Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution.

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

Global Gene Expression Analysis Reveals Complex Cuticle Organization of the Tribolium Compound Eye.

The red flour beetle Tribolium castaneum is a resource-rich model for genomic and developmental studies. To extend previous studies on Tribolium eye development, we produced transcriptomes for normal-eyed and eye-depleted heads of pupae and adults to identify differentially transcript-enriched (DE) genes in the visual system. Unexpectedly, cuticle-related genes were the largest functional class in the pupal compound eye DE gene population, indicating differential enrichment in three distinct cuticle components: clear lens facet cuticle, highly melanized cuticle of the ocular diaphragm, which surrounds the Tribolium compound eye for internal fortification, and newly identified facet margins of the tanned cuticle, possibly enhancing external fortification. Phylogenetic, linkage, and high-throughput gene knockdown data suggest that most cuticle proteins (CPs) expressed in the Tribolium compound eye stem from the deployment of ancient CP genes. Consistent with this, TcasCPR15, which we identified as the major lens CP gene in Tribolium, is a beetle-specific but pleiotropic paralog of the ancient CPR RR-2 CP gene family. The less abundant yet most likely even more lens-specific TcasCP63 is a member of a sprawling family of noncanonical CP genes, documenting a role of local gene family expansions in the emergence of the Tribolium compound eye CP repertoire. Comparisons with Drosophila and the mosquito Anopheles gambiae reveal a steady turnover of lens-enriched CP genes during insect evolution.

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.

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single cell resolution.

Synthetic glucocorticoids, such as dexamethasone, have been used as treatment for many immune conditions, such as asthma and more recently severe COVID-19. Single cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.

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.

Single cell transcriptional signatures of the human placenta in term and preterm parturition.

More than 135 million births occur each year; yet, the molecular underpinnings of human parturition in gestational tissues, and in particular the placenta, are still poorly understood. The placenta is a complex heterogeneous organ including cells of both maternal and fetal origin, and insults that disrupt the maternal-fetal dialogue could result in adverse pregnancy outcomes such as preterm birth. There is limited knowledge of the cell type composition and transcriptional activity of the placenta and its compartments during physiologic and pathologic parturition. To fill this knowledge gap, we used scRNA-seq to profile the placental villous tree, basal plate, and chorioamniotic membranes of women with or without labor at term and those with preterm labor. Significant differences in cell type composition and transcriptional profiles were found among placental compartments and across study groups. For the first time, two cell types were identified: 1) lymphatic endothelial decidual cells in the chorioamniotic membranes, and 2) non-proliferative interstitial cytotrophoblasts in the placental villi. Maternal macrophages from the chorioamniotic membranes displayed the largest differences in gene expression (e.g. NFKB1) in both processes of labor; yet, specific gene expression changes were also detected in preterm labor. Importantly, several placental scRNA-seq transcriptional signatures were modulated with advancing gestation in the maternal circulation, and specific immune cell type signatures were increased with labor at term (NK-cell and activated T-cell signatures) and with preterm labor (macrophage, monocyte, and activated T-cell signatures). Herein, we provide a catalogue of cell types and transcriptional profiles in the human placenta, shedding light on the molecular underpinnings and non-invasive prediction of the physiologic and pathologic parturition.

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.

Multifunctional glial support by Semper cells in the Drosophila retina.

Glial cells play structural and functional roles central to the formation, activity and integrity of neurons throughout the nervous system. In the retina of vertebrates, the high energetic demand of photoreceptors is sustained in part by Müller glia, an intrinsic, atypical radial glia with features common to many glial subtypes. Accessory and support glial cells also exist in invertebrates, but which cells play this function in the insect retina is largely undefined. Using cell-restricted transcriptome analysis, here we show that the ommatidial cone cells (aka Semper cells) in the Drosophila compound eye are enriched for glial regulators and effectors, including signature characteristics of the vertebrate visual system. In addition, cone cell-targeted gene knockdowns demonstrate that such glia-associated factors are required to support the structural and functional integrity of neighboring photoreceptors. Specifically, we show that distinct support functions (neuronal activity, structural integrity and sustained neurotransmission) can be genetically separated in cone cells by down-regulating transcription factors associated with vertebrate gliogenesis (pros/Prox1, Pax2/5/8, and Oli/Olig1,2, respectively). Further, we find that specific factors critical for glial function in other species are also critical in cone cells to support Drosophila photoreceptor activity. These include ion-transport proteins (Na/K+-ATPase, Eaat1, and Kir4.1-related channels) and metabolic homeostatic factors (dLDH and Glut1). These data define genetically distinct glial signatures in cone/Semper cells that regulate their structural, functional and homeostatic interactions with photoreceptor neurons in the compound eye of Drosophila. In addition to providing a new high-throughput model to study neuron-glia interactions, the fly eye will further help elucidate glial conserved "support networks" between invertebrates and vertebrates.

