A multi-omics atlas of the human retina at single-cell resolution.
A multi-omics atlas of the human retina at single-cell resolution.
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DOI:
10.1016/j.xgen.2023.100298
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发表时间:
2023-06-14
期刊:
影响因子:
--
通讯作者:
Chen R
中科院分区:
文献类型:
--
作者:
Liang Q;Cheng X;Wang J;Owen L;Shakoor A;Lillvis JL;Zhang C;Farkas M;Kim IK;Li Y;DeAngelis M;Chen R
Cell classes in the human retina are highly heterogeneous with their abundance varying by several orders of magnitude. Here, we generated and integrated a multi-omics single-cell atlas of the adult human retina, including more than 250,000 nuclei for single-nuclei RNA-seq and 137,000 nuclei for single-nuclei ATAC-seq. Cross-species comparison of the retina atlas among human, monkey, mice, and chicken revealed relatively conserved and non-conserved types. Interestingly, the overall cell heterogeneity in primate retina decreases compared with that of rodent and chicken retina. Through integrative analysis, we identified 35,000 distal cis-element-gene pairs, constructed transcription factor (TF)-target regulons for more than 200 TFs, and partitioned the TFs into distinct co-active modules. We also revealed the heterogeneity of the cis-element-gene relationships in different cell types, even from the same class. Taken together, we present a comprehensive single-cell multi-omics atlas of the human retina as a resource that enables systematic molecular characterization at individual cell-type resolution. Targeted enrichment of rare cell types in the human retina Cross-species analysis reveals different conservation levels among cell types Cis- and trans-regulatory elements identified through integrative analysis Heterogeneity in regulatory elements for the same gene in different cell types Liang et al. report a comprehensive multi-omics single-cell atlas with nearly 400,000 nuclei and 69 cell types in adult human retina. They identify regulatory elements that are specific to cell classes and cell types through integrative analysis. The dataset enables molecular characterization of the human retina at individual cell-type level.
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影响因子:
33.6
作者:
Do MT;Yau KW
通讯作者:
Yau KW
影响因子:
64.5
作者:
Cowan CS;Renner M;De Gennaro M;Gross-Scherf B;Goldblum D;Hou Y;Munz M;Rodrigues TM;Krol J;Szikra T;Cuttat R;Waldt A;Papasaikas P;Diggelmann R;Patino-Alvarez CP;Galliker P;Spirig SE;Pavlinic D;Gerber-Hollbach N;Schuierer S;Srdanovic A;Balogh M;Panero R;Kusnyerik A;Szabo A;Stadler MB;Orgül S;Picelli S;Hasler PW;Hierlemann A;Scholl HPN;Roma G;Nigsch F;Roska B
通讯作者:
Roska B
影响因子:
64.8
作者:
Buenrostro JD;Wu B;Litzenburger UM;Ruff D;Gonzales ML;Snyder MP;Chang HY;Greenleaf WJ
通讯作者:
Greenleaf WJ
影响因子:
8.8
作者:
Lyu P;Hoang T;Santiago CP;Thomas ED;Timms AE;Appel H;Gimmen M;Le N;Jiang L;Kim DW;Chen S;Espinoza DF;Telger AE;Weir K;Clark BS;Cherry TJ;Qian J;Blackshaw S
通讯作者:
Blackshaw S
影响因子:
9.3
作者:
McGinnis, Christopher S.;Murrow, Lyndsay M.;Gartner, Zev J.
通讯作者:
Gartner, Zev J.