Phylostratigraphic analysis of gene co-expression network reveals the evolution of functional modules for ovarian cancer

Growth of Biological Complexity from Prokaryotes to Hominids Reflected in the Human Genome

The growth of complexity in evolution is a most intriguing phenomenon. Using gene phylostratigraphy, we showed this growth (as reflected in regulatory mechanisms) in the human genome, tracing the path from prokaryotes to hominids. Generally, the different regulatory gene families expanded at different times, yet only up to the Euteleostomi (bony vertebrates). The only exception was the expansion of transcription factors (TF) in placentals; however, we argue that this was not related to increase in general complexity. Surprisingly, although TF originated in the Prokaryota while chromatin appeared only in the Eukaryota, the expansion of epigenetic factors predated the expansion of TF. Signaling receptors, tumor suppressors, oncogenes, and aging- and disease-associated genes (indicating vulnerabilities in terms of complex organization and strongly enrichment in regulatory genes) also expanded only up to the Euteleostomi. The complexity-related gene properties (protein size, number of alternative splicing mRNA, length of untranslated mRNA, number of biological processes per gene, number of disordered regions in a protein, and density of TF–TF interactions) rose in multicellular organisms and declined after the Euteleostomi, and possibly earlier. At the same time, the speed of protein sequence evolution sharply increased in the genes that originated after the Euteleostomi. Thus, several lines of evidence indicate that molecular mechanisms of complexity growth were changing with time, and in the phyletic lineage leading to humans, the most salient shift occurred after the basic vertebrate body plan was fixed with bony skeleton. The obtained results can be useful for evolutionary medicine.

Transcription Factors Drive Opposite Relationships between Gene Age and Tissue Specificity in Male and Female Drosophila Gonads

Evolutionarily young genes are usually preferentially expressed in the testis across species. Although it is known that older genes are generally more broadly expressed than younger genes, the properties that shaped this pattern are unknown. Older genes may gain expression across other tissues uniformly, or faster in certain tissues than others. Using Drosophila gene expression data, we confirmed previous findings that younger genes are disproportionately testis biased and older genes are disproportionately ovary biased. We found that the relationship between gene age and expression is stronger in the ovary than any other tissue and weakest in testis. We performed ATAC-seq on Drosophila testis and found that although genes of all ages are more likely to have open promoter chromatin in testis than in ovary, promoter chromatin alone does not explain the ovary bias of older genes. Instead, we found that upstream transcription factor (TF) expression is highly predictive of gene expression in ovary but not in testis. In the ovary, TF expression is more predictive of gene expression than open promoter chromatin, whereas testis gene expression is similarly influenced by both TF expression and open promoter chromatin. We propose that the testis is uniquely able to express younger genes controlled by relatively few TFs, whereas older genes with more TF partners are broadly expressed with peak expression most likely in the ovary. The testis allows widespread baseline expression that is relatively unresponsive to regulatory changes, whereas the ovary transcriptome is more responsive to trans-regulation and has a higher ceiling for gene expression.

Ovarian morphological features and proteome reveal fecundity fitness disadvantages in β-cypermethrin-resistant strains of Blattella germanica (L.) (Blattodea: Blattellidae)

To evaluate whether the development of β-cypermethrin resistance in Blattella germanica (L.) (Blattaria: Blattellidae) affects the fecundity fitness of this insect and to determine the underlying mechanism, we compared fecundity differences between β-cypermethrin-resistant (R) and sensitive (S) strains of B. germanica, observed the physiological structural changes of ovaries from an visual perspective, and analyzed differences in the ovarian proteome using proteomic methods. The results showed that, compared with the S strain of B. germanica, the R strain of B. germanica had a significantly higher ootheca shedding rate, a significantly lower number of hatched and surviving nymphs, a significantly higher female proportion in the population and defective ovarian development. Ovarian proteomic analysis showed a total of 64 differentially expressed proteins in the R strain, including 18 upregulated proteins and 46 downregulated proteins. Twenty-four significantly differentially expressed proteins were further studied, and 14 were successfully identified, which were mainly classified into the following categories: immunity-related proteins, development-related proteins, structural proteins, energy metabolism-related proteins and proteins with unknown functions. The differential expression of these proteins reflects the overall changes in cell structure and metabolism associated with β-cypermethrin resistance and explains the possible molecular mechanism of fecundity fitness disadvantages. In summary, β-cypermethrin resistance can cause fecundity fitness disadvantages in B. germanica. The metabolic deviations needed to overcome the adverse effects of insecticides may result in an energy exchange that affects energy allocation and, ultimately, the basic needs of the insect. The fitness cost due to insecticide resistance is critical to the delay of the evolution of resistance.

