Precise Characterization of Genetic Interactions in Cancer via Molecular Network Refining Processes.

Genetic interactions (GIs), such as the synthetic lethal interaction, are promising therapeutic targets in precision medicine. However, despite extensive efforts to characterize GIs by large-scale perturbation screening, considerable false positives have been reported in multiple studies. We propose a new computational approach for improved precision in GI identification by applying constraints that consider actual biological phenomena. In this study, GIs were characterized by assessing mutation, loss of function, and expression profiles in the DEPMAP database. The expression profiles were used to exclude loss-of-function data for nonexpressed genes in GI characterization. More importantly, the characterized GIs were refined based on Kyoto Encyclopedia of Genes and Genomes (KEGG) or protein-protein interaction (PPI) networks, under the assumption that genes genetically interacting with a certain mutated gene are adjacent in the networks. As a result, the initial GIs characterized with CRISPR and RNAi screenings were refined to 65 and 23 GIs based on KEGG networks and to 183 and 142 GIs based on PPI networks. The evaluation of refined GIs showed improved precision with respect to known synthetic lethal interactions. The refining process also yielded a synthetic partner network (SPN) for each mutated gene, which provides insight into therapeutic strategies for the mutated genes; specifically, exploring the SPN of mutated BRAF revealed ELAVL1 as a potential target for treating BRAF-mutated cancer, as validated by previous research. We expect that this work will advance cancer therapeutic research.

New Insights Into Mitochondrial Dysfunction at Disease Susceptibility Loci in the Development of Type 2 Diabetes.

This study investigated the potential genetic mechanisms which underlie adipose tissue mitochondrial dysfunction in Type 2 diabetes (T2D), by systematically identifying nuclear-encoded mitochondrial genes (NEMGs) among the genes regulated by T2D-associated genetic loci. The target genes of these 'disease loci' were identified by mapping genetic loci associated with both disease and gene expression levels (expression quantitative trait loci, eQTL) using high resolution genetic maps, with independent estimates co-locating to within a small genetic distance. These co-locating signals were defined as T2D-eQTL and the target genes as T2D cis-genes. In total, 763 cis-genes were associated with T2D-eQTL, of which 50 were NEMGs. Independent gene expression datasets for T2D and insulin resistant cases and controls confirmed that the cis-genes and cis-NEMGs were enriched for differential expression in cases, providing independent validation that genetic maps can identify informative functional genes. Two additional results were consistent with a potential role of T2D-eQTL in regulating the 50 identified cis-NEMGs in the context of T2D risk: (1) the 50 cis-NEMGs showed greater differential expression compared to other NEMGs and (2) other NEMGs showed a trend towards significantly decreased expression if their expression levels correlated more highly with the subset of 50 cis-NEMGs. These 50 cis-NEMGs, which are differentially expressed and associated with mapped T2D disease loci, encode proteins acting within key mitochondrial pathways, including some of current therapeutic interest such as the metabolism of branched-chain amino acids, GABA and biotin.

Learning epistatic gene interactions from perturbation screens.

The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which contribute to a phenotype in a non-linear fashion. Experimental identification of the full landscape of genetic interactions by perturbing all gene combinations is prohibitive due to the exponential growth of testable hypotheses. Here we present a model for the inference of pairwise epistatic, including synthetic lethal, gene interactions from siRNA-based perturbation screens. The model exploits the combinatorial nature of siRNA-based screens resulting from the high numbers of sequence-dependent off-target effects, where each siRNA apart from its intended target knocks down hundreds of additional genes. We show that conditional and marginal epistasis can be estimated as interaction coefficients of regression models on perturbation data. We compare two methods, namely glinternet and xyz, for selecting non-zero effects in high dimensions as components of the model, and make recommendations for the appropriate use of each. For data simulated from real RNAi screening libraries, we show that glinternet successfully identifies epistatic gene pairs with high accuracy across a wide range of relevant parameters for the signal-to-noise ratio of observed phenotypes, the effect size of epistasis and the number of observations per double knockdown. xyz is also able to identify interactions from lower dimensional data sets (fewer genes), but is less accurate for many dimensions. Higher accuracy of glinternet, however, comes at the cost of longer running time compared to xyz. The general model is widely applicable and allows mining the wealth of publicly available RNAi screening data for the estimation of epistatic interactions between genes. As a proof of concept, we apply the model to search for interactions, and potential targets for treatment, among previously published sets of siRNA perturbation screens on various pathogens. The identified interactions include both known epistatic interactions as well as novel findings.

