Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets

Caglayan, Emre; Liu, Yuxiang; Konopka, Genevieve

doi:10.1016/j.neuron.2022.09.010

Cited by 137Single-cell and spatial transcriptomicsGenomics and Phylogenetic StudiesMolecular Biology Techniques and Applications

Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets

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Caglayan, Emre, Liu, Yuxiang, Konopka, Genevieve·2022·Neuron

DOI 10.1016/j.neuron.2022.09.010PMC PMC9789184

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Abstract

Ambient RNA contamination in single-cell and single-nuclei RNA sequencing (snRNA-seq) is a significant problem, but its consequences are poorly understood. Here, we show that ambient RNAs in brain snRNA-seq datasets have a nuclear or non-nuclear origin with distinct gene set signatures. Both ambient RNA signatures are predominantly neuronal, and we find that some previously annotated neuronal cell types are distinguished by ambient RNA contamination. We detect pervasive neuronal ambient RNA contamination in all glial cell types unless glia and neurons are physically separated prior to sequencing. We demonstrate that this contamination can be removed in silico and show that previous single-nuclei RNA-seq-based annotations of immature oligodendrocytes are glial nuclei contaminated with ambient RNAs. After ambient RNA removal, we detect rare, committed oligodendrocyte progenitor cells not annotated in most previous adult human brain datasets. Together, these results provide an in-depth analysis of ambient RNA contamination in brain single-nuclei datasets.

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Ambient RNA from lysed cells can lead to false positives in gene expression profiles, obscuring true cell type-specific markers.
“For example, ambient RNA from lysed cells, a ubiquitous issue of scRNA- and snRNA-seq datasets, can lead to false positives in gene expression profiles, obscuring true cell type-specific markers[34, 35].”
From Comparative analysis of nuclei isolation methods for brain single-nucleus RNA sequencing (2026) · cites this paper as [34]
The Introduction (page unavailable) says freely floating transcripts contaminate endogenous expression profiles and can skew them enough to cause biological misinterpretation. The Results section on glial nuclei (page unavailable) reports ambient RNA markers appearing falsely expressed in those nuclei, supporting the concern about misleading cell-type profiles. Our copy does not establish that the RNA specifically comes from lysed cells, and the paper’s findings focus on brain single-nuclei datasets rather than demonstrating the claim across scRNA- and snRNA-seq datasets generally. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Ambient RNA contamination may distort transcriptomic profiles, leading to the underrepresentation of specific cell types or misclassification of cellular states.
“This contamination may distort transcriptomic profiles, leading to the underrepresentation of specific cell types or misclassification of cellular states[34, 37].”
From Comparative analysis of nuclei isolation methods for brain single-nucleus RNA sequencing (2026) · cites this paper as [34]

