Integrative detection of genome-wide translation using iRibo.

Ribosome profiling is a sequencing technique that provides a global picture of translation across a genome. Here, we present iRibo, a software program for integrating any number of ribosome profiling samples to obtain sensitive inference of annotated or unannotated translated open reading frames. We describe the process of using iRibo to generate a species' translatome from a set of ribosome profiling samples using S. cerevisiae as an example. For complete details on the use and execution of this protocol, please refer to Wacholder et al. (2023).1.

Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry.

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here, we leveraged recent advances in ribosome profiling and MS to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly expressed to be detected by shotgun MS at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.

A vast evolutionarily transient translatome contributes to phenotype and fitness.

Translation is the process by which ribosomes synthesize proteins. Ribosome profiling recently revealed that many short sequences previously thought to be noncoding are pervasively translated. To identify protein-coding genes in this noncanonical translatome, we combine an integrative framework for extremely sensitive ribosome profiling analysis, iRibo, with high-powered selection inferences tailored for short sequences. We construct a reference translatome for Saccharomyces cerevisiae comprising 5,400 canonical and almost 19,000 noncanonical translated elements. Only 14 noncanonical elements were evolving under detectable purifying selection. A representative subset of translated elements lacking signatures of selection demonstrated involvement in processes including DNA repair, stress response, and post-transcriptional regulation. Our results suggest that most translated elements are not conserved protein-coding genes and contribute to genotype-phenotype relationships through fast-evolving molecular mechanisms.

Biological Factors and Statistical Limitations Prevent Detection of Most Noncanonical Proteins by Mass Spectrometry.

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here we leveraged recent advances in ribosome profiling and mass spectrometry to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly-expressed to be detected by shotgun mass spectrometry at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for four noncanonical proteins in mass spectrometry data, which were also supported by evolution and translation data. These results illustrate the power of mass spectrometry to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly-expressed proteins.

On the illusion of auxotrophy: met15Δ yeast cells can grow on inorganic sulfur, thanks to the previously uncharacterized homocysteine synthase Yll058w.

Organisms must either synthesize or assimilate essential organic compounds to survive. The homocysteine synthase Met15 has been considered essential for inorganic sulfur assimilation in yeast since its discovery in the 1970s. As a result, MET15 has served as a genetic marker for hundreds of experiments that play a foundational role in eukaryote genetics and systems biology. Nevertheless, we demonstrate here through structural and evolutionary modeling, in vitro kinetic assays, and genetic complementation, that an alternative homocysteine synthase encoded by the previously uncharacterized gene YLL058W enables cells lacking Met15 to assimilate enough inorganic sulfur for survival and proliferation. These cells however fail to grow in patches or liquid cultures unless provided with exogenous methionine or other organosulfurs. We show that this growth failure, which has historically justified the status of MET15 as a classic auxotrophic marker, is largely explained by toxic accumulation of the gas hydrogen sulfide because of a metabolic bottleneck. When patched or cultured with a hydrogen sulfide chelator, and when propagated as colony grids, cells without Met15 assimilate inorganic sulfur and grow, and cells with Met15 achieve even higher yields. Thus, Met15 is not essential for inorganic sulfur assimilation in yeast. Instead, MET15 is the first example of a yeast gene whose loss conditionally prevents growth in a manner that depends on local gas exchange. Our results have broad implications for investigations of sulfur metabolism, including studies of stress response, methionine restriction, and aging. More generally, our findings illustrate how unappreciated experimental variables can obfuscate biological discovery.

Origins, evolution, and physiological implications of de novo genes in yeast.

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.

Evolutionary Characterization of the Short Protein SPAAR.

Microproteins (<100 amino acids) are receiving increasing recognition as important participants in numerous biological processes, but their evolutionary dynamics are poorly understood. SPAAR is a recently discovered microprotein that regulates muscle regeneration and angiogenesis through interactions with conserved signaling pathways. Interestingly, SPAAR does not belong to any known protein family and has known homologs exclusively among placental mammals. This lack of distant homology could be caused by challenges in homology detection of short sequences, or it could indicate a recent de novo emergence from a noncoding sequence. By integrating syntenic alignments and homology searches, we identify SPAAR orthologs in marsupials and monotremes, establishing that SPAAR has existed at least since the emergence of mammals. SPAAR shows substantial primary sequence divergence but retains a conserved protein structure. In primates, we infer two independent evolutionary events leading to the de novo origination of 5' elongated isoforms of SPAAR from a noncoding sequence and find evidence of adaptive evolution in this extended region. Thus, SPAAR may be of ancient origin, but it appears to be experiencing continual evolutionary innovation in mammals.

De novo emergence of adaptive membrane proteins from thymine-rich genomic sequences.

Recent evidence demonstrates that novel protein-coding genes can arise de novo from non-genic 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 non-genic regions and subsequently accumulate changes molded by natural selection.

Finding and extending ancient simple sequence repeat-derived regions in the human genome.