Selection for cooperativity causes epistasis predominately between native contacts and enables epistasis-based structure reconstruction.

Epistasis and cooperativity of folding both result from networks of energetic interactions in proteins. Epistasis results from energetic interactions among mutants, whereas cooperativity results from energetic interactions during folding that reduce the presence of intermediate states. The two concepts seem intuitively related, but it is unknown how they are related, particularly in terms of selection. To investigate their relationship, we simulated protein evolution under selection for cooperativity and separately under selection for epistasis. Strong selection for cooperativity created strong epistasis between contacts in the native structure but weakened epistasis between nonnative contacts. In contrast, selection for epistasis increased epistasis in both native and nonnative contacts and reduced cooperativity. Because epistasis can be used to predict protein structure only if it preferentially occurs in native contacts, this result indicates that selection for cooperativity may be key for predicting structure using epistasis. To evaluate this inference, we simulated the evolution of guanine nucleotide-binding protein (GB1) with and without cooperativity. With cooperativity, strong epistatic interactions clearly map out the native GB1 structure, while allowing the presence of intermediate states (low cooperativity) obscured the structure. This indicates that using epistasis measurements to reconstruct protein structure may be inappropriate for proteins with stable intermediates.

PIWIL1 interacting RNA piR-017061 inhibits pancreatic cancer growth via regulating EFNA5.

PIWI (P element induced wimpy testis) integrating RNAs (piRNAs) are small non-coding RNAs with the length of approximately 30 nucleotides that plays crucial roles in germ cells and adult stem cells. Recently, accumulating data have shown that piRNA and PIWI proteins are involved in tumorigenesis. However, the roles of PIWI proteins and piRNAs in pancreatic cancer are still elusive. Here, we showed that piR-017061 is significantly downregulated in pancreatic cancer patients' samples and pancreatic cancer cell lines. Furthermore, we studied the function of piR-017061 in pancreatic cancer and our data revealed that piR-017061 inhibits pancreatic cancer cell growth in vitro and in vivo. Moreover, we analyzed the genomic loci around piR-017061 and identified EFNA5 as a novel target of piR-017061. Importantly, our data further revealed a direct binding between piR-017061 and EFNA5 mRNA mediated by PIWIL1. Mechanically, piR-017061 cooperates with PIWIL1 to facilitate EFNA5 mRNA degradation and loss of piR-017061 results in accumulation of EFNA5 which facilitates pancreatic cancer development. Hence, our data provided novel insights into PIWI/piRNA-mediated gene regulation and their function in pancreatic cancer. Since PIWI proteins and piRNA predominately express in germline and cancer cells, our study provided novel therapeutic strategy for pancreatic cancer treatment.

Genome-wide association study of flowering time reveals complex genetic heterogeneity and epistatic interactions in rice.

