High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction

Li, Gang; Martínez‐Bonet, Marta; Wu, Di; Yu, Yang; Cui, Jing; Nguyen, Hung N.; Cunin, Pierre; Levescot, Anaïs; Bai, Ming-Yi; Westra, Harm Jan; Okada, Yukinori; Brenner, Michael B.; Raychaudhuri, Soumya; Hendrickson, Eric A.; Maas, Richard L.; Nigrović, Peter A.

doi:10.1038/s41588-018-0159-z

Cited by 33 publications

(69 citation statements)

References 45 publications

(53 reference statements)

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“…Regulatory variants commonly alter gene expression by modulating the binding of transcription factors. Identification of these transcription factors will link the regulation of IL1RN to cellular pathways and thereby suggest new targets for intervention . How is systemic JIA that evolves in children with high levels of IL‐1Ra different demographically, clinically, and pathophysiologically from systemic JIA that does not?…”

mentioning

confidence: 99%

Editorial: Toward Personalized Treatment for Systemic Juvenile Idiopathic Arthritis

Vastert

Nigrović

2018

Arthritis & Rheumatology

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confidence: 99%

Editorial: Toward Personalized Treatment for Systemic Juvenile Idiopathic Arthritis

Vastert

Nigrović

2018

Arthritis & Rheumatology

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“…We first compared experimentally validated regulatory SNPs in mononuclear cells ( 35 ) and detected substantially more experimentally validated SNPs by our method compared with all 5 methods ( Figure 2A ). Consistent results were found in 2 nonimmune cell types (K562, HepG2) ( 36 ), in which our method had substantially more experimentally validated regulatory SNPs compared with 3 other methods (FIRE, GWAS4D, and IW-Scoring) ( Supplemental Figure 4 ).…”

Section: Resultsmentioning

confidence: 99%

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

Chen¹,

Guo²,

Duan³

et al. 2020

JCI Insight

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More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell–specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes ( NFKB1 and SH2B3 ) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.

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“…(a) Description of top-scored SNPs sets from each method for functional comparing in b-f, which are marked by different colors (bottom). (b) Comparison of experimentally validated functional SNPs between our method and other five methods from a high-throughput screen assay in mononuclear cells [26]. (c-f) Comparison of percentage of annotated SNPs within different regulatory evidence between our method and other five methods, including (c) potential regulatory SNPs with predicted target gene by combining cis-QTL and chromatin interaction analysis, (d) potential functional SNPs with significant molecular QTL (bQTL, hQTL, dsQTL or caQTL) association, (e) casual autoimmune associated SNPs identified by PICS approach [18], and (f) potential regulatory SNPs within eRNA detected from IBD patients [28].…”

Section: Resultsmentioning

confidence: 99%

“…We firstly compared experimentally validated regulatory SNPs in mononuclear cells [26], and detected substantially more validated SNPs by our method compared with either FIRE, GWAS4D or IW-Scoring (Figure 3b). We also detected much more validated SNPs compared with 3DSNP under the first two functionality support and comparable validated SNPs compared with RegulomeDB (Figure 3b).…”

Section: Resultsmentioning

confidence: 99%

“…For collected functional SNPs set from each methods, we firstly compared their experimentally validated SNPs count in three cell types (blood mononuclear cells, K562 and HepG2) from two recent high-throughput screen reports [26, 27]. We next compared their functionality enrichment on multiple regulatory data support using Fisher’s exact test, including (1) SNPs with predicted local or distal target genes by integrating cis-QTL and chromatin interaction analysis on over 30 blood immune cell types (Table S4), (2) SNPs annotated with molecular QTL (bQTL, hQTL, dsQTL and caQTL) on multiple blood immune cell types (Table S7), (3) reported causal SNPs associated with 16 autoimmune diseases (AA, AS, ATD, CEL, CRO, JIA, MS, PBC, PSC, PSO, RA, SLE, SSC, T1D, UC, VIT) prioritized by the PICS approach [18], and (4) SNPs annotated with enhancer RNA (eRNA) from IBD patient samples [28].…”

Section: Methodsmentioning

confidence: 99%

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Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

Chen

Guo

Duan

et al. 2019

Preprint

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14The genome-wide association studies (GWAS) have identified hundreds of 15 susceptibility loci associated with autoimmune diseases. However, over 90% of risk 16 variants are located in the noncoding regions, leading to great challenges in 17 deciphering the underlying causal functional variants/genes and biological 18 mechanisms. Previous studies focused on developing new scoring method to 19 prioritize functional/disease-relevant variants. However, they principally 20 incorporated annotation data across all cells/tissues while omitted the cell-specific or 21 context-specific regulation. Moreover, limited analyses were performed to dissect the 22 detailed molecular regulatory circuits linking functional GWAS variants to disease 23 etiology. Here we devised a new analysis frame that incorporate hundreds of immune 24 cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs 25 with gene targets and further dissect their downstream molecular mechanisms and 26 clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic 27 associations with transcription factors (TFs) binding, histone modification or 28 chromatin accessibility, indicating their allelic regulatory roles on target genes. Their 29 target genes were significantly enriched in immunologically related pathways and 30other immunologically related functions. We also detected long-range regulation on 31 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, 32 CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the 33 important roles of long-range chromatin interaction in autoimmune diseases. 34Moreover, we identified hundreds of known or predicted druggable genes, and 35 predicted some new potential drug targets for several autoimmune diseases, including 36 two genes (NFKB1, SH2B3) with known drug indications on other diseases, 37 highlighting their potential drug repurposing opportunities. In summary, our analyses 38 may provide unique resource for future functional follow-up and drug application on 39 autoimmune diseases, which are freely available at http://fngwas.online/. 40 41 42 3 Author Summary 43Autoimmune diseases are groups of complex immune system disorders with high 44 prevalence rates and high heritabilities. Previous studies have unraveled thousands 45 of SNPs associated with different autoimmune diseases. However, it remains largely 46 unknown on the molecular mechanisms underlying these genetic associations. 47Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging 48 multiple immune cell-specific multi-omics data across genomic, epigenetic, 49 transcriptomic and 3D chromatin interaction information, we systematically analyzed 50 the functional variants/genes and biological mechanisms underlying genetic 51 association on 19 autoimmune diseases. We found that most functional SNPs may 52 affect target gene expression through altering transcription factors (TFs) binding, 53 histone modification or chromatin acce...

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High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction

Cited by 33 publications

References 45 publications

Editorial: Toward Personalized Treatment for Systemic Juvenile Idiopathic Arthritis

Editorial: Toward Personalized Treatment for Systemic Juvenile Idiopathic Arthritis

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

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