Identification of the key regulating genes of diminished ovarian reserve (DOR) by network and gene ontology analysis

Investigating the impact of regulatory B cells and regulatory B cell-related genes on bladder cancer progression and immunotherapeutic sensitivity

BACKGROUND

Regulatory B cells (Bregs), a specialized subset of B cells that modulate immune responses and maintain immune tolerance in malignant tumors, have not been extensively investigated in the context of bladder cancer (BLCA). This study aims to elucidate the roles of Bregs and Breg-related genes in BLCA.

METHODS

We assessed Breg infiltration levels in 34 pairs of BLCA and corresponding paracancerous tissues using immunohistochemical staining. We conducted transwell and wound healing assays to evaluate the impact of Bregs on the malignant phenotype of SW780 and T24 cells. Breg-related genes were identified through gene sets and transcriptional analysis. The TCGA-BLCA cohort served as the training set, while the IMvigor210 and 5 GEO cohorts were used as external validation sets. We employed LASSO regression and random forest for feature selection and developed a risk signature using Cox regression. Primary validation of the risk signature was performed through immunohistochemical staining and RT-qPCR experiments using the 34 local BLCA samples. Additionally, we employed transfection assays and flow cytometry to investigate Breg expansion ability and immunosuppressive functions.

RESULTS

Breg levels in BLCA tissues were significantly elevated compared to paracancerous tissues (P < 0.05) and positively correlated with tumor malignancy (P < 0.05). Co-incubation of SW780 and T24 cells with Bregs resulted in enhanced invasion and migration abilities (all P < 0.05). We identified 27 Breg-related genes, including CD96, OAS1, and CSH1, which were integrated into the risk signature. This signature demonstrated robust prognostic classification across the 6 cohorts (pooled HR = 2.25, 95% CI = 1.52-3.33). Moreover, the signature exhibited positive associations with advanced tumor stage (P < 0.001) and Breg infiltration ratios (P < 0.05) in the local samples. Furthermore, the signature successfully predicted immunotherapeutic sensitivity in three cohorts (all P < 0.05). Knockdown of CSH1 in B cells increased Breg phenotype and enhanced suppressive ability against CD8 + T cells (all P < 0.05).

CONCLUSIONS

Bregs play a pro-tumor role in the development of BLCA. The Breg-related gene signature established in this study holds great potential as a valuable tool for evaluating prognosis and predicting immunotherapeutic response in BLCA patients.

Transcriptomic signature of cancer cachexia by integration of machine learning, literature mining and meta-analysis

BACKGROUND

Cancer cachexia is a severe metabolic syndrome marked by skeletal muscle atrophy. A successful clinical intervention for cancer cachexia is currently lacking. The study of cachexia mechanisms is largely based on preclinical animal models and the availability of high-throughput transcriptomic datasets of cachectic mouse muscles is increasing through the extensive use of next generation sequencing technologies.

METHODS

Cachectic mouse muscle transcriptomic datasets of ten different studies were combined and mined by seven attribute weighting models, which analysed both categorical variables and numerical variables. The transcriptomic signature of cancer cachexia was identified by attribute weighting algorithms and was used to evaluate the performance of eleven pattern discovery models. The signature was employed to find the best combination of drugs (drug repurposing) for developing cancer cachexia treatment strategies, as well as to evaluate currently used cachexia drugs by literature mining.

RESULTS

Attribute weighting algorithms ranked 26 genes as the transcriptomic signature of muscle from mice with cancer cachexia. Deep Learning and Random Forest models performed better in differentiating cancer cachexia cases based on muscle transcriptomic data. Literature mining revealed that a combination of melatonin and infliximab has negative interactions with 2 key genes (Rorc and Fbxo32) upregulated in the transcriptomic signature of cancer cachexia in muscle.

CONCLUSIONS

The integration of machine learning, meta-analysis and literature mining was found to be an efficient approach to identifying a robust transcriptomic signature for cancer cachexia, with implications for improving clinical diagnosis and management of this condition.