Since domestication, rice has cultivated in a wide range of latitudes with different day lengths. Selection of diverse natural variations in heading date and photoperiod sensitivity is critical for adaptation of rice to different geographical environments. To unravel the genetic architecture underlying natural variation of rice flowering time, we conducted a genome wide association study (GWAS) using several association analysis strategies with a diverse worldwide collection of 529 O. sativa accessions. Heading date was investigated in three environments under long-day or short-day conditions, and photosensitivity was evaluated. By dividing the whole association panel into subpopulations and performing GWAS with both linear mixed models and multi-locus mixed-models, we revealed hundreds of significant loci harboring novel candidate genes as well as most of the known flowering time genes. In total, 127 hotspots were detected in at least two GWAS. Universal genetic heterogeneity was found across subpopulations. We further detected abundant interactions between GWAS loci, especially in indica. Functional gene families were revealed from enrichment analysis of the 127 hotspots. The results demonstrated a rich of genetic interactions in rice flowering time genes and such epistatic interactions contributed to the large portions of missing heritability in GWAS. It suggests the increased complexity of genetic heterogeneity might discount the power of increasing the sample sizes in GWAS.

Identifying Clear Cell Renal Cell Carcinoma Coexpression Networks Associated with Opioid Signaling and Survival.

While opioids constitute the major component of perioperative analgesic regimens for surgery in general, a variety of evidence points to an association between perioperative opioid exposure and longer term oncologic outcomes. The mechanistic details underlying these effects are not well understood. In this study, we focused on clear cell renal cell carcinoma (ccRCC) and utilized RNA sequencing and outcome data from both The Cancer Genome Atlas, as well as a local patient cohort to identify survival-associated gene coexpression networks. We then projected drug-induced transcriptional profiles from in vitro cancer cells to predict drug effects on these networks and recurrence-free, cancer-specific, and overall survival. The opioid receptor agonist, leu-enkephalin, was predicted to have antisurvival effects in ccRCC, primarily through Th2 immune- and NRF2-dependent macrophage networks. Conversely, the antagonist, naloxone, was predicted to have prosurvival effects, primarily through angiogenesis, fatty acid metabolism, and hemopoesis pathways. Eight coexpression networks associated with survival endpoints in ccRCC were identified, and master regulators of the transition from the normal to disease state were inferred, a number of which are linked to opioid pathways. These results are the first to suggest a mechanism for opioid effects on cancer outcomes through modulation of survival-associated coexpression networks. While we focus on ccRCC, this methodology may be employed to predict opioid effects on other cancer types and to personalize analgesic regimens in patients with cancer for optimal outcomes. SIGNIFICANCE: This study suggests a possible molecular mechanism for opioid effects on cancer outcomes generally, with implications for personalization of analgesic regimens.

The interaction of ASAH1 and NGF gene involving in neurotrophin signaling pathway contributes to schizophrenia susceptibility and psychopathology.

The neurodevelopmental hypothesis of schizophrenia has been widely accepted. In light of our previous microarray data, two neurodevelopment-related genes were focused on inclduing the N-acylsphingosine amidohydrolase 1 gene (ASAH1) and the nerve growth factor gene (NGF). The evidence that ASAH1 and NGF are associated with schizophrenia is far from conclusive. Furthermore, their interactions in schizophrenia have not been investigated. Total 413 patients and 578 controls were included. Eleven single-nucleotide polymorphisms (SNPs) in ASAH1 and NGF were selected. A multifactor dimensionality reduction (MDR) was applied to investigate gene-gene interactions in schizophrenia, and the traditional odds ratio methods was applied to validate it. The effects of ASAH1, NGF and their interaction on the severity of the disease were analyzed by 3 × 3 covariance analysis of (ANCOVA). The biological interaction between ASAH1 and NGF was examined. KEGG was used to identify the related signaling pathways. After correction by Bonferroni, there were no differences in the genotypic, allelic, or haplotypic frequencies of 11 SNPs between patients and controls. However, the interaction of certain SNPs had effect on susceptibility to schizophrenia, including two high-risk and one low-risk genotypic combinations (OR = 1.49 [1.11-2.00]; OR = 1.45 [1.09-1.92], and OR = 0.64 [0.41-0.98]). ASAH1-rs7830490 and its interaction with NGF-rs4332358 were associated with the general psychopathological subscale score (F adjusted = 3.94, p adjusted = 0.01; F adjusted = 2.36, p adjusted = 0.03). We also found that ASAH1 and NGF interacted with CaMK2B involving in the neurotrophin signaling pathway. Our results suggest that the interaction of ASAH1 and NGF with CaMK2B involved in neurotrophin signaling pathway may contribute to schizophrenia susceptibility and psychopathology.

