New data and collaborations at the Saccharomyces Genome Database: updated reference genome, alleles, and the Alliance of Genome Resources

Qarles: a web server for the quick characterization of large sets of genes

The characterization of gene sets is a recurring task in computational biology. Identifying specific properties of a hit set compared to a reference set can reveal biological roles and mechanisms, and can lead to the prediction of new hits. However, collecting the features to evaluate can be time consuming, and implementing an informative but compact graphical representation of the multiple comparisons can be challenging, particularly for bench scientists. Here, I present Qarles (quick characterization of large sets of genes), a web server that annotates Saccharomyces cerevisiae gene sets by querying a database of 31 features widely used by the yeast community and that identifies their specific properties, providing publication-ready figures and reliable statistics. Qarles has a deliberately simple user interface with all the functionality in a single web page and a fast response time to facilitate adoption by the scientific community. Qarles provides a rich and compact graphical output, including up to five gene set comparisons across 31 features in a single dotplot, and interactive boxplots to enable the identification of outliers. Qarles can also predict new hit genes by using a random forest trained on the selected features. The web server is freely available at https://qarles.org.

Essential proteins discover based on hypergraph and mult-omics data integration model

Essential proteins are critical for cell regulation, reproduction and metabolism, with their absence leading to the cessation of cell replication or cell death. Therefore, identifying essential proteins is vital for the developing antibiotics, new therapies and targeted drugs. However, current computational methods rarely or insufficiently consider the impact of features importance and the noisy data in protein-protein interaction network on recognition accuracy. To address these issues, we propose a essential protein identification method based on a hypergraph and Hierarchical Advantage Suppression Model, HGMO. Firstly, based on the principles of co-expression and co-localization, a hypergraph network is constructed using protein-protein interaction network, gene expression data, and subcellular localization data. From this network, a new feature score, the Topological Significance (TS) score, is extracted. Then, we extract subcellular localization scores and orthologous scores from the subcellular localization data and orthologous data, respectively. Finally, we uses a multi-omics data integration model, Hierarchical Advantage Suppression Model, for feature fusion, thus proposing the HGMO method. Experimental results show that HGMO consistently outperforms other methods on three S.cerevisiae datasets. Moreover, TS demonstrates a higher identification rate than other centrality methods.

Structural insights into spliceosome fidelity: DHX35-GPATCH1- mediated rejection of aberrant splicing substrates

The spliceosome, a highly dynamic macromolecular assembly, catalyzes the precise removal of introns from pre-mRNAs. Recent studies have provided comprehensive structural insights into the step-wise assembly, catalytic splicing and final disassembly of the spliceosome. However, the molecular details of how the spliceosome recognizes and rejects suboptimal splicing substrates remained unclear. Here, we show cryo-electron microscopy structures of spliceosomal quality control complexes from a thermophilic eukaryote, Chaetomium thermophilum. The spliceosomes, henceforth termed B*Q, are stalled at a catalytically activated state but prior to the first splicing reaction due to an aberrant 5' splice site conformation. This state is recognized by G-patch protein GPATCH1, which is docked onto PRP8-EN and -RH domains and has recruited the cognate DHX35 helicase to its U2 snRNA substrate. In B*Q, DHX35 has dissociated the U2/branch site helix, while the disassembly helicase DHX15 is docked close to its U6 RNA 3'-end substrate. Our work thus provides mechanistic insights into the concerted action of two spliceosomal helicases in maintaining splicing fidelity by priming spliceosomes that are bound to aberrant splice substrates for disassembly.

Pervasive formation of double-stranded RNAs by overlapping sense/antisense transcripts in budding yeast mitosis and meiosis

Previous RNA profiling studies revealed coexpression of overlapping sense/antisense (s/a) transcripts in pro- and eukaryotic organisms. Functional analyses in yeast have shown that certain s/a mRNA/mRNA and mRNA/lncRNA pairs form stable double-stranded RNAs (dsRNAs) that affect transcript stability. Little is known, however, about the genome-wide prevalence of dsRNA formation and its potential functional implications during growth and development in diploid budding yeast. To address this question, we monitored dsRNAs in a Saccharomyces cerevisiae strain expressing the ribonuclease DCR1 and the RNA-binding protein AGO1 from Naumovozyma castellii We identify dsRNAs at 347 s/a loci that express partially or completely overlapping transcripts during mitosis, meiosis, or both stages of the diploid life cycle. We associate dsRNAs with s/a loci previously thought to be exclusively regulated by antisense interference, and others that encode antisense RNAs, which down-regulate sense mRNA-encoded protein levels. To facilitate hypothesis building, we developed the sense/antisense double-stranded RNA (SensR) expression viewer. Users are able to retrieve different graphical displays of dsRNA and RNA expression data using genome coordinates and systematic or standard names for mRNAs and different types of stable or cryptic long noncoding RNAs (lncRNAs). Our data are a useful resource for improving yeast genome annotation and for work on RNA-based regulatory mechanisms controlling transcript and protein levels. The data are also interesting from an evolutionary perspective, since natural antisense transcripts that form stable dsRNAs have been detected in many species from bacteria to humans. The SensR viewer is freely accessible at https://sensr.genouest.org.

Saccharomyces Genome Database: advances in genome annotation, expanded biochemical pathways, and other key enhancements

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here, we describe recent updates at SGD, including the 2 most recent reference genome annotation updates, expanded biochemical pathway representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

Free introns of tRNAs as complementarity-dependent regulators of gene expression

From archaea to humans, a subset of transfer RNA (tRNA) genes possesses an intron that must be removed from transcribed pre-tRNAs to generate mature, functional tRNAs. Evolutionary conservation of tRNA intron sequences suggests that tRNA introns perform sequence-dependent cellular functions, which are presently unknown. Here, we demonstrate that free introns of tRNAs (fitRNAs) in Saccharomyces cerevisiae serve as small regulatory RNAs that inhibit mRNA levels via long (13-15 nt) statistically improbable stretches of (near) perfect complementarity to mRNA coding regions. The functions of fitRNAs are both constitutive and inducible because genomic deletion or inducible overexpression of tRNAIle introns led to corresponding increases or decreases in levels of complementary mRNAs. Remarkably, although tRNA introns are usually rapidly degraded, fitRNATrp selectively accumulates following oxidative stress, and target mRNA levels decrease. Thus, fitRNAs serve as gene regulators that fine-tune basal mRNA expression and alter the network of mRNAs that respond to oxidative stress.

