New & Noteworthy

Finding Your Publication in SGD

August 28, 2026

One of the most common questions we receive is: “Where can I find my paper in SGD?”

Your work is probably here, on SGD’s Literature tab. The Literature tab is organized into groups of papers, making it easy to find specific topics or reviews.

The Locus Summary Tab Is a Curated Snapshot

When you visit a locus page like ZIP1, you land on the Locus Summary tab. At the bottom of that page, you’ll see a few references.

This is not the full reference list for the locus.

Think of these Locus Summary references more like footnotes. Only the publications used as references for the specific information displayed on that particular Locus Summary tab are in that small section.

For example, here is the ZIP1 Overview with 6 ZIP1-related references. These publications include:

• The paper used as the reference for the gene name, and in this case, the same paper was also cited for the Name Description
• Publications used as references for statements in the description

The Literature tab is where you can find SGD’s complete, curated collection of publications for a locus.

At the bottom of the ZIP1 Locus Summary page, the six references used in the Overview are presented. For the complete list of all 245 ZIP1-related publications, click on the Literature section links (boxed in purple) just above that References section.

The Complete Reference List Is on the Literature Tab

Every curated publication for a locus is catalogued on the Literature tab. The Literature tab is designed to organize all publications by topic, making it easy to explore the full breadth of research on any gene.

The Bottom Line

The Locus Summary tab shows footnotes. The Literature tab shows the complete reference list.

If you’re looking for comprehensive information about what’s known for a locus, including whether your publication or a colleague’s work has been curated, the Literature tab is the place to look. You can also search the full text of yeast publications using Textpresso.

Looking for a specific publication?

While we work hard to capture all relevant yeast literature, some publications may not have been reviewed yet or certain data may not have been captured. If you believe your work should be in SGD but can’t find it, or if you notice missing data from a publication that is in SGD, please contact us. We sincerely appreciate our community’s help in keeping SGD accurate, complete, and up to date.

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Questions about how your research appears in SGD? Contact us

Explore all references in SGD here, or browse recent yeast publications at yeastgenome.org/reference/recent.

Categories: Tutorial

Tags: Literature Tab, Locus Summary, Saccharomyces cerevisiae

SGD Newsletter, August 2026

August 20, 2026

About this newsletter:
This is the August 2026 issue of the SGD newsletter. This issue features a celebration of the 30th anniversary of the first eukaryotic genome sequence, a suite of powerful new SGD features including Pathway Pages and Functional Networks, and practical guides to help you get the most out of your yeast research.

Contents

• Celebrating 30 Years Since the First Eukaryotic Genome
• New Pathway Pages: Comprehensive Views of Yeast Biochemical Pathways
• Explore the Redesigned SGD Search Landing Page
• New Filtering Options on the Yeast Papers Page
• Overhauled Complex Pages: Enhanced Data Access and Improved User Experience
• Functional Networks: Visualizing Gene Relationships at SGD
• Redesigned Chemical Pages: Comprehensive Small Molecule Information in One Place
• How to: Add a New Gene to the Reference Genome Annotation
• How to: Find UTR Lengths for Yeast Genes
• Resource Guide: Where to Order Yeast Strains
• Alliance of Genome Resources News
• microPublications – Latest Yeast Papers
• Upcoming Conferences & Courses

Celebrating 30 Years Since the First Eukaryotic Genome

This year marks the 30th anniversary of a landmark achievement in biology: the publication of the complete Saccharomyces cerevisiae genome sequence in 1996 – the first eukaryotic genome ever sequenced.

Since before the genome was even complete, SGD has served as the authoritative resource for yeast genomics. Over three decades, we’ve evolved from a simple sequence repository to a comprehensive biological knowledge hub, providing expert curation and multi-dimensional annotations that support researchers worldwide.

Thank you to the yeast research community for three decades of collaboration, contributions, and discoveries!

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New Pathway Pages: Comprehensive Views of Yeast Biochemical Pathways

SGD now has Pathway Pages – dedicated pages for each of the 220 manually curated biochemical pathways in yeast.

Pathway pages offer a complete view of specific biochemical pathways in Saccharomyces cerevisiae. Each page integrates information from multiple sources to help you understand what the pathway does, which genes are involved, how gene products interact, and which chemicals are involved.

Interactive Pathway Diagrams

Each pathway page features a pathway diagram showing the chemical reactions and metabolic flow. The diagram displays:

• Chemical compounds involved (substrates and products)
• Enzymes catalyzing each reaction
• Reaction directionality and relationships

A “View interactive diagram at YeastPathways” button takes you to the full interactive version where you can explore the pathway in greater detail.

Pathway Summary

Expert-curated descriptive text explains:

• What the pathway does and why it’s important
• Biological context and cellular roles
• Connections to other metabolic processes
• Key regulatory mechanisms

For example, the glyoxylate cycle page explains how this essential pathway allows yeast to grow on two-carbon compounds and its role in providing precursors for biosynthesis.

Genes Involved

A comprehensive table of genes participating in the pathway includes:

• Gene names (standard and systematic)
• EC numbers for enzymatic activities
• Functional descriptions
• Direct links to gene pages for detailed information

This makes it easy to see all the players in a pathway at a glance and access detailed information on any gene of interest.

