当前位置: X-MOL 学术Nat. Genet. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression
Nature Genetics ( IF 30.8 ) Pub Date : 2021-09-02 , DOI: 10.1038/s41588-021-00913-z
Urmo Võsa 1, 2 , Annique Claringbould 1, 3, 4 , Harm-Jan Westra 1, 3 , Marc Jan Bonder 1, 5 , Patrick Deelen 1, 3, 6, 7 , Biao Zeng 8 , Holger Kirsten 9, 10 , Ashis Saha 11 , Roman Kreuzhuber 12, 13, 14 , Seyhan Yazar 15 , Harm Brugge 1, 3 , Roy Oelen 1, 3 , Dylan H de Vries 1, 3 , Monique G P van der Wijst 1, 3 , Silva Kasela 2 , Natalia Pervjakova 2 , Isabel Alves 16, 17 , Marie-Julie Favé 16 , Mawussé Agbessi 16 , Mark W Christiansen 18 , Rick Jansen 19 , Ilkka Seppälä 20 , Lin Tong 21 , Alexander Teumer 22, 23 , Katharina Schramm 24, 25 , Gibran Hemani 26 , Joost Verlouw 27 , Hanieh Yaghootkar 28, 29, 30 , Reyhan Sönmez Flitman 31, 32 , Andrew Brown 33, 34 , Viktorija Kukushkina 2 , Anette Kalnapenkis 2 , Sina Rüeger 35 , Eleonora Porcu 35 , Jaanika Kronberg 2 , Johannes Kettunen 36, 37, 38, 39 , Bernett Lee 40 , Futao Zhang 41 , Ting Qi 41 , Jose Alquicira Hernandez 15 , Wibowo Arindrarto 42 , Frank Beutner 43 , , , Julia Dmitrieva 44 , Mahmoud Elansary 44 , Benjamin P Fairfax 45 , Michel Georges 44 , Bastiaan T Heijmans 42 , Alex W Hewitt 46, 47 , Mika Kähönen 48 , Yungil Kim 11, 49 , Julian C Knight 45 , Peter Kovacs 50 , Knut Krohn 51 , Shuang Li 1, 6 , Markus Loeffler 9, 10 , Urko M Marigorta 8, 52, 53 , Hailang Mei 54 , Yukihide Momozawa 44, 55 , Martina Müller-Nurasyid 24, 25, 56 , Matthias Nauck 23, 57 , Michel G Nivard 58 , Brenda W J H Penninx 19 , Jonathan K Pritchard 59, 60 , Olli T Raitakari 61, 62, 63 , Olaf Rotzschke 40 , Eline P Slagboom 42 , Coen D A Stehouwer 64 , Michael Stumvoll 65 , Patrick Sullivan 66 , Peter A C 't Hoen 67 , Joachim Thiery 10, 68 , Anke Tönjes 65 , Jenny van Dongen 69 , Maarten van Iterson 42 , Jan H Veldink 70 , Uwe Völker 71 , Robert Warmerdam 1, 3 , Cisca Wijmenga 1 , Morris Swertz 6 , Anand Andiappan 40 , Grant W Montgomery 41 , Samuli Ripatti 72, 73, 74 , Markus Perola 75 , Zoltan Kutalik 76 , Emmanouil Dermitzakis 32, 33, 77 , Sven Bergmann 31, 32 , Timothy Frayling 28 , Joyce van Meurs 27 , Holger Prokisch 78, 79 , Habibul Ahsan 21 , Brandon L Pierce 21 , Terho Lehtimäki 20 , Dorret I Boomsma 69 , Bruce M Psaty 80 , Sina A Gharib 18, 81 , Philip Awadalla 16 , Lili Milani 2 , Willem H Ouwehand 12, 13, 82 , Kate Downes 12, 13 , Oliver Stegle 5, 14, 83 , Alexis Battle 11, 84 , Peter M Visscher 41 , Jian Yang 41, 85, 86 , Markus Scholz 9, 10 , Joseph Powell 15, 87 , Greg Gibson 8 , Tõnu Esko 2 , Lude Franke 1, 3
Affiliation  

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.



中文翻译:

大规模的 cis- 和 trans-eQTL 分析确定了数千个调节血液基因表达的基因位点和多基因评分

性状相关的遗传变异主要通过转录组的调控机制影响复杂的表型。为了研究基因表达的遗传学,我们通过 eQTLGen 联盟使用来自 31,684 名个体的血液衍生表达进行了顺式反式表达数量性状基因座 (eQTL) 分析。我们检测到88% 的基因的cis -eQTL,这些在许多组织中都是可复制的。远端反式-eQTL(在 10,317 个测试的性状相关变体中检测到 37%)显示出较低的复制率,部分原因是复制能力低和细胞类型组成的混杂。然而,单细胞 RNA-seq 数据中的复制分析优先考虑细胞内trans - eQTL。Trans -eQTL 通过多种机制发挥作用,主要是通过转录因子的调节。13% 的基因表达与 1,263 种表型的多基因评分相关,从而确定了这些性状的潜在驱动因素。总之,这项工作代表了一个庞大的 eQTL 资源,其结果可作为深入解释复杂表型的起点。

更新日期:2021-09-02
down
wechat
bug