Biology subjects

Acar, O.

Publications and source records attributed to Acar, O..

7 recordsLinked to original sources

bioRxiv2024

Ancestral Sequence Reconstruction as a tool to detect and study de novo gene emergence

New protein-coding genes can evolve from previously non-coding genomic regions through a process known as de novo gene emergence. Evidence suggests that this process has likely occurred throughout evolution and across the tree of life. Yet, confidently identifying de novo emerged genes remains challenging. Ancestral Sequence Reconstruction (ASR) is a promising approach for inferring whether a gene has emerged de novo or not, as it can enable us to inspect whether a given genomic locus ancestrally harbored protein-coding capacity. However, the use of ASR in the context of de novo emergence is still in its infancy and its capabilities, limitations, and overall potential are largely unknown. Notably, it is difficult to formally evaluate the protein-coding capacity of ancestral sequences, particularly when new gene candidates are short. How well-suited is ASR as a tool for the detection and study of de novo genes? Here, we address this question by designing an ASR workflow incorporating different tools and sets of parameters and by introducing a formal criterion that allows to estimate, within a desired level of confidence, when protein-coding capacity originated at a particular locus. Applying this workflow on [~]2,600 short, annotated budding yeast genes (<1,000 nucleotides), we found that ASR robustly predicts an ancient origin for most widely conserved genes, which constitute "easy" cases. For less robust cases, we calculated a randomization-based empirical P-value estimating whether the observed conservation between the extant and ancestral reading frame could be attributed to chance. This formal criterion allowed us to pinpoint a branch of origin for most of the less robust cases, identifying 33 genes that can unequivocally be considered de novo originated since the split of the Saccharomyces genus, including 20 S. cerevisiae-specific genes. We find that the remaining, equivocal cases, may be explained by different evolutionary scenarios including rapid evolution and multiple losses, as well as a very recent de novo origin. Overall, our findings suggest that ASR is a valuable tool to study de novo gene emergence but should be applied with caution and awareness of its limitations.

evolutionary biology↗

bioRxiv2023

Exploring the noncanonical translatome using massively integrated coexpression analysis

BackgroundRecent studies uncovered pervasive transcription and translation of thousands of noncanonical open reading frames (nORFs) outside of annotated genes. The contribution of nORFs to cellular phenotypes is difficult to infer using conventional approaches because nORFs tend to be short, of recent de novo origins, and lowly expressed. Here we develop a dedicated coexpression analysis framework that accounts for low expression to investigate the transcriptional regulation, evolution, and potential cellular roles of nORFs in Saccharomyces cerevisiae. ResultsOur results reveal that nORFs tend to be preferentially coexpressed with genes involved in cellular transport or homeostasis but rarely with genes involved in RNA processing. Mechanistically, we discover that young de novo nORFs located downstream of conserved genes tend to leverage their neighbors promoters through transcription readthrough, resulting in high coexpression and high expression levels. Transcriptional piggybacking also influences the coexpression profiles of young de novo nORFs located upstream of genes, but to a lesser extent and without detectable impact on expression levels. Transcriptional piggybacking influences, but does not determine, the transcription profiles of de novo nORFs emerging nearby genes. About 40% of nORFs are not strongly coexpressed with any gene but are transcriptionally regulated nonetheless and tend to form entirely new transcription modules. We offer a web browser interface (https://carvunislab.csb.pitt.edu/shiny/coexpression/) to efficiently query, visualize and download our coexpression inferences. ConclusionsOur results suggest that nORF transcription is highly regulated. Our coexpression dataset serves as an unprecedented resource for unraveling how nORFs integrate into cellular networks, contribute to cellular phenotypes, and evolve.

systems biology↗

bioRxiv2022

α-Arrestins maintain phospholipid balance and Atg18 distribution to permit efficient autophagy