Regulation of HBEGF by Micro-RNA for Survival of Developing Human Trophoblast Cells.

INTRODUCTION: The growth factor HBEGF is upregulated post-transcriptionally in the low O2 environment of the human placenta during the first 10 weeks of pregnancy. We have examined the possible roles of HBEGF turnover and micro-RNA (miRNA) in its regulation by O2 in human first trimester trophoblast. METHODS: HTR-8/SVneo trophoblast cells were cultured at 2% or 20% O2. The cells were transfected with a dual luciferase reporter construct (psiCHECK-2) containing no insert (control), the HBEGF 3' untranslated region (3'UTR), or sub-regions of the 3'UTR, as well as with siRNA for DGCR8. RNA was extracted from trophoblast cells cultured at 2% O2 for 0-4 h for next-generation sequencing. HBEGF was quantified by ELISA. HBEGF, DGCR8, and ß-actin were examined by western blotting. RESULTS: Protein turnover studies, using 10 µg/ml cyclohexamide, 1 µg/ml lactocystin, or 100 µg/ml MG132, demonstrated faster HBEGF degradation at 20% O2 than 2% O2, mediated by the proteasome. However, proteasome inhibition failed to initiate HBEGF accumulation at 20% O2. Reporter assays, comparing to empty vector, demonstrated that the intact HBEGF 3' UTR inhibited expression (0.26), while fragments containing only its flanking regions increased reporter activity (3.15; 3.43). No differential expression of miRNAs was found in trophoblast cells cultured at 2% and 20% O2. Nevertheless, HBEGF upregulation at 2% O2 was blocked when the miRNA-processing protein DGCR8 was silenced, suggesting a role for miRNA. CONCLUSION: Our findings suggest involvement of flanking regions of the 3'UTR in activating HBEGF protein synthesis in response to 2% O2, possibly through a miRNA-mediated mechanism.

Response to Comment on "Absence of sperm RNA elements correlates with idiopathic male infertility".

RNAs from other cell types have minimal impact on male fecundity-associated sperm RNA elements.

The protein and transcript profiles of human semen.

The increasing use of "-omics" (genomic, transcriptomic, proteomic, epigenomic, and metabolomic) high-throughput measurement technologies over the past decade is beginning to reveal the complexity of human biology and physiology through the interactions of DNA, RNA, related proteins and small molecules. In reproductive medicine, the majority of this work, has thus far focused on the female factors, e.g., the oocyte, since they provide both the environment and the majority of elements required for embryogenesis. State-of-the-art sequencing and computational analyses have enabled a deeper understanding of the underlying components. Contrary to being simply a silent delivery vehicle to the oocyte of the packaged male DNA, sperm provide both a specific epigenetically marked genome together with a complex population of RNAs and proteins that are crucial for early embryogenesis. In addition to the sperm, seminal fluid appears to serve multiple roles providing a supplementary series of components that allow the sperm to successfully reach and fertilize the oocyte and prepare the female immune system to tolerate the semiallosteric embryo. A global analysis and review of what is presently known regarding the unique role of each component of the male factor and their associated interactions begins to shed light on this emergent field.

Absence of sperm RNA elements correlates with idiopathic male infertility.