BACKGROUND: Previously, 3% of the human genome has been annotated as simple sequence repeats (SSRs), similar to the proportion annotated as protein coding. The origin of much of the genome is not well annotated, however, and some of the unidentified regions are likely to be ancient SSR-derived regions not identified by current methods. The identification of these regions is complicated because SSRs appear to evolve through complex cycles of expansion and contraction, often interrupted by mutations that alter both the repeated motif and mutation rate. We applied an empirical, kmer-based, approach to identify genome regions that are likely derived from SSRs. RESULTS: The sequences flanking annotated SSRs are enriched for similar sequences and for SSRs with similar motifs, suggesting that the evolutionary remains of SSR activity abound in regions near obvious SSRs. Using our previously described P-clouds approach, we identified 'SSR-clouds', groups of similar kmers (or 'oligos') that are enriched near a training set of unbroken SSR loci, and then used the SSR-clouds to detect likely SSR-derived regions throughout the genome. CONCLUSIONS: Our analysis indicates that the amount of likely SSR-derived sequence in the human genome is 6.77%, over twice as much as previous estimates, including millions of newly identified ancient SSR-derived loci. SSR-clouds identified poly-A sequences adjacent to transposable element termini in over 74% of the oldest class of Alu (roughly, AluJ), validating the sensitivity of the approach. Poly-A's annotated by SSR-clouds also had a length distribution that was more consistent with their poly-A origins, with mean about 35 bp even in older Alus. This work demonstrates that the high sensitivity provided by SSR-Clouds improves the detection of SSR-derived regions and will enable deeper analysis of how decaying repeats contribute to genome structure.

Inference of transposable element ancestry.

Most common methods for inferring transposable element (TE) evolutionary relationships are based on dividing TEs into subfamilies using shared diagnostic nucleotides. Although originally justified based on the "master gene" model of TE evolution, computational and experimental work indicates that many of the subfamilies generated by these methods contain multiple source elements. This implies that subfamily-based methods give an incomplete picture of TE relationships. Studies on selection, functional exaptation, and predictions of horizontal transfer may all be affected. Here, we develop a Bayesian method for inferring TE ancestry that gives the probability that each sequence was replicative, its frequency of replication, and the probability that each extant TE sequence came from each possible ancestral sequence. Applying our method to 986 members of the newly-discovered LAVA family of TEs, we show that there were far more source elements in the history of LAVA expansion than subfamilies identified using the CoSeg subfamily-classification program. We also identify multiple replicative elements in the AluSc subfamily in humans. Our results strongly indicate that a reassessment of subfamily structures is necessary to obtain accurate estimates of mutation processes, phylogenetic relationships and historical times of activity.

Genome-wide congealing and rapid transitions across the speciation continuum during speciation with gene flow.

Our current understanding of speciation is often based on considering a relatively small number of genes, sometimes in isolation of one another. Here, we describe a possible emergent genome process involving the aggregate effect of many genes contributing to the evolution of reproductive isolation across the speciation continuum. When a threshold number of divergently selected mutations of modest to low fitness effects accumulate between populations diverging with gene flow, nonlinear transitions can occur in which levels of adaptive differentiation, linkage disequilibrium, and reproductive isolation dramatically increase. In effect, the genomes of the populations start to "congeal" into distinct entities representing different species. At this stage, reproductive isolation changes from being a characteristic of specific, divergently selected genes to a property of the genome. We examine conditions conducive to such genome-wide congealing (GWC), describe how to empirically test for GWC, and highlight a putative empirical example involving Rhagoletis fruit flies. We conclude with cautious optimism that the models and concepts discussed here, once extended to large numbers of neutral markers, may provide a framework for integrating information from genome scans, selection experiments, quantitative trait loci mapping, association studies, and natural history to develop a deeper understanding of the genomics of speciation.

Theoretical models of the influence of genomic architecture on the dynamics of speciation.

A long-standing problem in evolutionary biology has been determining whether and how gradual, incremental changes at the gene level can account for rapid speciation and bursts of adaptive radiation. Using genome-scale computer simulations, we extend previous theory showing how gradual adaptive change can generate nonlinear population transitions, resulting in the rapid formation of new, reproductively isolated species. We show that these transitions occur via a mechanism rooted in a basic property of biological heredity: the organization of genes in genomes. Genomic organization of genes facilitates two processes: (i) the build-up of statistical associations among large numbers of genes and (ii) the action of divergent selection on persistent combinations of alleles. When a population has accumulated a critical amount of standing, divergently selected variation, the combination of these two processes allows many mutations of small effect to act synergistically and precipitously split one population into two discontinuous, reproductively isolated groups. Periods of allopatry, chromosomal linkage among loci, and large-effect alleles can facilitate this process under some conditions, but are not required for it. Our results complement and extend existing theory on alternative stable states during population divergence, distinct phases of speciation and the rapid emergence of multilocus barriers to gene flow. The results are thus a step towards aligning population genomic theory with modern empirical studies.

Chronic psychosocial stressors and salivary biomarkers in emerging adults.

We investigated whole saliva as a source of biomarkers to distinguish individuals who have, and who have not, been chronically exposed to severe and threatening life difficulties. We evaluated RNA and DNA metrics, expression of 37 candidate genes, and cortisol release in response to the Trier Social Stress Test, as well as clinical characteristics, from 48 individuals stratified on chronic exposure to psychosocial stressors within the last year as measured by the Life Events and Difficulties Schedule. Candidate genes were selected based on their differential gene expression ratio in circulating monocytes from a published genome-wide analysis of adults experiencing different levels of exposure to a chronic stressor. In univariate analyses, we observed significantly decreased RNA integrity (RIN) score (P = 0.04), and reduced expression of glucocorticoid receptor-regulated genes (Ps < 0.05) in whole saliva RNA from individuals exposed to chronic stressors, as compared to those with no exposure. In those exposed, we observed significantly decreased BMI (P < 0.001), increased ever-smoking and increased lifetime alcohol abuse or dependence (P ≤ 0.03), and a reduction of cortisol release. In post hoc multivariate analyses including clinical and biospecimen-derived variables, we consistently observed significantly decreased expression of IL8 (Ps<0.05) in individuals exposed, with no significant association to RIN score. Alcohol use disorders, tobacco use, a reduced acute stress response and decreased salivary IL8 gene expression characterize emerging adults chronically exposed to severe and threatening psychosocial stressors.