Gene Interaction Studies Research Articles

Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis.

The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may have an important role in cancer progression, including colorectal cancer (CRC). The present study used machine learning and gene interaction study tools to explore the prognostic and diagnostic value of miRNAs in CRC. Integrative analysis of 353 CRC samples and normal tissue data was obtained from the TCGA database and further analyzed by R packages to define the deferentially expressed miRNAs (DEMs). Furthermore, machine learning and Kaplan Meier survival analysis helped better specify the significant prognostic value of miRNAs. A combination of online databases was then used to evaluate the interactions between target genes, their molecular pathways, and the correlation between the DEMs. The results indicated that miR-19b and miR-20a have a significant prognostic role and are associated with CRC progression. The ROC curve analysis discovered that miR-20a alone and combined with other miRNAs, including hsa-mir-21 and hsa-mir-542, are diagnostic biomarkers in CRC. In addition, 12 genes, including NTRK2, CDC42, EGFR, AGO2, PRKCA, HSP90AA1, TLR4, IGF1, ESR1, SMAD2, SMAD4, and NEDD4L, were found to be the highest score targets for these miRNAs. Pathway analysis identified the two correlated tyrosine kinase and MAPK signaling pathways with the key interaction genes, i.e., EGFR, CDC42, and HSP90AA1. To better define the role of these miRNAs, the ceRNA network, including lncRNAs, was also prepared. In conclusion, the combination of R data analysis and machine learning provides a robust approach to resolving complicated interactions between miRNAs and their targets.

Poor statistical power in population-based association study of gene interaction

BackgroundStatistical epistasis, or “gene–gene interaction” in genetic association studies, means the nonadditive effects between the polymorphic sites on two different genes affecting the same phenotype. In the genetic association analysis of complex traits, nevertheless, the researchers haven’t found enough clues of statistical epistasis so far.MethodsWe developed a statistical model where the statistical epistasis was presented as an extra linkage disequilibrium between the polymorphic sites of different risk genes. The power of statistical test for identifying the gene–gene interaction was calculated and then compared in different hypothesis scenarios.ResultsOur results show the statistical power increases with the increasing of interaction coefficient, relative risk, and linkage disequilibrium with genetic markers. However, the power of interaction discovery is much lower than that of regular single-site association test. When rigorous criteria were employed in statistical tests, the identification of gene–gene interaction became a very difficult task. Since the criterion of significance was given to be p-value ≤ 5.0 × 10–8, the same as that of many genome-wide association studies, there is little chance to identify the gene–gene interaction in all kind of circumstances.ConclusionsThe lack of epistasis tends to be an inevitable result caused by the statistical principles of methods in the genetic association studies and therefore is the inherent characteristic of the research itself.

ЭМПИРИЧЕСКАЯ ТЕОРИЯ ФОРМИРОВАНИЯ ЭМОЦИОНАЛЬНОГО И ВОЛЕВОГО ДЕФИЦИТА ПРИ ШИЗОФРЕНИИ С ПРЕОБЛАДАНИЕМ НЕГАТИВНЫХ РАССТРОЙСТВ, ПОЛУЧЕННАЯ НА ОСНОВЕ АНАЛИЗА СВЯЗИ КЛИНИЧЕСКИХ И ГЕНЕТИЧЕСКИХ ДАННЫХ С ПРИМЕНЕНИЕМ ДСМ-МЕТОДА АВТОМАТИЗИРОВАННОЙ ПОДДЕРЖКИ ИССЛЕДОВАНИЙ

The study attempted to test experts' assumptions about the difference in the genetic mechanisms of the formation of emotional and volitional deficits in schizophrenia with predominance of negative disorders. The aim of the study is to create empirical theory of these two phenomena using an approach based on JSM-method for automated research support (JSM-method ARS). Polymorphisms of four genes associated with schizophrenia (BDNF, 5HTR2A, HTTLPR, ZNF804A) and clinical data presented as PANSS score were used as empirical data. The use of generalized JSM-method ARS, which generates ternary relationships “cause-blocker-effect”, allows us considering in detail the interaction of specific gene variants for emotional and volitional deficits in negative schizophrenia. The result of the study is confirmation of the experts' hypothesis about the difference in the mechanisms of these clinical manifestations. This conclusion was based on a comparison of knowledge fragments for two phenomena. The utilized approach can be extrapolated to a larger number of genes. We suggest that the use of the generalized JSM-method ARS is a promising approach to studying gene interactions in schizophrenia.