Growth factors and female reproduction in vertebrates

Female reproductive efficiency is influenced by the outcomes of various processes, including folliculogenesis, apoptosis, response to gonadotropin signaling, oocyte maturation, and ovulation. The role of hormones in regulating these processes and other reproductive activities has been well established. It is becoming increasingly evident that in addition to well-characterized hormones, growth factors play vital roles in regulating some of these reproductive activities. Growth factors and their receptors are widely distributed in vertebrate ovaries at different stages of ovarian development, indicating their involvement in intraovarian reproductive functions. In the ovary, cell surface receptors allow growth factors to regulate intraovarian reproductive activities. Understanding these actions in the reproductive axis would provide a tool to target growth factors and/or their receptors to yield desirable reproductive outcomes. These include enrichment of in vitro maturation and fertilization culture media, and management of infertility. This review discusses some widely characterized growth factors belonging to the TGF, EGF, IGF, FGF, and BDNF family of peptides and their role in female reproduction in vertebrates, with a focus on mammals.

Genetic screening in patients with ovarian dysfunction

Ovarian dysfunction, including premature ovarian insufficiency and decreased ovarian reserve, affects the ovarian reserve and is one of the leading causes of female infertility. More and more cases of ovarian dysfunction are associated with genetic factors. Here, we identified eight potential variants in five genes (MSH4, HFM1, SYCE1, FSHR, and C14orf39) from six independent families by exome sequencing. The splice-site variants in SYCE1 and MSH4 affected canonical splicing isoforms, leading to missing protein domains or premature termination. Our findings expand the mutational spectrum of ovarian dysfunction and provide potential biomarkers for future genetic counseling and for more personalized treatments. Exome sequencing was shown to be a useful tool to better dissect the genetic basis for ovarian dysfunction and yielded a genetic diagnosis in about 5.0% (6/124) of cases in a cohort of 124 patients with ovarian dysfunction.

Identification of Hub Genes and Biomarkers between Hyperandrogen and Normoandrogen Polycystic Ovary Syndrome by Bioinformatics Analysis

BACKGROUND

The common and divergent genetic mechanisms of hyperandrogen (HA) and normoandrogen (NA) polycystic ovary syndrome (PCOS) are currently unknown.

OBJECTIVE

This study aimed to explore the hub genes and potential mechanisms of HA and NA PCOS through bioinformatics analysis.

METHODS

The GSE137684 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The co-expressed genes and differentially expressed genes (DEGs) between HA and NA PCOS samples were functionally annotated by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The protein-protein interaction (PPI) network of the DEGs was constructed and visualized using STRING and Cytoscape, respectively, and the hub genes were screened using the Cytohubba plug-in. The transcription factors (TFs) of these hub genes were identified with the JASPAR database, and the hub gene-TF regulatory network was constructed.

RESULTS

A total of 327 DEGs, including 191 upregulated and 136 downregulated genes, were identified in HA PCOS relative to NA PCOS. Ten hub genes were screened, of which MYC, CAV1, and HGF were mainly enriched in the Proteoglycans in the cancer pathway. In addition, 47 TFs were identified that were found to be involved in the regulation of hub genes.

CONCLUSION

MYC, CAV1, and HGF are potential diagnostic biomarkers and therapeutic targets for HA PCOS.

Age-related changes in Folliculogenesis and potential modifiers to improve fertility outcomes - A narrative review

Reproductive aging is characterized by a decline in oocyte quantity and quality, which is directly associated with a decline in reproductive potential, as well as poorer reproductive success and obstetrical outcomes. As women delay childbearing, understanding the mechanisms of ovarian aging and follicular depletion have become increasingly more relevant. Age-related meiotic errors in oocytes are well established. In addition, it is also important to understand how intraovarian regulators change with aging and how certain treatments can mitigate the impact of aging. Individual studies have demonstrated that reproductive pathways involving antimullerian hormone (AMH), vascular endothelial growth factor (VEGF), neurotropins, insulin-like growth factor 1 (IGF1), and mitochondrial function are pivotal for healthy oocyte and cumulus cell development and are altered with increasing age. We provide a comprehensive review of these individual studies and explain how these factors change in oocytes, cumulus cells, and follicular fluid. We also summarize how modifiers of folliculogenesis, such as vitamin D, coenzyme Q, and dehydroepiandrosterone (DHEA) may be used to potentially overcome age-related changes and enhance fertility outcomes of aged follicles, as evidenced by human and rodent studies.

