对四种软件进行比较和评估,为生物学研究者选择最佳的短序列比对软件提供理论和实践依据。     

高通量测序技术在农作物全基因组序列测定中的应用概览

近几年飞速发展的高通量测序技术(next generation sequencing,NGS)在生命科学研究的各个领域充分展现了其低成本、高通量和应用面广等优势。在现代农业生物技术领域,利用高通量测序技术,科学家们不仅能更经济而高效对农作物、模式植物或不同栽培品种进行深入的全基因组测序、重测序,也可以对成百上千的栽培品种进行高效而准确的遗传差异分析、分子标记分析、连锁图谱分析、表观遗传学分析、转录组分析,进而改进农作物的育种技术,加快新品种的育种研究。其中,获得农作物的全基因组序列是其他研究和分析的基础。本文通过介绍近年来发表的一些利用高通量测序技术进行的农作物全基因组测定和组装的工作,展示高通量测序技术在现代农业生物技术领域的广泛前景以及其建立起来的研究基础。     

高通量测序技术及其应用

高通量测序技术是DNA测序发展历程的一个里程碑,它为现代生命科学研究提供了前所未有的机遇。详细介绍了以454、Solexa和SOLiD为代表的第二代高通量测序技术,以HeliScope TIRM和Pacific Biosciences SMRT为代表的单分子测序技术,以及最近Life Science公司推出的Ion Personal Genome Machine (PGM)测序技术等高通量测序技术的最新进展。在此基础上,阐述了高通量测序技术在基因组测序、转录组测序、基因表达调控、转录因子结合位点的检测以及甲基化等研究领域的应用。最后,讨论了高通量测序技术在成本和后续数据分析等方面存在的问题及其未来的发展前景。     

一种结合单张芯片序列捕获和高通量测序技术测序外显子组的方法

随着高通量测序技术的发展,全外显子测序已经成为一种研究人类疾病的重要方法.本文展示了一种通过Nimblegen2.1M芯片进行外显子DNA序列捕获和高通量测序的方法,包括两步法文库制备.测序的平均覆盖深度达33倍时,95.6%的34M目标区域得到均衡覆盖,特异性达到80%.对比全基因组鸟枪法测序的结果,此方法在检测SNP时的假阳性率为0.97%,假阴性率为6.27%.本方法对于全基因组扩增的DNA也适用.结果显示,全外显子测序技术可以在大规模的群体研究和医学研究中起到重要作用.     

牛全基因组高通量测序技术研究进展

现代科技迅速发展的今天,无疑是分子生物学的世界。基因组测序是对生物的遗传结构进行分析的一种技术。作为一项尤为重要的生物技术。在近几年来得到了迅猛的发展以及应用,并取得了跨越性的进展,在很多领域取得了革命性的成就。无论是在人类疾病的防治,还是在畜牧遗传育种发面都发挥着重要的作用。本综述主要介绍了第一代测序技术、第二代测序技术以及第三代测序技术的原理,并对三者的优缺点进行了比较说明,还分别阐述了全基因组高通量技术在肉牛的起源、遗传育种与优良性状的选育和奶牛的疾病防治、生产性能的提高等方面的研究进展,对当下的高通量测序技术存在的问题进行了讨论,并对其未来进行了展望。     

高通量测序数据的基因组拷贝数变异检测方法综述

拷贝数变异是指基因组中发生大片段的DNA序列的拷贝数增加或者减少。根据现有的研究可知,拷贝数变异是多种人类疾病的成因,与其发生与发展机制密切相关。高通量测序技术的出现为拷贝数变异检测提供了技术支持,在人类疾病研究、临床诊疗等领域,高通量测序技术已经成为主流的拷贝数变异检测技术。虽然不断有新的基于高通量测序技术的算法和软件被人们开发出来,但是准确率仍然不理想。本文全面地综述基于高通量测序数据的拷贝数变异检测方法,包括基于reads深度的方法、基于双末端映射的方法、基于拆分read的方法、基于从头拼接的方法以及基于上述4种方法的组合方法,深入探讨了每类不同方法的原理,代表性的软件工具以及每类方法适用的数据以及优缺点等,并展望未来的发展方向。     

高通量测序在可变剪接中的研究进展

在真核生物基因表达的过程中, mRNA的可变剪接(alternative splicing, AS)导致同一基因蛋白质亚型多样性的产生,同时也增加了基因表达调控的多样性。高达95%的人类基因可以通过AS来产生具有不同功能的蛋白质。除此之外,约15%的人类遗传疾病和癌症与AS相关。作为一种精密的基因表达调控方式, AS协助完成重要的生物过程,如细胞发育和分化等。近年来,高通量测序的发展推动了AS在分析组织特异性基因表达领域的研究。然而,两者的有机结合应用仍然具有挑战性。该文总结了高通量测序在AS研究中的应用,进一步分析了其中存在的问题,并提出了解决方法,为推动该领域的发展提供了新的策略与思路。     