Pipecolic acid mitigates ferroptosis in diabetic retinopathy by regulating GPX4-YAP signaling

Diabetic retinopathy (DR) is currently recognized as the leading cause of end-stage eye disease. Pipecolic acid, a metabolite, has a significant regulatory effect on several pathological processes. However, the exact mechanism by which it causes damage in diabetic retinopathy is unknown. Between September 2021 and December 2022, 40 patients were retrospectively examined and divided into two groups: the healthy group (n = 20) and the DR group (n = 20). Metabolomic analysis found that pipecolic acid plays an important role in this process. Streptozotocin-induced diabetic mice and high-glucose cultured human retinal capillary endothelial cells (HRCECs) were then treated with pipecolic acid. Several oxidative stress measurements and RNA sequencing of retinal cells were tested. A gene interaction study was conducted using bioinformatics. Comparison of serological metabolites between healthy volunteers and DR patients showed that pipecolic acid was significantly lower in DR patients, and there was a negative correlation between the level of pipecolic acid with blood glucose and glycated hemoglobin. Yes-associated protein (YAP) mRNA, Malondialdehyde (MDA), and reactive oxygen species (ROS) levels were significantly higher in diabetic mice, but glutathione peroxidase (GSH-Px) levels were significantly lower. Pipecolic acid significantly alleviated oxidative stress and YAP expression. The number of vascular tubes was significantly higher in the DR group, and pipecolic acid treatment significantly reduced tube formation. RNA-Sequencing analysis revealed that YAP and glutathione-dependent lipid hydroperoxidase glutathione peroxidase 4 (GPX4) expression was reduced, and functional enrichment analysis revealed that ferroptosis and Hippo signaling pathways play an important role in this process. Additionally, pipecolic acid's ability to improve DR is diminished after YAP and GPX4 ablation. This study found that pipecolic acid, as a metabolite, may impede the progression of DR by inhibiting the YAP-GPX4 signaling pathway.

Agrobacterium rhizogenes: paving the road to research and breeding for woody plants.

Woody plants play a vital role in global ecosystems and serve as valuable resources for various industries and human needs. While many woody plant genomes have been fully sequenced, gene function research and biotechnological breeding advances have lagged behind. As a result, only a limited number of genes have been elucidated, making it difficult to use newer tools such as CRISPR-Cas9 for biotechnological breeding purposes. The use of Agrobacterium rhizogenes as a transformative tool in plant biotechnology has received considerable attention in recent years, particularly in the research field on woody plants. Over the past three decades, numerous woody plants have been effectively transformed using A. rhizogenes-mediated techniques. Some of these transformed plants have successfully regenerated. Recent research on A. rhizogenes-mediated transformation of woody plants has demonstrated its potential for various applications, including gene function analysis, gene expression profiling, gene interaction studies, and gene regulation analysis. The introduction of the Ri plasmid has resulted in the emergence of several Ri phenotypes, such as compact plant types, which can be exploited for Ri breeding purposes. This review paper presents recent advances in A. rhizogenes-mediated basic research and Ri breeding in woody plants. This study highlights various aspects of A. rhizogenes-mediated transformation, its multiple applications in gene function analysis, and the potential of Ri lines as valuable breeding materials.

