蛋白质序列与EST序列的反翻译联配

随着大规模技术的进步,收录到数据库中的序列很快,其中大多是未知功能的ＥＳＴｓ（表达序列标签,Ｅｘｐｒｅｓｓｅｄ Ｓｅｑｕｅｎｃｅ Ｔａｇｓ）,一般通过蛋白南－ＥＳＴ序列联配来实验ＥＳＴ的功能提示。由于ＥＳＴ含有５％左右的误差,特别严重的是其中的移框误差,用通常的方法将ＥＳＴ按６个框翻译为蛋白南序列再进行联配难以处理移框误差问题。通过考虑ＥＳＴ序列各种可能的误差,将氨基酸序列反翻译为核苷酸序列,在核     

HaMStR: Profile hidden markov model based search for orthologs in ESTs

Background  

EST sequencing is a versatile approach for rapidly gathering protein coding sequences. They provide direct access to an organism's gene repertoire bypassing the still error-prone procedure of gene prediction from genomic data. Therefore, ESTs are often the only source for biological sequence data from taxa outside mainstream interest. The widespread use of ESTs in evolutionary studies and particularly in molecular systematics studies is still hindered by the lack of efficient and reliable approaches for automated ortholog predictions in ESTs. Existing methods either depend on a known species tree or cannot cope with redundancy in EST data.     

Pooled library tissue tags for EST-based gene discovery

MOTIVATION: In gene discovery projects based on EST sequencing, effective post-sequencing identification methods are important in determining tissue sources of ESTs within pooled cDNA libraries. In the past, such identification efforts have been characterized by higher than necessary failure rates due to the presence of errors within the subsequence containing the oligo tag intended to define the tissue source for each EST. RESULTS: A large-scale EST-based gene discovery program at The University of Iowa has led to the creation of a unique software method named UITagCreator usable in the creation of large sets of synthetic tissue identification tags. The identification tags provide error detection and correction capability and, in conjunction with automated annotation software, result in a substantial improvement in the accurate identification of the tissue source in the presence of sequencing and base-calling errors. These identification rates are favorable, relative to past paradigms. AVAILABILITY: The UITagCreator source code and installation instructions, along with detection software usable in concert with created tag sets, is freely available at http://genome.uiowa.edu/pubsoft/software.html CONTACT: tomc@eng.uiowa.edu     

Refined annotation of the Arabidopsis genome by complete expressed sequence tag mapping

Expressed sequence tags (ESTs) currently encompass more entries in the public databases than any other form of sequence data. Thus, EST data sets provide a vast resource for gene identification and expression profiling. We have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing. All results of this study were parsed into a database and are accessible via a flexible Web interface at http://www.plantgdb.org/AtGDB/.     

Gene expression profile of human bone marrow stromal cells: high-throughput expressed sequence tag sequencing analysis

Human bone marrow stromal cells (HBMSC) are pluripotent cells with the potential to differentiate into osteoblasts, chondrocytes, myelosupportive stroma, and marrow adipocytes. We used high-throughput DNA sequencing analysis to generate 4258 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' (97) and 3' (4161) ends of human cDNA clones from a HBMSC cDNA library. Our goal was to obtain tag sequences from the maximum number of possible genes and to deposit them in the publicly accessible database for ESTs (dbEST of the National Center for Biotechnology Information). Comparisons of our EST sequencing data with nonredundant human mRNA and protein databases showed that the ESTs represent 1860 gene clusters. The EST sequencing data analysis showed 60 novel genes found only in this cDNA library after BLAST analysis against 3.0 million ESTs in NCBI's dbEST database. The BLAST search also showed the identified ESTs that have close homology to known genes, which suggests that these may be newly recognized members of known gene families. The gene expression profile of this cell type is revealed by analyzing both the frequency with which a message is encountered and the functional categorization of expressed sequences. Comparing an EST sequence with the human genomic sequence database enables assignment of an EST to a specific chromosomal region (a process called digital gene localization) and often enables immediate partial determination of intron/exon boundaries within the genomic structure. It is expected that high-throughput EST sequencing and data mining analysis will greatly promote our understanding of gene expression in these cells and of growth and development of the skeleton.     

Motifer, a search tool for finding amino acid sequence patterns from nucleotide sequence databases.

Motifer is a software tool able to find directly in nucleotide databases very distant homologues to an amino acid query sequence. It focuses searches on a specific amino acid pattern, scoring the matching and intervening residues as specified by the user. The program has been developed for searching databases of expressed sequence tags (ESTs), but it is also well suited to search genomic sequences. The query sequence can be a variable pattern with alternative amino acids or gaps and the sequences searched can contain introns or sequencing errors with accompanying frame shifts. Other features include options to generate a searchable output, set the maximal sequencing error frequency, limit searches to given species, or exclude already known matches. Motifer can find sequence homologues that other search algorithms would deem unrelated or would not find because of sequencing errors or a too large number of other homologues. The ability of Motifer to find relatives to a given sequence is exemplified by searches for members of the transforming growth factor-beta family and for proteins containing a WW-domain. The functions aimed at enhancing EST searches are illustrated by the 'in silico' cloning of a novel cytochrome P450 enzyme.     

