| Literature DB >> 26546342 |
Kamil Krawczynski1, Stefan Bauersachs2,3, Zaneta P Reliszko1, Alexander Graf2, Monika M Kaczmarek4.
Abstract
BACKGROUND: Embryo implantation is a complex, synchronized process that requires establishment of a reciprocal dialogue between a receptive endometrium and developing blastocysts. Recently, microRNAs (miRNAs), known to modulate gene expression through post-transcriptional mechanisms, were implicated in regulation of early pregnancy events including maternal recognition of pregnancy and implantation. To characterize complex transcriptomic changes, expression of miRNAs in pregnant and cyclic endometria collected on days 12, 16 and 20 was analyzed using Illumina deep sequencing and analyzed with bioinformatic pipeline. Moreover, expression profiles of ten genes related to miRNA synthesis and transport such as DROSHA, DGCR8, XPO5, DICER, TARBP2, TNRC6A, and AGO1-4 were determined.Entities:
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Year: 2015 PMID: 26546342 PMCID: PMC4636777 DOI: 10.1186/s12864-015-2172-2
Source DB: PubMed Journal: BMC Genomics ISSN: 1471-2164 Impact factor: 3.969
Fig. 1miRNA synthesis and transport related molecules are differentially expressed in the porcine endometrium. a Relative expression of ten genes related to miRNA synthesis/transport. Levels of DROSHA, DGCR8, XPO5, DICER1, TARBP2, TNRC6A and AGO 1–4 genes are presented relatively to geometric means of ACTB and PPIB. Results are presented as boxplots with means ± SEM. Means with different superscripts differ significantly (small letters – the estrous cycle, capital letters – pregnancy). * p < 0.05, ** p < 0.01, and *** p < 0.001 indicate difference between reproductive states (estrous cycle vs. pregnancy) within the same day (n = 5-8 animals/group). AU – arbitrary units. b Microphotographs illustrating immunofluorescent staining of DICER1 (red) and AGO2 (green) proteins in the endometrial sections from D12 of pregnancy (upper panel) and D12 of estrous cycle (middle panel). Lower panel shows negative controls; staining with mouse IgG1 or NRS. DAPI was used for counterstaining of the nuclei (blue). NSB – non-specific binding (erythrocytes), GE – glandular epithelium, LE – luminal epithelium, S – stroma
Fig. 2Modifications of miRNA length expressed in the porcine endometria collected on different days of the estrous cycle or pregnancy. a Percent of modifications affecting either 3’ end, 5’ end or both ends; b Percent of additions and deletions on 3’ end, and percent of additions and deletions on 5’ end. c Mean values of normalized read counts from all groups for reference/canonical miR-140-3p or its isomiRs and sum of normalized read counts for each seed sequence. d Expression of reference/canonical miR-140-3p (seed sequence ACCACAG) and its 5’ isomiR with seed sequence CCACAGG. miRNA/isomiR expression on different days of the estrous cycle and pregnancy (n = 4-6 animals/group) is presented as mean of normalized reads counts (NRC) ± SEM. Two-way ANOVA analysis with Bonferoni post-hoc test was performed on log-transformed values to find statistical differences. Means with different superscripts differ significantly (small letters – the estrous cycle, capital letters – pregnancy). ** p < 0.01, indicate difference between reproductive states (estrous cycle vs. pregnancy) within the same day
Fig. 3miRNAs/isomiRs showing differential expression on D12, D16 and D20 of the estrous cycle and early pregnancy. a Dendrogram representing results of unsupervised hierarchical clustering (HCL) created with Pearson correlation coefficient. Rows indicate single miRNAs, while columns represent different days of the estrous cycle and pregnancy. b Clusters generated by Self Organizing Tree Algorithm (SOTA) representing expression profiles of mature, canonical miRNAs expressed in the porcine endometrium of pregnant and cyclic pigs. c Venn diagrams demonstrating relations between DE miRNAs and isomiRs for selected comparisons during pregnancy. Marked up- and down-regulated miRNAs were chosen for microarray validation by real-time RT-PCR. d Relative expression of DE miRNAs selected for validation of Illumina sequencing, using stem-loop real-time RT-PCR. miRNA expression on different days of the estrous cycle and pregnancy (n = 7-9 animals/group) is presented relative to the reference let-7d-3p. Two-way ANOVA analysis with Bonferoni post-hoc test was performed to find statistical differences. Results are presented as boxplots with means ± SEM. Means with different superscripts differ significantly (small letters – the estrous cycle, capital letters – pregnancy). * p < 0.05, indicate difference between reproductive states (estrous cycle vs. pregnancy) within the same day. AU – arbitrary units
