Comprehensive Bulk and Single Cell Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2906-2906 ◽  
Author(s):  
Jean Fan ◽  
Lili Wang ◽  
Angela N Brooks ◽  
Youzhong Wan ◽  
Donna S Neuberg ◽  
...  

Abstract Large-scale sequencing efforts have identified SF3B1 as arecurrently mutated gene in chronic lymphocytic leukemia (CLL). While SF3B1 mutations have been associated with adverse clinical outcome in CLL, mechanistic understanding of its role in the oncogenic phenotype remains lacking. We therefore undertook a comprehensive transcriptomic characterization of CLL in relation to SF3B1 mutation status at both bulk and single cell levels. We first profiled bulk mature poly-A selected RNA by sequencing (RNA-seq) from 37 CLLs (13 SF3B1 wild-type, 24 mutated). After identifying and classifying splice alterations using the tool JuncBASE, we found SF3B1 mutation to be associated with increased alternative splicing, with the most pervasive changes in 3' splice site selection. 304 alternatively spliced events were significantly associated with SF3B1 mutation, 4 of which we validated by qRT-PCR in 20 independent CLL samples with known SF3B1 mutation status. We further identified 1963 differentially expressed genes (q < 0.2) associated with SF3B1 mutation. By gene set enrichment analysis, SF3B1 mutation appeared to impact a variety of cancer and CLL-associated gene pathways, including DNA damage response, apoptosis regulation, chromatin remodeling, RNA processing, and Notch activation (q < 0.01). ~20% of these gene sets were also found to be significantly enriched for genes exhibiting alternative splicing in association with SF3B1 mutation. As SF3B1 acts at the level of pre-mRNA, we also performed bulk RNA-seq with total RNA libraries generated from 5 CLLs (2 SF3B1 wild-type, 3 with the common K700E mutation). We again observed an enrichment of 3' splice site changes, along with ~30% overlap of differentially expressed genes, and ~16% overlap of enriched gene sets with the aforementioned poly-A data analysis. One differentially over-expressed gene associated with SF3B1 mutation unique to this total RNA data analysis and validated by total RNA qPCR of independent CLL samples was TERC, an essential RNA component of telomerase that serves as a replication template during telomeric elongation. TERC is a non-polyadenylated transcript and thus was undetected by our previous poly-A selected RNA-seq and by targeted qRT-PCR of oligo dT-generated cDNA. Recent reports have highlighted the involvement of the spliceosome in telomerase RNA processing, and shorter telomere length of CLLs with SF3B1 mutation. Thus, although further investigation will be needed, our analyses suggest a potential mechanism by which SF3B1 mutation contributes to aberrant regulation of telomerase activity. Since SF3B1 is commonly found as a subclonal mutation in CLL, and because signals obtained from bulk analyses reflect only the average characteristics of the population, we assessed the transcriptomic effects of SF3B1 mutation in single cells within a subset of CLL cases. We developed a novel and sensitive microfluidic approach that performs multiplexed targeted amplification of RNA to simultaneously detect somatic mutation status, gene expression (96 targets), and alternative splicing (45 targets) within the same individual cell for 96 to 288 cells from 5 patients with different SF3B1 mutations. From the same patient sample, single cells with SF3B1 mutation generally exhibited increased alternative splicing for events identified from the bulk analysis, thus confirming the association of SF3B1 mutation with altered splicing at the single cell level. Different SF3B1 hotspot mutations within the HEAT repeat domains exhibited similar patterns of alternative splicing while a mutation outside of the repeat domain did not. Furthermore, we confirmed significant changes in gene expression between SF3B1 wild-type and mutant cells of target genes involved in the Notch pathway (NCOR2), cell cycle (CDKN2A, CCND1) and apoptosis (TXNIP). Consistent with these analyses, functional studies with overexpression of full-length mutated SF3B1 in a hematopoietic cell lines confirmed the modulation of these pathways by this putative CLL driver. Our high-resolution single cell analysis further uncovered 2 transcription factors strongly associated with SF3B1 mutation but not previously appreciated (KLF3 and KLF8). Our comprehensive transcriptomic analysis thus highlights SF3B1 mutation as an efficient mechanism by which a complex of changes relevant to CLL biology are generated that can contribute to disease progression. Disclosures Kipps: Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Li:Fluidigm: Employment. Livak:Fluidigm: Employment.

