Dataset Information

Prioritization of PLEC and GRINA as Osteoarthritis Risk Genes Through the Identification and Characterization of Novel Methylation Quantitative Trait Loci.

ABSTRACT: OBJECTIVE:To identify methylation quantitative trait loci (mQTLs) correlating with osteoarthritis (OA) risk alleles and to undertake mechanistic characterization as a means of target gene prioritization. METHODS:We used genome-wide genotyping and cartilage DNA methylation array data in a discovery screen of novel OA risk loci. This was followed by methylation, gene expression analysis, and genotyping studies in additional cartilage samples, accompanied by in silico analyses. RESULTS:We identified 4 novel OA mQTLs. The most significant mQTL contained 9 CpG sites where methylation correlated with OA risk genotype, with 5 of the CpG sites having P values <1 × 10-10 . The 9 CpG sites reside in an interval of only 7.7 kb within the PLEC gene and form 2 distinct clusters. We were able to prioritize PLEC and the adjacent gene GRINA as independent targets of the OA risk. We identified PLEC and GRINA expression QTLs operating in cartilage, as well as methylation-expression QTLs operating on the 2 genes. GRINA and PLEC also demonstrated differential expression between OA hip and non-OA hip cartilage. CONCLUSION:PLEC encodes plectin, a cytoskeletal protein that maintains tissue integrity by regulating intracellular signaling in response to mechanical stimuli. GRINA encodes the ionotropic glutamate receptor TMBIM3 (transmembrane BAX inhibitor 1 motif-containing protein family member 3), which regulates cell survival. Based on our results, we hypothesize that in a joint predisposed to OA, expression of these genes alters in order to combat aberrant biomechanics, and that this is epigenetically regulated. However, carriage of the OA risk-conferring allele at this locus hinders this response and contributes to disease development.

SUBMITTER: Rice SJ

PROVIDER: S-EPMC6790675 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Prioritization of PLEC and GRINA as Osteoarthritis Risk Genes Through the Identification and Characterization of Novel Methylation Quantitative Trait Loci.

Rice Sarah J SJ Tselepi Maria M Sorial Antony K AK Aubourg Guillaume G Shepherd Colin C Almarza David D Skelton Andrew J AJ Pangou Ioanna I Deehan David D Reynard Louise N LN Loughlin John J

Arthritis & rheumatology (Hoboken, N.J.) 20190627 8

<h4>Objective</h4>To identify methylation quantitative trait loci (mQTLs) correlating with osteoarthritis (OA) risk alleles and to undertake mechanistic characterization as a means of target gene prioritization.<h4>Methods</h4>We used genome-wide genotyping and cartilage DNA methylation array data in a discovery screen of novel OA risk loci. This was followed by methylation, gene expression analysis, and genotyping studies in additional cartilage samples, accompanied by in silico analyses.<h4>Re ...[more]

PMID: 30730609

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Project description:Genetic dissection of the S rat genome has provided strong evidence for the presence of two interacting blood pressure (BP) quantitative trait loci (QTLs), termed QTL1 and QTL2, on rat chromosome 5. However, the identities of the underlying interacting genetic factors remain unknown. Further experiments targeted to identify the interacting genetic factors by the substitution mapping approach alone are difficult because of the interdependency of natural recombinations to occur at the two QTLs. We hypothesized that the interacting genetic factors underlying these two QTLs may interact at the level of gene transcription and thereby represent expression QTLs (eQTLs). To detect these interacting eQTLs, a custom QTL chip containing the annotated genes within QTL1 and QTL2 was developed and used to conduct a transcriptional profiling study of S and two congenic strains that retain either one or both the QTLs. The results uncovered an interaction between two transcription factors, DMRTA2 and NFIA. Further, the âbiological signatureâ elicited by these two transcription factors was differential between the congenic strain that retained LEW alleles at both QTL1 and 2 compared to the congenic strain that retained LEW alleles at QTL1 alone. A network of transcription factors potentially affecting BP could be traced, lending support to our hypothesis. Pairs of Cy5 and Cy3 labeled targets were co-hybridized onto either a custom long oligonucleotide microarray for the interrogation of 231 genes encompassed by QTL1 and QTL2, or a TIGR rat cDNA array consisting of 26,401 probe elements representing 20,465 unique non-QTL genes. A âflip-dyeâ or âbalanced blockâ design was used as the experimental method of choice to account for potential dye-bias labeling effects. Six âbalanced blockâ normalized files are submitted for the long oligonucleotide array interrogating the hearts from S versus S.LEW(5)x6x9 animals, fourteen âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x9 animals, and twelve âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x11 animals. GPR and MEV files cannot be located.

Dataset Information

Prioritization of PLEC and GRINA as Osteoarthritis Risk Genes Through the Identification and Characterization of Novel Methylation Quantitative Trait Loci.

Publications

Prioritization of PLEC and GRINA as Osteoarthritis Risk Genes Through the Identification and Characterization of Novel Methylation Quantitative Trait Loci.

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