Moringa leaf and flower transcriptome as a genomic resource database for gene and pathway identification
Ontology highlight
ABSTRACT:
INSTRUMENT(S): HiSeq X Ten
ORGANISM(S): Moringa oleifera
SUBMITTER: PARIMALAN RANGAN
PROVIDER: E-MTAB-8460 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:ARABIDOPSIS SKP1-LIKE1 (ASK1) protein is involved in regulating flower development. We have compared ask1 mutant floral transcriptome with wild-type Ler to identify the role of ASK1-containing E3 ubiquitin ligases in regulating flower transcriptome. In this dataset, we include the expression data obtained from Arabidopsis thaliana Ler and ask1 mutant flower buds. We identified 42 genes and 74 genes that are down-regulated and up-regulated, respectively. Totally 5 samples were analyzed: 3 samples of ask1 and 2 samples of Ler. The average values were compared between ask1 and Ler.
2013-02-01 | E-GEOD-42841 | biostudies-arrayexpress
Project description:Salvia miltiorrhiza has been comprehensively studied as a medicinal model plant. However, research progress on this species is significantly hindered by its unavailable genome sequences and limited number of expressed sequence tags in the National Center for Biotechnology Information database. Thus, a transcript database must be developed to assist researchers to browse, search, and align sequences for gene cloning and functional analysis in S. miltiorrhiza. In this study, the Danshen Transcriptional Resource Database (DsTRD) was built using 76,531 transcribed sequences assembled from 12 RNA-Seq transcriptomes. Among these 12 RNA-seq data, ten were downloaded from NCBI database. The remaining two were enced on the Hiseq2000 platform using the stem and hairy-root of S. miltiorrhiza. The transcripts were annotated as protein-coding RNAs, long non-coding RNAs, microRNA precursors, and phased secondary small-interfering RNA genes through several bioinformatics methods. The tissue expression levels for each transcript were also calculated and presented in terms of RNA-Seq data. Overall, DsTRD facilitates browsing and searching for sequences and functional annotations of S. miltiorrhiza. DsTRD is freely available at http://bi.sky.zstu.edu.cn/DsTRD/home.php.
| S-EPMC4765898 | biostudies-literature
Project description:Moringa leaf and flower transcriptome as a genomic resource database for gene and pathway identification
| PRJEB35044 | ENA
Project description:The long-tailed chinchilla (Chinchilla lanigera) is an established animal model for diseases of the inner and middle ear, among others. In particular, chinchilla is commonly used to study diseases involving viral and bacterial pathogens and polymicrobial infections of the upper respiratory tract and the ear, such as otitis media. The value of the chinchilla as a model for human diseases prompted the sequencing of its genome in 2012 and the more recent development of the Chinchilla Research Resource Database (http://crrd.mcw.edu) to provide investigators with easy access to relevant datasets and software tools to enhance their research. The Chinchilla Research Resource Database contains a complete catalog of genes for chinchilla and, for comparative purposes, human. Chinchilla genes can be viewed in the context of their genomic scaffold positions using the JBrowse genome browser. In contrast to the corresponding records at NCBI, individual gene reports at CRRD include functional annotations for Disease, Gene Ontology (GO) Biological Process, GO Molecular Function, GO Cellular Component and Pathway assigned to chinchilla genes based on annotations from the corresponding human orthologs. Data can be retrieved via keyword and gene-specific searches. Lists of genes with similar functional attributes can be assembled by leveraging the hierarchical structure of the Disease, GO and Pathway vocabularies through the Ontology Search and Browser tool. Such lists can then be further analyzed for commonalities using the Gene Annotator (GA) Tool. All data in the Chinchilla Research Resource Database is freely accessible and downloadable via the CRRD FTP site or using the download functions available in the search and analysis tools. The Chinchilla Research Resource Database is a rich resource for researchers using, or considering the use of, chinchilla as a model for human disease.Database URL: http://crrd.mcw.edu.
| S-EPMC4865329 | biostudies-literature
Project description:Several viruses within the Coronaviridae family have been categorized as either emerging or re-emerging human pathogens, with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) being the most well known. The NIAID-sponsored Virus Pathogen Database and Analysis Resource (ViPR, www.viprbrc.org) supports bioinformatics workflows for a broad range of human virus pathogens and other related viruses, including the entire Coronaviridae family. ViPR provides access to sequence records, gene and protein annotations, immune epitopes, 3D structures, host factor data, and other data types through an intuitive web-based search interface. Records returned from these queries can then be subjected to web-based analyses including: multiple sequence alignment, phylogenetic inference, sequence variation determination, BLAST comparison, and metadata-driven comparative genomics statistical analysis. Additional tools exist to display multiple sequence alignments, view phylogenetic trees, visualize 3D protein structures, transfer existing reference genome annotations to new genomes, and store or share results from any search or analysis within personal private 'Workbench' spaces for future access. All of the data and integrated analysis and visualization tools in ViPR are made available without charge as a service to the Coronaviridae research community to facilitate the research and development of diagnostics, prophylactics, vaccines and therapeutics against these human pathogens.
