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Transcriptome analysis of bovine macrophages (BoMac) cells after infection with bovine immunodeficiency virus Cover

Transcriptome analysis of bovine macrophages (BoMac) cells after infection with bovine immunodeficiency virus

Open Access
|Dec 2022

Figures & Tables

Fig. 1

Top canonical pathways enriched in differentially expressed genes (DEGs). The value of −log(p) >1.3 reflects a significant association between the canonical pathway and the involved genes. The percentage indicates the number of DEGs overlapping with molecules associated to canonical pathways. The colours represent up- (red) and downregulated (green) genes. The numbers on top of the bars represent the total number of molecules associated to each pathway
Top canonical pathways enriched in differentially expressed genes (DEGs). The value of −log(p) >1.3 reflects a significant association between the canonical pathway and the involved genes. The percentage indicates the number of DEGs overlapping with molecules associated to canonical pathways. The colours represent up- (red) and downregulated (green) genes. The numbers on top of the bars represent the total number of molecules associated to each pathway

Fig. 2

Most prominent canonical pathways ordered according to z-score value and their predicted activation state with regard to −log (p-value) greater than 1.3. The bars represent the p-values of overlap (−log) of differentially expressed genes in the dataset with known pathway-associated molecules. Pathways in orange are those predicted to be activated and pathways in blue are those predicted to be inhibited. The higher the intensity of the colours, the higher the absolute z-score
Most prominent canonical pathways ordered according to z-score value and their predicted activation state with regard to −log (p-value) greater than 1.3. The bars represent the p-values of overlap (−log) of differentially expressed genes in the dataset with known pathway-associated molecules. Pathways in orange are those predicted to be activated and pathways in blue are those predicted to be inhibited. The higher the intensity of the colours, the higher the absolute z-score

Fig. 3

The inflammation of joints (A) and inflammatory response (B) pathways in BIV infected BoMac cells. The shapes of the nodes reflect the functional class of each gene product: transcriptional regulator (horizontal ellipse), transmembrane receptor (vertical ellipse), enzyme (rhombus), cytokine/growth factor (square), kinase (triangle), and complex/group/other (circle). Other indicators are explained in the prediction legend
The inflammation of joints (A) and inflammatory response (B) pathways in BIV infected BoMac cells. The shapes of the nodes reflect the functional class of each gene product: transcriptional regulator (horizontal ellipse), transmembrane receptor (vertical ellipse), enzyme (rhombus), cytokine/growth factor (square), kinase (triangle), and complex/group/other (circle). Other indicators are explained in the prediction legend

Disease and biofunctions identified by IPA ordered with respect to activation z-score

Diseases or functions annotationP-valueActivation z-scoreNumber of molecules
Inflammation of joints4.61E−09−3.228*143
Inflammatory response1.71E−06−2.003*103
Activation of leukocytes6.71E−07−1.66488
Inflammation of respiratory system component6.93E−06−1.51876
Inflammation of body cavity4.07E−06−1.467139
Rheumatoid arthritis2.18E−07−1.387102
Inflammation of lungs3.60E−06−1.37954
Allergic pulmonary eosinophilia2.95E−06−1.34212
Inflammation of organs1.03E−07−1.088187
Inflammation of absolute anatomical region6.76E−06−1.049153
Immune response of tumour cell lines1.06E−05−0,78829
Dermatitis9.31E−06−0.36368

Primers and TaqMan probes used in this study for BIV and GAPDH gene amplification

Primer/ProbeSequence 5′ → 3′Position in target sequenceProduct length (bp)Application
BIVg723FGAAGCAGACATCGAATCAGA723–742a552BIV standard
BIVg1274RTCTTTTGTGGTTTCTGGAGC1255–1274 a DNA
BTG1FTGATGCTGGTGCTGAGTATGTG4–25b182GAPDH standard
BTG2RCCTTCAAGTGAGCCTGCAGCAA164–185 b DNA
BIVg1074FACAAGCCACCCTGATCTCAGTA1074–1095 a128RT-qPCR and
BIVg1202RTCCTTGGGTTCCCTGATGAATGT1181–1202 a qPCR-
BIVg1107PCy5 - AACTTTCAGACAGTGGGTGCTGCAGG - BHQ31107–1132 a-BIV gag gene
BTG3FCCACTGGGGTCTTCACTACCAT33–54 b
BTG4RAAGTTAATTGCACCCGGGCTCT137–158 b126GAPDH qPCR-
BTG5PJOE - CTGGAGAGGAGGGTGTAACAGGA - BHQ183–105 b-

The top-scoring regulatory networks identified using IPA software

Consistency scoreNode totalRegulator totalRegulatorsTarget totalTarget molecules in datasetDiseases & functions
1.291
20
4
ELF4, INSIG1, INSR, mir-148
15
ACSL1, C1QA, CA2, CD68, CXCL2, DUSP1, FABP4, FDFT1, GABRB3, HSPD1, LDLR, LGALS1, MMP9, PRDM1, VCAM1
Inflammation of joints
−7.211
15
1
INSR
13
ALDH2, CLCA1, DUSP1,EGR1, FABP4,GADD45A, HSPD1, LGALS1, MFN2, MMP9, PRDM1, SERPINB1, VCAM1
Inflammatory response
−7.500
6
1
RABGEF1
4
CTSH, GBA, HEXB, LDLR
Metabolism of protein
−7.506
5
1
ALDH1A2
3
ALDH1A3, CCN2, CD44
Neonatal death
−8.66051DDX3X3CCND1, ODC1, RPS5Metabolism of protein

Comparison of gene expression changes observed in microarray analysis and RT-qPCR

GeneReference sequence IDPrimer sequence (5′–3′)FC
MicroarrayRT-qPCR
UCHL5*174481* NM_F: ACAAAGACAACTTGCTGAGGAACCCN/AN/A
R: GGCAACCTCTGACTGAATAGCACTT
ATRXM_002685057.2F: AATGCACGTGTCCTTCGATA2.451.05
R: TGAAAAGGCCAAGACTCATGT
LTANM_001013401.2F: CCCTCAGAGCCTCGCTTT2.001.19
R: GCGAGACATCAGAAGAAAGAGC
IL-18NM_001562F: AGACAGGTTGATTTCCCTGGT−1.50−1.15
R: CCTGGAATCAGATCACTTTGG
HYAL2XM_024982390F: GCGACCAGAGGGGGAACTC−1.50−1.03
R: TAGCACTGGCAGCGAAAGTGCA
F: TGGTGGAGACTGCCTGCG
DCTN6XM_024986251R: CCGACTAAAGAGGTTCTAGCAC3.001.12
Language: English
Page range: 487 - 495
Submitted on: Sep 28, 2022
Accepted on: Dec 13, 2022
Published on: Dec 26, 2022
Published by: National Veterinary Research Institute in Pulawy
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Marzena Rola-Łuszczak, Magdalena Materniak-Kornas, Piotr Kubiś, Aneta Pluta, Marlena Smagacz, Jacek Kuźmak, published by National Veterinary Research Institute in Pulawy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.