Recent evidence demonstrates that novel protein-coding genes can arise de novo from nongenic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of non-genic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Here, we systematically characterize how these de novo emerging coding sequences impact fitness in budding yeast. Disruption of emerging sequences is generally inconsequential for fitness in the laboratory and in natural populations. Overexpression of emerging sequences, however, is enriched in adaptive fitness effects compared to overexpression of established genes. We find that adaptive emerging sequences tend to encode putative transmembrane domains, and that thymine-rich intergenic regions harbor a widespread potential to produce transmembrane domains. These findings, together with in-depth examination of the de novo emerging YBR196C-A locus, suggest a novel evolutionary model whereby adaptive transmembrane polypeptides emerge de novo from thymine-rich nongenic regions and subsequently accumulate changes molded by natural selection.

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Microbial growth characteristics have long been used to investigate fundamental questions of biology. Colony-based high-throughput screens enable parallel fitness estimation of thousands of individual strains using colony growth as a proxy for fitness. However, fitness estimation is complicated by spatial biases affecting colony growth, including uneven nutrient distribution, agar surface irregularities, and batch effects. Analytical methods that have been developed to correct for these spatial biases rely on the following assumptions: (1) that fitness effects are normally distributed, and (2) that most genetic perturbations lead to minor changes in fitness. Although reasonable for many applications, these assumptions are not always warranted and can limit the ability to detect small fitness effects. Beneficial fitness effects, in particular, are notoriously difficult to detect under these assumptions. Here, we developed the linear interpolation-based detector (LI Detector) framework to enable sensitive colony-based screening without making prior assumptions about the underlying distribution of fitness effects. The LI Detector uses a grid of reference colonies to assign a relative fitness value to every colony on the plate. We show that the LI Detector is effective in correcting for spatial biases and equally sensitive toward increase and decrease in fitness. LI Detector offers a tunable system that allows the user to identify small fitness effects with unprecedented sensitivity and specificity. LI Detector can be utilized to develop and refine gene–gene and gene–environment interaction networks of colony-forming organisms, including yeast, by increasing the range of fitness effects that can be reliably detected.

De novo gene birth is the process by which new genes emerge in sequences that were previously noncoding. Over the past decade, researchers have taken advantage of the power of yeast as a model and a tool to study the evolutionary mechanisms and physiological implications of de novo gene birth. We summarize the mechanisms that have been proposed to explicate how noncoding sequences can become protein‐coding genes, highlighting the discovery of pervasive translation of the yeast transcriptome and its presumed impact on evolutionary innovation. We summarize current best practices for the identification and characterization of de novo genes. Crucially, we explain that the field is still in its nascency, with the physiological roles of most young yeast de novo genes identified thus far still utterly unknown. We hope this review inspires researchers to investigate the true contribution of de novo gene birth to cellular physiology and phenotypic diversity across yeast strains and species.

Falls are a leading cause of injury and mortality among adults over the age of 65 years. Given the strong relation between fear of falling and fall risk, identification of the mechanisms that underlie anxiety-related changes in postural control may pave the way to the development of novel therapeutic strategies aimed at reducing fall risk in older adults. First, we review potential mechanisms underlying anxiety-mediated changes in postural control in older adults with and without neurological conditions. We then present a system that allows for the simultaneous recording of neural, physiological, and behavioral data in an immersive virtual reality (VR) environment while implementing sensory and mechanical perturbations to evaluate alterations in sensorimotor integration under conditions with high postural threat. We also discuss applications of VR in minimizing falls in older adults and potential future studies.

In budding yeast, the Met15 enzyme has long been assumed to be the sole homocysteine synthase, facilitating de novo synthesis of sulfur-containing organic compounds (organosulfurs) from inorganic precursors. Here we show that an alternative homocysteine synthase encoded by the previously uncharacterized gene YLL058W supports growth of mutants lacking MET15 in the absence of exogenous organosulfurs. This growth is observed specifically when cells are deposited in an automated fashion to seed colonies, but not with traditional cell propagation techniques such as thick patches of cells or liquid cultures. We show that the lack of growth in these contexts, which has historically justified the status of MET15 as a classic auxotrophic marker, is largely due to toxic levels of hydrogen sulfide accumulation rather than an inability to perform de novo homocysteine biosynthesis. These data have broad implications for investigations of sulfur starvation/metabolism, including studies of aging and emerging cancer therapeutics.

LI Detector's imageanalyzer function makes the use of the MATLAB Colony Analyzer Toolkit to generate colony size estimations from image files.