| S-EPMC3509690 | biostudies-literature
Project description:We present a new release of the immune epitope database analysis resource (IEDB-AR, http://tools.immuneepitope.org), a repository of web-based tools for the prediction and analysis of immune epitopes. New functionalities have been added to most of the previously implemented tools, and a total of eight new tools were added, including two B-cell epitope prediction tools, four T-cell epitope prediction tools and two analysis tools.
| S-EPMC2447801 | biostudies-literature
Project description:Fighting infections and developing novel drugs and vaccines requires advanced knowledge of pathogen's biology. Readily accessible genomic, functional genomic, and population data aids biological and translational discovery. The Eukaryotic Pathogen Database Resources ( http://eupathdb.org ) are data mining resources that support hypothesis driven research by facilitating the discovery of meaningful biological relationships from large volumes of data. The resource encompasses 13 sites that support over 170 species including pathogenic protists, oomycetes, and fungi as well as evolutionarily related nonpathogenic species. EuPathDB integrates preanalyzed data with advanced search capabilities, data visualization, analysis tools and a comprehensive record system in a graphical interface that does not require prior computational skills. This chapter describes guiding concepts common across EuPathDB sites and illustrates the powerful data mining capabilities of some of the available tools and features.
| S-EPMC7124890 | biostudies-literature
Project description:BackgroundMany model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources.ResultsWe report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome.PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.phpConclusionPCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified.
| S-EPMC293463 | biostudies-literature
Project description:BackgroundMedicago truncatula has been chosen as a model species for genomic studies. It is closely related to an important legume, alfalfa. Transporters are a large group of membrane-spanning proteins. They deliver essential nutrients, eject waste products, and assist the cell in sensing environmental conditions by forming a complex system of pumps and channels. Although studies have effectively characterized individual M. truncatula transporters in several databases, until now there has been no available systematic database that includes all transporters in M. truncatula.DescriptionThe M. truncatula transporter database (MTDB) contains comprehensive information on the transporters in M. truncatula. Based on the TransportTP method, we have presented a novel prediction pipeline. A total of 3,665 putative transporters have been annotated based on International Medicago Genome Annotated Group (IMGAG) V3.5 V3 and the M. truncatula Gene Index (MTGI) V10.0 releases and assigned to 162 families according to the transporter classification system. These families were further classified into seven types according to their transport mode and energy coupling mechanism. Extensive annotations referring to each protein were generated, including basic protein function, expressed sequence tag (EST) mapping, genome locus, three-dimensional template prediction, transmembrane segment, and domain annotation. A chromosome distribution map and text-based Basic Local Alignment Search Tools were also created. In addition, we have provided a way to explore the expression of putative M. truncatula transporter genes under stress treatments.ConclusionsIn summary, the MTDB enables the exploration and comparative analysis of putative transporters in M. truncatula. A user-friendly web interface and regular updates make MTDB valuable to researchers in related fields. The MTDB is freely available now to all users at http://bioinformatics.cau.edu.cn/MtTransporter/.
| S-EPMC3298476 | biostudies-literature
Project description:Purpose: The goals of this study are to analyze the transcriptome of five time point in broccoli seed germination and sprout development and to find the putative glucosinolate metabolism genes in the stage. Methods: Total mRNA of germinated seeds, 3 day cotyledons, 7 day botyledons, 11 day cotyledons and 11 day euphyllas of wild-type broccoli were harvested. Each sample was harvested in three independent biological replicates with equal weight and subsequently pooled together for sequencing. The sequence reads that passed quality filters were de novo assembled using VELVET followed by OASES. Then the assembled unigenes were used for the abundance and functional analysis. Results: A total of ~85million 251bp reads were obtained. After de novo assembly and searching the assembled transcripts against the Arabidopsis thaliana and Nr databases, 19,441 top-hit transcripts were clustered as unigenes with an average length of 2,133bp. These unigenes were classified according to their putative functional categories. Cluster analysis of total unigenes with similar expression patterns and differentially expressed unigenes among different tissues,as well as transcription factor analysis were performed. We identified 25 putative glucosinolate metabolismgenes sharing 62.04-89.72% nucleotide sequence identity with the Arabidopsis orthologs. This established a broccoli glucosinolate metabolic pathway with high colinearity to Arabidopsis. Many of the biosynthetic and degradation genes showed higher expression after germination than in seeds; especially the expression of the myrosinaseTGG2 was 20-130 times higher.These results along with the previous reports that glucosinolate concentration decreased exponentially once after germination indicate the breakdown products of glucosinolates may play important roles in broccoli seed germination and sprout development. Conclusion: Our study provides the largest genetic resource of broccoli to date. These data will pave the way for further studies and genetic engineering of broccoli sprouts to develop functional vegetables containing high levels of the anticarcinogenic glucosinolates. They will also provide new insight into the genomic research of this species and its relatives. Wild-type broccoli mRNA profiles of seeds, 3 day cotyledons, 7 day botyledons, 11 day cotyledons and 11 day euphyllas were generated by deep sequencing, three biological replicates pooling together for each tissue, using Illumina Myseq platform.
2014-03-18 | E-GEOD-53298 | biostudies-arrayexpress