December 05, 2019
This is the Fall 2019 issue of the 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.
Contents:
From August 18th-22nd, PI Mike Cherry, Principal Biocuration Scientist Stacia Engel, Senior Biocuration Scientists Barbara Dunn, Edith Wong, and Rob Nash, Biocuration Scientist Suzi Aleksander, Software Developer Felix Gondwe, and Associate Biocuration Scientist Patrick Ng attended the 29th International Conference on Yeast Genetics and Molecular Biology in Gothenburg, Sweden. Our attending staff presented at a workshop and poster sessions at the meeting, and presentation materials are downloadable at the links below. We had a great time interacting with users and getting their feedback on how to improve SGD as a resource for the budding yeast community.
Presenter | Presentation Title |
Mike Cherry | “Introduction to SGD Workshop” |
Stacia Engel | “SGD’s Collaboration with the Alliance of Genome Resources” |
Rob Nash | “Disease Associations and Protein Abundance” |
Edith Wong | “Macromolecular Complexes and Chemical Pages at SGD” |
Suzi Aleksander | “Gene Ontology at SGD: GO Slim Mapper” |
Patrick Ng | “Depicting the S288C Transcriptome at SGD” |
The Alliance of Genome Resources, a collaborative effort from SGD and other model organism databases (MOD), released version 2.3 in November. Notable improvements and new features include:
SGD recently updated the YeastPathways resource, containing more than 200 biochemical pathways, with help from the BioCyc group at SRI to provide an updated web portal and tools. You can query for metabolic network, pathway, enzyme, or metabolites, as well as access pathways from SGD’s Function menu or locus pages for genes with enzymatic roles.
Sequence tracks that depict single nucleotide polymorphisms and small insertion/deletions mapped relative to the reference strain S288C by Song et al. 2015 in 25 S.cerevisiae strains are now viewable in SGD JBrowse. They are accessible from the “variants” category when you click the “Select tracks” tab on the upper-left hand of the page.
We want to take this opportunity to wish you and your family, friends and lab mates the best during the upcoming holidays. Stanford University will be closed for two weeks starting on December 24. Although SGD staff members will be taking time off, the website will be up and running throughout the winter break, and we will resume responding to user requests and questions in the new year.
The Allied Genetics Conference – TAGC 2020
Metro Washington, DC
April 22 to April 26, 2020
15th International Congress on Yeasts
University of Vienna, Vienna, Austria
August 23 to August 27, 2020
The 31st Fungal Genetics Conference
Asilomar Conference Grounds, Pacific Grove, CA
March 09 to March 14, 2021
Categories: Newsletter
August 02, 2019
Did you know that SGD has over 200 curated biochemical pathways for you to explore? SGD’s YeastPathways is a database of metabolic pathways and enzymes in Saccharomyces cerevisiae. YeastPathways enables you to visualize yeast metabolism from large metabolic networks to individual pathways, and from biochemical reactions down to individual metabolites. Search tools and click-to-browse features in YeastPathways enable quick navigation and intuitive exploration of yeast metabolism.
As the first major content update to YeastPathways since 2012, we have recently updated 62 pathways with expertly-curated summaries on pathway biochemistry, genetics, regulation, and more. Compounds that were previously missing a structure have also now been updated, along with the stoichiometry and scheme of many pathway reactions. In addition to content updates, YeastPathways has also received a major software upgrade that provides new tools, pages, and visual aids.
With new content and software, YeastPathways is better than ever. Users new to YeastPathways will find that it’s easy to get started—simply access YeastPathways through the Function menu at SGD, then run a search for a pathway, compound, enzyme, or reaction on the YeastPathways homepage. You can also access YeastPathways through gene pages at SGD. Just run a search for your favorite metabolic enzyme at SGD (example: TPI1) and find the Pathways section on the locus summary page. Any pathways in which the protein is involved will be listed and linked to YeastPathways.
Check out YeastPathways and be sure to contact us if you have any questions or feedback!
Categories: Data updates
June 12, 2019
We are excited to announce that 50 new “Variants” data tracks are now available for use in our genome browsing tool JBrowse. Utilizing whole-genome sequencing data published by Song et al. (2015), these data tracks visualize how the sequences of 25 S. cerevisiae strains differ from that of the reference genome strain, S288C.
Two data tracks are available for each of the 25 strains: a track that indicates single nucleotide polymorphisms (SNPs) relative to strain S288C, and a track that shows insertions or deletions (“indels”) relative to S288C.
Accessing these new data tracks is easy—just enter JBrowse and click on the “Select tracks” tab on the upper-left hand part of the page. Then, select the “variants” category. You can also download the variants, annotation, and sequence files on these strains for use in your own analyses.
