Transcriptome structure variability in Saccharomyces cerevisiae strains determined with a newly developed assembly software

RNA-seq studies have an important role for both large-scale analysis of gene expression and for transcriptome reconstruction. However, the lack of software specifically developed for the analysis of the transcriptome structure in lower eukaryotes, has so far limited the comparative studies among different species and strains.Results: In order to fill this gap, an innovative software called ORA (Overlapped Reads Assembler) was developed. This software allows a simple and reliable analysis of the transcriptome structure in organisms with a low number of introns. It can also determine the size and the position of the untranslated regions (UTR) and of polycistronic transcripts. As a case study, we analyzed the transcriptional landscape of six S. cerevisiae strains in two different key steps of the fermentation process. This comparative analysis revealed differences in the UTR regions of transcripts. By extending the transcriptome analysis to yeast species belonging to the Saccharomyces genus, it was possible to examine the conservation level of unknown non-coding RNAs and their putative functional role.Conclusions: By comparing the results obtained using ORA with previous studies and with the transcriptome structure determined with other software, it was proven that ORA has a remarkable reliability. The results obtained from the training set made it possible to detect the presence of transcripts with variable UTRs between S. cerevisiae strains. Finally, we propose a regulatory role for some non-coding transcripts conserved within the Saccharomyces genus and localized in the antisense strand to genes involved in meiosis and cell wall biosynthesis

The architecture of the Rag GTPase signaling network

The evolutionarily conserved target of rapamycin complex 1 (TORC1) couples an array of intra- and extracellular stimuli to cell growth, proliferation and metabolism, and its deregulation is associated with various human pathologies such as immunodeficiency, epilepsy, and cancer. Among the diverse stimuli impinging on TORC1, amino acids represent essential input signals, but how they control TORC1 has long remained a mystery. The recent discovery of the Rag GTPases, which assemble as heterodimeric complexes on vacuolar/lysosomal membranes, as central elements of an amino acid signaling network upstream of TORC1 in yeast, flies, and mammalian cells represented a breakthrough in this field. Here, we review the architecture of the Rag GTPase signaling network with a special focus on structural aspects of the Rag GTPases and their regulators in yeast and highlight both the evolutionary conservation and divergence of the mechanisms that control Rag GTPases

Amino Acids Stimulate TORC1 through Lst4-Lst7, a GTPase-Activating Protein Complex for the Rag Family GTPase Gtr2

Rag GTPases assemble into heterodimeric complexes consisting of RagA or RagB and RagC or RagD in higher eukaryotes, or Gtr1 and Gtr2 in yeast, to relay amino acid signals toward the growth-regulating target of rapamycin complex 1 (TORC1). The TORC1-stimulating state of Rag GTPase heterodimers, containing GTP- and GDP-loaded RagA/B/Gtr1 and RagC/D/Gtr2, respectively, is maintained in part by the FNIP-Folliculin RagC/D GAP complex in mammalian cells. Here, we report the existence of a similar Lst4-Lst7 complex in yeast that functions as a GAP for Gtr2 and that clusters at the vacuolar membrane in amino acid-starved cells. Refeeding of amino acids, such as glutamine, stimulated the Lst4-Lst7 complex to transiently bind and act on Gtr2, thereby entailing TORC1 activation and Lst4-Lst7 dispersal from the vacuolar membrane. Given the remarkable functional conservation of the RagC/D/Gtr2 GAP complexes, our findings could be relevant for understanding the glutamine addiction of mTORC1-dependent cancers

The I-BAR protein Ivy1 is an effector of the Rab7 GTPase Ypt7 involved in vacuole membrane homeostasis

Membrane fusion at the vacuole depends on a conserved machinery that includes SNAREs, the Rab7 homolog Ypt7 and its effector HOPS. Here, we demonstrate that Ypt7 has an unexpected additional function by controlling membrane homeostasis and nutrient-dependent signaling on the vacuole surface. We show that Ivy1, the yeast homolog of mammalian missing-in-metastasis (MIM), is a vacuolar effector of Ypt7-GTP and interacts with the EGO/ragulator complex, an activator of the target of rapamycin kinase complex 1 (TORC1) on vacuoles. Loss of Ivy1 does not affect EGO vacuolar localization and function. In combination with the deletion of individual subunits of the V-ATPase, however, we observed reduced TORC1 activity and massive enlargement of the vacuole surface. Consistent with this, Ivy1 localizes to invaginations at the vacuole surface and on liposomes in a phosphoinositide- and Ypt7-GTP-controlled manner, which suggests a role in microautophagy. Our data, thus, reveal that Ivy1 is a novel regulator of vacuole membrane homeostasis with connections to TORC1 signaling