Novel module and hub genes of distinctive breast cancer associated fibroblasts identified by weighted gene co-expression network analysis

BACKGROUND

As abundant and heterogeneous stromal cells in tumor microenvironment, carcinoma-associated fibroblasts (CAFs) are critically involved in cancer progression.

METHODS

To identify co-expression module and hub genes of distinctive breast CAFs, weighted gene co-expression network analysis (WGCNA) was conducted based on the expression array results of CAFs from seven chemo-sensitive breast cancer (BC) patients and seven chemo-resistant ones before neo-adjuvant chemotherapy.

RESULTS

A total of 4916 genes were included in WGCNA, and 12 modules were determined. Module-trait assay showed that the blue module (cor = 0.97, P < 0.001) was associated with CAF-related chemo-resistance, which was enriched mainly as "inflammatory response", "interferon-gamma-mediated signaling" and "NIK/NF-kappaB signaling" pathways. Moreover, CXCL8, CXCL10, CXCL11, PLSCR1, RIPK2 and USP18 were found to be potentially associated with chemo-resistance related to CAFs and prognosis of BC.

CONCLUSIONS

Our current data offered valuable insights into the molecular mechanisms of distinctive breast CAFs, which was beneficial for revealing how chemo-resistance of BC was initiated.

Phylostratigraphic Analysis Shows the Earliest Origination of the Abiotic Stress Associated Genes in A. thaliana

Plants constantly fight with stressful factors as high or low temperature, drought, soil salinity and flooding. Plants have evolved a set of stress response mechanisms, which involve physiological and biochemical changes that result in adaptive or morphological changes. At a molecular level, stress response in plants is performed by genetic networks, which also undergo changes in the process of evolution. The study of the network structure and evolution may highlight mechanisms of plants adaptation to adverse conditions, as well as their response to stresses and help in discovery and functional characterization of the stress-related genes. We performed an analysis of Arabidopsis thaliana genes associated with several types of abiotic stresses (heat, cold, water-related, light, osmotic, salt, and oxidative) at the network level using a phylostratigraphic approach. Our results show that a substantial fraction of genes associated with various types of abiotic stress is of ancient origin and evolves under strong purifying selection. The interaction networks of genes associated with stress response have a modular structure with a regulatory component being one of the largest for five of seven stress types. We demonstrated a positive relationship between the number of interactions of gene in the stress gene network and its age. Moreover, genes of the same age tend to be connected in stress gene networks. We also demonstrated that old stress-related genes usually participate in the response for various types of stress and are involved in numerous biological processes unrelated to stress. Our results demonstrate that the stress response genes represent the ancient and one of the fundamental molecular systems in plants.

Identification of modules and hub genes associated with platinum-based chemotherapy resistance and treatment response in ovarian cancer by weighted gene co-expression network analysis

High-grade serous ovarian carcinoma (HGSOC) is the most prevalent and malignant ovarian tumor.To identify co-expression modules and hub genes correlated with platinum-based chemotherapy resistant and sensitive HGSOC, we performed weighted gene co-expression network analysis (WGCNA) on microarray data of HGSOC with 12 resistant samples and 16 sensitive samples of GSE51373 dataset.A total of 5122 genes were included in WGCNA, and 16 modules were identified. Module-trait analysis identified that the module salmon (cor = 0.50), magenta (cor = 0.49), and black (cor = 0.45) were discovered associated with chemotherapy resistant, and the significance for these platinum-resistant modules were validated in the GSE63885 dataset. Given that the black module was validated to be the most related one, hub genes of this module, alcohol dehydrogenase 1B, cadherin 11, and vestigial like family member 3were revealed to be expressional related with platinum resistance, and could serve as prognostic markers for ovarian cancer.Our analysis might provide insight for molecular mechanisms of platinum-based chemotherapy resistance and treatment response in ovarian cancer.