Lorenzo Tattini

Response to divergent selection on meiotic recombination in Saccharomyces cerevisiae

The paper uses experimental evolution in yeast to study how recombination rates change under divergent selection, finding increased and decreased rates in selected lineages.

Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

This paper presents a workflow using XGBoost, LightGBM, and TabNet to classify variants in tumour-only data, showing improved accuracy across ancestries and tumour types.

μSeq: Universal mutation rate quantification via deep sequencing of a single clonal expansion.

This paper introduces μSeq, a method for accurately quantifying mutation rates using deep sequencing of single clonal expansions, showing it outperforms existing methods in robustness and accuracy.

Building pangenome graphs

This paper introduces PGGB, a pipeline for building pangenome graphs that includes all variation without bias, enabling variation detection, conservation measurement, recombination event detection, and phylogenetic inference.

142 telomere-to-telomere assemblies reveal the genome structural landscape in Saccharomyces cerevisiae

This paper presents 142 high-quality yeast genomes to improve pangenome understanding, identifying structural variants and complex genomic regions.

Aborting meiosis overcomes hybrid sterility

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

Accurate tracking of the mutational landscape of diploid hybrid genomes

The paper introduces MuLoYDH, a method to accurately track mutations in yeast diploid hybrids, revealing genetic background effects and loss-of-heterozygosity patterns.