一种新的EST聚类方法

该研究发展了一种EST（expressed sequence tag）聚类方法（ESTClustering）,用于分析大规模EST测序中所产生的大量数据,以获得高质量,非重复表达序列,该方法在聚类过程中采用MEGABLAST工具对一致序列进行序列同源比较,并用phrap程序对每一EST簇进行拼接检验。这一聚类策略能降低测序错误带来的影响,有效识别基因家族成员,并避免选择性剪接的干扰,与NCB（National Center for Biotechnology Information）的UniGene clustering）方法相比,ESTClustering的聚类结果可以更好地反映表达序列的多样性,用ESTClustering对112256条拟南芥EST聚类测试,产生23581个EST簇,其中13597个EST簇有对应拟南芥基因组编码序列,与该基因组中有EST作为依据的预测基因数目接近。应用该方法对收集的147191条水稻EST序列进行聚类,形成33896个EST簇。     

ESMP: A high-throughput computational pipeline for mining SSR markers from ESTs

With the advent of high-throughput sequencing technology, sequences from many genomes are being deposited to public databases at a brisk rate. Open access to large amount of expressed sequence tag (EST) data in the public databases has provided a powerful platform for simple sequence repeat (SSR) development in species where sequence information is not available. SSRs are markers of choice for their high reproducibility, abundant polymorphism and high inter-specific transferability. The mining of SSRs from ESTs requires different high-throughput computational tools that need to be executed individually which are computationally intensive and time consuming. To reduce the time lag and to streamline the cumbersome process of SSR mining from ESTs, we have developed a user-friendly, web-based EST-SSR pipeline "EST-SSR-MARKER PIPELINE (ESMP)". This pipeline integrates EST pre-processing, clustering, assembly and subsequently mining of SSRs from assembled EST sequences. The mining of SSRs from ESTs provides valuable information on the abundance of SSRs in ESTs and will facilitate the development of markers for genetic analysis and related applications such as marker-assisted breeding. AVAILABILITY: The database is available for free at http://bioinfo.aau.ac.in/ESMP.     

杨树基因组中染色体基因丰度分化及EST序列对基因覆盖度的检测(英文)

高等植物基因组中,大部分序列为非表达序列,基因序列所占的比例很小,了解基因在基因组中的分布是研究基因组结构的一个重要方面。在美国能源部资助下,一个毛果杨无性系的基因组测序已经完成并对公众发布。杨树全基因组序列的完成,为我们了解林木基因组中基因的分布提供了一个特例。在本文中,我们利用泊松分析对杨树基因组中基因在各个染色体上的密度进行了检测,结果表明杨树基因组中各条染色体的基因含量存在显著差异。杨树全基因组测序项目揭示现代杨树基因组起源于一次古全基因组复制事件(称为杨柳科基因组复制),所以杨树基因组不同染色体间存在很大的同源复制片段。但是我们的研究显示,杨树基因组中大多数高度同源的染色体上基因的密度与染色体间的同源性没有明显关系,这说明杨柳科全基因组复制事件后,各个高度同源染色体上的基因发生了流失,且基因流失的速率是不一样的。同时本文还对近九万条毛果杨EST序列进行了比对分析,结果显示这些EST序列覆盖的基因仅占杨树基因组中基因总数的16.8%左右。EST测序虽然是发现基因的一个重要手段,但小规模EST测序对基因的覆盖度很低,所以小规模EST测序的应用价值是有限的。     

Efficient clustering of large EST data sets on parallel computers

Clustering expressed sequence tags (ESTs) is a powerful strategy for gene identification, gene expression studies and identifying important genetic variations such as single nucleotide polymorphisms. To enable fast clustering of large-scale EST data, we developed PaCE (for Parallel Clustering of ESTs), a software program for EST clustering on parallel computers. In this paper, we report on the design and development of PaCE and its evaluation using Arabidopsis ESTs. The novel features of our approach include: (i) design of memory efficient algorithms to reduce the memory required to linear in the size of the input, (ii) a combination of algorithmic techniques to reduce the computational work without sacrificing the quality of clustering, and (iii) use of parallel processing to reduce run-time and facilitate clustering of larger data sets. Using a combination of these techniques, we report the clustering of 168 200 Arabidopsis ESTs in 15 min on an IBM xSeries cluster with 30 dual-processor nodes. We also clustered 327 632 rat ESTs in 47 min and 420 694 Triticum aestivum ESTs in 3 h and 15 min. We demonstrate the quality of our software using benchmark Arabidopsis EST data, and by comparing it with CAP3, a software widely used for EST assembly. Our software allows clustering of much larger EST data sets than is possible with current software. Because of its speed, it also facilitates multiple runs with different parameters, providing biologists a tool to better analyze EST sequence data. Using PaCE, we clustered EST data from 23 plant species and the results are available at the PlantGDB website.     

