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000165517 0247_ $$2doi$$a10.1016/j.isci.2022.105328
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000165517 1001_ $$0P:(DE-2719)9001512$$aBonaguro, Lorenzo$$b0$$eFirst author$$udzne
000165517 245__ $$aHuman variation in population-wide gene expression data predicts gene perturbation phenotype.
000165517 260__ $$aSt. Louis$$bElsevier$$c2022
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000165517 520__ $$aPopulation-scale datasets of healthy individuals capture genetic and environmental factors influencing gene expression. The expression variance of a gene of interest (GOI) can be exploited to set up a quasi loss- or gain-of-function 'in population' experiment. We describe here an approach, huva (human variation), taking advantage of population-scale multi-layered data to infer gene function and relationships between phenotypes and expression. Within a reference dataset, huva derives two experimental groups with LOW or HIGH expression of the GOI, enabling the subsequent comparison of their transcriptional profile and functional parameters. We demonstrate that this approach robustly identifies the phenotypic relevance of a GOI allowing the stratification of genes according to biological functions, and we generalize this concept to almost 16,000 genes in the human transcriptome. Additionally, we describe how huva predicts monocytes to be the major cell type in the pathophysiology of STAT1 mutations, evidence validated in a clinical cohort.
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000165517 650_7 $$2Other$$aClinical genetics
000165517 650_7 $$2Other$$aHuman genetics
000165517 650_7 $$2Other$$aPathophysiology
000165517 7001_ $$0P:(DE-2719)9001500$$aSchulte-Schrepping, Jonas$$b1$$udzne
000165517 7001_ $$0P:(DE-2719)9001303$$aCarraro, Caterina$$b2$$udzne
000165517 7001_ $$aSun, Laura L$$b3
000165517 7001_ $$aReiz, Benedikt$$b4
000165517 7001_ $$0P:(DE-2719)2812074$$aGemünd, Ioanna$$b5$$udzne
000165517 7001_ $$0P:(DE-2719)2812564$$aSaglam, Adem$$b6$$udzne
000165517 7001_ $$aRahmouni, Souad$$b7
000165517 7001_ $$aGeorges, Michel$$b8
000165517 7001_ $$aArts, Peer$$b9
000165517 7001_ $$aHoischen, Alexander$$b10
000165517 7001_ $$aJoosten, Leo A B$$b11
000165517 7001_ $$avan de Veerdonk, Frank L$$b12
000165517 7001_ $$aNetea, Mihai G$$b13
000165517 7001_ $$0P:(DE-2719)2812735$$aHändler, Kristian$$b14$$udzne
000165517 7001_ $$0P:(DE-2719)2811372$$aMukherjee, Sach$$b15$$udzne
000165517 7001_ $$0P:(DE-2719)9000845$$aUlas, Thomas$$b16$$udzne
000165517 7001_ $$0P:(DE-2719)2811660$$aSchultze, Joachim L$$b17$$udzne
000165517 7001_ $$0P:(DE-2719)2812913$$aAschenbrenner, Anna Christin$$b18$$eLast author$$udzne
000165517 773__ $$0PERI:(DE-600)2927064-9$$a10.1016/j.isci.2022.105328$$gVol. 25, no. 11, p. 105328 -$$n11$$p105328$$tiScience$$v25$$x2589-0042$$y2022
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