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Record W3158563321 · doi:10.1210/jendso/bvab048.1332

Single Nucleus Transcriptome and Chromatin Accessibility Landscapes of Human Pituitaries

2021· article· en· W3158563321 on OpenAlexaff
Frederique Murielle Ruf-Zamojski, Zidong Zhang, Michel Zamojski, Gregory R. Smith, Val Yianni, Thea L. Willis, Natalia Mendelev, Hanna Pinças, Nitish Seenarine, Mary Anne S. Amper, Mital Vasoya, Xiang Zhou, Luisina Ongaro Gambino, Gauthier Schang, Sagie Mofsowitz, Venugopalan D. Nair, Corrine K. Welt, Olga G. Troyanskaya, Judith L. Turgeon, Daniel J. Bernard, Cynthia L. Andoniadou, Stuart C. Sealfon

Bibliographic record

VenueJournal of the Endocrine Society · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyTranscriptomeCell typeChromatinSOX2SMARCA4GeneLGR5CellGeneticsGene expressionInternal medicineWnt signaling pathwayTranscription factorChromatin remodelingMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.251
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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