Functional Networks

Pathway pages now include the same Functional Networks features available on gene pages:

Shared Annotations Network: Visualizes how genes in the pathway share phenotype and GO annotations, helping you identify:

• Functional relationships between pathway genes
• Connections to genes in related pathways
• Potential regulatory relationships

You can filter the network by the number of shared pathway genes to focus on the most relevant connections.

GO-CAMs: When available, Gene Ontology Causal Activity Model pathway models are displayed, showing:

• Causal relationships between molecular activities
• How gene products work together mechanistically
• Regulatory interactions and dependencies

If multiple GO-CAM models involve genes from the pathway, you can switch between them using a dropdown menu.

GO Enrichment Analysis

The GO Enrichment section shows which biological processes are statistically overrepresented among pathway genes. This helps you:

• Understand the broader biological context
• See connections to related processes
• Identify key functional themes

Each enriched term links to the genes involved and shows the statistical significance (p-value).

Browse All Pathways

Explore all 220 curated pathways:

• Browse pathways: Search for pathways
• Example: Glyoxylate cycle
• YeastPathways: All metabolic pathways

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Explore the Redesigned SGD Search Landing Page

SGD’s search landing page has been redesigned to make it easier to find the yeast biological information you need.

Enhanced Search Experience The new landing page features an improved search box with smart autocomplete functionality that suggests genes, chemicals, pathways, and other entities as you type. This makes searching faster and helps you discover relevant results even if you’re not sure of the exact name.

Quick Category Browsing Need to browse rather than search? The new page includes quick access buttons for popular categories including genes, complexes, pathways, and chemicals. Click any category to start exploring without typing a single character.

Advanced Filtering Refine your search results by category or other criteria to quickly zero in on exactly what you’re looking for. The redesigned interface provides clearer visual organization with distinct sections for different data types.

Stay Current with SGD The right side of the page now highlights SGD’s latest activity:

• New Literature Added shows the most recently curated publications
• Recent Annotations displays the latest curated data, including new phenotypes, alleles, and GO annotations

This makes it easy to stay up-to-date with the newest information added to SGD.

There are two easy ways to reach the new search landing page:

1. Click the red “Explore SGD” button on the SGD homepage
2. Press return/enter in the search box without typing anything (empty search)

Or go directly to: https://www.yeastgenome.org/search

Happy exploring!

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New Filtering Options on the Yeast Papers Page

The page has always been a great way to stay current with Saccharomyces cerevisiae research, listing newly-added publications over the last 30 days along with the genes, alleles, complexes, and pathways associated with each paper. It’s updated daily, and now you can filter it by:

• Author: find papers by a specific researcher
• Journal: browse what’s new in your favorite publications
• Year: narrow the list by publication year
• Associated genes: zero in on papers linked to your gene of interest
• Associated alleles: filter by specific alleles
• Associated complexes: find papers connected to a complex you’re studying
• Associated pathways: focus on your pathway of interest

Each filter shows the most frequently occurring values along with reference counts, giving you an at-a-glance view of what’s trending in this month’s yeast literature. Combine multiple filters to get as specific as you need, and use Clear all filters to reset. And as always, you can download the full reference list in .nbib format for your reference manager.

Access the New Yeast Papers page anytime via the Literature menu in the purple SGD navigation bar, or from SGD’s new Search landing page (bookmark this!) or go directly to yeastgenome.org/reference/recent. Happy reading!

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Overhauled Complex Pages: Enhanced Data Access and Improved User Experience

Why Protein Complexes Matter

Protein complexes are fundamental functional units in cells that operate as groups of proteins that work together to carry out specific biological processes. Since 2019, SGD has provided detailed information about yeast protein complexes, including subunit composition, functions, interactions, and references.

All Gene Ontology Information on One Page

One of the most significant improvements is the reorganization of Gene Ontology (GO) annotations. Previously, GO information was tucked away on a separate tab, requiring you to navigate away from the main view. Now, all GO annotations are prominently displayed right on the Summary page.

What you can see at a glance:

• Molecular Function: What the complex does
• Biological Process: What pathways or processes it participates in
• Cellular Component: Where in the cell it’s located

All three are now visible directly on the Summary page.

GO-CAM Pathway Models for Complexes

We’ve also integrated GO-CAM (Gene Ontology Causal Activity Models) pathway models directly into complex pages. When available, these models appear below the GO annotations, showing how entire protein complexes fit into larger biological pathways and regulatory networks.

Enhanced Composition Section

Stoichiometry Data: For complexes where the subunit ratios have been experimentally determined, you’ll now see the exact stoichiometry, providing quantitative information about complex architecture.

Structural Information:

• Expert-curated notes about complex assembly and structural features
• Direct links to Protein Data Bank (PDB) entries for complexes with experimentally determined 3D structures
• Protein-protein binding regions and interaction interfaces (when characterized)

Organized Display: Subunits are now grouped by their roles or relationships within the complex, making it easier to understand how the complex is organized.

