128 Next-generation RNA sequencing of horse adipose and endometrial mesenchymal stem cells from the same donors unveils striking differences in their transcriptomic pattern
Bibliographic record
Abstract
Earlier we successfully isolated and characterised endometrial (eMSC) and adipose (aMSC) mesenchymal stem cells from the same donors. Mesenchymal stem cells share biological traits but display different surface marker phenotype and migration ability. Here we extended our research to their mRNA signature using next-generation sequencing. The RNA from cells (3 biological replicates from each cell type and 3 technical replicates) at 90% confluence was extracted using a total RNA extraction kit and sent for mRNA-Seq (Norgen, Ontario, Canada; Illumina Sequencing Platform NextSEqn 500). Raw 76-bp single-end reads were aligned against the EquCab3 genome using RNA-STAR aligner. Counts were filtrated at a minimum of 5. Pairwise comparisons between the cell types were the input for gene ontology enrichment analysis. Only genes differentially expressed (DE) with 5 folds change (FC; P < 0.05) were analysed. For DE analysis, eMSC were set as control and compared with aMSC. Unsupervised hierarchical clustering of the global gene expression signatures was done to compare the samples from each line using principal component analysis (PCA) and EdgeR: v3.20.9. Gene expression was normalized using FPKM. The heat map was built using R studio with G-plot package. A total of 14,896 transcripts with at least 5 reads were found; of these, 1598 were DE: 627 up-regulated (FC range: 2 to 236×) and 971 down-regulated (FC range: 2 to 464×) in eMSC. There was a marked dispersion in the FC of up- and down-regulated genes (>50×: 8 and 13; >20×, <50×: 9 and 17; >10×, <20×: 29 and 63; >5×, <10×: 91 and 130 and >2×, <5×: 490 and 748, respectively). Only genes DE with FC at least 5× were used for gene ontology and PCA analysis. Though 14,058 genes were common to both cell types, specific set of genes were found only in eMSC (n = 162) or aMSC (n = 676). Among the top 50 genes overexpressed in eMSC, several genes key for stem cell growth, immune response, migration and angiogenesis were found: TRIL, CXCL8, PDGF-D, SEMA5A, PTGS2, FGD, LAMA2, IL36G. In the top 50 down-regulated genes, some pivotal for osteoblast, adipogenic and neural differentiation were dramatically down-regulated (GPM6B, SCARA5 and NOTCH3 or NEFM, respectively), but no genes involved in immune rejection or stem cell proliferation were found. In gene ontology, the categories represented the most were cellular, developmental, metabolic, and immune system processes, as well as biological regulation, response to stimuli, organellar biogenesis, locomotion, localization and biological adhesion. Heat map and PCA analysis showed that one individual cell line from each type diverged markedly from the shared pattern. Individual variability of the donors may impinge upon the results; nevertheless, striking differences in the mRNA portfolio of eMSC and aMSC were detected. The importance and potential biological role of several of the genes and processes named above will be discussed in detail elsewhere. This work was supported by grant FONDECYT REGULAR 1150757 and the Government of Chile.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".