In silico analysis of promoter regions and regulatory elements (motifs and CpG islands) of the genes encoding for alcohol production in Saccharomyces cerevisiaea S288C and Schizosaccharomyces pombe 972h

PM2.5, component cause of severe metabolically abnormal obesity: An in silico, observational and analytical study

Obesity is currently one of the most alarming pathological conditions due to the progressive increase in its prevalence. In the last decade, it has been associated with fine particulate matter suspended in the air (PM2.5). The purpose of this study was to explore the mechanistic interaction of PM2.5 with a high-fat diet (HFD) through the differential regulation of transcriptional signatures, aiming to identify the association of these particles with metabolically abnormal obesity. The research design was observational, using bioinformatic methods and an explanatory approach based on Rothman's causal model. We propose three new transcriptional signatures in murine adipose tissue. The sum of transcriptional differences between the group exposed to an HFD and PM2.5, compared to the control group, were 0.851, 0.265, and -0.047 (p > 0.05). The HFD group increased body mass by 20% with two positive biomarkers of metabolic impact. The group exposed to PM2.5 maintained a similar weight to the control group but exhibited three positive biomarkers. Enriched biological pathways (p < 0.05) included PPAR signaling, small molecule transport, adipogenesis genes, cytokine-cytokine receptor interaction, and HIF-1 signaling. Transcriptional regulation predictions revealed CpG islands and common transcription factors. We propose three new transcriptional signatures: FAT-PM2.5-CEJUS, FAT-PM2.5-UP, and FAT-PM2.5-DN, whose transcriptional regulation profile in adipocytes was statistically similar by dietary intake and HFD and exposure to PM2.5 in mice; suggesting a mechanistic interaction between both factors. However, HFD-exposed murines developed moderate metabolically abnormal obesity, and PM2.5-exposed murines developed severe abnormal metabolism without obesity. Therefore, in Rothman's terms, it is concluded that HFD is a sufficient cause of the development of obesity, and PM2.5 is a component cause of severe abnormal metabolism of obesity. These signatures would be integrated into a systemic biological process that would induce transcriptional regulation in trans, activating obesogenic biological pathways, restricting lipid mobilization pathways, decreasing adaptive thermogenesis and angiogenesis, and altering vascular tone thus inducing a severe metabolically abnormal obesity.

Genomic Effect of DNA Methylation on Gene Expression in Colorectal Cancer

Simple Summary

Abnormal DNA methylation is known to regulate gene expression, and its features have been frequently observed in colorectal cancer (CRC) patients. In addition, alterations in DNA methylation can be proposed as biomarkers for cancer prognosis, as they occur in the early stage of carcinogenesis. Although numerous studies have attempted to shed light on the impacts of DNA methylation on gene expression, it is still unclear which specific regions regulate gene expression and how they are associated with patient survival. In this study, we elucidated the intricate relationship between DNA methylation and gene expression. Furthermore, we found genes that were influenced by DNA methylation and were associated with survival; these genes were mainly enriched in immune-related pathways.

Abstract

The aberrant expression of cancer-related genes can lead to colorectal cancer (CRC) carcinogenesis, and DNA methylation is one of the causes of abnormal expression. Although many studies have been conducted to reveal how DNA methylation affects transcription regulation, the ways in which it modulates gene expression and the regions that significantly affect DNA methylation-mediated gene regulation remain unclear. In this study, we investigated how DNA methylation in specific genomic areas can influence gene expression. Several regression models were constructed for gene expression prediction based on DNA methylation. Among these models, ElasticNet, which had the best performance, was chosen for further analysis. DNA methylation near transcription start sites (TSS), especially from 2 kb upstream to 7 kb downstream of TSS, had an essential regulatory role in gene expression. Moreover, methylation-affected and survival-associated genes were compiled and found to be mainly enriched in immune-related pathways. This study investigated genomic regions in which methylation changes can affect gene expression. In addition, this study proposed that aberrantly expressed genes due to DNA methylation can lead to CRC pathogenesis by the immune system.

In Silico Study of Mercury Resistance Genes Extracted from Pseudomonas spp. Involved in Bioremediation: Understanding the Promoter Regions and Regulatory Elements

