Allele-Specific Expression and High-Throughput Reporter Assay Reveal Functional Variants in Human Brains with Alcohol Use Disorders

AbstractTranscriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with alcohol use disorder (AUDs) may cause expression differences, we integrated deep RNA-seq and genome-wide association studies (GWAS) data from four postmortem brain regions of 30 AUDs subjects and 30 controls (social/non-drinkers) and analyzed allele-specific expression (ASE). We identified 90 genes with differential ASE in subjects with AUDs compared to controls. Of these, 61 genes contained 437 single nucleotide polymorphisms (SNPs) in the 3’ untranslated regions (3’UTR) with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that showed affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these are in binding sites of miRNAs and RNA binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE.

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ASEP: gene-based detection of allele-specific expression in a population by RNA-seq

10.1101/798124 ◽

2019 ◽

Author(s):

Jiaxin Fan ◽

Jian Hu ◽

Chenyi Xue ◽

Hanrui Zhang ◽

Muredach P. Reilly ◽

...

Keyword(s):

Association Studies ◽

Genome Wide Association Studies ◽

Rna Seq ◽

Specific Expression ◽

Allele Specific Expression ◽

Wide Range ◽

Gene Level ◽

Shared Information ◽

Allele Specific ◽

Regulated Gene Expression

ABSTRACTAllele-specific expression (ASE) analysis, which quantifies the relative expression of two alleles in a diploid individual, is a powerful tool for identifying cis-regulated gene expression variations that underlie phenotypic differences among individuals. Existing methods for gene-level ASE detection analyze one individual at a time, therefore wasting shared information across individuals. Failure to accommodate such shared information not only loses power, but also makes it difficult to interpret results across individuals. However, ASE detection across individuals is challenging because the data often include individuals that are either heterozygous or homozygous for the unobserved cis-regulatory SNP, leading to heterogeneity in ASE as only those heterozygous individuals are informative for ASE, whereas those homozygous individuals have balanced expression. To simultaneously model multi-individual information and account for such heterogeneity, we developed ASEP, a mixture model with subject-specific random effect accounting for multi-SNP correlations within the same gene. ASEP is able to detect gene-level ASE under one condition and differential ASE between two conditions (e.g., pre-versus post-treatment). Extensive simulations have demonstrated the convincing performance of ASEP under a wide range of scenarios. We further applied ASEP to RNA-seq data of human macrophages, and identified genes showing evidence of differential ASE pre-versus post-stimulation, which were extended through findings in cardiometabolic trait-relevant genome-wide association studies. To the best of our knowledge, ASEP is the first method for gene-level ASE detection at the population level. With the growing adoption of RNA-seq, we believe ASEP will be well-suited for various ASE studies for human diseases.

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Leveraging allele-specific expression to refine fine-mapping for eQTL studies

10.1101/257279 ◽

2018 ◽

Cited By ~ 2

Author(s):

Jennifer Zou ◽

Farhad Hormozdiari ◽

Brandon Jew ◽

Jason Ernst ◽

Jae Hoon Sul ◽

...

Keyword(s):

Gene Expression ◽

Fine Mapping ◽

Complex Traits ◽

Association Studies ◽

Reduction Rate ◽

Genome Wide Association Studies ◽

Specific Expression ◽

Allele Specific Expression ◽

Allele Specific ◽

Causal Variants

AbstractMany disease risk loci identified in genome-wide association studies are present in non-coding regions of the genome. It is hypothesized that these variants affect complex traits by acting as expression quantitative trait loci (eQTLs) that influence expression of nearby genes. This indicates that many causal variants for complex traits are likely to be causal variants for gene expression. Hence, identifying causal variants for gene expression is important for elucidating the genetic basis of not only gene expression but also complex traits. However, detecting causal variants is challenging due to complex genetic correlation among variants known as linkage disequilibrium (LD) and the presence of multiple causal variants within a locus. Although several fine-mapping approaches have been developed to overcome these challenges, they may produce large sets of putative causal variants when true causal variants are in high LD with many non-causal variants. In eQTL studies, there is an additional source of information that can be used to improve fine-mapping called allele-specific expression (ASE) that measures imbalance in gene expression due to different alleles. In this work, we develop a novel statistical method that leverages both ASE and eQTL information to detect causal variants that regulate gene expression. We illustrate through simulations and application to the Genotype-Tissue Expression (GTEx) dataset that our method identifies the true causal variants with higher specificity than an approach that uses only eQTL information. In the GTEx dataset, our method achieves the median reduction rate of 11% in the number of putative causal [email protected], [email protected]

