Biomedical subjects

Jonas Warringer

Publications and source records attributed to Jonas Warringer.

11 recordsLinked to original sources

PubMed2025

Reproductive Isolation due to Divergent Ecological Selection Is Accompanied by Vast Genomic Instability in Experimentally Evolved Yeast Populations.

Populations evolving independently in divergent environments accumulate genetic differences and potentially evolve reproductive isolation as a by-product of divergence. The speed and mechanisms underlying this process are difficult to investigate because we rarely get the opportunity to witness them in natural settings, and histories of selection and gene flow between populations are often unknown. Here, we experimentally evolved yeast for 1000 generations of evolution in both divergent and parallel environments. At regular time points during experimental evolution, we made crosses between parallel- and divergent-evolving populations to measure postzygotic reproductive isolation (gamete viability). We used whole genome population sequencing to determine the mutational load, the number and types of structural variation, and other genomic features of the parent, F1 and F2 intraspecific hybrids. We found evidence for large-scale phenotypic and genome-wide differentiation in response to divergent laboratory selection. Divergent-selected populations produced hybrids with reduced gamete viability-a classic signature of postzygotic reproductive isolation in the form of hybrid breakdown. Parallel-selected populations, on the other hand, remained more reproductively compatible (with exceptions). We found that F2 hybrid genomes contained vast genomic instability, that is, new structural variants (especially insertions, deletions and interchromosomal translocations) that were not observed in parent and F1 genomes, which is likely a result of chromosome missegregation and recombination errors in hybrid meiosis. Our results provide phenotypic and genomic evidence that partial reproductive isolation evolved due to adaptation to divergent environments, consistent with predictions of ecological speciation theory.

Reproductive Isolation↗

PubMed2025

Predicting natural variation in the yeast phenotypic landscape with machine learning.

Most organismal traits result from the complex interplay of many genetic and environmental factors, making their prediction difficult. Here, we used machine learning (ML) models to explore phenotype predictions for 223 traits measured across 1011 genome-sequenced Saccharomyces cerevisiae strains isolated worldwide. We benchmarked a ML pipeline with multiple linear and non-linear models to predict phenotypes from genotypes and gene expression, and determined gradient boosting machines as the best-performing model. Gene function disruption scores and gene presence/absence emerged as best predictors, suggesting a considerable contribution of the accessory genome in controlling phenotypes. The prediction accuracy broadly varied among phenotypes, with stress resistance being easier to predict compared to growth across nutrients. ML identified relevant genomic features linked to phenotypes, including high-impact variants with established relationships to phenotypes, despite these being rare in the population. Near-perfect accuracies were achieved when other phenomics data mostly in similar conditions were used, suggesting that useful information can be conveyed across phenotypes. Overall, our study underscores the power of ML to interpret the functional outcome of genetic variants.

Genetic Variation↗

PubMed2006

PROPHECY--a yeast phenome database, update 2006.

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics--the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale--connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at http://prophecy.lundberg.gu.se. Via phenotyping of 984 heterozygous diploids for all essential genes the genotypes analysed and presented in PROPHECY have been extended and now include all genes in the yeast genome. Further, phenotypic data from gene overexpression of 574 membrane spanning proteins has recently been included. To facilitate the interpretation of quantitative phenotypic data we have developed a new phenotype display option, the Comparative Growth Curve Display, where growth curve differences for a large number of mutants compared with the wild type are easily revealed. In addition, PROPHECY now offers a more informative and intuitive first-sight display of its phenotypic data via its new summary page. We have also extended the arsenal of data analysis tools to include dynamic visualization of phenotypes along individual chromosomes. PROPHECY is an initiative to enhance the growing field of phenome bioinformatics.

Chromosomes, Fungal↗

PubMed2006

Evolutionary constraints on yeast protein size.

