基于第二代测序技术的基因资源挖掘

转录组研究一直是生命科学研究的一个重要方向,在第二代测序技术问世以前,已经产生了一些行之有效的转录组研究方法,但这些方法存在一定的局限性。第二代测序技术的出现不仅使转录组研究很快进入了高速发展期,同时也为遗传资源的挖掘提供了一套全新的技术平台。本文简要介绍了第二代测序技术的化学原理和特性,重点阐述了利用第二代测序技术进行转录组测序,从而在此基础上挖掘遗传资源的研究。     

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。     

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...     

高通量转录组测序技术及其在鳞翅目昆虫上的应用

转录组是指组织或者细胞在某一特定状态下转录出来的所有RNA的集合。高通量第2代测序技术使转录组学的研究模式发生了巨大的改变,所衍生出的转录组测序迅速成为研究非模式生物的先进技术。转录组测序能够在整体水平上探究细胞内基因表达的种类和数量,揭示在特定条件下机体生理生化发生过程以及其中的分子机理。本文简要阐述了转录组测序技术的基本概念、技术流程与原理,详细介绍了转录组测序在解决鳞翅目昆虫的分类、毒理、发育、与寄主互作以及非编码RNA调控等问题上做出的贡献,并对该技术现存的困难进行了系统的阐述并对其未来的发展趋势作出了简要的预测与剖析。     

基于短序列测序数据的四倍体拟南芥转录组研究

为了促进对四倍体拟南芥(A.suecica)的研究,阐明多倍体植物在染色体加倍过程中遗传物质的变化,从而在分子层面上解释多倍体植物的环境适应和进化机制,描述了一套基于第二代测序技术的转录组短序列组装和生物信息学分析方法.通过对23 000 000条来至于Illumina测序平台的序列数据进行SOAPdenovo组装,以...     

基于Illumina RNA-Seq短序列的转录组从头组装软件比较与优化

利用公共数据库中果蝇F1代和栽培水稻基于高通量Illumina测序平台的RNA-Seq短序列数据,比较了8个(ABySS,Velvet,SOAPdenovo,Oases,Trinity,Multiple-k,T-IDBA and Trans-ABySS)转录组从头组装软件.结果显示,在基于单一k-mer和多重k-mer方法的两类软件中,Trinity和Trans-ABySS分别表现出最好的组装性能,而其它软件性能比较接近.我们还发现基于多重k-mer比单一k-mer可以组装获得更多的总碱基数目,但是即使利用最好的多重k-mer组装软件,所获得的数据质量也比研究人员所期望的要低.鉴于此,我们提出了“ETM”优化方法,将多重k-mer方法组合到Trinity中,使其在具有最好的组装性能的基础上兼具了多重k-mer的优势,测试结果显示了该方法具有一定的优越性.我们的研究结果为用户选择合适的软件提供了依据,对推动基于高通量Illumina测序的转录组研究具有重要意义.     

基于Illumina RNA Seq短序列的转录组从头组装软件比较与优化

利用公共数据库中果蝇F1代和栽培水稻基于高通量Illumina测序平台的RNA Seq短序列数据,比较了8个 (ABySS, Velvet, SOAPdenovo, Oases, Trinity, Multiple k, T IDBA and Trans ABySS) 转录组从头组装软件。结果显示,在基于单一k mer和多重k mer方法的两类软件中,Trinity和Trans ABySS分别表现出最好的组装性能,而其它软件性能比较接近。我们还发现基于多重k mer比单一k mer可以组装获得更多的总碱基数目,但是即使利用最好的多重k mer组装软件,所获得的数据质量也比研究人员所期望的要低。鉴于此,我们提出了“ETM”优化方法,将多重k mer方法组合到Trinity中,使其在具有最好的组装性能的基础上兼具了多重k mer的优势,测试结果显示了该方法具有一定的优越性。我们的研究结果为用户选择合适的软件提供了依据,对推动基于高通量Illumina测序的转录组研究具有重要意义。     

生长滞缓与正常罗氏沼虾转录组差异分析

旨在利用浙江地区生长正常和生长滞缓两种生长状态下的罗氏沼虾,通过转录组测序技术,比对基因表达量的差异,探究生长滞缓的原因.本研究采用IlluminaHiSeqTM4000测序平台,对存在生长差异的罗氏沼虾的鳃、肝胰腺、肌肉三种组织共18个样本进行了转录组测序分析,将得到的基因片段组装后与NR、GO、KEGG、eggNO...     

An Integrated Pipeline for de Novo Assembly of Microbial Genomes

Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron''s Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage.     

A strategy for assembling the maize (Zea mays L.) genome

Because the bulk of the maize (Zea mays L.) genome consists of repetitive sequences, sequencing efforts are being targeted to its 'gene-rich' fraction. Traditional assembly programs are inadequate for this approach because they are optimized for a uniform sampling of the genome and inherently lack the ability to differentiate highly similar paralogs. RESULTS: We report the development of bioinformatics tools for the accurate assembly of the maize genome. This software, which is based on innovative parallel algorithms to ensure scalability, assembled 730,974 genomic survey sequences fragments in 4 h using 64 Pentium III 1.26 GHz processors of a commodity cluster. Algorithmic innovations are used to reduce the number of pairwise alignments significantly without sacrificing quality. Clone pair information was used to estimate the error rate for improved differentiation of polymorphisms versus sequencing errors. The assembly was also used to evaluate the effectiveness of various filtering strategies and thereby provide information that can be used to focus subsequent sequencing efforts.     

Augmenting Chinese hamster genome assembly by identifying regions of high confidence

Chinese hamster Ovary (CHO) cell lines are the dominant industrial workhorses for therapeutic recombinant protein production. The availability of genome sequence of Chinese hamster and CHO cells will spur further genome and RNA sequencing of producing cell lines. However, the mammalian genomes assembled using shot‐gun sequencing data still contain regions of uncertain quality due to assembly errors. Identifying high confidence regions in the assembled genome will facilitate its use for cell engineering and genome engineering. We assembled two independent drafts of Chinese hamster genome by de novo assembly from shotgun sequencing reads and by re‐scaffolding and gap‐filling the draft genome from NCBI for improved scaffold lengths and gap fractions. We then used the two independent assemblies to identify high confidence regions using two different approaches. First, the two independent assemblies were compared at the sequence level to identify their consensus regions as ”high confidence regions“ which accounts for at least 78 % of the assembled genome. Further, a genome wide comparison of the Chinese hamster scaffolds with mouse chromosomes revealed scaffolds with large blocks of collinearity, which were also compiled as high‐quality scaffolds. Genome scale collinearity was complemented with EST based synteny which also revealed conserved gene order compared to mouse. As cell line sequencing becomes more commonly practiced, the approaches reported here are useful for assessing the quality of assembly and potentially facilitate the engineering of cell lines.