Semen parameters are typically used to diagnose male infertility and specify clinical interventions. In idiopathic infertile couples, an unknown male factor could be the cause of infertility even when the semen parameters are normal. Next-generation sequencing of spermatozoal RNAs can provide an objective measure of the paternal contribution and may help guide the care of these couples. We assessed spermatozoal RNAs from 96 couples presenting with idiopathic infertility and identified the final reproductive outcome and sperm RNA elements (SREs) reflective of fecundity status. The absence of required SREs reduced the probability of achieving live birth by timed intercourse or intrauterine insemination from 73 to 27%. However, the absence of these same SREs does not appear to be critical when using assisted reproductive technologies such as in vitro fertilization with or without intracytoplasmic sperm injection. About 30% of the idiopathic infertile couples presented an incomplete set of required SREs, suggesting a male component as the cause of their infertility. Conversely, analysis of couples that failed to achieve a live birth despite presenting with a complete set of SREs suggested that a female factor may have been involved, and this was confirmed by their diagnosis. The data in this study suggest that SRE analysis has the potential to predict the individual success rate of different fertility treatments and reduce the time to achieve live birth.

A comparison of sperm RNA-seq methods.

A significant challenge to the effective application of RNA-seq to the complete transcript analysis of low quantity and/or degraded samples is the amplification of minimal input RNA to enable sequencing library construction. Several strategies have been commercialized in order to facilitate this goal. However, each strategy has its own specific protocols and methodology, and each may introduce unique bias and in some cases show specific preference for a collection of sequences. Our wider investigation of human spermatozoal RNAs was able to reveal their complexity despite being generally characterized by low quantity and high fragmentation. In this study, the following four commercially available RNA-seq amplification and library protocols for the preparation of low quantity/highly fragmented samples, SMARTer™ Ultra Low RNA (SU) for Illumina® Sequencing, SeqPlex RNA Amplification (SP), Ovation® RNA-Seq System V2 (OR), and Ovation® RNA-Seq Formalin Fixed Paraffin Embedded System (FFPES) were assessed using human sperm RNAs. Further investigation analyzed the effects on the end results of two different library preparation methods, Encore NGS Multiplex System I (Enc) and Ovation Ultralow Library Systems (UL), that appeared best suited to this type of RNA, along with other potential confounding factors such as FFPE preservation. Our results indicate that for each library preparation protocol, the differences in the initial amount of input RNA and choice of RNA purification step do not generate marked differences in terms of RNA profiling. However, substantial disparity is introduced by individual amplification methods prior to library construction. These significant differences may be caused by the different priming methods or amplification strategies used in each of the four different protocols examined. The observation of intra-sample variation introduced by the choice of protocol highlights the role that external factors play in planning and subsequent reliable interpretation of results of any RNA-seq experiment.

The presence, role and clinical use of spermatozoal RNAs.

BACKGROUND Spermatozoa are highly differentiated, transcriptionally inert cells characterized by a compact nucleus with minimal cytoplasm. Nevertheless they contain a suite of unique RNAs that are delivered to oocyte upon fertilization. They are likely integrated as part of many different processes including genome recognition, consolidation-confrontation, early embryonic development and epigenetic transgenerational inherence. Spermatozoal RNAs also provide a window into the developmental history of each sperm thereby providing biomarkers of fertility and pregnancy outcome which are being intensely studied. METHODS Literature searches were performed to review the majority of spermatozoal RNA studies that described potential functions and clinical applications with emphasis on Next-Generation Sequencing. Human, mouse, bovine and stallion were compared as their distribution and composition of spermatozoal RNAs, using these techniques, have been described. RESULTS Comparisons highlighted the complexity of the population of spermatozoal RNAs that comprises rRNA, mRNA and both large and small non-coding RNAs. RNA-seq analysis has revealed that only a fraction of the larger RNAs retain their structure. While rRNAs are the most abundant and are highly fragmented, ensuring a translationally quiescent state, other RNAs including some mRNAs retain their functional potential, thereby increasing the opportunity for regulatory interactions. Abundant small non-coding RNAs retained in spermatozoa include miRNAs and piRNAs. Some, like miR-34c are essential to the early embryo development required for the first cellular division. Others like the piRNAs are likely part of the genomic dance of confrontation and consolidation. Other non-coding spermatozoal RNAs include transposable elements, annotated lnc-RNAs, intronic retained elements, exonic elements, chromatin-associated RNAs, small-nuclear ILF3/NF30 associated RNAs, quiescent RNAs, mse-tRNAs and YRNAs. Some non-coding RNAs are known to act as epigenetic modifiers, inducing histone modifications and DNA methylation, perhaps playing a role in transgenerational epigenetic inherence. Transcript profiling holds considerable potential for the discovery of fertility biomarkers for both agriculture and human medicine. Comparing the differential RNA profiles of infertile and fertile individuals as well as assessing species similarities, should resolve the regulatory pathways contributing to male factor infertility. CONCLUSIONS Dad delivers a complex population of RNAs to the oocyte at fertilization that likely influences fertilization, embryo development, the phenotype of the offspring and possibly future generations. Development is continuing on the use of spermatozoal RNA profiles as phenotypic markers of male factor status for use as clinical diagnostics of the father's contribution to the birth of a healthy child.

