New & Noteworthy

Updated Genome Browser

March 27, 2016


In an effort to provide a comprehensive view of sequence-based functional elements in Saccharomyces cerevisiae, we have upgraded our genome browser, and added new data tracks, to allow users to quickly and easily browse the information-rich yeast genome. We invite authors to work with us to integrate published data into our new JBrowse genome viewer pre- and/or post-publication. Please contact us if you are interested in participating or have questions and comments. Watch for the regular addition of new tracks to SGD’s JBrowse in the future!

Take a look at our newest video tutorial to get acquainted with JBrowse, and let us know if you have any questions or suggestions.

For more SGD Help Videos, visit our YouTube channel, and be sure to subscribe so you don’t miss anything!

Categories: Data updates Website changes

Reference Genome Annotation Update R64.2.1

February 23, 2015

SGD curators periodically update the chromosomal annotations of the S. cerevisiae Reference Genome, which is derived from strain S288C. Last November, the genome annotation was updated for the first time since the release of the major S288C resequencing update in February 2011. Note that the underlying sequence of 16 assembled nuclear chromosomes, plus the mitochondrial genome, remained unchanged in annotation release R64.2.1 (relative to genome sequence release R64.1.1).

The R64.2.1 annotation release included various updates and additions. The annotations of 2 existing proteins changed (GRX3/YDR098C and HOP2/YGL033W), and 1 new ORF (RDT1/YCL054W-A) and 4 RNAs (RME2, RME3, IRT1, ZOD1) were added to the genome annotation. Other additions include 8 nuclear matrix attachment sites, and 8 mitochondrial origins of replication. The coordinates of many autonomously replicating sequences (ARS) were updated, and many new ARS consensus sequences were added. Complete details can be found in the Summary of Chromosome Sequence and Annotation Updates.

Categories: New Data Data updates Sequence

New Protein Modification and Abundance Data in YeastMine

December 17, 2014

Have you ever wondered what’s happening to your favorite protein as it’s hanging out in the cell? SGD’s advanced search tool, YeastMine, now includes four new templates that can be used to find protein modification and abundance data.

The Gene -> Protein Modifications template retrieves phosphorylation, ubiquitination, succinylation, acetylation and methylation data, currently curated from the following 11 publications: Peng et al. 2003, Hitchcock et al. 2003, Seyfried et al. 2008, Vogtle et al. 2009, Ziv et al. 2011, Mommen et al. 2012, Henriksen et al. 2012, Swaney et al. 2013, Kolawa et al. 2013, Weinert et al. 2013, and Wang et al. 2014.

The Gene -> Experimental N-termini and N-terminal modifications template retrieves experimentally-determined amino-terminal sequence and acetylation data, currently curated from Vogtle et al. 2009 and Mommen et al. 2012.

Lastly, two new templates pull protein abundance data curated from Ghaemmaghami et al. 2003. Gene -> Protein Abundance retrieves molecules/cell counts for a gene or list of genes. The same data can be quickly filtered using the Retrieve -> Proteins in a given molecules/cell abundance range template.

Please explore these new YeastMine protein data templates, and send us your feedback.

Categories: New Data Data updates

New Alternative Reference Genomes

December 08, 2014

At SGD, we are expanding our scope to provide annotation and comparative analyses of all major budding yeast strains, and are making progress in our move toward providing multiple reference genomes. To this end, the following new S. cerevisiae genomes have been incorporated into SGD as “Alternative References”: CEN.PK, D273-10B, FL100, JK9-3d, RM11-1a, SEY6210, SK1, Sigma1278b, W303, X2180-1A, Y55. These genomes are accessible via Sequence, Strain, and Contig pages, and are the genomes for which we have curated the most phenotype data, and for which we aim to curate specific functional information. It is important to emphasize that we are not abandoning a standard sequence; S288C is still in place as “The Reference Genome”. However, we do recognize that it is helpful for students and researchers to be able to ‘shift the reference’, selecting the genome that is most appropriate and informative for a specific area of study.

These new genome sequences have been also been added to SGD’s BLAST datasets, multiple sequence alignments, the Pattern Matching tool, and the Downloads site. Please explore these new genomes, and send us your feedback.