Fig. 4miRNAs showing differential expression in porcine endometrium classified into various functions and pathways by Ingenuity Pathway Analysis (IPA). a Top molecular functions enriched with DE miRNAs for PD20 vs. CD20, PD20 vs. PD16, PD16 vs. CD16, PD16 vs. PD12 and CD16 vs. C12 comparisons. The X-axis represents score for the likelihood [−log (Benjamin-Hochberg p-value < 0.05)] that genes belonging to a specific function category are affected in the specific comparisons. b Networks representing molecules of interest differentially regulated in selected comparisons. The network is displayed graphically as nodes (miRNAs/genes/genes products) and edges (biological relationship between nodes). The node color intensity indicates the fold-change expression of miRNAs; with red representing up-regulation and green down-regulation of miRNAs. The log2 fold change value and FDR for individual miRNAs is indicated under each node. The shapes of nodes indicate the functional class of the gene product and the lines indicate the type of interaction, explained in the legend. All connections were integrated into the computationally generated networks on the basis of the evidence stored in the IPA knowledge memory indicating relevance for these networks
Selected pregnancy associated target genes for differentially expressed miRNAs in the porcine endometrium
| Functional category | Target genea | DE miRNAs |
|---|---|---|
| Prostaglandin signaling and metabolism | PTGS2 | miR-758, miR-16, miR-320, let-7a, miR-199a-3p, miR-203 |
| PTGER2 | miR-429 | |
| PTGFR | miR-23b, miR-92b-3p, miR-205, miR-429 | |
| PTGIS | miR-449a, miR-150, miR-200a | |
| PTGIR | miR-1, miR-205 | |
| Inflammatory mediators | IL6 | let-7e, miR-365-3p, miR-574 |
| IL6R | miR-200a, miR-27a/b, miR-24-3p, miR-342, miR-23b, miR-495, let-7a, miR-17, miR-449a | |
| LIF | miR-106b-5p, miR-27a/b, miR-17-5p, miR-574 | |
| LIFR | miR-1, miR-142-3p, miR-342, miR-365-3p, miR-203, miR-30d, miR-27a, miR-23b, miR-205, miR-191, miR-199a-3p | |
| Growth factors, receptors and related proteins | IGF1 | miR-1, miR-495, miR-186, miR-486, miR-23b, miR-27a, miR-380, miR-30d, miR-361-5p, miR-16, let-7a |
| IGF1R | let-7a, miR-100, miR-200a, miR-186, miR-16, miR-30d, miR-96, miR-495, miR-375 | |
| IGFBP1 | miR-140-3p, miR-205, let-7a | |
| IGFBP3 | miR-374a-5p, miR-449a, miR-1249, let-7a | |
| IGFBP5 | miR-1, miR-24-3p, miR-146a-5p, miR-193b-3p, miR-203, miR-27a | |
| VEGFA | miR-342, miR-200a, miR-1, miR-1249, miR-186, miR-449a, miR-16, miR-205, miR-203, miR-150, miR-374a-5p, miR-361-5p, miR-17-5p, miR-106b, miR-23b, miR-429 | |
| KDR | miR-16, miR-200b, miR-23b | |
| Flt1 | miR-96, miR-142-3p, miR-200b, miR-200a, miR-374a-5p, miR-193b-3p, miR-17-5p, miR-106b | |
| FGF7 | miR-27a, miR-186, miR-495, miR-199b-3p, miR-361-5p, miR-140, miR-16, miR-132, miR-486, miR-17, miR-429 | |
| FGF2 | miR-16, miR-23b, miR-203, miR-17 | |
| SPRED1 | miR-1, miR-96, miR-16, mniR-199a-3p, miR-132, miR-142-3p, miR-200c-3p, miR-17-5p, miR-106b, miR-449a, miR-126 | |
| Other | Wnt4 | miR-16, miR-186, miR-24-3p, miR-429 |
| Wnt5a | miR-129b, miR-140-3p, miR-374b-5p, miR-200a, miR-92b-3p, miR-365-3p, miR-186, miR-30d, miR-23b, miR-203, miR-205, miR-574 | |
| Wnt7a | miR-361-5p, miR-16 | |
| CTNNB1 | miR-150, miR-200a | |
| CDH1 | miR-495, let-7a, miR-23b | |
| HoxA10 | miR-27a, miR-374b-5p, miR-16 | |
| ESR1 | miR-1, miR-17-5p, miR-20a, miR-203, miR-129b, miR-193, miR-106b, miR-23b | |
| PGR | miR-342, miR-129b, miR-96, miR-23b, miR-140-3p, miR-495 |
aTarget prediction for DE miRNAs was done using IPA and miRWalk, which incorporate information from several algorithms such as: miRanda, TargetScan, miRDB, RNA22, PICTAR or DIANA-microT and miRwalk. miRNA target genes identified by at least three of these algorithms were considered for analysis
Fig. 5isomiRs work cooperatively with canonical miRNAs to affect putative targets gene expression in endometrial stromal cells. a Venn diagrams demonstrating relations between targets identified for canonical and non-canonical miR-140-3p harboring different seed sequences. b Top functional annotations organized into network representing common target mRNAs regulated by canonical and non-canonical miR-140-3p. The network is displayed graphically as nodes (genes/genes products) and edges (biological relationship between nodes). The shapes of nodes indicate the functional class of the gene product, explained in the legend. All connections were integrated into the computationally generated networks on the basis of the evidence stored in the IPA knowledge memory indicating relevance for these networks. c Fold change expression of miR-140-3p and its 5’ isomiR mimic transfected into endometrial stromal cells collected on D16 of pregnancy (n = 6) is compared to negative control. let-7d-3p was used as reference for miR-140-3p and isomiR miR-140-3p 5’ DEL U expression. Mimics were used at 50 nM dose when added separately or 25 nM dose each when added simultaneously. d Relative expression of canonical and non-canonical miR-140-3p putative target genes after mimics transfection into endometrial stromal cells from D16 of pregnancy (n = 4-6). Levels of ACVR2B, KCMA1, SIRT1, LIF and LPAR2 genes are presented relatively to geometric means of HPRT1 and ACTB. Results are shown as boxplots with means ± SEM. Asterisks indicate significant differences, in comparison to the negative control (50 nM; miRNA negative control mimic). *p < 0.05; **p < 0.01; ***p < 0.001