scholarly journals TIGER: The gene expression regulatory variation landscape of human pancreatic islets

2021 ◽  
Author(s):  
Lorena Alonso ◽  
Anthony Piron ◽  
Ignasi Moran ◽  
Marta Guindo-Martinez ◽  
Silvia Bonas-Guarch ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Low Frequency ◽  
Tissue Expression ◽  
Human Islet ◽  
Rna Seq ◽  
Specific Expression ◽  
Data Resource ◽  
Allele Specific ◽  
Insight Into

GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

scholarly journals Assessing allele specific expression across multiple tissues from RNA-seq read data

2014 ◽  
Author(s):  
Matti Pirinen ◽  
Tuuli Lappalainen ◽  
Noah A Zaitlen ◽  
GTEx Consortium ◽  
Emmanouil T Dermitzakis ◽  
...  
Keyword(s):  
Expression Profile ◽  
Rare Variants ◽  
Real Data ◽  
Tissue Expression ◽  
Rna Seq ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Expression Studies ◽  
Regulatory Impact ◽  
Allele Specific

Motivation: RNA sequencing enables allele specific expression (ASE) studies that complement standard genotype expression studies for common variants and, importantly, also allow measuring the regulatory impact of rare variants. The Genotype-Tissue Expression project (GTEx) is collecting RNA-seq data on multiple tissues of a same set of individuals and novel methods are required for the analysis of these data. Results: We present a statistical method to compare different patterns of ASE across tissues and to classify genetic variants according to their impact on the tissue-wide expression profile. We focus on strong ASE effects that we are expecting to see for protein-truncating variants, but our method can also be adjusted for other types of ASE effects. We illustrate the method with a real data example on a tissue-wide expression profile of a variant causal for lipoid proteinosis, and with a simulation study to assess our method more generally. Availability: MAMBA software: http://birch.well.ox.ac.uk/~rivas/mamba/ R source code and data examples: http://www.iki.fi/mpirinen/ Contact: [email protected] [email protected]

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

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.

scholarly journals Replicate sequencing libraries are important for quantification of allelic imbalance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Asia Mendelevich ◽  
Svetlana Vinogradova ◽  
Saumya Gupta ◽  
Andrey A. Mironov ◽  
Shamil R. Sunyaev ◽  
...  
Keyword(s):  
Allelic Imbalance ◽  
False Positive Rate ◽  
Error Rates ◽  
Differential Analysis ◽  
Rna Seq ◽  
Specific Expression ◽  
Technical Noise ◽  
Specific Analysis ◽  
Positive Rate ◽  
Allele Specific

AbstractA sensitive approach to quantitative analysis of transcriptional regulation in diploid organisms is analysis of allelic imbalance (AI) in RNA sequencing (RNA-seq) data. A near-universal practice in such studies is to prepare and sequence only one library per RNA sample. We present theoretical and experimental evidence that data from a single RNA-seq library is insufficient for reliable quantification of the contribution of technical noise to the observed AI signal; consequently, reliance on one-replicate experimental design can lead to unaccounted-for variation in error rates in allele-specific analysis. We develop a computational approach, Qllelic, that accurately accounts for technical noise by making use of replicate RNA-seq libraries. Testing on new and existing datasets shows that application of Qllelic greatly decreases false positive rate in allele-specific analysis while conserving appropriate signal, and thus greatly improves reproducibility of AI estimates. We explore sources of technical overdispersion in observed AI signal and conclude by discussing design of RNA-seq studies addressing two biologically important questions: quantification of transcriptome-wide AI in one sample, and differential analysis of allele-specific expression between samples.

scholarly journals Analysis of Allele-Specific Expression in Mouse Liver by RNA-Seq: A Comparison With Cis-eQTL Identified Using Genetic Linkage

Genetics ◽  
2013 ◽  
Vol 195 (3) ◽  
pp. 1157-1166 ◽  
Author(s):  
Sandrine Lagarrigue ◽  
Lisa Martin ◽  
Farhad Hormozdiari ◽  
Pierre-François Roux ◽  
Calvin Pan ◽  
...  
Keyword(s):  
Mouse Liver ◽  
Genetic Linkage ◽  
Rna Seq ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Allele Specific

scholarly journals Patterns of genome-wide allele-specific expression in hybrid rice and the implications on the genetic basis of heterosis