BACKGROUND: Despite a strong evolutionary pressure to reduce genome size, proteins vary in length over a surprisingly wide range also in very compact genomes. Here we investigated the evolutionary forces that act on protein size in the yeast Saccharomyces cerevisiae utilizing a system-wide bioinformatics approach. Data on yeast protein size was compared to global experimental data on protein expression, phenotypic pleiotropy, protein-protein interactions, protein evolutionary rate and biochemical classification. RESULTS: Comparing the experimentally determined abundance of individual proteins, highly expressed proteins were found to be consistently smaller than lowly expressed proteins, in accordance with the biosynthetic cost minimization hypothesis. Yeast proteins able to maintain a high expression level despite a large size tended to belong to a very distinct set of protein families, notably nuclear transport and translation initiation/elongation. Large proteins have significantly more protein-protein interactions than small proteins, suggesting that a requirement for multiple interaction domains may constitute a positive selective pressure for large protein size in yeast. The higher frequency of protein-protein interactions in large proteins was not accompanied by a higher phenotypic pleiotropy. Hence, the increase in interactions may not reflect an increase in function differentiation. Proteins of different sizes also evolved at similar rates. Finally, whereas the biological process involved was found to have little influence on protein size the biochemical activity exerted by the protein represented a dominant factor. More than one third of all biochemical activity classes were enriched in one or more size intervals. CONCLUSION: In yeast, there is an inverse relationship between protein size and protein expression such that highly expressed proteins tend to be of smaller size. Also, protein size is moderately affected by protein connectivity and strongly affected by biochemical activity. Phenotypic pleiotropy does not seem to affect protein size.

Amino Acid Sequence↗

PubMed2006

Phenotypic effects of membrane protein overexpression in Saccharomyces cerevisiae.

Large-scale protein overexpression phenotype screens provide an important complement to the more common gene knockout screens. Here, we have targeted the so far poorly understood Saccharomyces cerevisiae membrane proteome and report growth phenotypes for a strain collection overexpressing approximately 600 C-terminally tagged integral membrane proteins grown both under normal and three different stress conditions. Although overexpression of most membrane proteins reduce the growth rate in synthetic defined medium, we identify a large number of proteins that, when overexpressed, confer specific resistance to various stress conditions. Our data suggest that regulation of glycosylphosphatidylinositol anchor biosynthesis and the Na(+)/K(+) homeostasis system constitute major downstream targets of the yeast PKA/RAS pathway and point to a possible connection between the early secretory pathway and the cells' response to oxidative stress. We also have quantified the expression levels for >550 membrane proteins, facilitating the choice of well expressing proteins for future functional and structural studies.

Caffeine↗

PubMed2006

Involvement of yeast YOL151W/GRE2 in ergosterol metabolism.

The Saccharomyces cerevisiae gene YOL151W/GRE2 is widely used as a model gene in studies on yeast regulatory responses to osmotic and oxidative stress. Nevertheless, information concerning the physiological role of this enzyme, a distant homologue of mammalian 3-beta-hydroxysteroid dehydrogenases, is scarce. Combining quantitative phenotypic profiling and protein expression analysis studies, we here report the involvement of yeast Gre2p in ergosterol metabolism. Growth was significantly and exclusively reduced in gre2Delta strains subjected to environmental stress straining the cell membrane. Furthermore, whereas no compensatory mechanisms were activated due to loss of Gre2p during growth in favourable conditions (synthetic defined media, no stress), a striking and highly specific induction of the ergosterol biosynthesis pathway, represented by the enzymes Erg10p, Erg19p and Erg6p, was observed in gre2Delta during growth in a stress condition in which lack of Gre2p significantly affects growth. Involvement of Gre2p in ergosterol metabolism was confirmed by application of an array of selective inhibitors of lipid biosynthesis, as gre2Delta displayed vastly impaired tolerance exclusively to agents targeting the ergosterol biosynthesis. The approach outlined here, combining broad-spectrum phenotypic profiling, expression analysis during conditions reducing the growth of the mutant and functional confirmation by application of highly selective inhibitors, may prove a valuable tool in gene functional analysis.

Brefeldin A↗

PubMed2006

Genetic pleiotropy in Saccharomyces cerevisiae quantified by high-resolution phenotypic profiling.

Genetic pleiotropy, the ability of a mutation in a single gene to give rise to multiple phenotypic outcomes, constitutes an important but incompletely understood biological phenomenon. We used a high-resolution and high-precision phenotypic profiling approach to quantify the fitness contribution of genes on the five smallest yeast chromosomes during different forms of environmental stress, selected to probe a wide diversity of physiological features. We found that the extent of pleiotropy is much higher than previously claimed; 17% of the yeast genes were pleiotropic whereof one-fifth were hyper-pleiotropic. Pleiotropic genes preferentially participate in functions related to determination of protein fate, cell growth and morphogenesis, signal transduction and transcription. Contrary to what has earlier been proposed we did not find experimental evidence for slower evolutionary rate of pleiotropic genes/proteins. We also refute the existence of phenotypic islands along chromosomes but report on a remarkable loss both of pleiotropy and of phenotypic penetrance towards chromosomal ends. Thus, the here reported features of pleiotropy both have implications on our understanding of evolutionary processes as well as the mechanisms underlying disease.

