Gianni Liti

CRISpy-pop designs and predicts CRISPR/Cas9 guide RNA activity across diverse yeast and bacterial strains, including human genome cross-referencing for biosafety.

The paper analyzes mitochondrial and nuclear genomes of Saccharomyces cerevisiae to show discordant evolutionary patterns between the two genomes.

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

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

The paper analyzes the genetic distribution of Saccharomyces eubayanus and finds that Patagonian lineages likely originated the species, which then dispersed globally.

simuG generates simulated genomes with predefined and random variants for benchmarking genomic analyses.

LRSDAY streamlines long-read sequencing analysis for yeasts, producing high-quality genome assemblies and annotations for S. cerevisiae and other eukaryotes.

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

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

The paper evaluates nanopore-only genome assemblies of yeast isolates using MinION, showing improved contiguity and structural variant detection compared to Illumina-only assemblies.

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.