scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.
scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.
复制标题
DOI：
10.1186/s12864-020-07334-y
复制
发表时间：
2021-01-08
期刊：
影响因子：
4.4
通讯作者：
Horvath A
中科院分区：
文献类型：
--
作者：
Liu H;Prashant NM;Spurr LF;Bousounis P;Alomran N;Ibeawuchi H;Sein J;Słowiński P;Tsaneva-Atanasova K;Horvath A
最近，针对单细胞 RNA 测序 (scRNA-seq) 数据的开创性表达数量性状位点 (eQTL) 研究揭示了新的细胞特异性调节单核苷酸变异 (SNV)。在这里，我们提出了一种适用于从 scRNA-seq 数据转录 SNV 位点的替代 QTL 相关方法：scReQTL。 ScReQTL 在表达的双等位基因位点使用变异等位基因片段 (VAFRNA)，并将其与相应细胞的基因表达相关联。我们的方法的优点是，当从多个细胞进行估计时，VAFRNA 可用于评估 SNV 在单个样本或个体中的影响。在这种情况下，scReQTL 在相同基因型的背景下运行，它可能捕获 RNA 介导的遗传相互作用与细胞特异性和瞬时效应。将 scReQTL 应用于 10 × Genomics Chromium 平台上生成的 scRNA-seq 数据，该数据使用来自三名健康女性捐赠者的脂肪组织的 26,640 个间充质细胞，我们鉴定了 1272 个独特的 scReQTL。个体或细胞类型之间常见的 ScReQTL 在关系的方向性和效应大小方面是一致的。与批量测序数据中的 eQTL 进行比较评估表明，scReQTL 分析识别出一组独特的 SNV-基因相关性，这些相关性在已知的基因-基因相互作用和重要的全基因组关联研究 (GWAS) 位点中大幅丰富。 ScReQTL 与快速增长的 scRNA-seq 数据源相关，可用于从单个 scRNA-seq 数据集中概述可能有助于细胞类型特异性和/或动态遗传相互作用的 SNV。可用性：https://github.com/HorvathLab/NGS/tree/master/scReQTL 在线版本包含可在 10.1186/s12864-020-07334-y 获取的补充材料。
Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell. Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci. ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset. Availability: https://github.com/HorvathLab/NGS/tree/master/scReQTL The online version contains supplementary material available at 10.1186/s12864-020-07334-y.
登录
查看更多内容
遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
影响因子：
9.8
作者：
Lloyd-Jones, Luke R.;Holloway, Alexander;Powell, Joseph E.
通讯作者：
Powell, Joseph E.
影响因子：
14.9
作者：
Movassagh M;Alomran N;Mudvari P;Dede M;Dede C;Kowsari K;Restrepo P;Cauley E;Bahl S;Li M;Waterhouse W;Tsaneva-Atanasova K;Edwards N;Horvath A
通讯作者：
Horvath A
影响因子：
64.8
作者：
La Manno G;Soldatov R;Zeisel A;Braun E;Hochgerner H;Petukhov V;Lidschreiber K;Kastriti ME;Lönnerberg P;Furlan A;Fan J;Borm LE;Liu Z;van Bruggen D;Guo J;He X;Barker R;Sundström E;Castelo-Branco G;Cramer P;Adameyko I;Linnarsson S;Kharchenko PV
通讯作者：
Kharchenko PV