In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes.

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

In Silico Functional and Structural Analysis of Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) in Human Paired Box 4 Gene.

In human genome, members of Paired box (PAX) transcription factor family are highly sequence-specific DNA-binding proteins. Among PAX gene family members, PAX4 gene has significant role in growth, proliferation, differentiation, and insulin secretion of pancreatic ß-cells. Single nucleotide polymorphisms (SNPs) in PAX4 gene progress in the pathogenesis of various human diseases. Hence, the molecular mechanism of how these SNPs in PAX4 gene significantly progress diseases pathogenesis needs to be elucidated. For the reason, a series of bioinformatic analyzes were done to identify the SNPs of PAX4 gene that contribute in diseases pathogenesis. From the analyzes, 4145 SNPs (rsIDs) in PAX4 gene were obtained, where, 362 missense (8.73%), 169 synonymous (4.08%), and 2323 intron variants (56.04%). The rest SNPs were unspecified. Among the 362 missense variants, 118 nsSNPs were found as deleterious in SIFT analysis. Among those, 25 nsSNPs were most probably damaging and 23 were deleterious as observed in PolyPhen-2 and PROVEAN analyzes, respectively. Following all analyzes, 14 nsSNPs (rs149708455, rs115887120, rs147279315, rs35155575, rs370095957, rs373939873, rs145468905, rs121917718, rs2233580, rs3824004, rs372751660, rs369459316, rs375472849, rs372497946) were common and observed as deleterious, probably damaging, affective and diseases associated. Following structural analyzes, 11 nsSNPs guided proteins were found as most unstable and highly conserved. Among these, R20W, R39Q, R45Q, R60H, G65D, and A223D mutated proteins were highly harmful. Hence, the results from above-mentioned integrated comprehensive bioinformatic analyzes guide how different nsSNPs in PAX4 gene alter structural and functional characteristics of the protein that might progress diseases pathogenesis in human including type 2 diabetes.

Phylogenetic analysis and characterization of arsenic (As) transforming bacterial marker proteins following isolation of As-tolerant indigenous bacteria.

Marker proteins play a significant role in bacterial arsenic (As) transformation. Phylogenetic analysis and three-dimensional (3D) characteristics of As transforming bacterial marker proteins guide the evolutionary origin and As transforming potential of the species. Indeed, As-tolerant bacteria also show a significant level of As transformation. Hence, characterization of As transforming bacterial marker proteins, isolation of As transforming bacteria, and proper integration of the findings may guide to elucidate how bacteria transform As. Therefore, phylogenetic analysis and 3D characterization of As transforming bacterial marker protein following isolation of potential indigenous As-tolerant indigenous bacteria were done to explore the mechanism of bacterial As transformation. Phylogenetic analysis of ten As transforming marker proteins (arsA, arsB, arsC, arsD, arsR, aioA, arrA, aioB, acr1, and acr3) in 20 potential bacterial genomes (except 19 for the acr3) were studied. Some bacterial genomes featured up to five marker proteins, and therefore, 3D characteristics of the marker proteins were analyzed in those genomes having three-to-five marker proteins. In phylogeny, species in close clades represent their phylogenetic resemblances and may have similar functions. P. aeruginosa, E. coli, and K. pneumonia were found to be more effective due to having the highest number (five) of marker proteins. In 3D protein modeling, most of the marker proteins were found to be active. Among 19 indigenous bacterial isolates, multiple isolates showed tolerance up to 50 mM As(III) and 250 mM As(V), which may potentially transform a significant quantities of As. Hence, integration of the results of phylogenetic analysis, 3D protein characteristics, and As tolerance in the bacterial isolates could guide to explore the mechanism of how bacteria transform As at cellular and molecular levels.

In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population.

Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease's pathophysiology.

Genome-Wide Identification and Functional Analysis of Lysine Histidine Transporter (LHT) Gene Families in Maize.

Amino acid transporters (AATs) are essential membrane proteins that transfer amino acids across cells. They are necessary for plant growth and development. The lysine histidine transporter (LHT) gene family in maize (Zea mays) has not yet been characterized. According to sequence composition and phylogenetic placement, this study found 15 LHT genes in the maize genome. The ZmLHT genes are scattered across the plasma membrane. The study also analyzed the evolutionary relationships, gene structures, conserved motifs, 3D protein structure, a transmembrane domain, and gene expression of the 15 LHT genes in maize. Comprehensive analyses of ZmLHT gene expression profiles revealed distinct expression patterns in maize LHT genes in various tissues. This study's extensive data will serve as a foundation for future ZmLHT gene family research. This study might make easier to understand how LHT genes work in maize and other crops.