Easy Navigation: Each subunit links directly to its SGD gene page, so you can access detailed information on individual components.

Shared Biology Networks

Complex pages now include a Shared Biology section that shows GO annotations shared with other complexes, subunits shared between complexes, and ranked lists that prioritize the most functionally related complexes.

Improved User Experience Throughout

• Clearer section headers make information easy to find
• Better spacing and organization improve readability
• Consistent styling with other SGD page types provides a unified experience
• Logical information hierarchy puts the most commonly accessed data front and center

• Example: Sulfite reductase complex (NADPH)
• Browse all complexes: Search for complexes

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Functional Networks: Visualizing Gene Relationships at SGD

New Functional Networks sections are now available on gene and complex pages. This addition helps researchers understand how genes and proteins work together in biological systems.

Shared Annotations Networks

Ever wondered which other genes might have similar functions to your gene of interest? The Shared Annotations network visualizes genes that share similar Gene Ontology (GO) annotations with your query gene. These networks are generated based on overlapping GO terms across Molecular Function, Biological Process, and Cellular Component.

Why is this useful?

• Identify potential interaction partners
• Find paralogs with related functions
• Discover genes that may participate in similar biological processes
• Generate hypotheses for experimental design

Most genes in the S. cerevisiae genome have sufficient GO annotations to generate these networks, providing broad coverage across the yeast proteome.

GO-CAM Pathway Models

GO-CAMs (Gene Ontology Causal Activity Models) represent an exciting advancement in pathway representation. Unlike traditional GO annotations that link individual genes to single terms, GO-CAMs show how multiple gene products work together in integrated pathway models with causal relationships showing how one molecular activity leads to another.

What makes GO-CAMs special?

• Causal relationships: See how one molecular activity leads to another, including activation, inhibition, and regulatory interactions
• Integrated view: Combines Molecular Function, Biological Process, and Cellular Component information in one unified model
• Evidence-based: All models are manually curated by expert biologists and supported by published experimental data

Currently, 470 yeast genes are associated with GO-CAM models, and this number continues to grow as additional pathways are curated.

When multiple GO-CAM models are available for a gene, you can easily switch between them using a pull-down menu. Each model includes a “View GO-CAM at Gene Ontology” link that opens the interactive pathway in AmiGO, where you can explore detailed evidence codes, supporting references, and connections to other pathways.

Functional Networks on Complex Pages

We’ve also added a Shared Biology section to macromolecular complex pages. This section shows:

• GO annotations shared with other complexes
• Subunits shared between complexes
• A ranked list summarizing these relationships

This helps researchers understand how protein complexes relate to each other and identify functionally similar complexes.

How to Access

Simply navigate to any gene page at SGD and scroll to the Functional Networks section (located beneath Gene Ontology). For complex pages, look for the Shared Biology section.

• Example gene page: https://www.yeastgenome.org/locus/MET2
• Example complex page: https://www.yeastgenome.org/complex/CPX-3163

Part of a Bigger Picture

The GO-CAM display on SGD gene pages replicates the implementation from the Alliance of Genome Resources, providing a consistent user experience across model organism databases. This integration reflects our commitment to making yeast data accessible and interoperable with other genomic resources.

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Redesigned Chemical Pages: Comprehensive Small Molecule Information in One Place

SGD’s chemical pages have been redesigned to provide comprehensive information about small molecules relevant to yeast biology such as metabolites, drugs, and experimental compounds, all in a more accessible, more user-friendly format.

Small molecules play crucial roles in yeast biology, from essential metabolites that keep cells functioning to experimental compounds that reveal how cellular processes work. SGD chemical pages bring together curated information about how these chemicals affect yeast, connecting chemical entities to genes, phenotypes, and biological pathways.

Chemical Structures Front and Center

The redesigned pages now display interactive 2D chemical structures prominently at the top of each page. These structures clearly show molecular connectivity and functional groups, providing immediate visual recognition of the compound.

All Information on One Page

No need to navigate between multiple tabs! Everything you need to know about a chemical is now presented on a single, unified page:

Comprehensive Identifiers and Database Links:

• ChEBI ID (we use the Chemical Entities of Biological Interest ontology maintained by EMBL-EBI)
• IUPAC name
• PubChem CID
• Common names and synonyms
• Molecular formula and weight

This integration makes it easy to explore the chemical across multiple resources and access broader chemical and metabolic information.

Curated Experimental Data

Each chemical page now includes rich experimental data curated from the yeast literature:

Phenotype Annotations
See the effects of the chemical on yeast:

• Growth effects
• Metabolic changes
• Other cellular processes

This section includes annotation statistics, top genes and phenotypes involving each chemical. Every phenotype annotation is linked to supporting experimental evidence and literature references, so you can trace findings back to the original research.

Gene Ontology Annotations and Enrichment

The GO Annotations section shows how the chemical is annotated within the Gene Ontology framework, connecting it to specific biological processes, molecular functions, and cellular components.

For metabolites, you’ll also find links to relevant metabolic pathways in YeastPathways throughout the GO annotation tables, connecting chemical entities to their biological context in small molecule metabolism.

