Jonas Warringer

This study reprograms yeast telomeres to human-like sequences and identifies adaptive mutations that allow survival and fitness recovery.

This study shows that divergent ecological selection in yeast leads to reproductive isolation and genomic instability through hybrid breakdown and structural variants.

This study develops a parallelized ALE platform to evolve wine yeasts with enhanced metabolic traits, finding that expanded replicates and lineages improve the chances of evolving improved strains with desirable industrial performance.

This study uses machine learning to predict yeast phenotypes from genotypes, finding gradient boosting machines perform best and accessory genome contributes significantly.

This study quantifies mutation rates and spectra in yeast under rapamycin and hydroxyurea treatments, revealing distinct mutagenic effects and their impact on cell fitness.

This paper predicts the evolution of fitness-costly traits by designing selection niches using metabolic models and validates it in yeast for increased aroma compound secretion.

The paper investigates mutagenic mechanisms of cancer-associated DNA polymerase ε alleles, showing that exonuclease domain mutations cause ultra-mutagenesis with mutation patterns similar to cancer Signature 14.

Aborting meiosis followed by return-to-growth promotes genome-wide recombination in sterile yeast hybrids, enabling adaptation and genetic mapping.

The paper identifies intragenic repeat expansions in yeast that influence chronological aging by altering cellular metabolism and environmental interaction.

This paper predicts antibiotic resistance in E. coli from whole genome sequences using machine learning, achieving high accuracy without prior knowledge of resistance mechanisms.

This study introduces a high-throughput experimental framework to screen genetic factors affecting conjugation-based antibiotic resistance transmission in E. coli.

The paper investigates how standing and de novo genetic variants contribute to drug adaptation in yeast, finding they act on shared molecular targets but via different mechanisms.

The paper investigates how clonal heterogeneity and genetic variation influence antimicrobial resistance in yeast, showing that both pre-existing and de novo mutations contribute to fitness and adaptation.

This study compares structural genome dynamics between domesticated and wild yeasts using long-read sequencing, revealing differences in rearrangement rates and types.

The paper predicts quantitative traits in yeast with high accuracy using family data and genetic variants, showing that close relatives improve predictions more than large cohorts.

This paper introduces Phased Outbred Lines (POLs) to decompose trait variation in diploid organisms, achieving high heritability and precise estimation of genetic components in yeast.

The paper introduces a high-throughput microbial phenomics framework that enables accurate and scalable growth phenotype analysis in bakers yeast.