STAT3-mediated allelic imbalance of novel genetic variant rs1047643 and B cell specific super-enhancer in association with systemic lupus erythematosus
- HudsonAlpha Institute for Biotechnology, United States
- Zymo Research Corp, United States
Abstract
Mapping of allelic imbalance (AI) at heterozygous loci has the potential to establish links between genetic risk for disease and biological function. Leveraging multi-omics data for AI analysis and functional annotation, we discovered a novel functional risk variant rs1047643 at 8p23 in association with systemic lupus erythematosus (SLE). This variant displays dynamic AI of chromatin accessibility and allelic expression on FDFT1 gene in B cells with SLE. We further found a B-cell restricted super-enhancer (SE) that physically contacts with this SNP-residing locus, an interaction that also appears specifically in B cells. Quantitative analysis of chromatin accessibility and DNA methylation profiles further demonstrated that the SE exhibits aberrant activity in B cell development with SLE. Functional studies identified that STAT3, a master factor associated with autoimmune diseases, directly regulates both the AI of risk variant and the activity of SE in cultured B cells. Our study reveals that STAT3-mediated SE activity and cis-regulatory effects of SNP rs1047643 at 8p23 locus are associated with B cell deregulation in SLE.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 2-5.
-
Accessible chromatin profiles of B cell subsets from healthy and SLE subjectsNCBI Gene Expression Omnibus, GSE118253.
-
Effects of biobanking on chromatin accessibilityNCBI Gene Expression Omnibus, GSE71338.
-
Transcriptome profiles of B cell subsets from healthy and SLE subjectsNCBI Gene Expression Omnibus, GSE118254.
-
Gene expresison studies of lupus and healthy B cell subsets through RNA sequencingNCBI Gene Expression Omnibus, GSE92387.
-
DNA methylation profiles profiles of B cell subsets from healthy and SLE subjectsNCBI Gene Expression Omnibus, GSE118255.
-
HepG2 Hi-CNCBI Gene Expression Omnibus, GSE113405.
-
CHiCAGO: Robust Detection of DNA Looping Interactions in Capture Hi-C dataNCBI Gene Expression Omnibus, GSE81503.
Article and author information
Author details
Funding
HudsonAlpha Institute for biotechnology funds
- Yanfeng Zhang
- Devin M Absher
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Zhang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 728
- views
-
- 100
- downloads
-
- 7
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
STAT3-mediated allelic imbalance of novel genetic variant rs1047643 and B cell specific super-enhancer in association with systemic lupus erythematosus
eLife 11:e72837.
https://doi.org/10.7554/eLife.72837
Further reading
-
- Computational and Systems Biology
- Neuroscience
Accumulating evidence to make decisions is a core cognitive function. Previous studies have tended to estimate accumulation using either neural or behavioral data alone. Here we develop a unified framework for modeling stimulus-driven behavior and multi-neuron activity simultaneously. We applied our method to choices and neural recordings from three rat brain regions - the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS) - while subjects performed a pulse-based accumulation task. Each region was best described by a distinct accumulation model, which all differed from the model that best described the animal's choices. FOF activity was consistent with an accumulator where early evidence was favored while the ADS reflected near perfect accumulation. Neural responses within an accumulation framework unveiled a distinct association between each brain region and choice. Choices were better predicted from all regions using a comprehensive, accumulation-based framework and different brain regions were found to differentially reflect choice-related accumulation signals: FOF and ADS both reflected choice but ADS showed more instances of decision vacillation. Previous studies relating neural data to behaviorally-inferred accumulation dynamics have implicitly assumed that individual brain regions reflect the whole-animal level accumulator. Our results suggest that different brain regions represent accumulated evidence in dramatically different ways and that accumulation at the whole-animal level may be constructed from a variety of neural-level accumulators.
-
- Computational and Systems Biology
- Ecology
Environmental DNA (eDNA) is becoming an increasingly important tool in diverse scientific fields from ecological biomonitoring to wastewater surveillance of viruses. The fundamental challenge in eDNA analyses has been the bioinformatical assignment of reads to taxonomic groups. It has long been known that full probabilistic methods for phylogenetic assignment are preferable, but unfortunately, such methods are computationally intensive and are typically inapplicable to modern Next-Generation Sequencing data. We here present a fast approximate likelihood method for phylogenetic assignment of DNA sequences. Applying the new method to several mock communities and simulated datasets, we show that it identifies more reads at both high and low taxonomic levels more accurately than other leading methods. The advantage of the method is particularly apparent in the presence of polymorphisms and/or sequencing errors and when the true species is not represented in the reference database.