If you’re new to JBrowse, don’t miss out—getting started takes no time at all. For information on how to use this tool, be sure to check out the JBrowse playlist on the SGD YouTube Channel or visit the JBrowse help page. If you have any questions or feedback about the new “Variants” data tracks or about our genome browsing tool, please don’t hesitate to contact us.
Table of strains with “Variants” data tracks in JBrowse, along with links to download their respective dataset:
Categories: New Data
June 03, 2019
This is the Spring 2019 issue of the 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.
Contents:
Wednesday, May 8th, marked the 25th year that the SGD website has been live. Although we celebrated the 25th anniversary of the database last year, the actual website wasn’t online until the following year (when the “World Wide Web” had only been in existence for about 22 months). Starting in 1994, you could simply access SacchDB from our old server genome-www.stanford.edu to find information on your favorite model organism. We’d like to express our gratitude to all of our users, collaborators, advisors, staff, and anyone else who has supported SGD over the last 25 years. Without such a great community behind us, SGD would not be the fantastic resource it is today.
SGD staff celebrated the day by taking a tour around the Stanford campus and enjoying the beautiful California spring weather. Did you catch our throwback page for CDC6?
We have recently equipped our genome browsing tool JBrowse with 9 new Transcriptome data tracks, making JBrowse an even more powerful way to explore the vast heterogeneity of the S288C transcriptome. These information-rich data tracks visualize RNA transcripts from the TIF-seq dataset published by Pelechano et al. (2013), enabling quick and easy viewing of the position, length, and abundance of transcript isoforms sequenced in the study.
SGD has also updated our JBrowse with an additional 157 new data tracks related to genome-wide experiments and omics data for you to explore. The categories added include: Transcription & Transcriptional Regulation; Histone Modification; Chromatin Organization; RNA Catabolism; Transposons; DNA Replication, Recombination, and Repair.
SGD has now incorporated proteome-wide protein abundance data obtained from a comprehensive meta-analysis by Ho et al., 2018. The authors normalized and combined 21 different S. cerevisiae protein abundance datasets—including data from both untreated cells and cells treated with various environmental stressors—to create a unified protein abundance dataset where all values are in the intuitive units of molecules per cell. Normalized abundance measurements and associated metadata from untreated and treated cells are displayed in tabular form in the experimental data section of protein-tabbed pages (e.g. CDC28). Several different controlled vocabularies have been employed to standardize the metadata display. In addition, calculated median abundance and median absolute deviation (MAD) values are displayed in the protein section of Locus Summary pages (e.g. PHO85).
Two new YeastMine templates have been created to provide access to these data: Gene → Protein Abundance and Gene → Median Protein Abundance.
In March, the Alliance released version 2.1. The release showcases the combined effort from SGD and the other core Alliance members. Notable improvements and new features include:
From April 7th-10th, PI Mike Cherry, Principal Biocuration Scientist Stacia Engel, Senior Biocuration Scientist Edith Wong, Biocuration Scientist Suzi Aleksander and Software Developer Felix Gondwe attended the International Society for Biocuration’s 12th International Biocuration Conference in Cambridge, UK. Several of our staff presented posters, while Edith also gave a great talk on her recent Database publication: Integration of Macromolecular Complex Data into the Saccharomyces Genome Database. Below are the posters and the talk SGD staff presented at Biocuration 2019. Click on any of the links to download the presentation.
Presenter | Presentation Title |
Edith Wong | “Integration of Macromolecular Complex Data into the Saccharomyces Genome Database” |
Presenter | Poster Title |
Suzi Aleksander | “In the Know About GO: A Newly Redesigned Website for the Gene Ontology” |
Felix Gondwe | “Downloading Data from SGD” |
Edith Wong | “Integration of Macromolecular Complex Data into the Saccharomyces Genome Database” |
You might see some of our SGD members at these upcoming events:
Senior Biocuration Scientist Rob Nash will be conducting a workshop at the annual Yeast Genetics & Genomics course at Cold Spring Harbor Laboratory July 23 – August 12, 2019.
SGD will be attending ICYGMB2019, the 29th International Conference on Yeast Genetics and Molecular Biology in Göteborg, Sweden August 18-22, 2019. If you’re going, be sure to attend the SGD Workshop on the afternoon of Day 4, Wednesday August 21!