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Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets
Maden, S. K., Kwon, S. H., Huuki-Myers, L. A., Collado‐Torres, L., Hicks, S. C., & Maynard, K. R. (2023) · Genome biology · doi:10.1186/s13059-023-03123-4 · Cited by 58 · see citing works
“In the brain, recent work highlighted advantages for sorting approaches that remove non-nuclear ambient RNA contaminating glial cell populations [94].”
Background
Single-cell genotyping and transcriptomic profiling of mosaic focal cortical dysplasia
Baldassari, S., Klingler, E., Teijeiro, L. G., Doladilhe, M., Raoux, C., Roig‐Puiggros, S., Bizzotto, S., Couturier, J., Gilbert, A., Sami, L., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01936-z · Cited by 51 · see citing works
“Cell-type annotation was slightly adjusted based on a recent publication 42 : the V19 cluster annotations ‘NRGN-I’, ‘NRGN-II’ and ‘Mat.”
Single-cell transcriptomic and genomic changes in the ageing human brain
Jeffries, A. M., Yu, T., Ziegenfuss, J. S., Tolles, A. K., Baer, C. E., Sotelo, C. B., Kim, Y., Weng, Z., & Lodato, M. A. (2025) · Nature · doi:10.1038/s41586-025-09435-8 · Cited by 66 · see citing works
“In the snRNA-seq experiments, 367,317 nuclei remained after quality control and artefact filtering 18 , with a mean of 19,332 per donor (Supplementary Fig.”
Aging activates escape of the silent X chromosome in the female mouse hippocampus
Gadek, M., Shaw, C. K., Abdulai-Saiku, S., Saloner, R., Marino, F., Wang, D., Bonham, L. W., Yokoyama, J. S., Panning, B., Benayoun, B. A., et al. (2025) · Science Advances · doi:10.1126/sciadv.ads8169 · Cited by 48 · see citing works
Lost in space: what single-cell RNA sequencing cannot tell you
Adema, K., Schon, M. A., Nodine, M. D., & Kohlen, W. (2024) · Trends in Plant Science · doi:10.1016/j.tplants.2024.03.010 · Cited by 42 · see citing works
Challenges of profiling motor neuron transcriptomes from human spinal cord
Gautier, O., Blum, J. A., Maksymetz, J., Chen, D. C., Schweingruber, C., Mei, I., Hermann, A., Hackos, D. H., Hedlund, E., Ravits, J., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.10.035 · Cited by 42 · see citing works
Protracted neuronal recruitment in the temporal lobes of young children
Nascimento, M. A., Biagiotti, S. W., Herranz‐Pérez, V., Santiago, S., Bueno, R., Ye, C., Abel, T. J., Zhang, Z., Rubio-Moll, J. S., Kriegstein, A. R., et al. (2023) · Nature · doi:10.1038/s41586-023-06981-x · Cited by 38 · see citing works
Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease
Kilfeather, P., Khoo, J. H., Wagner, K., Liang, H., Caiazza, M. C., An, Y., Zhang, X., Chen, X., Connor‐Robson, N., Shang, Z., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113784 · Cited by 32 · see citing works
The committed oligodendrocyte precursor cell, a newly‐defined intermediate progenitor cell type in oligodendroglial lineage
Fang, M., Chen, L., Tang, T., Qiu, M. S., & Xu, X. (2023) · Glia · doi:10.1002/glia.24426 · Cited by 27 · see citing works
STING Deletion Protects Against Amyloid β‐induced Alzheimer's Disease Pathogenesis
Thanos, J. M., Campbell, O. C., Cowan, M. N., Bruch, K. R., Moore, K. A., Ennerfelt, H. E., Natale, N. R., Mangalmurti, A., Kerur, N., & Lukens, J. R. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70305 · Cited by 26 · see citing works
Are we there yet? Exploring astrocyte heterogeneity one cell at a time
O’Dea, M. R., & Hasel, P. (2024) · Glia · doi:10.1002/glia.24621 · Cited by 27 · see citing works
Cell-type-informed genotyping of mosaic focal epilepsies reveals cell-autonomous and non-cell-autonomous disease-associated transcriptional programs
Bizzotto, S., Talukdar, M., Stronge, E., Ramirez, R. B., Yang, Y., Huang, A. Y., Hu, Q., Hou, Y., Hylton, N. K., Finander, B., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2509622122 · Cited by 21 · see citing works
Implementation and validation of single-cell genomics experiments in neuroscience
Colonna, M., Konopka, G., Liddelow, S. A., Nowakowski, T. J., Awatramani, R. B., Bateup, H. S., Cadwell, C. R., Caglayan, E., Chen, J. L., Gillis, J., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01814-0 · Cited by 22 · see citing works
“Recent studies have shown that technical artifacts such as doublets and ambient RNA contamination can lead to misinterpretations 156 .”
Self-citation
The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics
Weber, L. M., Divecha, H. R., Tran, M. N., Kwon, S. H., Spangler, A., Montgomery, K. D., Tippani, M., Bharadwaj, R. A., Kleinman, J. E., Page, S. C., et al. (2024) · eLife · doi:10.7554/elife.84628.3 · Cited by 18 · see citing works
Cell-type-specific roles of FOXP1 in the excitatory neuronal lineage during early neocortical murine development