Stability, delivery and functions of human sperm RNAs at fertilization.

Increasing attention has focused on the significance of RNA in sperm, in light of its contribution to the birth and long-term health of a child, role in sperm function and diagnostic potential. As the composition of sperm RNA is in flux, assigning specific roles to individual RNAs presents a significant challenge. For the first time RNA-seq was used to characterize the population of coding and non-coding transcripts in human sperm. Examining RNA representation as a function of multiple methods of library preparation revealed unique features indicative of very specific and stage-dependent maturation and regulation of sperm RNA, illuminating their various transitional roles. Correlation of sperm transcript abundance with epigenetic marks suggested roles for these elements in the pre- and post-fertilization genome. Several classes of non-coding RNAs including lncRNAs, CARs, pri-miRNAs, novel elements and mRNAs have been identified which, based on factors including relative abundance, integrity in sperm, available knockout data of embryonic effect and presence or absence in the unfertilized human oocyte, are likely to be essential male factors critical to early post-fertilization development. The diverse and unique attributes of sperm transcripts that were revealed provides the first detailed analysis of the biology and anticipated clinical significance of spermatozoal RNAs.

Local and global factors affecting RNA sequencing analysis.

High-throughput RNA sequencing (RNA-seq) continues to provide unparalleled insight into transcriptome complexity. Now the "gold standard" for assessing global transcript levels, RNA-seq is poised to revolutionize our understanding of transcription and posttranscriptional regulation of RNA. Despite significant advantages over prior experimental strategies, RNA-seq is not without pitfalls. We have identified a number of confounding factors that significantly affect sequencing coverage. These include regional GC content, preferential sites of fragmentation, and read "pile-up" due to primer affinity and transcript end effects. Independent of cell type and laboratory, when ignored, these factors can bias analyses. Understanding the underlying principles responsible for producing these artifacts is key to recognizing both their presence and how their effects may be controlled. Here we outline the causes of and strategies to avoid several previously unreported complicating factors common to RNA-seq experiments.

Strategy for microbiome analysis using 16S rRNA gene sequence analysis on the Illumina sequencing platform.

Understanding the identity and changes of organisms in the urogenital and other microbiomes of the human body may be key to discovering causes and new treatments of many ailments, such as vaginosis. High-throughput sequencing technologies have recently enabled discovery of the great diversity of the human microbiome. The cost per base of many of these sequencing platforms remains high (thousands of dollars per sample); however, the Illumina Genome Analyzer (IGA) is estimated to have a cost per base less than one-fifth of its nearest competitor. The main disadvantage of the IGA for sequencing PCR-amplified 16S rRNA genes is that the maximum read-length of the IGA is only 100 bases; whereas, at least 300 bases are needed to obtain phylogenetically informative data down to the genus and species level. In this paper we describe and conduct a pilot test of a multiplex sequencing strategy suitable for achieving total reads of > 300 bases per extracted DNA molecule on the IGA. Results show that all proposed primers produce products of the expected size and that correct sequences can be obtained, with all proposed forward primers. Various bioinformatic optimization of the Illumina Bustard analysis pipeline proved necessary to extract the correct sequence from IGA image data, and these modifications of the data files indicate that further optimization of the analysis pipeline may improve the quality rankings of the data and enable more sequence to be correctly analyzed. The successful application of this method could result in an unprecedentedly deep description (800,000 taxonomic identifications per sample) of the urogenital and other microbiomes in a large number of samples at a reasonable cost per sample.