Mitochondrial-Y chromosome epistasis in Drosophila melanogaster.

The coordination between mitochondrial and nuclear genes is crucial to eukaryotic organisms. Predicting the nature of these epistatic interactions can be difficult because of the transmission asymmetry of the genes involved. While autosomes and X-linked genes are transmitted through both sexes, genes on the Y chromosome and in the mitochondrial genome are uniparentally transmitted through males and females, respectively. Here, we generate 36 otherwise isogenic Drosophila melanogaster strains differing only in the geographical origin of their mitochondrial genome and Y chromosome, to experimentally examine the effects of the uniparentally inherited parts of the genome, as well as their interaction, in males. We assay longevity and gene expression through RNA-sequencing. We detect an important role for both mitochondrial and Y-linked genes, as well as extensive mitochondrial-Y chromosome epistasis. In particular, genes involved in male reproduction appear to be especially sensitive to such interactions, and variation on the Y chromosome is associated with differences in longevity. Despite these interactions, we find no evidence that the mitochondrial genome and Y chromosome are co-adapted within a geographical region. Overall, our study demonstrates a key role for the uniparentally inherited parts of the genome for male biology, but also that mito-nuclear interactions are complex and not easily predicted from simple transmission asymmetries.

LncRNA SNHG10 increases the methylation of miR-218 gene to promote glucose uptake and cell proliferation in osteosarcoma.

BACKGROUND: This study aimed to investigate the roles of lncRNA SNHG10 (SNHG10) and miR-218 in osteosarcoma (OS). METHODS: Paired OS and non-tumor tissues were collected from 58 OS patients. The expression of SNHG10 and miR-218 in tissue samples were determined by RT-qPCR. The interaction between SNHG10 and miR-218 was evaluated by overexpression experiment. Methylation-specific PCR was performed to assess the methylation status of miR-218. Glucose uptake in OS cells was analyzed by glucose uptake assay. Cell proliferation was detected by cell proliferation assay. RESULTS: SNHG10 was upregulated in OS, while miR-218 was downregulated in OS. The expression of SNHG10 and miR-218 were inversely correlated. In OS cells, high glucose induced the upregulation of SNHG10 and downregulation of miR-218. In OS cells, SNHG10 positively, and miR-218 negatively regulated glucose uptake. Overexpression of SNHG10 increased miR-218 gene methylation and decreased the expression of miR-218. In addition, overexpression of SNHG10 also suppressed the inhibitory effects of overexpression of miR-218 on cell proliferation. CONCLUSIONS: SNHG10 increases the methylation of miR-218 gene to promote glucose uptake and cell proliferation in OS.

Allelic Distribution of Genes for Apolipoprotein E and MTHFR in Patients with Alzheimer's Disease and Their Epistatic Interaction.