Spatially distinct pools of TORC1 balance protein homeostasis

The eukaryotic TORC1 kinase is a homeostatic controller of growth that integrates nutritional cues and mediates signals primarily from the surface of lysosomes or vacuoles. Amino acids activate TORC1 via the Rag GTPases that combine into structurally conserved multi-protein complexes such as the EGO complex (EGOC) in yeast. Here we show that Ego1, which mediates membrane-anchoring of EGOC via lipid modifications that it acquires while traveling through the trans-Golgi network, is separately sorted to vacuoles and perivacuolar endosomes. At both surfaces, it assembles EGOCs, which regulate spatially distinct pools of TORC1 that impinge on functionally divergent effectors: vacuolar TORC1 predominantly targets Sch9 to promote protein synthesis, whereas endosomal TORC1 phosphorylates Atg13 and Vps27 to inhibit macroautophagy and ESCRT-driven microautophagy, respectively. Thus, the coordination of three key regulatory nodes in protein synthesis and degradation critically relies on a division of labor between spatially sequestered populations of TORC

Population Based Study of 12 Autoimmune Diseases in Sardinia, Italy: Prevalence and Comorbidity

BACKGROUND: The limited availability of prevalence data based on a representative sample of the general population, and the limited number of diseases considered in studies about co-morbidity are the critical factors in study of autoimmune diseases. This paper describes the prevalence of 12 autoimmune diseases in a representative sample of the general population in the South of Sardinia, Italy, and tests the hypothesis of an overall association among these diseases. METHODS: Data were obtained from 21 GPs. The sample included 25,885 people. Prevalence data were expressed with 95% Poisson C.I. The hypothesis of an overall association between autoimmune diseases was tested by evaluating the co-occurrence within individuals. RESULTS: Prevalence per 100,000 are: 552 rheumatoid arthritis, 124 ulcerative colitis, 15 Crohn's disease, 464 type 1 diabetes, 81 systemic lupus erythematosus, 124 celiac disease, 35 myasthenia gravis, 939 psoriasis/psoriatic arthritis, 35 systemic sclerosis, 224 multiple sclerosis, 31 Sjogren's syndrome, and 2,619 autoimmune thyroiditis. An overall association between autoimmune disorders was highlighted. CONCLUSIONS: The comparisons with prevalence reported in current literature do not show outlier values, except possibly for a few diseases like celiac disease and myasthenia gravis. People already affected by a first autoimmune disease have a higher probability of being affected by a second autoimmune disorder. In the present study, the sample size, together with the low overall prevalence of autoimmune diseases in the population, did not allow us to examine which diseases are most frequently associated with other autoimmune diseases. However, this paper makes available an adequate control population for future clinical studies aimed at exploring the co-morbidity of specific pairs of autoimmune disease

Transcriptome structure variability in Saccharomyces cerevisiae strains determined with a newly developed assembly software

BACKGROUND: RNA-seq studies have an important role for both large-scale analysis of gene expression and for transcriptome reconstruction. However, the lack of software specifically developed for the analysis of the transcriptome structure in lower eukaryotes, has so far limited the comparative studies among different species and strains. RESULTS: In order to fill this gap, an innovative software called ORA (Overlapped Reads Assembler) was developed. This software allows a simple and reliable analysis of the transcriptome structure in organisms with a low number of introns. It can also determine the size and the position of the untranslated regions (UTR) and of polycistronic transcripts. As a case study, we analyzed the transcriptional landscape of six S. cerevisiae strains in two different key steps of the fermentation process. This comparative analysis revealed differences in the UTR regions of transcripts. By extending the transcriptome analysis to yeast species belonging to the Saccharomyces genus, it was possible to examine the conservation level of unknown non-coding RNAs and their putative functional role. CONCLUSIONS: By comparing the results obtained using ORA with previous studies and with the transcriptome structure determined with other software, it was proven that ORA has a remarkable reliability. The results obtained from the training set made it possible to detect the presence of transcripts with variable UTRs between S. cerevisiae strains. Finally, we propose a regulatory role for some non-coding transcripts conserved within the Saccharomyces genus and localized in the antisense strand to genes involved in meiosis and cell wall biosynthesis