A fundamental goal in biology is to achieve a mechanistic understanding of how and to what extent ecological variation imposes selection for distinct traits and favors the fixation of specific genetic variants. Key to such an understanding is the detailed mapping of the natural genomic and phenomic space and a bridging of the gap that separates these worlds. Here we chart a high-resolution map of natural trait variation in one of the most important genetic model organisms, the budding yeast Saccharomyces cerevisiae, and its closest wild relatives and trace the genetic basis and timing of major phenotype changing events in its recent history. We show that natural trait variation in S. cerevisiae exceeds that of its relatives, despite limited genetic variation, and follows the population history rather than the source environment. In particular, the West African population is phenotypically unique, with an extreme abundance of low-performance alleles, notably a premature translational termination signal in GAL3 that cause inability to utilize galactose. Our observations suggest that many S. cerevisiae traits may be the consequence of genetic drift rather than selection, in line with the assumption that natural yeast lineages are remnants of recent population bottlenecks. Disconcertingly, the universal type strain S288C was found to be highly atypical, highlighting the danger of extrapolating gene-trait connections obtained in mosaic, lab-domesticated lineages to the species as a whole. Overall, this study represents a step towards an in-depth understanding of the causal relationship between co-variation in ecology, selection pressure, natural traits, molecular mechanism, and alleles in a key model organism.

Background Spinal muscular atrophy is a rare neuromuscular disorder with a spectrum of severity related to age at onset and the number of SMN2 gene copies. Infantile-onset (≤ 6 months of age) is the most severe spinal muscular atrophy and is the leading monogenetic cause of infant mortality; patients with later-onset (> 6 months of age) spinal muscular atrophy can survive into adulthood. Nusinersen is a new treatment for spinal muscular atrophy. Objective The objective of this study was to evaluate the cost effectiveness of nusinersen for the treatment of patients with infantile-onset spinal muscular atrophy and later-onset spinal muscular atrophy in Sweden. Methods One Markov cohort health-state transition model was developed for each population. The infantile-onset and later-onset models were based on the efficacy results from the ENDEAR phase III trial and the CHERISH phase III trial, respectively. The cost effectiveness of nusinersen in both models was compared with standard of care in Sweden. Results For a time horizon of 40 years in the infantile-onset model and 80 years in the later-onset model, treatment with nusinersen resulted in 3.86 and 9.54 patient incremental quality-adjusted life-years and 0.02 and 2.39 caregiver incremental quality-adjusted life-years and an incremental cost of 21.9 and 38.0 million SEK (Swedish krona), respectively. These results translated into incremental cost-effectiveness ratios (including caregiver quality-adjusted life-years) of 5.64 million SEK (€551,300) and 3.19 million SEK (€311,800) per quality-adjusted life-year gained in the infantile-onset model and later-onset model, respectively. Conclusions Treatment with nusinersen resulted in overall survival and quality-adjusted life-year benefits but with incremental costs above 21 million SEK (€2 million) [mainly associated with maintenance treatment with nusinersen over a patient's lifespan]. Nusinersen was not cost effective when using a willingness-to-pay threshold of 2 million SEK (€195,600), which has been considered in a recent discussion by the Dental and Pharmaceutical Benefits Agency as a reasonable threshold for rare disease. Nonetheless, nusinersen gained reimbursement in Sweden in 2017 for paediatric patients (below 18 years old) with spinal muscular atrophy type I-IIIa.

In this study, we looked at the cost outcome when performing prostatectomies by robot-assisted laparoscopic technique compared with open surgery in Sweden. We found that the robot-assisted procedure was associated with a higher mean cost.

Single-channel optical density measurements of population growth are the dominant large scale phenotyping methodology for bridging the gene-function gap in yeast. However, a substantial amount of the genetic variation induced by single allele, single gene or double gene knock-out technologies fail to manifest in detectable growth phenotypes under conditions readily testable in the laboratory. Thus, new high-throughput phenotyping technologies capable of providing information about molecular level consequences of genetic variation are sorely needed. Here we report a protocol for high-throughput Fourier transform infrared spectroscopy (FTIR) measuring biochemical fingerprints of yeast strains. It includes high-throughput cultivation for FTIR spectroscopy, FTIR measurements and spectral pre-treatment to increase measurement accuracy. We demonstrate its capacity to distinguish not only yeast genera, species and populations, but also strains that differ only by a single gene, its excellent signal-to-noise ratio and its relative robustness to measurement bias. Finally, we illustrated its applicability by determining the FTIR signatures of all viable Saccharomyces cerevisiae single gene knock-outs corresponding to lipid biosynthesis genes. Many of the examined knock-out strains showed distinct, highly reproducible FTIR phenotypes despite having no detectable growth phenotype. These phenotypes were confirmed by conventional lipid analysis and could be linked to specific changes in lipid composition. We conclude that the introduced protocol is robust to noise and bias, possible to apply on a very large scale, and capable of generating biologically meaningful biochemical fingerprints that are strain specific, even when strains lack detectable growth phenotypes. Thus, it has a substantial potential for application in the molecular functionalization of the yeast genome.