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Genomic annotation of disease-associated variants reveals shared functional contexts

  • Yasuhiro Kyono
  • Jacob O. Kitzman
  • Stephen C. J. ParkerEmail author
Review

Abstract

Variation in non-coding DNA, encompassing gene regulatory regions such as enhancers and promoters, contributes to risk for complex disorders, including type 2 diabetes. While genome-wide association studies have successfully identified hundreds of type 2 diabetes loci throughout the genome, the vast majority of these reside in non-coding DNA, which complicates the process of determining their functional significance and level of priority for further study. Here we review the methods used to experimentally annotate these non-coding variants, to nominate causal variants and to link them to diabetes pathophysiology. In recent years, chromatin profiling, massively parallel sequencing, high-throughput reporter assays and CRISPR gene editing technologies have rapidly become indispensable tools. Rather than treating individual variants in isolation, we discuss the importance of accounting for context, both genetic (such as flanking DNA sequence) and environmental (such as cellular state or environmental exposure). Incorporating these features shows promise in terms of revealing biologically convergent molecular signatures across distant and seemingly unrelated loci. Studying regulatory elements in the proper context will be crucial for interpreting the functional significance of disease-associated variants and applying the resulting knowledge to improve patient care.

Keywords

Chromatin Diabetes Epigenome Gene expression Genetics Genome-wide association study Human Reporter assay Review Transcription 

Abbreviations

ATAC-seq

Assay for transposase-accessible chromatin sequencing

ChIP-seq

Chromatin immunoprecipitation sequencing

dCas9

Dead CRISPR-associated protein 9

DHS

DNase I hypersensitive site

eQTL

Expression quantitative trait loci

GATA1

GATA-binding factor 1

GFP

Green fluorescent protein

GWAS

Genome-wide association studies

LPS

Lipopolysaccharides

MPRA

Massively parallel reporter assay

RFX

Regulatory factor X

SE

Stretch enhancer

sgRNA

Single guide RNA

SNP

Single-nucleotide polymorphism

STARR-seq

Self-transcribing active regulatory region sequencing

Notes

Acknowledgements

We thank members of the Kitzman and Parker laboratories, and associated collaborators, for invaluable discussions. We apologise in advance to authors whose work we were unable to cite or discuss because of space limitations.

Contribution statement

All authors were responsible for drafting the article and revising it critically for important intellectual content. All authors approved the version to be published.

Funding

Work in the laboratories of SCJP is supported by the American Diabetes Association Pathway to Stop Diabetes Initiator Award 1-14-INI-07 (SCJP) and NIH/NIDDK grants R00 DK099240 and R01 DK117960 (SCJP).

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2019_4823_MOESM1_ESM.pptx (675 kb)
Slideset of figures (PPTX 674 kb).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Yasuhiro Kyono
    • 1
    • 2
    • 3
  • Jacob O. Kitzman
    • 1
    • 2
  • Stephen C. J. Parker
    • 1
    • 2
    Email author
  1. 1.Department of Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA
  2. 2.Department of Human GeneticsUniversity of MichiganAnn ArborUSA
  3. 3.Institute for Genomics and Systems BiologyUniversity of ChicagoChicagoUSA

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