The GO Enrichment section shows which biological processes and molecular functions are significantly associated with genes affected by the chemical, helping you:

• Understand the broader biological context of chemical-gene interactions
• Identify patterns in how chemicals influence cellular systems
• Generate hypotheses about mechanism of action

Shared Chemicals Network

The Shared Chemicals section displays other chemical entities that share similar properties, annotations, or biological roles. This makes it easy to:

• Explore chemical families
• Find compounds with similar effects
• Identify potential alternative compounds for experiments

Complete Literature Coverage

The References section compiles all publications from which data about the chemical has been curated. This provides direct access to the primary literature and shows you the full scope of research on each compound.

• Example: Cisplatin
• Example: Caffeine
• Browse all chemicals: Search for chemicals

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Resource Guide: Where to Order Yeast Strains

Finding Strains Through SGD

SGD makes it easy to locate available strains directly from gene pages. Here’s how:

1. Start at the Locus Summary page for your gene of interest (example: https://www.yeastgenome.org/locus/S000005000)
2. Click on the “Phenotype” tab to navigate to the Phenotype Details page (example: https://www.yeastgenome.org/locus/S000005000/phenotype)
3. Scroll to the “Resources” section at the bottom of the page

The Resources section includes direct links to several strain resources:

• Addgene Plasmids — Plasmid repository
• DNASU Plasmids — Plasmid resource collection
• LibrarYeast — Yeast strain and plasmid libraries

European Collections

• Euroscarf (European Saccharomyces cerevisiae Archive for Functional Analysis) — One of the largest yeast strain collections, providing deletion mutants, overexpression strains, and other specialized collections.
• National Collection of Yeast Cultures (NCYC) — Maintains over 4,000 yeast strains, including wild-type isolates and reference strains.
• Industrial Yeasts Collection DBVPG — Houses over 6,000 yeast strains with a focus on industrial and wild yeasts.
• CABRI (Common Access to Biological Resources and Information) — Provides access to catalogs from multiple European culture collections.

North American Collections

• ATCC (American Type Culture Collection) — A premier biological resource center offering authenticated yeast strains, including reference strains and mutant collections.

Specialized Collections and Commercial Sources

• Schuldiner Lab Collections and Libraries — Specialized strain collections and genomic libraries.
• Creative Biogene Knockout Strains — Offers S. cerevisiae S288C knockout strains.
• Horizon Discovery Yeast Tools — Provides parental strains and yeast research tools.

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Alliance of Genome Resources News

Alliance of Genome Resources – Advance Release Notes: 9.1.0

The 9.1.0 release includes data refreshes from each of the model organism source databases as well as various backend improvements.

As of release 9.1.0, there are new Genes and Phenotypes download files on the Alliance Downloads page. Prior releases included Gene Descriptions downloadable files; these files have been removed and replaced by the new Genes download files that contain the respective gene descriptions. All downloadable JSON file formats and some TSV file formats have changed.

Several API endpoints have changed their response payload format to include new, richer data and JSON files formatted according to the Alliance LinkML Data Model, including all endpoints that return download files available on the Alliance Downloads page. These include the following endpoints:

• https://www.alliancegenome.org/api/download/{filename}
• https://www.alliancegenome.org/api/downloads

Several TSV files have changed format, including:

• Variant-Allele TSV download will no longer have the “Variant Id” column (column 6) in favor of the “Variant Symbol” column providing the HGVS name of the variant
• Disease association TSV download will have new columns — see the full release notes for the complete column specification
• VCF files now have an additional header line (##reference) to declare the genome assembly version used across the whole file

Note that stable URLs for Alliance download files have changed in many instances and likely need to be updated in downstream consuming applications. For example, the all species disease JSON download stable URL has changed from: https://fms.alliancegenome.org/download/DISEASE-ALLIANCE-JSON_COMBINED.json.gz

to: https://www.alliancegenome.org/download/DISEASE-ALLIANCE_JSON_COMBINED.json.gz

Additional API changes affect disease annotation endpoints and phenotype annotation endpoints. See the full release notes for complete details.

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microPublications – Latest Yeast Papers

Each article is peer-reviewed, assigned a DOI, and indexed through PubMed and PubMedCentral. Consider microPublications when you have a result that doesn’t necessarily fit into a larger story, but will be of value to others. Latest yeast microPublications:

