Functional testing of thousands of osteoarthritis-associated variants for regulatory activity

Klein, Jason C.; Keith, Aidan M.; Rice, S.J.; Shepherd, Colin; Agarwal, Vikram; Loughlin, John; Shendure, Jay

doi:10.1038/s41467-019-10439-y

Cited by 86 publications

(58 citation statements)

References 58 publications

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“…The mapping of risk loci for polygenic traits is now a relatively straightforward procedure, with the next major step in complex trait analysis being the transition from association signal to functional characterization 32 . For OA, considerable strides have been made in this regard in recent years 33–35 . Our interest is in the epigenetic dimension of OA genetic risk and especially the role of DNA methylation.…”

Section: Discussionmentioning

confidence: 99%

Multi-tissue epigenetic analysis of the osteoarthritis susceptibility locus mapping to the plectin genePLEC

Sorial

Hofer

Tselepi

et al. 2020

Preprint

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Running headline: Epigenetic analysis of the PLEC OA risk locusObjective 1 Osteoarthritis (OA) associated single nucleotide polymorphism (SNP) rs11780978 correlates 2 with differential expression of PLEC, and methylation quantitative trait loci (mQTLs) at PLEC 3 CpGs in cartilage. This implies that methylation links chondrocyte genotype and phenotype, 4 thus driving the functional effect. PLEC encodes plectin, a cytoskeletal protein that enables 5 tissues to respond to mechanical forces. We sought to assess whether PLEC functional effects 6 were cartilage specific. 7 8 Method 9Cartilage, fat pad, synovium and peripheral blood were collected from patients undergoing 10 arthroplasty. PLEC CpGs were analysed for mQTLs and allelic expression imbalance (AEI) 11 was performed. We focussed on previously reported mQTL clusters neighbouring cg19405177 12 and cg14598846. Plectin was knocked down in a mesenchymal stem cell (MSC) line using 13 CRISPR/Cas9 and cells phenotyped by RNA-sequencing. 14 15Results 16 Novel mQTLs were discovered in fat pad, synovium and peripheral blood at both clusters. The 17 genotype-methylation effect of rs11780978 was stronger in cg14598846 than in cg19405177 18 and stronger in joint tissues than in peripheral blood. We observed AEI in synovium in the 19 same direction as for cartilage. Knocking-down plectin impacted on pathways reported to have 20 a role in OA, including Wnt signalling, glycosaminoglycan biosynthesis and immune 21 regulation. 22 23 Conclusions 24Synovium is also a target of the rs11780978 OA association functionally operating on PLEC. 25In fat pad, mQTLs were identified but these did not correlate with PLEC expression, suggesting 26 the functional effect is not joint-wide. Our study highlights interplay between genetic risk, 27 DNA methylation and gene expression in OA, and reveals clear differences between tissues 28 from the same diseased joint. 29 30

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Section: Discussionmentioning

confidence: 99%

Multi-tissue epigenetic analysis of the osteoarthritis susceptibility locus mapping to the plectin genePLEC

Sorial

Hofer

Tselepi

et al. 2020

Preprint

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“…Follow-up from GWAS studies has required techniques such as allelic expression imbalance and reporter assays to determine the function of the specific genetic changes. 39,40 The current approach extends the possibilities of functional validation by generating isogenic populations of primary chondrocytes -where the only difference from control cells is the user-defined change. These sophisticated models will be critical for assessing the increasing number of genetic variants that have been identified as risk factors for OA.…”

Section: Discussionmentioning

confidence: 99%

Engineered cartilage from human chondrocytes with homozygous knockout of cell cycle inhibitor p21

D’Costa

Rich

Diekman

2019

Preprint

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Risk factors for the development of osteoarthritis (OA) include genetic background and focal cartilage injury.The search for disease-modifying OA therapies would benefit from a more comprehensive knowledge of the genetic variants that contribute to chondrocyte dysfunction and the barriers to cartilage regeneration. One goal of this study was to establish a system for producing engineered cartilage tissue from genetically-defined primary human chondrocytes through genome editing and single-cell expansion. This process was utilized to investigate the functional effect of bi-allelic knockout of the cell cycle inhibitor p21. The use of ribonucleoprotein (RNP) CRISPR/Cas9 complexes targeting two sites in the coding region of p21 resulted in a high frequency (16%) of colonies with homozygous p21 knockout. Chondrogenic pellet cultures from expanded chondrocytes with complete loss of p21 produced more glycosaminoglycans (GAG) and maintained a higher cell number. Single-cell derived colonies retained the potential for robust matrix production after expansion, allowing for analysis of colony variability from the same population of targeted cells. The effect of enhanced cartilage matrix production in p21 knockout chondrocytes persisted when matrix production from individual colonies was analyzed. Chondrocytes had lower levels of p21 protein with further expansion, and the difference in GAG production with p21 knockout was strongest at early passages. These results support previous findings that implicate p21 as a barrier to cartilage matrix production and regenerative capacity. Further, this work establishes the use of genome-edited human chondrocytes as a promising approach for engineered tissue models containing user-defined gene knockouts and other genetic variants for investigation of OA pathogenesis.

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“…MPRAs have been most broadly applied to explore and computationally model "regulatory grammar" of transcriptional regulators: how sequence features such as binding motifs, their abundance, and arrangement affect regulatory capacity (31)(32)(33)(34)(35)(36)(37)(38). More recently, these approaches have been applied to identify the transcriptional consequences of SNPs and rare variants (39)(40)(41)(42)(43)(44)(45). Figure 1A-B, a canonical 'enhancer' MPRA utilizes a promoter with candidate elements either immediately upstream or in a 3'UTR (STARRseq) (same approach as Figure 1D) (46).…”

Section: Part 1: Mpras For Identification Of Sequence Variants With Fmentioning

confidence: 99%

“…Expression-representing transcription or RNA stability-is typically measured as the counts of RNA barcode per encoding DNA barcode (Figure 1G). To define active or differentially active elements, expression levels can be normalized to e.g., a minimalpromoter only set of barcodes (31,34,37,(47)(48)(49), compared between alleles (39)(40)(41)(42)(43)(44)(45), or compared to shuffled parent sequence(s) (32,37) MPRAs also enable study of post-transcriptional regulatory elements. As shown in Figure 1C and 1D, the same architecture and RNA/DNA expression metric can be used to assess UTR effects on transcript stability.…”

Section: Part 1: Mpras For Identification Of Sequence Variants With Fmentioning

confidence: 99%

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

Mulvey¹,

Lagunas²,

Dougherty³

2020

Preprint

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Neuropsychiatric phenotypes have been long known to be influenced by heritable risk factors. The past decade of genetic studies have confirmed this directly, revealing specific common and rare genetic variants enriched in disease cohorts. However, the early hope for these studies-that only a small set of genes would be responsible for a given disorder-proved false. The picture that has emerged is far more complex: a given disorder may be influenced by myriad coding and noncoding variants of small effect size, and/or by rare but severe variants of large effect size, many de novo.Noncoding genomic sequences harbor a large portion of these variants, the molecular functions of which cannot usually be inferred from sequence alone. This creates a substantial barrier to understanding the higher-order molecular and biological systems underlying disease risk. Fortunately, a proliferation of genetic technologies-namely, scalable oligonucleotide synthesis, high-throughput RNA sequencing, CRISPR, and CRISPR derivatives-have opened novel avenues to experimentally identify biologically significant variants en masse. These advances have yielded an especially versatile technique adaptable to large-scale functional assays of variation in both untranscribed and untranslated regulatory features: Massively Parallel Reporter Assays (MPRAs). MPRAs are powerful molecular genetic tools that can be used to screen tens of thousands of predefined sequences for functional effects in a single experiment. This approach has several ideal features for psychiatric genetics, but remains underutilized in the field to date. To emphasize the opportunities MPRA holds for dissecting psychiatric polygenicity, we review here its applications in the literature, discuss its ability to test several biological variables implicated in psychiatric disorders, illustrate this flexibility with a proof-of-principle, in vivo cell-type specific implementation of the assay, and envision future outcomes of applying MPRA to both computational and experimental neurogenetics.

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Functional testing of thousands of osteoarthritis-associated variants for regulatory activity

Cited by 86 publications

References 58 publications

Multi-tissue epigenetic analysis of the osteoarthritis susceptibility locus mapping to the plectin genePLEC

Multi-tissue epigenetic analysis of the osteoarthritis susceptibility locus mapping to the plectin genePLEC

Engineered cartilage from human chondrocytes with homozygous knockout of cell cycle inhibitor p21

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

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