PUBLICATIONS (ORCID)

Fast, sensitive and accurate integration of single-cell data with Harmony

Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-ru Loh, and Soumya Raychaudhuri

Abstract: The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~106 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.

Paper: Nature Methods. November 18, 2019. doi:10.1038/s41592-019-0619-0 | Pubmed | PDF

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Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

Chenglong Xia*, Jean Fan*, George Emanuel*, Junjie Hao, and Xiaowei Zhuang

Abstract: The spatial organization of RNAs within cells and spatial patterning of cells within tissues play crucial roles in many biological processes. Here, we demonstrate that multiplexed error-robust FISH (MERFISH) can achieve near-genome-wide, spatially resolved RNA profiling of individual cells with high accuracy and high detection efficiency. Using this approach, we identified RNA species enriched in different subcellular compartments, observed transcriptionally distinct cell states corresponding to different cell-cycle phases, and revealed spatial patterning of transcriptionally distinct cells. Spatially resolved transcriptome quantification within cells further enabled RNA velocity and pseudotime analysis, which revealed numerous genes with cell cycle-dependent expression. We anticipate that spatially resolved transcriptome analysis will advance our understanding of the interplay between gene regulation and spatial context in biological systems.

Paper: PNAS. Sept 9, 2019, doi:10.1073/pnas.1912459116 | Pubmed | PDF

A Murine Model of Chronic Lymphocytic Leukemia Based on B Cell-Restricted Expression of Sf3b1 Mutation and Atm Deletion

Shanye Yin, Rutendo G. Gambe, Jing Sun, Aina Zurita Martinez, Zachary J.Cartun, Fara Faye D.Regis, Youzhong Wan, Jean Fan, Angela N.Brooks, Sarah E. M. Herman, Elisaten Hacken, AmaroTaylor-Weiner, Laura Z. Rassenti, Emanuela M. Ghia, Thomas J. Kipps, Esther A. Obeng, Carrie L. Cibulskis, Donna Neuberg, Dean R.Campagna, Mark D. Fleming, Benjamin L. Ebert, Adrian Wiestner, Ignaty Leshchiner, James A. DeCaprio, Gad Getz, Robin Reed, Ruben D. Carrasco, Catherine J. Wu, Lili Wang

Abstract: SF3B1 is recurrently mutated in chronic lymphocytic leukemia (CLL), but its role in the pathogenesis of CLL remains elusive. Here, we show that conditional expression of Sf3b1-K700E mutation in mouse B cells disrupts pre-mRNA splicing, alters cell development, and induces a state of cellular senescence. Combination with Atm deletion leads to the overcoming of cellular senescence and the development of CLL-like disease in elderly mice. These CLL-like cells show genome instability and dysregulation of multiple CLL-associated cellular processes, including deregulated B cell receptor signaling, which we also identified in human CLL cases. Notably, human CLLs harboring SF3B1 mutations exhibit altered response to BTK inhibition. Our murine model of CLL thus provides insights into human CLL disease mechanisms and treatment.

Paper: Cancer Cell. Feb 11, 2019. doi:10.1016/j.ccell.2018.12.013 | Pubmed | PDF

RNA velocity of single cells

Gioele La Manno, Ruslan Soldatov, Amit Zeisel, Emelie Braun, Hannah Hochgerner, Viktor Petukhov, Katja Lidschreiber, Maria E Kastriti, Peter Lönnerberg, Alessandro Furlan, Jean Fan, Lars E Borm, Zehua Liu, David van Bruggen, Jimin Guo, Xiaoling He, Roger Barker, Erik Sundström, Gonçalo Castelo-Branco, Patrick Cramer, Igor Adameyko, Sten Linnarsson, Peter V Kharchenko

Abstract: RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity—the time derivative of the gene expression state—can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

Paper: Nature. August 8, 2018. doi:10.1038/s41586-018-0414-6 | Pubmed | PDF

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Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data

Jean Fan*, Hae-Ock Lee*, Soohyun Lee, Da-eun Ryu, Semin Lee, Catherine Xue, Seok Jin Kim, Kihyun Kim, Nikolas Barkas, Peter J Park, Woong-Yang Park and Peter V Kharchenko

Abstract: Characterization of intratumoral heterogeneity is critical to cancer therapy, as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct underlying subclonal architecture. Examining several tumor types, we show that HoneyBADGER is effective at identifying deletion, amplifications, and copy-neutral loss-of-heterozygosity events, and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Surprisingly, other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure, and were likely driven by alternative, non-clonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer.

