scholarly journals Single Nucleus Transcriptome and Chromatin Accessibility Landscapes of Human Pituitaries

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A653-A654
Author(s):  
Frederique Murielle Ruf-Zamojski ◽  
Zidong Zhang ◽  
Michel Zamojski ◽  
Gregory R Smith ◽  
Val Yianni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Pituitary Cell ◽  
Intermediate Lobe ◽  
Pars Tuberalis ◽  
Human Pituitary ◽  
Regulatory Pathways

Abstract The pituitary gland regulates key physiological functions, including growth, sexual maturation, reproduction, and lactation. Here, we present a paired single-nuclei (sn) transcriptome and chromatin accessibility characterization of six post-mortem human pituitaries. These samples were from juvenile, adult, and elderly male and female subjects. Well-correlated snRNAseq and snATACseq datasets facilitated robust identification of the major pituitary cell types in each sample. Using latent variable pathway analysis, we uncovered previously unreported coordinated gene expression modules and chromatin accessibility programs for each major cell type as well as an age-specific program across all the endocrine cell types. These largely appear to be congruent between human and mouse datasets. Given the importance of murine models in the study of human pituitary disorders and pituitary physiology, we next sought to compare expression profiles of pituitary cell types in mouse vs. human. Murine and human cell types were well correlated, exemplified by coordinated gene expression programs, especially for undifferentiated stem cells (SCs). In both species, we identified clusters corresponding to naive and committing SCs. All human SC clusters expressed the established SC markers SOX2 and SOX9, as well as genes involved in SC regulatory pathways (WWTR1, YAP1 andPITX2). Additional markers previously reported in murine pituitary SCs were also found in human SC, including WIF1, LGR5, FOS, CDH1, EGFR, LGR4, and WLS. Remarkably, in human, the main naive SC cluster was roughly divided into a high-JUN and a low-JUN expressing subgroup, whereas Jun expression was less pronounced in the murine SC cluster. In both species, committing SC clusters expressed the endocrine markers for POU1F1, TSHB, or POMC, while SCs committing to an intermediate lobe/melanotrope cell identity were distinguishable based on PAX7 expression. In addition, in the human datasets we identify a population of cells as originating from the pars tuberalis. We offer a range of markers that can be utilized for in vivo validation of these cells. Overall, the characterization of the murine and human pituitary SCs strongly suggests the co-existence of subpopulations with different lineage commitments in addition to a single uncommitted SC population. This sn atlas of the human pituitary is a valuable resource that will be made web-accessible.

scholarly journals Analysis of the transcriptome of bovine endometrial cells isolated by laser micro-dissection (1): specific signatures of stromal, glandular and luminal epithelial cells

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Wiruntita Chankeaw ◽  
Sandra Lignier ◽  
Christophe Richard ◽  
Theodoros Ntallaris ◽  
Mariam Raliou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Localization ◽  
Expression Profiles ◽  
Cell Types ◽  
Molecular Signature ◽  
Receptor Protein ◽  
Specific Gene ◽  
Specific Cell ◽  
Biological Processes ◽  
Endometrial Cells

Abstract Background A number of studies have examined mRNA expression profiles of bovine endometrium at estrus and around the peri-implantation period of pregnancy. However, to date, these studies have been performed on the whole endometrium which is a complex tissue. Consequently, the knowledge of cell-specific gene expression, when analysis performed with whole endometrium, is still weak and obviously limits the relevance of the results of gene expression studies. Thus, the aim of this study was to characterize specific transcriptome of the three main cell-types of the bovine endometrium at day-15 of the estrus cycle. Results In the RNA-Seq analysis, the number of expressed genes detected over 10 transcripts per million was 6622, 7814 and 8242 for LE, GE and ST respectively. ST expressed exclusively 1236 genes while only 551 transcripts were specific to the GE and 330 specific to LE. For ST, over-represented biological processes included many regulation processes and response to stimulus, cell communication and cell adhesion, extracellular matrix organization as well as developmental process. For GE, cilium organization, cilium movement, protein localization to cilium and microtubule-based process were the only four main biological processes enriched. For LE, over-represented biological processes were enzyme linked receptor protein signaling pathway, cell-substrate adhesion and circulatory system process. Conclusion The data show that each endometrial cell-type has a distinct molecular signature and provide a significantly improved overview on the biological process supported by specific cell-types. The most interesting result is that stromal cells express more genes than the two epithelial types and are associated with a greater number of pathways and ontology terms.