Presenter | Poster Title |
Barbara Dunn | “Associating Yeast Genes with Human Disease-related Genes at SGD” |
Kevin MacPherson | “Comparative Genomics at the Saccharomyces Genome Database” |
Categories: Newsletter
April 25, 2019
We have recently equipped our genome browsing tool JBrowse with 9 new Transcriptome data tracks, making JBrowse an even more powerful way to explore the vast heterogeneity of the S288C transcriptome. These information-rich data tracks visualize RNA transcripts from the TIF-seq dataset published by Pelechano et al. (2013), enabling quick and easy viewing of the position, length, and abundance of transcript isoforms sequenced in the study.
You can easily access these new tracks by entering JBrowse and clicking on the left-hand “Select tracks” tab. They are located in the Transcriptome category. In addition to viewing the data in JBrowse, you can also download the .gff3 and .bw files for these tracks for use in your own analyses.
Check out our video tutorial from the SGD YouTube channel at the top of this page for a quick overview of the new transcriptome data tracks and how to access them. More information about these tracks and how SGD created them can also be found on our Genome Browser help page.
If you have any questions or feedback about the new Transcriptome data tracks or about our genome browser, please don’t hesitate to contact us.
Data tracks that visualize transcript isoforms that fully overlap a gene coding region:
Data Track Title | Description |
longest_full-ORF_transcripts_ypd | This track contains the longest transcript overlapping each individual ORF completely for WT cells grown in glucose (ypd) media. |
longest_full-ORF_transcripts_gal | This track contains the longest transcript overlapping each individual ORF completely for WT cells grown in galactose (gal) media. |
most_abundant_full-ORF_transcripts_ypd | This track contains the most abundant transcript overlapping each individual ORF completely for WT cells grown in glucose (ypd) media. |
most_abundant_full-ORF_transcripts_gal | This track contains the most abundant transcript overlapping each individual ORF completely for WT cells grown in galactose (gal) media. |
unfiltered_full-ORF_transcripts | This track contains all transcripts that overlapped individual open reading frame (ORF) completely for WT cells grown in either glucose (ypd) or galactose (gal) media. |
Data tracks that quantify the number of transcripts that cover a given nucleotide in the S288c genome:
Data Track Title | Description |
plus_strand_coverage_ypd | For WT cells grown in glucose media (ypd), the amount of transcripts covering each position on the plus strand is represented in this track. |
plus_strand_coverage_gal | For WT cells grown in galactose media (gal), the amount of transcripts covering each position on the plus strand is represented in this track. |
minus_strand_coverage_ypd | For WT cells grown in glucose media (ypd), the amount of transcripts covering each position on the minus strand is represented in this track. |
minus_strand_coverage_gal | For WT cells grown in galactose media (gal), the amount of transcripts covering each position on the minus strand is represented in this track. |
Categories: New Data, Tutorial
April 04, 2019
The 29th International Conference on Yeast Genetics and Molecular Biology (ICYGMB) will be held at the the Swedish Exhibition & Congress Centre, Gothenburg, Sweden, from August 18-22, 2019.
The ICYGMB brings together scientists from all around the globe to present and discuss cutting-edge research on yeast. Described as the “most important event in yeast research“, the conference facilitates an environment where the international yeast community can freely exchange information, strike collaborations, and build new projects and alliances.
The 2019 meeting is enriched with over 50 speakers and a program that aims to provide an up-to-date overview of the most exciting topics in yeast research. The program includes lectures and workshops that discuss topics such as cell signaling, evolutionary genetics, aging and disease models, yeast biotechnology, and more.
Registration and abstract submission are now open. The early registration deadline has been extended to May 1. The abstract submission deadline is May 15. Special conference rates for accommodation are guaranteed only until June 1.
Categories: Conferences
March 11, 2019
SGD has now incorporated proteome-wide protein abundance data obtained from a comprehensive meta-analysis by Ho et al., 2018. The authors normalized and combined 21 different S. cerevisiae protein abundance datasets—including data from both untreated cells and cells treated with various environmental stressors—to create a unified protein abundance dataset where all values are in the intuitive units of molecules per cell. The original datasets were initially obtained using different methodologies (mass spectrometry, fluorescence microscopy, flow cytometry, and TAP-immunoblot), allowing Ho et al. to evaluate the strengths and weaknesses of these methods in addition to providing the community with a comprehensive reference map of the yeast proteome.
Normalized abundance measurements and associated metadata from untreated and treated cells are displayed in tabular form in the experimental data section of protein-tabbed pages (e.g. CDC28). Several different controlled vocabularies have been employed to standardize the metadata display. In addition, calculated median abundance and median absolute deviation (MAD) values are displayed in the protein section of Locus Summary pages (e.g. PHO85). Two new YeastMine templates have been created to provide access to these data: Gene -> Protein Abundance and Gene -> Median Protein Abundance
Special thanks to Brandon Ho and Grant Brown for generating this comprehensive reference map of protein abundance, and for their help in making this data available to the larger community.
