Allele Specific Expression in Human – Genomic Makeup and Phenotypic Implications

Mapping Intimacies ◽

10.1101/757997 ◽

2019 ◽

Author(s):

Kerem Wainer-Katsir ◽

Michal Linial

Keyword(s):

Statistical Significance ◽

Healthy Human ◽

Specific Expression ◽

Allele Specific Expression ◽

Distribution Width ◽

Allele Specific ◽

Mhc Locus ◽

Phenotype Diversity ◽

The Uk ◽

Gwas Catalog

AbstractThe allele-specific expression phenomenon refers to unbalanced expression from the two parental alleles in a tissue of a diploid organism. AlleleDB is a high-quality resource that reports on about 30,000 ASE variants (ASE-V) from hundreds of human samples. In this study, we present the genomic characteristics and phenotypic implications of ASE. We identified tens of segments with extreme density of ASE-V, many of them are located at the major histocompatibility complex (MHC) locus. Notably, at a resolution of 100 nucleotides, the likelihood of ASE-V increases with the density of polymorphic sites. Another dominant trend of ASE is a strong bias of the expression to the major allele. This observation relies on the known allele frequencies in the healthy human population. Overlap of ASE-V and GWAS associations was calculated for 48 phenotypes from the UK-Biobank. ASE-V were significantly associated with a risk for inflammation (e.g. asthma), autoimmunity (e.g., rheumatoid arthritis, multiple sclerosis, and type 1 diabetes) and several blood cell traits (e.g., red cell distribution width). At the level of the ASE-genes, we seek association with all traits and conditions reported in the GWAS catalog. The statistical significance of ASE-genes to GWAS catalog reveals association with the susceptibility to virus infection, autoimmunity, inflammation, allergies, blood cancer and more. We postulate that ASE determines phenotype diversity between individuals and the risk for a variety of immune-related conditions.

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Inferring the genetic architecture of expression variation from replicated high throughput allele-specific expression experiments

10.1101/699074 ◽

2019 ◽

Author(s):

Xinwen Zhang ◽

J.J. Emerson

Keyword(s):

False Positive ◽

Statistical Significance ◽

False Positive Rate ◽

Regulatory Sequences ◽

Binomial Model ◽

Specific Expression ◽

Allele Specific Expression ◽

Expression Variation ◽

Positive Rate ◽

Allele Specific

AbstractGene expression variation between alleles in a diploid cell is mediated by variation in cis regulatory sequences, which usually refers to the differences in DNA sequence between two alleles near the gene of interest. Expression differences caused by cis variation has been estimated by the ratio of the expression level of the two alleles under a binomial model. However, the binomial model underestimates the variance among replicated experiments resulting in the exaggerated statistical significance of estimated cis effects and thus many false discoveries of cis-affected genes. Here we describe a beta-binomial model that estimates the cis-effect for each gene while permitting overdispersion of variance among replicates. We demonstrated with simulated null data (data without true cis-effect) that the new model fits the true distribution better, resulting in approximately 5% false positive rate under 5% significance level in all null datasets, considerably better than the 6%-40% false positive rate of the binomial model. Additional replicates increase the performance of the beta-binomial model but not of the binomial model. We also collected new allele-specific expression data from an experiment comprised of 20 replicates of a yeast hybrid (YPS128/RM11-1a). We eliminated the mapping bias problem with de novo assemblies of the two parental genomes. By applying the beta-binomial model to this dataset, we found that cis effects are ubiquitous, affecting around 70% of genes. However, most of these changes are small in magnitude. The high number of replicates enabled us a better approximation of cis landscape within species and also provides a resource for future exploration for better models.

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Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas

10.1101/2021.01.25.428155 ◽

2021 ◽

Author(s):

Weisheng Wu ◽

Jennie L. Lovett ◽

Kerby Shedden ◽

Beverly I. Strassmann ◽

Claudius Vincenz

Keyword(s):