BACKGROUND: Genetic risk factors play an important role in the pathogenesis of Alzheimer's disease (AD). However, the gene-gene interaction (epistasis) between specific allelic variants is only partially understood. OBJECTIVE: In our study, we examined the presence of the ɛ4 allele of apolipoprotein E (APOE) and the presence of C677T and A1298C (rs1801133 and rs1801131) polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene in patients with AD and controls. We also evaluated the epistatic interaction between MTHFR and the APOE variants. METHODS: A total of 564 patients with AD and 534 cognitively unimpaired age-matched controls were involved in the study. RESULTS: The presence of the ɛ4 allele of APOE increases the risk of developing AD in a dose-dependent manner (OR 32.7: homozygotes, 15.6: homozygotes + heterozygotes, 14.3: heterozygotes). The combination of genotypes also increases the risk of developing AD in a dose-dependent manner: OR 18.3 (APOE 4/X and 4/4 + CT rs1801133), OR 19.4 (APOE 4/X and 4/4 + CT rs1801133 + AC rs1801131), OR 22.4 (APOE 4/X and 4/4 + TT rs1801133), and OR 21.2 (APOE 4/X and 4/4 + CC rs1801131). Homozygotes for variant alleles of MTHFR as well as patients with AD had significantly higher levels of homocysteine than homozygotes for standard alleles or controls. CONCLUSION: Homozygotes for APOE4 and carriers of APOE4 with TT genotype of rs1801133 were found to be at the highest risk of developing AD. These findings suggest that the epistatic interaction of specific gene variants can have a significant effect on the development of AD.

Transcriptomic and computational analysis identified LPA metabolism, KLHL14 and KCNE3 as novel regulators of Epithelial-Mesenchymal Transition.

Epithelial-mesenchymal transition (EMT) is a complex biological program between physiology and pathology. Here, amniotic epithelial cells (AEC) were used as in vitro model of transiently inducible EMT in order to evaluate the transcriptional insights underlying this process. Therefore, RNA-seq was used to identify the differentially expressed genes and enrichment analyses were carried out to assess the intracellular pathways involved. As a result, molecules exclusively expressed in AEC that experienced EMT (GSTA1-1 and GSTM3) or when this process is inhibited (KLHL14 and KCNE3) were identified. Lastly, the network theory was used to obtain a computational model able to recognize putative controller genes involved in the induction and in the prevention of EMT. The results suggested an opposite role of lysophosphatidic acid (LPA) synthesis and degradation enzymes in the regulation of EMT process. In conclusion, these molecules may represent novel EMT regulators and also targets for developing new therapeutic strategies.

The interaction of histone modification related H3F3B and NSD2 genes increases the susceptibility to schizophrenia in a Chinese population.

The role of histone modifications in the pathogenesis of schizophrenia has been proposed previously. H3F3B is a member of the histone 3. NSD2 is a histone methyltransferase that mediates dimethylation of Histone 3 lysine 36 (H3K36me2). The aim of the current study was to explore the associations between SNPs within H3F3B gene (rs60700976, rs3214028) and NSD2 gene (rs13148597, rs75820801) and the susceptibility to schizophrenia in a Chinese population. A total of 810 patients and 490 healthy controls were recruited and genetic association analyses were performed. The H3F3B gene polymorphisms rs3214028 and rs60700976 were significantly associated with schizophrenia. Rs60700976 was also associated with psychotic symptoms in schizophrenia patients. Furthermore, we found the interaction between NSD2 gene and H3F3B gene was related to the susceptibility to schizophrenia. The corresponding best three-locus model was H3F3B (rs60700976) - NSD2 (rs75820801, rs13148597), and the high-risk genotype combination was rs13148597(CC)- rs60700976(GG)-rs75820801(TT) (OR = 1.388[1.091-1.766], P = .007). The low-risk genotype combination was rs13148597(CC)-rs60700976(GG)-rs75820801(CT) (OR = 0.57 [0.330-0.985], P = .042). Our findings provided the preliminary evidence that the histone modification related H3F3B and NSD2 genes may confer the susceptibility to schizophrenia in a Chinese population.

[SLC6A14, a modifier gene in cystic fibrosis]. / SLC6A14, un gène modificateur dans la mucoviscidose.

Although cystic fibrosis is a monogenic disease, a considerable clinical phenotypic variability is observed in patients with the same CFTR mutations. Thanks to the development of new and powerful tools for carrying out genetic studies, several genes called "modifier genes" have been identified as being associated with the severity of the lung function disorder in cystic fibrosis patients. Among these genes, SLC6A14 may modulate the anti-infective response and epithelial integrity of the airways, thus providing a potential therapeutic target to improve the patient's lung function.

