Inferring genes that escape X-Chromosome inactivation reveals important contribution of variable escape genes to sex-biased diseases.
Inferring genes that escape X-Chromosome inactivation reveals important contribution of variable escape genes to sex-biased diseases.
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DOI:
10.1101/gr.275677.121
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发表时间:
2021-09
期刊:
影响因子:
7
通讯作者:
Liu DJ
中科院分区:
文献类型:
--
作者:
Sauteraud R;Stahl JM;James J;Englebright M;Chen F;Zhan X;Carrel L;Liu DJ
The X Chromosome plays an important role in human development and disease. However, functional genomic and disease association studies of X genes greatly lag behind autosomal gene studies, in part owing to the unique biology of X-Chromosome inactivation (XCI). Because of XCI, most genes are only expressed from one allele. Yet, ∼30% of X genes “escape” XCI and are transcribed from both alleles, many only in a proportion of the population. Such interindividual differences are likely to be disease relevant, particularly for sex-biased disorders. To understand the functional biology for X-linked genes, we developed X-Chromosome inactivation for RNA-seq (XCIR), a novel approach to identify escape genes using bulk RNA-seq data. Our method, available as an R package, is more powerful than alternative approaches and is computationally efficient to handle large population-scale data sets. Using annotated XCI states, we examined the contribution of X-linked genes to the disease heritability in the United Kingdom Biobank data set. We show that escape and variable escape genes explain the largest proportion of X heritability, which is in large part attributable to X genes with Y homology. Finally, we investigated the role of each XCI state in sex-biased diseases and found that although XY homologous gene pairs have a larger overall effect size, enrichment for variable escape genes is significantly increased in female-biased diseases. Our results, for the first time, quantitate the importance of variable escape genes for the etiology of sex-biased disease, and our pipeline allows analysis of larger data sets for a broad range of phenotypes.
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影响因子:
64.8
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Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者:
Marchini J
影响因子:
64.8
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14.9
作者:
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者:
Smyth GK
影响因子:
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通讯作者:
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DOI:
10.1073/pnas.1806811115
发表时间:
2018-12-18
影响因子:
11.1
作者:
Garieri, Marco;Stamoulis, Georgios;Antonarakis, Stylianos E.
通讯作者:
Antonarakis, Stylianos E.