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。     

From Arabidopsis to rice genomics: a survey of French programmes.

During the last ten years, Arabidopsis thaliana has become the most favoured plant system for the study of many aspects of development and adaptation to adverse conditions and diseases. The sequencing of the Arabidopsis thaliana genome is nearly completed with more than 90% of the sequence being released in public databases. This is the first plant genome to be analysed and it has revealed a tremendous amount of information about the nature of the genes it contains and its largely duplicated organisation. French groups have been involved in Arabidopsis genomics at several steps: EST (expressed sequence tags) sequencing, construction and ordering (physical mapping of chromosomes) of a YAC (yeast artificial chromosomes) library, genomic sequencing. In parallel an extensive programme of functional genomics is being undertaken through the systematic analysis of insertional mutants. This information provides a support for analysing other more economically important plant genomes such as the rice genome and constitutes the beginning of a systematic investigation on plant gene functions and will promote new strategies for plant improvement.     

The Arabidopsis thaliana genome project

The genome of the model plant Arabidopsis thaliana is being analyzed in more and more detail. This paper reviews recent progress over the last 5 years. A first goal was to establish a catalogue of expressed genes using the EST (expressed sequence tag) strategy. Two consortia (French and American) have together released close to 30 000 EST representing approximately 10 000 genes. Such a catalogue has already facilitated a number of biological analyses. The next step, which is sequencing the whole genome, has already started with a European Union pilot project, which has demonstrated the feasability of the large scale sequencing of this genome. During the last 3 years 2.5 Mbp have been determined and data acquisition is accelerating tremendously. Two major questions remain for the future. What is the function of the genes with no known homology? How can this enormous information resource be used for the benefit of other plants? A few current ideas and perspectives are discussed.     

The organization of cytoplasmic ribosomal protein genes in the Arabidopsis genome

Eukaryotic ribosomes are made of two components, four ribosomal RNAs, and approximately 80 ribosomal proteins (r-proteins). The exact number of r-proteins and r-protein genes in higher plants is not known. The strong conservation in eukaryotic r-protein primary sequence allowed us to use the well-characterized rat (Rattus norvegicus) r-protein set to identify orthologues on the five haploid chromosomes of Arabidopsis. By use of the numerous expressed sequence tag (EST) accessions and the complete genomic sequence of this species, we identified 249 genes (including some pseudogenes) corresponding to 80 (32 small subunit and 48 large subunit) cytoplasmic r-protein types. None of the r-protein genes are single copy and most are encoded by three or four expressed genes, indicative of the internal duplication of the Arabidopsis genome. The r-proteins are distributed throughout the genome. Inspection of genes in the vicinity of r-protein gene family members confirms extensive duplications of large chromosome fragments and sheds light on the evolutionary history of the Arabidopsis genome. Examination of large duplicated regions indicated that a significant fraction of the r-protein genes have been either lost from one of the duplicated fragments or inserted after the initial duplication event. Only 52 r-protein genes lack a matching EST accession, and 19 of these contain incomplete open reading frames, confirming that most genes are expressed. Assessment of cognate EST numbers suggests that r-protein gene family members are differentially expressed.     

How can we deliver the large plant genomes? Strategies and perspectives

The first sequenced plant genome, from the small mustard plant Arabidopsis thaliana, was published at the end of 2000. The sequencing of the rice genome is well under way. The sizes of plant genomes vary by a factor of up to 1000, and many important crop plants have genomes that are several times larger than the human genome. To gain insight into the gene toolbox of plant species, numerous large-scale EST sequencing projects have been launched successfully, and analysis procedures are constantly being refined to add maximum value to the sequence data. In addition, an alternative approach to exclude repetitive noncoding DNA and to enrich sequence libraries for gene-containing genomic regions has been developed. This strategy has the potential to deliver information about both genes and regulatory regions outside the transcribed regions.     

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。     

Wheat EST sequence assembly facilitates comparison of gene contents among plant species and discovery of novel genes.

Using a strategy requiring only modest computational resources, wheat expressed sequence tag (EST) sequences from various sources were assembled into contigs and compared with a nonredundant barley sequence assembly, with ESTs, with complete draft genome sequences of rice and Arabidopsis thaliana, and with ESTs from other plant species. These comparisons indicate that (i) wheat sequences available from public sources represent a substantial proportion of the diversity of wheat coding sequences, (ii) prediction of open reading frames in the whole genome sequence improves when supplemented with EST information from other species, (iii) a substantial number of candidates for novel genes that are unique to wheat or related species can be identified, and (iv) a smaller number of genes can be identified that are common to monocots and dicots but absent from Arabidopsis. The sequences in the last group may have been lost from Arabidopsis after descendance from a common ancestor. Examples of potential novel wheat genes and Triticeae-specific genes are presented.     

