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Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more representative of other insects than is Drosophila, a fact reflected in gene content and function. For example, Tribolium has retained more ancestral genes involved in cellcell communication than Drosophila, some being expressed in the growth zone crucial for axial elongation in short-germ development. Systemic RNA interference in T. castaneum functions differently from that in Caenorhabditis elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.

We aimed to explore whether changes in circulating levels of miRNAs according to type 2 diabetes mellitus (T2DM) or prediabetes status could be used as biomarkers to evaluate the risk of developing the disease. The study included 462 patients without T2DM at baseline from the CORDIOPREV trial. After a median follow-up of 60 months, 107 of the subjects developed T2DM, 30 developed prediabetes, 223 maintained prediabetes and 78 remained disease-free. Plasma levels of four miRNAs related to insulin signaling and beta-cell function were measured by RT-PCR. We analyzed the relationship between miRNAs levels and insulin signaling and release indexes at baseline and after the follow-up period. The risk of developing disease based on tertiles (T1-T2-T3) of baseline miRNAs levels was evaluated by COX analysis. Thus, we observed higher miR-150 and miR-30a-5p and lower miR-15a and miR-375 baseline levels in subjects with T2DM than in disease-free subjects. Patients with high miR-150 and miR-30a-5p baseline levels had lower disposition index ( p  = 0.047 and p  = 0.007, respectively). The higher risk of disease was associated with high levels (T3) of miR-150 and miR-30a-5p ( HR T3-T1  = 4.218 and HR T3-T1  = 2.527, respectively) and low levels (T1) of miR-15a and miR-375 ( HR T1-T3  = 3.269 and HR T1-T3  = 1.604, respectively). In conclusion, our study showed that deregulated plasma levels of miR-150 , miR-30a-5p , miR-15a , and miR-375 were observed years before the onset of T2DM and pre-DM and could be used to evaluate the risk of developing the disease, which may improve prediction and prevention among individuals at high risk for T2DM. Metabolic disease: a red flag for diabetes risk Tiny RNA molecules circulating in the blood could give early warning of type 2 diabetes risk. MicroRNAs help regulate the expression of other genes, and recent research has linked irregularities in these molecules to many different diseases. Researchers led by José López Miranda of the University of Córdoba in Spain monitored a cohort of 462 patients for several years to assess how plasma levels of certain microRNAs are deregulated before the onset and progression of diabetes. They observed a striking ‘signature’ of altered expression in four microRNAs for patients who developed diabetes over the course of the study. Intriguingly, patients with markedly elevated blood sugar—state known as prediabetes—exhibited a similar signature, but with more modest alteration in the gene expression levels, indicating that these microRNAs could help clinicians track and prevent disease onset.

Background:Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms.Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. Results:We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration.Conclusion:We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more assertive antidepressant strategies, including the addition of other antidepressants or antiinflammatory drugs.

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center ( https://danio-code.zfin.org ) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis -regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals. The DANIO-CODE consortium leverages a large-scale multiomic dataset to improve zebrafish genome annotation. They identify ~140,000 cis -regulatory elements throughout development and perform a comparison with the mouse regulatory landscape.

Supergenes underlie striking polymorphisms in nature, yet the evolutionary mechanisms by which they arise and persist remain enigmatic. These clusters of linked loci can spread in populations because they captured coadapted alleles or by selfishly distorting the laws of Mendelian inheritance. Here, we show that the supergene haplotype associated with multiple-queen colonies in Alpine silver ants is a maternal effect killer. All eggs from heterozygous queens failed to hatch when they did not inherit this haplotype. Hence, the haplotype specific to multiple-queen colonies is a selfish genetic element that enhances its own transmission by causing developmental arrest of progeny that do not carry it. At the population level, such transmission ratio distortion favors the spread of multiple-queen colonies, to the detriment of the alternative haplotype associated with single-queen colonies. Hence, selfish gene drive by one haplotype will impact the evolutionary dynamics of alternative forms of colony social organization. This killer hidden in a social supergene shows that large nonrecombining genomic regions are prone to cause multifarious effects across levels of biological organization.

