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Long noncoding RNAs (lncRNAs) are emerging as regulators of fundamental biological processes. Here we report on the characterization of an intergenic lncRNA expressed in epithelial tissues which we termed EPR (Epithelial cell Program Regulator). EPR is rapidly downregulated by TGF-β and its sustained expression largely reshapes the transcriptome, favors the acquisition of epithelial traits, and reduces cell proliferation in cultured mammary gland cells as well as in an animal model of orthotopic transplantation. EPR generates a small peptide that localizes at epithelial cell junctions but the RNA molecule per se accounts for the vast majority of EPR-induced gene expression changes. Mechanistically, EPR interacts with chromatin and regulates Cdkn1a gene expression by affecting both its transcription and mRNA decay through its association with SMAD3 and the mRNA decay-promoting factor KHSRP, respectively. We propose that EPR enables epithelial cells to control proliferation by modulating waves of gene expression in response to TGF-β. Several lncRNAs are regulated by TGF-β. Here the authors report that an intergenic lncRNA —EPR— is a component of the TGF-β signaling pathway and controls epithelial cell proliferation by altering transcription and mRNA decay of Cdkn1a. EPR overexpression restrains tumor growth of orthotopically transplanted mice.

This study aims to identify the ecological factors that drive the survival of Douglas‐fir (Pseudotsuga menziesii [Mirb.] Franco) in Italy, using data from old‐growth experimental stands. A record of 124 Douglas‐fir plantations was compiled from a literature review and ground survey, including 98 Douglas‐fir stands established in the early 20th century. The probability of survival of the species at the surveyed sites was modeled using Species Distribution Models (SDM) with soil and climatic variables as predictors. Pseudo‐absences were also used to balance the proportion of presences and absences in the modeling steps. The best‐fitting models were used to predict the probability of survival of Douglas‐fir stands across the entire country and in the native range of the species to assess the model's goodness of fit. Fitted models performed well with a mean True Skill Statistics (TSS) score of 0.91, suggesting that temperature‐related factors primarily influence the survival of Douglas‐fir stands in Italy. The two most relevant predictors were GDD5 (growing degree‐days above 5°C) and AHM (Annual Heat Moisture), indicating the importance of temperatures and water availability also in the Mediterranean area. A large portion of Italy was predicted to be potentially suitable for Douglas‐fir afforestation or reforestation, mainly across the Apennine Mountains of central Italy. Model projections for the species' native area largely overlap with the range of the coastal variety of Douglas‐fir (P. menziesii var. viridis), supporting the hypothesis that most Douglas‐fir stands in Italy were established using propagation material from this region. The spatial modeling of Douglas‐fir old‐growth stands in Italy demonstrated the relevance of temperatures (GDD5) also in the Mediterranean area and showed a good climate matching between the Italian planting range and the coastal part of Douglas‐fir native range.

The limited clinical response observed in high-grade serous ovarian cancer (HG-SOC) with high frequency of TP53 mutations (mutp53) might be related to mutp53-driven oncogenic pathway network. Here we show that β-arrestin1 (β-arr1), interacts with YAP, triggering its cytoplasmic-nuclear shuttling. This interaction allows β-arr1 to recruit mutp53 to the YAP-TEAD transcriptional complex upon activation of endothelin-1 receptors (ET-1R) in patient-derived HG-SOC cells and in cell lines bearing mutp53. In parallel, β-arr1 mediates the ET-1R-induced Trio/RhoA-dependent YAP nuclear accumulation. In the nucleus, ET-1 through β-arr1 orchestrates the tethering of YAP and mutp53 to YAP/mutp53 target gene promoters, including EDN1 that ensures persistent signals. Treatment of patient-derived xenografts reveals synergistic antitumoral and antimetastatic effects of the dual ET-1R antagonist macitentan in combination with cisplatinum, shutting-down the β-arr1-mediated YAP/mutp53 transcriptional programme. Furthermore, ET A R/β-arr1/YAP gene signature correlates with a worst prognosis in HG-SOC. These findings support effective combinatorial treatment for repurposing the ET-1R antagonists in HG-SOC. YAP and mutant p53 crosstalk to regulate transcriptional processes in cancers. Here, the authors show that endothelin-1 mediated activation of β-arrestin interacts with YAP to recruit mutant p53 to the TEAD/YAP complex to promote metastasis and chemoresistance in ovarian cancer.