Long-Term Calorie Restriction Alters Anxiety-like Behaviour and the Brain and Adrenal Gland Transcriptomes of the Ageing Male Rat

Further examination of the molecular regulators of long-term calorie restriction (CR), reported to have an anxiolytic effect, may highlight novel therapeutic targets for anxiety disorders. Here, adult male Hooded Wistar rats were exposed to a 25% CR whilst anxiety-like behaviour was assessed at 6-, 12-, and 18-months of age via the elevated plus maze, open field, and acoustic startle tests. Next-generation sequencing was then used to measure transcriptome-wide gene expression in the hypothalamus, amygdala, pituitary, and adrenal glands. Results showed an anxiolytic behavioural profile across early, middle, and late adulthood by CR, with the strongest effects noted at 6-months. Transcriptomic analysis by seven attribute weighting algorithms, including Info Gain Ratio, Rule, Chi Squared, Gini Index, Uncertainty, Relief, and Info Gain, led to the development of a signature of long-term CR, independent of region. Complement C1q A chain (C1qa), an extracellular protein, expression was significantly decreased by CR in most regions examined. Furthermore, text mining highlighted the positive involvement of C1qa in anxiety, depression, neurodegeneration, stress, and ageing, collectively identifying a suitable biomarker candidate for CR. Overall, the current study identified anxiety-related phenotypic changes and a novel transcriptome signature of long-term CR, indicating potential therapeutic targets for anxiety, depression, and neurodegeneration.

Expression of long noncoding RNAs in the ovarian granulosa cells of women with diminished ovarian reserve using high-throughput sequencing

Background

Infertility is a global reproductive-health problem, and diminished ovarian reserve (DOR) is one of the common causes of female infertility. Long noncoding RNAs (lncRNAs) are crucial regulators of numerous physiological and pathological processes in humans. However, whether lncRNAs are involved in the development of DOR remains to be elucidated.

Methods

Ovarian granulosa cells (OGCs) extracted from infertile women with DOR and from women with normal ovarian reserve (NOR) were subjected to high-throughput sequencing. Comprehensive bioinformatics analysis was conducted to identify the differential expression of messenger RNAs (mRNAs) and lncRNAs. Sequencing results were validated by the selection of lncRNAs and mRNAs using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

Results

Compared with the NOR group, a total of 244 lncRNAs were upregulated (53 known and 191 novel), and 222 lncRNAs were downregulated (36 known and 186 novel) in the DOR group. Similarly, 457 mRNAs had differential expression between the two groups. Of these, 169 were upregulated and 288 were downregulated. Bioinformatics analysis revealed that the differentially expressed genes of mRNA and lncRNAs were considerably enriched in “cell adhesion and apoptosis”, “steroid biosynthesis”, and “immune system”. A co-expression network comprising lncRNAs and their predicted target genes revealed the possible involvement of the “thyroid hormone signaling pathway” and “protein binding, digestion and absorption” in DOR pathogenesis. The expression of SLC16A10 was positively regulated by multiple lncRNAs. After RT-qPCR validation of seven differentially expressed lncRNAs and mRNAs, respectively, the expression of lncRNA NEAT1, GNG12, ZEB2-AS1, and mRNA FN1, HAS3, RGS4, SUOX were in accordance with RNA-sequencing.

Conclusions

We presented the first data showing that the expression profiles of lncRNA and mRNA in OGCs between NOR and DOR patients using RNA sequencing. The lncRNAs and mRNAs that we identified may serve as novel diagnostic biomarkers for patients with DOR.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-022-01053-6.

Apoptotic effects of human amniotic fluid mesenchymal stem cells conditioned medium on human MCF-7 breast cancer cell line

Introduction

Breast cancer, as the most common malignancy among women, is shown to have a high mortality rate and resistance to chemotherapy. Research has shown the possible inhibitory role of Mesenchymal stem cells in curing cancer. Thus, the present work used human amniotic fluid mesenchymal stem cell-conditioned medium (hAFMSCs-CM) as an apoptotic reagent on the human MCF-7 breast cancer cell line.

