Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells

Tanja Burnik Papler, Eda Vrtacnik Bokal, Ales Maver, Andreja Natasa Kopitar, Luca Lovrečić, Tanja Burnik Papler, Eda Vrtacnik Bokal, Ales Maver, Andreja Natasa Kopitar, Luca Lovrečić

Abstract

Specific gene expression in oocytes and its surrounding cumulus (CC) and granulosa (GC) cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10-4); of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2), higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK), higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Principal component analysis between granulosa…
Fig 1. Principal component analysis between granulosa and cumulus cells.
The axes of the plot represent first two main components of variance, obtained by performing principal component analysis (PCA) on global expression profiles. GC- granulosa cells; CC- cumulus cells.
Fig 2. Top network enriched in granulosa…
Fig 2. Top network enriched in granulosa cells (Enrichment score: 32) generated with Ingenuity Pathway Analysis (IPA).
The network is associated with hematological system development and function, cancer and cellular movement. Up-regulated genes in our study are marked in green colour; the colour intensity of the nodes indicates the degree of up-regulation. Transcripts in grey were not differentially expressed. Genes are represented as nodes, and the biological relationship between two nodes is represented as a line: the plain line indicates direct interaction, the dashed line indicates indirect interaction; the line without arrowhead indicates binding only, the line finishing with a vertical line indicates inhibition; the line with an arrowhead indicates ‘acts on’.
Fig 3. Top network enriched in cumulus…
Fig 3. Top network enriched in cumulus cells (Enrichment score: 41) generated with Ingenuity Pathway Analysis (IPA).
The network is associated with cellular development, skeletal and muscular system development and function and tissue development. Up-regulated genes in our study are marked in red colour; the colour intensity of the nodes indicates the degree of up-regulation. Transcripts in grey were not differentially expressed. Genes are represented as nodes, and the biological relationship between two nodes is represented as a line: the plain line indicates direct interaction, the dashed line indicates indirect interaction; the line without arrowhead indicates binding only, the line finishing with a vertical line indicates inhibition; the line with an arrowhead indicates ‘acts on’.
Fig 4. Validation of microarray results by…
Fig 4. Validation of microarray results by qPCR in additional 19 GC and 19 CC samples, derived from sixteen women.
For all genes, except ACE2, there was a statistically significant difference in expression between CC and GC. Data are presented as mean log2 fold change (FC) between expression in CC and GC. Blue bars represent log2 FC as measured by microarray; red bars represent log2 FC as measured by qPCR.
Fig 5. qPCR validation of microarray data.
Fig 5. qPCR validation of microarray data.
The results represent mean relative mRNA expression of the selected genes ± SEM.

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