Understanding Non-Mendelian Genetic Risk
© 2019 Bentham Science Publishers..
This opinion paper highlights strategies for a better understanding of non-Mendelian genetic risk that was revealed by genome-wide association studies (GWAS) of complex diseases. The genetic risk resides predominantly in non-coding regulatory DNA, such as in enhancers. The identification of mechanisms, the causal variants (mainly SNPs), and their target genes are, however, not always apparent but are likely involved in a network of risk determinants; the identification presents a bottle-neck in the full understanding of the genetics of complex phenotypes. Here, we propose strategies to identify functional SNPs and link risk enhancers with their target genes. The strategies are 1) identifying fine-mapped SNPs that break/form response elements within chromatin bio-features in relevant cell types 2) considering the nearest gene on linear DNA, 3) analyzing eQTLs, 4) mapping differential DNA methylation regions and relating them to gene expression, 5) employing genomic editing with CRISPR/cas9 and 6) identifying topological associated chromatin domains using chromatin conformation capture.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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| Enthalten in: |
Current genomics - 20(2019), 5 vom: 21. Aug., Seite 322-324 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Coetzee, Gerhard A [VerfasserIn] |
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| Links: |
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| Themen: |
Chromatin |
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| Anmerkungen: |
Date Revised 28.09.2020 published: Print Citation Status PubMed-not-MEDLINE |
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| doi: |
10.2174/1389202920666191018085511 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM310574196 |
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| 520 | |a This opinion paper highlights strategies for a better understanding of non-Mendelian genetic risk that was revealed by genome-wide association studies (GWAS) of complex diseases. The genetic risk resides predominantly in non-coding regulatory DNA, such as in enhancers. The identification of mechanisms, the causal variants (mainly SNPs), and their target genes are, however, not always apparent but are likely involved in a network of risk determinants; the identification presents a bottle-neck in the full understanding of the genetics of complex phenotypes. Here, we propose strategies to identify functional SNPs and link risk enhancers with their target genes. The strategies are 1) identifying fine-mapped SNPs that break/form response elements within chromatin bio-features in relevant cell types 2) considering the nearest gene on linear DNA, 3) analyzing eQTLs, 4) mapping differential DNA methylation regions and relating them to gene expression, 5) employing genomic editing with CRISPR/cas9 and 6) identifying topological associated chromatin domains using chromatin conformation capture | ||
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