Methods

Conditioned medium (CM) was prepared from hAFMSCs. After treating MCF-7 cells with CM, a number of analytical procedures (MTT, real-time PCR, western blot, and flow cytometry) were recruited to evaluate the cell viability, Bax and Bcl-2 gene expression, P53 protein expression, and apoptosis, respectively. Human fibroblast cells (Hu02) were used as the negative control. In addition, an integrated approach to meta-analysis was performed.

Results

The MCF-7 cells' viability was decreased significantly after 24 hours (P < 0.0001) and 72 hours (P < 0.05) of treatment. Compared with the control cells, Bax gene's mRNA expression increased and Bcl-2's mRNA expression decreased considerably after treating for 24 hours with 80% hAFMSCs-CM (P = 0.0012, P < 0.0001, respectively); an increasing pattern in P53 protein expression could also be observed. The flow cytometry analysis indicated apoptosis. Results from literature mining and the integrated meta-analysis showed that hAFMSCs-CM is able to activate a molecular network where Bcl2 downregulation stands in harmony with the upregulation of P53, EIF5A, DDB2, and Bax, leading to the activation of apoptosis.

Conclusion

Our finding demonstrated that hAFMSCs-CM presents apoptotic effect on MCF-7 cells; therefore, the application of hAFMSCs-CM, as a therapeutic reagent, can suppress breast cancer cells' viabilities and induce apoptosis.

Transcriptome Analyses Identify Potential Key microRNAs and Their Target Genes Contributing to Ovarian Reserve

Female endocrinological symptoms, such as premature ovarian inefficiency (POI) are caused by diminished ovarian reserve and chemotherapy. The etiology of POI remains unknown, but this can lead to infertility. This has accelerated the search for master regulator genes or other molecules that contribute as enhancers or silencers. The impact of regulatory microRNAs (miRNAs) on POI has gained attention; however, their regulatory function in this condition is not well known. RNA sequencing was performed at four stages, 2-(2 W), 6-(6 W), 15-(15 W), and 20-(20 W) weeks, on ovarian tissue samples and 5058 differentially expressed genes (DEGs) were identified. Gene expression and enrichment were analyzed based on the gene ontology and KEGG databases, and their association with other proteins was assessed using the STRING database. Gene set enrichment analysis was performed to identify the key target genes. The DEGs were most highly enriched in 6 W and 15 W groups. Figla, GDF9, Nobox, and Pou51 were significantly in-creased at 2 W compared with levels at 6 W and 20 W, whereas the expression of Foxo1, Inha, and Taf4b was significantly de-creased at 20 W. Ccnd2 and Igf1 expression was maintained at similar levels in each stage. In total, 27 genes were upregulated and 26 genes interacted with miRNAs; moreover, stage-specific upregulated and downregulated interactions were demonstrated. Increased and decreased miRNAs were identified at each stage in the ovaries. The constitutively expressed genes, Ccnd2 and Igf1, were identified as the major targets of many miRNAs (p < 0.05), and Fshr and Foxo3 interacted with miRNAs, namely mmu-miR-670-3p and mmu-miR-153-3p. miR-26a-5p interacted with Piwil2, and its target genes were downregulated in the 20 W mouse ovary. In this study, we aimed to identify key miRNAs and their target genes encompassing the reproductive span of mouse ovaries using mRNA and miRNA sequencing. These results indicated that gene sets are regulated in the reproductive stage-specific manner via interaction with miRNAs. Furthermore, consistent expression of Ccnd2 and Igf1 is considered crucial for the ovarian reserve and is regulated by many interactive miRNAs.

Gene network analysis to determine the effect of hypoxia-associated genes on brain damages and tumorigenesis using an avian model

BACKGROUND

Hypoxia refers to the condition of low oxygen pressure in the atmosphere and characterization of response to hypoxia as a biological complex puzzle, is challenging. Previously, we carried out a comparative genomic study by whole genome resequencing of highland and lowland Iranian native chickens to identify genomic variants associated with hypoxia conditions. Based on our previous findings, we used chicken as a model and the identified hypoxia-associated genes were converted to human's orthologs genes to construct the informative gene network. The main goal of this study was to visualize the features of diseases due to hypoxia-associated genes by gene network analysis.