Drosophila enabled promotes synapse morphogenesis and regulates active zone form and function.

BACKGROUND: Recent studies of synapse form and function highlight the importance of the actin cytoskeleton in regulating multiple aspects of morphogenesis, neurotransmission, and neural plasticity. The conserved actin-associated protein Enabled (Ena) is known to regulate development of the Drosophila larval neuromuscular junction through a postsynaptic mechanism. However, the functions and regulation of Ena within the presynaptic terminal has not been determined. METHODS: Here, we use a conditional genetic approach to address a presynaptic role for Ena on presynaptic morphology and ultrastructure, and also examine the pathway in which Ena functions through epistasis experiments. RESULTS: We find that Ena is required to promote the morphogenesis of presynaptic boutons and branches, in contrast to its inhibitory role in muscle. Moreover, while postsynaptic Ena is regulated by microRNA-mediated mechanisms, presynaptic Ena relays the output of the highly conserved receptor protein tyrosine phosphatase Dlar and associated proteins including the heparan sulfate proteoglycan Syndecan, and the non-receptor Abelson tyrosine kinase to regulate addition of presynaptic varicosities. Interestingly, Ena also influences active zones, where it restricts active zone size, regulates the recruitment of synaptic vesicles, and controls the amplitude and frequency of spontaneous glutamate release. CONCLUSION: We thus show that Ena, under control of the Dlar pathway, is required for presynaptic terminal morphogenesis and bouton addition and that Ena has active zone and neurotransmission phenotypes. Notably, in contrast to Dlar, Ena appears to integrate multiple pathways that regulate synapse form and function.

3D interactions with the growth hormone locus in cellular signalling and cancer-related pathways.

Growth hormone (GH) is a peptide hormone predominantly produced by the anterior pituitary and is essential for normal growth and metabolism. The GH locus contains five evolutionarily related genes under the control of an upstream locus control region that coordinates tissue-specific expression of these genes. Compromised GH signalling and genetic variation in these genes has been implicated in various disorders including cancer. We hypothesised that regulatory regions within the GH locus coordinate expression of a gene network that extends the impact of the GH locus control region. We used the CoDeS3D algorithm to analyse 529 common single nucleotide polymorphisms (SNPs) across the GH locus. This algorithm identifies colocalised Hi-C and eQTL associations to determine which SNPs are associated with a change in gene expression at loci that physically interact within the nucleus. One hundred and eighty-one common SNPs were identified that interacted with 292 eGenes across 48 different tissues. One hundred and forty-five eGenes were regulated in trans. eGenes were found to be enriched in GH/GHR-related cellular signalling pathways including MAPK, PI3K-AKT-mTOR, ERBB and insulin signalling, suggesting that these pathways may be co-regulated with GH signalling. Enrichment was also observed in the Wnt and Hippo signalling pathways and in pathways associated with hepatocellular, colorectal, breast and non-small cell lung carcinoma. Thirty-three eQTL SNPs identified in our study were found to be of regulatory importance in a genome-wide Survey of Regulatory Elements reporter screen. Our data suggest that the GH locus functions as a complex regulatory region that coordinates expression of numerous genes in cis and trans, many of which may be involved in modulating GH function in normal and disease states.

PAM haploinsufficiency does not accelerate the development of diet- and human IAPP-induced diabetes in mice.