Bacterial vaginosis (BV), a condition defined by increased vaginal discharge without significant inflammation, is characterized by a change in the bacterial composition of the vagina. Lactobacillus spp., associated with a healthy vaginal microbiome, are outnumbered by BV-associated organisms. These bacteria could form a polymicrobial biofilm which allows them to persist in spite of antibiotic treatment. In this study, we examined the presence of Gardnerella vaginalis and Atopobium vaginae in vaginal biofilms using Peptide Nucleic Acid (PNA) probes targeting these bacteria. For this purpose, we developed three new PNA probes for A. vaginae. The most specific A. vaginae probe, AtoITM1, was selected and then used in an assay with two existing probes, Gard162 and BacUni-1, to evaluate multiplex FISH on clinical samples. Using quantitative polymerase chain reaction (qPCR) as the gold standard, we demonstrated a sensitivity of 66.7% (95% confidence interval: 54.5% - 77.1%) and a specificity of 89.4% (95% confidence interval: 76.1% - 96%) of the new AtoITM1 probe. FISH enabled us to show the presence of a polymicrobial biofilm in bacterial vaginosis, in which Atopobium vaginae is part of a Gardnerella vaginalis-dominated biofilm. We showed that the presence of this biofilm is associated with high bacterial loads of A. vaginae and G. vaginalis.

Background: The effects of blood flow restriction (training) may serve as a model of peripheral artery disease. In both conditions, circulating micro RNAs (miRNAs) are suggested to play a crucial role during exercise-induced arteriogenesis. We aimed to determine whether the profile of circulating miRNAs is altered after acute resistance training during blood flow restriction (BFR) as compared with unrestricted low- and high-volume training, and we hypothesized that miRNA that are relevant for arteriogenesis are affected after resistance training. Methods: Eighteen healthy volunteers (aged 25 ± 2 years) were enrolled in this three-arm, randomized-balanced crossover study. The arms were single bouts of leg flexion/extension resistance training at (1) 70% of the individual single-repetition maximum (1RM), (2) at 30% of the 1RM, and (3) at 30% of the 1RM with BFR (artificially applied by a cuff at 300 mm Hg). Before the first exercise intervention, the individual 1RM (N) and the blood flow velocity (m/s) used to validate the BFR application were determined. During each training intervention, load-associated outcomes (fatigue, heart rate, and exhaustion) were monitored. Acute effects (circulating miRNAs, lactate) were determined using pre-and post-intervention measurements. Results: All training interventions increased lactate concentration and heart rate (p < 0.001). The high-intensity intervention (HI) resulted in a higher lactate concentration than both lower-intensity training protocols with BFR (LI-BFR) and without (LI) (LI, p = 0.003; 30% LI-BFR, p = 0.008). The level of miR-143-3p was down-regulated by LI-BFR, and miR-139-5p, miR-143-3p, miR-195-5p, miR-197-3p, miR-30a-5p, and miR-10b-5p were up-regulated after HI. The lactate concentration and miR-143-3p expression showed a significant positive linear correlation (p = 0.009, r = 0.52). A partial correlation (intervention partialized) showed a systematic impact of the type of training (LI-BFR vs. HI) on the association (r = 0.35 remaining after partialization of training type). Conclusions: The strong effects of LI-BFR and HI on lactate- and arteriogenesis-associated miRNA-143-3p in young and healthy athletes are consistent with an important role of this particular miRNA in metabolic processes during (here) artificial blood flow restriction. BFR may be able to mimic the occlusion of a larger artery which leads to increased collateral flow, and it may therefore serve as an external stimulus of arteriogenesis.

Type 2 Diabetes Mellitus (T2DM) is the most prevalent form of diabetes in the USA, thus, the identification of biomarkers that could be used to predict the progression from prediabetes to T2DM would be greatly beneficial. Recently, circulating RNA including microRNAs (miRNAs) present in various body fluids have emerged as potential biomarkers for various health conditions, including T2DM. Whereas studies that examine the changes of miRNA spectra between healthy controls and T2DM individuals have been reported, the goal of this study is to conduct a baseline comparison of prediabetic individuals who either progress to T2DM, or remain prediabetic. Using an advanced small RNA sequencing library construction method that improves the detection of miRNA species, we identified 57 miRNAs that showed significant concentration differences between progressors (progress from prediabetes to T2DM) and non‐progressors. Among them, 26 have been previously reported to be associated with T2DM in either body fluids or tissue samples. Some of the miRNAs identified were also affected by obesity. Furthermore, we identified miRNA panels that are able to discriminate progressors from non‐progressors. These results suggest that upon further validation these miRNAs may be useful to predict the risk of conversion to T2DM from prediabetes.