RESULTS

It was found that hypoxia-associated genes contained several gene networks of disorders such as Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and cancers. We found that biological pathways are involved in mitochondrion dysfunctions including peroxynitrous acid production denoted in brain injuries. Lewy body and neuromelanin were reported as key symptoms in Parkinson disease. Furthermore, calmodulin, and amyloid precursor protein were detected as leader proteins in Alzheimer's diseases. Dexamethasone was reported as the candidate toxic drug under the hypoxia condition that implicates diabetes, osteoporosis, and neurotoxicity. Our results suggested DNA damages caused by the high doses of UV radiation in high-altitude conditions, were associated with breast cancer, ovarian cancer, and colorectal cancer.

CONCLUSIONS

Our results showed that hypoxia-associated genes were enriched in several gene networks of disorders including Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and different types of cancers. Furthermore, we suggested, UV radiation and low oxygen conditions in high-altitude regions may be responsible for the variety of human diseases.

In Vitro Activation Early Follicles: From the Basic Science to the Clinical Perspectives

Development of early follicles, especially the activation of primordial follicles, is strictly modulated by a network of signaling pathways. Recent advance in ovarian physiology has been allowed the development of several therapies to improve reproductive outcomes by manipulating early folliculogenesis. Among these, in vitro activation (IVA) has been recently developed to extend the possibility of achieving genetically related offspring for patients with premature ovarian insufficiency and ovarian dysfunction. This method was established based on basic science studies of the intraovarian signaling pathways: the phosphoinositide 3-kinase (PI3K)/Akt and the Hippo signaling pathways. These two pathways were found to play crucial roles in folliculogenesis from the primordial follicle to the early antral follicle. Following the results of rodent experiments, IVA was implemented in clinical practice. There have been multiple recorded live births and ongoing pregnancies. Further investigations are essential to confirm the efficacy and safety of IVA before used widely in clinics. This review aimed to summarize the published literature on IVA and provide future perspectives for its improvement.

Ovarian Fragmentation and AKT Stimulation for Expansion of Fertile Lifespan

Since the first baby was born after in vitro fertilization, the female infertility treatment has been well-developed, yielding successful outcomes. However, successful pregnancies for patients with premature ovarian insufficiency and diminished ovarian reserve are still difficult and diverse therapies have been suggested to improve the chances to have their genetically linked offspring. Recent studies demonstrated that the activation Akt pathway by using a phosphatase and tensin homolog enzyme inhibitor and a phosphatidylinositol-3 kinase stimulator can activate dormant primordial follicles in both mice and human ovaries. Subsequent researches suggested that the disruption of Hippo signaling pathway by ovarian fragmentation increased the expression of downstream growth factors and secondary follicle growth. Based on the combination of ovarian fragmentation and Akt stimulation, the in vitro activation (IVA) approach has resulted in successful follicle growth and live births in premature ovarian insufficiency patients. The approach with disruption of Hippo signaling only was also shown to be effective for treating poor ovarian responders with diminishing ovarian reserve, including advanced age women and cancer patients undergoing sterilizing treatments. This review aims to summarize the effectiveness of ovarian fragmentation and Akt stimulation on follicle growth and the potential of IVA in extending female fertile lifespan.

New insights into the genetic basis of premature ovarian insufficiency: Novel causative variants and candidate genes revealed by genomic sequencing

Ovarian deficiency, including premature ovarian insufficiency (POI) and diminished ovarian reserve (DOR), represents one of the main causes of female infertility. POI is a genetically heterogeneous condition but current understanding of its genetic basis is far from complete, with the cause remaining unknown in the majority of patients. The genes that regulate DOR have been reported but the genetic basis of DOR has not been explored in depth. Both conditions are likely to lie along a continuum of degrees of decrease in ovarian reserve. We performed genomic analysis via whole exome sequencing (WES) followed by in silico analyses and functional experiments to investigate the genetic cause of ovarian deficiency in ten affected women. We achieved diagnoses for three of them, including the identification of novel variants in STAG3, GDF9, and FANCM. We identified potentially causative FSHR variants in another patient. This is the second report of biallelic GDF9 and FANCM variants, and, combined with functional support, validates these genes as bone fide autosomal recessive "POI genes". We also identified new candidate genes, NRIP1, XPO1, and MACF1. These genes have been linked to ovarian function in mouse, pig, and zebrafish respectively, but never in humans. In the case of NRIP1, we provide functional support for the deleterious nature of the variant via SUMOylation and luciferase/β-galactosidase reporter assays. Our study provides multiple insights into the genetic basis of POI/DOR. We have further elucidated the involvement of GDF9, FANCM, STAG3 and FSHR in POI pathogenesis, and propose new candidate genes, NRIP1, XPO1, and MACF1, which should be the focus of future studies.

