枫香叶片变色期全长转录组测序及分析

枫香因其树形优美,入秋后叶色红艳或橙黄,极具观赏价值,是优良的景观生态树种。为了解枫香叶片变色及其次级代谢过程的遗传基础,该文以枫香5个叶片变色期叶片混合样品为材料,利用单分子实时测序技术(PacBio平台)对其进行全长转录组测序。结果表明:(1)全长转录组测序共获得41.04 Gb的高质量数据,从中鉴定出全长非嵌合序列563 180条,通过聚类和去冗余,获得27 269条高质量全长转录本。在27 269条全长转录本中预测到2 035条长链非编码RNA(lncRNA),并检测出14 892个简单重复序列(SSR)位点和1 856个转录因子。(2)基因注释结果表明,NR、GO、COG、KEGG 等8个数据库共注释了24 857条转录本,KEGG数据库共获得了124个条代谢途径,主要有核糖体、碳代谢、氨基酸生物合成等,在类黄酮和叶绿素代谢途径中分别有49和71个转录本参与。上述结果初步揭示了枫香叶片变色期转录组信息以及功能特性,为后续研究枫香叶片变色分子机制、色素代谢合成途径和调控、相关功能基因克隆以及叶色改良提供基础数据。     

YPED:An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database(YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a singlelaboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry(LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring(MRM)/selective reaction monitoring(SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.     

Predicting stable functional peptides from the intergenic space of E. coli

Expression of synthetic proteins from intergenic regions of E. coli and their functional association was recently demonstrated (Dhar et al. in J Biol Eng 3:2, 2009. doi:10.1186/1754-1611-3-2). This gave birth to the question: if one can make ‘user-defined’ genes from non-coding genome—how big is the artificially translatable genome? (Dinger et al. in PLoS Comput Biol 4, 2008; Frith et al. in RNA Biol 3(1):40–48, 2006a; Frith et al. in PLoS Genet 2(4):e52, 2006b). To answer this question, we performed a bioinformatics study of all reported E. coli intergenic sequences, in search of novel peptides and proteins, unexpressed by nature. Overall, 2500 E. coli intergenic sequences were computationally translated into ‘protein sequence equivalents’ and matched against all known proteins. Sequences that did not show any resemblance were used for building a comprehensive profile in terms of their structure, function, localization, interactions, stability so on. A total of 362 protein sequences showed evidence of stable tertiary conformations encoded by the intergenic sequences of E. coli genome. Experimental studies are underway to confirm some of the key predictions. This study points to a vast untapped repository of functional molecules lying undiscovered in the non-expressed genome of various organisms.     

tsORFdb: Theoretical Small Open Reading Frames (ORFs) database and massProphet: Peptide Mass Fingerprinting (PMF) tool for unknown small functional ORFs

Peptide mass fingerprinting (PMF) has become one of the most widely used methods for rapid identification of proteins in proteomics research. Many peaks, however, remain unassigned after PMF analysis, partly because of post-translational modification and the limited scope of protein sequences. Almost all PMF tools employ only known or predicted protein sequences and do not include open reading frames (ORFs) in the genome, which eliminates the chance of finding novel functional peptides. Unlike most tools that search protein sequences from known coding sequences, the tool we developed uses a database for theoretical small ORFs (tsORFs) and a PMF application using a tsORFs database (tsORFdb). The tsORFdb is a database for ORFeome that encompasses all potential tsORFs derived from whole genome sequences as well as the predicted ones. The massProphet system tries to extend the search scope to include the ORFeome using the tsORFdb. The tsORFdb and massProphet should be useful for proteomics research to give information about unknown small ORFs as well as predicted and registered proteins.     

Using reaction mechanism to measure enzyme similarity

The concept of reaction similarity has been well studied in terms of the overall transformation associated with a reaction, but not in terms of mechanism. We present the first method to give a quantitative measure of the similarity of reactions based upon their explicit mechanisms. Two approaches are presented to measure the similarity between individual steps of mechanisms: a fingerprint-based approach that incorporates relevant information on each mechanistic step; and an approach based only on bond formation, cleavage and changes in order. The overall similarity for two reaction mechanisms is then calculated using the Needleman-Wunsch alignment algorithm. An analysis of MACiE, a database of enzyme mechanisms, using our measure of similarity identifies some examples of convergent evolution of chemical mechanisms. In many cases, mechanism similarity is not reflected by similarity according to the EC system of enzyme classification. In particular, little mechanistic information is conveyed by the class level of the EC system.     

籼稻'93-11'一段基因组序列的完善及分析

超级杂交稻父本‘93-11＇的基因组序列测定的完成,为进行作物遗传改良和不同作物之间的比较基因组学研究提供了又一重要序列资源.但是,该基因组序列中还存在很多“缺口”,为使‘93-11＇的基因组序列更加精确,同时提供一些“缺口”填补策略和方法,本研究采用PCR扩增、回收克隆测序的方法对该基因组中一段长约160 kb、含有6个“缺口”的基因组序列进行了完善,并运用相关分子生物学和生物信息学软件进行了详细分析,结果表明：该6个“缺口”中,存在1个“缺口”估计错误,2个序列拼接错误;“缺口”主要位于非编码区,位于编码区的只有1个,其改变了对本处基因的注释,使此基因由原来的9个外显子增加为11个;填补“缺口”后,基因密度增加.     

An automated protein annotation filter for integrating web-based annotation tools

A wide range of web based prediction and annotation tools are frequently used for determining protein function from sequence. However, parallel processing of sequences for annotation through web tools is not possible due to several constraints in functional programming for multiple queries. Here, we propose the development of APAF as an automated protein annotation filter to overcome some of these difficulties through an integrated approach.     

Long‐term datasets: From descriptive to predictive data using ecoinformatics

This Special Feature includes contributions on data‐processing of large ecological datasets under the heading ecoinformatics. Herewith the latter term is now al so established in the Journal of Vegetation Science. Ecoinfomatics is introduced as a rapid growing field within community ecology which is generating exciting new developments in ecology and in particular vegetation ecology. In our field, ecoinformatics deals with the understanding of patterns of species distributions at local and regional scales, and on the assemblages of species in relation to their properties, the local environment and their distribution in the region. Community ecology using ecoinformatics is related to bioinformatics, community ecology, biogeography and macroecology. We make clear how ecoinformatics in vegetation science and particularly the IAVS Working Group on Ecoinformatics has developed from the work of the old Working Group for Data Processing which was active during the 1970s and 1980s. Recent developments, including the creation of TURBOVEG and Syn Bio Sys in Europa and VEGBANK in the USA, form a direct link with these pioneer activities, both scientifically and personally. The contributions collected in this Special Feature present examples of seco‐infeveral types of the use of databases and the application of programmes and models. The main types are the study of long‐term vegetation dynamics in different cases of primary and secondary succession and the understanding of successional developments in terms of species traits. Among the future developments of great significance we mention the use of a variety of different large datasets for the study of the distribution and ecology and conservation of rare and threatened species.