Regulatory SNPs and their widespread effects on the transcriptome

Allelic effects on KLHL17 expression underlie a pancreatic cancer genome-wide association signal at chr1p36.33

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the U.S. Both rare and common germline variants contribute to PDAC risk. Here, we fine-map and functionally characterize a common PDAC risk signal at chr1p36.33 (tagged by rs13303010) identified through a genome wide association study (GWAS). One of the fine-mapped SNPs, rs13303160 (OR = 1.23 (95% CI 1.15-1.32), P-value = 2.74×10-9, LD r2 = 0.93 with rs13303010 in 1000 G EUR samples) demonstrated allele-preferential gene regulatory activity in vitro and binding of JunB and JunD in vitro and in vivo. Expression Quantitative Trait Locus (eQTL) analysis identified KLHL17 as a likely target gene underlying the signal. Proteomic analysis identified KLHL17 as a member of the Cullin-E3 ubiquitin ligase complex with vimentin and nestin as candidate substrates for degradation in PDAC-derived cells. In silico differential gene expression analysis of high and low KLHL17 expressing GTEx pancreas samples suggested an association between lower KLHL17 levels (risk associated) and pro-inflammatory pathways. We hypothesize that KLHL17 may mitigate cell injury and inflammation by recruiting nestin and vimentin for ubiquitination and degradation thereby influencing PDAC risk.

Allelic effects on KLHL17 expression likely mediated by JunB/D underlie a PDAC GWAS signal at chr1p36.33

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the U.S. Both rare and common germline variants contribute to PDAC risk. Here, we fine-map and functionally characterize a common PDAC risk signal at 1p36.33 (tagged by rs13303010) identified through a genome wide association study (GWAS). One of the fine-mapped SNPs, rs13303160 (r2=0.93 in 1000G EUR samples, OR=1.23, P value=2.74x10-9) demonstrated allele-preferential gene regulatory activity in vitro and allele-preferential binding of JunB and JunD in vitro and in vivo. Expression Quantitative Trait Locus (eQTL) analysis identified KLHL17 as a likely target gene underlying the signal. Proteomic analysis identified KLHL17 as a member of the Cullin-E3 ubiquitin ligase complex in PDAC-derived cells. In silico differential gene expression analysis of the GTExv8 pancreas data suggested an association between lower KLHL17 (risk associated) and pro-inflammatory pathways. We hypothesize that KLHL17 may mitigate inflammation by recruiting pro-inflammatory proteins for ubiquitination and degradation thereby influencing PDAC risk.

EEF1A1 transcription cofactor gene polymorphism is associated with muscle gene expression and residual feed intake in Nelore cattle

Cis-acting effects of noncoding variants on gene expression and regulatory molecules constitute a significant factor for phenotypic variation in complex traits. To provide new insights into the impacts of single-nucleotide polymorphisms (SNPs) on transcription factors (TFs) and transcription cofactors (TcoF) coding genes, we carried out a multi-omic analysis to identify cis-regulatory effects of SNPs on these genes' expression in muscle and describe their association with feed efficiency-related traits in Nelore cattle. As a result, we identified one SNP, the rs137256008C > T, predicted to impact the EEF1A1 gene expression (β = 3.02; P-value = 3.51E-03) and the residual feed intake trait (β = - 3.47; P-value = 0.02). This SNP was predicted to modify transcription factor sites and overlaps with several QTL for feed efficiency traits. In addition, co-expression network analyses showed that animals containing the T allele of the rs137256008 SNP may be triggering changes in the gene network. Therefore, our analyses reinforce and contribute to a better understanding of the biological mechanisms underlying gene expression control of feed efficiency traits in bovines. The cis-regulatory SNP can be used as biomarker for feed efficiency in Nelore cattle.

Disease-associated genetic variants in the regulatory regions of human genes: mechanisms of action on transcription and genomic resources for dissecting these mechanisms

Whole genome and whole exome sequencing technologies play a very important role in the studies of the genetic aspects of the pathogenesis of various diseases. The ample use of genome-wide and exome-wide association study methodology (GWAS and EWAS) made it possible to identify a large number of genetic variants associated with diseases. This information is accumulated in the databases like GWAS central, GWAS catalog, OMIM, ClinVar, etc. Most of the variants identified by the GWAS technique are located in the noncoding regions of the human genome. According to the ENCODE project, the fraction of regions in the human genome potentially involved in transcriptional control is many times greater than the fraction of coding regions. Thus, genetic variation in noncoding regions of the genome can increase the susceptibility to diseases by disrupting various regulatory elements (promoters, enhancers, silencers, insulator regions, etc.). However, identification of the mechanisms of influence of pathogenic genetic variants on the diseases risk is difficult due to a wide variety of regulatory elements. The present review focuses on the molecular genetic mechanisms by which pathogenic genetic variants affect gene expression. At the same time, attention is concentrated on the transcriptional level of regulation as an initial step in the expression of any gene. A triggering event mediating the effect of a pathogenic genetic variant on the level of gene expression can be, for example, a change in the functional activity of transcription factor binding sites (TFBSs) or DNA methylation change, which, in turn, affects the functional activity of promoters or enhancers. Dissecting the regulatory roles of polymorphic loci have been impossible without close integration of modern experimental approaches with computer analysis of a growing wealth of genetic and biological data obtained using omics technologies. The review provides a brief description of a number of the most well-known public genomic information resources containing data obtained using omics technologies, including (1) resources that accumulate data on the chromatin states and the regions of transcription factor binding derived from ChIP-seq experiments; (2) resources containing data on genomic loci, for which allele-specific transcription factor binding was revealed based on ChIP-seq technology; (3) resources containing in silico predicted data on the potential impact of genetic variants on the transcription factor binding sites

