We describe an ontology for cell types that covers the prokaryotic, fungal, animal and plant worlds. It includes over 680 cell types. These cell types are classified under several generic categories and are organized as a directed acyclic graph. The ontology is available in the formats adopted by the Open Biological Ontologies umbrella and is designed to be used in the context of model organism genome and other biological databases. The ontology is freely available at http://obo.sourceforge.net/ and can be viewed using standard ontology visualization tools such as OBO-Edit and COBrA.

In flowering plants, repression of the seed maturation program is essential for the transition from the seed to the vegetative phase, but the underlying mechanisms remain poorly understood. The B3-domain protein VIVIPAROUS1/ABSCISIC ACID-INSENSITIVE3-LIKE 1 (VAL1) is involved in repressing the seed maturation program. Here we uncovered a molecular network triggered by the plant hormone brassinosteroid (BR) that inhibits the seed maturation program during the seedto-seedling transition in Arabidopsis (Arabidopsis thaliana). val1-2 mutant seedlings treated with a BR biosynthesis inhibitor form embryonic structures, whereas BR signaling gain-of-function mutations rescue the embryonic structure trait. Furthermore, the BR-activated transcription factors BRI1-EMS-SUPPRESSOR 1 and BRASSINAZOLE-RESISTANT 1 bind directly to the promoter of AGAMOUS-LIKE15 (AGL15), which encodes a transcription factor involved in activating the seed maturation program, and suppress its expression. Genetic analysis indicated that BR signaling is epistatic to AGL15 and represses the seed maturation program by downregulating AGL15. Finally, we showed that the BR-mediated pathway functions synergistically with the VAL1/2-mediated pathway to ensure the full repression of the seed maturation program. Together, our work uncovered a mechanism underlying the suppression of the seed maturation program, shedding light on how BR promotes seedling growth.

The Arabidopsis Information Resource (TAIR; http://www.arabidopsis.org) is a comprehensive Web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene expression, mutant phenotypes, biological materials such as DNA and seed stocks, genetic markers, genetic and physical maps, biochemical pathways, genome organization, images of mutant plants and protein sub-cellular localizations, publications, and the research community Data in TAIR are extensively interconnected and can be accessed through a variety of Web-based search and display tools. This unit primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes. Gene expression data from microarrays is a recent addition to the database and methods for accessing these data are also described. Two pattern identification programs are described for mining TAIR's unique Arabidopsis sequence data sets. We also describe how to use AraCyc for mining plant metabolic pathways.

Isotopically dimethyl labeling was applied in a quantitative post-translational modification (PTM) proteomic study of phosphoproteomic changes in the drought responses of two contrasting soybean cultivars. A total of 9457 phosphopeptides were identified subsequently, corresponding to 4571 phosphoprotein groups and 3889 leading phosphoproteins, which contained nine kinase families consisting of 279 kinases. These phosphoproteins contained a total of 8087 phosphosites, 6106 of which were newly identified and constituted 54% of the current soybean phosphosite repository. These phosphosites were converted into the highly conserved kinase docking sites by bioinformatics analysis, which predicted six kinase families that matched with those newly found nine kinase families. The overly post-translationally modified proteins (OPP) occupies 2.1% of these leading phosphoproteins. Most of these OPPs are photoreceptors, mRNA-, histone-, and phospholipidbinding proteins, as well as protein kinase/phosphatases. The subgroup population distribution of phosphoproteins over the number of phosphosites of phosphoproteins follows the exponential decay law, Y = 4.13e(-0.)(098X)_ 0.04. Out of 218 significantly regulated unique phosphopeptide groups, 188 phosphoproteins were regulated by the drought-tolerant cultivar under the water loss condition. These significantly regulated phosphoproteins (SRP) are mainly enriched in the biological functions of water transport and deprivation, methionine metabolic processes, photosynthesis/light reaction, and response to cadmium ion, osmotic stress, and ABA response. Seventeen and 15 SRPs are protein kinases/phosphatases and transcription factors, respectively. Bioinformatics analysis again revealed that three members of the calcium dependent protein kinase family (CAMK family), GmSRK2I, GmCIPK25, and GmAKIN beta 1 kinases, constitute a phosphor-relay-mediated signal transduction network, regulating ion channel activities and many nuclear events in this drought-tolerant cultivar, which presumably contributes to the development of the soybean drought tolerance under water deprivation process.

MetaCyc ( http:// metacyc. org) contains experimentally determined biochemical pathways to be used as a reference database for metabolism. In conjunction with the Pathway Tools software, MetaCyc can be used to computationally predict the metabolic pathway complement of an annotated genome. To increase the breadth of pathways and enzymes, more than 60 plant- specific pathways have been added or updated in MetaCyc recently. In contrast to MetaCyc, which contains metabolic data for a wide range of organisms, AraCyc is a species- specific database containing only enzymes and pathways found in the model plant Arabidopsis ( Arabidopsis thaliana). AraCyc ( http:// arabidopsis. org/ tools/ aracyc/) was the first computationally predicted plant metabolism database derived from MetaCyc. Since its initial computational build, AraCyc has been under continued curation to enhance data quality and to increase breadth of pathway coverage. Twenty- eight pathways have been manually curated from the literature recently. Pathway predictions in AraCyc have also been recently updated with the latest functional annotations of Arabidopsis genes that use controlled vocabulary and literature evidence. AraCyc currently features 1,418 unique genes mapped onto 204 pathways with 1,156 literature citations. The Omics Viewer, a user data visualization and analysis tool, allows a list of genes, enzymes, or metabolites with experimental values to be painted on a diagram of the full pathway map of AraCyc. Other recent enhancements to both MetaCyc and AraCyc include implementation of an evidence ontology, which has been used to provide information on data quality, expansion of the secondary metabolism node of the pathway ontology to accommodate curation of secondary metabolic pathways, and enhancement of the cellular component ontology for storing and displaying enzyme and pathway locations within subcellular compartments.

