RESUMEN
Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. Clustering chromatin accessibility profiles of 96,002 total nuclei identified 17 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type using individuals of European ancestry which identified 6,901 caQTLs at FDR < .10 and 4,220 caQTLs at FDR < .05, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,941 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs at 622 candidate causal variants, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naïve CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types.
Asunto(s)
Secuenciación de Inmunoprecipitación de Cromatina , Cromatina , Humanos , Cromatina/genética , Herencia Multifactorial , Leucocitos Mononucleares , Sitios de Carácter Cuantitativo/genéticaRESUMEN
High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the "GigaAssay", a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.
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VIH-1 , Productos del Gen tat del Virus de la Inmunodeficiencia Humana , Línea Celular , Duplicado del Terminal Largo de VIH , VIH-1/genética , Mutagénesis , Activación Transcripcional , Productos del Gen tat del Virus de la Inmunodeficiencia Humana/genética , Productos del Gen tat del Virus de la Inmunodeficiencia Humana/metabolismoRESUMEN
Dietary guidelines recommended by key health agencies are generally designed for a global population. However, ethnicity affects human disease and environment-gene interactions, including nutrient intake. Historically, isolated human populations with different genetic backgrounds have adapted to distinct environments with varying food sources. Ethnicity is relevant to the interaction of food intake with genes and disease susceptibility; yet major health agencies generally do not recommend food and nutrients codified by population genotypes and their frequencies. In this paper, we have consolidated published nutrigenetic variants and examine their frequencies in human superpopulations to prioritize these variants for future investigation of population-specific genotype-directed nutrition. The nutrients consumed by individuals interact with their genome and may alter disease risk. Herein, we searched the literature, designed a data model, and manually curated hundreds of papers. The resulting database houses 101 variants that reached significance (p < 0.05), from 35 population studies. Nutrigenetic variants associated with modified nutrient intake have the potential to reduce the risk of colorectal cancer, obesity, metabolic syndrome, type 2 diabetes, and several other diseases. Since many nutrigenetic studies have identified a major variant in some populations, we suggest that superpopulation-specific genotype-directed nutrition modifications be prioritized for future study and evaluation. Genotype-directed nutrition approaches to dietary modification have the potential to reduce disease risk in select human populations.
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Nutrigenómica/métodos , Genotipo , Humanos , Estado Nutricional , Polimorfismo de Nucleótido Simple/genéticaRESUMEN
The data in this article are associated with the research paper "GigaAssay - an adaptable high-throughput saturation mutagenesis assay" [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the "GigaAssay". A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.
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We combined functional genomics and human genetics to investigate processes that affect type 1 diabetes (T1D) risk by mediating beta cell survival in response to proinflammatory cytokines. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) in beta cells using ATAC-seq and snATAC-seq and linked them to target genes using co-accessibility and HiChIP. Using a genome-wide CRISPR screen in EndoC-ßH1 cells, we identified 867 genes affecting cytokine-induced survival, and genes promoting survival and up-regulated in cytokines were enriched at T1D risk loci. Using SNP-SELEX, we identified 2,229 variants in cytokine-responsive cCREs altering transcription factor (TF) binding, and variants altering binding of TFs regulating stress, inflammation, and apoptosis were enriched for T1D risk. At the 16p13 locus, a fine-mapped T1D variant altering TF binding in a cytokine-induced cCRE interacted with SOCS1, which promoted survival in cytokine exposure. Our findings reveal processes and genes acting in beta cells during inflammation that modulate T1D risk.
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Respiratory failure associated with COVID-19 has placed focus on the lungs. Here, we present single-nucleus accessible chromatin profiles of 90,980 nuclei and matched single-nucleus transcriptomes of 46,500 nuclei in non-diseased lungs from donors of ~30 weeks gestation,~3 years and ~30 years. We mapped candidate cis-regulatory elements (cCREs) and linked them to putative target genes. We identified distal cCREs with age-increased activity linked to SARS-CoV-2 host entry gene TMPRSS2 in alveolar type 2 cells, which had immune regulatory signatures and harbored variants associated with respiratory traits. At the 3p21.31 COVID-19 risk locus, a candidate variant overlapped a distal cCRE linked to SLC6A20, a gene expressed in alveolar cells and with known functional association with the SARS-CoV-2 receptor ACE2. Our findings provide insight into regulatory logic underlying genes implicated in COVID-19 in individual lung cell types across age. More broadly, these datasets will facilitate interpretation of risk loci for lung diseases.
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COVID-19/genética , COVID-19/virología , Interacciones Microbiota-Huesped/genética , Pulmón/metabolismo , Pulmón/virología , Adulto , Factores de Edad , Células Epiteliales Alveolares/clasificación , Células Epiteliales Alveolares/metabolismo , Células Epiteliales Alveolares/virología , Enzima Convertidora de Angiotensina 2/genética , Enzima Convertidora de Angiotensina 2/metabolismo , COVID-19/metabolismo , Preescolar , Mapeo Cromosómico , Perfilación de la Expresión Génica , Variación Genética , Interacciones Microbiota-Huesped/fisiología , Humanos , Recién Nacido , Proteínas de Transporte de Membrana/genética , Proteínas de Transporte de Membrana/metabolismo , Pandemias , Receptores Virales/genética , Receptores Virales/metabolismo , SARS-CoV-2/genética , SARS-CoV-2/patogenicidad , Análisis de la Célula Individual , Internalización del VirusRESUMEN
All translated proteins end with a carboxylic acid commonly called the C-terminus. Many short functional sequences (minimotifs) are located on or immediately proximal to the C-terminus. However, information about the function of protein C-termini has not been consolidated into a single source. Here, we built a new "C-terminome" database and web system focused on human proteins. Approximately 3,600 C-termini in the human proteome have a minimotif with an established molecular function. To help evaluate the function of the remaining C-termini in the human proteome, we inferred minimotifs identified by experimentation in rodent cells, predicted minimotifs based upon consensus sequence matches, and predicted novel highly repetitive sequences in C-termini. Predictions can be ranked by enrichment scores or Gene Evolutionary Rate Profiling (GERP) scores, a measurement of evolutionary constraint. By searching for new anchored sequences on the last 10 amino acids of proteins in the human proteome with lengths between 3-10 residues and up to 5 degenerate positions in the consensus sequences, we have identified new consensus sequences that predict instances in the majority of human genes. All of this information is consolidated into a database that can be accessed through a C-terminome web system with search and browse functions for minimotifs and human proteins. A known consensus sequence-based predicted function is assigned to nearly half the proteins in the human proteome. Weblink: http://cterminome.bio-toolkit.com.