Cells selectively reorganize their membrane proteome in response to stressors via selective protein trafficking. The -arrestins, a family of conserved protein trafficking adaptors, bind to select membrane proteins and interact with the ubiquitin ligase Rsp5. The -arrestins recruit Rsp5 to its membrane protein substrates, permitting their ubiquitination and endocytosis. To identify new -arrestin functions, we performed a genetic screen to isolate mutants that alter -arrestin-mediated resistance to rapamycin, a drug that inhibits TORC1. Interestingly, loss of many of the ATG genes, which encode the machinery needed for the self-degradative process of autophagy, disrupted -arrestins ability to promote growth on rapamycin. Herein we define a genetic network linking -arrestins to autophagy. We show autophagy impairment in the absence of select -arrestins, with increased autophagosome lifetimes and delayed/reduced delivery of autophagosomes to the vacuole. The -arrestin mutants that impeded autophagy had vacuole morphology defects and increased vacuolar retention of Atg18, a member of the PROPPIN family that is needed to maintain vacuole shape and facilitate lipid transfer to expanding autophagosomes. Atg18 binds phosphatidylinositol 3 phosphate (PI3P) and phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2), and we observed increased PI3P on the vacuole membrane in -arrestin mutants. The levels of Vps34 and Fab1, the kinases responsible for the generation of PI3P and PI(3,5)P2, respectively, were also elevated at vacuole membranes in cells lacking -arrestins. We posit that altered phospholipids in the vacuolar membrane form the basis for the Atg18-Atg2 mislocalization and autophagy defect. These data demonstrate a previously unappreciated link between the -arrestins and autophagy, expanding the functional impact of these trafficking adaptors in responding to nutrient stress. Author SummaryCells survive nutrient starvation by degrading parts of themselves through the process of autophagy. During autophagy, cells make a double membrane, known as an autophagosome (AP), around bits of cytoplasm or organelles. The AP and its engulfed material are delivered to the vacuole, an organelle that helps break down proteins and lipids. These materials can then be used as building blocks to generate the essential components needed for the cell to survive starvation. For cells to undergo efficient autophagy, they need -arrestins, a group of proteins important for deciding where membrane proteins localize. In cells lacking -arrestins, the AP forms slowly, likely due to a problem in growing the AP membrane. This results in less material being delivered to the vacuole via APs when cells do not have -arrestins. This study defines a new role for -arrestins in promoting AP formation and starvation survival.

cell biology↗

bioRxiv2021

A reference translatome map reveals two modes of protein evolution

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. Surprisingly, 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.

genomics↗

bioRxiv2021

Elastic Network Modeling of Cellular Networks Unveils Sensor and Effector Genes that Control Information Flow

The high-level organization of the cell is embedded in long-range interactions that connect distinct cellular processes. Existing approaches for detecting long-range interactions consist of propagating information from source nodes through cellular networks, but the selection of source nodes is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of long-range interactions by adapting a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic network. The genetic network revealed a superior propensity for long-range interactions relative to simulated networks with similar topology. Long-range interactions were detected systematically throughout the network and found to be enriched in specific biological processes. Furthermore, perturbation-response scanning identified the major sources and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters. Long-range interactions between effector and sensor clusters represent the major paths of information in the network. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization of the cell.

systems biology↗

bioRxiv2021

Quantitative proteomics identifies secreted diagnostic biomarkers as well as tumor-dependent prognostic targets for clear cell Renal Cell Carcinoma

Clear cell Renal Cell Carcinoma (ccRCC) is the third most common and most malignant urological cancer, with a 5-year survival rate of 10% for patients with advanced tumors. Here, we identified 10,160 unique proteins by in-depth quantitative proteomics, of which 955 proteins were significantly regulated between tumor and normal adjacent tissues. We verified 4 putatively secreted biomarker candidates, namely PLOD2, FERMT3, SPARC and SIRP, as highly expressed proteins that are not affected by intra- and inter-tumor heterogeneity. Moreover, SPARC displayed a significant increase in urine samples of ccRCC patients, making it a promising marker for clinical screening assays. Furthermore, based on molecular expression profiles, we propose a biomarker panel for the robust classification of ccRCC tumors into two main clusters, which significantly differed in patient outcome with an almost three times higher risk of death for cluster 1 tumors compared to cluster 2 tumors. Moreover, among the most significant clustering proteins, 13 were targets of repurposed inhibitory FDA-approved drugs. Our rigorous proteomics approach identified promising diagnostic and tumor-discriminative biomarker candidates which can serve as therapeutic targets for the treatment of ccRCC.

cancer biology↗

bioRxiv2019

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

Recent evidence demonstrates that novel protein-coding genes can arise de novo from intergenic loci. This evolutionary innovation is thought to be facilitated by the pervasive translation of intergenic transcripts, which exposes a reservoir of variable polypeptides to natural selection. Do intergenic translation events yield polypeptides with useful biochemical capacities? The answer to this question remains controversial. Here, we systematically characterized how de novo emerging coding sequences impact fitness. In budding yeast, overexpression of these sequences was enriched in beneficial effects, while their disruption was generally inconsequential. We found that beneficial emerging sequences have a strong tendency to encode putative transmembrane proteins, which appears to stem from a cryptic propensity for transmembrane signals throughout thymine-rich intergenic regions of the genome. These findings suggest that novel genes with useful biochemical capacities, such as transmembrane domains, tend to evolve de novo within intergenic loci that already harbored a blueprint for these capacities.

evolutionary biology↗