SGD Quarterly Newsletter, Spring 2014
About this newsletter:
This is the Spring 2014 issue of the quarterly SGD newsletter. The goal of this newsletter is to
inform our users about new features in SGD and to foster communication within the yeast community.
You can also subscribe to SGD's RSS feed to receive updates on SGD news:
- 1 Human Disease & Fungal Homologs in YeastMine
- 2 Transcriptome Data in YeastMine
- 3 Explore a Large New Chemogenomics Dataset Via SGD
- 4 Educational Resources on the SGD Community Wiki
- 5 Yeast Researchers Take the Lion's Share of GSA 2014 Awards
- 6 GO Annotation Extension Data, Redesigned GO and Phenotype Pages
- 7 Changes to the SGD GAF File of Gene Ontology Annotations
- 8 Upcoming Meetings
Human Disease & Fungal Homologs in YeastMine
You can now use SGD's advanced search tool, YeastMine, to find the human homolog(s) of your favorite yeast gene and their corresponding disease associations. Or, begin with your favorite human gene or disease keyword and retrieve the yeast counterparts of the relevant gene(s). As an example, you can search for the S. cerevisiae homologs of all human genes associated with disorders that contain the keyword “diabetes” (view search).
We have recently loaded data from OMIM (Online Mendelian Inheritance in Man) into our fast, flexible search resource, YeastMine, and provided 3 predefined queries (templates) that make it simple to perform the above searches. Newly updated HomoloGene, Ensembl, TreeFam, and Panther data sets are used to define the homology between S. cerevisiae and human genes. The results table provides identifiers and standard names for the yeast and human genes, as well as OMIM gene and disease identifiers and names. As with other YeastMine templates, results can be saved as lists and analyzed further. You can also now create a list of human names and/or identifiers using the updated Create Lists feature that allows you to specify the organism representing the genes in your list. The query for yeast homologs can then be made against this list.
In addition to human disease homologs, we have incorporated fungal homolog data for 24 additional species of fungi. You can now query for the fungal homologs of a given S. cerevisiae gene using the template Gene--> Fungal Homologs. This fungal homology data comes from various sources including FungiDB, the "> Candida Gene Order Browser (CGOB) and PomBase, and the results link directly to the corresponding gene pages in the relevant databases, including Candida Genome Database (CGD) and Aspergillus Genome Database (AspGD).
All of the new templates that query human and fungal homolog data can be found on the YeastMine Home page under the new tab "Homology." These templates complement the template Gene--> Non-Fungal and S. cerevisiae Homologs] that retrieves homologs of S. cerevisiae genes in human, rat, mouse, worm, fly, mosquito, and zebrafish.
Transcriptome Data in YeastMine
Towards the goal of compiling datasets to produce a complete transcriptome of yeast (the set of all RNA molecules produced in a single cell or population of cells), we have loaded a defined set of transcripts, based primarily on data from Pelechano, et al, but supported by other datasets, into SGD's flexible search tool, YeastMine. The representative set includes transcripts that Pelechano et al. identified by simultaneous determination of the 5’ and 3’ ends of mRNA molecules whose end coordinates are supported by datasets from other laboratories.
The transcript data can be accessed in YeastMine using the Gene -> Transcripts template, which allows you to specify a gene name or list of gene names and return the list of all associated transcripts based on the collection of data described above. The results include the start and end coordinates for each transcript, the number of counts observed for each transcript in glucose and galactose, notes, and references for the relevant datasets.
Explore a Large New Chemogenomics Dataset Via SGD
What happens when you cross two comprehensive deletion mutant collections with a library of more than 1800 structurally diverse chemicals? HIP HOP happens. Not the music, but a whole lot of very informative phenotype data - over 40 million data points!
The response of S. cerevisiae mutant strains to a chemical can tell us a lot about which pathways or processes the chemical affects. This is not only interesting for yeast biologists, but also has important implications for human molecular biology and disease research. So a group at The Novartis Institutes of Biomedical Research decided to test the sensitivity of nearly 6,000 mutant yeast strains to a panel of about 1,800 compounds.
Hoepfner and colleagues have published these results and have also generously offered them to SGD. They used the HIP and HOP methods (HIP, HaploInsufficiency Profiling, using diploid heterozygous deletion mutant strains; HOP, HOmozygous deletion Profiling, using diploid homozygous deletion mutant strains) that have proven very useful in yeast since the creation of the systematic deletion mutant collections.
To do this mammoth series of experiments they obviously needed to set up an automated pipeline. These sorts of experiments have been done before, but in this study Hoepfner et al. improved on existing procedures in many ways: the physical techniques, the controls and replicates included, and the methods for data analysis.
Phenotype annotations in SGD. We’ve incorporated a subset of these results into SGD as mutant phenotype annotations. Why a subset? Some of the chemicals that were used in these experiments are un-named proprietary compounds, so the individual phenotypes would not be very informative in the context of SGD. We've added the phenotypes that involve named chemicals to SGD - more than 5,500 annotations. These may be viewed on Phenotype Details pages for individual genes (see example), retrieved as a set using YeastMine, or downloaded along with all SGD mutant phenotype annotations in our phenotype data download file.