Paper: Genome Research. June 13, 2018. doi:10.1101/gr.228080.117 | Pubmed | PDF

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Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain

Blue B Lake*, Song Chen*, Brandon C Sos*, Jean Fan*, Gwendolyn E Kaeser, Yun C Yung, Thu E Duong, Derek Gao, Jerold Chun, Peter V Kharchenko, Kun Zhang

Abstract: Detailed characterization of the cell types in the human brain requires scalable experimental approaches to examine multiple aspects of the molecular state of individual cells, as well as computational integration of the data to produce unified cell-state annotations. Here we report improved high-throughput methods for single-nucleus droplet-based sequencing (snDrop-seq) and single-cell transposome hypersensitive site sequencing (scTHS-seq). We used each method to acquire nuclear transcriptomic and DNA accessibility maps for >60,000 single cells from human adult visual cortex, frontal cortex, and cerebellum. Integration of these data revealed regulatory elements and transcription factors that underlie cell-type distinctions, providing a basis for the study of complex processes in the brain, such as genetic programs that coordinate adult remyelination. We also mapped disease-associated risk variants to specific cellular populations, which provided insights into normal and pathogenic cellular processes in the human brain. This integrative multi-omics approach permits more detailed single-cell interrogation of complex organs and tissues.

Paper: Nature Biotechnology. December 11, 2017. doi:10.1038/nbt.4038 | Pubmed | PDF

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Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

Lili Wang*, Jean Fan*, Joshua M. Francis, George Georghiou, Sarah Hergert, Shuqiang Li, Rutendo Gambe, Chensheng W. Zhou, Chunxiao Yang, Sheng Xiao, Paola Dal Cin, Michaela Bowden, Dylan Kotliar, Sachet A. Shukla, Jennifer R. Brown, Donna Neuberg, Dario R. Alessi, Cheng-Zhong Zhang, Peter V. Kharchenko, Kenneth J. Livak, Catherine J. Wu

Abstract: Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype–phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Paper: Genome Research. May 22, 2017. doi/10.1101/gr.217331.116 | Pubmed | PDF

Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

Lili Wang*, Angela N. Brooks*, Jean Fan*, Youzhong Wan*, Rutendo Gambe, Shuqiang Li, Sarah Hergert, Shanye Yin, Samuel S. Freeman, Joshua Z. Levin, Lin Fan, Michael Seiler, Silvia Buonamici, Peter G. Smith, Kevin F. Chau, Carrie L. Cibulskis, Wandi Zhang, Laura Z. Rassenti, Emanuela M. Ghia, Thomas J. Kipps, Stacey Fernandes, Donald B. Bloch, Dylan Kotliar, Dan A. Landau, Sachet A. Shukla, Jon C. Aster, Robin Reed, David S. DeLuca, Jennifer R. Brown, Donna Neuberg, Gad Getz, Kenneth J. Livak, Matthew M. Meyerson, Peter V. Kharchenko, Catherine J. Wu

Abstract: Mutations in SF3B1, which encodes a spliceosome component, are associated with poor outcome in chronic lymphocytic leukemia (CLL), but how these contribute to CLL progression remains poorly understood. We undertook a transcriptomic characterization of primary human CLL cells to identify transcripts and pathways affected by SF3B1 mutation. Splicing alterations, identified in the analysis of bulk cells, were confirmed in single SF3B1-mutated CLL cells and also found in cell lines ectopically expressing mutant SF3B1. SF3B1 mutation was found to dysregulate multiple cellular functions including DNA damage response, telomere maintenance, and Notch signaling (mediated through KLF8 upregulation, increased TERC and TERT expression, or altered splicing of DVL2 transcript, respectively). SF3B1 mutation leads to diverse changes in CLL-related pathways.

Paper: Cancer Cell. November 3, 2016. doi.org/10.1016/j.ccell.2016.10.005 | Pubmed | PDF

Cell-Type-Specific Alternative Splicing Governs Cell Fate in the Developing Cerebral Cortex

Xiaochang Zhang, Ming Hui Chen, Xuebing Wu, Andrew Kodani, Jean Fan, Ryan Doan, Manabu Ozawa, Jacqueline Ma, Nobuaki Yoshida, Jeremy F. Reiter, Douglas L. Black, Peter V. Kharchenko, Phillip A. Sharp, Christopher A. Walsh

Abstract: Alternative splicing is prevalent in the mammalian brain. To interrogate the functional role of alternative splicing in neural development, we analyzed purified neural progenitor cells (NPCs) and neurons from developing cerebral cortices, revealing hundreds of differentially spliced exons that preferentially alter key protein domains—especially in cytoskeletal proteins—and can harbor disease-causing mutations. We show that Ptbp1 and Rbfox proteins antagonistically govern the NPC-to-neuron transition by regulating neuron-specific exons. Whereas Ptbp1 maintains apical progenitors partly through suppressing a poison exon of Flna in NPCs, Rbfox proteins promote neuronal differentiation by switching Ninein from a centrosomal splice form in NPCs to a non-centrosomal isoform in neurons. We further uncover an intronic human mutation within a PTBP1-binding site that disrupts normal skipping of the FLNA poison exon in NPCs and causes a brain-specific malformation. Our study indicates that dynamic control of alternative splicing governs cell fate in cerebral cortical development.