Hippo signaling disruption and ovarian follicle activation in infertile patients

The Hippo signaling pathway, which is important in organ size regulation, is present in organisms from the fly to mammals. Disruption of the Hippo signaling pathway leads to increased nuclear translocation of the effector Yes-associated protein (YAP), resulting in the expression of cystein-rich 61, connective tissue growth factor, and nephroblastoma overexpressed (CCN) growth factors and baculoviral inhibitors of apoptosis repeat containing (BIRC) apoptosis inhibitors to increase organ sizes. Furthermore, genome-wide knockdown of genes in insect cells demonstrated that actin polymerization promoted nuclear translocation of YAP. In the mammalian ovary, we demonstrated the expression of Hippo signaling pathway genes and showed that ovarian fragmentation increased actin polymerization, leading to YAP nuclear translocation and increased expression of cystein-rich 61, CCN growth factors and BIRC apoptosis inhibitors, followed by enhanced follicle growth. Here we summarize evidence suggesting the role of mechanical stress on follicle growth in the ovary and describe recent use of ovary-damaging procedures to treat ovarian infertility. Ovarian fragmentation, together with in vitro incubation with Akt-stimulating drugs, formed the basis of an in vitro activation (IVA) therapy to treat patients with premature ovarian insufficiency, whereas ovarian fragmentation alone (drug-free IVA) was successful in treating patients with premature ovarian insufficiency with recent menses cessation. For middle-aged women with poor ovarian responses and diminished ovarian reserve, drug-free IVA was also effective in promoting follicle growth for infertility treatment. In addition, an in vivo follicle activation approach based on laparoscopic ovarian incision showed promise for patients with resistant ovary syndrome. With initial success using mechanical disruption approaches, future investigation could evaluate possibilities to refine mechanical methods and to locally administer actin polymerization-enhancing drugs for ovarian infertility treatment.

MicroRNA-based regulatory circuit involved in sperm infertility

miRNAs (MicroRNAs), known as noncoding and important endogenous factors regulating the expression protein-coding genes, are vital regulators in each biological process. Thus, this study aims to explore the key role of four microRNAs in regulating the spermatogenesis. To conduct this experiment, 55 infertile and fertile men provided the study with the sperm and testicular tissue samples. To study the spermatozoa in terms of the morphology, Diff-Quick was applied. Then, quantitative real-time polymerase chain reaction (RT-PCR) was conducted on samples. Our data indicated that in contrast to the miR-15b, significant increasing of miR-383 and miR-122 occurred in both severe oligoasthenoteratozoospermia (SOAT) and moderate oligoasthenoteratozoospermia (MOAT) compared to normal sperm group (N). In addition, it was observed that miR-15b and miR-122 increased in patients with nonobstructive azoospermia (NOA) compared with obstructive azoospermia (OA) group. Expression levels of target genes including P53, CASPASE-9 and CYCLIN D1 underwent principle changes according to miRNAs expression level. Our finding indicated that miRNAs had essential role in the regulation of spermatogenesis, and their expression altering was associated with sperm abnormalities. Thus, microRNAs can be introduced as useful biomarkers to determine male infertility reasons to choose the effective treatment.

