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Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases.
Cavalli, Marco; Baltzer, Nicholas; Pan, Gang; Bárcenas Walls, José Ramón; Smolinska Garbulowska, Karolina; Kumar, Chanchal; Skrtic, Stanko; Komorowski, Jan; Wadelius, Claes.
Affiliation
  • Cavalli M; Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Baltzer N; Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden.
  • Pan G; Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Bárcenas Walls JR; Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
  • Smolinska Garbulowska K; Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden.
  • Kumar C; AstraZeneca, Gothenburg, Sweden.
  • Skrtic S; AstraZeneca, Gothenburg, Sweden.
  • Komorowski J; Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden.
  • Wadelius C; Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland.
Hum Genomics ; 13(1): 20, 2019 04 29.
Article in En | MEDLINE | ID: mdl-31036066
ABSTRACT

BACKGROUND:

Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases.

METHODS:

The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles.

RESULTS:

We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites.

CONCLUSIONS:

This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Diabetes Mellitus, Type 2 / Liver / Metabolic Diseases Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Hum Genomics Journal subject: GENETICA Year: 2019 Document type: Article Affiliation country: Sweden

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Diabetes Mellitus, Type 2 / Liver / Metabolic Diseases Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Hum Genomics Journal subject: GENETICA Year: 2019 Document type: Article Affiliation country: Sweden