• Ghuge A, Gottfried S, Schiemann AH, Sattlegger E (2026) A genetic approach to identify amino acids in human GCN1 required for mediating Gcn2 activation. MicroPubl Biol. 2026 Jul 27.
• Dewitt D, Amyx A, Holderman K, Maxwell C, Ball I, Bennington D, Terry R, Ruiz Garcia D, Branstetter R, Boyd W, Schweitzer JK (2026) Yeast Gene ILM1 Influences Passage Through G1/S. MicroPubl Biol. 2026 Jul 16.
• Paxton KM, Avaala JA, Creviston CS, Gumina J, True JD, Rubenstein EM (2026) Ubiquitin-elongating enzyme Ufd2 confers resistance to hygromycin B in Saccharomyces cerevisiae. MicroPubl Biol. 2026 Jun 30.
• Sherpa CD, Woghiren P, Leonello E, Abdel-Khalek M, Schuessler BJ, Vermaas JV, Backues SK (2026) Screening Atg11, a central organizer of yeast selective autophagy, for residues involved in the Atg11-Atg9 interaction. MicroPubl Biol. 2026 May 29.
• Villasi W, Frederic R, Qureshi S, Zheng B, Torrente MP, Fisher RMA (2026) Histone H3 Post-Translational Modification Changes are Linked to Manganese and Copper Exposure in Saccharomyces cerevisiae. MicroPubl Biol. 2026 May 21.
• Avaala JA, Palackel M, Tesch IM, Gumina J, Creviston CS, True JD, Crowder JJ, Rubenstein EM (2026) Ubiquitin-conjugating enzyme membrane anchor Cue1 confers resistance to hygromycin B in Saccharomyces cerevisiae. MicroPubl Biol. 2026 May 14.
• Takesue H, Okada S, Ito T (2026) Transcriptional capacity limits copper resistance in yeast harboring highly expanded CUP1 arrays. MicroPubl Biol. 2026 May 14.
• Germain G, Lamphere S, Molinari E, Boynton P (2026) Sodium chloride stress inhibits Saccharomyces paradoxus meiosis. MicroPubl Biol. 2026 May 5.

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Upcoming Conferences & Courses

• Life with 6000 Genes
  • August 31 to September 01, 2026
  • Palazzo Medici Riccardi, Florence, Italy
• 41st SMYTE Small Meeting on Yeast Transport and Energetics
  • September 12 to September 16, 2026
  • Chaves, Portugal
• 39th International Specialized Symposium on Yeasts (ISSY39)
  • November 08 to November 12, 2026
  • Seoul, South Korea
• 40th International Specialized Symposium on Yeasts (ISSY40)
  • August 22 to August 26, 2027
  • Santos, Sao Paulo, Brazil

Note: The goal of this newsletter is to inform our users about new features in SGD and to foster communication within the yeast community. If you wish to receive this newsletter via email, please contact the SGD Help Desk at sgd-helpdesk@lists.stanford.edu.

Categories: Uncategorized

Tags: Newsletter, Saccharomyces cerevisiae, yeast

Changes to Saccharomyces cerevisiae GFF3 file

March 01, 2024

The saccharomyces_cerevisiae.gff contains sequence features of Saccharomyces cerevisiae and related information such as Locus descriptions and GO annotations. It is fully compatible with Generic Feature Format Version 3. It is updated weekly.

After November 2020, SGD updated the transcripts in the GFF file to reflect the experimentally determined transcripts (Pelechano et al. 2013, Ng et al. 2020), when possible. The longest transcripts were determined for two different growth media – galactose and dextrose. When available, experimentally determined transcripts for one or both conditions were added for a gene. When this data was absent, transcripts matching the start and stop coordinates of an open reading frame (ORF) were used. 

Beginning in February 2024, SGD increased the start and stop coordinates of genes to encompass the start and stop coordinates of the longest experimentally determined transcripts, regardless of condition.  This change was made in order to comply with JBrowse 2, a newer and more extensible genome browser, which requires that parent features in GFF files (genes) are larger than child features (mRNA, CDS, etc) (Diesh et al., 2023). 

This is a standard format used by many groups. SGD uses the GFF file to load the reference tracks in SGD’s genome browser resource.

Categories: Announcements, Data updates

Tags: biology, blog, genetics, news, Saccharomyces cerevisiae

Fpt1p is a negative regulator of RNA Polymerase III embedded in the tDNA chromatin-proteome

November 27, 2023

Gene transcription is facilitated by RNA polymerase enzyme complexes that collaborate with transcription factors, repressors, chromatin remodelers, and other cellular factors. RNA Polymerase III (RNAPIII) mainly transcribes short DNA fragments called tDNAs, that code for transfer-RNAs (tRNAs). In repressive conditions, tDNA transcription is repressed by the well-characterized protein Maf1. A new study by Van Breugel et al., recently published in Molecular Cell, identified Fpt1p (YKR011C) as an additional regulator of RNAPIII in S. cerevisiae.  

By using Epi-Decoder, a technique based on synthetic genetic array (SGA), chromatin immunoprecipitation and DNA-barcode sequencing, the local chromatin-proteome of a single tDNA was decoded in active and repressive conditions. The authors found major reprogramming of the core RNAPIII transcription machinery and other known chromatin-binding proteins. Surprisingly, they found the protein Ykr011c to be enriched in the tDNA chromatin-proteome, especially under repressive conditions, prompting the authors to rename the gene FPT1 (Factor in the Proteome of tDNAs number 1).