Genes, Fungal↗

PubMed2006

Physiological importance and identification of novel targets for the N-terminal acetyltransferase NatB.

The N-terminal acetyltransferase NatB in Saccharomyces cerevisiae consists of the catalytic subunit Nat3p and the associated subunit Mdm20p. We here extend our present knowledge about the physiological role of NatB by a combined proteomics and phenomics approach. We found that strains deleted for either NAT3 or MDM20 displayed different growth rates and morphologies in specific stress conditions, demonstrating that the two NatB subunits have partly individual functions. Earlier reported phenotypes of the nat3Delta strain have been associated with altered functionality of actin cables. However, we found that point mutants of tropomyosin that suppress the actin cable defect observed in nat3Delta only partially restores wild-type growth and morphology, indicating the existence of functionally important acetylations unrelated to actin cable function. Predicted NatB substrates were dramatically overrepresented in a distinct set of biological processes, mainly related to DNA processing and cell cycle progression. Three of these proteins, Cac2p, Pac10p, and Swc7p, were identified as true NatB substrates. To identify N-terminal acetylations potentially important for protein function, we performed a large-scale comparative phenotypic analysis including nat3Delta and strains deleted for the putative NatB substrates involved in cell cycle regulation and DNA processing. By this procedure we predicted functional importance of the N-terminal acetylation for 31 proteins.

Acetylation↗

PubMed2005

PROPHECY--a database for high-resolution phenomics.

The rapid recent evolution of the field phenomics--the genome-wide study of gene dispensability by quantitative analysis of phenotypes--has resulted in an increasing demand for new data analysis and visualization tools. Following the introduction of a novel approach for precise, genome-wide quantification of gene dispensability in Saccharomyces cerevisiae we here announce a public resource for mining, filtering and visualizing phenotypic data--the PROPHECY database. PROPHECY is designed to allow easy and flexible access to physiologically relevant quantitative data for the growth behaviour of mutant strains in the yeast deletion collection during conditions of environmental challenges. PROPHECY is publicly accessible at http://prophecy.lundberg.gu.se.

Computer Graphics↗

PubMed2003

High-resolution yeast phenomics resolves different physiological features in the saline response.

We present a methodology for gene functional prediction based on extraction of physiologically relevant growth variables from all viable haploid yeast knockout mutants. This quantitative phenomics approach, here applied to saline cultivation, identified marginal but functionally important phenotypes and allowed the precise determination of time to adapt to an environmental challenge, rate of growth, and efficiency of growth. We identified approximately 500 salt-sensitive gene deletions, the majority of which were previously uncharacterized and displayed salt sensitivity for only one of the three physiological features. We also report a high correlation to protein-protein interaction data; in particular, several salt-sensitive subcellular networks indicating functional modules were revealed. In contrast, no correlation was found between gene dispensability and gene expression. It is proposed that high-resolution phenomics will be instrumental in systemwide descriptions of intragenomic functional networks.

Cytoskeleton↗

PubMed2003

Automated screening in environmental arrays allows analysis of quantitative phenotypic profiles in Saccharomyces cerevisiae.

A methodology for large-scale automated phenotypic profiling utilizing quantitative changes in yeast growth has been tested and applied to the analysis of some commonly used laboratory strains. This yeast-adjusted methodology is based on microcultivation in 350 microl liquid medium, where growth is frequently optically recorded, followed by automated extraction of relevant variables from obtained growth curves. We report that cultivation at this micro-scale displayed overall growth features and protein expression pattern highly similar to growth in well aerated medium-scale (10 ml) culture. However, differences were also encountered, mainly relating to the respiratory potential and the production of stress-induced proteins. Quantitative phenotypic profiles for the laboratory yeast strains W303, FY1679 and CEN-PK.2 were screened for in environmental arrays, including 98 different conditions composed of low, medium and high concentrations of 33 growth inhibitors. We introduce the concepts phenotypic index(rate) and phenotypic index(stationary), which relate to changes in rate of growth and the stationary phase optical density increment, respectively, in a particular environment relative a reference strain. The laboratory strains presented selective phenotypic profiles in both phenotypic indexes and the two features appeared in many cases to be independent characteristics. We propose the utilization of this methodology in large-scale screening of the complete collection of yeast deletion mutants.

Fungal Proteins↗