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circVAR database: genome-wide archive of genetic variants for human circular RNAs

10.21203/rs.3.rs-48904/v2 ◽

2020 ◽

Author(s):

Min Zhao ◽

Hong Qu

Keyword(s):

Genetic Variants ◽

Complex Traits ◽

Large Scale ◽

Rna Binding ◽

Rna Binding Proteins ◽

Association Studies ◽

Chromosome 17 ◽

Circular Rnas ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background: Circular RNAs (circRNAs) play important roles in regulating gene expression through binding miRNAs and RNA binding proteins. Genetic variation of circRNAs may affect complex traits/diseases by changing their binding efficiency to target miRNAs and proteins. There is a growing demand for investigations of the functions of genetic changes using large-scale experimental evidence. However, there is no online genetic resource for circRNA genes. Results: We performed extensive genetic annotation of 295,526 circRNAs integrated from circBase, circNet and circRNAdb. All pre-computed genetic variants were presented at our online resource, circVAR, with data browsing and search functionality. We explored the chromosome-based distribution of circRNAs and their associated variants. We found that, based on mapping to the 1000 Genomes and ClinVAR databases, chromosome 17 has a relatively large number of circRNAs and associated common and health-related genetic variants. Following the annotation of genome wide association studies (GWAS)-based circRNA variants, we found many non-coding variants within circRNAs, suggesting novel mechanisms for common diseases reported from GWAS studies. For cancer-based somatic variants, we found that chromosome 7 has many highly complex mutations that have been overlooked in previous research. Conclusion: We used the circVAR database to collect SNPs and small insertions and deletions (INDELs) in putative circRNA regions and to identify their potential phenotypic information. To provide a reusable resource for the circRNA research community, we have published all the pre-computed genetic data concerning circRNAs and associated genes together with data query and browsing functions at http://soft.bioinfo-minzhao.org/circvar .

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Hybrid allele-specific ChIP-Seq analysis links variation in transcription factor binding to traits in maize

10.21203/rs.3.rs-543958/v1 ◽

2021 ◽

Author(s):

Thomas Hartwig ◽

Michael Banf ◽

Gisele Prietsch ◽

Julia Engelhorn ◽

Jinliang Yang ◽

...

Keyword(s):

Transcription Factor ◽

Target Genes ◽

Phenotypic Diversity ◽

Association Studies ◽

Chromatin Accessibility ◽

Genome Wide Association Studies ◽

Functional Variants ◽

Genome Wide ◽

Allele Specific ◽

Hybrid Allele

Abstract Variation in transcriptional regulation is a major cause of phenotypic diversity. Genome-wide association studies (GWAS) have shown that most functional variants reside in non-coding regions, where they potentially affect transcription factor (TF) binding and chromatin accessibility to alter gene expression. Pinpointing such regulatory variations, however, remains challenging. Here, we developed a hybrid allele-specific chromatin binding sequencing (HASCh-seq) approach and identified variations in target binding of the brassinosteroid (BR) responsive transcription factor ZmBZR1 in maize. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) in B73xMo17 F1s identified thousands of target genes of ZmBZR1. Allele-specific ZmBZR1 binding (ASB) was observed for about 14.3% of target genes. It correlated with over 550 loci containing sequence variation in BZR1-binding motifs and over 340 loci with haplotype-specific DNA methylation, linking genetic and epigenetic variations to ZmBZR1 occupancy. Comparison with GWAS data linked hundreds of ASB loci to important yield, growth, and disease-related traits. Our study provides a robust method for analyzing genome-wide variations of transcription factor occupancy and identified genetic and epigenetic variations of the BR response transcription network in maize.