ESTimating plant phylogeny: lessons from partitioning

Background  

While Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies.     

Analysis of expressed sequence tags from the fungus Aspergillus oryzae cultured under different conditions.

We performed random sequencing of cDNAs from nine biologically or industrially important cultures of the industrially valuable fungus Aspergillus oryzae to obtain expressed sequence tags (ESTs). Consequently, 21 446 raw ESTs were accumulated and subsequently assembled to 7589 non-redundant consensus sequences (contigs). Among all contigs, 5491 (72.4%) were derived from only a particular culture. These included 4735 (62.4%) singletons, i.e. lone ESTs overlapping with no others. These data showed that consideration of culture grown under various conditions as cDNA sources enabled efficient collection of ESTs. BLAST searches against the public databases showed that 2953 (38.9%) of the EST contigs showed significant similarities to deposited sequences with known functions, 793 (10.5%) were similar to hypothetical proteins, and the remaining 3843 (50.6%) showed no significant similarity to sequences in the databases. Culture-specific contigs were extracted on the basis of the EST frequency normalized by the total number for each culture condition. In addition, contig sequences were compared with sequence sets in eukaryotic orthologous groups (KOGs), and classified into the KOG functional categories.     

Initial assessment of gene diversity for the oomycete pathogen Phytophthora infestans based on expressed sequences

A total of 1000 expressed sequence tags (ESTs) corresponding to 760 unique sequence sets were identified using random sequencing of clones from a cDNA library constructed from mycelial RNA of Phytophthora infestans. A number of software programs, represented by a relational database and an analysis pipeline, were developed for the automated analysis and storage of the EST sequence data. A set of 419 nonredundant sequences, which correspond to a total of 632 ESTs (63.2%), were identified as showing significant matches to sequences deposited in public databases. A putative cellular identity and role was assigned to all 419 sequences. All major functional categories were represented by at least several ESTs. Four novel cDNAs containing sequences related to elicitins, a family of structurally related proteins that induce the hypersensitive response and condition avirulence of P. infestans on Nicotiana plants, were among the most notable genes identified. Two of these elicitin-like cDNAs were among the most abundant cDNAs examined. The set also contained several ESTs with high sequence similarity to unique plant genes.     

QualitySNP: a pipeline for detecting single nucleotide polymorphisms and insertions/deletions in EST data from diploid and polyploid species

Background  

Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only.     

Snipping polymorphisms from large EST collections in barley (<Emphasis Type="Italic">Hordeum vulgare </Emphasis>L.)

The public EST (expressed sequence tag) databases represent an enormous but heterogeneous repository of sequences, including many from a broad selection of plant species and a wide range of distinct varieties. The significant redundancy within large EST collections makes them an attractive resource for rapid pre-selection of candidate sequence polymorphisms. Here we present a strategy that allows rapid identification of candidate SNPs in barley (Hordeum vulgare L.) using publicly available EST databases. Analysis of 271,630 EST sequences from different cDNA libraries, representing 23 different barley varieties, resulted in the generation of 56,302 tentative consensus sequences. In all, 8171 of these unigene sequences are members of clusters with six or more ESTs. By applying a novel SNP detection algorithm (SNiPpER) to these sequences, we identified 3069 candidate inter-varietal SNPs. In order to verify these candidate SNPs, we selected a small subset of 63 present in 36 ESTs. Of the 63 SNPs selected, we were able to validate 54 (86%) using a direct sequencing approach. For further verification, 28 ESTs were mapped to distinct loci within the barley genome. The polymorphism information content (PIC) and nucleotide diversity () values of the SNPs identified by the SNiPpER algorithm are significantly higher than those that were obtained by random sequencing. This demonstrates the efficiency of our strategy for SNP identification and the cost-efficient development of EST-based SNP-markers.The first two authors contributed equally to this work     

陆地棉EST长度多态性与其SSR分布特征相关性分析

目的:分析陆地棉EST长度多态性与其SSR分布特征的相关性。方法:从NCBI公共数据库下载陆地棉EST序列,应用SSRIT搜索SSR,分析20 000条无冗余的EST序列。结果:在剔除低质量和冗余的序列后,得到全长为7 363.878kb的无冗余EST序列7 322条,其中含有SSR位点的EST序列数520条,占被分析EST比例的2.60%。长度在400bp以下的EST序列含SSR的比例为1.46%;长度在400bp以上的EST序列含SSR的比例为8.94%。在1～6bp的重复基元中,二核苷酸重复基元的SSR重复频率最高,占总数的63.46%,其次是三核苷酸,占总数的34.04%。二核苷酸类型(AG)n、(AT)n和三核苷酸类型(AAG)n、(ACC)n、(ACT)n、(AAT)n是SSR的主要重复基元。结论:棉花EST-SSR可用于棉花分子标记,为有针对性设计陆地棉EST-SSR引物奠定基础。