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. 2013 Mar 14;9(3):e1003362. doi: 10.1371/journal.pgen.1003362

Table 1. Features of the Blood Expression Axes.

Axis Gene Ontology1 Abnormal mouse phenotype1 TF/miR1 , 2 Human Disease1 N genes3
Axis 1 Translation T cell physiology (4.0E-06) ELK1 T-negative SCID 866
Ribosome constituents Leukopoiesis (4.0E-04) NRF2 anemia
Axis 2 Oxygen transporter activity Platelet aggregation (9.0E-04) GATA3 hemolytic anemia 237
Wound healing Haematopoiesis (8.0E-06)
Axis 3 B-cell activation B-cell morphology (4.0E-19) miR-486 SLE 99
External to plasma membrane Immunoglobulin level (4.0E-16) miR-146a Immunodeficiency
Axis 4 mRNA metabolism, RNA splicing Embryonic lethality (3.0E-10) ELK1, NRF1 982
Intracellular transport Low embryonic growth (5.0E-06) miR-590, 548, 561
Axis 5 Cytokine receptor activity Adaptive immunity (7.0E-14) ETS2, PEA3, AP1 1028
Inflammatory response Innate immunity (3.0E-14) miR-1207 Liver disease
Axis 6 miR-483, 590 550
Axis 7 Viral response Response to infection (4.0E-13) IRF, ISRE, ICSBP 169
Interferon-mediated signaling Susceptibility to viral infection (3.0E-12)
Axis 8 RNA processing B cell activation (0.03) NRF1, ARNT 571
miR-590, 548, 607
Axis 9 Signal transduction by phosphorylation B cell number (7.0E-05) STAT5A, STAT6 242
Programmed cell death T-cell morphology (2.0E-04) miR-548, 155, 34b, 603, 103
1

See Dataset S3 for details of the GO catergories, number of genes, and significance levels.

2

Simply reflecting enrichment frm the ToppFun analysis, not meant to imply that these are the only regulatory factors or that there is direct evidence for their involvement in regulation of the axes. Dataset S3 shows that each bind only a subset of genes in the axis.

3

The number of genes associated with each Axis in a multivariate model including all 9 Axes, at Bonferroni significance and in common between the CHDWB and Morocco studies.