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew X. Chen ◽  
Robyn D. Gartrell ◽  
Junfei Zhao ◽  
Pavan S. Upadhyayula ◽  
Wenting Zhao ◽  
...  

Abstract Background Macrophages are the most common infiltrating immune cells in gliomas and play a wide variety of pro-tumor and anti-tumor roles. However, the different subpopulations of macrophages and their effects on the tumor microenvironment remain poorly understood. Methods We combined new and previously published single-cell RNA-seq data from 98,015 single cells from a total of 66 gliomas to profile 19,331 individual macrophages. Results Unsupervised clustering revealed a pro-tumor subpopulation of bone marrow-derived macrophages characterized by the scavenger receptor MARCO, which is almost exclusively found in IDH1-wild-type glioblastomas. Previous studies have implicated MARCO as an unfavorable marker in melanoma and non-small cell lung cancer; here, we find that bulk MARCO expression is associated with worse prognosis and mesenchymal subtype. Furthermore, MARCO expression is significantly altered over the course of treatment with anti-PD1 checkpoint inhibitors in a response-dependent manner, which we validate with immunofluorescence imaging. Conclusions These findings illustrate a novel macrophage subpopulation that drives tumor progression in glioblastomas and suggest potential therapeutic targets to prevent their recruitment.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3887-3887
Author(s):  
Moosa Qureshi ◽  
Fernando Calero-Nieto ◽  
Iwo Kucinski ◽  
Sarah Kinston ◽  
George Giotopoulos ◽  
...  

Abstract The C/EBPα transcription factor plays a pivotal role in myeloid differentiation and E2F-mediated cell cycle regulation. Although CEBPA mutations are common in acute myeloid leukaemia (AML), little is known regarding pre-leukemic alterations caused by mutated CEBPA. Here, we investigated early events involved in pre-leukemic transformation driven by CEBPA N321D in the LMPP-like cell line Hoxb8-FL (Redecke et al., Nat Methods 2013), which can be maintained in vitro as a self-renewing LMPP population using Flt3L and estradiol, as well as differentiated both in vitro and in vivo into myeloid and lymphoid cell types. Hoxb8-FL cells were retrovirally transduced with Empty Vector (EV), wild-type CEBPA (CEBPA WT) or its N321D mutant form (CEBPA N321D). CEBPA WT-transduced cells showed increased expression of cd11b and SIRPα and downregulation of c-kit, suggesting that wild-type CEBPA was sufficient to promote differentiation even under LMPP growth conditions. Interestingly, we did not observe the same phenotype in CEBPA N321D-transduced cells. Upon withdrawal of estradiol, both EV and CEBPA WT-transduced cells differentiated rapidly into a conventional dendritic cell (cDC) phenotype by day 7 and died within 12 days. By contrast, CEBPA N321D-transduced cells continued to grow for in excess of 56 days, with an initial cDC phenotype but by day 30 demonstrating a plasmacytoid dendritic cell precursor phenotype. CEBPA N321D-transduced cells were morphologically distinct from EV-transduced cells. To test leukemogenic potential in vivo, we performed transplantation experiments in lethally irradiated mice. Serial monitoring of peripheral blood demonstrated that Hoxb8-FL derived cells had disappeared by 4 weeks, and did not reappear. However, at 6 months CEBPA N321D-transduced cells could still be detected in bone marrow in contrast to EV-transduced cells but without any leukemic phenotype. To identify early events involved in pre-leukemic transformation, the differentiation profiles of EV, CEBPA WT and CEBPA N321D-transduced cells were examined with single cell RNA-seq (scRNA-seq). 576 single cells were taken from 3 biological replicates at days 0 and 5 post-differentiation, and analysed using the Automated Single-Cell Analysis Pipeline (Gardeux et al., Bioinformatics 2017). Visualisation by t-SNE (Fig 1) demonstrated: (i) CEBPA WT-transduced cells formed a distinct cluster at day 0 before withdrawal of estradiol; (ii) CEBPA N321D-transduced cells separated from EV and CEBPA WT-transduced cells after 5 days of differentiation, (iii) two subpopulations could be identified within the CEBPA N321D-transduced cells at day 5, with a cluster of five CEBPA N321D-transduced single cells distributed amongst or very close to the day 0 non-differentiated cells. Differential expression analysis identified 224 genes upregulated and 633 genes downregulated specifically in the CEBPA N321D-transduced cells when compared to EV cells after 5 days of differentiation. This gene expression signature revealed that CEBPA N321D-transduced cells switched on a HSC/MEP/CMP transcriptional program and switched off a myeloid dendritic cell program. Finally, in order to further dissect the effect of the N321D mutation, the binding profile of endogenous and CEBPA N321D was compared by ChIP-seq before and after 5 days of differentiation. Integration with scRNA-seq data identified 160 genes specifically downregulated in CEBPA N321D-transduced cells which were associated with the binding of the mutant protein. This list of genes included genes previously implicated in dendritic cell differentiation (such as NOTCH2, JAK2), as well as a number of genes not previously implicated in the evolution of AML, representing potentially novel therapeutic targets. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1943-1943 ◽  
Author(s):  
Lili Wang ◽  
Dylan Kotliar ◽  
Jean Fan ◽  
Shuqiang Li ◽  
Jonna Grimsby ◽  
...  

