Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

Alcohol use disorder (AUD) is likely associated with complex transcriptional alterations in addiction-relevant brain regions. We characterize AUD-associated differences in cell type-specific gene expression and chromatin accessibility in the caudate nucleus by conducting a single-nucleus RNA-seq assay and a single-nucleus RNA-seq + ATAC-seq (multiome) assay on caudate tissue from 143 human postmortem brains (74 with AUD). We identified 17 cell types. AUD was associated with a higher proportion of microglia in an activated state and more astrocytes in a reactive state. There was widespread evidence for differentially expressed genes across cell types with the most identified in oligodendrocytes and astrocytes, including genes involved in immune response and synaptic regulation, many of which appeared to be regulated in part by JUND and OLIG2. Microglia-astrocyte communication via interleukin-1 beta, and microglia-astrocyte-oligodendrocyte interaction via transforming growth factor beta 1 were increased in individuals with AUD. Expression quantitative trait loci analysis revealed potential driver genes of AUD, including ADAL, that may protect against AUD in medium spiny neurons and interneurons. This work provides a thorough profile of the effects of AUD in the human brain and identifies several promising genes for further study.

RFMix-reader: Accelerated reading and processing for local ancestry studies

Motivation

Local ancestry inference is a powerful technique in genetics, revealing population history and the genetic basis of diseases. It is particularly valuable for improving eQTL discovery and fine-mapping in admixed populations. Despite the widespread use of the RFMix software for local ancestry inference, large-scale genomic studies face challenges of high memory consumption and processing times when handling RFMix output files.

Results

Here, I present RFMix-reader , a new Python-based parsing software, designed to streamline the analysis of large-scale local ancestry datasets. This software prioritizes computational eiciency and memory optimization, leveraging GPUs when available for additional speed boosts. By overcoming these data processing hurdles, RFMix-reader empowers researchers to unlock the full potential of local ancestry data for understanding human health and health disparities.

Availability

RFMix-reader is freely available on PyPI at https://pypi.org/project/rfmix-reader/ , implemented in Python 3, and supported on Linux, Windows, and Mac OS.

Contact

KynonJade.Benjamin@libd.org.

Supplementary information

Supplementary data are available at https://rfmix-reader.readthedocs.io/en/latest/ .

Cell type-specific expression of angiotensin receptors in the human lung with implications for health, aging, and chronic disease

The renin-angiotensin system is a highly characterized integrative pathway in mammalian homeostasis whose clinical spectrum has been expanded to lung disorders such as chronic obstructive pulmonary disease (COPD)-emphysema, idiopathic pulmonary fibrosis (IPF), and COVID pathogenesis. Despite this widespread interest, specific localization of this receptor family in the mammalian lung is limited, partially due to the imprecision of available antibody reagents. In this study, we establish the expression pattern of the two predominant angiotensin receptors in the human lung, AGTR1 and AGTR2, using complementary and comprehensive bulk and single-cell RNA-sequence datasets that are publicly available. We show these two receptors have distinct localization patterns and developmental trajectories in the human lung, pericytes for AGTR1 and a subtype of alveolar epithelial type 2 cells for AGTR2. In the context of disease, we further pinpoint AGTR2 localization to the COPD-associated subpopulation of alveolar epithelial type 2 (AT2B) and AGTR1 localization to fibroblasts, where their expression is upregulated in individuals with COPD, but not in individuals with IPF. Finally, we examine the genetic variation of the angiotensin receptors, finding AGTR2 associated with lung phenotype (i.e., cystic fibrosis) via rs1403543. Together, our findings provide a critical foundation for delineating this pathway's role in lung homeostasis and constructing rational approaches for targeting specific lung disorders.