A functional connection between translation elongation and protein folding at the ribosome exit tunnel in Saccharomyces cerevisiae

Proteostasis needs to be tightly controlled to meet the cellular demand for correctly de novo folded proteins and to avoid protein aggregation. While a coupling between translation rate and co-translational folding, likely involving an interplay between the ribosome and its associated chaperones, clearly appears to exist, the underlying mechanisms and the contribution of ribosomal proteins remain to be explored. The ribosomal protein uL3 contains a long internal loop whose tip region is in close proximity to the ribosomal peptidyl transferase center. Intriguingly, the rpl3[W255C] allele, in which the residue making the closest contact to this catalytic site is mutated, affects diverse aspects of ribosome biogenesis and function. Here, we have uncovered, by performing a synthetic lethal screen with this allele, an unexpected link between translation and the folding of nascent proteins by the ribosome-associated Ssb-RAC chaperone system. Our results reveal that uL3 and Ssb-RAC cooperate to prevent 80S ribosomes from piling up within the 5′ region of mRNAs early on during translation elongation. Together, our study provides compelling in vivo evidence for a functional connection between peptide bond formation at the peptidyl transferase center and chaperone-assisted de novo folding of nascent polypeptides at the solvent-side of the peptide exit tunnel

Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Regional Variation in RBM20 Causes a Highly Penetrant Arrhythmogenic Cardiomyopathy

Background Variants in the cardiomyocyte-specific RNA splicing factor RBM20 have been linked to familial cardiomyopathy, but the causative genetic architecture and clinical consequences of this disease are incompletely defined. Methods and Results To define the genetic architecture of RBM20 cardiomyopathy, we first established a database of RBM20 variants associated with cardiomyopathy and compared these to variants observed in the general population with respect to their location in the RBM20 coding transcript. We identified 2 regions significantly enriched for cardiomyopathy-associated variants in exons 9 and 11. We then assembled a registry of 74 patients with RBM20 variants from 8 institutions across the world (44 index cases and 30 from cascade testing). This RBM20 patient registry revealed highly prevalent family history of sudden cardiac death (51%) and cardiomyopathy (72%) among index cases and a high prevalence of composite arrhythmias (including atrial fibrillation, nonsustained ventricular tachycardia, implantable cardiac defibrillator discharge, and sudden cardiac arrest, 43%). Patients harboring variants in cardiomyopathy-enriched regions identified by our variant database analysis were enriched for these findings. Further, these characteristics were more prevalent in the RBM20 registry than in large cohorts of patients with dilated cardiomyopathy and TTNtv cardiomyopathy and not significantly different from a cohort of patients with LMNA-associated cardiomyopathy. Conclusions Our data establish RBM20 cardiomyopathy as a highly penetrant and arrhythmogenic cardiomyopathy. These findings underline the importance of arrhythmia surveillance and family screening in this disease and represent the first step in defining the genetic architecture of RBM20 disease causality on a population level

Role of Duplicate Genes in Robustness against Deleterious Human Mutations

It is now widely recognized that robustness is an inherent property of biological systems [1],[2],[3]. The contribution of close sequence homologs to genetic robustness against null mutations has been previously demonstrated in simple organisms [4],[5]. In this paper we investigate in detail the contribution of gene duplicates to back-up against deleterious human mutations. Our analysis demonstrates that the functional compensation by close homologs may play an important role in human genetic disease. Genes with a 90% sequence identity homolog are about 3 times less likely to harbor known disease mutations compared to genes with remote homologs. Moreover, close duplicates affect the phenotypic consequences of deleterious mutations by making a decrease in life expectancy significantly less likely. We also demonstrate that similarity of expression profiles across tissues significantly increases the likelihood of functional compensation by homologs

Maximal Extraction of Biological Information from Genetic Interaction Data

Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse

Multiple populations in globular clusters. Lessons learned from the Milky Way globular clusters

Recent progress in studies of globular clusters has shown that they are not simple stellar populations, being rather made of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is then arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second parameter problem, it also opens new perspectives about the relation between globular clusters and the halo of our Galaxy, and by extension of all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focusing on the most recent studies. Several points remain to be properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.Comment: In press (The Astronomy and Astrophysics Review

Genetic Architecture of Highly Complex Chemical Resistance Traits across Four Yeast Strains

Many questions about the genetic basis of complex traits remain unanswered. This is in part due to the low statistical power of traditional genetic mapping studies. We used a statistically powerful approach, extreme QTL mapping (X-QTL), to identify the genetic basis of resistance to 13 chemicals in all 6 pairwise crosses of four ecologically and genetically diverse yeast strains, and we detected a total of more than 800 loci. We found that the number of loci detected in each experiment was primarily a function of the trait (explaining 46% of the variance) rather than the cross (11%), suggesting that the level of genetic complexity is a consistent property of a trait across different genetic backgrounds. Further, we observed that most loci had trait-specific effects, although a small number of loci with effects in many conditions were identified. We used the patterns of resistance and susceptibility alleles in the four parent strains to make inferences about the allele frequency spectrum of functional variants. We also observed evidence of more complex allelic series at a number of loci, as well as strain-specific signatures of selection. These results improve our understanding of complex traits in yeast and have implications for study design in other organisms

Antagonistic Changes in Sensitivity to Antifungal Drugs by Mutations of an Important ABC Transporter Gene in a Fungal Pathogen

Fungal pathogens can be lethal, especially among immunocompromised populations, such as patients with AIDS and recipients of tissue transplantation or chemotherapy. Prolonged usage of antifungal reagents can lead to drug resistance and treatment failure. Understanding mechanisms that underlie drug resistance by pathogenic microorganisms is thus vital for dealing with this emerging issue. In this study, we show that dramatic sequence changes in PDR5, an ABC (ATP-binding cassette) efflux transporter protein gene in an opportunistic fungal pathogen, caused the organism to become hypersensitive to azole, a widely used antifungal drug. Surprisingly, the same mutations conferred growth advantages to the organism on polyenes, which are also commonly used antimycotics. Our results indicate that Pdr5p might be important for ergosterol homeostasis. The observed remarkable sequence divergence in the PDR5 gene in yeast strain YJM789 may represent an interesting case of adaptive loss of gene function with significant clinical implications