{"id":4457,"date":"2025-12-17T10:13:35","date_gmt":"2025-12-17T03:13:35","guid":{"rendered":"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/?p=4457"},"modified":"2025-12-17T10:14:33","modified_gmt":"2025-12-17T03:14:33","slug":"quantification-of-escape-from-x-chromosome-inactivation-with-single-cell-omics-data-reveals-heterogeneity-across-cell-types-and-tissues","status":"publish","type":"post","link":"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/en\/quantification-of-escape-from-x-chromosome-inactivation-with-single-cell-omics-data-reveals-heterogeneity-across-cell-types-and-tissues\/","title":{"rendered":"Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues"},"content":{"rendered":"<h2 class=\"title\">Abstract<\/h2>\n<div id=\"eng-abstract\" class=\"abstract-content selected\">\n<div class=\"title\"><\/div>\n<p class=\"chapter-para\">Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood scRNA-seq datasets consistently identified the stronger escape in lymphocytes than in myeloid cells. An extension of scLinaX to a 10x multiome dataset (scLinaX-multi) suggested a stronger escape in lymphocytes than in myeloid cells at the chromatin-accessibility level. The scLinaX analysis of human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes suggested the underlying impact of escape on the genotype-phenotype association. Overall, scLinaX and the quantified escape catalog identified the heterogeneity of escape across cell types and tissues.<\/p>\n<p><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/39084228\/\">https:\/\/pubmed.ncbi.nlm.nih.gov\/39084228\/<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Abstract Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood [&#8230;]\n","protected":false},"author":6,"featured_media":4459,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[],"class_list":["post-4457","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-innovation-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues - \u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e0a\u0e35\u0e27\u0e40\u0e04\u0e21\u0e35 \u0e04\u0e13\u0e30\u0e41\u0e1e\u0e17\u0e22\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e28\u0e34\u0e23\u0e34\u0e23\u0e32\u0e0a\u0e1e\u0e22\u0e32\u0e1a\u0e32\u0e25 \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e21\u0e2b\u0e34\u0e14\u0e25<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/en\/quantification-of-escape-from-x-chromosome-inactivation-with-single-cell-omics-data-reveals-heterogeneity-across-cell-types-and-tissues\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues - \u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e0a\u0e35\u0e27\u0e40\u0e04\u0e21\u0e35 \u0e04\u0e13\u0e30\u0e41\u0e1e\u0e17\u0e22\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e28\u0e34\u0e23\u0e34\u0e23\u0e32\u0e0a\u0e1e\u0e22\u0e32\u0e1a\u0e32\u0e25 \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e21\u0e2b\u0e34\u0e14\u0e25\" \/>\n<meta property=\"og:description\" content=\"Abstract Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood [...]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/en\/quantification-of-escape-from-x-chromosome-inactivation-with-single-cell-omics-data-reveals-heterogeneity-across-cell-types-and-tissues\/\" \/>\n<meta property=\"og:site_name\" content=\"\u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e0a\u0e35\u0e27\u0e40\u0e04\u0e21\u0e35 \u0e04\u0e13\u0e30\u0e41\u0e1e\u0e17\u0e22\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e28\u0e34\u0e23\u0e34\u0e23\u0e32\u0e0a\u0e1e\u0e22\u0e32\u0e1a\u0e32\u0e25 \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e21\u0e2b\u0e34\u0e14\u0e25\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/SIBBprogram\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-17T03:13:35+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-17T03:14:33+00:00\" \/>\n<meta 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