Nuclei multiplexing with barcoded antibodies for single-nucleus genomics

Jellert T. Gaublomme*, Bo Li, Cristin McCabe, Abigail Knecht, Yiming Yang, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Julia Waldman, Danielle Dionne, Lan Nguyen, Philip L. De Jager, Bertrand Yeung, Xinfang Zhao, Naomi Habib, Orit Rozenblatt-Rosen, Aviv Regev

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

74 Scopus citations


Single-nucleus RNA-seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate or are frozen, and opens the way to human genetics studies, clinical trials, and precise cell atlases of large organs. However, such applications are currently limited by batch effects, processing, and costs. Here, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter recovered profiles. We develop DemuxEM, a computational tool that detects inter-sample multiplets and assigns singlets to their sample of origin, and validate its accuracy using sex-specific gene expression, species-mixing and natural genetic variation. Our approach will facilitate tissue atlases of isogenic model organisms or from multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.

Original languageAmerican English
Article number2907
JournalNature Communications
Issue number1
StatePublished - 1 Dec 2019

Bibliographical note

Funding Information:
This publication is part of the Human Cell Atlas ( publications). We thank Dr. David Bennett at RUSH University for the use of samples from the Religious Order Study (ROS) and the Memory and Aging Project (MAP). We thank Chun (Jimmie) Ye for his input on setting appropriate Demuxlet parameters. We thank Jiarui Ding for helpful discussions in appropriate preprocessing of the species-mixing data. We thank Leslie Gaffney, Anna Hupalowska and Jennifer Rood for help with figure and paper preparation. This work was supported by the NIH BRAIN Initiative grant U19MH114821 and the Klarman Cell Observatory. The ROSMAP sample collection and data used in this paper were supported by U01 AG046152, RF1 AG057473, RF1 AG015819, P30 AG10161, and R01 AG17917.

Publisher Copyright:
© 2019, The Author(s).


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