Ortiz, A., Ayhan, F., Khandelwal, N., Outland, E. H., Jankovic, M. J., Harper, M. J., & Konopka, G. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115384 · Cited by 17 · see citing works
“Cell Ranger ATAC 2.0.0 was used to process Chromium Single Cell ATAC-seq data (10X Genomics), running mkfastq, and cellranger-atac count with reads aligned to mm10 reference genome (cellranger-arc-mm10–2020-A-2.”
InfluentialSelf-citation
The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics
Weber, L. M., Divecha, H. R., Tran, M. N., Kwon, S., Spangler, A., Montgomery, K. D., Tippani, M., Bharadwaj, R. A., Kleinman, J. E., Page, S. C., et al. (2023) · eLife · doi:10.7554/elife.84628 · Cited by 30 · see citing works
Single-nucleus RNA sequencing of developing superior colliculus identifies neuronal diversity and candidate mediators of circuit assembly
Choi, J. S., Ayupe, A. C., Beckedorff, F., Catanuto, P., McCartan, R., Levay, K., & Park, K. K. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113037 · Cited by 20 · see citing works
“64 To mitigate the effects of ambient RNA contamination in DE testing, we applied ambient profile estimation algorithms in the DropletUtils R package (Figure S1A).”
Method
SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis
Gonzalez-Ferrer, J., Lehrer, J., O’Farrell, A., Paten, B., Teodorescu, M., Haussler, D. H., Jönsson, V. D., & Mostajo-Radji, M. A. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100581 · Cited by 15 · see citing works
Concepts and new developments in droplet-based single cell multi-omics
Chow, A., & Lareau, C. A. (2024) · Trends in biotechnology · doi:10.1016/j.tibtech.2024.07.006 · Cited by 14 · see citing works
Benchmarking long-read RNA-sequencing technologies with LongBench: a cross-platform reference dataset profiling cancer cell lines with bulk and single-cell approachesPreprint
You, Y., Solano, A. N., Lancaster, J., David, M., Wang, C., Tan, J. W., Su, S., Pasquali, C., Zeglinski, K., Ghamsari, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.11.675724 · Cited by 16 · see citing works
Sex effects on gene expression across the human cerebral cortex at cell type resolution
DeCasien, A. R., Auluck, P. K., Liu, S., Feng, N., Elkahloun, A. G., Xu, Q., Marenco, S., Cookson, M., & Raznahan, A. (2026) · Science · doi:10.1126/science.aea9063 · Cited by 21 · see citing works
Cell-type-specific effects of autism-associated 15q duplication syndrome in the human brain
Dias, C., Mo, A., Cai, C., Sun, L., Cabral, K., Brownstein, C. A., Rockowitz, S., & Walsh, C. A. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.07.002 · Cited by 16 · see citing works
“21 There is increased variability in snRNA-seq studies from human tissue.”
Transcriptional profiles of immature neurons in aged human hippocampus track Alzheimer’s pathology and cognitive resilience
Tosoni, G., Ayyildiz, D., Snoeck, S., Moreno‐Jiménez, E. P., Penning, A., Santiago-Mujika, E., Ormaechea, O. R., Lee, H., Poovathingal, S. K., Davie, K., et al. (2026) · Cell stem cell · doi:10.1016/j.stem.2026.04.002 · Cited by 13 · see citing works
A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping
Dong, P., Song, L., Bendl, J. M., Misir, R., Shao, Z., Edelstien, J., Davis, D. A., Haroutunian, V. H., Scott, W. K., Acker, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54448-y · Cited by 12 · see citing works
“This observation could be attributed to the presence of ambientRNAs 30 coupledwiththehighdegreeofregionalhomogeneity in non-neuronal cells.”
Single-cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism
Perez, Y., Velmeshev, D., Wang, L., White, M. L., Siebert, C., Baltazar, J., Zuo, G., Moriano, J., Chen, S., Steffen, D. M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61184-4 · Cited by 12 · see citing works
“Afterremovingaclusterofneuronaldebriscontaminated by ambient RNA 19 (Methods, Supplementary Fig.”
Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex
Viswanadham, V., Kim, S. N., Caglayan, E., Doan, R. N., Dou, Y., Bizzotto, S., Khoshkhoo, S., Huang, A. Y., Yeh, R. C., Chhouk, B. H., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116458 · Cited by 11 · see citing works
“Brodmann area identification and sampling were completed by the NIH NeuroBioBank at the University of Maryland Brain and Tissue Bank.”
Self-citation
Decoding fibrosis in the human central nervous system
Holl, D., & Göritz, C. (2023) · American Journal of Physiology-Cell Physiology · doi:10.1152/ajpcell.00243.2023 · Cited by 11 · see citing works
Comparative transcriptomic analyses of thymocytes using 10x Genomics and Parse scRNA-seq technologies
Filippov, I. V., Philip, C. S., Schauser, L., & Peterson, P. (2024) · BMC Genomics · doi:10.1186/s12864-024-10976-x · Cited by 10 · see citing works