Network Modeling of Apoptosis-Related Genes Reveal a High-Risk Cluster in Multiple Myeloma

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. Recent studies have shown the complexity of biological systems associated with poor outcomes in MM. One hallmark of cancer pathogenesis, applicable to MM, is the dysregulation of apoptotic cell death. Understanding the relationship between known drivers of MM and critical pathways in the apoptosis gene network is key towards identifying novel therapeutic targets. Recently, there has been a surge of interest in developing network-based approaches to study gene interactions and use machine learning tools to further elucidate useful biological factors. It is well-known that genes operate as network systems; however, interpretable computational methods are still limited. In this work, we combine a set of network analysis tools to provide novel biological insights into how the apoptosis network is dysregulated in MM. We identify a set of genes associated with poor outcomes in MM using both univariate and network-based approaches. Genomic and clinical data, including RNA-sequencing (RNA-seq) and copy number alteration (CNA), for 659 subjects were obtained from the Multiple Myeloma Research Foundation's CoMMpass (IA19) database. The apoptosis gene set is defined using the apoptosis hallmark pathway provided by the gene set enrichment analysis tool. The interactions between the given list of genes are provided via MetaCore. Univariate gene modeling is done using a Cox proportional hazards model. To determine the relationship between genes, we used Ollivier-Ricci curvature (ORC), a measure of network robustness. The ORC value between two genes incorporates information about both the two genes in question and their local neighborhoods, a concept critical for understanding the role a neighborhood of genes has on a given connection. Once edge information is computed, we used a uniform manifold approximation and projection (UMAP) to reduce the complexity of the dataset. The resulting projection is clustered using k-means clustering, and survival analysis of the given clusters is done using the Kaplan-Meier (KM) method. To understand which features are most informative, we used a random forest to predict the cluster labels using the RNA-seq data. After five-fold cross-validation, feature importance was computed using random forest's permutation importance methodology. All statistical significance testing was corrected for multiple comparisons via the Benjamini-Hochberg false discovery rate method with an alpha set to 0.05. Using RNA-seq data of genes associated with apoptosis, we identified nineteen apoptosis genes associated with poor prognosis in MM. Some of these genes, such as ANXA1 and WEE1 are known to have an effect in MM, while others, such as AVPR1A have yet to be studied extensively for their role in MM. When examining CNA data associated with apoptosis, a similar pattern emerged - nineteen genes were associated with poor prognosis. However, between the two key gene sets found by RNA-seq and CNA, only FAS appeared in both lists. FAS, Fas Cell Surface Death Receptor, is critical for triggering apoptosis. Half of the 37 genes identified using RNA-seq and CNA data are directly connected to the TP53 gene. While TP53 mutations are not a marker of the presence of MM itself, TP53 mutations have been shown to be associated with poorer outcomes. After reducing the complexity of the Ollivier-Ricci curvature analysis of the RNA-seq apoptosis network using UMAPs, the data revealed five clusters with KM curves for progression-free survival were significant (p<0.001). To identify the genes most impactful for separating these clusters, we trained a random forest model on the RNA-seq - note, it was the edge robustness values that were clustered - and evaluated its performance for predicted class membership. The model had an overall accuracy of approximately 78% with F1 scores for each class ranging from 61% to 87%. The top three features associated with the model include CTNNB1, RELA, and LEF1. Of note, CTNNB1 and RELA are directly interacted with the TP53 gene. Because these three genes discriminate between all five clusters, their expression levels may play a mediating effect on MM outcomes. Further investigation with external datasets is needed to validate these results.

Genome-wide identification of transcriptional enhancers during human placental development and association with function, differentiation, and disease†.

