scHLAcount: Allele-specific HLA expression from single-cell gene expression data

AbstractStudies in bulk RNA sequencing data suggest cell-type and allele-specific expression of the human leukocyte antigen (HLA) genes. These loci are extremely diverse and they function as part of the major histocompatibility complex (MHC) which is responsible for antigen presentation. Mutation and or misregulation of expression of HLA genes has implications in diseases, especially cancer. Immune responses to tumor cells can be evaded through HLA loss of function. However, bulk RNA-seq does not fully disentangle cell type specificity and allelic expression. Here we present scHLAcount, a workflow for computing allele-specific molecule counts of the HLA genes in single cells an individualized reference. We demonstrate that scHLAcount can be used to find cell-type specific allelic expression of HLA genes in blood cells, and detect different allelic expression patterns between tumor and normal cells in patient biopsies. scHLAcount is available at https://github.com/10XGenomics/scHLAcount.

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A Bayesian mixture model for the analysis of allelic expression in single cells

Nature Communications ◽

10.1038/s41467-019-13099-0 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 3

Author(s):

Kwangbom Choi ◽

Narayanan Raghupathy ◽

Gary A. Churchill

Keyword(s):

Gene Expression ◽

Single Cell ◽

Mixture Model ◽

Time Course ◽

Single Cells ◽

Expression Patterns ◽

Allelic Expression ◽

Specific Expression ◽

Allele Specific Expression ◽

Allele Specific

AbstractAllele-specific expression (ASE) at single-cell resolution is a critical tool for understanding the stochastic and dynamic features of gene expression. However, low read coverage and high biological variability present challenges for analyzing ASE. We demonstrate that discarding multi-mapping reads leads to higher variability in estimates of allelic proportions, an increased frequency of sampling zeros, and can lead to spurious findings of dynamic and monoallelic gene expression. Here, we report a method for ASE analysis from single-cell RNA-Seq data that accurately classifies allelic expression states and improves estimation of allelic proportions by pooling information across cells. We further demonstrate that combining information across cells using a hierarchical mixture model reduces sampling variability without sacrificing cell-to-cell heterogeneity. We applied our approach to re-evaluate the statistical independence of allelic bursting and track changes in the allele-specific expression patterns of cells sampled over a developmental time course.

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Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data

Genes ◽

10.3390/genes11030240 ◽

2020 ◽

Vol 11 (3) ◽

pp. 240 ◽

Cited By ~ 2

Author(s):

Prashant N. M. ◽

Hongyu Liu ◽

Pavlos Bousounis ◽

Liam Spurr ◽

Nawaf Alomran ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Single Cells ◽

Sequencing Data ◽

Specific Expression ◽

Single Nucleotide ◽

Healthy Donors ◽

Allele Expression ◽

Single Cell Rna Sequencing ◽

Allele Specific

With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAFRNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAFRNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

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scBASE: A Bayesian mixture model for the analysis of allelic expression in single cells

10.1101/383224 ◽

2018 ◽

Author(s):

Kwangbom Choi ◽

Narayanan Raghupathy ◽

Gary A. Churchill

Keyword(s):

Single Cell ◽

Single Cells ◽

Allelic Expression ◽

Biological Variability ◽

Rna Seq ◽

Dynamic Features ◽

Specific Expression ◽

Bayesian Mixture Model ◽

Bayesian Mixture ◽

Allele Specific

Allele-specific expression (ASE) at single-cell resolution is a critical tool for understanding the stochastic and dynamic features of gene expression. However, low read coverage and high biological variability present challenges for analyzing ASE. We propose a new method for ASE analysis from single cell RNA-Seq data that accurately classifies allelic expression states and improves estimation of allelic proportions by pooling information across cells.

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Genome-wide analysis of allele-specific expression of genes in the model diatom Phaeodactylum tricornutum

Scientific Reports ◽

10.1038/s41598-021-82529-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Antoine Hoguin ◽

Achal Rastogi ◽

Chris Bowler ◽

Leila Tirichine

Keyword(s):

Phaeodactylum Tricornutum ◽

Protein Transport ◽

Natural Hybridization ◽

Allelic Expression ◽

Monoallelic Expression ◽

Sequencing Data ◽

Specific Expression ◽

Allele Specific Expression ◽

Biallelic Expression ◽

Allele Specific

AbstractRecent advances in next generation sequencing technologies have allowed the discovery of widespread autosomal allele-specific expression (aASE) in mammals and plants with potential phenotypic effects. Extensive numbers of genes with allele-specific expression have been described in the diatom Fragilariopsis cylindrus in association with adaptation to external cues, as well as in Fistulifera solaris in the context of natural hybridization. However, the role of aASE and its extent in diatoms remain elusive. In this study, we investigate allele-specific expression in the model diatom Phaeodactylum tricornutum by the re-analysis of previously published whole genome RNA sequencing data and polymorphism calling. We found that 22% of P. tricornutum genes show moderate bias in allelic expression while 1% show nearly complete monoallelic expression. Biallelic expression associates with genes encoding components of protein metabolism while moderately biased genes associate with functions in catabolism and protein transport. We validated candidate genes by pyrosequencing and found that moderate biases in allelic expression were less stable than monoallelically expressed genes that showed consistent bias upon experimental validations at the population level and in subcloning experiments. Our approach provides the basis for the analysis of aASE in P. tricornutum and could be routinely implemented to test for variations in allele expression under different environmental conditions.