Following up on the Epi-Decoder finding, genome-wide sequencing methods such as ChIP-seq and ChIP-exo revealed that Fpt1p uniquely binds RNAPIII-regulated genes. Using the anchor away system to conditionally deplete core RNAPIII transcription factors from the nucleus, Fpt1 binding to tRNA genes was found to require both TFIIIB and TFIIIC but not RNAPIII or ongoing transcription. tRNA genes have been described to differentially respond to repressive signals but gene-specific regulatory mechanisms have largely remained elusive. Looking at Fpt1p, Van Breugel et al. found a correlation between tDNA responsiveness to repressive signals and Fpt1p occupancy, suggesting a negative regulatory role for Fpt1p. Substantiating these results, FPT1 knockout strains showed increased occupancy of RNAPIII and TFIIIB at tRNA genes, while TFIIIC occupancy decreased. These outcomes point towards a role for Fpt1p in promoting eviction of RNAPIII upon repressive signals. 

In summary, taking advantage of multiple yeast genetic approaches, Van Breugel et al. found that the previously uncharacterized protein Fpt1 is a bona fide RNAPIII regulator in S. cerevisiae. Their research emphasizes the importance of not overlooking uncharacterized proteins, as they may possess alternative regulatory roles that could change our views on fundamental cellular processes.

Text and image provided by Marlize van Breugel, MSc.

Categories: News and Views

Tags: RNA polymerase III, Saccharomyces cerevisiae

Reference Genome Annotation Update R64.4

September 08, 2023

The S. cerevisiae strain S288C reference genome annotation was updated. The new genome annotation is release R64.4.1, dated 2023-08-23. Note that the underlying genome sequence itself was not altered in any way.

This annotation update included:

• new uORFs for 3 ORFs:
  • FPS1/YLL043W
  • ACC1/YNR016C
  • HOL1/YNR055C
• 8 new ncRNAs:
  • SUT035/YNCC0015W
  • SUT053/YNCD0033W
  • SUT468/YNCD0034C
  • SUT532/YNCG0047C
  • SUT125/YNCG0048W
  • SUT126/YNCG0049W
  • SUT390/YNCP0025W
  • SUT418/YNCP0026W
• 3 ORFs demoted from ‘Uncharacterized’ to ‘Dubious’ based on request from NCBI because they overlap tRNAs:
  • YDR278C
  • YOL013W-A
  • YPR108W-A

R64.4 Annotation update details

Chr	Feature	Description of change	Reference
III	SUT035/YNCC0015W	New ncRNA chrIII:205766..205942 (+ strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158
IV	YDR278C	Change ORF qualifier from Uncharacterized to Dubious	Requested by NCBI
IV	SUT053/YNCD0033W	New ncRNA chrIV:506334..507774 (+ strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158
IV	SUT468/YNCD0034C	New ncRNA chrIV:506546..507450 (- strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158
VII	SUT532/YNCG0047C	New ncRNA chrVII:17213..17709 (- strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158
VII	SUT125/YNCG0048W	New ncRNA chrVII:650855..651159 (+ strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158, Feng MW, et al. (2022) PMID:36712349
VII	SUT126/YNCG0049W	New ncRNA chrVII:660087..661399 (+ strand)	Xu Z, et al. (2009) PMID:19169243,Balarezo-Cisneros LN, et al. (2021) PMID:33493158
XII	FPS1/YLL043W	New uORF uORF2 3 codons chrXII:49924..49932 (+ strand) ATGCATTAA	Cartwright SP, et al. (2017) PMID:28279185
XIV	ACC1/YNR016C	New uORF 4 codons chrXIV:661704..661715 (- strand) ATGTGTTTATAA	Blank HM, et al. (2017) PMID:28057705
XIV	HOL1/YNR055C	New uORF 7 codons chrXIV:730381..730401 (- strand) ATGCTATTACTACCAAGTTGA	Vindu A, et al. (2021) PMID:34375581
XV	YOL013W-A	Change ORF qualifier from Uncharacterized to Dubious	Requested by NCBI
XVI	SUT390/YNCP0025W	New ncRNA chrXVI:52977..53465 (+ strand)	Xu Z, et al. (2009) PMID:19169243, Feng MW, et al. (2022) PMID:36712349
XVI	SUT418/YNCP0026W	New ncRNA chrXVI:588998..589830 (+ strand)	Xu Z, et al. (2009) PMID:19169243, Feng MW, et al. (2022) PMID:36712349
XVI	YPR108W-A	Change ORF qualifier from Uncharacterized to Dubious	Requested by NCBI

Various sequence and annotation files are available on SGD’s Downloads site.

Categories: Data updates

Tags: genome annotation update, Saccharomyces cerevisiae

Prion-like domain in Ty1 Gag protein

July 18, 2023

Retrovirus-like retrotransposons help shape the genome evolution of their hosts and replicate within cytoplasmic particles. However, how their building blocks associate and assemble within the cell is poorly understood. A new study by Sean Beckwith and coworkers, recently published in PNAS, reports a prion-like domain (PrLD) in the Saccharomyces retrotransposon Ty1 Gag protein.

Gag, also found in retroviruses like HIV, is the structural protein that assembles virus-like particles (VLPs). The PrLD has similar sequence properties to prions and disordered protein domains that can drive the formation of assemblies that range from liquid to solid. The Ty1 PrLD acts like a prion when tested in a cell-based prionogenesis assay, and is essential for transposition (Ty1 doesn’t transpose without it!), but researchers were able to restore transposition by replacing the Ty1 PrLD with similar disordered sequences from yeast SUP35 and mouse PrP prions (how cool is that?!).