scholarly journals Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bing He ◽  
Ping Chen ◽  
Sonia Zambrano ◽  
Dina Dabaghie ◽  
Yizhou Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Kidney ◽  
Cell Types ◽  
Model Organisms ◽  
Mural Cell ◽  
Glomerular Cell ◽  
Individual Gene ◽  
The Individual

AbstractMolecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

scholarly journals LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanan Ren ◽  
Ting-You Wang ◽  
Leah C. Anderton ◽  
Qi Cao ◽  
Rendong Yang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Regulatory Pathways ◽  
Cancer Transcriptome ◽  
Versatile Tool

Abstract Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

Characterization of gene expression profiles at low and very low doses of ionizing radiation

DNA Repair ◽  
2013 ◽  
Vol 12 (7) ◽  
pp. 508-517 ◽  
Author(s):  
Ingrid Nosel ◽  
Aurélie Vaurijoux ◽  
Joan-Francesc Barquinero ◽  
Gaetan Gruel
Keyword(s):  
Gene Expression ◽  
Ionizing Radiation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Low Doses

Gene Expression Regulation underlying Osteo-, Adipo-, and Chondro-Genic Lineage Commitment of Human Mesenchymal Stem Cells

2013 ◽  
pp. 76-94 ◽  
Author(s):  
Ana M. Sotoca ◽  
Michael Weber ◽  
Everardus J. J. van Zoelen
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Gene Expression Regulation ◽  
Expression Profiles ◽  
Human Mesenchymal Stem Cells ◽  
Gene Expression Profiles ◽  
Stem Cell Differentiation ◽  
Cell Types ◽  
Lineage Commitment

Human mesenchymal stem cells have a high potential in regenerative medicine. They can be isolated from a variety of adult tissues, including bone marrow, and can be differentiated into multiple cell types of the mesodermal lineage, including adipocytes, osteocytes, and chondrocytes. Stem cell differentiation is controlled by a process of interacting lineage-specific and multipotent genes. In this chapter, the authors use full genome microarrays to explore gene expression profiles in the process of Osteo-, Adipo-, and Chondro-Genic lineage commitment of human mesenchymal stem cells.

Histopathology of pituitary tumours

2011 ◽  
pp. 121-127
Author(s):  
Eva Horvath ◽  
Kalman Kovacs
Keyword(s):  
Mammalian Species ◽  
Cell Types ◽  
Pars Intermedia ◽  
Pars Tuberalis ◽  
Posterior Lobe ◽  
Human Pituitary ◽  
Human Pituitary Gland ◽  
Fibre Network ◽  
Pars Anterior ◽  
A Minor

The human pituitary gland consists of two major components: the adenohypophysis comprising the hormone producing cells of the pars anterior, pars intermedia, and pars tuberalis, and the neurohypophysis, also called pars nervosa or posterior lobe (1). In contrast to most mammalian species, the human gland has no anatomically distinct pars intermedia (2). The exclusively proopiomelanocortin (POMC)-producing cells of the pars intermedia are sandwiched between the anterior and posterior lobes in the majority of mammals, whereas in the human they are incorporated within the pars anterior, thereby constituting the pars distalis (3). The pars tuberalis is a minor upward extension of the adenohypophysis attached to the exterior of the lower pituitary stalk. In this chapter we deal only with adenohypophyseal tumours. Histologically, the adenohypophysis consists of a central median (or mucoid) wedge flanked by the two lateral wings. The hormone-producing cell types are distributed in an uneven, but characteristic manner. The cells are arranged within evenly sized acini surrounded by a delicate but well-defined reticulin fibre network giving the pituitary its distinct architecture (4). In the center of the acini is the long-neglected pituitary follicle composed of the agranular nonendocrine folliculo-stellate cells (5).

scholarly journals Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Julien Racle ◽  
Kaat de Jonge ◽  
Petra Baumgaertner ◽  
Daniel E Speiser ◽  
David Gfeller
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Types ◽  
Response To Therapy ◽  
Expression Data ◽  
Cell Type ◽  
Tumor Gene Expression ◽  
Tumor Gene

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

Sign in / Sign up

Export Citation Format

Share Document