Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution

Edahiro, Ryuya; Sato, Go; Naito, Tatsuhiko; Shirai, Yuya; Saiki, Ryunosuke; Sonehara, Kyuto; Tomofuji, Yoshihiko; Yamamoto, Kenichi; Namba, Shinichi; Sasa, Noah; Nagao, Genta; Wang, Qingbo S.; Takahashi, Yugo; Hasegawa, Takanori; Kishikawa, Toshihiro; Suzuki, Ken; Liu, Yu Chen; Motooka, Daisuke; Takuwa, Ayako; Tanaka, Hiromu; Azekawa, Shuhei; Japan COVID-19 Task Force; Namkoong, Ho; Koike, Ryuji; Kimura, Akinori; Imoto, Seiya; Miyano, Satoru; Kanai, Takanori; Fukunaga, Koichi; Uemura, Mamoru; Morita, Takayoshi; Kato, Yasuhiro; Hirata, Haruhiko; Takeda, Yoshito; Doki, Yuichiro; Eguchi, Hidetoshi; Okuzaki, Daisuke; Sakakibara, Shuhei; Ogawa, Seishi; Kumanogoh, Atsushi; Okada, Yukinori

doi:https://doi.org/10.1038/s41588-025-02266-3

Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution

Edahiro, Ryuya; Sato, Go; Naito, Tatsuhiko et al.

Nature Genetics, 2025, 57(8), 1905-1921

Number of Access:269（2025-12-04 16:46 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/102930

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Title	Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution
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Description	Edahiro R., Sato G., Naito T., et al. Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution. Nature Genetics 57, 1905 (2025); https://doi.org/10.1038/s41588-025-02266-3.
Abstract	Current molecular quantitative trait locus catalogs are mostly at bulk resolution and centered on Europeans. Here, we constructed an immune cell atlas with single-cell transcriptomics of >1.5 million peripheral blood mononuclear cells, host genetics, plasma proteomics and gut metagenomics from 235 Japanese persons, including patients with coronavirus disease 2019 (COVID-19) and healthy individuals. We mapped germline genetic effects on gene expression within immune cell types and across cell states. We elucidated cell type- and context-specific human leukocyte antigen (HLA) and genome-wide associations with T and B cell receptor repertoires. Colocalization using dynamic genetic regulation provided better understanding of genome-wide association signals. Differential gene and protein expression analyses depicted cell type- and context-specific effects of polygenic risks. Various somatic mutations including mosaic chromosomal alterations, loss of Y chromosome and mitochondrial DNA (mtDNA) heteroplasmy were projected into single-cell resolution. We identified immune features specific to somatically mutated cells. Overall, immune cells are dynamically regulated in a cell state-dependent manner characterized with multiomic profiles.
Publisher	Nature Research
Source Title	Nature Genetics
Volume (Issue)	57(8)
Page	1905-1921
Date of Issued	2025-07-28
Language	English
Handle URL	https://hdl.handle.net/11094/102930
PISSN	10614036
eISSN	15461718
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1038/s41588-025-02266-3
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	Nature Genetics. 2025, 57(8), p. 1905-1921
DC.title	Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution
DC.creator	Edahiro, Ryuya
	Sato, Go
	Naito, Tatsuhiko
	Shirai, Yuya
	Saiki, Ryunosuke
	Sonehara, Kyuto
	Tomofuji, Yoshihiko
	Yamamoto, Kenichi
	Namba, Shinichi
	Sasa, Noah
	Nagao, Genta
	Wang, Qingbo S.
	Takahashi, Yugo
	Hasegawa, Takanori
	Kishikawa, Toshihiro
	Suzuki, Ken
	Liu, Yu Chen
	Motooka, Daisuke
	Takuwa, Ayako
	Tanaka, Hiromu
	Azekawa, Shuhei
	Japan COVID-19 Task Force
	Namkoong, Ho
	Koike, Ryuji
	Kimura, Akinori
	Imoto, Seiya
	Miyano, Satoru
	Kanai, Takanori
	Fukunaga, Koichi
	Uemura, Mamoru
	Morita, Takayoshi
	Kato, Yasuhiro
	Hirata, Haruhiko
	Takeda, Yoshito
	Doki, Yuichiro
	Eguchi, Hidetoshi
	Okuzaki, Daisuke
	Sakakibara, Shuhei
	Ogawa, Seishi
	Kumanogoh, Atsushi
	Okada, Yukinori
DC.publisher	Nature Research
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-07-28
DC.identifier	https://doi.org/10.1038/s41588-025-02266-3
DC.description	Edahiro R., Sato G., Naito T., et al. Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution. Nature Genetics 57, 1905 (2025); https://doi.org/10.1038/s41588-025-02266-3.
DCTERMS.abstract	Current molecular quantitative trait locus catalogs are mostly at bulk resolution and centered on Europeans. Here, we constructed an immune cell atlas with single-cell transcriptomics of >1.5 million peripheral blood mononuclear cells, host genetics, plasma proteomics and gut metagenomics from 235 Japanese persons, including patients with coronavirus disease 2019 (COVID-19) and healthy individuals. We mapped germline genetic effects on gene expression within immune cell types and across cell states. We elucidated cell type- and context-specific human leukocyte antigen (HLA) and genome-wide associations with T and B cell receptor repertoires. Colocalization using dynamic genetic regulation provided better understanding of genome-wide association signals. Differential gene and protein expression analyses depicted cell type- and context-specific effects of polygenic risks. Various somatic mutations including mosaic chromosomal alterations, loss of Y chromosome and mitochondrial DNA (mtDNA) heteroplasmy were projected into single-cell resolution. We identified immune features specific to somatically mutated cells. Overall, immune cells are dynamically regulated in a cell state-dependent manner characterized with multiomic profiles.
DC.rights	This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
DC.format	102930
citation_title	Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution
citation_author	Edahiro, Ryuya
	Sato, Go
	Naito, Tatsuhiko
	Shirai, Yuya
	Saiki, Ryunosuke
	Sonehara, Kyuto
	Tomofuji, Yoshihiko
	Yamamoto, Kenichi
	Namba, Shinichi
	Sasa, Noah
	Nagao, Genta
	Wang, Qingbo S.
	Takahashi, Yugo
	Hasegawa, Takanori
	Kishikawa, Toshihiro
	Suzuki, Ken
	Liu, Yu Chen
	Motooka, Daisuke
	Takuwa, Ayako
	Tanaka, Hiromu
	Azekawa, Shuhei
	Japan COVID-19 Task Force
	Namkoong, Ho
	Koike, Ryuji
	Kimura, Akinori
	Imoto, Seiya
	Miyano, Satoru
	Kanai, Takanori
	Fukunaga, Koichi
	Uemura, Mamoru
	Morita, Takayoshi
	Kato, Yasuhiro
	Hirata, Haruhiko
	Takeda, Yoshito
	Doki, Yuichiro
	Eguchi, Hidetoshi
	Okuzaki, Daisuke
	Sakakibara, Shuhei
	Ogawa, Seishi
	Kumanogoh, Atsushi
	Okada, Yukinori
citation_publisher	Nature Research
citation_language	English
citation_date	2025-07-28
citation_journal_title	Nature Genetics
citation_volume	57
citation_issue	8
citation_firstpage	1905
citation_lastpage	1921
citation_doi	https://doi.org/10.1038/s41588-025-02266-3
citation_public_url	https://hdl.handle.net/11094/102930

Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution

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