Abstract Cancer cell phenotype is controlled by both genetic composition and gene expression. Recent large-scale cancer sequencing studies have revealed extensive intratumoral genetic heterogeneity and have demonstrated its potential impact on clonal evolution and clinical outcome. The most direct approach to uncovering the impact of genetic heterogeneity on cellular phenotype requires integration of genetic and transcriptomic profiles of single cells. Currently, however, RNA and DNA cannot be reliably isolated from the same cell. Here, we demonstrate the feasibility for linking single-cell somatic mutation data with cellular transcriptional heterogeneity through a targeted RNA-based approach. By leveraging a microfluidic platform (Fluidigm BioMarkTMHD system) to perform multiplexed targeted amplification of RNA derived from hundreds of single cells, we have generated a versatile approach for the integrated detection of somatic mutations in relation to specific gene transcripts. We focused on a series of chronic lymphocytic leukemia (CLL) B cells that were previously characterized by bulk whole-exome (WES) and RNA-sequencing (RNA-Seq). We developed 2 classes of assays. First, we generated multiplexed nested quantitative RT-PCR assays of 96 genes with known involvement in CLL biology. Second, to simultaneously detect patient-specific somatic mutations in the same cell, we devised multiplexed pre-amplification primers targeting transcribed regions containing somatic point mutations. These regions were then amplified using paired nested primers, for detection of the wild-type or mutant alleles. We focused on those somatic mutations with detectable expression in bulk CLL RNA (> 5 FPKM by RNA-seq). When applied to either artificial oligonucleotide templates or bulk patient cDNA, these paired wild-type and mutant allele detection assays reliably demonstrated consistent differences in DCT values of >6 cycles. In total, we designed expression assays for 96 genes and 46 mutation detection applied to 5 CLL samples (median of 9 assays/sample, range 6-13). We examined up to 384 single cells from each of 5 samples and from normal CD19+ B cells. Based on expression of housekeeping genes ACTB and B2M, we observed viable expression in 1951 of 2112 cells (92.4%). We could clearly discern that expression of the 96 genes was heterogeneous across 354 single CLL-B cells and could discriminate CLL from 174 normal B cells by principal component analysis. 32 out of 46 (70%) mutation detection assays successfully distinguished between wild-type and mutant alleles and the mutant allele was consistently observed in the originating CLL cells, but not in unrelated CLL or non-leukemic B cells. Our RNA-based estimates of allele frequency agreed with single-cell targeted DNA-based detection of somatic mutations conducted for 3 of 5 CLL samples as well as with frequencies estimated from bulk WES-based cancer cell fraction (CCF) measurements. We applied our integrated assay design to 2 CLL samples known to harbor mutations in the putative CLL driver SF3B1: Patient 1 with bulk CCF of 17% (G742D) and Patient 2 with 87% (K700E). Mutation of this critical spliceosome component broadly changes RNA splicing profiles although the functional impact of these alternative splice variants on CLL biology remains unknown. We generated multiplex assays for SF3B1 mutation detection and for expression of mutation-associated alternative splice variants. Consistent with the bulk-sequencing results, we detected 50 of 373 (13.4%) single CLL cells from Patient 1 with SF3B1 mutation. Moreover, the subset of cells with SF3B1 mutation demonstrated high expression of splice variants relative to wild-type cells (GCC2 and MAP3K7, p< 0.000001). This SF3B1 mutated subclone also displayed reduced expression of RNA splicing factors (BTAF1, DDX17, SNW1, SRSF3, U2SURP; all p<0.05), cell cycle regulators (CDC27, PDS5A; p<0.015) and an inflammatory pathway gene (MALT1p=0.039), suggesting involvement of SF3B1 mutation in these biological processes. Analysis of Patient 2 is ongoing. Taken together, our study demonstrates the feasibility of linking genotype with gene expression at the RNA level. Furthermore, these analyses reveal the potential for single cell RNA-based analysis to directly uncover the effects of driver mutations on the leukemia cell phenotype. Disclosures Brown: Sanofi, Onyx, Vertex, Novartis, Boehringer, GSK, Roche/Genentech, Emergent, Morphosys, Celgene, Janssen, Pharmacyclics, Gilead: Consultancy.