Replication-IDentifier links epigenetic and metabolic pathways to the replication stress response

Perturbation of DNA replication, for instance by hydroxyurea-dependent dNTP exhaustion, often leads to stalling or collapse of replication forks. This triggers a replication stress response that stabilizes these forks, activates cell cycle checkpoints, and induces expression of DNA damage response genes. While several factors are known to act in this response, the full repertoire of proteins involved remains largely elusive. Here, we develop Replication-IDentifier (Repli-ID), which allows for genome-wide identification of regulators of DNA replication in Saccharomyces cerevisiae. During Repli-ID, the replicative polymerase epsilon (Pol ε) is tracked at a barcoded origin of replication by chromatin immunoprecipitation (ChIP) coupled to next-generation sequencing of the barcode in thousands of hydroxyurea-treated yeast mutants. Using this approach, 423 genes that promote Pol ε binding at replication forks were uncovered, including LGE1 and ROX1. Mechanistically, we show that Lge1 affects replication initiation and/or fork stability by promoting Bre1-dependent H2B mono-ubiquitylation. Rox1 affects replication fork progression by regulating S-phase entry and checkpoint activation, hinging on cellular ceramide levels via transcriptional repression of SUR2. Thus, Repli-ID provides a unique resource for the identification and further characterization of factors and pathways involved in the cellular response to DNA replication perturbation.

Cell integrity limits ploidy in budding yeast

Evidence suggests that increases in ploidy have occurred frequently in the evolutionary history of organisms and can serve adaptive functions to specialized somatic cells in multicellular organisms. However, the sudden multiplication of all chromosome content may present physiological challenges to the cells in which it occurs. Experimental studies have associated increases in ploidy with reduced cell survival and proliferation. To understand the physiological challenges that suddenly increased chromosome content imposes on cells, we used S. cerevisiae to ask how much chromosomal DNA cells may contain and what determines this limit. We generated polyploid cells using 2 distinct methods causing cells to undergo endoreplication and identified the maximum ploidy of these cells, 32-64C. We found that physical determinants that alleviate or exacerbate cell surface stress increase and decrease the limit to ploidy, respectively. We also used these cells to investigate gene expression changes associated with increased ploidy and identified the repression of genes involved in ergosterol biosynthesis. We propose that ploidy is inherently limited by the impacts of growth in size, which accompany whole-genome duplication, to cell surface integrity.

A proteome-wide yeast degron collection for the dynamic study of protein function

Genome-wide collections of yeast strains, known as libraries, revolutionized the way systematic studies are carried out. Specifically, libraries that involve a cellular perturbation, such as the deletion collection, have facilitated key biological discoveries. However, short-term rewiring and long-term accumulation of suppressor mutations often obscure the functional consequences of such perturbations. We present the AID library which supplies "on demand" protein depletion to overcome these limitations. Here, each protein is tagged with a green fluorescent protein (GFP) and an auxin-inducible degron (AID), enabling rapid protein depletion that can be quantified systematically using the GFP element. We characterized the degradation response of all strains and demonstrated its utility by revisiting seminal yeast screens for genes involved in cell cycle progression as well as mitochondrial distribution and morphology. In addition to recapitulating known phenotypes, we also uncovered proteins with previously unrecognized roles in these central processes. Hence, our tool expands our knowledge of cellular biology and physiology by enabling access to phenotypes that are central to cellular physiology and therefore rapidly equilibrated.

FuncFetch: an LLM-assisted workflow enables mining thousands of enzyme-substrate interactions from published manuscripts

MOTIVATION

Thousands of genomes are publicly available, however, most genes in those genomes have poorly defined functions. This is partly due to a gap between previously published, experimentally characterized protein activities and activities deposited in databases. This activity deposition is bottlenecked by the time-consuming biocuration process. The emergence of large language models presents an opportunity to speed up the text-mining of protein activities for biocuration.

RESULTS

We developed FuncFetch-a workflow that integrates NCBI E-Utilities, OpenAI's GPT-4, and Zotero-to screen thousands of manuscripts and extract enzyme activities. Extensive validation revealed high precision and recall of GPT-4 in determining whether the abstract of a given paper indicates the presence of a characterized enzyme activity in that paper. Provided the manuscript, FuncFetch extracted data such as species information, enzyme names, sequence identifiers, substrates, and products, which were subjected to extensive quality analyses. Comparison of this workflow against a manually curated dataset of BAHD acyltransferase activities demonstrated a precision/recall of 0.86/0.64 in extracting substrates. We further deployed FuncFetch on nine large plant enzyme families. Screening 26 543 papers, FuncFetch retrieved 32 605 entries from 5459 selected papers. We also identified multiple extraction errors including incorrect associations, nontarget enzymes, and hallucinations, which highlight the need for further manual curation. The BAHD activities were verified, resulting in a comprehensive functional fingerprint of this family and revealing that ∼70% of the experimentally characterized enzymes are uncurated in the public domain. FuncFetch represents an advance in biocuration and lays the groundwork for predicting the functions of uncharacterized enzymes.

AVAILABILITY AND IMPLEMENTATION

Code and minimally curated activities are available at: https://github.com/moghelab/funcfetch and https://tools.moghelab.org/funczymedb.

