Computational and Experimental Modeling of Alternative Polyadenylation
Computational and Experimental Modeling of Alternative Polyadenylation
批准号:
10364457
负责人:
Wei Li
金额:
$38.88万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
未结题
起止时间:
2015-12-01 至 2026-02-28
关键词:
3&apos Untranslated RegionsAlgorithmsAtlasesBinding SitesBioinformaticsBiologicalCancer-Predisposing GeneClinical TrialsClustered Regularly Interspaced Short Palindromic RepeatsComplexComputer ModelsDataDiseaseEngineeringEnvironmental Risk FactorExperimental ModelsGene ExpressionGenesGeneticGenetic StructuresGenotypeGenotype-Tissue Expression ProjectGlioblastomaGrantHereditary DiseaseHeterogeneityHumanIn VitroIndividualLinkLungMalignant neoplasm of prostateMethodsMicroRNAsModelingMolecularNatureOncogenesPTEN genePlayPolyadenylationPositioning AttributePost-Transcriptional RegulationPrevalencePulmonary FibrosisQuantitative Trait LociRNARNA SplicingRNA-Binding ProteinsRegulationRegulatory ElementReportingRiskRoleSamplingSingle Nucleotide PolymorphismStatistical MethodsSubgroupSusceptibility GeneSystemTissuesTranscriptTumor Suppressor GenesUntranslated RNAUntranslated RegionsWorkbasecell typegenome wide association studyhuman diseasein vivoinnovationinsightmolecular phenotypeneuropsychiatric disorderneuropsychiatrynovelpatient subsetsprostate cancer progressiontraittranscriptometranscriptome sequencingtreatment effect
中文摘要
项目摘要/摘要
英文摘要
Project Summary / Abstract
Alternative polyadenylation (APA) plays an important role in the post-transcriptional regulation of most human
genes. The broad importance of APA is well exemplified by the altered expression of NUDT21, a key APA
regulator that we reported in the first cycle of this grant, in diseases such as glioblastoma, diopathic pulmonary
fibrosis, and neuropsychiatric disorders. More recently, our work has revealed a novel mechanism by which 3ʹ-
UTR shortening can repress tumor suppressor genes (e.g., PTEN) in trans by disrupting competing
endogenous RNA (ceRNA) crosstalk, rather than by inducing oncogenes in cis. Aside from these few
examples, the prevalence and functions of APA in a wide spectrum of human traits and diseases remain
largely unknown. Most human traits/diseases have been found as associated with hundreds of thousands of
noncoding single-nucleotide polymorphisms (SNPs) in numerous genome-wide association studies (GWASs).
However, functional interpretation of these SNPs remains a significant challenge because GWAS data do not
show how the SNPs work. To better understand their effects, expression quantitative trait loci (eQTLs) have
been widely used to link GWAS SNPs to gene expression. Despite massive efforts on elucidating eQTLs, the
functions of many GWAS SNPs remain unexplained. An important reason is that eQTLs do not consider APA
regulation. We have recently constructed the first human 3′UTR APA quantitative trait loci (3′aQTLs), which
contain ~0.4 million SNPs associated with APA of target genes, using ~8,000 GTEx v7 RNA-seq samples
across 46 tissue types (Nature Genetics, accepted in 2021). These 3′aQTLs can explain ~16.1% of GWAS
SNPs in 15 common traits/diseases, and they are largely distinct from eQTLs and splicing QTLs. Based on
these exciting preliminary data, we hypothesize that computational and experimental modeling of APA will
substantially facilitate the interpretation of numerous GWAS SNPs important for APA regulation, which are
enriched in 3′UTRs and gene downstream regions. Hence, we propose to develop innovative bioinformatics
and experimental methods for identifying 3′aQTLs and nominating APA-linked disease/trait susceptibility genes
in a wide variety of cell types and environmental factors, followed by in vivo functional characterization using
our unique CRISPR engineering system. We expect to establish APA as an emerging and important molecular
phenotype to explain a large fraction of GWAS risk SNPs, leading to significant novel biological insights into
the genetic basis of APA and APA-linked susceptibility genes in a wide spectrum of human traits and diseases.
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