A vast resource of allelic expression data spanning human tissues

AbstractAllele specific expression (ASE) analysis robustly measurescisregulatory effects. Here, we present a vast ASE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of ASE at the SNP-level and 153 million measurements at the haplotype-level. In addition, we developed an extension of our tool phASER that allows effect sizes ofcisregulatory variants to be estimated using haplotype-level ASE data. This ASE resource is the largest to date and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

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A vast resource of allelic expression data spanning human tissues

Genome Biology ◽

10.1186/s13059-020-02122-z ◽

2020 ◽

Vol 21 (1) ◽

Cited By ~ 2

Author(s):

Stephane E. Castel ◽

◽

François Aguet ◽

Pejman Mohammadi ◽

Kristin G. Ardlie ◽

...

Keyword(s):

Effect Sizes ◽

Allelic Expression ◽

Human Tissues ◽

Expression Data ◽

Future Studies ◽

Regulatory Variation ◽

Regulatory Variants ◽

Level Data ◽

Allele Expression ◽

Regulatory Effects

Abstract Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

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Genotype-Based Test in Mapping Cis-Regulatory Variants from Allele-Specific Expression Data

PLoS ONE ◽

10.1371/journal.pone.0038667 ◽

2012 ◽

Vol 7 (6) ◽

pp. e38667 ◽

Cited By ~ 4

Author(s):

Jean Francois Lefebvre ◽

Emilio Vello ◽

Bing Ge ◽

Stephen B. Montgomery ◽

Emmanouil T. Dermitzakis ◽

...

Keyword(s):

Expression Data ◽

Specific Expression ◽

Allele Specific Expression ◽

Regulatory Variants ◽

Allele Specific

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Linear modeling reveals a predominance of cis- over trans- regulatory effects in wild and domesticated barley

10.1101/661926 ◽

2019 ◽

Author(s):

Matthew Haas ◽

Axel Himmelbach ◽

Martin Mascher

Keyword(s):

Crop Improvement ◽

Rna Seq ◽

Linear Modeling ◽

Specific Expression ◽

Allele Specific Expression ◽

Genetic Changes ◽

Regulatory Changes ◽

Allele Specific ◽

Regulatory Effects ◽

Practical Implications

AbstractBarley, like other crops, has experienced a series of genetic changes that have impacted its architecture and growth habit to suit the needs of humans, termed the domestication syndrome. Domestication also resulted in a concomitant bottleneck that reduced sequence diversity in genes and regulatory regions. Little is known about regulatory changes resulting from domestication in barley. We used RNA-seq to examine allele-specific expression (ASE) in hybrids between wild and domesticated barley. Our results show that most genes have conserved regulation. In contrast to studies of allele specific expression in interspecific hybrids, we find almost a complete absence of trans effects. We also find that cis regulation is largely stable in response to short-term cold stress. Our study has practical implications for crop improvement using wild relatives. Genes regulated in cis are more likely to be expressed in a new genetic background at the same level as in their native background.

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WED 139 Gene expression regulation in CD4+ t-cell dysfunction in ms

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2018-abn.57 ◽

2018 ◽

Vol 89 (10) ◽

pp. A16.1-A16

Author(s):

Hrastelj James ◽

Bray Nicholas ◽

Williams Nigel ◽

Robertson Neil

Keyword(s):

Gene Expression ◽

T Lymphocytes ◽

Gene Expression Regulation ◽

Cell Types ◽

Expression Data ◽

Specific Expression ◽

Complex Disorders ◽

Risk Variants ◽

Allele Specific ◽

Regulatory Effects

BackgroundGenetic risk variants for complex disorders such as multiple sclerosis (MS) rarely encode protein. Growing evidence suggests risk variants regulate gene expression in specific disease-relevant cells by altering regulatory genetic sequences. This can be explored by correlating genotype at risk loci with expression of nearby genes (cis-regulation), with greatest sensitivity demonstrated in the most relevant cell types. Identifying genes under regulation by the MS risk variants could be a crucial step in identifying novel therapeutic targets.Aims1) Interrogate MS risk loci for cis-regulatory effects using allele-specific expression (ASE) analysis. 2) Establish a publicly available resource of genome-wide RNA-seq expression data in CSF-derived CD4 +T lymphocytes. 3) Correlate gene expression data with longitudinal clinical data to seek biomarkers of prognosis.Method and progressWe have extracted RNA from FACS-sorted CSF-derived CD4 +T lymphocytes from over 100 individuals. cDNA library preparation and sequencing for each sample is underway.Data analysisASE analysis makes use of a pre-selected transcribed SNP to differentiate maternal and paternal transcripts of each gene of interest. When an individual is heterozygous at an additional functional regulatory locus the ratio of maternal: paternal expression will deviate from 1:1. Each MS risk locus will be interrogated for this effect.

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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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