The placenta is a dynamic organ that must perform a remarkable variety of functions during its relatively short existence in order to support a developing fetus. These functions include nutrient delivery, gas exchange, waste removal, hormone production, and immune barrier protection. Proper placenta development and function are critical for healthy pregnancy outcomes, but the underlying genomic regulatory events that control this process remain largely unknown. We hypothesized that mapping sites of transcriptional enhancer activity and associated changes in gene expression across gestation in human placenta tissue would identify genomic loci and predicted transcription factor activity related to critical placenta functions. We used a suite of genomic assays [i.e., RNA-sequencing (RNA-seq), Precision run-on-sequencing (PRO-seq), and Chromatin immunoprecipitation-sequencing (ChIP-seq)] and computational pipelines to identify a set of >20000 enhancers that are active at various time points in gestation. Changes in the activity of these enhancers correlate with changes in gene expression. In addition, some of these enhancers encode risk for adverse pregnancy outcomes. We further show that integrating enhancer activity, transcription factor motif analysis, and transcription factor expression can identify distinct sets of transcription factors predicted to be more active either in early pregnancy or at term. Knockdown of selected identified transcription factors in a trophoblast stem cell culture model altered the expression of key placental marker genes. These observations provide a framework for future mechanistic studies of individual enhancer-transcription factor-target gene interactions and have the potential to inform genetic risk prediction for adverse pregnancy outcomes.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.

Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples.

Predictive modeling is useful but very challenging in biological image analysis due to the high cost of obtaining and labeling training data. For example, in the study of gene interaction and regulation in Drosophila embryogenesis, the analysis is most biologically meaningful when in situ hybridization (ISH) gene expression pattern images from the same developmental stage are compared. However, labeling training data with precise stages is very time-consuming even for developmental biologists. Thus, a critical challenge is how to build accurate computational models for precise developmental stage classification from limited training samples. In addition, identification and visualization of developmental landmarks are required to enable biologists to interpret prediction results and calibrate models. To address these challenges, we propose a deep two-step low-shot learning framework to accurately classify ISH images using limited training images. Specifically, to enable accurate model training on limited training samples, we formulate the task as a deep low-shot learning problem and develop a novel two-step learning approach, including data-level learning and feature-level learning. We use a deep residual network as our base model and achieve improved performance in the precise stage prediction task of ISH images. Furthermore, the deep model can be interpreted by computing saliency maps, which consists of pixel-wise contributions of an image to its prediction result. In our task, saliency maps are used to assist the identification and visualization of developmental landmarks. Our experimental results show that the proposed model can not only make accurate predictions but also yield biologically meaningful interpretations. We anticipate our methods to be easily generalizable to other biological image classification tasks with small training datasets. Our open-source code is available at https://github.com/divelab/lsl-fly.

Synteny Identifies Reliable Orthologs for Phylogenomics and Comparative Genomics of the Brassicaceae.

Large genomic data sets are becoming the new normal in phylogenetic research, but the identification of true orthologous genes and the exclusion of problematic paralogs is still challenging when applying commonly used sequencing methods such as target enrichment. Here, we compared conventional ortholog detection using OrthoFinder with ortholog detection through genomic synteny in a data set of 11 representative diploid Brassicaceae whole-genome sequences spanning the entire phylogenetic space. Then, we evaluated the resulting gene sets regarding gene number, functional annotation, and gene and species tree resolution. Finally, we used the syntenic gene sets for comparative genomics and ancestral genome analysis. The use of synteny resulted in considerably more orthologs and also allowed us to reliably identify paralogs. Surprisingly, we did not detect notable differences between species trees reconstructed from syntenic orthologs when compared with other gene sets, including the Angiosperms353 set and a Brassicaceae-specific target enrichment gene set. However, the synteny data set comprised a multitude of gene functions, strongly suggesting that this method of marker selection for phylogenomics is suitable for studies that value downstream gene function analysis, gene interaction, and network studies. Finally, we present the first ancestral genome reconstruction for the Core Brassicaceae which predating the Brassicaceae lineage diversification ∼25 million years ago.