“Ambient RNA is majorly present in drop-let-based technology and can be described as the mRNA released in cell suspension from damaged or dying cells which contaminates the true cellular gene transcripts [18].”
Functional genomics and systems biology in human neuroscience
Konopka, G., & Bhaduri, A. (2023) · Nature · doi:10.1038/s41586-023-06686-1 · Cited by 10 · see citing works
“Yet, this approach (as well as single-cell profiling) can still suffer from excessive ambient RNA content, a phenomenon that releases cytoplasmic RNA into the cell suspension prior to analysis, impeding the accuracy of the single-cell nature of the experiment 44 .”
BackgroundSelf-citation
Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s diseasePreprint
Serrano‐Pozo, A., Li, Z., Woodbury, M. E., Muñoz‐Castro, C., Wachter, A., Jayakumar, R., Bryant, A. G., Noori, A., Welikovitch, L. A., Hu, M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.03.518999 · Cited by 10 · see citing works
Single-cell transcriptomic and genomic changes in the aging human brainPreprint
Jeffries, A. M., Yu, T., Ziegenfuss, J. S., Tolles, A. K., Kim, Y., Weng, Z., & Lodato, M. A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.07.566050 · Cited by 10 · see citing works
“290,814 nuclei remained after quality control and artifact filtering 19 , a mean of 22,370/donor (fig.”
Background
Single-nucleus transcriptomics reveals disease- and pathology-specific signatures in α-synucleinopathies
Nido, G. S., Castelli, M., Mostafavi, S., Rubiolo, A., Shadad, O., Alves, G. W., Tysnes, O., Flønes, I. H., Dölle, C., & Tzoulis, C. (2024) · Brain · doi:10.1093/brain/awae355 · Cited by 9 · see citing works
“20,21 In a first filtering pass, droplets with < 500 features, < 1000 counts, > 3% mitochondrial reads or > 2% ribosomal reads were discarded.”
Transcriptomic and morphologic vascular aberrations underlying FCDIIb etiology
Fang, C., Zhang, X., Yang, L., Sun, L., Lu, Y., Liu, Y., Guo, J., Wang, M., Tan, Y., Zhang, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58535-6 · Cited by 10 · see citing works
“3b) 18 .”
Self-citation
In vivo transcriptomic, functional, circuit-based, and translational analyses of enteric neurons
Millett, C. J., Shaver, J. J., Bracken, B., Jones, S. J., Lovelett, R. J., Rubinow, D. A., Singhal, R., Charlton, C., Piazza, N., Hauck, Q., et al. (2025) · Cell · doi:10.1016/j.cell.2025.11.024 · Cited by 9 · see citing works
Sleep need driven oscillation of glutamate synaptic phenotypePreprint
Vogt, K. E., Kulkarni, A., Pandey, R., Dehnad, M., Konopka, G., & Greene, R. W. (2024) · eLife · doi:10.7554/elife.98280 · Cited by 9 · see citing works
Self-citation
Ambient RNAs removal of cortex-specific snRNA-seq reveals Apoe+ microglia/macrophage after deeper cerebral hypoperfusion in mice
Zhang, Y., Tan, J., Yang, K., Fan, W., Yu, B., & Shi, W. (2023) · Journal of Neuroinflammation · doi:10.1186/s12974-023-02831-9 · Cited by 7 · see citing works
Comparative analysis of nuclei isolation methods for brain single-nucleus RNA sequencing
Kersey, H. N., Acri, D. J., Dabin, L. C., Hartigan, K. A., Mustaklem, R., Park, J. H., & Kim, J. (2026) · Cell Reports Methods · doi:10.1016/j.crmeth.2026.101337 · Cited by 8 · see citing works
Oligodendroglial heterogeneity in health, disease, and recovery: deeper insights into myelin dynamics
Serneels, P., Schutter, J. D. D., Groef, L. D., Moons, L., & Bergmans, S. (2024) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-24-00694 · Cited by 8 · see citing works
“Created with Tayasui Sketches and BioRender.com based on data from Jakovcevski et al., 2009; Marques et al., 2016; Ravanelli et al., 2018; Huang et al., 2020; Tsata et al., 2020; Scott et al., 2021; Caglayan et al., 2022; Häberlein et al., 2022.”
Influential
CellBouncer, a unified toolkit for single-cell demultiplexing and ambient RNA analysis, reveals hominid mitochondrial incompatibilities
Schaefer, N. K., Pavlovic, B. J., Schmitz, M. T., & Pollen, A. A. (2026) · Cell Genomics · doi:10.1016/j.xgen.2026.101275 · Cited by 9 · see citing works
“33 We present CellBouncer, a computational toolkit that rectifies these shortcomings, improves speed and accuracy over existing tools, and provides novel functionality (Figure 1).”
Influential
Understanding and mitigating the impact of ambient mRNA contamination in single-cell RNA-sequencing analysis
Arora, J. K., James, L. K., & Charoensawan, V. (2025) · PLoS ONE · doi:10.1371/journal.pone.0332440 · Cited by 8 · see citing works
“However, after computational removal of this ambient contamination, committed oligodendrocyte progenitor cells (a rare population) were detected, which had not been annotated in most previous adult human brain datasets [16].”
Functional Genomics Link REST to Endothelial Plasticity and Atherosclerosis
Viskadourou, M., Chaudhry, S. A., Scalco, A., Reventún, P., Toledano-Sanz, P., An, R., Alcharani, N., Delgado-Marín, M., Fennell, A., Zhao, Q., et al. (2025) · Circulation Research · doi:10.1161/circresaha.125.326628 · Cited by 8 · see citing works