Long noncoding RNAs (lncRNAs) interact with protein factors to regulate different layers of gene expression transcriptionally or posttranscriptionally. Here we report on the functional consequences of the unanticipated interaction of the RNA binding protein K homology-type splicing regulatory protein (KSRP) with the H19 lncRNA (H19). KSRP directly binds to H19 in the cytoplasm of undifferentiated multipotent mesenchymal C2C12 cells, and this interaction favors KSRP-mediated destabilization of labile transcripts such as myogenin. AKT activation induces KSRP dismissal from H19 and, as a consequence, myogenin mRNA is stabilized while KSRP is repurposed to promote maturation of myogenic microRNAs, thus favoring myogenic differentiation. Our data indicate that H19 operates as a molecular scaffold that facilitates effective association of KSRP with myogenin and other labile transcripts, and we propose that H19 works with KSRP to optimize an AKT-regulated posttranscriptional switch that controls myogenic differentiation. Significance Long noncoding RNAs (lncRNAs) provide new layers of complexity to gene expression control. We report on the functional consequences of the interaction between the ssRNA-binding protein K homology-type splicing regulatory protein (KSRP) with H19 lncRNA (H19) in multipotent C2C12 cells able to differentiate in culture toward myotubes in response to activation of cell signaling pathways, including AKT. KSRP and H19 interact exclusively in undifferentiated C2C12 cells, and this favors KSRP’s ability to interact with the promyogenic transcript myogenin and to favor its degradation. AKT activation induces KSRP dissociation from H19 and, as a consequence, from myogenin mRNA that is stabilized. H19 likely acts as a scaffold that favors KSRP-mediated degradation of myogenin to contribute to the maintenance of the undifferentiated state of C2C12 cells.

Jmjd3, a JmjC family histone demethylase, is induced by the transcription factor NF‐kB in response to microbial stimuli. Jmjd3 erases H3K27me3, a histone mark associated with transcriptional repression and involved in lineage determination. However, the specific contribution of Jmjd3 induction and H3K27me3 demethylation to inflammatory gene expression remains unknown. Using chromatin immunoprecipitation‐sequencing we found that Jmjd3 is preferentially recruited to transcription start sites characterized by high levels of H3K4me3, a marker of gene activity, and RNA polymerase II (Pol_II). Moreover, 70% of lipopolysaccharide (LPS)‐inducible genes were found to be Jmjd3 targets. Although most Jmjd3 target genes were unaffected by its deletion, a few hundred genes, including inducible inflammatory genes, showed moderately impaired Pol_II recruitment and transcription. Importantly, most Jmjd3 target genes were not associated with detectable levels of H3K27me3, and transcriptional effects of Jmjd3 absence in the window of time analysed were uncoupled from measurable effects on this histone mark. These data show that Jmjd3 fine‐tunes the transcriptional output of LPS‐activated macrophages in an H3K27 demethylation‐independent manner.

Transcription factor (TF)-induced reprogramming of somatic cells into induced pluripotent stem cells (iPSC) is associated with genome-wide changes in chromatin modifications. Polycomb-mediated histone H3 lysine-27 trimethylation (H3K27me3) has been proposed as a defining mark that distinguishes the somatic from the iPSC epigenome. Here, we dissected the functional role of H3K27me3 in TF-induced reprogramming through the inactivation of the H3K27 methylase EZH2 at the onset of reprogramming. Our results demonstrate that surprisingly the establishment of functional iPSC proceeds despite global loss of H3K27me3. iPSC lacking EZH2 efficiently silenced the somatic transcriptome and differentiated into tissues derived from the three germ layers. Remarkably, the genome-wide analysis of H3K27me3 in Ezh2 mutant iPSC cells revealed the retention of this mark on a highly selected group of Polycomb targets enriched for developmental regulators controlling the expression of lineage specific genes. Erasure of H3K27me3 from these targets led to a striking impairment in TF-induced reprogramming. These results indicate that PRC2-mediated H3K27 trimethylation is required on a highly selective core of Polycomb targets whose repression enables TF-dependent cell reprogramming.