Paper: Cell. August 25, 2016. doi.org/10.1016/j.cell.2016.07.025 | Pubmed | PDF

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Clonal evolution in patients with chronic lymphocytic leukaemia developing resistance to BTK inhibition

Jan A. Burger*, Dan A. Landau*, Amaro Taylor-Weiner*, Ivana Bozic*, Huidan Zhang*, Kristopher Sarosiek, Lili Wang, Chip Stewart, Jean Fan, Julia Hoellenriegel, Mariela Sivina, Adrian M. Dubuc, Cameron Fraser, Yulong Han, Shuqiang Li, Kenneth J. Livak, Lihua Zou, Youzhong Wan, Sergej Konoplev, Carrie Sougnez, Jennifer R. Brown, Lynne V. Abruzzo, Scott L. Carter, Michael J. Keating, Matthew S. Davids, William G. Wierda, Kristian Cibulskis, Thorsten Zenz, Lillian Werner, Paola Dal Cin, Peter Kharchencko, Donna Neuberg, Hagop Kantarjian, Eric Lander, Stacey Gabriel, Susan O’Brien, Anthony Letai, David A. Weitz, Martin A. Nowak, Gad Getz, Catherine J. Wu

Abstract: Resistance to the Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib has been attributed solely to mutations in BTK and related pathway molecules. Using whole-exome and deep-targeted sequencing, we dissect evolution of ibrutinib resistance in serial samples from five chronic lymphocytic leukaemia patients. In two patients, we detect BTK-C481S mutation or multiple PLCG2 mutations. The other three patients exhibit an expansion of clones harbouring del(8p) with additional driver mutations (EP300, MLL2 and EIF2A), with one patient developing trans-differentiation into CD19-negative histiocytic sarcoma. Using droplet-microfluidic technology and growth kinetic analyses, we demonstrate the presence of ibrutinib-resistant subclones and estimate subclone size before treatment initiation. Haploinsufficiency of TRAIL-R, a consequence of del(8p), results in TRAIL insensitivity, which may contribute to ibrutinib resistance. These findings demonstrate that the ibrutinib therapy favours selection and expansion of rare subclones already present before ibrutinib treatment, and provide insight into the heterogeneity of genetic changes associated with ibrutinib resistance.

Paper: Nature Communications. May 20, 2016. doi:10.1038/ncomms11589 | Pubmed | PDF

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Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis

Jean Fan, Neeraj Salathia, Rui Liu, Gwendolyn E Kaeser, Yun C Yung, Joseph L Herman, Fiona Kaper, Jian-Bing Fan, Kun Zhang, Jerold Chun, Peter V Kharchenko

Abstract: The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However, identifying such aspects from noisy single-cell RNA-seq data remains challenging. We developed pathway and gene set overdispersion analysis (PAGODA) to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.

Paper: Nature Methods. Jan 18, 2016. doi:10.1038/nmeth.3734 | Pubmed | PDF

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Locally Disordered Methylation Forms the Basis of Intratumor Methylome Variation in Chronic Lymphocytic Leukemia

Dan A. Landau*, Kendell Clement*, Michael J. Ziller, Patrick Boyle, Jean Fan, Hongcang Gu, Kristen Stevenson, Carrie Sougnez, Lili Wang, Shuqiang Li, Dylan Kotliar, Wandi Zhang, Mahmoud Ghandi, Levi Garraway, Stacey M. Fernandes, Kenneth J. Livak, Stacey Gabriel, Andreas Gnirke, Eric S. Lander, Jennifer R. Brown, Donna Neuberg, Peter V. Kharchenko, Nir Hacohen, Gad Getz, Alexander Meissner, Catherine J. Wu

Abstract: Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of 104 primary chronic lymphocytic leukemias (CLLs). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylation disorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.

Paper: Cancer Cell. Dec 8, 2014. doi:10.1016/j.ccell.2014.10.012 | Pubmed | PDF