DAP12 deletion reduces neuronal SLIT2 and demyelination and enhances brain resilience in female tauopathy mice
Chen, H., Fan, L., Guo, Q., Wong, M. Y., Zhu, J., Foxe, N. R., Wang, W. T., Nessim, A., Carling, G., Liu, B., et al. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00903-3 · Cited by 8 · see citing works
“Given recent findings that sin-gle-nucleus transcriptomic datasets can suffer from neuronal, ambient RNA contamination in glial populations [44].”
scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing
Li, K., Sun, Y. H., Ouyang, Z., Negi, S., Gao, Z., Zhu, J., Wang, W., Chen, Y., Piya, S., Hu, W., et al. (2023) · BMC Genomics · doi:10.1186/s12864-023-09332-2 · Cited by 8 · see citing works
“In a recent paper [48], CellBender [49] outperforms other tools including DecontX [50] and SoupX [51].”
Method
Single-Nucleus RNA Sequencing of Developing and Mature Superior Colliculus Identifies Neuronal Diversity and Candidate Mediators of Circuit AssemblyPreprint
Ayupe, A., Choi, J. S., Beckedorff, F., Catanuto, P., McCartan, R., Levay, K., & Park, K. K. (2023) · bioRxiv · doi:10.1101/2023.02.01.526254 · Cited by 3 · see citing works
Isolation and Molecular Profiling of Nuclei of Specific Neuronal Types from Human Cerebral Cortex and Striatum
Pressl, C., Baffuto, M., Darnell, P., Wang, C., Carroll, T. S., Heintz, N., & Mätlik, K. (2024) · Current Protocols · doi:10.1002/cpz1.70067 · Cited by 6 · see citing works
“Droplet-based snRNA-seq methods must compensate for contamination with ambient transcripts present in all preparations from human tissue, as these could otherwise lead to the misinterpretation of cell types and false-positive expression changes (Caglayan et al., 2022; Slyper et al., 2020).”
Single-cell omics technologies – Fundamentals on how to create single-cell looking glasses for reproductive health
Diop, M., Davidson, B. R., Fragiadakis, G. K., Sirota, M., Gaudilliere, B. L., & Combes, A. J. (2025) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2024.08.041 · Cited by 7 · see citing works
“37,38 Additional modalities measured by single-cell sequencing methods Single nuclear ATAC-seq: Motivated by the importance of post-transcriptional and epigenetic regulation in biological processes, scRNA-sequencing has been rapidly adapted to enable the measurement of additional cellular features…”
Mitigating ambient RNA and doublets effects on single cell transcriptomics analysis in cancer research
Saddala, M. S., Chittineni, M. S., Hariharan, N., Rias, A. L., & Nagaraju, G. P. (2025) · Cancer Letters · doi:10.1016/j.canlet.2025.217693 · Cited by 7 · see citing works
Spatial genomics: Mapping the landscape of fibrosis
Velu, P. P., Abhari, R. E., & Henderson, N. C. (2025) · Science Translational Medicine · doi:10.1126/scitranslmed.adm6783 · Cited by 8 · see citing works
Plexin-B1 safeguards astrocyte agility and glial alignment to facilitate wound corralling and axon pathfinding in mouse spinal cord injury model
Ni, H., Zhou, Z., Estill, M. S., Halawani, D., Alves, C. J., Shen, L., Xie, N., Friedel, R. H., & Zou, H. (2025) · Nature Communications · doi:10.1038/s41467-025-65095-2 · Cited by 7 · see citing works
“Of note, by employing the Split-seq platform, the likelihood of ambient RNA contamination, which can occur in droplet-based micro ﬂ uidics platforms 51 , is greatly reduced, as the four-round split-pool barcoding approach decreases the chance of erroneous barcode assignment.”
Physiology of oligodendroglia
Butt, A. M., Niu, J., Yi, C., & Verkhratsky, A. (2026) · Physiological Reviews · doi:10.1152/physrev.00023.2025 · Cited by 7 · see citing works
Spatial host-microbiome profiling demonstrates bacterial-associated host transcriptional alterations in pediatric ileal Crohn’s disease
Jang, S., Lee, E. J., Park, S., Lim, H. J., Ahn, B., Huh, Y., Koh, H., & Park, Y. R. (2025) · Microbiome · doi:10.1186/s40168-025-02178-8 · Cited by 6 · see citing works
Detecting gene expression in Caenorhabditis elegans
Calarco, J. A., Taylor, S. R., & Miller, D. M. (2024) · Genetics · doi:10.1093/genetics/iyae167 · Cited by 6 · see citing works
A Single-Cell-Resolution Quantitative Metric of Similarity to a Target Cell Type for scRNA-seq Data
Cheng, Z., Wei, S., & Yu, G. (2022) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm55620.2022.9995574 · Cited by 3 · see citing works
“For validation purposes, we compared our result with that of a recently published study [22].”
MethodResult
High-resolution single-cell analyses reveal evolutionary constraints and evolvability of sexual circuits in Drosophila
Walsh, J. T., Junker, I. P., Chen, Y., Chen, Y., Gifford, H., Chen, D. S., & Ding, Y. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2516083122 · Cited by 5 · see citing works
