Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

When grown on solid substrates, different microorganisms often form colonies with very specific morphologies. Whereas the pioneers of microbiology often used colony morphology to discriminate between species and strains, the phenomenon has not received much attention recently. In this study, we use a genome-wide assay in the model yeast Saccharomyces cerevisiae to identify all genes that affect colony morphology. We show that several major signalling cascades, including the MAPK, TORC, SNF1 and RIM101 pathways play a role, indicating that morphological changes are a reaction to changing environments. Other genes that affect colony morphology are involved in protein sorting and epigenetic regulation. Interestingly, the screen reveals only few genes that are likely to play a direct role in establishing colony morphology, with one notable example being FLO11, a gene encoding a cell-surface adhesin that has already been implicated in colony morphology, biofilm formation, and invasive and pseudohyphal growth. Using a series of modified promoters for fine-tuning FLO11 expression, we confirm the central role of Flo11 and show that differences in FLO11 expression result in distinct colony morphologies. Together, our results provide a first comprehensive look at the complex genetic network that underlies the diversity in the morphologies of yeast colonies.

In addition to Sanger sequencing, next-generation sequencing of gene panels and exomes has emerged as a standard diagnostic tool in many laboratories. However, these captures can miss regions, have poor efficiency, or capture pseudogenes, which hamper proper diagnoses. One such example is the primary immunodeficiency-associated gene IKBKG. Its pseudogene IKBKGP1 makes traditional capture methods aspecific. We therefore developed a long-range PCR method to efficiently target IKBKG, as well as two associated genes (IRAK4 and MYD88), while bypassing the IKBKGP1 pseudogene. Sequencing accuracy was evaluated using both conventional short-read technology and a newer long-read, single-molecule sequencer. Different mapping and variant calling options were evaluated in their capability to bypass the pseudogene using both sequencing platforms. Based on these evaluations, we determined a robust diagnostic application for unambiguous sequencing and variant calling in IKBKG, IRAK4, and MYD88. This method allows rapid identification of selected primary immunodeficiency diseases in patients suffering from life-threatening invasive pyogenic bacterial infections.

The positions of nucleosomes across the genome influence several cellular processes, including gene transcription. However, our understanding of the factors dictating where nucleosomes are located and how this affects gene regulation is still limited. Here, we perform an extensive in vivo study to investigate the influence of the neighboring chromatin structure on local nucleosome positioning and gene expression. Using truncated versions of the Saccharomyces cerevisiae URA3 gene, we show that nucleosome positions in the URA3 promoter are at least partly determined by the local DNA sequence, with so-called ‘antinucleosomal elements’ like poly(dA:dT) tracts being key determinants of nucleosome positions. In addition, we show that changes in the nucleosome positions in the URA3 promoter strongly affect the promoter activity. Most interestingly, in addition to demonstrating the effect of the local DNA sequence, our study provides novel in vivo evidence that nucleosome positions are also affected by the position of neighboring nucleosomes. Nucleosome structure may therefore be an important selective force for conservation of gene order on a chromosome, because relocating a gene to another genomic position (where the positions of neighboring nucleosomes are different from the original locus) can have dramatic consequences for the gene's nucleosome structure and thus its expression.