Categories: New Data Data updates Sequence

Tags: strains , Saccharomyces cerevisiae , reference genome

New Sequence, Chromosome, and Contig pages

August 25, 2014

New Sequence pages are now available in SGD for virtually every yeast gene (e.g., HMRA1 Sequence page), and include genomic sequence annotations for the Reference Strain S288C, as well as several Alternative Reference Genomes from strains such as CEN.PK, RM11-1a, Sigma1278b, and W303 (more Alternative References coming soon). Each page includes an Overview section containing descriptive information, maps depicting genomic context in Reference Strain S288C (as shown below) and Alternative Reference strains, as well as chromosomal and relative coordinates in S288C.

The sequence itself includes display options for genomic DNA, coding DNA, or translated protein.

Also available on each Sequence page are links to redesigned S288C Chromosome pages, links to new Contig pages for Alternative Reference Genomes, and a Downloads menu for easy access to DNA sequences of several other industrial strains and environmental isolates. The new Sequence, Chromosome, and Contig pages make use of many of the features you enjoy on other new or redesigned pages at SGD, including graphical display of data, sortable tables, and responsive visualizations. The Sequence pages also provide seamless access to other tools at SGD such as BLAST and Web Primer. Please explore these new pages, accessible via the Sequence tab on your favorite Locus Summary page, and send us your feedback.

Categories: Website changes New Data Data updates Sequence

Changes to the SGD GAF File of Gene Ontology Annotations

March 11, 2014

The SGD Gene Associations file (GAF; gene_association.sgd) contains Gene Ontology (GO) annotations for all yeast genes, in a standard file format specified by the GO Consortium. We are changing the taxon identifier in this file to be consistent with the reference genome sequence at GenBank and protein entries at UniProt.

Until now, the taxon identifier in column 13 of SGD’s GAF has been 4932, which refers to Saccharomyces cerevisiae in general rather than to a specific S. cerevisiae strain. Starting March 8th, 2014, we have changed this to taxon ID 559292, which is specific to the S288C strain used for the S. cerevisiae reference genome sequence.

Please note that the taxon ID 559292 merely reflects the sequence (genome) to which the geneIDs in column 2 are mapped. SGD will continue to capture gene functions (GO annotations) for all strains of S. cerevisiae. Please contact us if you have any questions.
The S. cerevisiae GO annotations (GAF) can be downloaded from SGD’s Downloads site.

Categories: Data updates

YeastMine Upgrade

May 28, 2013

YeastMine, SGD’s powerful search and retrieval tool, has been upgraded to use InterMine version 1.1 software. Highlights of this release include a new format for the template results page, the addition of PantherDB and Homologene homolog data, an improved representation of Gene Ontology (GO) information, the ability to set background population within the GO enrichment widget, and an option to share lists with other users. In addition to the existing video tutorials, a new Help document describes some common queries. See an overview of these new features in the video below, New, Fun YeastMine 1.1!:

New, Fun YeastMine 1.1! from yeastgenome on Vimeo.

Categories: New Data Data updates

Take SGD with you wherever you go!

May 07, 2012

The YeastGeome app splash screen on an iPad.

SGD has just released an app for the iPhone, iPad and iPod touch ap(p)tly called “YeastGenome”, containing the latest Saccharomyces cerevisiae information from the database, available now as a free download on iTunes. Search by gene names, gene descriptions or simply browse for quick access to Gene Ontology annotations, mutant phenotypes and protein and genetic interaction data for your favorite genes – all at your fingertips!

Use YeastGenome to:

  • Search using gene name or keywords
  • Browse by genomic feature types
  • Save your favorite genomic features
  • Quickly see fundamental genomic feature information
  • Find Gene Ontology terms, Phenotypes, Interactions, and References associated with genomic features

… with or without an internet connection!

How many ATP-dependent RNA helicases is the S. cerevisiae genome known to encode? Which proteins have a zinc finger motif? Now you can answer these questions and more with the YeastGenome app, whether you’re in line at the supermarket or having lunch with your colleagues or attending a seminar with no wifi-access! Get your friends and colleagues as fired up about The Awesome Power of Yeast as you are – use YeastGenome to email information about genomic features to collaborators and spread the word!

Please read our FAQ or visit iTunes for more information.