Dopamine and oxytocin and their relevance for attachment: A gene x gene interaction study

An interaction between dopamine and oxytocin has been shown in several human and animal studies. Effects of oxytocin on dopaminergic activity depend on the location of dopaminergic neurons resulting in increased prosocial or decreased exploratory behavior. Both components are associated with attachment and the knowledge so far justifies investigating the interaction on a molecular genetic level with respect to adult attachment. A total number of N = 545 participants were genotyped for COMT rs4680 and OXTR rs53576. The Attachment-Style-Questionnaire (ASQ) was used to measure adult attachment. The interaction of COMT and OXTR yielded a significant result for the ASQ. The combination of the COMT-Met/Met and OXTR-AA genotype yielded significantly higher Need for Approval and Relationships as Secondary. The results confirm the interaction between dopamine and oxytocin for certain aspects of adult attachment as a “behavioral phenotype” and will be discussed with respect to a better understanding of the neurobiological underpinnings of attachment.

Development of a petal protoplast transfection system for Sinningia speciosa.

PremiseTransient gene expression systems are powerful tools for studying gene interactions in plant species without available or stable genetic transformation protocols. We optimized a petal protoplast transformation protocol for Sinningia speciosa, a model plant, to study the development of floral symmetry.Methods and ResultsA high yield of petal protoplasts was obtained using a 6‐h enzyme digestion in a solution of 1.5% cellulase and 0.4% macerozyme. Modest transfection efficiency (average 41.4%) was achieved. The viability of the transfected protoplasts remained at more than 90%. A fusion of green fluorescent protein and CYCLOIDEA (SsCYC), the Teosinte branched 1/Cincinnata/Proliferating cell factor transcription factor responsible for floral symmetry, was subcellularly localized inside the nuclei of the protoplasts. Transiently overexpressing SsCYC indicates the success of this system, which resulted in the predicted increased (but nonsignificant) expression of its known target RADIALIS (SsRAD1), consistent with gene network expectations.ConclusionsThe transient transfection system presented herein can be effectively used to study gene‐regulatory interactions in Gesneriaceae species.

Interaction between cigarette smoking and genetic polymorphisms on the associations with age of natural menopause and reproductive lifespan: the Singapore Chinese Health Study.

Are there genetic variants that interact with smoking to reduce reproductive lifespan in East-Asian women? Our study corroborates several recently identified genetic loci associated with reproductive lifespan and highlights specific genetic predispositions that may interact with smoking status to adversely affect reproductive lifespan in East-Asian women. Epidemiological data as well as evaluations on genetic predisposition to smoke indicate on the importance of smoking in adverse effects on reproductive lifespan in women. However, there are no previous smoking and gene interaction studies for reproductive traits in East-Asian women. This population-based prospective cohort study comprised 11643 East-Asian Chinese women with overlapping genome-wide genotyping and reproductive data. We performed a genome-wide association study for reproductive lifespan in women (n = 11643) from the Singapore Chinese Health Study (SCHS) and carried out a genome-wide interaction study to identify loci that interacted with smoking status to affect age of natural menopause and reproductive-time. Two known loci associated with menopause, rs113430717 (near HMCES, chromosome 3, Pmeta = 5.72 × 10-15) and rs3020136 (near RAD21, chromosome 8, Pmeta = 1.38 × 10-8) were observed beyond genome-wide levels of association with age at menopause in this study. For reproductive lifespan, the genome-wide association observed at rs79784106 (chromosome 3, Pmeta = 5.05 × 10-12) was in linkage disequilibrium with the menopause lead single-nucleotide polymorphism (SNP) (rs113430717). Four additional loci, first reported to be associated with menopause, were also associated with reproductive lifespan in our study (PAdj between 7.42 × 10-5 to 4.51 × 10-3). A significant interaction was observed between smoking and an East-Asian specific SNP, rs140146885, for reduced reproductive lifespan, per copy of the minor C allele (beta = -1.417 years, Pinteraction = 2.31 × 10-10). This interaction was successfully replicated in additional independent samples (beta = -1.389 years, Pinteraction = 6.78 × 10-3). Another known variant associated with menopause, rs11031006 (near FSHB), was also observed to interact with smoking status to reduce age at menopause in our dataset (beta = -0.450 years, Padj = 0.042). The modest sample size of the replication datasets used likely affected the statistical power to firmly replicate all identified novel loci observed in our smoking interaction analyses. Age of natural menopause and reproductive lifespan have clear genetic predispositions with distinct ethnic differences, and they may be adversely truncated by lifestyle factors such as smoking, which can pose a significant impact on the reproductive lifespan and future health outcomes in women. The Singapore Chinese Health Study is funded by the National Medical Research Council, Singapore (NMRC/CIRG/1456/2016), National Institutes of Health (R01 CA144034 and UM1 CA182876) and National Research Foundation, Singapore (Project Number 370062002). W.-P.K. is supported by the National Medical Research Council, Singapore (MOH-CSASI19nov-0001). The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors do not report conflicts of interest. N/A.