Genes controlling hydrolysate toxin tolerance identified by QTL analysis of the natural Saccharomyces cerevisiae BCC39850

Lignocellulosic material can be converted to valorized products such as fuels. Pretreatment is an essential step in conversion, which is needed to increase the digestibility of the raw material for microbial fermentation. However, pretreatment generates by-products (hydrolysate toxins) that are detrimental to microbial growth. In this study, natural Saccharomyces strains isolated from habitats in Thailand were screened for their tolerance to synthetic hydrolysate toxins (synHTs). The Saccharomyces cerevisiae natural strain BCC39850 (toxin-tolerant) was crossed with the laboratory strain CEN.PK2-1C (toxin-sensitive), and quantitative trait locus (QTL) analysis was performed on the segregants using phenotypic scores of growth (OD600) and glucose consumption. VMS1, DET1, KCS1, MRH1, YOS9, SYO1, and YDR042C were identified from QTLs as candidate genes associated with the tolerance trait. CEN.PK2-1C knockouts of the VMS1, YOS9, KCS1, and MRH1 genes exhibited significantly greater hydrolysate toxin sensitivity to growth, whereas CEN.PK2-1C knock-ins with replacement of VMS1 and MRH1 genes from the BCC39850 alleles showed significant increased ethanol production titers compared with the CEN.PK2-1C parental strain in the presence of synHTs. The discovery of VMS1, YOS9, MRH1, and KCS1 genes associated with hydrolysate toxin tolerance in S. cerevisiae indicates the roles of the endoplasmic-reticulum-associated protein degradation pathway, plasma membrane protein association, and the phosphatidylinositol signaling system in this trait. KEY POINTS: • QTL analysis was conducted using a hydrolysate toxin-tolerant S. cerevisiae natural strain • Deletion of VMS1, YOS9, MRH1, and KCS1 genes associated with hydrolysate toxin-sensitivity • Replacement of VMS1 and MRH1 with natural strain alleles increased ethanol production titers in the presence of hydrolysate toxins.

Shedding Light on Calcium Dynamics in the Budding Yeast: A Review on Calcium Monitoring with Recombinant Aequorin

Recombinant aequorin has been extensively used in mammalian and plant systems as a powerful tool for calcium monitoring. While aequorin has also been widely applied in yeast research, a notable gap exists in the literature regarding comprehensive reviews of these applications. This review aims to address that gap by providing an overview of how aequorin has been used to explore calcium homeostasis, signaling pathways, and responses to stressors, heavy metals, and toxic compounds in Saccharomyces cerevisiae. We also discuss strategies for further developing the aequorin system in yeast, with particular emphasis on its use as a model for human calcium signaling studies, such as the reproduction of the mitochondrial calcium uniporter. By highlighting previous research and pinpointing potential future applications, we discuss the untapped potential of aequorin in yeast for drug screening, environmental toxicity testing, and disease-related studies.

Cohesin distribution alone predicts chromatin organization in yeast via conserved-current loop extrusion

BACKGROUND

Inhomogeneous patterns of chromatin-chromatin contacts within 10-100-kb-sized regions of the genome are a generic feature of chromatin spatial organization. These features, termed topologically associating domains (TADs), have led to the loop extrusion factor (LEF) model. Currently, our ability to model TADs relies on the observation that in vertebrates TAD boundaries are correlated with DNA sequences that bind CTCF, which therefore is inferred to block loop extrusion. However, although TADs feature prominently in their Hi-C maps, non-vertebrate eukaryotes either do not express CTCF or show few TAD boundaries that correlate with CTCF sites. In all of these organisms, the counterparts of CTCF remain unknown, frustrating comparisons between Hi-C data and simulations.

RESULTS

To extend the LEF model across the tree of life, here, we propose the conserved-current loop extrusion (CCLE) model that interprets loop-extruding cohesin as a nearly conserved probability current. From cohesin ChIP-seq data alone, we derive a position-dependent loop extrusion rate, allowing for a modified paradigm for loop extrusion, that goes beyond solely localized barriers to also include loop extrusion rates that vary continuously. We show that CCLE accurately predicts the TAD-scale Hi-C maps of interphase Schizosaccharomyces pombe, as well as those of meiotic and mitotic Saccharomyces cerevisiae, demonstrating its utility in organisms lacking CTCF.

CONCLUSIONS

The success of CCLE in yeasts suggests that loop extrusion by cohesin is indeed the primary mechanism underlying TADs in these systems. CCLE allows us to obtain loop extrusion parameters such as the LEF density and processivity, which compare well to independent estimates.

A multicellular developmental program in a close animal relative

All animals develop from a single-celled zygote into a complex multicellular organism through a series of precisely orchestrated processes1,2. Despite the remarkable conservation of early embryogenesis across animals, the evolutionary origins of how and when this process first emerged remain elusive. Here, by combining time-resolved imaging and transcriptomic profiling, we show that single cells of the ichthyosporean Chromosphaera perkinsii-a close relative that diverged from animals about 1 billion years ago3,4-undergo symmetry breaking and develop through cleavage divisions to produce a prolonged multicellular colony with distinct co-existing cell types. Our findings about the autonomous and palintomic developmental program of C. perkinsii hint that such multicellular development either is much older than previously thought or evolved convergently in ichthyosporeans.

Location of polyadenylation sites within 3' untranslated regions is linked to biological function in yeast

Expression of a typical yeast gene results in ∼50 3' mRNA isoforms that are distinguished by the locations of poly(A) sites within the 3' untranslated regions (3' UTRs). The location of poly(A) sites with respect to the translational termination codon varies considerably among genes, but whether this has any functional significance is poorly understood. Using hierarchical clustering of 3' UTRs, we identify eight classes of S. cerevisiae genes based on their poly(A) site locations. Genes involved in related biological functions (GO categories) are uniquely over-represented in six of these classes. Similar analysis of S. pombe genes reveals three classes of 3' UTRs, all of which show over-representation of functionally related genes. Remarkably, S. cerevisiae and S. pombe homologs share related patterns of poly(A) site locations. These observations suggest that the location of poly(A) sites within 3' UTRs has biological significance.