Lung cancer remains the first cause of cancer-related deaths worldwide. Thanks to the improvement in the knowledge of the biology of non-small cell lung cancer (NSCLC), patients’ survival has significantly improved. A growing number of targetable molecular alterations have been identified. Next-generation sequencing (NGS) has become one of the methodologies entered in clinical practice and was recently recommended by the European society for medical oncology (ESMO) to perform a comprehensive molecular characterization in patients with cancer. The current review provides an overview of the clinical trials that have explored the impact of NGS in patients with cancer, its limits, and advantages.

Epigenetic alterations in the pattern of DNA and histone modifications play a crucial role in cancer development. Analysis of patient samples, however, is hampered by technical limitations in the study of chromatin structure from pathology archives that usually consist of heavily fixed, paraffin-embedded material. Here, we present a methodology [pathology tissue—ChIP (PAT-ChIP)] to extract and immunoprecipitate chromatin from paraffin-embedded patient samples up to several years old. In a pairwise comparison with canonical ChIP, PAT-ChIP showed a high reproducibility of results for several histone marks and an identical ability to detect dynamic changes in chromatin structure upon pharmacological treatment. Finally, we showed that PAT-ChIP can be coupled with high-throughput sequencing (PAT-ChIP-Seq) for the genome-wide analysis of distinct chromatin modifications. PAT-ChIP therefore represents a versatile procedure and diagnostic tool for the analysis of epigenetic alterations in cancer and potentially other diseases.

The genetic structure of sweet chestnut (Castanea sativa Mill.) across Europe was assessed using 73 inter-simple sequence repeat markers to screen 1,768 individuals from 68 stands distributed across 29 sites in five European countries (Italy, France, Spain, Greece, and UK). At each site, trees were sampled from three distinct management types (domestication levels): naturalized stands, managed coppice, and grafted fruit orchards. In more than a third of the orchards, nonlocal genetic material (grafted clones) were evident, showing (as predicted) large differences from the other two domestication levels for most of the within-population genetic diversity parameters estimated. Randomly generated linkage disequilibrium analysis revealed weak though significant differences in two-locus allelic correlations between naturalized stands and coppice, suggesting that long-term management techniques may influence the genetic makeup of the populations. Multivariate analysis revealed the existence of five distinct gene pools across the study area; three were located in Greece, one on the northwestern coast of the Iberian peninsula and a large gene pool covering the rest of the Mediterranean basin. The implications of the results are discussed in relation to developing conservation strategies for chestnut genetic resources in Europe.

Statistical downscaling of climate data has been widely described in the literature, with the aim of improving the reliability of local climatic parameters from coarse-resolution (often >20 km) global datasets. In this article, we present ClimateDT, a dynamic downscaling web tool for monthly historical and future time series at a global scale. The core of ClimateDT is the 1 km 1981–2010 climatology from CHELSA Climate (version 2.1), where the CRU-TS layers for the period 1901-current are overlayed to generate a historic time series. ClimateDT also provides future scenarios from CMIP5 using UKCP18 projections (rcp2.6 and rcp8.5) and CMIP6 using 5 GCMs, also available on the CHELSA website. The system can downscale the grids using a dynamic approach (scale-free) by computing a local environmental lapse rate for each location as an adjustment for spatial interpolation. Local predictions of temperature and precipitation obtained by ClimateDT were compared with climate time series assembled from 12,000 meteorological stations, and the Mean Absolute Error (MAE) and the explained variance (R2) were used as indicators of performance. The average MAEs for monthly values on the whole temporal scale (1901–2022) were around 1.26 °C for the maximum monthly temperature, 0.80 °C for the average monthly temperature, and 1.32 °C for the minimum monthly temperature. Regarding monthly total precipitation, the average MAE was 19 mm. As for the proportion of variance explained, average R2 values were always greater than 0.95 for temperatures and around 0.70 for precipitation due to the different degrees of temporal autocorrelation of precipitation data across time and space, which makes the estimation more complex. The elevation adjustment resulted in very accurate estimates in mountainous regions and areas with complex topography and substantially improved the local climatic parameter estimations in the downscaling process. Since its first release in November 2022, more than 1300 submissions have been processed. It takes less than 2 min to calculate 45 locations and around 8 min for the full dataset (512 records).