Biology subjects

Mu, Z.

Publications and source records attributed to Mu, Z..

21 records · Page 2Linked to original sources

bioRxiv2020

Impact of cell-type and context-dependent regulatory variants on human immune traits

The effects of trait-associated variants are often studied in a single relevant cell-type or context. However, for many complex traits, multiple cell-types are involved. This applies particularly to immune-related traits, for which many immune cell-types and contexts play a role. Here, we studied the impact of immune gene regulatory variants on complex traits to better understand genetic risk mediated through immune cell-types. We identified 26,271 expression quantitative trait loci (QTLs) and 23,121 splicing QTLs in 18 immune cell-types, and analyzed their overlap with trait-associated loci from 72 genome-wide association studies (GWAS). We showed that effects on RNA expression and splicing in immune cells colocalize with an average of 40.4% and 27.7% GWAS loci for immune-related and non-immune traits, respectively. Notably, we found that a large number of loci (mean: 14%) colocalize with splicing QTLs but not expression QTLs. The 60% GWAS loci without colocalization harbor genes that have lower expression levels, are less tolerant to loss-of-function mutations, and more enhancerrich than genes at colocalized loci. To further investigate the 60% GWAS loci not explained by our regulatory QTLs, we collected H3K27ac CUT&Tag data from rheumatoid arthritis (RA) and healthy controls. We found several unexplained GWAS hits lying within regions with higher H3K27ac activity in RA patients. We also observed that enrichment of RA GWAS heritability is greater in H3K27ac regions in immune cell-types from RA patients compared to healthy controls. Our study paves the way for future QTL studies to elucidate the mechanisms of as yet unexplained GWAS loci.

genomics↗

bioRxiv2020

Alignment of single-cell RNA-seq samples without over-correction using kernel density matching

Single-cell RNA sequencing (scRNA-seq) technology is poised to replace bulk cell RNA sequencing for most biological and medical applications as it allows users to measure gene expression levels in a cell-type-specific manner. However, data produced by scRNA-seq often exhibit batch effects that can be specific to a cell-type, to a sample, or to an experiment, which prevent integration or comparisons across multiple experiments. Here, we present Dmatch, a method that leverages an external expression atlas of human primary cells and kernel density matching to align multiple scRNA-seq experiments for downstream biological analysis. Dmatch facilitates alignment of scRNA-seq datasets with cell-types that may overlap only partially, and thus allows integration of multiple distinct scRNA-seq experiments to extract biological insights. In simulation, Dmatch compares favorably to other alignment methods, both in terms of reducing sample-specific clustering, and in terms of avoiding over-correction. When applied to scRNA-seq data collected from clinical samples in a healthy individual and five autoimmune disease patients, Dmatch enabled cell-type-specific differential gene expression comparisons across biopsy sites and disease conditions, and uncovered a shared population of pro-inflammatory monocytes across biopsy sites in RA patients. We further show that Dmatch increases the number of eQTLs mapped from population scRNA-seq data. Dmatch is fast, scalable, and improves the utility of scRNA-seq for several important applications. Dmatch is freely available online (https://qzhan321.github.io/dmatch/).

bioinformatics↗

bioRxiv2019

Disruption of the HIV-1 Envelope allosteric network blocks CD4-induced rearrangements

The trimeric HIV-1 Envelope protein (Env) mediates viral-host cell fusion via a network of conformational transitions, with allosteric elements in each protomer orchestrating host receptor-induced exposure of the co-receptor binding site and fusion elements. To understand the molecular details of this allostery, we introduced Env mutations aimed to prevent CD4-induced rearrangements in the HIV-1 BG505 Env trimer. Binding analysis performed on the soluble ectodomain BG505 SOSIP Env trimers, cell-surface expressed BG505 full-length trimers and single-molecule Forster Resonance Energy Transfer (smFRET) performed on the full-length virion-bound Env confirmed that these mutations prevented CD4-induced transitions of the HIV-1 Env. Structural analysis by single-particle cryo-electron microscopy performed on the BG505 SOSIP mutant Env proteins revealed rearrangements in the gp120 topological layer contacts with gp41. Specifically, a conserved tryptophan at position 571 (W571) was displaced from its typical pocket at the interface of gp120 topological layers 1 and 2 by lysine 567, disrupting key gp120-gp41 contacts and rendering the Env insensitive to CD4 binding. Vector based analysis of closed Env SOSIP structures revealed the newly designed trimers exhibited a quaternary structure distinct from that typical of SOSIPs and residing near a cluster of Env trimers bound to vaccine-induced fusion peptide-directed antibodies (vFP Mabs). These results reveal the critical function of W571 as a conformational switch in Env allostery and receptor-mediated viral entry and provide insights on Env conformation that are relevant for vaccine design.

biochemistry↗