Skip to main content

Table 4 Upstream regulators predicted to be activated or inhibited in large follicles compared with small follicles, using the 3-fold differentially-regulated data set with FDR P < 0.05, on the basis of known interactions compiled in the IPA Upstream Regulator analysis

From: Transcriptome profiling of granulosa cells of bovine ovarian follicles during growth from small to large antral sizes

Upstream regulator

Molecule type

*Activation z-score

** P- value of overlap

Target genes in the data set

Predicted activated molecules/genes

 

Tacrolimus

Chemical drug

3.302

2.1×10-2

ABLIM1, ACTA1, CDK13, COL1A1, CYBB, FOS, ID3, IL33, MYC, PDCD4, PTGS2

STAT4

Transcription regulator

3.300

4.8×10-2

AKAP8L, ARFGAP3, ERRFI1, GLG1, IER3, MGARP, PYGL, RCN3, RNF128, SF3B1, WHSC1L1

Chorionic gonadotrophin

Hormone

3.224

2.4×10-9

ABCB1, AKR1C3, CDH2, CLU, CYP11A1, CYP19A1, F2RL1, HSD3B2, IER3, IGFBP4, IL33, IL4R, INHBA, ITGB5, LGALS3BP, LHCGR, MTPN, NPR3, NR5A2, NRP1, PFKFB3, PGR, PLAT, PPAP2B, PTGFR, PTGS2, SFRP4, STAR, TIMP1, TNFAIP6, VCAN

XBP1

Transcription regulator

2.887

1.5×10-3

APBB2, APOA1, ARFGAP3, COPZ1, DERL1, EDEM2, GOLGA4, HERPUD1, HM13, HMOX1, MYC, RCN3, RRT1, SEC63, VCAM1

FSH

Hormone

2.759

1.8×10-4

ACTA1, BCL2L2, BMPR1A, BMPR2, CDH2, CITED1, CYP11A1, CYP19A1, FOS, GRK5, HSD3B2, IGFBP4, INHBA, ITGB5, LHCGR, MAPK6, MYC, NOL3, PGR, PLAT, PTGS2, RPRM, STAR, TIMP1, TIMP2, TNFAIP6, TOB1

FOXO 3

Transcription regulator

2.613

7.4×10-2

EIF4EBP1, FGFR2, GABARAPL1, GADD45B, IER3, MYC, SLC40A1, TXNIP

AGN194204

Chemical drug

2.550

2.4×10-3

ANAPC5, BZW2, CLIC4, FDFT1, IL4R, KLF6, MAN1A1, MYC, PDCD4, RCAN3, STIM1, STRA6, TIMP1

Forskolin

Chemical toxicant

2.444

3.4×10-5

ACTA1, APOA1, ATP6V1A, CARTPT, CDH2, CLU, COL1A1, CYP11A1, CYP19A1, FOS, GRK5, HMOX1, HSD3B2, ID2, ID3, IGFBP6, INHBA, ITGB5, LARGE, LHCGR, LTF, MYC, NOL3, NT5E, PGR, PLAT, PTGS2, PTHLH, RAB7A, RPRM, SCG2, STAR, TIMP1, TNFAIP6, TXNIP, VCAN

INHBA

Growth factor

2.389

3.2×10-2

CPNE8, CYP11A1, CYP19A1, DTNA, INHBA, LHCGR, PRPF38B, STAR, TIMP1

GATA6

Transcription regulator

2.377

5.6×10-3

BMPR2, CYP11A1, CYP19A1, HSD3B2, LHCGR, STAR

8-bromo-cAMP

Chemical reagent

2.287

2.1×10-4

APOA1, CLU, CYP11A1, CYP19A1, FOS, HSD3B2, LHCGR, MYC, PGR, PLAT, PTGFR, PTGS2, STAR, TIMP1, TIMP2

Bucladesine

Chemical toxicant

2.166

1.0×10-4

CDH2, CLU, CYP11A1, CYP19A1, ENPP1, ERRFI1, F3, FOS, GADD45B, HMOX1, HSD3B2, IGFBP6, KIT, MYC, PTGS2, QSOX1, RGN, SCG2, STAR, TIMP1, TIMP2

Vegf

Cytokine

2.008

2.6×10-4

ABCB1, ADAM10, ANGPT2, ANGPTL2, BMP2K, F3, GRK5, HES1, HMOX1, IGFBP4, INHBA, LPHN2, LRP8, MYC, NOTCH1, NR5A2, NRP1, PPAP2B, PTGS2, PTHLH, TIMP1, TRIB2, VCAM1

Predicted inhibited molecules/genes

 

LEPR

Transmembrane receptor

−2.000

7.2×10-2

APOA1, APOA2, CARTPT, COL1A1, COL4A1, FOS, TIMP1

Losartan potassium

Chemical drug

−2.035

6.4×10-6

AQP1, COL1A1, CYBB, F3, FOS, GRK5, ITGB5, PTGS2, PTHLH, STAR, TIMP1, VCAM1

APOE

Transporter

−2.035

2.5×10-5

APOA1, CLU, COL1A1, CTSB, CYBB, F2R, F2RL1, F3, GPR77, GPX3, HMOX1, IGFBP6, LRP8, MYO1B, NPNT, PPAP2B, PTGS2, TIMP1, VCAM1

Tetrachlorodi-benzodioxin

Chemical toxicant

−2.038

7.2×10-2

ABCB1, CYP11A1, CYP19A1, FOS, HES1, HMOX1, INSIG2, LHCGR, MYC, MYO10, PTGFR, PTGS2, PTPN13, SLC40A1, SPOCK2, STAR

NR0B1

Ligand-dependent nuclear receptor

−2.092

2.0×10-4

CYP11A1, CYP19A1, HSD3B2, NR5A2, STAR

Tamoxifen

Chemical drug

−2.241

4.5×10-3

CDH11, CLU, EPHX1, F2R, FHL2, FOS, HES1, IER3, IGFBP4, MYC, PGR, PTGS2, UGCG

MGEA5

Enzyme

−2.500

1.9×10-3

ABLIM1, ACSS2, CMTM8, CREB3L2, FDFT1, FERMT2, IGFBP4, IL20RA, IL6R, ITGB5, LPHN2, MYO10, PFKM, PPAP2B, TIMP1, TIMP2

ERBB2

Kinase

−3.304

 

ACTA1, ADAM12, ANGPTL2, ATP6V1A, BEX2, CDH11, CHCHD10, CHST10, CLU, COL1A1, COL4A1, CUL1, CUL3, DERL1, EIF4EBP1, F2R, FOS, GPX3, HES1, ID2, IGFBP4, IGFBP6, KIT, LAMC2, MAN1A1, MAOA, MFAP2, MYC, MYO10, NDRG4, NEDD9, NOTCH1, NPNT, NRP1, PDCD4, PDLIM4, PFKFB3, PLAT, PTGS2, TGIF1, VCAN

  1. *The bias-corrected z-score is used to infer the activation states of transcriptional regulators. It is calculated from the proportions of genes which are differentially regulated in an expected direction based on the known interactions between the regulator and the genes present in the Ingenuity database. Those genes with a z-score greater or less than two are considered to be either activated or inhibited respectively.
  2. **The P value of overlap is the calculated statistical significance of overlap between genes from the dataset and genes that are known to be regulated by the upstream regulator using Fisher’s exact test.
Back to article page

BMC Genomics

ISSN: 1471-2164

Contact us