The 5-Fluorouracil RNA Expression Viewer (5-FUR) Facilitates Interpreting the Effects of Drug Treatment and RRP6 Deletion on the Transcriptional Landscape in Yeast

Saccharomyces cerevisiae is an excellent model to study the effect of external cues on cell division and stress response. 5-Fluorocuracil (5-FU) has been used to treat solid tumors since several decades. The drug was initially designed to interfere with DNA replication but was later found to exert its antiproliferative effect also via RNA-dependent processes. Since 5-FU inhibits the activity of the 3'-5'-exoribonuclease Rrp6 in yeast and mammals, earlier work has compared the effect of 5-FU treatment and RRP6 deletion at the transcriptome level in diploid synchronized yeast cells. To facilitate interpreting the expression data we have developed an improved 5-Fluorouracil RNA (5-FUR) expression viewer. Users can access information via genome coordinates and systematic or standard names for mRNAs and Xrn1-dependent-, stable-, cryptic-, and meiotic unannotated transcripts (XUTs, SUTs, CUTs, and MUTs). Normalized log2-transformed or linear data can be displayed as filled diagrams, line graphs or color-coded heatmaps. The expression data are useful for researchers interested in processes such as cell cycle regulation, mitotic repression of meiotic genes, the effect of 5-FU treatment and Rrp6 deficiency on the transcriptome and expression profiles of sense/antisense loci that encode overlapping transcripts. The viewer is accessible at http://5fur.genouest.org.

Saccharomyces Genome Database: Advances in Genome Annotation, Expanded Biochemical Pathways, and Other Key Enhancements

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here we describe recent updates at SGD, including the two most recent reference genome annotation updates, expanded biochemical pathways representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

Naming internal insertion alleles created using CRISPR in Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is a powerful model organism, partly because of the ease of genome alterations due to the combination of a fast generation time and many molecular genetic tools. Recent advances in CRISPR-based systems allow for the easier creation of alleles with internally inserted sequences within the coding regions of genes, such as the internal insertion of sequences that code for epitopes or fluorescent proteins. Here we briefly summarize some exisiting nomenclature standards and suggest nomenclature guidelines for internal insertion alleles which are informative, consistent, and computable.

PhyloAln: A Convenient Reference-Based Tool to Align Sequences and High-Throughput Reads for Phylogeny and Evolution in the Omic Era

The current trend in phylogenetic and evolutionary analyses predominantly relies on omic data. However, prior to core analyses, traditional methods typically involve intricate and time-consuming procedures, including assembly from high-throughput reads, decontamination, gene prediction, homology search, orthology assignment, multiple sequence alignment, and matrix trimming. Such processes significantly impede the efficiency of research when dealing with extensive data sets. In this study, we develop PhyloAln, a convenient reference-based tool capable of directly aligning high-throughput reads or complete sequences with existing alignments as a reference for phylogenetic and evolutionary analyses. Through testing with simulated data sets of species spanning the tree of life, PhyloAln demonstrates consistently robust performance compared with other reference-based tools across different data types, sequencing technologies, coverages, and species, with percent completeness and identity at least 50 percentage points higher in the alignments. Additionally, we validate the efficacy of PhyloAln in removing a minimum of 90% foreign and 70% cross-contamination issues, which are prevalent in sequencing data but often overlooked by other tools. Moreover, we showcase the broad applicability of PhyloAln by generating alignments (completeness mostly larger than 80%, identity larger than 90%) and reconstructing robust phylogenies using real data sets of transcriptomes of ladybird beetles, plastid genes of peppers, or ultraconserved elements of turtles. With these advantages, PhyloAln is expected to facilitate phylogenetic and evolutionary analyses in the omic era. The tool is accessible at https://github.com/huangyh45/PhyloAln.

Structural and Biophysical Dynamics of Fungal Plasma Membrane Proteins and Implications for Echinocandin Action in Candida glabrata

Fungal plasma membrane proteins represent key therapeutic targets for antifungal agents, yet their structure and spatial distribution in the native context remain poorly characterized. Herein, we employ an integrative multimodal approach to elucidate the structural and functional organization of plasma membrane protein complexes in Candida glabrata , focusing on prominent and essential membrane proteins, the polysaccharide synthase β-(1,3)-glucan synthase (GS) and the proton pump Pma1. Cryo-electron tomography (cryo-ET) and live cell imaging reveal that GS and Pma1 are heterogeneously distributed into distinct plasma membrane microdomains. Treatment with caspofungin, an echinocandin antifungal that targets GS, alters the plasma membrane and disrupts the native distribution of GS and Pma1. Based on these findings, we propose a model for echinocandin action that considers how drug interactions with the plasma membrane environment lead to inhibition of GS. Our work underscores the importance of interrogating the structural and dynamic characteristics of fungal plasma membrane proteins in situ to understand function and facilitate precisely targeted development of novel antifungal therapies.

Uncharacterized yeast gene YBR238C, an effector of TORC1 signaling in a mitochondrial feedback loop, accelerates cellular aging via HAP4- and RMD9-dependent mechanisms

Uncovering the regulators of cellular aging will unravel the complexity of aging biology and identify potential therapeutic interventions to delay the onset and progress of chronic, aging-related diseases. In this work, we systematically compared genesets involved in regulating the lifespan of Saccharomyces cerevisiae (a powerful model organism to study the cellular aging of humans) and those with expression changes under rapamycin treatment. Among the functionally uncharacterized genes in the overlap set, YBR238C stood out as the only one downregulated by rapamycin and with an increased chronological and replicative lifespan upon deletion. We show that YBR238C and its paralog RMD9 oppositely affect mitochondria and aging. YBR238C deletion increases the cellular lifespan by enhancing mitochondrial function. Its overexpression accelerates cellular aging via mitochondrial dysfunction. We find that the phenotypic effect of YBR238C is largely explained by HAP4- and RMD9-dependent mechanisms. Furthermore, we find that genetic- or chemical-based induction of mitochondrial dysfunction increases TORC1 (Target of Rapamycin Complex 1) activity that, subsequently, accelerates cellular aging. Notably, TORC1 inhibition by rapamycin (or deletion of YBR238C) improves the shortened lifespan under these mitochondrial dysfunction conditions in yeast and human cells. The growth of mutant cells (a proxy of TORC1 activity) with enhanced mitochondrial function is sensitive to rapamycin whereas the growth of defective mitochondrial mutants is largely resistant to rapamycin compared to wild type. Our findings demonstrate a feedback loop between TORC1 and mitochondria (the TORC1-MItochondria-TORC1 (TOMITO) signaling process) that regulates cellular aging processes. Hereby, YBR238C is an effector of TORC1 modulating mitochondrial function.