2019 ◽  
Vol 116 (12) ◽  
pp. 5653-5658 ◽  
Author(s):  
Lin Shao ◽  
Feng Xing ◽  
Conghao Xu ◽  
Qinghua Zhang ◽  
Jian Che ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Molecular Mechanisms ◽  
Sequencing Data ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Parental Allele ◽  
Genetic Components ◽  
Genome Wide ◽  
A Genome ◽  
Allele Specific

Utilization of heterosis has greatly increased the productivity of many crops worldwide. Although tremendous progress has been made in characterizing the genetic basis of heterosis using genomic technologies, molecular mechanisms underlying the genetic components are much less understood. Allele-specific expression (ASE), or imbalance between the expression levels of two parental alleles in the hybrid, has been suggested as a mechanism of heterosis. Here, we performed a genome-wide analysis of ASE by comparing the read ratios of the parental alleles in RNA-sequencing data of an elite rice hybrid and its parents using three tissues from plants grown under four conditions. The analysis identified a total of 3,270 genes showing ASE (ASEGs) in various ways, which can be classified into two patterns: consistent ASEGs such that the ASE was biased toward one parental allele in all tissues/conditions, and inconsistent ASEGs such that ASE was found in some but not all tissues/conditions, including direction-shifting ASEGs in which the ASE was biased toward one parental allele in some tissues/conditions while toward the other parental allele in other tissues/conditions. The results suggested that these patterns may have distinct implications in the genetic basis of heterosis: The consistent ASEGs may cause partial to full dominance effects on the traits that they regulate, and direction-shifting ASEGs may cause overdominance. We also showed that ASEGs were significantly enriched in genomic regions that were differentially selected during rice breeding. These ASEGs provide an index of the genes for future pursuit of the genetic and molecular mechanism of heterosis.

Variant calling from RNA-seq data of the brain transcriptome of pigs and its application for allele-specific expression and imprinting analysis

Gene ◽  
2018 ◽  
Vol 641 ◽  
pp. 367-375 ◽  
Author(s):  
Maria Oczkowicz ◽  
Tomasz Szmatoła ◽  
Katarzyna Piórkowska ◽  
Katarzyna Ropka-Molik
Keyword(s):  
Variant Calling ◽  
Rna Seq ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Brain Transcriptome ◽  
Allele Specific ◽  
The Brain

scholarly journals Hierarchical analysis of RNA-seq reads improves the accuracy of allele-specific expression

2018 ◽  
Vol 34 (13) ◽  
pp. 2177-2184 ◽  
Author(s):  
Narayanan Raghupathy ◽  
Kwangbom Choi ◽  
Matthew J Vincent ◽  
Glen L Beane ◽  
Keith S Sheppard ◽  
...  
Keyword(s):  
Hierarchical Analysis ◽  
Rna Seq ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Allele Specific

scholarly journals Improved haplotype inference by exploiting long-range linking and allelic imbalance in RNA-seq datasets

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily Berger ◽  
Deniz Yorukoglu ◽  
Lillian Zhang ◽  
Sarah K. Nyquist ◽  
Alex K. Shalek ◽  
...  
Keyword(s):  
Long Range ◽  
Genetic Variants ◽  
Read Length ◽  
Rna Seq ◽  
Sequencing Data ◽  
Specific Expression ◽  
Integrative Framework ◽  
Whole Exome ◽  
Allele Specific ◽  
Diverse Data

Abstract Haplotype reconstruction of distant genetic variants remains an unsolved problem due to the short-read length of common sequencing data. Here, we introduce HapTree-X, a probabilistic framework that utilizes latent long-range information to reconstruct unspecified haplotypes in diploid and polyploid organisms. It introduces the observation that differential allele-specific expression can link genetic variants from the same physical chromosome, thus even enabling using reads that cover only individual variants. We demonstrate HapTree-X’s feasibility on in-house sequenced Genome in a Bottle RNA-seq and various whole exome, genome, and 10X Genomics datasets. HapTree-X produces more complete phases (up to 25%), even in clinically important genes, and phases more variants than other methods while maintaining similar or higher accuracy and being up to 10×  faster than other tools. The advantage of HapTree-X’s ability to use multiple lines of evidence, as well as to phase polyploid genomes in a single integrative framework, substantially grows as the amount of diverse data increases.

RNA-Seq Analysis of Allele-Specific Expression in the Mouse Cochlea

2014 ◽  
Vol 151 (1_suppl) ◽  
pp. P226-P226
Author(s):  
Maria K. L. Ho ◽  
Yehudit Hasin ◽  
Aldons J. Lusis ◽  
Rick A. Friedman
Keyword(s):  
Rna Seq ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Allele Specific
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