2016 ◽  
Author(s):  
Olivier Poirion ◽  
Xun Zhu ◽  
Travers Ching ◽  
Lana X. Garmire

AbstractDespite its popularity, characterization of subpopulations with transcript abundance is subject to a significant amount of noise. We propose to use effective and expressed nucleotide variations (eeSNVs) from scRNA-seq as alternative features for tumor subpopulation identification. We developed a linear modeling framework, SSrGE, to link eeSNVs associated with gene expression. In all the datasets tested, eeSNVs achieve better accuracies than gene expression for identifying subpopulations. Previously validated cancer-relevant genes are also highly ranked, confirming the significance of the method. Moreover, SSrGE is capable of analyzing coupled DNA-seq and RNA-seq data from the same single cells, demonstrating its value in integrating multi-omics single cell techniques. In summary, SNV features from scRNA-seq data have merits for both subpopulation identification and linkage of genotype-phenotype relationship. The method SSrGE is available at https://github.com/lanagarmire/SSrGE.


2020 ◽  
Author(s):  
Alina Isakova ◽  
Norma Neff ◽  
Stephen R. Quake

ABSTRACTThe ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current RNA-seq methods are unable to simultaneously monitor both short and long, poly(A)+ and poly(A)-transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here, we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and non-coding RNA from a single cell. Built upon the template-switch mechanism, Smart-seq-total bears the key feature of its predecessor, Smart-seq2, namely, the ability to capture full-length transcripts with high yield and quality. It also outperforms current poly(A)–independent total RNA-seq protocols by capturing transcripts of a broad size range, thus, allowing us to simultaneously analyze protein-coding, long non-coding, microRNA and other non-coding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T and MCF7 cells as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. We show that simultaneous measurement of non-coding RNA and mRNA from the same cell enables elucidation of new roles of non-coding RNA throughout essential processes such as cell cycle or lineage commitment. Moreover, we show that cell types can be distinguished based on the abundance of non-coding transcripts alone.