“Ambient RNA in single - cell suspensions can introduce contamination, leading to false - positive signals that appear as lowly expressed genes (36), artificially inflating the breadth of gene expression.”
Deconstructing Intratumoral Heterogeneity through Multiomic and Multiscale Analysis of Serial Sections
Schupp, P. G., Shelton, S. J., Brody, D. J., Eliscu, R., Johnson, B., Mazor, T., Kelley, K. W., Potts, M. B., McDermott, M. W., Huang, E. J., et al. (2024) · Cancers · doi:10.3390/cancers16132429 · Cited by 5 · see citing works
“However, single-cell data are confounded by technical factors related to tissue dissociation, sampling bias, noise, contamination, and sparsity [26–30], which muddle the relationships between malignant cell genotypes and molecular phenotypes, particularly for cancers that lack consistent CNVs.”
Human CLOCK enhances neocortical function
Liu, Y., Fontenot, M. R., Kulkarni, A., Khandelwal, N., Park, S. H. E., Criswell, C. J., Harper, M. J., Xu, P., Gupta, N., Gibson, J. R., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01993-4 · Cited by 10 · see citing works
“Due to high levels of ambient RNA contamination 55 , one sample of each genotype was removed at P7.”
Self-citation
The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomicsPreprint
Weber, L. M., Divecha, H. R., Tran, M. N., Kwon, S. H., Spangler, A., Montgomery, K. D., Tippani, M., Bharadwaj, R. A., Kleinman, J. E., Page, S. C., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.28.514241 · Cited by 5 · see citing works
Sex effects on gene expression across the human cerebral cortex at single cell resolutionPreprint
DeCasien, A. R., Auluck, P. K., Liu, S., Marenco, S., Cookson, M., & Raznahan, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.30.661781 · Cited by 5 · see citing works
“To minimize contamination in cell type identification and differential expression [35], we removed ambient RNA and called cells using CellBender [36] (Table S4).”
The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomicsPreprint
Weber, L. M., Divecha, H. R., Tran, M. N., Kwon, S. H., Spangler, A., Montgomery, K. D., Tippani, M., Bharadwaj, R. A., Kleinman, J. E., Page, S. C., et al. (2023) · eLife · doi:10.7554/elife.84628.1 · Cited by 4 · see citing works
An Efficient and Principled Model to Jointly Learn the Agnostic and Multifactorial Effect in Large-Scale Biological DataPreprint
Cheng, Z., Wei, S., Wang, Y., Wang, Y., Lu, Q. R., Wang, Y., & Yu, G. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.12.589306 · Cited by 3 · see citing works
“For validation purposes, we compared our result with that of a recently published study ( 44 ).”
MethodResult
A consensus single-cell transcriptomic atlas of dermal fibroblast heterogeneityPreprint
Ascensión, A. M., & Izeta, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.05.611379 · Cited by 4 · see citing works
Uncovering the transcriptional hallmarks of endothelial cell aging via integrated single-cell analysisPreprint
Dobner, S., Kleißl, L., Tóth, F., Paxton, R. L., Yordanova, I., Brazdilova, K., Vanluyten, C., Aizenshtadt, A., Toth, H., Burton, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.18.669055 · Cited by 4 · see citing works
Dissecting the evolving cellular landscape of a remyelinating microenvironment
Melchor, G. S., Baydyuk, M., Manavi, Z., Hu, J., & Huang, J. K. (2024) · doi:10.1101/2024.12.25.630253 · Cited by 3 · see citing works
Single-cell gene expression and chromatin accessibility profiling of human pancreatic islets at basal and stimulatory conditions nominates mechanisms of type 1 diabetes genetic riskPreprint
Albanus, R. D., Tang, X., Taylor, H. J., Manickam, N., Erdos, M. R., Narisu, N., Han, Y., Orchard, P., Varshney, A., Liu, C., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.12.516291 · Cited by 2 · see citing works
The effect of background noise and its removal on the analysis of single-cell expression dataPreprint
Janssen, P., Kliesmete, Z., Vieth, B., Adiconis, X., Simmons, S., Marshall, J. L., Aubin, C., Heyn, H., Levin, J. Z., Enard, W., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.16.516780 · Cited by 3 · see citing works
An extra-circadian function for human CLOCK in the neocortexPreprint
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Eisen, M. B. (2023) · eLife · doi:10.7554/elife.84628.1.sa4
Author Response: The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics
Weber, L. M., Divecha, H. R., Tran, M. N., Kwon, S. H., Spangler, A., Montgomery, K. D., Tippani, M., Bharadwaj, R. A., Kleinman, J. E., Page, S. C., et al. (2023) · eLife · doi:10.7554/elife.84628.1.sa0
Reviewer #2 (Public Review): The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics
(2023) · eLife · doi:10.7554/elife.84628.1.sa2