Large-scale sequencing of plant genomes

The large number of ESTs generated for Arabidopsis and rice in recent years now act as an important complement to whole genome sequencing projects. The Arabidopsis Genome Initiative has begun a coordinated effort to sequence the entire genome and, as a result, increasing numbers of large sequence entries can be found in the public databases. In addition, the mitochondrial genome of Arabidopsis has been completely sequenced. Genome sequencing studies and the public sequence databases have begun to influence the direction of diverse areas of research from physiology to evolution.     

应用生物信息学技术对植物表达序列标签(EST)的大规模分析

目前 ,一些基因组较小的植物 (如拟南芥 ,水稻等 )的全基因组已经基本完成测序 ,较大基因组的测序工作则主要集中在基因组中表达基因的测序上 ,表达序列标签 (EST)计划由此产生。研究表明 ,对EST进行大规模研究已成为功能基因组学研究的最佳途经之一。本文着重介绍和讨论应用生物信息学技术对植物EST数据的大规模分析。     

EST分析技术在鸡基因组学研究中的应用

表达序列标签（EST）是由大量随机取出的cDNA库克隆经测序得到的组织或细胞基因组的一段cDNA序列,一个EST代表生物体某种组织某一时期的一个表达基因。综述了EST分析技术在鸡基因组研究中的应用。如用于鉴定、发现和预测鸡的新基因,用于基因图谱的绘制,用于筛选基因的单核苷酸多态性（SNP）位点,用于基因表达分析和基因芯片制作等。EST数据库和生物信息学的联合分析技术在推动家鸡后基因组的研究中发挥着重要的作用。     

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member of the (multi)gene families present and the metabolic networks that are operative. Additionally, one key to identifying physiological functions for many of these (and other) unknown genes, and their corresponding metabolic networks, awaits the development of technologies to comprehensively study molecular processes at the single cell level in particular tissues and organs, in order to establish the actual metabolic context.     

Gene identification in novel eukaryotic genomes by self-training algorithm

Finding new protein-coding genes is one of the most important goals of eukaryotic genome sequencing projects. However, genomic organization of novel eukaryotic genomes is diverse and ab initio gene finding tools tuned up for previously studied species are rarely suitable for efficacious gene hunting in DNA sequences of a new genome. Gene identification methods based on cDNA and expressed sequence tag (EST) mapping to genomic DNA or those using alignments to closely related genomes rely either on existence of abundant cDNA and EST data and/or availability on reference genomes. Conventional statistical ab initio methods require large training sets of validated genes for estimating gene model parameters. In practice, neither one of these types of data may be available in sufficient amount until rather late stages of the novel genome sequencing. Nevertheless, we have shown that gene finding in eukaryotic genomes could be carried out in parallel with statistical models estimation directly from yet anonymous genomic DNA. The suggested method of parallelization of gene prediction with the model parameters estimation follows the path of the iterative Viterbi training. Rounds of genomic sequence labeling into coding and non-coding regions are followed by the rounds of model parameters estimation. Several dynamically changing restrictions on the possible range of model parameters are added to filter out fluctuations in the initial steps of the algorithm that could redirect the iteration process away from the biologically relevant point in parameter space. Tests on well-studied eukaryotic genomes have shown that the new method performs comparably or better than conventional methods where the supervised model training precedes the gene prediction step. Several novel genomes have been analyzed and biologically interesting findings are discussed. Thus, a self-training algorithm that had been assumed feasible only for prokaryotic genomes has now been developed for ab initio eukaryotic gene identification.     

Mapping multiple co-sequenced T-DNA integration sites within the Arabidopsis genome

MOTIVATION: Insertion mutagenesis, using transgenes or endogenous transposons, is a popular method for generating null mutations (knockouts) in model organisms. Insertions are mapped to specific genes by amplifying (via TAIL-PCR) and sequencing genomic regions flanking the inserted DNA. The presence of multiple TAIL-PCR templates in one sequencing reaction results in chimeric sequence of intermittently low quality. Standard processing of this sequence by applying Phred quality requirements results in loss of informative sequence, whereas not trimming low-quality sequence causes inclusion of low-complexity homopolymers from the ends of sequence runs. Accurate mapping of the flanking sequences is complicated by the presence of gene families. RESULTS: Methods for extracting informative regions from sequence traces obtained by sequencing multiple TAIL-PCR fragments in a single reaction are described. The completely sequenced Arabidopsis genome was used to identify informative TAIL-PCR sequence regions. Methods were devised to define and select high quality matches and precisely map each insert to the correct genome location. These methods were used to analyze sequence of TAIL-PCR-amplified flanking regions of the inserts from individual plants in a T-DNA-mutagenized population of Arabidopsis thaliana, and are applicable to similar situations where a reference genome can be used to extract information from poor-quality sequence.