Genetic Appraisal of Wheat Progenies for Grain Yield and Yield Attributing Traits

The present investigation was carried out in F3 and F4 progenies of wheat to study gene interactions and its attributing traits during the Rabi season of 2014-15 and 2015-16. The crop was grown in research area of Wheat and Barley Section, Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar. Most of the traits were studied positively skewed and were being governed by several genes indicating quantitative inheritance. Skewness and kurtosis indicated dominance based complementary gene interaction involving large number of genes having decreasing effect in the inheritance of plant height, spike length, number of grains per spike, 1000 grain weight and biological yield per plant in both the progenies However, duplicate interaction was observed for grain length, number of spikelets per spike, grain yield per plant and harvest index in both the progenies, hence, genetic gain will be rapid under mild selection. Grain yield per plant and associated traits showed platykurtic distribution indicated the involvement of few genes in inheritance of these traits. This indicates that selection could be practiced for these component traits to increase grain yield per plant. Hence, as a concluding remark based on measures of shape in both F3 and F4, progenies directional selection will effectively enhance the performance of these yield attributing traits.

Interaction Effects of DRD2 Genetic Polymorphism and Interpersonal Stress on Problematic Gaming in College Students.

Problematic gaming has become a public concern, influenced both by genetic factors and stressful environments. Studies have reported the effects of dopamine-related genes and interpersonal stressors on problematic gaming, but gene and environment interaction (G × E) studies have not been conducted. In this study, we investigated the interaction effects of dopamine receptor D2 (DRD2) polymorphisms and interpersonal stress on problematic gaming and the mediating effect of avoidant coping to reveal the mechanism of the G × E process. We recruited 168 college students (mean age = 22; male 63.1%) and genotyped their DRD2 C957T (rs6277) and Taq1 (rs1800497) polymorphisms. The results of the mediated moderation analysis showed that, when experiencing interpersonal stressors, individuals with both the C957T T allele and the Taq1 A1 allele showed more elevated problematic gaming scores than non-carriers. Moreover, the interaction effect of the combined DRD2 polymorphisms and interpersonal stress was significantly mediated by avoidant coping. These findings suggest that the influence of interpersonal stress on problematic gaming can be changed as a function of DRD2 genotypes, which may be because of the avoidant coping styles of C957T T allele and Taq1 A1 allele carriers in response to stress.

DNA binding and cleavage, BRCA1 gene interaction, antiglycation and anticancer studies of transition metal complexes of sulfonamides.