Updates to the Alliance of Genome Resources central infrastructure

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

Krisp: A Python package to aid in the design of CRISPR and amplification-based diagnostic assays from whole genome sequencing data

Recent pandemics like COVID-19 highlighted the importance of rapidly developing diagnostics to detect evolving pathogens. CRISPR-Cas technology has recently been used to develop diagnostic assays for sequence-specific recognition of DNA or RNA. These assays have similar sensitivity to the gold standard qPCR but can be deployed as easy to use and inexpensive test strips. However, the discovery of diagnostic regions of a genome flanked by conserved regions where primers can be designed requires extensive bioinformatic analyses of genome sequences. We developed the Python package krisp to aid in the discovery of primers and diagnostic sequences that differentiate groups of samples from each other, using either unaligned genome sequences or a variant call format (VCF) file as input. Krisp has been optimized to handle large datasets by using efficient algorithms that run in near linear time, use minimal RAM, and leverage parallel processing when available. The validity of krisp results has been demonstrated in the laboratory with the successful design of a CRISPR diagnostic assay to distinguish the sudden oak death pathogen Phytophthora ramorum from closely related Phytophthora species. Krisp is released open source under a permissive license with all the documentation needed to quickly design CRISPR-Cas diagnostic assays.

Implication of Stm1 in the protection of eIF5A, eEF2 and tRNA through dormant ribosomes

Background: Dormant ribosomes are typically associated with preservation factors to protect themselves from degradation under stress conditions. Stm1/SERBP1 is one such protein that anchors the 40S and 60S subunits together. Several proteins and tRNAs bind to this complex as well, yet the molecular mechanisms remain unclear. Methods: Here, we reported the cryo-EM structures of five newly identified Stm1/SERBP1-bound ribosomes. Results: These structures highlighted that eIF5A, eEF2, and tRNA might bind to dormant ribosomes under stress to avoid their own degradation, thus facilitating protein synthesis upon the restoration of growth conditions. In addition, Ribo-seq data analysis reflected the upregulation of nutrient, metabolism, and external-stimulus-related pathways in the ∆stm1 strain, suggesting possible regulatory roles of Stm1. Discussion: The knowledge generated from the present work will facilitate in better understanding the molecular mechanism of dormant ribosomes.

A CUG codon-adapted anchor-away toolkit for functional analysis of genes in Candida albicans

Promoter shutoff of essential genes in the diploid Candida albicans has often been insufficient to create tight, conditional null alleles due to leaky expression and has been a stumbling block in pathogenesis research. Moreover, homozygous deletion of non-essential genes has often been problematic due to the frequent aneuploidy in the mutant strains. Rapid, conditional depletion of essential genes by the anchor-away strategy has been successfully employed in Saccharomyces cerevisiae and other model organisms. Here, rapamycin mediates the dimerization of human FK506-binding protein (FKBP12) and FKBP12-rapamycin-binding (FRB) domain-containing target protein, resulting in relocalization to altered sub-cellular locations. In this work, we used the ribosomal protein Rpl13 as the anchor and took two nuclear proteins as targets to construct a set of mutants in a proof-of-principle approach. We first constructed a rapamycin-resistant C. albicans strain by introducing a dominant mutation in the CaTOR1 gene and a homozygous deletion of RBP1, the ortholog of FKBP12, a primary target of rapamycin. The FKBP12 and the FRB coding sequences were then CUG codon-adapted for C. albicans by site-directed mutagenesis. Anchor-away strains expressing the essential TBP1 gene or the non-essential SPT8 gene as FRB fusions were constructed. We found that rapamycin caused rapid cessation of growth of the TBP-AA strain within 15 minutes and the SPT8-AA strain phenocopied the constitutive filamentous phenotype of the spt8Δ/spt8Δ mutant. Thus, the anchor-away toolbox for C. albicans developed here can be employed for genome-wide analysis to identify gene function in a rapid and reliable manner, further accelerating anti-fungal drug development in C. albicans.

IMPORTANCE

Molecular genetic studies thus far have identified ~27% open-reading frames as being essential for the vegetative growth of Candida albicans in rich medium out of a total 6,198 haploid set of open reading frames. However, a major limitation has been to construct rapid conditional alleles of essential C. albicans genes with near quantitative depletion of encoded proteins. Here, we have developed a toolbox for rapid and conditional depletion of genes that would aid studies of gene function of both essential and non-essential genes.

Updates to the Alliance of Genome Resources Central Infrastructure Alliance of Genome Resources Consortium

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively-studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, C. elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and APIs. Here we focus on developments over the last two years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse. We describe our progress towards a central persistent database to support curation, the data modeling that underpins harmonization, and progress towards a state-of-the art literature curation system with integrated Artificial Intelligence and Machine Learning (AI/ML).