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Identification of Nogo as a novel indicator of heart failure

Physiological Genomics ◽

10.1152/physiolgenomics.00200.2007 ◽

2008 ◽

Vol 32 (2) ◽

pp. 182-189 ◽

Cited By ~ 21

Author(s):

Tara A. Bullard ◽

Tricia L. Protack ◽

Frédérick Aguilar ◽

Suveer Bagwe ◽

H. Todd Massey ◽

...

Keyword(s):

Gene Expression ◽

Heart Failure ◽

Animal Models ◽

Expression Patterns ◽

Left Ventricular ◽

Cell Type ◽

Cell Type Specificity ◽

Novel Genes ◽

Specific Expression ◽

Adrenergic Signaling

Numerous genetically engineered animal models of heart failure (HF) exhibit multiple characteristics of human HF, including aberrant β-adrenergic signaling. Several of these HF models can be rescued by cardiac-targeted expression of the Gβγ inhibitory carboxy-terminus of the β-adrenergic receptor kinase (βARKct). We recently reported microarray analysis of gene expression in multiple animal models of HF and their βARKct rescue, where we identified gene expression patterns distinct and predictive of HF and rescue. We have further investigated the muscle LIM protein knockout model of HF (MLP−/−), which closely parallels human dilated cardiomyopathy disease progression and aberrant β-adrenergic signaling, and their βARKct rescue. A group of known and novel genes was identified and validated by quantitative real-time PCR whose expression levels predicted phenotype in both the larger HF group and in the MLP−/− subset. One of these novel genes is herein identified as Nogo, a protein widely studied in the nervous system, where it plays a role in regeneration. Nogo expression is altered in HF and normalized with rescue, in an isoform-specific manner, using left ventricular tissue harvested from both animal and human subjects. To investigate cell type-specific expression of Nogo in the heart, immunofluorescence and confocal microscopy were utilized. Nogo expression appears to be most clearly associated with cardiac fibroblasts. To our knowledge, this is the first report to demonstrate the relationship between Nogo expression and HF, including cell-type specificity, in both mouse and human HF and phenotypic rescue.

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HLA allele-specific expression loss in tumors can shorten survival and hinder immunotherapy

10.1101/2020.09.30.20204875 ◽

2020 ◽

Author(s):

Ioan Filip ◽

Rose Orenbuch ◽

Junfei Zhao ◽

Gulam Manji ◽

Evangelina López de Maturana ◽

...

Keyword(s):

Overall Survival ◽

Human Leukocyte ◽

Prognostic Indicator ◽

Cancer Prognosis ◽

Sequencing Data ◽

Specific Expression ◽

Allele Specific Expression ◽

Allele Specific ◽

Tumor Types ◽

Expression Loss

AbstractEfficient presentation of aberrant peptide fragments by the human leukocyte antigen class I (HLA-I) genes is necessary for immune detection and killing of cancer cells. Patient HLA-I genotypes are known to impact the efficacy of cancer immunotherapy, and the somatic loss of HLA-I heterozygosity has been established as a factor in immune evasion. While global deregulated expression of HLA-I has been reported in different tumor types, the role of HLA-I allele-specific expression loss – that is, the preferential RNA expression loss of specific HLA-I alleles – has not been fully characterized in cancer. In the present study, we quantified HLA-I allele-specific expression (ASE) across eleven TCGA tumor types using a novel method from input RNA and whole-exome sequencing data. Allele-specific loss in at least one of the three HLA-I genes (ASE loss) was pervasive and associated to worse overall survival across tumor types, including pancreatic adenocarcinomas, prostate carcinomas and glioblastomas, among others. In particular, our analysis shows that detection of neoantigens with binding affinity to the specific HLA-I genes subject to ASE loss was a top prognostic indicator of overall survival. Additionally, we found that ASE loss hindered immunotherapy in retrospective analyses. Together, these results highlight the prevalence of HLA-I ASE loss – a previously uncharacterized phenomenon in cancer – and provide initial evidence of its clinical significance in cancer prognosis and immunotherapy treatment.