Placental Tissue ◽

Read Depth ◽

Epigenetic Mechanism ◽

Imprinted Genes ◽

Rna Seq ◽

Healthy Human ◽

Specific Expression ◽

Allele Specific Expression ◽

Allele Specific ◽

Maternal Resources

AbstractGenomic imprinting is an epigenetic mechanism that results in allele specific expression (ASE) based on parent of origin. It is known to play a role in the prenatal and postnatal allocation of maternal resources in mammals. ASE detected by whole transcriptome RNA-seq (wht-RNAseq) has been widely used to analyze imprinted genes using reciprocal crosses in mice to generate large numbers of informative SNPs. Studies in humans are more challenging due to the paucity of SNPs and the poor preservation of RNA in term placentas and other tissues. Targeted RNA-seq (tar-RNAseq) can potentially mitigate these challenges by focusing sequencing resources on the regions of interest in the transcriptome. Here we compared tar-RNAseq and wht-RNAseq in a study of ASE in known imprinted genes in placental tissue collected from a healthy human cohort in Mali, West Africa. As expected, tar-RNAseq substantially improved the coverage of SNPs. Compared to wht-RNAseq, tar-RNAseq produced on average four times more SNPs in twice as many genes per sample and read depth at the SNPs increased 4-fold. In previous research on humans, discordant ASE values for SNPs of the same gene have limited the ability to accurately quantify ASE. We show that tar-RNAseq reduces this limitation as it unexpectedly increased the concordance of ASE between SNPs of the same gene, even in cases of degraded RNA. Studies aimed at discovering associations between individual variation in ASE and phenotypes in mammals and flowering plants will benefit from the improved power and accuracy of tar-RNAseq.

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Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab176 ◽

2021 ◽

Author(s):

Weisheng Wu ◽

Jennie L Lovett ◽

Kerby Shedden ◽

Beverly I Strassmann ◽

Claudius Vincenz

Keyword(s):

Placental Tissue ◽

Read Depth ◽

Epigenetic Mechanism ◽

Imprinted Genes ◽

Rna Seq ◽

Healthy Human ◽

Specific Expression ◽

Allele Specific Expression ◽

Allele Specific ◽

Maternal Resources

Abstract Genomic imprinting is an epigenetic mechanism that results in allele specific expression (ASE) based on parent of origin. It is known to play a role in the prenatal and postnatal allocation of maternal resources in mammals. ASE detected by whole transcriptome RNA-seq (wht-RNAseq) has been widely used to analyze imprinted genes using reciprocal crosses in mice to generate large numbers of informative SNPs. Studies in humans are more challenging due to the paucity of SNPs and the poor preservation of RNA in term placentas and other tissues. Targeted RNA-seq (tar-RNAseq) can potentially mitigate these challenges by focusing sequencing resources on the regions of interest in the transcriptome. Here we compared tar-RNAseq and wht-RNAseq in a study of ASE in known imprinted genes in placental tissue collected from a healthy human cohort in Mali, West Africa. As expected, tar-RNAseq substantially improved the coverage of SNPs. Compared to wht-RNAseq, tar-RNAseq produced on average four times more SNPs in twice as many genes per sample and read depth at the SNPs increased 4-fold. In previous research on humans, discordant ASE values for SNPs of the same gene have limited the ability to accurately quantify ASE. We show that tar-RNAseq reduces this limitation as it unexpectedly increased the concordance of ASE between SNPs of the same gene, even in cases of degraded RNA. Studies aimed at discovering associations between individual variation in ASE and phenotypes in mammals and flowering plants will benefit from the improved power and accuracy of tar-RNAseq.

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Investigation of allele specific expression in various tissues of broiler chickens using the detection tool VADT

Scientific Reports ◽

10.1038/s41598-021-83459-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

M. Joseph Tomlinson ◽

Shawn W. Polson ◽

Jing Qiu ◽

Juniper A. Lake ◽

William Lee ◽

...

Keyword(s):

Broiler Chickens ◽

Nucleotide Polymorphisms ◽

Rna Seq ◽

Specific Expression ◽

Single Nucleotide ◽

Allele Specific Expression ◽

Detection Tool ◽

Commercial Broiler ◽

Significant Phenomenon ◽

Allele Specific

AbstractDifferential abundance of allelic transcripts in a diploid organism, commonly referred to as allele specific expression (ASE), is a biologically significant phenomenon and can be examined using single nucleotide polymorphisms (SNPs) from RNA-seq. Quantifying ASE aids in our ability to identify and understand cis-regulatory mechanisms that influence gene expression, and thereby assist in identifying causal mutations. This study examines ASE in breast muscle, abdominal fat, and liver of commercial broiler chickens using variants called from a large sub-set of the samples (n = 68). ASE analysis was performed using a custom software called VCF ASE Detection Tool (VADT), which detects ASE of biallelic SNPs using a binomial test. On average ~ 174,000 SNPs in each tissue passed our filtering criteria and were considered informative, of which ~ 24,000 (~ 14%) showed ASE. Of all ASE SNPs, only 3.7% exhibited ASE in all three tissues, with ~ 83% showing ASE specific to a single tissue. When ASE genes (genes containing ASE SNPs) were compared between tissues, the overlap among all three tissues increased to 20.1%. Our results indicate that ASE genes show tissue-specific enrichment patterns, but all three tissues showed enrichment for pathways involved in translation.

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