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Loss of nucleoporin Nup50 is a risk factor for amyotrophic lateral sclerosis

10.1101/2021.08.23.21262299 ◽

2021 ◽

Author(s):

Salim Megat ◽

Natalia Mora ◽

Jason Sanogo ◽

Alberto Catanese ◽

Najwa Ouali ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Rna Binding ◽

Rna Binding Proteins ◽

Association Studies ◽

Nuclear Pore ◽

Genome Wide Association Studies ◽

Gene Encoding ◽

Pathogenic Variants ◽

Or Gene ◽

Lateral Sclerosis

The genetic basis of amyotrophic lateral sclerosis (ALS) is still incompletely understood. Using two independent genetic strategies, we show here that a large part of ALS heritability lies in genes expressed in inhibitory and excitatory neurons, especially at splicing sites regulated by a defined set of RNA binding proteins including TDP-43 and FUS. We conducted a transcriptome wide association study (TWAS) and identified 59 loci associated with ALS, including 14 previously identified genes, some of them not previously reaching significance in genome wide association studies. Among the 45 novel genes, several genes are involved in pathways known to be affected in ALS such as mitochondrial metabolism (including ATP5H, ATP5D, BCS1L), proteostasis (including COPS7A, G2E3, TMEM175, USP35) or gene expression and RNA metabolism (including ARID1B, ATXN3, PTBP2, TAF10). Interestingly, decreased expression of NUP50, a constrained gene encoding a nuclear pore basket protein, was associated with ALS in TWAS (Zscore = -4, FDR = 0.034). 11 potentially pathogenic variants (CADD score > 20) in 23 patients were identified in the NUP50 gene, most of them in the region of the protein mediating interaction with Importin alpha, and including 2 frameshift mutations. In cells from two patients carrying NUP50 variants, we showed decreased levels of NUP50 protein. Importantly, knocking down Nup50 led to increased neuronal death associated with p62 and nucleoporin inclusions in cultured neurons, and motor defects in Drosophila and zebrafish models. In all, our study identifies alterations in splicing in neurons as a critical pathogenic process in ALS, uncovers several new loci potentially contributing to ALS missing heritability, and provides genetic evidence linking nuclear pore defects to ALS.

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Variants of the Aggression-Related RBFOX1 Gene in a Population Representative Birth Cohort Study: Aggressiveness, Personality, and Alcohol Use Disorder

Frontiers in Psychiatry ◽

10.3389/fpsyt.2020.501847 ◽

2020 ◽

Vol 11 ◽

Author(s):

Mariliis Vaht ◽

Kariina Laas ◽

Noèlia Fernàndez-Castillo ◽

Triin Kurrikoff ◽

Margus Kanarik ◽

...

Keyword(s):

Alcohol Use ◽

Birth Cohort ◽

Alcohol Use Disorder ◽

Rna Binding ◽

Association Studies ◽

Structured Interview ◽

Health Study ◽

Birth Cohort Study ◽

Big Five Personality ◽

Genome Wide Association Studies

Background: Recently, RBFOX1, a gene encoding an RNA binding protein, has consistently been associated with aggressive and antisocial behavior. Several loci in the gene have been nominally associated with aggression in genome-wide association studies, the risk alleles being more frequent in the general population. We have hence examined the association of four RBFOX1 single nucleotide polymorphisms, previously found related to aggressive traits, with aggressiveness, personality, and alcohol use disorder in birth cohort representative samples.Methods: We used both birth cohorts of the Estonian Children Personality Behavior and Health Study (ECPBHS; original n = 1,238). Aggressiveness was assessed using the Buss–Perry Aggression Questionnaire and the Lifetime History of Aggressiveness structured interview at age 25 (younger cohort) or 33 (older cohort). Big Five personality at age 25 was measured with self-reports and the lifetime occurrence of alcohol use disorder assessed with the MINI interview. RBFOX1 polymorphisms rs809682, rs8062784, rs12921846, and rs6500744 were genotyped in all participants. Given the restricted size of the sample, correction for multiple comparisons was not applied.Results: Aggressiveness was not significantly associated with the RBFOX1 genotype. RBFOX1 rs8062784 was associated with neuroticism and rs809682 with extraversion. Two out of four analyzed RBFOX1 variants, rs8062784 and rs12921846, were associated with the occurrence of alcohol use disorder.Conclusions: In the birth cohort representative sample of the ECPBHS, no association of RBFOX1 with aggressiveness was found, but RBFOX1 variants affected basic personality traits and the prevalence of alcohol use disorder. Future studies on RBFOX1 should consider the moderating role of personality and alcohol use patterns in aggressiveness.

