A systems biology approach was used to elucidate the changes in gene expression that are important for ovarian primordial to primary follicle transition. A gene network analysis was performed on the ovarian transcriptomes following treatment with 8 different growth factors. The rat ovary was used as a model system to test the utility of this approach in investigating a normal developmental process. This is one of the first applications of network analysis to a normal developmental process. The objective was to identify critical regulatory factors and pathways in primordial follicle development following a bionetwork analysis.
Microarray analysis determined the alterations in the ovarian transcriptome that occurred in response to treatment of ovaries with AMH, FGF2, BMP4, GDNF, FGF7, KITL, LIF, and PDGFB. All of these have previously been shown to effect follicle transition 
. All these factors stimulate primordial follicle development except AMH that inhibits follicle development. The presence of both positive and negative factors provides a wider diversity of gene regulation to facilitate the network analysis. As expected the AMH regulated gene set is more distinct from the others. Surprisingly, there were few altered genes in common between all these growth factors and there were no genes that significantly changed in expression level in response to more than three of the eight growth factors. In contrast, the physiological processes impacted by these altered genes were found to have a higher level of overlap. Since a pathway includes groups of genes, it is expected that the overlap of pathways between growth factor treatments will be higher. The overlap of pathways was markedly high (70% to 82%) and statistically different, suggesting pathway associations provide a predicted capacity to identify regulatory factors. Certain pathways were significantly over-represented in the pool of genes with changed expression. This suggests that there are selected physiological pathways that are influenced by all the different growth factors (), but that each growth factor affects different genes at different points in these pathways (). Multiple input points into these physiological pathways could allow for more precise regulation and more effective compensation between the growth factors. Since many growth factors are acting in parallel to regulate these pathways, any one pathway system is robust and maintains function if one growth factor becomes inoperative. Since primordial follicle development is essential for female reproduction, a complex network of regulatory factors influencing different aspects of critical signaling pathways has evolved.
Scheme of direct connections to cellular processes for the 55 candidate regulatory genes obtained by global literature analysis.
For the eight growth factors evaluated the cellular processes affected in common () included changes in cell contact, morphogenesis, and cell proliferation and differentiation. These are processes that are necessary for the morphological changes that occur with primordial to primary follicle transition. During follicle transition granulosa cells change from squamous to cuboidal and the oocyte starts to grow in diameter (). Unexpectedly, what was also seen as an important affected cellular process was regulation of several key components of the complement and coagulation cascades (Figure S2
). These genes are not known for having roles in ovary or follicle development, and merit further investigation.
Gene networks provide a convenient framework for exploring the context within which single genes operate. For gene networks associated with biological systems, the nodes in the network typically represent genes, and edges (links) between any two nodes indicate a relationship between the two corresponding genes. An important end product from the gene co-expression network analysis is a set of gene modules which member genes are more highly correlated with each other than with genes outside a module. It has been demonstrate that these types of modules are enriched for known biological pathways for genes that associate with disease traits and for genes that are linked to common genetic loci 
The current study employed a weighted gene co-expression network approach that has been extensively used for uncovering biologically meaningful gene modules 
to explore novel pathways involved in primordial follicle development. An unsupervised and unbiased approach was used to nominate potential regulatory candidates for these modules based on gene network connectivity. The connectivity score shows how well under different treatments the changes in gene expression for a gene are correlated with the changes in expression for every other gene. In the current study, the gene co-expression network analysis helped select 55 highly connected genes for further functional analysis. An automated literature search of these 55 genes revealed a sub-network relationship among them as presented in . This sub-network suggested regulatory roles for Pdgfa and Fgfr2 (the receptor) for Fgf2 and Fgf7 (KGF). PDGF, KGF/FGF7 and FGF2 proteins have previously been shown to regulate primordial to primary follicle transition 
. Therefore, the bionetwork predicted to be involved in the regulation of primordial follicle development identified two previously known regulatory factors which validated the utility of the network analysis for identifying candidate regulatory genes, consistent with previous network studies 
. This sub-network also identified connective tissue growth factor (Ctgf) 
as a putative regulator of primordial follicle development. An ovarian organ culture experiment confirmed that CTGF promotes primordial to primary follicle transition. Therefore, a regulatory factor predicted to be important for primordial follicle development was confirmed to be involved which further validated the bionetwork approach. A microarray analysis of CTGF-treated ovaries showed an altered gene set similar to those of the other growth factors known to regulate follicle transition. These observations validate the network-based systems biology approach to elucidate the regulation of a complex developmental process.
Consideration of the 55 intra-module hub genes from critical regulatory modules revealed a number of signaling and cellular processes were influenced, and Figure S3
. In the growth factor/chemokine family Pdgfa and Ctgf were confirmed to be involved. The IL16 identified is currently being investigated as a potential regulatory candidate. The specific genes identified in and associated regulatory processes provide potential therapeutic targets to regulate primordial follicle development. The ability to inhibit or stimulate primordial follicle development with a therapeutic treatment has a number of clinical applications. A delay in primordial follicle development and maintenance of the primordial pool could delay the onset of menopause and extend the reproductive life span of a female. In addition, the ability to therapeutically inhibit primordial follicle development would provide a treatment for premature ovarian failure, a disease when the primordial pool is lost early in life causing female infertility. In contrast, the therapeutic stimulation of primordial follicle development could treat forms of female infertility 
. The induction of primordial follicle development also could promote the loss of the primordial pool and induce female sterility. The bionetwork identified in the current study produced a number of potential therapeutic targets to manipulate primordial follicle development and female reproductive capacity.
The systems biology approach taken with this network analysis of primordial follicle development identified clusters and modules of genes involved in this critical development process. A number of the growth factors previously shown to be involved (e.g. PDGF and bFGF) were identified, but other factors known to be important for ovarian development were not identified. Often a reductionist approach such as a knockout mouse model can identify a factor as being important for the maintenance of tissue development or function, but this does not mean the factor is regulated during the process. In addition, critical developmental processes such as primordial follicle development often have a set of compensatory factors that have evolved such that loss of any one will still allow the process to proceed. Therefore, knockout models often do not have phenotypes for these factors. This does not mean the factor is not important, but instead that the developmental process is essential and thus multiple factors compensate to assure the developmental process occurs. The current study takes a systems biology approach to identify networks of genes involved in the process without the bias of a reductionist model. Therefore, novel groups of factors and cellular processes were identified that now require further investigation.
The integrative analysis revealed a gene sub-network involved in primordial follicle development to elucidate the basic developmental biology of this process and provide potential therapeutic targets for ovarian disease and function. This sub-network was validated by the presence of two genes previously identified as being important. A new gene identified, Ctgf, was tested and found to regulate primordial follicle development. Therefore, the network based systems biology approach was partially validated for a normal developmental process. This type of approach will likely be invaluable to study development on a systems biology level in the future.