These findings from Beckwith et al. uncover a critical function for often overlooked disordered sequences, demonstrate greater flexibility in VLP assembly than previously appreciated, and establish an interchangeable “plug-and-play” platform to study disordered sequences in living cells – all by using the awesome power of yeast genetics (#APOYG!).

— Text from Sean Beckwith, with edits from SGD.

Categories: Research Spotlight

Tags: Saccharomyces cerevisiae, transposon

GENETICS Knowledgebase and Database Resources

May 08, 2023

The May 2023 issue of GENETICS features the second annual collection of Model Organism Database articles. Scientists from Alliance of Genome Resources member groups SGD, RGD, ZFIN, Gene Ontology, and Xenbase have provided updates on recent activities and innovations. Be sure to browse the issue and get acquainted with these excellent Knowledgebase and Database Resource papers at GENETICS. Cover art by Vivid Biology.

SGD	https://doi.org/10.1093/genetics/iyac191
RGD	https://doi.org/10.1093/genetics/iyad042
ZFIN	https://doi.org/10.1093/genetics/iyad032
Gene Ontology (GO)	https://doi.org/10.1093/genetics/iyad031
Xenbase	https://doi.org/10.1093/genetics/iyad018

Categories: Announcements

Tags: Saccharomyces cerevisiae, yeast

Role of Sumoylation in Regulating Replication

September 09, 2022

There are ~400 origins of replication in yeast, each of which can be “licensed” by the binding of the conserved origin recognition complex (ORC) and then the MCM replicative helicase complex, all of which happens in G1 phase. During the subsequent S phase, origins are then “activated” by binding of several other replication factors, leading to unwinding and then nascent strand synthesis.

The regulation of origin licensing and activation is a complex, multi-level process, for which numerous aspects of the picture remain unclear. As yeast has the most tools for studying this process, including a full map of origins and numerous options for genetic and biochemical modulations, it presents the ideal model in which to ask probing questions. A recent study by Regan-Mochrie et al. in Genes & Development has revealed the key role of sumoylation in regulation of genome replication.

The origin recognition complex comprises six subunits, encoded by ORC1 to ORC6. The authors built on previous results showing sumoylation of these proteins during DNA damage to ask about their modification status under normal growth. They were able to assess sumoylation status for four of the six subunits, observing various degrees of sumoylation of Orc1p, Orc2p, Orc4p, and Orc5p. They then created a construct to hypersumoylate Orc2p to ask how this affects cells, and found it led to cell lethality. This lethal effect was specific to the Orc protein, as other non-Orc hypersumoylated proteins were tolerated.

The lethality could be rescued by reducing the levels of a SUMO-conjugating enzyme, further indicating the specificity of the effect. The authors identified a subset of early origins that were preferentially inhibited upon hypersumoylation and, upon study, determined that the extra sumoylation interfered with loading of the MCM complex.

After identifying the residues becoming sumoylated on Orc2p, the authors were able to generate mutants to ask about the converse, i.e. hyposumoylation. Indeed, as might be hypothesized, lack of sumoylation caused DNA replication defects via abnormal increased firing of early origins.

Thus, by close study in yeast, the role of sumoylation in genomic stability becomes more clear, where sumoylation of ORC subunits affects loading of the MCM complex, which is itself the substrate for loading of activation factors. Modulated sumoylation status appears to provide a key level of regulatory control.

Categories: Research Spotlight

Tags: cell cycle control, DNA replication, ORC complex, origin recognition complex, regulation of replication, Saccharomyces cerevisiae, sumoylation

Humanizing Glycolysis in Yeast

September 02, 2022

While glycolysis is highly conserved between unicellular yeast and multicellular humans, it appears that not only the glycolytic functions but also the secondary (aka “moonlighting”) functions of the relevant proteins remain largely consistent. This consistency presents unique opportunities for better understanding human glycolysis in muscle tissue and elsewhere.

The technical challenges of studying glycolytic enzymes are not trivial—largely due to genetic redundancy for such critical components—but a recent report by Boonekamp et al. in Cell Reports explains how the authors built on previous work to overcome the obstacles in yeast.  Employing a minimized set of glycolytic genes that were also relocated to a single chromosome (strain SwYG) made it possible to swap in human orthologs with relative ease.

The authors first looked at direct complementation of yeast genes by 25 human glycolytic enzymes. Remarkably, 22 of 25 human genes readily complemented their yeast counterpart. The three exceptions were hexokinases 1, 2, and 3 (HsHK1, HsHK2, and HsHK3), which are roughly twice the size of their yeast orthologs and have lower sequence conservation.

As glycolysis cannot take place without the hexokinases, the authors first looked more closely at HsHK1 and HsHK2 to ask why they fail to function in yeast. Upon exposure to glucose, for which the native human proteins could not support growth, they created conditions to select for systematic mutations that conferred improved glycolysis. The mutant proteins proved to be less sensitive to inhibition by glucose-6-phosphate (G6P), a potent allosteric inhibitor of hexokinase activity.

