Comparative genomic analysis of novel conserved peptide upstream open reading frames in Drosophila melanogaster and other dipteran species

<p>Abstract</p> <p>Background</p> <p>Upstream open reading frames (uORFs) are elements found in the 5'-region of an mRNA transcript, capable of regulating protein production of the largest, or major ORF (mORF), and impacting organismal development and growth in fungi, plants, and animals. In Drosophila, approximately 40% of transcripts contain upstream start codons (uAUGs) but there is little evidence that these are translated and affect their associated mORF.</p> <p>Results</p> <p>Analyzing 19,389 <it>Drosophila melanogaster </it>transcript annotations and 666,153 dipteran EST sequences we have identified 44 putative conserved peptide uORFs (CPuORFs) in <it>Drosophila melanogaster </it>that show evidence of negative selection, and therefore are likely to be translated. Transcripts with CPuORFs constitute approximately 0.3% of the total number of transcripts, a similar frequency to the Arabidopsis genome, and have a mean length of 70 amino acids, much larger than the mean length of plant CPuORFs (40 amino acids). There is a statistically significant clustering of CPuORFs at cytological band 57 (p = 10^-5), a phenomenon that has never been described for uORFs. Based on GO term and Interpro domain analyses, genes in the uORF dataset show a higher frequency of ORFs implicated in mitochondrial import than the genome-wide frequency (p < 0.01) as well as methyltransferases (p < 0.02).</p> <p>Conclusion</p> <p>Based on these data, it is clear that Drosophila contain putative CPuORFs at frequencies similar to those found in plants. They are distinguished, however, by the type of mORF they tend to associate with, Drosophila CPuORFs preferentially occurring in transcripts encoding mitochondrial proteins and methyltransferases. This provides a basis for the study of CPuORFs and their putative regulatory role in mitochondrial function and disease.</p

Drosophila Species Learn Dialects Through Communal Living

Many species are able to share information about their environment by communicating through auditory, visual, and olfactory cues. In Drosophila melanogaster, exposure to para- sitoid wasps leads to a decline in egg laying, and exposed females communicate this threat to naïve flies, which also depress egg laying. We find that species across the genus Drosophila respond to wasps by egg laying reduction, activate cleaved caspase in oocytes, and communicate the presence of wasps to naïve individuals. Communication within a species and between closely related species is efficient, while more distantly related species exhibit partial communication. Remarkably, partial communication between some species is enhanced after a cohabitation period that requires exchange of visual and olfactory signals. This interspecies “dialect learning” requires neuronal cAMP signaling in the mushroom body, suggesting neuronal plasticity facilitates dialect learning and memory. These observations establish Drosophila as genetic models for interspecies social communication and evolution of dialects

DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages

Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named DeepEva, a Deep Learning based system capable of classifying both Italian and English sentences on the basis of their complexity. The system exploits the Treetagger annotation tool, two Long Short Term Memory (LSTM) neural unit layers, and a fully connected one. The last layer outputs the probability of a sentence belonging to the easy or complex class. The experimental results show the effectiveness of the approach for both languages, compared with several baselines such as Support Vector Machine, Gradient Boosting, and Random Forest

Social Communication of Predator-Induced Changes in Drosophila Behavior and Germ Line Physiology

Behavioral adaptation to environmental threats and subsequent social transmission of adaptive behavior has evolutionary implications. In Drosophila, exposure to parasitoid wasps leads to a sharp decline in oviposition. We show that exposure to predator elicits both an acute and learned oviposition depression, mediated through the visual system. However, long-term persistence of oviposition depression after predator removal requires neuronal signaling functions, a functional mushroom body, and neurally driven apoptosis of oocytes through effector caspases. Strikingly, wasp-exposed flies (teachers) can transmit egg-retention behavior and trigger ovarian apoptosis in naive, unexposed flies (students). Acquisition and behavioral execution of this socially learned behavior by naive flies requires all of the factors needed for primary learning. The ability to teach does not require ovarian apoptosis. This work provides new insight into genetic and physiological mechanisms that underlie an ecologically relevant form of learning and mechanisms for its social transmission

Condensin II Promotes the Formation of Chromosome Territories by Inducing Axial Compaction of Polyploid Interphase Chromosomes

The eukaryotic nucleus is both spatially and functionally partitioned. This organization contributes to the maintenance, expression, and transmission of genetic information. Though our ability to probe the physical structure of the genome within the nucleus has improved substantially in recent years, relatively little is known about the factors that regulate its organization or the mechanisms through which specific organizational states are achieved. Here, we show that Drosophila melanogaster Condensin II induces axial compaction of interphase chromosomes, globally disrupts interchromosomal interactions, and promotes the dispersal of peri-centric heterochromatin. These Condensin II activities compartmentalize the nucleus into discrete chromosome territories and indicate commonalities in the mechanisms that regulate the spatial structure of the genome during mitosis and interphase

D7.1 - Project leaflet and portal

This deliverable documents the creation of the first version of the project leafleft and the project web portal. Of course both the leaflet and the portal will be updated during the project lifetime, to document progress and tailor the message to the various project phases

Chiral separation and analysis of antifungal drugs by chromatographic and electromigration techniques: Results achieved in 2010–2020

AbstractThe determination and separation of enantiomers is an interesting and important topic of research in various fields, e.g., biochemistry, food science, pharmaceutical industry, environment, etc. Although these compounds possess identical physicochemical properties, a pair of enantiomers often has different pharmacological, toxicological, and metabolic activities. For this reason, chiral discrimination by using chromatographic and electromigration techniques has become an urgent need in the pharmaceutical field. This review intends to offer the "state of the art" about the separation of chiral antifungal drugs and several related precursors by both liquid and gas chromatography, as well as electromigration methods. This overview is organized into two sections. The first one describes general considerations on chiral antifungal drugs. The second part deals with the main analytical methods for the enantiomeric discrimination of these drugs, including a brief description of chiral selectors and stationary phases. Moreover, many recent applications attesting the great interest of analytical chemists in the field of enantiomeric separation are presented

Supporting Emotion Automatic Detection and Analysis over Real-Life Text Corpora via Deep Learning: Model, Methodology, and Framework

This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers