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YEAR IN REVIEW - Genetics, Genomics, Epigenetics
- 1. YEAR IN REVIEW Genetics, Genomics, Epigenetics Louise Reynard Newcastle University, UK louise.reynard@newcastle.ac.uk
- 2. Louise Reynard, PhD Lecturer Newcastle University, Newcastle upon Tyne, UK Disclosure Information I have no financial relationships with commercial interests to disclose AND My presentation does not include discussion of off-label or investigational use.
- 3. Systematic Literature Review Year in Review: Genetics, Genomics, Epigenetics From 26/04/2018 to 23/04/2019 identified 636 papers using the terms OSTEOARTHRITIS or CARTILAGE and GENETICS/SNP/GENOMICS/RNA sequencing/TRANSCRIPTOMICS/EPIGENETICS/ EPIGENOMICS/NON-CODING RNA/miRNA/lncRNA/HISTONE/DNA METHYLATION In this review, I will focus on - Identification of new OA genetic loci from genome-wide association studies - New publically available databases and datasets that will aid functional studies of - Genomic techniques used for the first time in cartilage (e.g. single-cell RNAseq, ATACseq, histone ChIPseq) OA risk loci and OA-associated epigenetic changes
- 4. GENETICS
- 5. 57 new OA genetic risk loci were identified this year Year in Review: Genetics, Genomics, Epigenetics GENETICS Total loci Novel loci >650,000 Icelandic +UK individuals from UKBB + deCODE cohorts PMID:30374069 >450,000 UK individuals from UK Biobank + arcOGEN cohorts PMID:30664745 joint Together, these studies almost tripled the number of OA risk loci from 33 to 90 Two large scale genome-wide association studies for OA were published
- 6. Replication of existing loci including GDF5, PTHLH, ASTN2, RUNX2, SMAD3 and ALDH1A2 UKBB + deCODE study Meta-analysis for OA hip or OA knee Also looked at association with height* UK Biobank + arcOGEN study Meta-analysis of OA hip, OA knee, OA hip&/or knee and OA any site DPEP1 CRADD SPTBN2 COL11A1 HDAC9 SMO FAM101A* COL11A1* LTBP1* LTBP3 COL27A1 GSDMC* IL11* NACA2 SBNO1* LMX1B TNC NFAT5/WWP2* HFE/HIST1H2BC ANP32E RABGAP1L COLGALT2 KIF26B SDPR RAPH1 MST1R FAM53 RAB28 ANAPC4 SLC39A8 AP3B1 FGFR18 COL11A2 CDC5L BMP5 DYNCIL1 PPR1R3B mir8068 DCDC5 TSKU LRIG3 CPSF6 linc00936 BCL7AUSP8 CSK NF1 SMG1 MAPT SOX9 TMEM241 SLC44A2 TGFB1 ERG SCUBE1 Year in Review: Genetics, Genomics, Epigenetics GENETICS 57 new OA genetic risk loci were identified this year 4 unique loci 12 shared loci 41 unique loci * Loci also associated with height at p<5x10-8
- 7. • 10 hip shape modules from DXA scans of 15,973 • Loci overlap established PTHLH & ASTN2 and novel OA loci near SOX9 1st meta-analysis GWAS for hip shape identified 12 loci at p< 5x10-8 SOX9 rs2158915 PTHLH rs10743612 ASTN2 rs1885285 PMID:30320955 New variants for hip shape and DHH co-localise with OA loci Genetic association between OA, hip shape and DDH suggests that OA genetic risk is established during development GWASs of hip shape and developmental dysplasia of the hip (DDH) GDF5 OA SNP rs143384 is also associated with DDH genetic risk • GDF5 rs143384 SNP p=3.55x10-22, OR 1.44 PMID:30273415 Gdf5 null mice have abnormal hips incl. smaller femoral heads and necks GDF5 is required for normal hip morphology in mice PMID:30388100 +/- -/- Year in Review: Genetics, Genomics, Epigenetics GENETICS
- 8. In 2019-2020, the number of OA loci will increase again…. Year in Review: Genetics, Genomics, Epigenetics GENETICS Meta-analysis of 18 GWAS cohorts by the Genetics of Osteoarthritis consortium* • 1st trans-ethnic GWAS meta-analysis for OA and includes 179,305 cases and >650,000 controls from Europe, Japan, Hong Kong and USA * Personal communication from Cindy Boer and Joyce van Meurs arcoGEN ARGO study Geisinger HKDDDC HUNT study TwinsUK Norwegian Arthroplasty Register Japanese OA cohort Leiden Longevity Study Nurses’ Health Study Rotterdam study UKBiobank CHECK deCODE EGCUT GARP RAAK UKHLS https://www.genetics-osteoarthritis.com/ • Phenotypes include hip, knee, spine, hand, thumb, finger OA and all OA • ~70 novel OA loci have been identified* • Polygenic risk score and heritability estimate analyses are now being performed* >2 fold increase in number of cases than previous meta-analyses
- 9. GENOMICS
- 10. Year in Review: Genetics, Genomics, Epigenetics GENOMICS RNAseq detected SNPs with allelic imbalance (AI) in OA cartilage ‘ .. data set for researchers in the OA research field to probe for disease-relevant genetic variation that affects gene expression in pivotal disease-affected tissue’ Transcriptome-wide quantification of SNP allelic output in heterozygotes A C AAA AAA AAA Allelic balance AAA AAA AAA A C AAA AAA AAA AAA AAA Allelic imbalance (AI) PMID:30298554 • AI assessed in 42 preserved and 5 lesioned OA cartilage samples • 2,070 SNPs that consistently marked AI of 1,031 unique genes (Supplementary Table S3) • 11 previously identified OA/mJSW risk genes contained SNPs that marked AI in OA cartilage (including ALDH1A2, MGP, MAP2K6, PLEC and COL11A1) • 4/57 new OA loci contain transcript SNPs with AI in cartilage (LTBP1, TNC, SBNO1/CDK2AP1 and SLC44A2)
- 11. SkeletalVis is a new database for skeletal transcriptomics data SkeletalVis transcriptomic data portal http://phenome.manchester.ac.uk/ Year in Review: Genetics, Genomics, Epigenetics GENOMICS ‘..will be useful for prioritization of differentially expressed genes…. and for initial functional characterization of novel disease-associated genes identified through GWAS..’ Database of ~300 consistently analysed cross-species transcriptomic experiments from skeletal tissues (including cartilage, bone, synovium, meniscus & blood) PMID:30481257
- 12. The first single-cell RNAseq analysis of cartilage identified seven molecular subgroups of OA chondrocytes Analysis of 1464 chondrocytes from the tibial plateau of 10 OA knee patients Year in Review: Genetics, Genomics, Epigenetics GENOMICS ‘reveal the overall pattern of transcriptome states during OA pathogenesis at the single-cell level’ PMID:30026257 - Identified 7 chondrocyte clusters and their markers genes - These included 3 novel populations; effector (ECs), regulatory (RegCs) and homeostatic (HomCs) chondrocytes
- 14. ‘..aimed to define a transcriptome of lncRNAs in OA cartilage, specifically comparing the lincRNA transcriptome of knee and hip cartilage.’ • 1692 hip & 648 knee lncRNAs TPM>1 • 198 DE hip & 93 DE knee lncRNAs e.g. MEG3 PMID:30611906 Two RNAseq studies systematically identified cartilage ncRNAs Genome-wide expression analysis of miRNAs and lncRNAs in OA cartilage • Integrated mRNA and miRNA RNAseq in paired preserved and lesioned OA cartilage ‘our miRNA interactome represents a comprehensive legacy to directly probe miRNAs of interest with their likely downstream signalling pathways..’ • 142 miRNAs & 2387 DE mRNAs at FDR≤0.05 • 62 miRNAs and 238 mRNAs formed the first comprehensive OA miRNA interactome PMID:30504444 Year in Review: Genetics, Genomics, Epigenetics EPIGENETICS DE lncRNAs
- 15. ATACseq identifed open chromatin regions in OA knee cartilage Year in Review: Genetics, Genomics, Epigenetics EPIGENETICS*assay for transposase-accessible chromatin using sequencing ATACseq* is a genome-wide method to identify open chromatin regions ATACseq is fast, sensitive, requires few cells and is becoming an essential epigenetic tool for identifying transcriptional regulatory regions including enhancers and promoters PMID:24097267 50,000 cells from paired damaged and intact regions of OA knee cartilage from 8 OA patients PMID:30341348 109,125 open chromatin regions were identified in OA knee cartilage
- 16. ATACseq identifed open chromatin regions in OA knee cartilage *based on Roadmap annotations • 71.1% peaks were annotated as enhancers* 109,125 open chromatin regions were identified in OA knee cartilage PMID:30341348 unknown (12%) promoter (16.9%%) enhancer (71.1%) More open in intact (2.6%) More open in damaged (1.4%) Unaltered 96% Open chromatin characteristics ‘..our study provides an accessible chromatin landscape of cartilage tissue for better interpretation of other genetic and epigenomic data relevant to OA..’ • Several previously reported OA SNPs overlap OA knee ATACseq peaks (GDF5, ALDH1A2, DOT1L, MCF2L, GLIS3 and MGP loci) • SNPs within 29/57 new OA loci overlap ATACseq peaks (including LTBP1, LTBP3, GSDMC, SBNO1, COL11A1, TNC and SLC44A2) Year in Review: Genetics, Genomics, Epigenetics EPIGENETICS
- 17. Histone ChIPseq identified promoters and enhancer regions in fetal and adult articular cartilage Year in Review: Genetics, Genomics, Epigenetics EPIGENETICS ChIPseq of 10,000 chondrocytes for H3K4me1, H3K4me3, H3K27Ac & H3K27me3 • Histone ChIPseq of 17 week human fetal & adult chondrocytes and hESC-derived chondrocytes • 12 chromatin states identified including inactive, poised and active enhancers (raw ChIPseq data available to download at GSE111850) • RNAseq analysis of 4 in vivo & 2 in vitro stages of chondrocyte differentiation, and 17 week fetal bone, muscle, ligament and tendon tissues (TPM data available as an excel file at GSE106292) PMID:30194383
- 18. Acknowledgements Thank you to Cindy Boer and Joyce van Meurs for sharing unpublished GWAS data from the GO consortium meta-analysis
Editor's Notes
- Total of 4134 cases, 5781 ctls
- Three years ago Joyce van Meurs gave the year in review and at the end of her presentation, she said that OA genetics was in the trough of dillusionment and would hopefully enter the plateau of productiveity. However, we have entered a golden age of identification of OA genetic loci, which will continue with the GO consortium.
- Use of emerging genomic methods in cartilage and databases and datasets that will aid future functional studies of genetic and epigenetic OA loci
- Analysed ctl hip, OA hip, preserved knee and lesioned knee cartilage
- alternative advanced method for MNase-seq (sequencing of micrococcal nuclease sensitive sites), FAIRE-seq and DNAse-seq (1). ATAC-seq is an emerging technique that’s gaining popularity among researchers from diverse backgrounds as it aids in a fast and sensitive analysis of the epigenome compared to DNase-seq or MNase-seq (2,3,4). The applications of ATAC-seq in enhancing the functional genomics field have been explored in recent literature in hopes to understand epigenetic regulation in the context of disease development and cell differentiation. Indeed, ATAC-seq is becoming an essential tool in epigenetics and genome-regulation research and a standard part of epigenetic analysis. It has been successfully adapted to efficiently identify open chromatin and identify regulatory elements across the genome. ATAC-seq identifies accessible DNA regions by probing open chromatin with hyperactive mutant Tn5 transposase that inserts sequencing adapters into open regions of the genome. The mutant Tn5 transposase excises any sufficiently long DNA in a process called tagmentation: the simultaneous fragmentation and tagging of DNA performed by Tn5 transposase pre-loaded with sequencing adaptors. The tagged DNA fragments are then purified, amplified by PCR and sent for sequencing. Sequencing reads can then be used to infer regions of increased accessibility as well as to map regions of transcription-factor binding sites and nucleosome positions. The key element of the ATAC-seq procedure is the action of the transposase Tn5 on the genomic DNA of the sample. Transposases are enzymes catalyzing the movement of transposons to other parts in the genome (5). While naturally occurring transposases have a low level of activity, ATAC-seq employs a mutated hyperactive transposase(5). The most common use of ATAC-Seq is in nucleosome mapping experiments (3). To this end, ATAC-Seq analysis has been used to investigate a number of chromatin-related signatures such as the genome-wide chromatin accessibility landscape in human cancer (6) and enhancer prediction. The utility of high-resolution enhancer mapping ranges from studying the evolutionary divergence of enhancer usage (e.g. between chimps and humans) during development (7) and uncovering a lineage-specific enhancer map used during blood cell differentiation (8). Most recently, ATAC-Seq has been used to reveal a genome-wide decrease in chromatin accessibility specifically related to macular degeneration (vision loss) (9).
- alternative advanced method for MNase-seq (sequencing of micrococcal nuclease sensitive sites), FAIRE-seq and DNAse-seq (1). ATAC-seq is an emerging technique that’s gaining popularity among researchers from diverse backgrounds as it aids in a fast and sensitive analysis of the epigenome compared to DNase-seq or MNase-seq (2,3,4). The applications of ATAC-seq in enhancing the functional genomics field have been explored in recent literature in hopes to understand epigenetic regulation in the context of disease development and cell differentiation. Indeed, ATAC-seq is becoming an essential tool in epigenetics and genome-regulation research and a standard part of epigenetic analysis. It has been successfully adapted to efficiently identify open chromatin and identify regulatory elements across the genome. ATAC-seq identifies accessible DNA regions by probing open chromatin with hyperactive mutant Tn5 transposase that inserts sequencing adapters into open regions of the genome. The mutant Tn5 transposase excises any sufficiently long DNA in a process called tagmentation: the simultaneous fragmentation and tagging of DNA performed by Tn5 transposase pre-loaded with sequencing adaptors. The tagged DNA fragments are then purified, amplified by PCR and sent for sequencing. Sequencing reads can then be used to infer regions of increased accessibility as well as to map regions of transcription-factor binding sites and nucleosome positions. The key element of the ATAC-seq procedure is the action of the transposase Tn5 on the genomic DNA of the sample. Transposases are enzymes catalyzing the movement of transposons to other parts in the genome (5). While naturally occurring transposases have a low level of activity, ATAC-seq employs a mutated hyperactive transposase(5). The most common use of ATAC-Seq is in nucleosome mapping experiments (3). To this end, ATAC-Seq analysis has been used to investigate a number of chromatin-related signatures such as the genome-wide chromatin accessibility landscape in human cancer (6) and enhancer prediction. The utility of high-resolution enhancer mapping ranges from studying the evolutionary divergence of enhancer usage (e.g. between chimps and humans) during development (7) and uncovering a lineage-specific enhancer map used during blood cell differentiation (8). Most recently, ATAC-Seq has been used to reveal a genome-wide decrease in chromatin accessibility specifically related to macular degeneration (vision loss) (9).