Disease susceptibility may be increased by accumulation of genetic variants in chromatin loops from disease-relevant cell-types
(2018) BINP32 20171Degree Projects in Bioinformatics
- Abstract
- Genome-wide association studies (GWAS) have identified more than 50,000 SNP-trait associations. Most of these SNPs or genetic variants map to noncoding regions, known as or gene desserts. This makes it challenging to describe the mechanism by which the variant confers susceptibility to the trait. Increasingly, there is an interest in characterization and interpretation of the effect of non-coding variants to find new biological targets. We wanted to study the effect of genetic variants in 3D chromatin loops on the phenotype. 3D loops are crucial for long-range gene regulation and structure of chromosomes and we expected to find an enrichment of statistically significant variants on these loops. We performed data integration analysis using... (More)
- Genome-wide association studies (GWAS) have identified more than 50,000 SNP-trait associations. Most of these SNPs or genetic variants map to noncoding regions, known as or gene desserts. This makes it challenging to describe the mechanism by which the variant confers susceptibility to the trait. Increasingly, there is an interest in characterization and interpretation of the effect of non-coding variants to find new biological targets. We wanted to study the effect of genetic variants in 3D chromatin loops on the phenotype. 3D loops are crucial for long-range gene regulation and structure of chromosomes and we expected to find an enrichment of statistically significant variants on these loops. We performed data integration analysis using 3D loop data from chromosome conformation capture Hi-C, in lymphoblast, lung fibroblast, and epithelium cell types. We also investigated the enrichment of different GWAS variants from different traits, specifically Inflammatory Bowel disease (IBD), Force vital capacity (FVC), and Amyotrophic Lateral Sclerosis (ALS). We found that 3D loops from epithelial and lymphoblast cells co-localize with some of the most significant variants from IBD more than expected by chance. We also showed that the 1% most significant genome variants from all our GWAS traits map to 3D loops by a significant margin. The enrichment of these genome variants in chromatin loops is stronger in disease relevant cell-types. Finally, we modeled a network using 3D loops and genes using regulatory connection as linkers, finding that the network is highly partitioned into communities. We found that community hubs, or nodes with the maximum number of connections in communities, have a higher accumulation of genetic variants. These findings suggest that complex diseases may be influenced by cumulative effects of small genetic variants in 3D loops, especially the ones from cell-types related to the disease. Furthermore, sets of 3D loops may be regulating sets of genes in a collective way. Finally, highest accumulation of genetic variants in loop anchors in the center of communities indicates that these variants can disrupt loops and affect the network stability and consequently, the phenotype. (Less)
- Popular Abstract
- The 3D conformation of the genome helps us understand complex disease
Why do some people get sick while others do not? Answering this question has been one of the main goals of medicine research for more than 2000 years. Today, due to advances in genetic techniques, we are closer than ever. Contemporary sequencing and genotyping technologies are able to disclose genetic differences between thousands of individuals, both sick and healthy. This means that we can identify genomic features that are associated with a specific disease. Such features are abnormalities located somewhere along the genome, and they're called genetic variants.
Monogenic diseases like Cystic fibrosis are caused by genetic variants in a single gene. When this... (More) - The 3D conformation of the genome helps us understand complex disease
Why do some people get sick while others do not? Answering this question has been one of the main goals of medicine research for more than 2000 years. Today, due to advances in genetic techniques, we are closer than ever. Contemporary sequencing and genotyping technologies are able to disclose genetic differences between thousands of individuals, both sick and healthy. This means that we can identify genomic features that are associated with a specific disease. Such features are abnormalities located somewhere along the genome, and they're called genetic variants.
Monogenic diseases like Cystic fibrosis are caused by genetic variants in a single gene. When this gene is translated into a protein, the genetic variant causes dysfunction which in turn leads to a diseased state in the individual. By contrast, complex diseases such as diabetes, inflammatory bowel disease, and amyothrophic lateral sclerosis, are polygenic. This means that the dysfunction stems from genetic variants in multiple genomic locations, as well as environmental factors. A serious concern for researchers in complex disease is that most associated genetic variants (~90%) in complex diseases are not found in the genes themselves, where it would be relatively simple to deduce their impact. Instead they are located along the stretches of genomic DNA that do not undergo translation into protein. These regions are sometimes referred (erroneously) to as "junk DNA".
