Conceptualization of functional single nucleotide polymorphisms of polycystic ovarian syndrome genes: an in silico approach.

PURPOSE: Polycystic ovarian syndrome (PCOS) is a multi-faceted endocrinopathy frequently observed in reproductive-aged females, causing infertility. Cumulative evidence revealed that genetic and epigenetic variations, along with environmental factors, were linked with PCOS. Deciphering the molecular pathways of PCOS is quite complicated due to the availability of limited molecular information. Hence, to explore the influence of genetic variations in PCOS, we mapped the GWAS genes and performed a computational analysis to identify the SNPs and their impact on the coding and non-coding sequences. METHODS: The causative genes of PCOS were searched using the GWAS catalog, and pathway analysis was performed using ClueGO. SNPs were extracted using an Ensembl genome browser, and missense variants were shortlisted. Further, the native and mutant forms of the deleterious SNPs were modeled using I-TASSER, Swiss-PdbViewer, and PyMOL. MirSNP, PolymiRTS, miRNASNP3, and SNP2TFBS, SNPInspector databases were used to find SNPs in the miRNA binding site and transcription factor binding site (TFBS), respectively. EnhancerDB and HaploReg were used to characterize enhancer SNPs. Linkage Disequilibrium (LD) analysis was performed using LDlink. RESULTS: 25 PCOS genes showed interaction with 18 pathways. 7 SNPs were predicted to be deleterious using different pathogenicity predictions. 4 SNPs were found in the miRNA target site, TFBS, and enhancer sites and were in LD with reported PCOS GWAS SNPs. CONCLUSION: Computational analysis of SNPs residing in PCOS genes may provide insight into complex molecular interactions among genes involved in PCOS pathophysiology. It may also aid in determining the causal variants and consequently contributing to predicting disease strategies.

Ecogenetics of lead toxicity and its influence on risk assessment.

Lead (Pb) toxicity is a public health problem affecting millions worldwide. Advances in 'omic' technology have paved the way to toxico-genomics which is currently revolutionizing the understanding of interindividual variations in susceptibility to Pb toxicity and its functional consequences to exposure. Our objective was to identify, comprehensively analyze, and curate all the potential genetic and epigenetic biomarkers studied to date in relation to Pb toxicity and its association with diseases. We screened a volume of research articles that focused on Pb toxicity and its association with genetic and epigenetic signatures in the perspective of occupational and environmental Pb exposure. Due to wide variations in population size, ethnicity, age-groups, and source of exposure in different studies, researchers continue to be skeptical on the topic of the influence of genetic variations in Pb toxicity. However, surface knowledge of the underlying genetic factors will aid in elucidating the mechanism of action of Pb. Moreover, in recent years, the application of epigenetics in Pb toxicity has become a promising area in toxicology to understand the influence of epigenetic mechanisms such as DNA methylation, chromatin remodeling, and small RNAs for the regulation of genes in response to Pb exposure during early life. Growing evidences of ecogenetic understanding (both genetic and epigenetic processes) in a dose-dependent manner may help uncover the mechanism of action of Pb and in the identification of susceptible groups. Such studies will further help in refining uncertainty factors and in addressing risk assessment of Pb poisoning.

Atomic pair distribution functions analysis of disordered low-Z materials.

Results of high-energy X-ray diffraction experiments coupled to atomic pair distribution function analysis of disordered low-Z materials are presented. Several scientifically and technologically important classes of disordered low-Z materials such as small and large organic molecules, graphitic powders, polymers and liquids are intentionally explored to certify the technique's performance. Results clearly show that disordered low-Z materials can be well characterized in terms of material's phase identity, relative abundance in mixtures and atomic-scale structure. The demonstrated efficiency of the technique provides the scientific community with much needed confidence to apply it more often than now.