A series of 4-((4-methylphenylsulfonamido)methyl)cyclohexanecarboxylic acid (NaMSCCA) transition metal complexes [Cu(II), Zn(II), Ni(II), Mn(II), and Co(II)] have been synthesized by precipitation method. The characterization was done by physical techniques, FT-IR spectroscopy, mass spectrometry, and NMR spectroscopy. The molecular structures of nickel (II) AZ-3 and cobalt (II) AZ-5 complexes were determined by the X-ray diffraction technique and found to crystallize in the triclinic space group P-1. The coordination geometry around the central nickel (AZ-3) and cobalt (AZ-5) atoms was square planar bipyramidal. Molecular docking was performed with duplex DNA of sequence d(CGCGAATTCGCG)2 DNA to determine the probable binding mode of compounds. Then these synthesized compounds were used to perform DNA cleavage activity through the agarose gel electrophoresis method. Among the compounds, compounds AZ-1 and AZ-2 exhibited good nuclease activity. The DNA sequence of breast-cancer suppressor gene 1 (BRCA1) was amplified through PCR and interaction studies of compounds AZ-1 and AZ-2 were performed through gel electrophoresis and fluorescence emission spectroscopy. The expression analysis of the BRCA1 gene was also performed to quantify the expression relative fold change (2^-(∆∆CT)) after treatment with compounds. All synthesized compounds were evaluated for their antioxidant and antiglycation activities and AZ-2 exhibited excellent results. The molecular docking study of these compounds was performed against the protein structure of advanced glycation end products to support the experimental results. Anticancer activity of compounds was performed through MTT assay. Copper and zinc complexes depicted the highest anticancer activity against human breast adenocarcinoma (MCF7) and human corneal epithelial cell (HCEC) cell lines.

Genetic Interaction between Mfrp and Adipor1 Mutations Affect Retinal Disease Phenotypes.

Adipor1tm1Dgen and Mfrprd6 mutant mice share similar eye disease characteristics. Previously, studies established a functional relationship of ADIPOR1 and MFRP proteins in maintaining retinal lipidome homeostasis and visual function. However, the independent and/or interactive contribution of both genes to similar disease phenotypes, including fundus spots, decreased axial length, and photoreceptor degeneration has yet to be examined. We performed a gene-interaction study where homozygous Adipor1tm1Dgen and Mfrprd6 mice were bred together and the resulting doubly heterozygous F1 offspring were intercrossed to produce 210 F2 progeny. Four-month-old mice from all nine genotypic combinations obtained in the F2 generation were assessed for white spots by fundus photo documentation, for axial length by caliper measurements, and for photoreceptor degeneration by histology. Two-way factorial ANOVA was performed to study individual as well as gene interaction effects on each phenotype. Here, we report the first observation of reduced axial length in Adipor1tmlDgen homozygotes. We show that while Adipor1 and Mfrp interact to affect spotting and degeneration, they act independently to control axial length, highlighting the complex functional association between these two genes. Further examination of the molecular basis of this interaction may help in uncovering mechanisms by which these genes perturb ocular homeostasis.

3029 – COMBINATORIAL GENE TARGETING IN PRIMARY HUMAN HEMATOPOIETIC STEM AND PROGENITOR CELLS

The CRISPR/Cas9 system offers enormous versatility for functional genomics. However, many applications, such as combinatorial perturbations for disease modelling and studies of gene interactions, have proven to be challenging in primary human cells compared to cell lines or mouse cells. Here, we addressed the challenge of multiplexed gene perturbations in primary human cord blood-derived hematopoietic stem and progenitor cells (HSPCs) by co-delivering lentiviral sgRNA vectors expressing either Enhanced Green Fluorescent Protein (EGFP) or Kusabira Orange (KuO), together with Cas9 mRNA, to simultaneously edit two genetic loci. The use of fluorescent markers allows for tracing of single- or double-edited cells and we achieved robust double knockout of the cell surface markers CD45 and CD44 with an efficiency of around 70%. As a functional proof of concept, we demonstrated the use of this system to study gene dependencies for cell survival by simultaneously targeting the cohesin genes STAG1 and STAG2, as a model of synthetic lethality. Furthermore, we showed that this system can be used to study cooperative genetic events, and found a combinatorial effect with potential synergy for HSPC expansion when targeting the Aryl Hydrocarbon Receptor (AHR) in combination with members of the epigenetic modifier CoREST. Taken together, we established a paradigm for multiplexed CRISPR/Cas9 editing in primary human HSPCs, which enables studies of genetic dependencies and cooperation. This traceable multiplexed system has important implications for modelling polygenic diseases and for investigating gene interactions. The CRISPR/Cas9 system offers enormous versatility for functional genomics. However, many applications, such as combinatorial perturbations for disease modelling and studies of gene interactions, have proven to be challenging in primary human cells compared to cell lines or mouse cells. Here, we addressed the challenge of multiplexed gene perturbations in primary human cord blood-derived hematopoietic stem and progenitor cells (HSPCs) by co-delivering lentiviral sgRNA vectors expressing either Enhanced Green Fluorescent Protein (EGFP) or Kusabira Orange (KuO), together with Cas9 mRNA, to simultaneously edit two genetic loci. The use of fluorescent markers allows for tracing of single- or double-edited cells and we achieved robust double knockout of the cell surface markers CD45 and CD44 with an efficiency of around 70%. As a functional proof of concept, we demonstrated the use of this system to study gene dependencies for cell survival by simultaneously targeting the cohesin genes STAG1 and STAG2, as a model of synthetic lethality. Furthermore, we showed that this system can be used to study cooperative genetic events, and found a combinatorial effect with potential synergy for HSPC expansion when targeting the Aryl Hydrocarbon Receptor (AHR) in combination with members of the epigenetic modifier CoREST. Taken together, we established a paradigm for multiplexed CRISPR/Cas9 editing in primary human HSPCs, which enables studies of genetic dependencies and cooperation. This traceable multiplexed system has important implications for modelling polygenic diseases and for investigating gene interactions.