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Authors: Caglayan, E., Liu, Y., & Konopka, G.
Affiliations: The University of Texas Southwestern Medical Center (US)
Corresponding author: Caglayan, Emre
ORCID: Caglayan, Emre
Liu, Yuxiang
Venue: Neuron
Publisher: Elsevier BV
Published: 2022-12
Volume: 110
Issue: 24
Pages: 4043-4056.e5
ISSN: 0896-6273 (ISSN-L)
DOI: 10.1016/j.neuron.2022.09.010
PMC: PMC9789184
OpenAlex: W4305016438
Cited by: 123
References: 60
Citations by year: 2026: 35 · 2025: 32 · 2024: 28 · 2023: 25 · 2022: 3
FWCI: 7.58
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 385 d)
doi.org/10.15223/policy-017 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-012 (stm-asf)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-004 (stm-asf)
Locations: Neuron (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: James S. McDonnell Foundation
American Heart Association (915654)
University of Texas Southwestern Medical Center
National Institute of Mental Health (MH103517, MH126481, R01MH103517, R01MH126481)
National Human Genome Research Institute (R01HG011641, HG011641)
National Institute of Neurological Disorders and Stroke (NS115821, UF1NS115821)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords: single-nucleus RNA sequencing, brain cell types, oligodendrocyte precursor cells, cell type annotation, human brain
MeSH terms: Adult, Cell Nucleus, Humans, Neurons, RNA, RNA, Small Nuclear, Sequence Analysis, RNA, Solitary Nucleus, Single-Cell Analysis

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Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets

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