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   Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease  
   
نویسنده lu q. ,powles r.l. ,abdallah s. ,ou d. ,wang q. ,hu y. ,lu y. ,liu w. ,li b. ,mukherjee s. ,crane p.k. ,zhao h.
منبع plos genetics - 2017 - دوره : 13 - شماره : 7
چکیده    Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. however,synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. here,we present genoskyline-plus,an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution,single tissue annotations. after validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature,we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different gwas traits. we show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or b-cells) provide deeper insights into disease etiology. additionally,we use our genoskyline-plus annotations in an in-depth case study of late-onset alzheimer’s disease (load). our analyses suggest a strong connection between load heritability and genetic variants contained in regions of the genome functional in monocytes. furthermore,we show that load shares a similar localization of snps to monocyte-functional regions with parkinson’s disease. overall,we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. our genoskyline-plus annotations are freely available at http://genocanyon.med.yale.edu/genoskyline. © 2017 lu et al.
آدرس department of biostatistics,yale school of public health,new haven,ct,united states,department of biostatistics and medical informatics,university of wisconsin-madison,madison,wi, United States, program of computational biology and bioinformatics,yale university,new haven,ct, United States, yale university school of medicine,new haven,ct, United States, yale university school of medicine,new haven,ct, United States, program of computational biology and bioinformatics,yale university,new haven,ct, United States, department of biostatistics,yale school of public health,new haven,ct, United States, department of immunobiology,yale university school of medicine,new haven,ct, United States, school of life sciences,peking university,beijing, China, department of biostatistics,yale school of public health,new haven,ct, United States, division of general internal medicine,department of medicine,university of washington,seattle,wa, United States, division of general internal medicine,department of medicine,university of washington,seattle,wa, United States, department of biostatistics,yale school of public health,new haven,ct,united states,program of computational biology and bioinformatics,yale university,new haven,ct,united states,va cooperative studies program coordinating center,west haven,ct, United States
 
     
   
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