Categories: New Data
March 05, 2019
For almost 50 years, the legendary Yeast Genetics & Genomics course has been taught each summer at Cold Spring Harbor Laboratory. (OK, the name didn’t include “Genomics” in the beginning…). The list of people who have taken the course reads like a Who’s Who of yeast research, including Nobel laureates and many of today’s leading scientists. The application deadline is April 1st, so don’t miss your chance! Find all the details and application form here. This year’s instructors – Grant Brown, Greg Lang, and Elçin Ünal – have designed a course (July 23 – August 12) that provides a comprehensive education in all things yeast, from classical genetics through up-to-the-minute genomics. Students will perform and interpret experiments, learning about things like:
Techniques have been summarized in a completely updated course manual, which was recently published by CSHL Press.
Scientists who aren’t part of large, well-known yeast labs are especially encouraged to apply – for example, professors and instructors who want to incorporate yeast into their undergraduate genetics classrooms; scientists who want to transition from mathematical, computational, or engineering disciplines into bench science; and researchers from small labs or institutions where it would otherwise be difficult to learn the fundamentals of yeast genetics and genomics. Significant stipends (in the 30-50% range of total fees) are available to individuals expressing a need for financial support and who are selected into the course.
Besides its scientific content, the fun and camaraderie at the course is also legendary. In between all the hard work there are late-night chats at the bar and swimming at the beach. There’s a fierce competition between students at the various CSHL courses in the Plate Race, which is a relay in which teams have to carry stacks of 40 Petri dishes (used, of course). There’s also a sailboat trip, a microscopy contest, and a mysterious “Dr. Evil” lab!
The Yeast Genetics & Genomics Course is loads of fun – don’t miss out!
Categories: Announcements
January 24, 2019
The 29th International Conference on Yeast Genetics and Molecular Biology (ICYGMB) will be held at the the Swedish Exhibition & Congress Centre, Gothenburg, Sweden, from August 18-22, 2019.
The ICYGMB brings together scientists from all around the globe to present and discuss cutting-edge research on yeast. Described as the “most important event in yeast research“, the conference facilitates an environment where the international yeast community can freely exchange information, strike collaborations, and build new projects and alliances.
The 2019 meeting is enriched with over 50 speakers and a program that aims to provide an up-to-date overview of the most exciting topics in yeast research. The program includes lectures and workshops that discuss topics such as cell signaling, evolutionary genetics, aging and disease models, yeast biotechnology, and more.
Registration and abstract submission are now open. The early registration deadline is April 1. The abstract submission deadline for oral presentations is May 15, whereas July 31 is the deadline for abstracts that will be included in the Conference Abstract book.
Categories: Conferences
January 15, 2019
SGD has updated our JBrowse genome browser with 157 new data tracks related to genome-wide experiments and omics data for you to explore. You can easily access these new tracks, which visualize data from the twenty publications listed below, by entering JBrowse and clicking on the left-hand “Select tracks” tab. Then, search for the PMID associated with the reference of interest.
Note that some references appear more than once, as they have multiple data tracks associated that belong to different categories in JBrowse.
For more information on using JBrowse, be sure to check out our playlist of JBrowse video tutorials on YouTube. If you have any questions or feedback about the new tracks or about our genome browser, please don’t hesitate to contact us.