用于多重PCR甲基化靶向测序的比对软件性能评估

多重PCR甲基化靶向测序数据尚缺乏针对性的比对软件。本研究评估了9种比对方案在处理多重PCR甲基化靶向测序数据时的性能,包括平均CPU运行时间、平均最大内存、平均比对率、 F1分数、平均比对速率、比对未通过率和差异甲基化位点,以及比对率受亚硫酸氢盐转化率和测序错误率的影响。本研究建立了打分系统以综合评价比对方案的优劣,结果显示,排名前三的方案依次为Bismarkbwt2(8.098分)、 BWA-meth(7.846分)和Bismarkbwt1(7.840分)。这三个方案的F1分数均为1.000,且在不同亚硫酸氢盐转化率和测序错误率下的比对率表现最优。此外,Bismarkbwt2还对应最多的差异甲基化位点和最低的比对未通过率,并在平均最大内存和平均比对率两项指标上表现良好。因此,本研究推荐Bowtie2模式下的Bismark作为后续搭建多重PCR甲基化靶向测序生物信息学分析流程的比对软件。     

高通量测序技术在食品微生物研究中的应用

高通量测序技术的快速发展对食品微生物发酵过程和机制研究产生了深刻的影响,主要体现在食品微生物生理功能、代谢能力和进化的研究以及食品微生物群落结构、动态变化及其对环境的响应机制等方面。另外,通过对食品微生物基因组和元基因组进行数据分析,也对食品发酵过程优化、微生物功能改造、食源性微生物疾病预防和控制等提供了重要的依据。本文总结了近年来利用高通量测序技术对食品微生物基因组和元基因组进行测序的研究,并探讨了测序技术的发展对食品微生物研究的影响及发展趋势。     

High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.     

Coval: Improving Alignment Quality and Variant Calling Accuracy for Next-Generation Sequencing Data

Accurate identification of DNA polymorphisms using next-generation sequencing technology is challenging because of a high rate of sequencing error and incorrect mapping of reads to reference genomes. Currently available short read aligners and DNA variant callers suffer from these problems. We developed the Coval software to improve the quality of short read alignments. Coval is designed to minimize the incidence of spurious alignment of short reads, by filtering mismatched reads that remained in alignments after local realignment and error correction of mismatched reads. The error correction is executed based on the base quality and allele frequency at the non-reference positions for an individual or pooled sample. We demonstrated the utility of Coval by applying it to simulated genomes and experimentally obtained short-read data of rice, nematode, and mouse. Moreover, we found an unexpectedly large number of incorrectly mapped reads in ‘targeted’ alignments, where the whole genome sequencing reads had been aligned to a local genomic segment, and showed that Coval effectively eliminated such spurious alignments. We conclude that Coval significantly improves the quality of short-read sequence alignments, thereby increasing the calling accuracy of currently available tools for SNP and indel identification. Coval is available at http://sourceforge.net/projects/coval105/.     

Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform

Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina''s MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.     

利用siRNA高通量测序技术筛查蚊子体内携带的RNA病毒

昆虫可以利用小干扰RNA(siRNA)机制干扰体内RNA病毒的增殖,从而获得对该病毒的免疫能力。通过第二代测序技术对蚊子的小RNA进行高通量测序,再通过生物信息学方法寻找其中的RNA病毒序列,发现在我国云南地区的白纹伊蚊和致倦库蚊体内存在Marayo,Omsk hemorrhagic fever和Ilheus等RNA病毒的基因片段。至此建立了发现媒介昆虫体内携带病毒的一种新方法,可用于媒介昆虫携带RNA病毒的本底调查。     

基于高通量测序的文冠果转录组分析

应用Illumina Hi-seqTM2000高通量测序技术对文冠果花芽进行转录组分析。共获得N50为1 180bp、平均长度为686bp的unigene 58 311条。与公共数据库Nr和Swiss-Prot同源性比较后发现37 047条unigene获得基因注释,另有21 264条unigene未被注释。利用COG数据库将unigene分成25类。通过GO分类和KEGG Pathway富集性分析,将unigene分别归类于55个GO term和128个代谢途径。此外,在9 794条unigene中共搜索到12 213个SSR位点,单核苷酸重复基元出现频率最高(34.95%),其次分别为二核苷酸(32.74%)和三核苷酸(28.64%)。在获得的unigene中发掘出涉及4个开花调控途径(光周期途径、春化途径、GA途径和自主途径)多个基因的同源序列。研究结果可在一定程度上解析文冠果花芽形态分化的分子调控模式与机制。     

Efficient Alignment of RNAs with Pseudoknots Using Sequence Alignment Constraints

When aligning RNAs, it is important to consider both the secondary structure similarity and primary sequence similarity to find an accurate alignment. However, algorithms that can handle RNA secondary structures typically have high computational complexity that limits their utility. For this reason, there have been a number of attempts to find useful alignment constraints that can reduce the computations without sacrificing the alignment accuracy. In this paper, we propose a new method for finding effective alignment constraints for fast and accurate structural alignment of RNAs, including pseudoknots. In the proposed method, we use a profile-HMM to identify the “seedâ€� regions that can be aligned with high confidence. We also estimate the position range of the aligned bases that are located outside the seed regions. The location of the seed regions and the estimated range of the alignment positions are then used to establish the sequence alignment constraints. We incorporated the proposed constraints into the profile context-sensitive HMM (profile-csHMM) based RNA structural alignment algorithm. Experiments indicate that the proposed method can make the alignment speed up to 11 times faster without degrading the accuracy of the RNA alignment.     

Choice of Reference Sequence and Assembler for Alignment of Listeria monocytogenes Short-Read Sequence Data Greatly Influences Rates of Error in SNP Analyses

The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (i.e., true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real Listeria monocytogenes strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (i.e., quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results.