AIMS/HYPOTHESIS: Peptide hormones are first synthesised as larger, inactive precursors that are converted to their active forms by endopeptidase cleavage and post-translational modifications, such as amidation. Recent, large-scale genome-wide studies have suggested that two coding variants of the amidating enzyme, peptidylglycine α-amidating monooxygenase (PAM), are associated with impaired insulin secretion and increased type 2 diabetes risk. We aimed to elucidate the role of PAM in modulating beta cell peptide amidation, beta cell function and the development of diabetes. METHODS: PAM transcript and protein levels were analysed in mouse islets following induction of endoplasmic reticulum (ER) or cytokine stress, and PAM expression patterns were examined in human islets. To study whether haploinsufficiency of PAM accelerates the development of diabetes, Pam+/- and Pam+/+ mice were fed a low-fat diet (LFD) or high-fat diet (HFD) and glucose homeostasis was assessed. Since aggregates of the PAM substrate human islet amyloid polypeptide (hIAPP) lead to islet inflammation and beta cell failure, we also investigated whether PAM haploinsufficiency accelerated hIAPP-induced diabetes and islet amyloid formation in Pam+/- and Pam+/+ mice with beta cell expression of hIAPP. RESULTS: Immunostaining revealed high expression of PAM in alpha, beta and delta cells in human pancreatic islets. Pam mRNA and PAM protein expression were reduced in mouse islets following administration of an HFD, and in isolated islets following induction of ER stress with thapsigargin, or cytokine stress with IL-1ß, IFN-γ and TFN-α. Despite Pam+/- only having 50% PAM expression and enzyme activity as compared with Pam+/+ mice, glucose tolerance and body mass composition were comparable in the two models. After 24 weeks of HFD, both Pam+/- and Pam+/+ mice had insulin resistance and impaired glucose tolerance, but no differences in glucose tolerance, insulin sensitivity or plasma insulin levels were observed in PAM haploinsufficient mice. Islet amyloid formation and beta cell function were also similar in Pam+/- and Pam+/+ mice with beta cell expression of hIAPP. CONCLUSIONS/INTERPRETATION: Haploinsufficiency of PAM in mice does not accelerate the development of diet-induced obesity or hIAPP transgene-induced diabetes.

Hemostasis-related gene polymorphisms and their epistatic relationship in women with idiopathic infertility.

: A numerous factor can cause infertility, but around one of four reproductive failure cases remain unexplained and diagnosed as idiopathic infertility. In the past few decades, analysis of gene polymorphisms takes a significant place in pathogenesis of infertility. The aim of this study was to evaluate the possible role of hemostasis-related gene polymorphisms in unexplained infertility. The study includes 117 female patients with idiopathic infertility and 130 fertile women with at least one born child. Eight polymorphisms important for hemostasis (ITGB3 1565T>C, FV 1691G>A, FII 20210G>A, MTHFR 677C>T and 1298A>C, ATIII 786G>A, PAI-14G/5G and ACE I/D) were genotyped by real-time PCR system. The frequencies of alleles and genotypes of examined polymorphisms were analyzed in SPSS statistical program, whereas gene interactions were identified using the GMDR software. Examination of etiological factors has shown that family history is a significant factor in assessing individual risk for infertility. The alleles and genotypes frequency of FV 1691G>A and FII 20210G>A polymorphisms were statistically different between control and patient group leading to a greater risk for infertility. The analysis of epistatic relationship between examined hemostasis-related gene polymorphisms identified more complex high-risk genotypes associated with infertility. Our results suggest that positive family history could be important predictive factor for fertility problems, pointing to the potential hereditary basis of this condition. Polymorphisms FVL and FII prothrombin are independent risk factors for idiopathic infertility, whereas multilocus interactions approach should be taken into consideration for the future research.

Identifying Epistasis in Cancer Genomes: A Delicate Affair.

Recent studies of the tumor genome seek to identify cancer pathways as groups of genes in which mutations are epistatic with one another or, specifically, "mutually exclusive." Here, we show that most mutations are mutually exclusive not due to pathway structure but to interactions with disease subtype and tumor mutation load. In particular, many cancer driver genes are mutated preferentially in tumors with few mutations overall, causing mutations in these cancer genes to appear mutually exclusive with numerous others. Researchers should view current epistasis maps with caution until we better understand the multiple cause-and-effect relationships among factors such as tumor subtype, positive selection for mutations, and gross tumor characteristics including mutational signatures and load.