Yueomyces silvicola sp. nov., a novel ascomycetous yeast species unable to utilize ammonium, glutamate, and glutamine as sole nitrogen sources

Five yeast strains isolated from tree bark and rotten wood collected in central and southwestern China, together with four Brazilian strains (three from soil and rotting wood collected in an Amazonian rainforest biome and one from Bromeliad collected in Alagoas state) and one Costa Rican strain isolated from a flower beetle, represent a new species closely related with Yueomyces sinensis in Saccharomycetaceae, as revealed by the 26S ribosomal RNA gene D1/D2 domain and the internal transcribed spacer region sequence analysis. The name Yueomyces silvicola sp. nov. is proposed for this new species with the holotype China General Microbiological Culture Collection Center 2.6469 (= Japan Collection of Microorganisms 34885). The new species exhibits a whole-genome average nucleotide identity value of 77.8% with Y. sinensis. The two Yueomyces species shared unique physiological characteristics of being unable to utilize ammonium and the majority of the amino acids, including glutamate and glutamine, as sole nitrogen sources. Among the 20 amino acids tested, only leucine and tyrosine can be utilized by the Yueomyces species. Genome sequence comparison showed that GAT1, which encodes a GATA family protein participating in transcriptional activation of nitrogen-catabolic genes in Saccharomyces cerevisiae, is absent in the Yueomyces species. However, the failure of the Yueomyces species to utilize ammonium, glutamate, and glutamine, which are generally preferred nitrogen sources for microorganisms, implies that more complicated alterations in the central nitrogen metabolism pathway might occur in the genus Yueomyces.

Inter-species association mapping links splice site evolution to METTL16 and SNRNP27K

Eukaryotic genes are interrupted by introns that are removed from transcribed RNAs by splicing. Patterns of splicing complexity differ between species, but it is unclear how these differences arise. We used inter-species association mapping with Saccharomycotina species to correlate splicing signal phenotypes with the presence or absence of splicing factors. Here, we show that variation in 5' splice site sequence preferences correlate with the presence of the U6 snRNA N6-methyladenosine methyltransferase METTL16 and the splicing factor SNRNP27K. The greatest variation in 5' splice site sequence occurred at the +4 position and involved a preference switch between adenosine and uridine. Loss of METTL16 and SNRNP27K orthologs, or a single SNRNP27K methionine residue, was associated with a preference for +4 U. These findings are consistent with splicing analyses of mutants defective in either METTL16 or SNRNP27K orthologs and models derived from spliceosome structures, demonstrating that inter-species association mapping is a powerful orthogonal approach to molecular studies. We identified variation between species in the occurrence of two major classes of 5' splice sites, defined by distinct interaction potentials with U5 and U6 snRNAs, that correlates with intron number. We conclude that variation in concerted processes of 5' splice site selection by U6 snRNA is associated with evolutionary changes in splicing signal phenotypes.

Fungal carboxylate transporters: recent manipulations and applications

Carboxylic acids containing acidic groups with additional keto/hydroxyl-groups or unsaturated bond have displayed great applicability in the food, agricultural, cosmetic, textile, and pharmaceutical industries. The traditional approach for carboxylate production through chemical synthesis is based on petroleum derivatives, resulting in concerns for the environmental complication and energy crisis, and increasing attention has been attracted to the eco-friendly and renewable bio-based synthesis for carboxylate production. The efficient and specific export of target carboxylic acids through the microbial membrane is essential for high productivity, yield, and titer of bio-based carboxylates. Therefore, understanding the characteristics, regulations, and efflux mechanisms of carboxylate transporters will efficiently increase industrial biotechnological production of carboxylic acids. Several transporters from fungi have been reported and used for improved synthesis of target products. The transport activity and substrate specificity are two key issues that need further improvement in the application of carboxylate transporters. This review presents developments in the structural and functional diversity of carboxylate transporters, focusing on the modification and regulation of carboxylate transporters to alter the transport activity and substrate specificity, providing new strategy for transporter engineering in constructing microbial cell factory for carboxylate production. KEY POINTS: • Structures of multiple carboxylate transporters have been predicted. • Carboxylate transporters can efficiently improve production. • Modification engineering of carboxylate transporters will be more popular in the future.

Using machine learning to predict protein-protein interactions between a zombie ant fungus and its carpenter ant host

Parasitic fungi produce proteins that modulate virulence, alter host physiology, and trigger host responses. These proteins, classified as a type of "effector," often act via protein-protein interactions (PPIs). The fungal parasite Ophiocordyceps camponoti-floridani (zombie ant fungus) manipulates Camponotus floridanus (carpenter ant) behavior to promote transmission. The most striking aspect of this behavioral change is a summit disease phenotype where infected hosts ascend and attach to an elevated position. Plausibly, interspecific PPIs drive aspects of Ophiocordyceps infection and host manipulation. Machine learning PPI predictions offer high-throughput methods to produce mechanistic hypotheses on how this behavioral manipulation occurs. Using D-SCRIPT to predict host-parasite PPIs, we found ca. 6000 interactions involving 2083 host proteins and 129 parasite proteins, which are encoded by genes upregulated during manipulated behavior. We identified multiple overrepresentations of functional annotations among these proteins. The strongest signals in the host highlighted neuromodulatory G-protein coupled receptors and oxidation-reduction processes. We also detected Camponotus structural and gene-regulatory proteins. In the parasite, we found enrichment of Ophiocordyceps proteases and frequent involvement of novel small secreted proteins with unknown functions. From these results, we provide new hypotheses on potential parasite effectors and host targets underlying zombie ant behavioral manipulation.

Did the early full genome sequencing of yeast boost gene function discovery?

BACKGROUND

Although the genome of Saccharomyces cerevisiae (S. cerevisiae) was the first one of a eukaryote organism that was fully sequenced (in 1996), a complete understanding of the potential of encoded biomolecular mechanisms has not yet been achieved. Here, we wish to quantify how far the goal of a full list of S. cerevisiae gene functions still is.

RESULTS

The scientific literature about S. cerevisiae protein-coding genes has been mapped onto the yeast genome via the mentioning of names for genomic regions in scientific publications. The match was quantified with the ratio of a given gene name's occurrences to those of any gene names in the article. We find that ~ 230 elite genes with ≥ 75 full publication equivalents (FPEs, FPE = 1 is an idealized publication referring to just a single gene) command ~ 45% of all literature. At the same time, about two thirds of the genes (each with less than 10 FPEs) are described in just 12% of the literature (in average each such gene has just ~ 1.5% of the literature of an elite gene). About 600 genes have not been mentioned in any dedicated article. Compared with other groups of genes, the literature growth rates were highest for uncharacterized or understudied genes until late nineties of the twentieth century. Yet, these growth rates deteriorated and became negative thereafter. Thus, yeast function discovery for previously uncharacterized genes has returned to the level of ~ 1980. At the same time, literature for anyhow well-studied genes (with a threshold T10 (≥ 10 FPEs) and higher) remains steadily growing.