Categories: Data updates

Tags: iPad , iPod , iPhone

Filter Expression Data by Experimental Condition

December 16, 2011

Expression analysis at SGD now offers the ability to filter datasets by condition(s) or process(es) studied. A set of controlled vocabulary (CV) terms describing various perturbations associated with microarray experiments has been constructed and defined, and these terms have been used to tag the comprehensive collection of almost 400 datasets now available in SGD’s instance of SPELL (Serial Pattern of Expression Levels Locator). In this manner, datasets displayed in search results can be filtered using tags (CV terms) such as “oxidative stress” or “sporulation.” Filtering is an option for the “New Search,” “Show Expression Levels,” and “Dataset Listing” features. The SPELL interface has been provided through a collaboration with the SGD Colony at Princeton University. Special thanks to Peter Koppstein, Lance Parsons, and Kara Dolinski for help in implementing the dataset tag filtering option for SPELL at SGD.

Categories: Data updates Website changes

GO Slims Updated

August 12, 2011

SGD has updated its Yeast Molecular Function and Biological Process GO Slims to include additional terms. The Yeast GO Slims are a set of GO terms that best represent the major biological processes, molecular functions, and cellular components that are found in S. cerevisiae. GO Slim terms are useful in mapping precise, “granular” gene annotations to more general “high-level” terms. These terms have been selected by SGD curators based on annotation statistics and biological significance. To complement the expanded Yeast GO Slims, we have also added “generic GO-Slim” options to our GO Slim Mapper tool. The generic GO-Slim is developed and maintained by the Gene Ontology Consortium and includes fewer and higher-level terms than those provided by the Yeast GO-Slim.

The Yeast GO Slims are available for analysis via the GO Slim Mapper tool and YeastMine. Mapping of all the yeast gene products to the Yeast GO Slims is also available as a graphical view on the Genome Snapshot page and via the go_slim_mapping.tab file on the downloads site.

Categories: Data updates

Textpresso now includes publications from 2011

June 21, 2011

The SGD full-text literature search (powered by Textpresso) has been upgraded and updated to include 58,000 papers. Textpresso now includes the ability to restrict your searches to a subset of PMIDs as well as limit the results to a specific section of a paper. The full-text literature search can be accessed via the Full-text Search link on the home page. Thanks to Arun Rangarajan and Hans-Michael Muller from Wormbase for their help upgrading the software.

Categories: Data updates

New Genome-wide High-throughput Data Tracks Added to GBrowse and PBrowse

June 09, 2011

We’ve added new data tracks to our GBrowse genome viewer from eight publications, including recent surveys of nucleosome occupancy and positioning (Kaplan et al., 2009; Field et al., 2008; Mavrich et al., 2008; Lee et al., 2007); ncRNAs and RNA secondary structures (Lardenois et al., 2011 and Kertesz et al., 2010); and transcription factor and RNA Pol II occupancy (Venters et al., 2011 and Mayer et al., 2010). We have also added a data track to our Pbrowse proteome browser, displaying mature N-termini of mitochondrial proteins as determined by Vögtle et al., 2009. Both GBrowse and PBrowse have been upgraded to the most recent software with several new features.
We invite authors to work with us to integrate their data into our GBrowse and PBrowse viewers pre- and/or post-publication as we move forward. Watch for the regular addition of new tracks to SGD’s GBrowse and PBrowse in the future! Please contact us if you are interested in participating or have questions and comments.

Categories: New Data Data updates

New Expression Analysis Tool and Datasets

February 23, 2011

Expression analysis at SGD has a new powerful interface and many new datasets. The new interface uses a tool called SPELL (Serial Pattern of Expression Levels Locator). This analysis tool facilitates the rapid identification of the most informative datasets and co-expressed genes based on patterns of expression shared with the query gene(s). By transitioning to this tool, expression data from a comprehensive collection of almost 400 datasets are now available at SGD. The expression analysis tool can be accessed via the expression tab, the expression summary histogram, and in the functional analysis pulldown located on Locus Summary pages. These new data and the SPELL interface have been provided through a collaboration with the SGD Colony at Princeton University. Thanks to Peter Koppstein, Lance Parsons, and Kara Dolinski for help with data preparation and implementation of SPELL at SGD. SPELL was developed by the Troyanskaya lab at Princeton University (Hibbs et al. (2007) Bioinformatics 23:2692).

Categories: Data updates Website changes

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