Bioinformatics pipeline to guide late-onset Alzheimer's disease (LOAD) post-GWAS studies: Prioritizing transcription regulatory variants within LOAD-associated regions.
Bioinformatics pipeline to guide late-onset Alzheimer's disease (LOAD) post-GWAS studies: Prioritizing transcription regulatory variants within LOAD-associated regions.
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DOI：
10.1002/trc2.12244
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Chiba-Falek O
中科院分区：
文献类型：
--
作者：
Lutz MW;Chiba-Falek O
随着新的晚发性阿尔茨海默病（LOAD）遗传风险位点的确定和脑细胞类型特异性组学数据的可用，对生物信息学框架的需求尚未得到满足，以优先考虑基因和变异，用于单细胞分子谱实验和使用疾病模型和基因编辑技术的验证。先前的工作已经表征并优先考虑了位于LOAD全基因组关联研究（GWAS）区域的活性增强子及其与候选基因的潜在相互作用。目前的研究通过关注这些LOAD增强子内的单核苷酸多态性（SNP）及其对改变转录因子（TF）结合的影响来扩展这项工作。拟议的生物信息学管道从位于LOAD‐GWAS区域的SNP进展到一组筛选的候选调控SNP，这些SNP对TF结合具有预测的强烈影响。鉴定LOAD相关区域内的活性增强子，并对位于增强子中的SNP进行编目。优先考虑破坏TF结合位点的SNP，并过滤相应的TF以仅包括在与LOAD相关的脑组织中表达的那些TF。通过ChIP-seq信号进一步证实TF与相应序列的结合。最后，将高优先级候选SNP评估为疾病相关组织中的表达数量性状基因座（eQTL）。我们在LOAD-GWAS区域编目了61个强增强子，包括326个SNP和104个TF结合位点。77个和78个TF分别在脑和单核细胞中表达，其中19个TF结合位点显示ChIP-seq信号。发现11个SNP中断TF结合，其中3个SNP也是显著的eQTL。这项研究提供了一个框架，目录非编码变异增强子位于LOAD-GWAS基因座，并表征其干扰TF结合的可能性。该方法集成了多种数据类型，使用单细胞多组学分析和基因编辑来表征和优先考虑SNP的推定调控功能。
As new late‐onset Alzheimer's disease (LOAD) genetic risk loci are identified and brain cell–type specific omics data becomes available, there is an unmet need for a bioinformatics framework to prioritize genes and variants for testing in single‐cell molecular profiling experiments and validation using disease models and gene editing technologies. Prior work has characterized and prioritized active enhancers located in LOAD‐genome‐wide association study (GWAS) regions and their potential interactions with candidate genes. The current study extends this work by focusing on single nucleotide polymorphisms (SNPs) within these LOAD enhancers and their impact on altering transcription factor (TF) binding. The proposed bioinformatics pipeline progresses from SNPs located in LOAD‐GWAS regions to a filtered set of candidate regulatory SNPs that have a predicted strong effect on TF binding. Active enhancers within LOAD‐associated regions were identified and SNPs located in the enhancers were catalogued. SNPs that disrupt TF binding sites were prioritized and the respective TFs were filtered to include only those that were expressed in brain tissues relevant to LOAD. The TFs binding to the corresponding sequence was further confirmed by ChIP‐seq signals. Finally, the high‐priority candidate SNPs were evaluated as expression quantitative trait loci (eQTLs) in disease‐relevant tissues. We catalogued 61 strong enhancers in LOAD‐GWAS regions encompassing 326 SNPs and 104 TF binding sites. Seventy‐seven and 78 of the TFs were expressed in brain and monocytes, respectively, out of which 19 TF‐binding sites showed ChIP‐seq signals. Eleven SNPs were found to interrupt with TF binding out of which three SNPs were also significant eQTL. This study provides a framework to catalogue noncoding variations in enhancers located in LOAD‐GWAS loci and characterize their likelihood to perturb TF binding. The approach integrates multiple data types to characterize and prioritize SNPs for putative regulatory function using single‐cell multi‐omics assays and gene editing.
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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：
30.8
作者：
Harold, Denise;Abraham, Richard;Hollingworth, Paul;Sims, Rebecca;Gerrish, Amy;Hamshere, Marian L.;Pahwa, Jaspreet Singh;Moskvina, Valentina;Dowzell, Kimberley;Williams, Amy;Jones, Nicola;Thomas, Charlene;Stretton, Alexandra;Morgan, Angharad R.;Lovestone, Simon;Powell, John;Proitsi, Petroula;Lupton, Michelle K.;Brayne, Carol;Rubinsztein, David C.;Gill, Michael;Lawlor, Brian;Lynch, Aoibhinn;Morgan, Kevin;Brown, Kristelle S.;Passmore, Peter A.;Craig, David;McGuinness, Bernadette;Todd, Stephen;Holmes, Clive;Mann, David;Smith, A. David;Love, Seth;Kehoe, Patrick G.;Hardy, John;Mead, Simon;Fox, Nick;Rossor, Martin;Collinge, John;Maier, Wolfgang;Jessen, Frank;Schuermann, Britta;van den Bussche, Hendrik;Heuser, Isabella;Kornhuber, Johannes;Wiltfang, Jens;Dichgans, Martin;Froelich, Lutz;Hampel, Harald;Huell, Michael;Rujescu, Dan;Goate, Alison M.;Kauwe, John S. K.;Cruchaga, Carlos;Nowotny, Petra;Morris, John C.;Mayo, Kevin;Sleegers, Kristel;Bettens, Karolien;Engelborghs, Sebastiaan;De Deyn, Peter P.;Van Broeckhoven, Christine;Livingston, Gill;Bass, Nicholas J.;Gurling, Hugh;McQuillin, Andrew;Gwilliam, Rhian;Deloukas, Panagiotis;Al-Chalabi, Ammar;Shaw, Christopher E.;Tsolaki, Magda;Singleton, Andrew B.;Guerreiro, Rita;Muehleisen, Thomas W.;Noethen, Markus M.;Moebus, Susanne;Joeckel, Karl-Heinz;Klopp, Norman;Wichmann, H-Erich;Carrasquillo, Minerva M.;Pankratz, V. Shane;Younkin, Steven G.;Holmans, Peter A.;O'Donovan, Michael;Owen, Michael J.;Williams, Julie
通讯作者：
Williams, Julie
影响因子：
10.6
作者：
Karch CM;Goate AM
通讯作者：
Goate AM
影响因子：
14.9
作者：
Amlie-Wolf A;Tang M;Mlynarski EE;Kuksa PP;Valladares O;Katanic Z;Tsuang D;Brown CD;Schellenberg GD;Wang LS
通讯作者：
Wang LS
影响因子：
9.8
作者：
De Jager, Philip L.;Ma, Yiyi;Bennett, David A.
通讯作者：
Bennett, David A.