Metabolic labeling using stable isotopes is widely used for the relative quantification of proteins in proteomic studies. In plants, metabolic labeling using N-15 has great potential, but the associated complexity of data analysis has limited its usage. Here, we present the N-15 stable-isotope labeled protein quantification workflow utilizing open-access web-based software Protein Prospector. Further, we discuss several important features of N-15 labeling required to make reliable and precise protein quantification. These features include ratio adjustment based on labeling efficiency, median and interquartile range for protein ratios, isotope cluster pattern matching to flag incorrect monoisotopic peak assignment, and caching of quantification results for fast retrieval.

We present a novel approach to deriving stellar labels for stars observed in MUSE fields making use of data-driven machine learning methods. Taking advantage of the comparable spectral properties (resolution and wavelength coverage) of the LAMOST and MUSE instruments, we adopt the data-driven Payne (DD-Payne) model used on LAMOST observations and apply it to stars observed in MUSE fields. Remarkably, in spite of instrumental differences, according to the cross-validation of 27 LAMOST-MUSE common stars, we are able to determine stellar labels with precision better than 75K in T-eff, 0.15 dex in log g, and 0.1 dex in abundances of [Fe/H], [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe], and [Cr/Fe] for current MUSE observations over a parameter range of 3800 < T-eff < 7000 K, -1.5 < [Fe/H] < 0.5 dex. To date, MUSE has been used to target 13 000 fields across the southern sky since it was first commissioned 6 yr ago and it is unique in its ability to study dense star fields such as globular clusters or the Milky Way bulge. Our method will enable the automated determination of stellar parameters for all stars in these fields. Additionally, it opens the door for applications to data collected by other spectrographs having resolution similar to LAMOST. With the upcoming BlueMUSE and MAVIS, we will gain access to a whole new range of chemical abundances with higher precision, especially critical s-process elements, such as [Y/Fe] and [Ba/Fe], that provide key age diagnostics for stellar targets.

Here, we present PatMatch, an efficient, web-based pattern-matching program that enables searches for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences. The program can be used to find matches to a user-specified sequence pattern that can be described using ambiguous sequence codes and a powerful and flexible pattern syntax based on regular expressions. A recent upgrade has improved performance and now supports both mismatches and wildcards in a single pattern. This enhancement has been achieved by replacing the previous searching algorithm, scan_for_ matches [D'Souza et al. ( 1997), Trends in Genetics, 13, 497-498], with nondeterministic-reverse grep ( NR- grep), a general pattern matching tool that allows for approximate string matching [Navarro ( 2001), Software Practice and Experience, 31, 1265-1312]. We have tailored NR- grep to be used for DNA and protein searches with PatMatch. The stand-alone version of the software can be adapted for use with any sequence dataset and is available for download at The Arabidopsis Information Resource (TAIR) at ftp://ftp.arabidopsis.org/home/ tair/ Software/ Patmatch/. The PatMatch server is available on the web at http://www.arabidopsis.org/cgi-bin/patmatch/ nph-patmatch.pl for searching Arabidopsis thaliana sequences.

Hundreds of leucine-rich repeat receptor kinases (LRR-RKs) have evolved to control diverse processes of growth, development and immunity in plants, but the mechanisms that link LRR-RKs to distinct cellular responses are not understood. Here we show that two LRR-RKs, the brassinosteroid hormone receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1) and the flagellin receptor FLAGELLIN SENSING 2 (FLS2), regulate downstream glycogen synthase kinase 3 (GSK3) and mitogen-activated protein (MAP) kinases, respectively, through phosphocoding of the BRI1-SUPPRESSOR1 (BSU1) phosphatase. BSU1 was previously identified as a component that inactivates GSK3s in the BRI1 pathway. We surprisingly found that the loss of the BSU1 family phosphatases activates effector-triggered immunity and impairs flagellin-triggered MAP kinase activation and immunity. The flagellin-activated BOTRYTIS-INDUCED KINASE 1 (BIK1) phosphorylates BSU1 at serine 251. Mutation of serine 251 reduces BSU1's ability to mediate flagellin-induced MAP kinase activation and immunity, but not its abilities to suppress effector-triggered immunity and interact with GSK3, which is enhanced through the phosphorylation of BSU1 at serine 764 upon brassinosteroid signalling. These results demonstrate that BSU1 plays an essential role in immunity and transduces brassinosteroid-BRI1 and flagellin-FLS2 signals using different phosphorylation sites. Our study illustrates that phosphocoding in shared downstream components provides signalling specificities for diverse plant receptor kinases.