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A nervous system-specific subnuclear organelle in Caenorhabditis elegans

Genetics ◽

10.1093/genetics/iyaa016 ◽

2021 ◽

Vol 217 (1) ◽

Author(s):

Kenneth Pham ◽

Neda Masoudi ◽

Eduardo Leyva-Díaz ◽

Oliver Hobert

Keyword(s):

Nervous System ◽

Caenorhabditis Elegans ◽

Homeobox Gene ◽

Cell Types ◽

Nuclear Bodies ◽

Loss Of Function ◽

Cell Type ◽

Cell Type Specificity ◽

Splicing Speckles ◽

Polycomb Bodies

Abstract We describe here phase-separated subnuclear organelles in the nematode Caenorhabditis elegans, which we term NUN (NUclear Nervous system-specific) bodies. Unlike other previously described subnuclear organelles, NUN bodies are highly cell type specific. In fully mature animals, 4–10 NUN bodies are observed exclusively in the nucleus of neuronal, glial and neuron-like cells, but not in other somatic cell types. Based on co-localization and genetic loss of function studies, NUN bodies are not related to other previously described subnuclear organelles, such as nucleoli, splicing speckles, paraspeckles, Polycomb bodies, promyelocytic leukemia bodies, gems, stress-induced nuclear bodies, or clastosomes. NUN bodies form immediately after cell cycle exit, before other signs of overt neuronal differentiation and are unaffected by the genetic elimination of transcription factors that control many other aspects of neuronal identity. In one unusual neuron class, the canal-associated neurons, NUN bodies remodel during larval development, and this remodeling depends on the Prd-type homeobox gene ceh-10. In conclusion, we have characterized here a novel subnuclear organelle whose cell type specificity poses the intriguing question of what biochemical process in the nucleus makes all nervous system-associated cells different from cells outside the nervous system.

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Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

10.1101/2020.10.21.349019 ◽

2020 ◽

Author(s):

Nil Aygün ◽

Angela L. Elwell ◽

Dan Liang ◽

Michael J. Lafferty ◽

Kerry E. Cheek ◽

...

Keyword(s):

Gene Expression ◽

Regulatory Elements ◽

Regulatory Mechanisms ◽

Specific Gene ◽

Cell Type ◽

Specific Expression ◽

Risk Variants ◽

Allele Specific ◽

Cell Type Specific ◽

Regulatory Effects

SummaryInterpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is mainly performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements of cells present during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74). Using colocalization and TWAS, we uncover cell-type specific regulatory mechanisms underlying risk for these traits.

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Cell-type Specific Expression Quantitative Trait Loci Associated with Alzheimer Disease in Blood and Brain Tissue

10.1101/2020.11.23.20237008 ◽

2020 ◽

Author(s):

Devanshi Patel ◽

Xiaoling Zhang ◽

John J. Farrell ◽

Jaeyoon Chung ◽

Thor D. Stein ◽

...

Keyword(s):

Gene Expression ◽

Quantitative Trait ◽

Expression Patterns ◽

Regulation Of Gene Expression ◽

Cell Types ◽

Eqtl Analysis ◽

Cell Type ◽

Specific Expression ◽

Cell Type Specific Expression ◽

Cell Type Specific

ABSTRACTBecause regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell-types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5,257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1Mb of genes was evaluated using linear regression models for unrelated subjects and linear mixed models for related subjects. Cell type-specific eQTL (ct-eQTL) models included an interaction term for expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2,533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell-types is supported by the observation that a large portion of GWS ct-eQTLs map within 1Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type specific analysis.

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Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo)

Animals ◽

10.3390/ani9100727 ◽

2019 ◽

Vol 9 (10) ◽

pp. 727

Author(s):

Kyu-Sang Lim ◽

Sun-Sik Chang ◽

Bong-Hwan Choi ◽

Seung-Hwan Lee ◽

Kyung-Tai Lee ◽

...

Keyword(s):

Phenotypic Variation ◽

Expression Patterns ◽

Monoallelic Expression ◽

Specific Expression ◽

Adult Cattle ◽

Korean Cattle ◽

Family Trio ◽

Epigenetic Effects ◽

Genome Wide ◽

Allele Specific

The functional hemizygosity could be caused by the MAE of a given gene and it can be one of the sources to affect the phenotypic variation in cattle. We aimed to identify MAE genes across the transcriptome in Korean cattle (Hanwoo). For three Hanwoo family trios, the transcriptome data of 17 tissues were generated in three offspring. Sixty-two MAE genes had a monoallelic expression in at least one tissue. Comparing genotypes among each family trio, the preferred alleles of 18 genes were identified (maternal expression, n = 9; paternal expression, n = 9). The MAE genes are involved in gene regulation, metabolic processes, and immune responses, and in particular, six genes encode transcription factors (FOXD2, FOXM1, HTATSF1, SCRT1, NKX6-2, and UBN1) with tissue-specific expression. In this study, we report genome-wide MAE genes in seventeen tissues of adult cattle. These results could help to elucidate epigenetic effects on phenotypic variation in Hanwoo.

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