Transcription & Transcriptional Regulation
Reference | PMID | Description in JBrowse |
Baptista et al. (2017) | 28918903 | ChEC-seq to map the genome-wide binding of the SAGA coactivator complex in budding yeast. |
Castelnuovo et al. (2014) | 24497191 | Genome-wide measurement of whole transcriptome versus histone modified mutants |
El Hage et al. (2014) | 25357144 | Genome-wide distribution of RNA-DNA hybrids identifies RNase H targets in tRNA genes retrotransposons and mitochondria. |
Freeberg et al. (2013) | 23409723 | Mapped regions of untranslated, polyadenylated transcriptome bound by RNA-binding proteins (RBPs) |
Kang et al. (2015) | 25213602 | Genome-wide transcript profiling by paired-end ditag sequencing |
Lee et al. (2018) | 29339748 | ChIP-Seq, mRNA-seq, ATAC-seq, and MNase-seq samples in wild-type (WT) and various mutants were prepared using Saccharomyces cerevisiae. |
Park et al. (2014) | 24413663 | Simultaneous mapping of RNA ends by sequencing (SMORE-seq) to identify the strongest transcription start sites and polyadenylation sites genome-wide |
Rossbach et al. (2017) | 28924058 | Authors utilized the Calling Cards Ty5 retrotransposon insertion method to identify binding sites of cdc7kd, cdc7kdΔcterm and Gal4 transcription factor within the yeast genome. |
Schaughnency et al. (2014) | 25299594 | Genome-wide identification of transcription termination sites; pA pathway and non-polyadenylation pathway in strains missing Sen1p or Nrd1p |
Histone Modification
Reference | PMID | Description in JBrowse |
Castelnuovo et al. (2014) | 24497191 | Genome-wide measurement of whole transcriptome versus histone modified mutants |
Hu J. et al. (2015) | 26628362 | ChIP-seq and MNase-seq to determine how histone modifications and chromatin structure directly regulate meiotic recombination. Identified acetylation of histone H4 at Lys44 (H4K44ac) as a new histone modification |
Joo et al. (2017) | 29203645 | Next-Generation-Sequecing (NGS)-derived genome-wide occupancy of TAF (Taf1) compared with other basal initiation components (TBP and TFIIB), histones (H3, H4, Htz1 and H4 acetylation) and histone regulator complexes (Swr1, Bdf1) in S. cerevisiae |
Kniewel et al. (2017) | 28986445 | ChIP-seq to determine the whole-genome enrichment of Mek1 targeted histone H3 threonine 11 phosphorylation (H3 T11ph) during Saccharomyces cerevisiae meiosis. |
Lee et al. (2018) | 29339748 | ChIP-Seq, mRNA-seq, ATAC-seq, and MNase-seq samples in wild-type (WT) and various mutants were prepared using Saccharomyces cerevisiae. |
Weiner et al. (2018) | 25801168 | Examining chromatin dynamics through genome-wide mapping of 26 histone modifications at 0 4 8 15 30 and 60 minutes after diamide addition using MNase-ChIP |
Chromatin Organization
Reference | PMID | Description in JBrowse |
Chereji et al. (2014) | 29426353 | Genome binding/occupancy profiling of single nucleosomes and linkers by high throughput sequencing |
Gutierrez et al. (2017) | 29212533 | Authors sought to correct sequence bias of MNase-Seq with a method based on the digestion of naked DNA and the use of the bioinformatic tool DANPOS |
Hu Z. et al. (2014) | 24532716 | Genome-wide measurement of nucleosome occupancy during cell aging |
Hu J. et al. (2015) | 26628362 | ChIP-seq and MNase-seq to determine how histone modifications and chromatin structure directly regulate meiotic recombination. Identified acetylation of histone H4 at Lys44 (H4K44ac) as a new histone modification |
Joo et al. (2017) | 29203645 | Next-Generation-Sequecing (NGS)-derived genome-wide occupancy of TAF (Taf1) compared with other basal initiation components (TBP and TFIIB), histones (H3, H4, Htz1 and H4 acetylation) and histone regulator complexes (Swr1, Bdf1) in S. cerevisiae |
Lee et al. (2018) | 29339748 | ChIP-Seq, mRNA-seq, ATAC-seq, and MNase-seq samples in wild-type (WT) and various mutants were prepared using Saccharomyces cerevisiae. |
RNA Catabolism
Reference | PMID | Description in JBrowse |
Geisberg et al. (2014) | 24529382 | Half-lives of 21,248 mRNA 3_ isoforms in yeast were measured by rapidly depleting RNA polymerase II from the nucleus and performing direct RNA sequencing throughout the decay process. |
Smith et al. (2014) | 24931603 | Identification of genome-wide transcripts; looking at nonsense-mediated RNA decay pathway |
Transposons
Reference | PMID | Description in JBrowse |
Lee et al. (2018) | 29339748 | ChIP-Seq, mRNA-seq, ATAC-seq, and MNase-seq samples in wild-type (WT) and various mutants were prepared using Saccharomyces cerevisiae. |
Michel et al. (2017) | 28481201 | Genome-wide examination of protein function by using transposons for targeted gene disruption |
Rossbach et al. (2017) | 28924058 | Authors utilized the Calling Cards Ty5 retrotransposon insertion method to identify binding sites of cdc7kd, cdc7kdΔcterm and Gal4 transcription factor within the yeast genome. |
DNA Replication, Recombination, and Repair
Reference | PMID | Description in JBrowse |
Mao et al. (2017) | 28912372 | Map of N-methylpurine (NMP) lesion alkalation damage across the yeast genome |
Categories: New Data