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Association of the Sp1 binding site and -1997 promoter variations in COL1A1 with osteoporosis risk: The application of meta-analysis and bioinformatics approaches offers a new perspective for future research

As a complex disease, osteoporosis is influenced by several genetic markers. Many studies have examined the link between the Sp1 binding site +1245 G > T (rs1800012) and -1997 G > T (rs1107946) variations in the COL1A1 gene with osteoporosis risk. However, the findings of these studies have been contradictory; therefore, we performed a meta-analysis to aggregate additional information and obtain increased statistical power to more efficiently estimate this correlation. A meta-analysis was conducted with studies published between 1991-2020 that were identified by a systematic electronic search of the Scopus and Clarivate Analytics databases. Studies with bone mineral density (BMD) data and complete genotypes of the single-nucleotide variations (SNVs) for the overall and postmenopausal female population were included in this meta-analysis and analyzed using the R metaphor package. A relationship between rs1800012 and significantly decreased BMD values at the lumbar spine and femoral neck was found in individuals carrying the "ss" versus the "SS" genotype in the overall population according to a random effects model (p < 0.0001). Similar results were also found in the postmenopausal female population (p = 0.003 and 0.0002, respectively). Such findings might be an indication of increased osteoporosis risk in both studied groups in individuals with the "ss" genotype. Although no association was identified between the -1997 G > T and low BMD in the overall population, those individuals with the "GT" genotype showed a higher level of BMD than those with "GG" in the subgroup analysis (p = 0.007). To determine which transcription factor (TF) might bind to the -1997 G > T in COL1A1, 45 TFs were identified based on bioinformatics predictions. According to the GSE35958 microarray dataset, 16 of 45 TFs showed differential expression profiles in osteoporotic human mesenchymal stem cells relative to normal samples from elderly donors. By identifying candidate TFs for the -1997 G > T site, our study offers a new perspective for future research.

Transposable elements contribute to the genomic response to insecticides in Drosophila melanogaster

Most of the genotype–phenotype analyses to date have largely centred attention on single nucleotide polymorphisms. However, transposable element (TE) insertions have arisen as a plausible addition to the study of the genotypic–phenotypic link because of to their role in genome function and evolution. In this work, we investigate the contribution of TE insertions to the regulation of gene expression in response to insecticides. We exposed four Drosophila melanogaster strains to malathion, a commonly used organophosphate insecticide. By combining information from different approaches, including RNA-seq and ATAC-seq, we found that TEs can contribute to the regulation of gene expression under insecticide exposure by rewiring cis-regulatory networks.

This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation’.

Potential regulatory SNPs in the ATXN7L3B and KRT15 genes are associated with gender-specific colorectal cancer risk

Aim: According to the current data, a major factor for phenotypic variation of complex traits and disease susceptibility is the cis-acting effects of noncoding variants on gene expression. Our purpose was to evaluate the association between colorectal cancer (CRC) and six single nucleotide polymorphisms identified using our original bioinformatics approach as regulatory and putatively related to CRC. Materials: One hundred and sixty CRC patients and 185 healthy controls have been genotyped for rs590352, rs2072580, rs78317230, rs3829202, rs11542583 and rs4796672. Results: Genotypes and alleles distributions of rs590352 of ATXN7L3B gene were significantly different between the male CRC subjects and controls. Significant correlation of genotype with CRC is observable for women only for the rs4796672 of KRT15 gene. Analysis of haplotypes reveals that rs2072580 of the ISCU and SART3 genes can be also associated with CRC. Conclusion: We have identified three SNPs associated with CRC risk and demonstrated a gender specificity of rs590352 and rs4796672.

Rare Human Missense Variants can affect the Function of Disease-Relevant Proteins by Loss and Gain of Peroxisomal Targeting Motifs

Single nucleotide variants (SNVs) resulting in amino acid substitutions (i.e., missense variants) can affect protein localization by changing or creating new targeting signals. Here, we studied the potential of naturally occurring SNVs from the Genome Aggregation Database (gnomAD) to result in the loss of an existing peroxisomal targeting signal 1 (PTS1) or gain of a novel PTS1 leading to mistargeting of cytosolic proteins to peroxisomes. Filtering down from 32,985 SNVs resulting in missense mutations within the C-terminal tripeptide of 23,064 human proteins, based on gene annotation data and computational prediction, we selected six SNVs for experimental testing of loss of function (LoF) of the PTS1 motif and five SNVs in cytosolic proteins for gain in PTS1-mediated peroxisome import (GoF). Experimental verification by immunofluorescence microscopy for subcellular localization and FRET affinity measurements for interaction with the receptor PEX5 demonstrated that five of the six predicted LoF SNVs resulted in loss of the PTS1 motif while three of five predicted GoF SNVs resulted in de novo PTS1 generation. Overall, we showed that a complementary approach incorporating bioinformatics methods and experimental testing was successful in identifying SNVs capable of altering peroxisome protein import, which may have implications in human disease.