Estrogen distinctly regulates transcription and translation of lncRNAs and pseudogenes in breast cancer cells.

Estrogen drives key transcriptional changes in breast cancer and stimulates breast cancer cells' growth with multiple mechanisms to coordinate transcription and translation. In addition to protein-coding transcripts, estrogen can regulate long non-coding RNA (lncRNA) transcripts, plus diverse non-coding RNAs including antisense, enhancer, and intergenic. LncRNA genes comprise the majority of human genes. The accidental, or regulated, translation of their short open reading frames by ribosomes remains a controversial topic. Here we report for the first time an integrated analysis of RNA abundance and ribosome occupancy level, using Ribo-seq combined with RNA-Seq, in the estrogen-responsive, estrogen receptor α positive, human breast cancer cell model MCF7, before and after hormone treatment. Translational profiling can determine, in an unbiased manner, which fraction of the genome is actually translated into proteins, as well as resolving whether transcription and translation respond concurrently, or differentially, to estrogen treatment. Our data showed specific transcripts more robustly detected in RNA-Seq than in the ribosome-profiling data, and vice versa, suggesting distinct gene-specific estrogen responses at the transcriptional and the translational level, respectively. Here, we showed that estrogen stimulation affects the expression levels of numerous lncRNAs, but not their association with ribosomes, and that most lncRNAs are not ribosome-bound. For the first time, we also demonstrated the transcriptional and translational response of expressed pseudogenes to estrogen, pointing to new perspectives for drug-target development in breast cancer in the future.

Derangement of Metabolic and Lysosomal Gene Profiles in Response to Dexamethasone Treatment in Sarcoidosis.

Glucocorticoids (GCs) play a central role in modulation of inflammation in various diseases, including respiratory diseases such as sarcoidosis. Surprisingly, the specific anti-inflammatory effects of GCs on different myeloid cells especially in macrophages remain poorly understood. Sarcoidosis is a systemic granulomatous disease of unknown etiology that occurs worldwide and is characterized by granuloma formation in different organs. Alveolar macrophages play a role in sarcoidosis granuloma formation and progressive lung disease. The goal of the present study is to identify the effect of GCs on transcriptomic profiles and the cellular pathways in sarcoidosis alveolar macrophages and their corresponding blood myeloid cells. We determined and compared the whole transcriptional signatures of alveolar macrophages from sarcoidosis patients and blood CD14+ monocytes of the same subjects in response to in vitro treatment with dexamethasone (DEX) via RNA-sequencing. In response to DEX, we identified 2,834 genes that were differentially expressed in AM. Predominant pathways affected were as following: metabolic pathway (FDR = 4.1 × 10-10), lysosome (FDR = 6.3 × 10-9), phagosome (FDR = 3.9 × 10-5). The DEX effect on AMs is associated with metabolic derangements involving glycolysis, oxidative phosphorylation and lipid metabolisms. In contrast, the top impacted pathways in response to DEX treatment in blood CD14+ monocytes were as following; cytokine-cytokine receptor interaction (FDR = 6 × 10-6) and transcriptional misregulation in cancer (FDR = 1 × 10-4). Pathways similarly affected in both cell types were genes involved in lysosomes, cytoskeleton and transcriptional misregulation in cancer. These data suggest that the different effects of DEX on AMs and peripheral blood monocytes are partly dictated by lineage specific transcriptional programs and their physiological functions.

Sperm RNA elements as markers of health.

Idiopathic infertility, an etiology not identified as part of standard clinical assessment, represents approximately 20% of all infertility cases. Current male infertility diagnosis focuses on the concentration, motility, and morphology of spermatozoa. This is of limited value when predicting birth success and of limited utility when selecting the optimum treatment. At fertilization, spermatozoa provide their genomic contribution, as well as a set of RNAs and proteins that have distinct roles in development. The potential of spermatozoal RNAs to be used as a prognostic of live birth has been shown [Jodar et al. (2015) Science Translational Medicine 7(295):295re6]. This relied on a set of 648 sperm RNA elements derived from 285 genes that are perhaps indicative of future health status. To address this tenet, the present study correlated the levels of each transcript among all samples to assess linkage between transcript absence, birth success, and possible disease association. Correlations between transcript levels of the 285 genes were analyzed amongst themselves, and within the context of the entire transcript population for these samples. The transcripts ACE, GIGYF2, and ODF2 had many negative correlations and form the majority of correlations, suggesting an important function for these transcripts. Eleven of the 285 queried genes had disease-associated variants within a sperm RNA element. Three genes, GPX4, NDRG1, and RPS24 had SREs were absent in at least one individual from the test cohort. GPX4 and RPS24 are associated with developmental defects and/or neonatal lethality. This leaves the intriguing possibility that, while sperm RNAs delivered to the oocyte inform the success of live birth, they may also be predictors of human health. ABBREVIATIONS: GO: Gene Ontology; ART: assisted reproductive technology; IVF: in vitro fertilization; ICSI: intra-cytoplasmic sperm injection; RNA-seq: RNA-sequencing; TIC: timed intercourse; IUI: intrauterine insemination; SRE: sperm RNA elements; HPA: Human Protein Atlas; SMDS: sedaghatian-type spondylometaphyseal dysplasia; DBA: Diamond-Blackfan anemia; RPKM: reads per kilobase per million; TPM: transcripts per million; IPA: Ingenuity Pathway Analysis; OMIM: Online Mendelian Inheritance in Man.