CONCLUSIONS

Did the early full genome sequencing of yeast boost gene function discovery? The data proves that the moment of publishing the full genome in reality coincides with the onset of decline of gene function discovery for previously uncharacterized genes. If the current status of literature about yeast molecular mechanisms can be extrapolated into the future, it will take about another ~ 50 years to complete the yeast gene function list. We found that a small group of scientific journals contributed extraordinarily to publishing early reports relevant to yeast gene function discoveries.

Unlocking the Mysteries of Alpha-N-Terminal Methylation and its Diverse Regulatory Functions

Protein post-translation modifications (PTMs) are a critical regulatory mechanism of protein function. Protein α-N-terminal (Nα) methylation is a conserved PTM across prokaryotes and eukaryotes. Studies of the Nα methyltransferases responsible for Να methylation and their substrate proteins have shown that the PTM involves diverse biological processes, including protein synthesis and degradation, cell division, DNA damage response, and transcription regulation. This review provides an overview of the progress toward the regulatory function of Να methyltransferases and their substrate landscape. More than 200 proteins in humans and 45 in yeast are potential substrates for protein Nα methylation based on the canonical recognition motif, XP[KR]. Based on recent evidence for a less stringent motif requirement, the number of substrates might be increased, but further validation is needed to solidify this concept. A comparison of the motif in substrate orthologs in selected eukaryotic species indicates intriguing gain and loss of the motif across the evolutionary landscape. We discuss the state of knowledge in the field that has provided insights into the regulation of protein Να methyltransferases and their role in cellular physiology and disease. We also outline the current research tools that are key to understanding Να methylation. Finally, challenges are identified and discussed that would aid in unlocking a system-level view of the roles of Να methylation in diverse cellular pathways.

Saccharomyces genome database update: server architecture, pan-genome nomenclature, and external resources

As one of the first model organism knowledgebases, Saccharomyces Genome Database (SGD) has been supporting the scientific research community since 1993. As technologies and research evolve, so does SGD: from updates in software architecture, to curation of novel data types, to incorporation of data from, and collaboration with, other knowledgebases. We are continuing to make steps toward providing the community with an S. cerevisiae pan-genome. Here, we describe software upgrades, a new nomenclature system for genes not found in the reference strain, and additions to gene pages. With these improvements, we aim to remain a leading resource for students, researchers, and the broader scientific community.

Paths to adaptation under fluctuating nitrogen starvation: The spectrum of adaptive mutations in Saccharomyces cerevisiae is shaped by retrotransposons and microhomology-mediated recombination

There are many mechanisms that give rise to genomic change: while point mutations are often emphasized in genomic analyses, evolution acts upon many other types of genetic changes that can result in less subtle perturbations. Changes in chromosome structure, DNA copy number, and novel transposon insertions all create large genomic changes, which can have correspondingly large impacts on phenotypes and fitness. In this study we investigate the spectrum of adaptive mutations that arise in a population under consistently fluctuating nitrogen conditions. We specifically contrast these adaptive alleles and the mutational mechanisms that create them, with mechanisms of adaptation under batch glucose limitation and constant selection in low, non-fluctuating nitrogen conditions to address if and how selection dynamics influence the molecular mechanisms of evolutionary adaptation. We observe that retrotransposon activity accounts for a substantial number of adaptive events, along with microhomology-mediated mechanisms of insertion, deletion, and gene conversion. In addition to loss of function alleles, which are often exploited in genetic screens, we identify putative gain of function alleles and alleles acting through as-of-yet unclear mechanisms. Taken together, our findings emphasize that how selection (fluctuating vs. non-fluctuating) is applied also shapes adaptation, just as the selective pressure (nitrogen vs. glucose) does itself. Fluctuating environments can activate different mutational mechanisms, shaping adaptive events accordingly. Experimental evolution, which allows a wider array of adaptive events to be assessed, is thus a complementary approach to both classical genetic screens and natural variation studies to characterize the genotype-to-phenotype-to-fitness map.

Highly complete long-read genomes reveal pangenomic variation underlying yeast phenotypic diversity

Understanding the genetic causes of trait variation is a primary goal of genetic research. One way that individuals can vary genetically is through variable pangenomic genes: genes that are only present in some individuals in a population. The presence or absence of entire genes could have large effects on trait variation. However, variable pangenomic genes can be missed in standard genotyping workflows, owing to reliance on aligning short-read sequencing to reference genomes. A popular method for studying the genetic basis of trait variation is linkage mapping, which identifies quantitative trait loci (QTLs), regions of the genome that harbor causative genetic variants. Large-scale linkage mapping in the budding yeast Saccharomyces cerevisiae has found thousands of QTLs affecting myriad yeast phenotypes. To enable the resolution of QTLs caused by variable pangenomic genes, we used long-read sequencing to generate highly complete de novo genome assemblies of 16 diverse yeast isolates. With these assemblies, we resolved QTLs for growth on maltose, sucrose, raffinose, and oxidative stress to specific genes that are absent from the reference genome but present in the broader yeast population at appreciable frequency. Copies of genes also duplicate onto chromosomes where they are absent in the reference genome, and we found that these copies generate additional QTLs whose resolution requires pangenome characterization. Our findings show the need for highly complete genome assemblies to identify the genetic basis of trait variation.