Analysis of NR5A1 in 142 patients with premature ovarian insufficiency, diminished ovarian reserve, or unexplained infertility

Ovarian deficiency, including diminished ovarian reserve and premature ovarian insufficiency, represents one of the main causes of female infertility. Little is known of the genetic basis of diminished ovarian reserve, while premature ovarian insufficiency often has a genetic basis, with genes affecting various processes. NR5A1 is a key gene required for gonadal function, and variants are associated with a wide phenotypic spectrum of disorders of sexual development, and are found in 0.26-8% of patients with premature ovarian insufficiency. As there is some debate about the extent of involvement of NR5A1 in the pathogenesis of ovarian deficiency, we performed an in-depth analysis of NR5A1 variants detected in a cohort of 142 patients with premature ovarian insufficiency, diminished ovarian reserve, or unexplained infertility associated with normal ovarian function. We identified rare non-synonymous protein-altering variants in 2.8 % of women with ovarian deficiency and no such variants in our small cohort of women with infertility but normal ovarian function. We observed previously reported variants associated with premature ovarian insufficiency in patients with diminished ovarian reserve, highlighting a genetic relationship between these conditions. We confirmed functional impairment resulting from a p.Val15Met variant, detected for the first time in a patient with premature ovarian insufficiency. The remaining variants were associated with preserved transcriptional activity and localization of NR5A1, indicating that rare NR5A1 variants may be incorrectly curated if functional studies are not undertaken, and/or that NR5A1 variants may have only a subtle impact on protein function and/or confer risk of ovarian deficiency via oligogenic inheritance.

Genomic analysis reveals variant association with high altitude adaptation in native chickens

Native chickens are endangered genetic resources that are kept by farmers for different purposes. Native chickens distributed in a wide range of altitudes, have developed adaptive mechanisms to deal with hypoxia. For the first time, we report variants associated with high-altitude adaptation in Iranian native chickens by whole genome sequencing of lowland and highland chickens. We found that these adaptive variants are involved in DNA repair, organs development, immune response and histone binding. Amazingly, signature selection analysis demonstrated that differential variants are adaptive in response to hypoxia and are not due to other evolutionary pressures. Cellular component analysis of variants showed that mitochondrion is the most important organelle for hypoxia adaptation. A total of 50 variants was detected in mtDNA for highland and lowland chickens. High-altitude associated with variant discovery highlighted the importance of COX3, a gene involved in cell respiration, in hypoxia adaptation. The results of study suggest that MIR6644-2 is involved in hypoxia and high-altitude adaptations by regulation of embryo development. Finally, 3877 novel SNVs including the mtDNA ones, were submitted to EBI (PRJEB24944). Whole-genome sequencing and variant discovery of native chickens provided novel insights about adaptation mechanisms and highlights the importance of valuable genomic variants in chickens.

Tissue-specific transcriptional biomarkers in medicinal plants: Application of large-scale meta-analysis and computational systems biology

Biosynthesis of secondary metabolites in plant is a complex process, regulated by many genes and influenced by several factors. In recent years, the next-generation sequencing (NGS) technology and advanced statistical analysis such as meta-analysis and computational systems biology have provided novel opportunities to overcome biological complexity. Here, we performed a meta-analysis on publicly available transcriptome datasets of twelve economically significant medicinal plants to identify differentially expressed genes (DEGs) between shoot and root tissues and to find the key molecular features which may be effective in the biosynthesis of secondary metabolites. Meta-analysis identified a total of 880 genes with differential expression between two tissues. Functional enrichment and KEGG pathway analysis indicated that the functions of those DEGs are highly associated with the developmental process, starch metabolic process, response to stimulus, porphyrin and chlorophyll metabolism, biosynthesis of secondary metabolites and phenylalanine metabolism. In addition, systems biology analysis of the DEGs was applied to find protein-protein interaction network and discovery of significant modules. The detected modules were associated with hormone signal transduction, transcription repressor activity, response to light stimulus and epigenetic processes. Finally, analysis was extended to search for putative miRNAs that are associated with DEGs. A total of 31 miRNAs were detected which belonged to 16 conserved families. The present study provides a comprehensive view to better understand the tissue-specific expression of genes and mechanisms involved in secondary metabolites synthesis and may provide candidate genes for future researches to improve yield of secondary metabolites.