Assessment the effect of vitamin D supplementation on plasma vitamin D levels, inflammation, and oxidative stress biomarkers based on vitamin D receptor genetic variation in breast cancer survivors: a protocol for clinical trial

BackgroundBoth human genes and environmental exposures, due to complex interplay, play important role in the cancer etiology. Vitamin D is associated with a reduced risk of incidence and mortality of several human cancers. This study will aim to investigate the possible effects of individual polymorphisms in vitamin D receptor (VDR) as well as effects of VDR haplotypes on response to vitamin D supplementation in breast cancer survivors.MethodsThis is an interventional study in which the effects of vitamin D supplementation on plasma vitamin D levels, inflammatory and antioxidant biomarkers and factors associated with cell proliferation, differentiation, damage, and apoptosis will be investigated stratified by variations in VDR genotype. The present study will be conducted on breast cancer survivors referred to the Shohadaye Tajrish hospital and its associated clinics. One hundred ninety-eight breast cancer survivors will receive 4000 IU of vitamin D3 daily for 12 weeks. VDR Fok1, ApaI, TaqI, BsmI, and Cdx-2 genotype will be determined at the end of the study and responses to vitamin D supplements (inflammatory, antioxidant, cell proliferation, differentiation, damage, and apoptosis biomarkers) will be compared between the three subgroups of each VDR polymorphism as well as different VDR haplotype categories.DiscussionGenetic variation is a fundamental factor influencing individuals’ divergent responses to diet, nutritional status, metabolic response, and diet-related health disorders. Furthermore, studies of gene and environment interactions will provide a precise and accurate assessments of individuals’ dietary requirements by considering both the genetic and environmental aspects simultaneously. The results of the current study, to some extent, will highlight the discrepancies existing in the findings of different studies regarding vitamin D, VDR, and cancer by considering both the genetic and environmental aspects simultaneously. If responses to vitamin D supplementation could be modified by VDR SNPs, determining the distribution of VDR polymorphisms in both breast cancer survivors and healthy populations will provide a new insight into the vitamin D requirements of individuals to prevent cancer and its related mortality based on their genotypes.Trial registration This trial has been registered on Iranian Registry of Clinical Trials (IRCT) under the identification code: IRCT2017091736244N1, registration date: 2017-11-10, http://www.irct.ir/trial/27153

Newly synthesized metal complexes of sulfonamides: DNA cleavage, BRCA1 gene interaction, expression analysis, antioxidant and antiglycation studies

Newly synthesized metal complexes of sulfonamides: DNA cleavage, BRCA1 gene interaction, expression analysis, antioxidant and antiglycation studies