Overexpression profiling reveals cellular requirements in the context of genetic backgrounds and environments

Overexpression can help life adapt to stressful environments, making an examination of overexpressed genes valuable for understanding stress tolerance mechanisms. However, a systematic study of genes whose overexpression is functionally adaptive (GOFAs) under stress has yet to be conducted. We developed a new overexpression profiling method and systematically identified GOFAs in Saccharomyces cerevisiae under stress (heat, salt, and oxidative). Our results show that adaptive overexpression compensates for deficiencies and increases fitness under stress, like calcium under salt stress. We also investigated the impact of different genetic backgrounds on GOFAs, which varied among three S. cerevisiae strains reflecting differing calcium and potassium requirements for salt stress tolerance. Our study of a knockout collection also suggested that calcium prevents mitochondrial outbursts under salt stress. Mitochondria-enhancing GOFAs were only adaptive when adequate calcium was available and non-adaptive when calcium was deficient, supporting this idea. Our findings indicate that adaptive overexpression meets the cell's needs for maximizing the organism's adaptive capacity in the given environment and genetic context.

CeGAL: Redefining a Widespread Fungal-Specific Transcription Factor Family Using an In Silico Error-Tracking Approach

In fungi, the most abundant transcription factor (TF) class contains a fungal-specific ‘GAL4-like’ Zn2C6 DNA binding domain (DBD), while the second class contains another fungal-specific domain, known as ‘fungal_trans’ or middle homology domain (MHD), whose function remains largely uncharacterized. Remarkably, almost a third of MHD-containing TFs in public sequence databases apparently lack DNA binding activity, since they are not predicted to contain a DBD. Here, we reassess the domain organization of these ‘MHD-only’ proteins using an in silico error-tracking approach. In a large-scale analysis of ~17,000 MHD-only TF sequences present in all fungal phyla except Microsporidia and Cryptomycota, we show that the vast majority (>90%) result from genome annotation errors and we are able to predict a new DBD sequence for 14,261 of them. Most of these sequences correspond to a Zn2C6 domain (82%), with a small proportion of C2H2 domains (4%) found only in Dikarya. Our results contradict previous findings that the MHD-only TF are widespread in fungi. In contrast, we show that they are exceptional cases, and that the fungal-specific Zn2C6–MHD domain pair represents the canonical domain signature defining the most predominant fungal TF family. We call this family CeGAL, after the highly characterized members: Cep3, whose 3D structure is determined, and GAL4, a eukaryotic TF archetype. We believe that this will not only improve the annotation and classification of the Zn2C6 TF but will also provide critical guidance for future fungal gene regulatory network analyses.

Identification of genetic variants of the industrial yeast Komagataella phaffii (Pichia pastoris) that contribute to increased yields of secreted heterologous proteins

The yeast Komagataella phaffii (formerly called Pichia pastoris) is used widely as a host for secretion of heterologous proteins, but only a few isolates of this species exist and all the commonly used expression systems are derived from a single genetic background, CBS7435 (NRRL Y-11430). We hypothesized that other genetic backgrounds could harbor variants that affect yields of secreted proteins. We crossed CBS7435 with 2 other K. phaffii isolates and mapped quantitative trait loci (QTLs) for secretion of a heterologous protein, β-glucosidase, by sequencing individual segregant genomes. A major QTL mapped to a frameshift mutation in the mannosyltransferase gene HOC1, which gives CBS7435 a weaker cell wall and higher protein secretion than the other isolates. Inactivation of HOC1 in the other isolates doubled β-glucosidase secretion. A second QTL mapped to an amino acid substitution in IRA1 that tripled β-glucosidase secretion in 1-week batch cultures but reduced cell viability, and its effects are specific to this heterologous protein. Our results demonstrate that QTL analysis is a powerful method for dissecting the basis of biotechnological traits in nonconventional yeasts, and a route to improving their industrial performance.

The importance of being the HGNC

The HUGO Gene Nomenclature Committee (HGNC) has been providing standardized symbols and names for human genes since the late 1970s. As funding agencies change their priorities, finding financial support for critical biomedical resources such as the HGNC becomes ever more challenging. In this article, we outline the key roles the HGNC currently plays in aiding communication and the need for these activities to be maintained.

Heme Oxygenase-1 (HMX1) Loss of Function Increases the In-Host Fitness of the Saccharomyces 'boulardii' Probiotic Yeast in a Mouse Fungemia Model

The use of yeast-containing probiotics is on the rise; however, these products occasionally cause fungal infections and possibly even fungemia among susceptible probiotic-treated patients. The incidence of such cases is probably underestimated, which is why it is important to delve deeper into the pathomechanism and the adaptive features of S. ‘boulardii’. Here in this study, the potential role of the gene heme oxygenase-1 (HMX1) in probiotic yeast bloodstream-derived infections was studied by generating marker-free HMX1 deletion mutants with CRISPR/Cas9 technology from both commercial and clinical S. ‘boulardii’ isolates. The six commercial and clinical yeasts used here represented closely related but different genetic backgrounds as revealed by comparative genomic analysis. We compared the wild-type isolates against deletion mutants for their tolerance of iron starvation, hemolytic activity, as well as kidney burden in immunosuppressed BALB/c mice after lateral tail vein injection. Our results reveal that the lack of HMX1 in S. ‘boulardii’ significantly (p < 0.0001) increases the kidney burden of the mice in most genetic backgrounds, while at the same time causes decreased growth in iron-deprived media in vitro. These findings indicate that even a single-gene loss-of-function mutation can, surprisingly, cause elevated fitness in the host during an opportunistic systemic infection. Our findings indicate that the safety assessment of S. ‘boulardii’ strains should not only take strain-to-strain variation into account, but also avoid extrapolating in vitro results to in vivo virulence factor determination.

Harmonizing model organism data in the Alliance of Genome Resources

The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of orthology relationships and the use of common ontologies. The key types of data are alleles and variants, gene function based on gene ontology annotations, phenotypes, association to human disease, gene expression, protein-protein and genetic interactions, and participation in pathways. The information is presented on uniform gene pages that allow facile summarization of information about each gene in each of the 7 organisms covered (budding yeast, roundworm Caenorhabditis elegans, fruit fly, house mouse, zebrafish, brown rat, and human). The harmonized knowledge is freely available on the alliancegenome.org portal, as downloadable files, and by APIs. We expect other existing and emerging knowledge bases to join in the effort to provide the union of useful data and features that each knowledge base currently provides.