Understanding the effect of genetic variants is key during development of medical products. In order to gain this understanding, we put the genetic variants into their biological contexts. Unless something has gone wrong, every single cell nuclei in an individual contains the same genome, but between types of tissue and types of cells there are differences in whether a gene is expressed into protein or not. This is one of the reasons why for example liver cells and neurons are very different from each other even though they have the same genome in their nuclei. One of many regulators of gene expression is the chromatin 3D loop. Genomic regions that are spaced far apart in the linear sense may be very close in three-dimensional space, because of these chromatin 3D loops. Many chromatin loops cause genes to be in close proximity to DNA that assist in activation of said genes. Chromatin loop structure across the entire genome is different between cell-types.
We hypothesize that certain genetic variants cause disruption of these loops, modifying the regulation of gene expression, leading to increased risk of disease in the cells' tissue.
To test this hypothesis, we analyzed the genetic variations associated with inflammatory bowel disease (IBD. Prolonged immune response to microbiota along the intestinal tract), amyothrophic lateral sclerosis (ALS) and force vital capacity (FVC. A measure of lung function). We discovered a significant enrichment of disease-causing genetic variants in 3D loops. The enrichment is more substantial in loops from cells related to the disease. IBD, for example, features a higher number of genetic variants in loops of immune cells as compared to loops in lung or skin cells. This indicates that complex diseases may be caused by genetic variants that disrupt chromatin 3D loops involved with gene expression in certain cell-types.
In the future, when more data is available on 3D loops and other regulatory mechanisms, we will be able to rank cell-types by their contribution to complex disease. This will further our understanding about the causes of complex disease, and eventually improve treatment at the clinic.
Master’s Degree Project in Bioinformatics 60 credits 2018.
Genetic Department, UMC Utrecht, Utrecht University.
Sara L. Pulit (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8947919
- author
- Acera Mateos, Pablo
- supervisor
- organization
- course
- BINP32 20171
- year
- 2018
- type
- H2 - Master's Degree (Two Years)
- subject
- language
- English
- id
- 8947919
- date added to LUP
- 2018-06-11 13:31:44
- date last changed
- 2018-06-11 13:31:44
@misc{8947919,
abstract = {{Genome-wide association studies (GWAS) have identified more than 50,000 SNP-trait associations. Most of these SNPs or genetic variants map to noncoding regions, known as or gene desserts. This makes it challenging to describe the mechanism by which the variant confers susceptibility to the trait. Increasingly, there is an interest in characterization and interpretation of the effect of non-coding variants to find new biological targets. We wanted to study the effect of genetic variants in 3D chromatin loops on the phenotype. 3D loops are crucial for long-range gene regulation and structure of chromosomes and we expected to find an enrichment of statistically significant variants on these loops. We performed data integration analysis using 3D loop data from chromosome conformation capture Hi-C, in lymphoblast, lung fibroblast, and epithelium cell types. We also investigated the enrichment of different GWAS variants from different traits, specifically Inflammatory Bowel disease (IBD), Force vital capacity (FVC), and Amyotrophic Lateral Sclerosis (ALS). We found that 3D loops from epithelial and lymphoblast cells co-localize with some of the most significant variants from IBD more than expected by chance. We also showed that the 1% most significant genome variants from all our GWAS traits map to 3D loops by a significant margin. The enrichment of these genome variants in chromatin loops is stronger in disease relevant cell-types. Finally, we modeled a network using 3D loops and genes using regulatory connection as linkers, finding that the network is highly partitioned into communities. We found that community hubs, or nodes with the maximum number of connections in communities, have a higher accumulation of genetic variants. These findings suggest that complex diseases may be influenced by cumulative effects of small genetic variants in 3D loops, especially the ones from cell-types related to the disease. Furthermore, sets of 3D loops may be regulating sets of genes in a collective way. Finally, highest accumulation of genetic variants in loop anchors in the center of communities indicates that these variants can disrupt loops and affect the network stability and consequently, the phenotype.}},
author = {{Acera Mateos, Pablo}},
language = {{eng}},
note = {{Student Paper}},
title = {{Disease susceptibility may be increased by accumulation of genetic variants in chromatin loops from disease-relevant cell-types}},
year = {{2018}},
}