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Allele-specific binding of RNA-binding proteins reveals functional genetic variants in the RNA

10.1101/396275 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ei-Wen Yang ◽

Jae Hoon Bahn ◽

Esther Yun-Hua Hsiao ◽

Boon Xin Tan ◽

Yiwei Sun ◽

...

Keyword(s):

Genetic Variants ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Specific Binding ◽

Specific Protein ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Allele Specific ◽

Rna Interaction

AbstractAllele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants influencing RNA processing and gene expression phenotypes. Recently, genome-wide detection of in vivo binding sites of RNA binding proteins (RBPs) is greatly facilitated by the enhanced UV crosslinking and immunoprecipitation (eCLIP) protocol. Hundreds of eCLIP-Seq data sets were generated from HepG2 and K562 cells during the ENCODE3 phase. These data afford a valuable opportunity to examine allele-specific binding (ASB) of RBPs. To this end, we developed a new computational algorithm, called BEAPR (Binding Estimation of Allele-specific Protein-RNA interaction). In identifying statistically significant ASB sites, BEAPR takes into account UV cross-linking induced sequence propensity and technical variations between replicated experiments. Using simulated data and actual eCLIP-Seq data, we show that BEAPR largely outperforms often-used methods Chi-Squared test and Fisher’s Exact test. Importantly, BEAPR overcomes the inherent over-dispersion problem of the other methods. Complemented by experimental validations, we demonstrate that ASB events are significantly associated with genetic regulation of splicing and mRNA abundance, supporting the usage of this method to pinpoint functional genetic variants in post-transcriptional gene regulation. Many variants with ASB patterns of RBPs were found as genetic variants with cancer or other disease relevance. About 38% of ASB variants were in linkage disequilibrium with single nucleotide polymorphisms from genome-wide association studies. Overall, our results suggest that BEAPR is an effective method to reveal ASB patterns in eCLIP and can inform functional interpretation of disease-related genetic variants.

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circVAR Database: Genome-Wide Archive of Genetic Variants for Human Circular RNAs

10.21203/rs.3.rs-48904/v1 ◽

2020 ◽

Author(s):

Min Zhao ◽

Hong Qu

Keyword(s):

Genetic Variants ◽

Complex Traits ◽

Large Scale ◽

Rna Binding ◽

Rna Binding Proteins ◽

Association Studies ◽

Chromosome 17 ◽

Circular Rnas ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background: Circular RNAs (circRNAs) play important roles in regulating gene expression through binding miRNAs and RNA binding proteins. Genetic variation of circRNAs may affect complex traits/diseases by changing their binding efficiency to target miRNAs and proteins. There is a growing demand for investigations of the functions of genetic changes using large-scale experimental evidence. However, there is no online genetic resource for circRNA genes. Results: We performed extensive genetic annotation of 295,526 circRNAs integrated from circBase, circNet and circRNAdb. All pre-computed genetic variants were presented at our online resource, circVAR, with data browsing and search functionality. We explored the chromosome-based distribution of circRNAs and their associated variants. We found that, based on mapping to the 1000 Genomes and ClinVAR databases, chromosome 17 has a relatively large number of circRNAs and associated common and health-related genetic variants. Following the annotation of genome wide association studies (GWAS)-based circRNA variants, we found many non-coding variants within circRNAs, suggesting novel mechanisms for common diseases reported from GWAS studies. For cancer-based somatic variants, we found that chromosome 7 has many highly complex mutations that have been overlooked in previous research.Conclusion: We used the circVAR database to collect SNPs and small insertions and deletions (INDELs) in putative circRNA regions and to identify their potential phenotypic information. To provide a reusable resource for the circRNA research community, we have published all the pre-computed genetic data concerning circRNAs and associated genes together with data query and browsing functions at http://soft.bioinfo-minzhao.org/circvar.