Easy access to the full dataset and analyses. We've also added a new set of links to SGD that take you directly from your favorite gene to the authors' website, which provides full access to all of the data and interesting ways to look at it (see below). When you click on a "HIP HOP Profile" link from the Locus Summary page or the Phenotype Details page of a gene in SGD, the landing page at the authors' website allows you to explore data for mutants in that gene or for chemicals affecting that mutant strain. You can see which chemicals had the greatest effects, which other mutant strains have a similar range of phenotypes, and much more. And if a chemical that has interesting effects is proprietary, don’t worry; Hoepfner and colleagues have stated that they "encourage future academic collaborations around individual compounds used in this study."
Information about mutant strains. In the course of this study, the authors also generated some very useful data about particular mutant strains in the deletion collection. Some of them were hypersensitive to more than 100 different chemicals. Others turned out to be carrying additional background mutations that could affect the phenotypes of the mutant strain. We are planning to display this kind of information (from this and other studies) directly on SGD Phenotype Details pages in the future.
We thank Dominic Hoepfner and colleagues for sharing these data with SGD and for helping us to incorporate the data. And we encourage you to explore this new resource and contact us with any questions or suggestions.
Educational Resources on the SGD Community Wiki
Did you know you can find and contribute teaching and other educational resources to SGD? We have updated our Educational Resources page, found on the SGD Community Wiki. There are links to teaching resources such as classroom materials, courses, and fun sites, as well as pointers to books, dedicated learning sites, and tutorials that can help you learn more about basic genetics. Many thanks to Dr. Erin Strome and Dr. Bethany Bowling of Northern Kentucky University for being the first to contribute to this updated site by providing a series of Bioinformatics Project Modules designed to introduce undergraduates to using SGD and other bioinformatics resources.
We would like to encourage others to contribute additional teaching or general educational resources to this page. To do so, just request a wiki account by contacting us at the SGD Help Desk - you will then be able to edit the SGD Community Wiki. If you prefer, we would also be happy to assist you directly with these edits.
Note that there are many other types of information you can add to the SGD Community Wiki, including information about your favorite genes, protocols, upcoming meetings, and job postings. The Community Wiki can be accessed from most SGD pages by clicking on "Community" on the main menu bar and selecting "Wiki." The Educational Resources page is linked from the left menu bar under "Resources" from all the SGD Community Wiki pages. For more information on this newly updated page, please view the video Educational Resources on the SGD Community Wiki.
Congratulations to fellow yeasties Angelika Amon, Charlie Boone, and Robin Wright for winning three of the five annual Genetics Society of America awards for 2014! Just another confirmation that the awesome power of yeast genetics attracts excellent researchers...
Angelika Amon, of MIT and the Howard Hughes Medical Institute, has been awarded the Genetics Society of America Medal for outstanding contributions to the field of genetics during the past 15 years. Charlie Boone, of the University of Toronto and a longstanding member of SGD’s Scientific Advisory Board, received the Edward Novitski Prize for his extraordinary level of creativity and intellectual ingenuity in solving significant problems in genetics research. Robin Wright, of the University of Minnesota, has been awarded the Elizabeth W. Jones Award for Excellence in Education, which recognizes significant and sustained impact in genetics education. Find full details about the awards and recipients at the GSA website.
GO Annotation Extension Data, Redesigned GO and Phenotype Pages
Annotation Extension data for select GO annotations are now available at SGD. The Annotation Extension field (also referred to as column 16 after its position in the gene_association file of GO annotations) was introduced by the Gene Ontology Consortium (GOC) to capture details such as substrates of a protein kinase, targets of regulators, or spatial/temporal aspects of processes. The information in this field serves to provide more biological context to the GO annotation. At SGD, these data are accessible for select GO annotations via the small blue 'i' icon on the newly redesigned GO Details pages. See, for example, the substrate information for MEK1 kinase (image below). Currently, a limited number of GO annotations contain data in this field because we have only recently begun to capture this information; more will be added in the future.
We have also redesigned the GO Details and Phenotype Details tab pages to make it easier to understand and make connections within the data. In addition to all of the annotations that were previously displayed, these pages now include graphical summaries, interactive network diagrams displaying relationships between genes and tables that can be sorted, filtered, or downloaded. In addition, SGD Paper pages, each focusing on a particular reference that has been curated in SGD, now show all of the various types of data that are derived from that paper in addition to the list of genes covered in the paper (example). These pages provide seamless access to other tools at SGD such as GO Term Finder, GO Slim Mapper, and YeastMine. Please explore all of these new features from your favorite Locus Summary page and send us your feedback.
Changes to the SGD GAF File of Gene Ontology Annotations
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 Download site.
- Room M106, Alway Building, Stanford University, Stanford, CA
- April 19, 2014
- Gene Transcription in Yeast: from Regulatory Networks to Mechanisms
- Sant Feliu de Guixols, Spain
- June 14-19, 2014
- Steamboat Springs, Colorado
- July 13-16, 2014
- Cold Spring Harbor Labs, Cold Spring Harbor, New York
- July 22 - August 11, 2014
- University of Washington, Seattle, Washington
- July 29 - August 3, 2014
- EMBL Conference
- Frontiers in Fungal Systems Biology
- EMBL Heidelberg, Germany
- September 28-30, 2014
- Vipava and Nova Gorica, Slovenia
- October 9-12, 2014
- EMBL Conference
- Experimental Approaches to Evolution and Ecolgy using Yeast & other Model Systems
- EMBL Heidelberg, Germany
- October 12-15, 2014
*asterisks indicate attendance by SGD
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