Unified Transcriptomic Signature of Arbuscular Mycorrhiza Colonization in Roots of Medicago truncatula by Integration of Machine Learning, Promoter Analysis, and Direct Merging Meta-Analysis

Plant root symbiosis with Arbuscular mycorrhizal (AM) fungi improves uptake of water and mineral nutrients, improving plant development under stressful conditions. Unraveling the unified transcriptomic signature of a successful colonization provides a better understanding of symbiosis. We developed a framework for finding the transcriptomic signature of Arbuscular mycorrhiza colonization and its regulating transcription factors in roots of Medicago truncatula. Expression profiles of roots in response to AM species were collected from four separate studies and were combined by direct merging meta-analysis. Batch effect, the major concern in expression meta-analysis, was reduced by three normalization steps: Robust Multi-array Average algorithm, Z-standardization, and quartiling normalization. Then, expression profile of 33685 genes in 18 root samples of Medicago as numerical features, as well as study ID and Arbuscular mycorrhiza type as categorical features, were mined by seven models: RELIEF, UNCERTAINTY, GINI INDEX, Chi Squared, RULE, INFO GAIN, and INFO GAIN RATIO. In total, 73 genes selected by machine learning models were up-regulated in response to AM (Z-value difference > 0.5). Feature weighting models also documented that this signature is independent from study (batch) effect. The AM inoculation signature obtained was able to differentiate efficiently between AM inoculated and non-inoculated samples. The AP2 domain class transcription factor, GRAS family transcription factors, and cyclin-dependent kinase were among the highly expressed meta-genes identified in the signature. We found high correspondence between the AM colonization signature obtained in this study and independent RNA-seq experiments on AM colonization, validating the repeatability of the colonization signature. Promoter analysis of upregulated genes in the transcriptomic signature led to the key regulators of AM colonization, including the essential transcription factors for endosymbiosis establishment and development such as NF-YA factors. The approach developed in this study offers three distinct novel features: (I) it improves direct merging meta-analysis by integrating supervised machine learning models and normalization steps to reduce study-specific batch effects; (II) seven attribute weighting models assessed the suitability of each gene for the transcriptomic signature which contributes to robustness of the signature (III) the approach is justifiable, easy to apply, and useful in practice. Our integrative framework of meta-analysis, promoter analysis, and machine learning provides a foundation to reveal the transcriptomic signature and regulatory circuits governing Arbuscular mycorrhizal symbiosis and is transferable to the other biological settings.

Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle

Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as bio-signature and confirmed that some of the top-ranked genes -ZC3H12A, CXCL2, GRO, CFB- as biomarkers for E. coli mastitis (with the accuracy 83% in average). This research properly indicated that by combination of two novel data mining tools, meta-analysis and machine learning, increased power to detect most informative genes that can help to improve the diagnosis and treatment strategies for E. coli associated with mastitis in cattle.

Enhancement of anticancer activity by silibinin and paclitaxel combination on the ovarian cancer

BACKGROUND

Ovarian carcinoma is the most lethal cancer among all gynaecological malignancies. One of the most chemotherapy drugs used for ovarian cancer is paclitaxel which induces apoptosis. Paclitaxel has been used for many years. Similar to the most cancers this responds to chemotherapy initially but in a long run, drug resistance happens which fails the treatment procedure. Combination of chemotherapy drugs has been suggested to deal with this issue. Silibinin, a plant extraction, has been used from ancient time in traditional medicine and identified to have powerful antioxidant activity.

AIM

The aim of this study was to examine the effect of paclitaxel and silibinin combination on SKOV-3 cancer cell line.

MATERIALS AND METHODS

The human epithelial ovarian cancer cell line, SKOV-3, was cultured and treated with paclitaxel, silibinin and paclitaxel plus silibinin for 48 hours. MTT assay was carried out to determine cell viability. For apoptotic process, we used real-time PCR to study P53 and P21 genes expression after drug treatment and network analysis was performed using Pathway Studio web tool (Elsevier).

RESULTS

Cell growth was inhibited considerably (p < .05) by combination of paclitaxel and silibinin after 48 hours of treatment. Also silibinin and paclitaxel combination induced apoptosis in SKOV-3 cells. Expression analysis by real-time PCR showed the significant up-regulation of two tumour suppressor genes, P53 and P21 in response to combination of silibinin and paclitaxel. In addition, computational network analysis demonstrated the crosstalk between paclitaxel, silibinin and ovarian cancer.

CONCLUSIONS

Our results showed that combination of chemotherapy drugs of silibinin and paclitaxel can be more efficient in treatment of ovarian cancer cells.