Single-cell genomics meets human genetics

被引:50
作者
Cuomo, Anna S. E. [1 ,2 ,3 ]
Nathan, Aparna [4 ,5 ,6 ,7 ,8 ]
Raychaudhuri, Soumya [4 ,5 ,6 ,7 ,8 ]
MacArthur, Daniel G. [2 ,3 ]
Powell, Joseph E. [1 ,9 ]
机构
[1] Garvan Inst Med Res, Darlinghurst, Sydney, NSW, Australia
[2] Garvan Inst Med Res, Ctr Populat Genom, Sydney, NSW, Australia
[3] Murdoch Childrens Res Inst, Ctr Populat Genom, Melbourne, Vic, Australia
[4] Brigham & Womens Hosp, Ctr Data Sci, Boston, MA USA
[5] Harvard Med Sch, Boston, MA USA
[6] Brigham & Womens Hosp, Dept Med, Div Rheumatol & Genet, Boston, MA USA
[7] Harvard Med Sch, Dept Biomed Informat, Boston, MA USA
[8] Broad Inst & Harvard, Program Med & Populat Genet, Cambridge, MA USA
[9] Univ New South Wales, UNSW Cellular Genom Futures Inst, Sydney, NSW, Australia
关键词
MESSENGER-RNA-SEQ; WIDE ASSOCIATION; COMPLEX TRAITS; EXPRESSION; TRANSCRIPTOME; VARIANTS; ARCHITECTURE; SEQUENCE; LOCI; THOUSANDS;
D O I
10.1038/s41576-023-00599-5
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
In this Review, the authors describe the emerging field of single-cell genetics, which lies at the intersection of single-cell genomics and human genetics. They review the first single-cell expression quantitative trait loci studies, which combine single-cell information with genotype data at the population scale and thereby link genetic variation to the cellular processes underpinning key aspects of human biology and disease. Single-cell genomic technologies are revealing the cellular composition, identities and states in tissues at unprecedented resolution. They have now scaled to the point that it is possible to query samples at the population level, across thousands of individuals. Combining single-cell information with genotype data at this scale provides opportunities to link genetic variation to the cellular processes underpinning key aspects of human biology and disease. This strategy has potential implications for disease diagnosis, risk prediction and development of therapeutic solutions. But, effectively integrating large-scale single-cell genomic data, genetic variation and additional phenotypic data will require advances in data generation and analysis methods. As single-cell genetics begins to emerge as a field in its own right, we review its current state and the challenges and opportunities ahead.
引用
收藏
页码:535 / 549
页数:15
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