2021 ◽  
Vol 118 (51) ◽  
pp. e2113568118
Author(s):  
Alina Isakova ◽  
Norma Neff ◽  
Stephen R. Quake

The ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current single-cell RNA-sequencing (RNA-seq) methods are unable to simultaneously monitor all forms of RNA transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and noncoding RNA from a single cell. Smart-seq-total does not require splitting the RNA content of a cell and allows the incorporation of unique molecular identifiers into short and long RNA molecules for absolute quantification. It outperforms current poly(A)-independent total RNA-seq protocols by capturing transcripts of a broad size range, thus enabling simultaneous analysis of protein-coding, long-noncoding, microRNA, and other noncoding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T, and MCF7 cells, as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. By analyzing the coexpression patterns of both noncoding RNA and mRNA from the same cell, we were able to discover new roles of noncoding RNA throughout essential processes, such as cell cycle and lineage commitment during embryonic development. Moreover, we show that independent classes of short-noncoding RNA can be used to determine cell-type identity.


2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii108-ii108
Author(s):  
Hailong Liu ◽  
Yongqiang Liu ◽  
Janusz Franco-Barraza ◽  
Xinguang Yu ◽  
Shiyu Feng

Abstract Poor response of human glioblastoma to current therapies are influenced by tumor microenvironment. Although glioblastoma is recognized by large enrichment of microglia, characterization of diverse cell subsets and their functions remain challenging because of high heterogenicity. Here, we analyzed single-cell transcriptomics to comprehensively map the cell populations and determine the roles of microglia in IDH1/2 wild-type (IDH-wt) glioblastoma progression. Besides finding microglia were significantly enriched in IDH-wt glioblastoma compared to IDH1/2 mutant (IDH-mut) gliomas, we identified a unique high-grade glioma microglia (HGAM) subtype characterized by proinflammatory and stem-like features. In particular, HGAM’s pro-tumoral IL1β secretion is mediated via ApoE-induced activation of NLRP1 inflammasome. HGAM phagocytosed OPC-like malignant cells forming the neoplastic microglia, which presented the stem-like potential giving rise to activated microglia. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation. Additionally, an intricated evaluation of glioma patients revealed that SETD2 mutation/low-expression correlated with adverse prognosis. Further analysis showed that SETD2 -dificient tumor cells presented hypersensitivity to HGAM-derived IL1β via epigenetic dysregulation of PHF6. Also, SETD2 -deficient tumor cells produced TGF-β1 contributing to microglia activation. Finally, targeting the TGF-β1/TβRI signaling impaired HGAM activation and tumor growth. Our studies identify a unique neoplastic microglia subpopulation and establish cellular basis of interactions with tumor cells important for disease progression.


Author(s):  
Carlos F. Buen Abad Najar ◽  
Nir Yosef ◽  
Liana F. Lareau

Single cell RNA sequencing provides powerful insight into the factors that determine each cell’s unique identity, including variation in transcription and RNA splicing among diverse cell types. Previous studies led to the surprising observation that alternative splicing outcomes among single cells are highly variable and follow a bimodal pattern: a given cell consistently produces either one or the other isoform for a particular splicing choice, with few cells producing both isoforms. Here we show that this pattern arises almost entirely from technical limitations. We analyzed single cell alternative splicing in human and mouse single cell RNA-seq datasets, and modeled them with a probablistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms in single cells. This gives the appearance of a binary isoform distribution, even when the underlying reality is consistent with more than one isoform per cell. We show that accounting for the true amount of information recovered can produce biologically meaningful measurements of splicing in single cells.


eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Carlos F Buen Abad Najar ◽  
Nir Yosef ◽  
Liana F Lareau

Single-cell RNA sequencing provides powerful insight into the factors that determine each cell’s unique identity. Previous studies led to the surprising observation that alternative splicing among single cells is highly variable and follows a bimodal pattern: a given cell consistently produces either one or the other isoform for a particular splicing choice, with few cells producing both isoforms. Here, we show that this pattern arises almost entirely from technical limitations. We analyze alternative splicing in human and mouse single-cell RNA-seq datasets, and model them with a probabilistic simulator. Our simulations show that low gene expression and low capture efficiency distort the observed distribution of isoforms. This gives the appearance of binary splicing outcomes, even when the underlying reality is consistent with more than one isoform per cell. We show that accounting for the true amount of information recovered can produce biologically meaningful measurements of splicing in single cells.


2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.


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