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circVAR database: genome-wide archive of genetic variants for human circular RNAs

BMC Genomics ◽

10.1186/s12864-020-07172-y ◽

2020 ◽

Vol 21 (1) ◽

Cited By ~ 1

Author(s):

Min Zhao ◽

Hong Qu

Keyword(s):

Genetic Variants ◽

Complex Traits ◽

Large Scale ◽

Rna Binding ◽

Rna Binding Proteins ◽

Association Studies ◽

Chromosome 17 ◽

Circular Rnas ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background Circular RNAs (circRNAs) play important roles in regulating gene expression through binding miRNAs and RNA binding proteins. Genetic variation of circRNAs may affect complex traits/diseases by changing their binding efficiency to target miRNAs and proteins. There is a growing demand for investigations of the functions of genetic changes using large-scale experimental evidence. However, there is no online genetic resource for circRNA genes. Results We performed extensive genetic annotation of 295,526 circRNAs integrated from circBase, circNet and circRNAdb. All pre-computed genetic variants were presented at our online resource, circVAR, with data browsing and search functionality. We explored the chromosome-based distribution of circRNAs and their associated variants. We found that, based on mapping to the 1000 Genomes and ClinVAR databases, chromosome 17 has a relatively large number of circRNAs and associated common and health-related genetic variants. Following the annotation of genome wide association studies (GWAS)-based circRNA variants, we found many non-coding variants within circRNAs, suggesting novel mechanisms for common diseases reported from GWAS studies. For cancer-based somatic variants, we found that chromosome 7 has many highly complex mutations that have been overlooked in previous research. Conclusion We used the circVAR database to collect SNPs and small insertions and deletions (INDELs) in putative circRNA regions and to identify their potential phenotypic information. To provide a reusable resource for the circRNA research community, we have published all the pre-computed genetic data concerning circRNAs and associated genes together with data query and browsing functions at http://soft.bioinfo-minzhao.org/circvar.

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Allele-specific expression of Parkinson’s disease susceptibility genes in human brain

Scientific Reports ◽

10.1038/s41598-020-79990-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Margrete Langmyhr ◽

Sandra Pilar Henriksen ◽

Chiara Cappelletti ◽

Wilma D. J. van de Berg ◽

Lasse Pihlstrøm ◽

...

Keyword(s):

Gene Expression ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Whole Blood ◽

Allelic Expression ◽

Genome Wide Association Studies ◽

Specific Expression ◽

Allele Specific Expression ◽

Specific Effects ◽

Allele Specific

AbstractGenome-wide association studies have identified genetic variation in genomic loci associated with susceptibility to Parkinson’s disease (PD), the most common neurodegenerative movement disorder worldwide. We used allelic expression profiling of genes located within PD-associated loci to identify cis-regulatory variation affecting gene expression. DNA and RNA were extracted from post-mortem superior frontal gyrus tissue and whole blood samples from PD patients and controls. The relative allelic expression of transcribed SNPs in 12 GWAS risk genes was analysed by real-time qPCR. Allele-specific expression was identified for 9 out of 12 genes tested (GBA, TMEM175, RAB7L1, NUCKS1, MCCC1, BCKDK, ZNF646, LZTS3, and WDHD1) in brain tissue samples. Three genes (GPNMB, STK39 and SIPA1L2) did not show significant allele-specific effects. Allele-specific effects were confirmed in whole blood for three genes (BCKDK, LZTS3 and MCCC1), whereas two genes (RAB7L1 and NUCKS1) showed brain-specific allelic expression. Our study supports the hypothesis that changes to the cis-regulation of gene expression is a major mechanism behind a large proportion of genetic associations in PD. Interestingly, allele-specific expression was also observed for coding variants believed to be causal variants (GBA and TMEM175), indicating that splicing and other regulatory mechanisms may be involved in disease development.

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