Challenges and progress in interpretation of non-coding genetic variants associated with human disease Article Swipe
Yizhou Zhu
,
Cagdas Tazearslan
,
Yousin Suh
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1177/1535370217713750
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1177/1535370217713750
Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.
Related Topics
Concepts
Genome-wide association study
Computational biology
Genetic association
Epigenomics
Genome
Human genome
Genomics
Biology
Computer science
Genetics
Gene
Single-nucleotide polymorphism
Genotype
DNA methylation
Gene expression
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/1535370217713750
- OA Status
- green
- Cited By
- 70
- References
- 97
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2621435244
All OpenAlex metadata
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https://openalex.org/W2621435244Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1177/1535370217713750Digital Object Identifier
- Title
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Challenges and progress in interpretation of non-coding genetic variants associated with human diseaseWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-06-05Full publication date if available
- Authors
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Yizhou Zhu, Cagdas Tazearslan, Yousin SuhList of authors in order
- Landing page
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https://doi.org/10.1177/1535370217713750Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.ncbi.nlm.nih.gov/pmc/articles/5529005Direct OA link when available
- Concepts
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Genome-wide association study, Computational biology, Genetic association, Epigenomics, Genome, Human genome, Genomics, Biology, Computer science, Genetics, Gene, Single-nucleotide polymorphism, Genotype, DNA methylation, Gene expressionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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70Total citation count in OpenAlex
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2025: 4, 2024: 22, 2023: 11, 2022: 4, 2021: 6Per-year citation counts (last 5 years)
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97Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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