Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: A multi-cancer approach

Molecular Mechanisms and the Significance of Synonymous Mutations

Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

WGS Data Collections: How Do Genomic Databases Transform Medicine?

As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and may play an important regulatory function. The first WGS-based datasets have already been released including underrepresented populations. Although many databases contain pooled data from several cohorts, recently the importance of local databases has been highlighted. Genomic databases are not only collecting data but may also contribute to better diagnostics and therapies. They may find applications in population studies, rare diseases, oncology, pharmacogenetics, and infectious and inflammatory diseases. Further data may be analysed with Al technologies and in the context of other omics data. To exemplify their utility, we put a highlight on the Polish genome database and its practical application.

In silico identification of single nucleotide variations at CpG sites regulating CpG island existence and size

Genetic and epigenetic modifications of genes involved in the key regulatory pathways play a significant role in the pathophysiology and progression of multifactorial diseases. The present study is an attempt to identify single nucleotide variations (SNVs) at CpG sites of promoters of ACAT1, APOB, APOE, CYBA, FAS, FLT1, KSR2, LDLR, MMP9, PCSK9, PHOX2A, REST, SH2B3, SORT1 and TIMP1 genes influencing CpG island (CGI) existence and size associated with the pathophysiology of Diabetes mellitus, Coronary artery disease and Cancers. Promoter sequences located between -2000 to + 2000 bp were retrieved from the EPDnew database and predicted the CpG island using MethPrimer. Further, SNVs at CpG sites were accessed from NCBI, Ensembl while transcription factor (TF) binding sites were accessed using AliBaba2.1. CGI existence and size were determined for each SNV at CpG site with respect to wild type and variant allele by MethPrimer. A total of 200 SNVs at CpG sites were analyzed from the promoters of ACAT1, APOB, APOE, CYBA, FAS, FLT1, KSR2, LDLR, MMP9, PCSK9, PHOX2A, REST, SH2B3, SORT1 and TIMP1 genes. Of these, only 17 (8.5%) SNVs were found to influence the loss of CGI while 70 (35%) SNVs were found to reduce the size of CGI. It has also been found that 59% (10) of CGI abolishing SNVs are showing differences in binding of TFs. The findings of the study suggest that the candidate SNVs at CpG sites regulating CGI existence and size might influence the DNA methylation status and expression of genes involved in molecular pathways associated with several diseases. The insights of the present study may pave the way for new experimental studies to undertake challenges in DNA methylation, gene expression and protein assays.

LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients

The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.

Global DNA methylation in placental tissues from pregnant with preeclampsia: A systematic review and pathway analysis

Pre-eclampsia (PE) is the major cause of fetal and maternal mortality and can be classified according to gestational age of onset into early-onset (EOPE, <34 weeks of gestation) and late- (LOPE, ≥34 weeks of gestation). DNA methylation (DNAm) may help to understand the abnormal placentation in PE. Therefore, we performed a systematic review to assess the role of global DNAm on pathophysiology of PE, focused on fetal and maternal tissues of placenta from pregnant with PE, including EOPE and LOPE. We searched the databases EMBASE, Medline/PubMed, Cochrane Central Register of Controlled Trials, Scopus, Lilacs, Scielo and Google Scholar, and followed the MOOSE guidelines. Moreover, we performed pathway analysis with the overlapping genes from the included studies. Twelve out of 24 included studies in the qualitative analysis considered the classification into EOPE and LOPE. We did not found heterogeneity in the criteria used for diagnosis of PE, and a few studies evaluated whether confounding factors would influence placental DNAm. Fourteen out of 24 included studies showed hypomethylation in placental tissue from pregnant with PE compared to controls. The differences in DNAm are specific to genes or differentially methylated regions, and more evident in EOPE and preterm PE compared to controls, rather than LOPE and term PE. The overlapping genes from included studies revealed pathways relevant to pathophysiology of PE. Our findings highlighted the heterogeneous results of the included studies, mainly focused on North America and China. Replication studies in different populations should use the same placental tissues, techniques to assess DNAm and pipelines for bioinformatic analysis.

Identification Six Metabolic Genes as Potential Biomarkers for Lung Adenocarcinoma

Metabolic genes have been reported to act as crucial roles in tumor progression. Lung adenocarcinoma (LUAD) is one of the most common cancers worldwide. This study aimed to predict the potential mechanism and novel markers of metabolic signature in LUAD. The gene expression profiles and the clinical parameters were obtained from The Cancer Genome Atlas-Lung adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus data set (GSE72094). A total of 105 differentially expressed metabolic genes of intersect expression in TCGA-LUAD and GSE72094 were screened by R language. Univariate Cox regression model found 18 survival-related genes and then the least absolute shrinkage and selection operator model was successfully constructed. Six significant genes prognostic model was validated though independent prognosis analysis. The model revealed high values for prognostic biomarkers by time-dependent receiver operating characteristic (ROC) analysis, risk score, Heatmap, and nomogram. In addition, Gene Set Enrichment Analysis showed that multiplex metabolism pathways correlated with LUAD. Furthermore, we found the six genes aberrantly expressed in LUAD samples. Our study showed that metabolism pathways play important roles in LUAD progression. The six metabolic genes could predict potential prognostic and diagnostic biomarkers in LUAD.

Familial analysis reveals rare risk variants for migraine in regulatory regions

The most recent genome-wide association study of migraine increased the total number of known migraine risk loci to 38. Still, most of the heritability of migraine remains unexplained, and it has been suggested that rare gene dysregulatory variants play an important role in migraine etiology. Addressing the missing heritability of migraine, we aim to fine-map signals from the known migraine risk loci to regulatory mechanisms and associate these to downstream genic targets. We analyzed a large cohort of whole-genome sequenced patients from extended migraine pedigrees (1040 individuals from 155 families). We test for association between rare variants segregating in regulatory regions with migraine. The findings were replicated in an independent case-control cohort (2027 migraineurs, 1650 controls). We report an increased burden of rare variants in one CpG island and three polycomb group response elements near four migraine risk loci. We found that the association is independent of the common risk variants in the loci. The regulatory regions are suggested to affect different genes than those originally tagged by the index SNPs of the migraine loci. Families with familial clustering of migraine have an increased burden of rare variants in regulatory regions near known migraine risk loci, with effects that are independent of the variants in the loci. The possible regulatory targets suggest different genes than those originally tagged by the index SNPs of the migraine loci.