Microbial genes and their product were diverse and beneficial for heavy metal bioremediation from the contaminated sites. Screening of genes and gene products plays a significant role in the detoxification of pollutants. Understanding of the promoter region and its regulatory elements is a vital implication of microbial genes. To the best of our knowledge, there is no in silico study reported so far on mer gene families used for heavy metal bioremediation. The motif distribution was observed densely upstream of the TSSs (transcription start sites) between +1 and -350 bp and sparsely distributed above -350 bp, according to the current study. MEME identified the best common candidate motifs of TFs (transcription factors) binding with the lowest e value (7.2 $e$ -033) and is the most statistically significant candidate motif. The EXPREG output of the 11 TFs with varying degrees of function such as activation, repression, transcription, and dual purposes was thoroughly examined. Data revealed that transcriptional gene regulation in terms of activation and repression was observed at 36.4% and 54.56%, respectively. This shows that most TFs are involved in transcription gene repression rather than activation. Likewise, EXPREG output revealed that transcriptional conformational modes, such as monomers, dimers, tetramers, and other factors, were also analyzed. The data indicated that most of the transcriptional conformation mode was dual, which accounts for 96%. CpG island analysis using online and offline tools revealed that the gene body had fewer CpG islands compared to the promoter regions. Understanding the common candidate motifs, transcriptional factors, and regulatory elements of the mer operon gene cluster using a machine learning approach could help us better understand gene expression patterns in heavy metal bioremediation.

Phylogenetic analysis of phytochrome A gene from Lablab purpureus (L.) Sweet

BACKGROUND

Phytochromes are the best characterized photoreceptors that perceive Red (R)/Far-Red (FR) signals and mediate key developmental responses in plants. It is well established that photoperiodic control of flowering is regulated by PHY A (phytochrome A) gene. So far, the members of PHY A gene family remains unexplored in Lablab purpureus, and therefore, their functions are still not deciphered. PHYA3 is the homologue of phytochrome A and known to be involved in dominant suppression of flowering under long day conditions by downregulating florigens in Glycine max. The present study is the first effort to identify and characterize any photoreceptor gene (PHYA3, in this study) in Lablab purpureus and decipher its phylogeny with related legumes.

RESULTS

PHYA3 was amplified in Lablab purpureus cv GNIB-21 (photo-insensitive and determinate) by utilizing primers designed from GmPHYA3 locus of Glycine max. This study was successful in partially characterizing PHYA3 in Lablab purpureus (LprPHYA3) which is 2 kb longer and belongs to exon 1 region of PHYA3 gene. Phylogenetic analysis of the nucleotide and protein sequences of PHYA genes through MEGA X delineated the conservation and evolution of Lablab purpureus PHYA3 (LprPHYA3) probably from PHYA genes of Vigna unguiculata, Glycine max and Vigna angularis. A conserved basic helix-loop-helix motif bHLH69 was predicted having DNA binding property. Domain analysis of GmPHYA protein and predicted partial protein sequence corresponding to exon-1 of LprPHYA3 revealed the presence of conserved domains (GAF and PAS domains) in Lablab purpureus similar to Glycine max.

CONCLUSION

Partial characterization of LprPHYA3 would facilitate the identification of complete gene in Lablab purpureus utilizing sequence information from phylogenetically related species of Fabaceae. This would allow screening of allelic variants for LprPHYA3 locus and their role in photoperiod responsive flowering. The present study could aid in modulating photoperiod responsive flowering in Lablab purpureus and other related legumes in near future through genome editing.

In silico analysis of promoter region and regulatory elements of glucan endo-1,3-beta-glucosidase encoding genes in Solanum tuberosum: cultivar DM 1-3 516 R44

Background

Potato (Solanum tuberosum L.) is one of the most important food crops in the world. Pathogens remain as one of the major constraints limiting potato productivity. Thus, understanding of gene regulation mechanism of pathogenesis-related genes such as glucan endo-1,3-beta-glucosidase is a foundation for genetic engineering of potato for disease resistance and reduces the use of fungicides. In the present study, 19 genes were selected and attempts were made through in silico methods to identify and characterize the promoter regions, regulatory elements, and CpG islands of glucan endo-1,3-beta-glucosidase gene in Solanum tuberosum cultivar DM 1-3 516 R44.

Results

The current analysis revealed that single transcription start sites (TSSs) were present in 12/19 (63.2%) of promoter regions analyzed. The predictive score at a cutoff value of 0.8 for the majority (84.2%) of the promoter regions ranged from 0.90 to 1.00. The locations for 42% of the TSSs were below −500 bp relative to the start codon (ATG). MβGII was identified as the common promoter motif for 94.4% of the genes with an E value of 3.5e−001. The CpG analysis showed low CpG density in the promoter regions of most of the genes except for gene ID102593331 and ID: 102595860. The number of SSRs per gene ranged from 2 to 9 with repeat lengths of 2 to 6 bp. Evolutionary distances ranged from 0.685 to 0.770 (mean = 0.73), demonstrating narrower genetic diversity range. Phylogeny was inferred using the UPGMA method, and gene sequences from different species were found to be clustered together.

Conclusion

In silico identified regulatory elements in promoter regions will contribute to our understanding of the regulatory mechanism of glucan endo-1,3-beta-glucosidase genes and provide a promising target for genetic engineering to improve disease resistance in potatoes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-021-00240-0.