With this understanding, the authors set out to complement the entire pathway in yeast with human proteins. They created two different strains, one with HsHK2 because it is considered the main isoenzyme in human muscle (strain HsGly-HK2), and one with HsHK4 because it shows less inhibition by G6P (strain HsGly-HK4). The HsGly-HK2 strain could not grow well on glucose until after a long lag phase in which mutations were selected near the G6P-binding site of HsHK2.

Comparing the uptake and output of the two humanized yeast strains to the native yeast strain revealed a number of intriguing differences, especially around the different enzyme activities between human and yeast. These differences led to different behaviors on different carbon sources and overall slower growth and glycolytic flux for the humanized strains versus native yeast.

Three glycolytic yeast enzymes have secondary “moonlighting” roles beyond their function in glycolysis. Hexokinases are involved in glucose repression of genes such as invertase (SUC2), and, indeed, it appears that human hexokinases can also at least partially complement this secondary function. Yeast aldolase (FBA1) plays a secondary role in vacuolar function that is required for growth at alkaline pH.  This function is likewise complemented by the human orthologs, where the humanized strains can grow at pH 7.5. The third moonlighter is enolase, where yeast ENO2 is required for mitochondrial import of tRNA^Lys, thereby allowing growth at higher temperatures and on non-fermentable carbon sources. All three human enolases can at least partially complement this growth defect, and thus appear to have the same secondary function.

Despite the high conservation of functions, the humanized yeast strains have a slow growth phenotype. The authors used this phenotype to employ adaptive laboratory evolution to see which genomic changes restore growth. Interestingly, the mutations that restored growth were mostly not in the glycolytic enzymes themselves, but in associated factors that regulate enzyme abundance and activity. The identity of these regulators and the potential for targeting them in human muscle have already rewarded the successful transfer of skeletal muscle glycolysis into yeast.

Categories: Research Spotlight

Tags: glycolysis, humanizing yeast, muscle glycolysis, Saccharomyces cerevisiae, yeast model for glycolysis

Link Between Aging and Iron

August 25, 2022

Perturbations in iron homeostasis affect aging, but how this happens has remained a bit of a black box. A new study by Patnaik et al. in Cell Reports illuminates this box by looking more closely at the transcription factors that are first to respond when iron becomes limiting.

Key among these are Atf1p and Atf2p, which activate the full suite of iron-mobilization genes, among which is TIS11/CTH2, which encodes an RNA-binding protein that targets specific messages for decay.

The targeted messages flagged for decay encode mitochondrial proteins, as these use iron but are not the most essential in the set. The most essential Fe-requiring enzymes are those involved in DNA synthesis and repair, such that slowing/shutting mitochondrial function is a response to iron deficiency. Intriguingly, mitochondrial function also happens to decline with age.

To find the specific mechanisms linking iron with aging, the authors used an unbiased analysis of genes involved in iron homeostasis to see which showed connection with aging. The strain with a tis11Δ mutation lived longer than any others, with a lifespan extended by 51.1%. In a broader sense, they found that genes involved in different aspects of response to iron deficiency also had different effects on fitness and aging.

Delving more deeply into the role of Tis11p/Cth2p in aging, the authors used RNA-seq and Ribo-seq to look at temporal changes in transcription versus translation in aging cells. They showed how, overall, aging leads to inhibition of translation—except for certain genes which are upregulated instead. Interestingly, most of the upregulated genes are in the Fe regulon that gets activated by the first responder Atf1p.

While the expression of TIS11/CTH2 increases both with aging and with iron deficiency, the deletion of the gene extends lifespan. Thus, multiple lines of evidence suggest Tis11p/Cth2p is a negative regulator of longevity. The key connection appears to be mitochondrial translation, where the function of Tis11p/Cth2p to inhibit translation of mitochondrial transcripts for repressing non-essential Fe-requiring enzymes serves to simultaneously repress overall mitochondrial respiration, which speeds aging.

As not all genes translationally upregulated in the tis11Δ mutant contained appropriate binding sites in the 3’ UTR, the authors looked further and found binding sequences for Puf3p, a protein known to bind and inhibit translation of mRNAs coding for mitochondrial ribosome proteins. Thus, Puf3p appears to be a critical partner for Tis11p/Cth2p in mediating downregulation of mitochondrial function. Further, they questioned the relationship with the Hap4p transcription factor, which regulates numerous components of the electron transport chain and whose overexpression extends lifespan. As the combination of a tis11Δ deletion with HAP4 overexpression had no additive effect in an epistasis experiment, they concluded that Tis11p-dependent repression acts through Hap4p.

The role of phosphorylation of Tis11p/Cth2p was examined by mutating N-terminal serine residues, which impairs degradation of the protein. Consistent with the converse result of extended lifespan in null mutants, the nondegradable version of the protein shortens lifespan.

Thus, the ease of the yeast model once more illuminates intricate connections between critical proteins, facilitating potential drug discovery around several new aging factors.

Categories: Research Spotlight

Tags: aging, cell aging, iron homeostasis, Saccharomyces cerevisiae, yeast model for aging

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