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Table 8 Upstream regulators predicted by target gene expression in the atretic versus healthy dataset

From: Transcriptome profiling of granulosa cells from bovine ovarian follicles during atresia

Upstream regulator

Predicted activation state

Bias-corrected z-Score

P value of overlap

Target molecules in dataset

TP53

activated

4.272

5.78E-11

ALB, ANXA1, ANXA2, ARHGEF2, ARPC1B, ATF3, CALD1, CAV1, CFLAR, CLIC4, CNN1, COL18A1, COL1A2, COL3A1, COL4A1, CTGF, CTSH, CYR61, DKK3, DUSP1, EGR1, FBLN2, FERMT2, GADD45A, GLRX, GPX3, GSN, HMGCS1, ID1, ID3, IER3, IFI30, IGF2, IGFBP5, JUN, KRT8, LGALS3, MAP4K1, MMP23B, MPDZ, NDRG1, NOS2, NR2F1, PCDH7, PDE6A, PGFRA, PHLDA1, PIM1, PLAUR, POSTN, RAD51AP1, SAT1, SERPINE1, SGK1, SNAI2, SPP1, STAU1, STK17A, TAGLN2, TGFBR2, THBS2, TOP2A, TP53INP1, VCL, VEGFA

FOXO4

activated

2.203

5.41E-05

BCL6, CTGF, GADD45A, HMGCS1, IER3, SERPINE1, SGK1, VEGFA

CEBPB

activated

2.142

1.59E-07

ALB, CEBPD, COL1A2, CPT1A, CSN2, CYP19A1, DAB2, DCN, GADD45A, GLIPR2, ID1, IFIT, M3, MGP, MMP11, NDRG4, NOS2, PDGFRA, PDK4, PLAUR, SAT1, SERPINE1, SGK1, SPP1, STAR, TMEM176A, TNFAIP6, TOP1

RXRA

inhibited

-2.100

3.52E-04

CEBPD, CPT1A, CYP2C9, FABP5, GCLC, GPT, IER3, LPL, MGP, MMP11, OLR1, PNMT, SAT1, SLC10A2, SPP1, STAR, VEGFA

HNF1A

inhibited

-2.168

4.07E-01

ALB, BCL6, C1S, CD55, COL3A1, IHH, SERPINE1, SLC10A2, SLC40A1, SLC4A2, UGT2B4

MYC

inhibited

-3.197

7.80E-07

ACTN1, ALB, AQP1, BCL6, CALD1, CAST, CAV1, CD9, CEBPD, CFLAR, CLIC4, COL1A2, COL3A1, COL4A1, CPT1A, CSTB, DSTN, DUSP1, FABP5, FBLN2, GADD45A, GCLC, GTF2F2, HLA-A, ID1, ID3, IER3, KLF6, LUM, NDRG1, PLAUR, PLP1, POLR3D, SGK1, SPP1, TAGLN2, TGFBR2, THBS2, TIMP1, TLN1, TSPO, VEGFA

MYCN

inhibited

-3.202

8.50E-03

ARPC1B, CAV1, CCNT1, CITED2, COL18A1, COL4A1, CTGF, DKK3, FGFR2, HLA-A, SDC2, SERPINE1, TAGLN

  1. The predicted activation state is inferred from the bias-corrected z-score, (+ = activated, - = inhibited). The bias-corrected z-score is computed based on the proportion of target genes present in the dataset which are directionally regulated as expected according to known effects of the regulator on the target compiled from the literature. The P value of overlap measures the statistical significance of overlap using Fisher’s exact t-test, between genes from the dataset and those known to be acted upon by an upstream regulator.