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Tian Y, Wu L, Huang CC, Wang L. Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.599704. [PMID: 38948854 PMCID: PMC11213234 DOI: 10.1101/2024.06.19.599704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.
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Affiliation(s)
- Yijun Tian
- Department of Tumor Biology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, United States
| | - Lang Wu
- Population Sciences in the Pacific Program, University of Hawai i Cancer Center, University of Hawai i at Mānoa, Honolulu, HI 96813, USA
| | - Chang-Ching Huang
- Zilber College of Public Health, University of Wisconsin, Milwaukee, WI 53226, United States
| | - Liang Wang
- Department of Tumor Biology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, United States
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2
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Jiang TT, Cao S, Kruglov O, Virmani A, Geskin LJ, Falo LD, Akilov OE. Deciphering Tumor Cell Evolution in Cutaneous T-Cell Lymphomas: Distinct Differentiation Trajectories in Mycosis Fungoides and Sézary Syndrome. J Invest Dermatol 2024; 144:1088-1098. [PMID: 38036289 PMCID: PMC11034798 DOI: 10.1016/j.jid.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/08/2023] [Accepted: 10/25/2023] [Indexed: 12/02/2023]
Abstract
Cutaneous T-cell lymphomas are a heterogeneous group of neoplasms originating in the skin, with mycosis fungoides (MF) and Sézary syndrome (SS) representing the most common variants. The cellular origin of cutaneous lymphomas has remained controversial owing to their immense phenotypic heterogeneity that obfuscates lineage reconstruction on the basis of classical surface biomarkers. To overcome this heterogeneity and reconstruct the differentiation trajectory of malignant cells in MF and SS, TCR sequencing was performed in parallel with targeted transcriptomics at the single-cell resolution among cutaneous samples in MF and SS. Unsupervised lineage reconstruction showed that Sézary cells exist as a population of CD4+ T cells distinct from those in patch, plaque, and tumor MF. Further investigation of malignant cell heterogeneity in SS showed that Sézary cells phenotypically comprised at least 3 subsets on the basis of differential proliferation potentials and expression of exhaustion markers. A T helper 1-polarized cell type, intermediate cell type, and exhausted T helper 2-polarized cell type were identified, with T helper 1- and T helper 2-polarized cells displaying divergent proliferation potentials. Collectively, these findings provide evidence to clarify the relationship between MF and SS and reveal cell subsets in SS that suggest a possible mechanism for therapeutic resistance.
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Affiliation(s)
- Tony T Jiang
- Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Simon Cao
- Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Oleg Kruglov
- Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Aman Virmani
- School of Art and Science, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Larisa J Geskin
- Department of Dermatology, Columbia University, New York, New York, USA
| | - Louis D Falo
- Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Oleg E Akilov
- Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
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3
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Inayatullah M, Mahesh A, Turnbull AK, Dixon JM, Natrajan R, Tiwari VK. Basal-epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer. EMBO Mol Med 2024; 16:823-853. [PMID: 38480932 PMCID: PMC11018633 DOI: 10.1038/s44321-024-00050-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 02/07/2024] [Accepted: 02/14/2024] [Indexed: 03/18/2024] Open
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by extensive intratumoral heterogeneity, high metastasis, and chemoresistance, leading to poor clinical outcomes. Despite progress, the mechanistic basis of these aggressive behaviors remains poorly understood. Using single-cell and spatial transcriptome analysis, here we discovered basal epithelial subpopulations located within the stroma that exhibit chemoresistance characteristics. The subpopulations are defined by distinct signature genes that show a frequent gain in copy number and exhibit an activated epithelial-to-mesenchymal transition program. A subset of these genes can accurately predict chemotherapy response and are associated with poor prognosis. Interestingly, among these genes, elevated ITGB1 participates in enhancing intercellular signaling while ACTN1 confers a survival advantage to foster chemoresistance. Furthermore, by subjecting the transcriptional signatures to drug repurposing analysis, we find that chemoresistant tumors may benefit from distinct inhibitors in treatment-naive versus post-NAC patients. These findings shed light on the mechanistic basis of chemoresistance while providing the best-in-class biomarker to predict chemotherapy response and alternate therapeutic avenues for improved management of TNBC patients resistant to chemotherapy.
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Affiliation(s)
- Mohammed Inayatullah
- Institute for Molecular Medicine, University of Southern Denmark, Odense M, Denmark
| | - Arun Mahesh
- Institute for Molecular Medicine, University of Southern Denmark, Odense M, Denmark
| | - Arran K Turnbull
- Edinburgh Breast Cancer Now Research Group, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - J Michael Dixon
- Edinburgh Breast Cancer Now Research Group, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Rachael Natrajan
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Vijay K Tiwari
- Institute for Molecular Medicine, University of Southern Denmark, Odense M, Denmark.
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry & Biomedical Science, Queens University Belfast, Belfast, BT9 7BL, UK.
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, BT9 7AE, UK.
- Danish Institute for Advanced Study (DIAS), Odense M, Denmark.
- Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark.
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4
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Black GS, Huang X, Qiao Y, Moos P, Sampath D, Stephens DM, Woyach JA, Marth GT. Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotype and phenotype in chronic lymphocytic leukemia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585298. [PMID: 38559060 PMCID: PMC10979946 DOI: 10.1101/2024.03.15.585298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Bruton's tyrosine kinase (BTK) inhibitors are effective for the treatment of chronic lymphocytic leukemia (CLL) due to BTK's role in B cell survival and proliferation. Treatment resistance is most commonly caused by the emergence of the hallmark BTKC481S mutation that inhibits drug binding. In this study, we aimed to investigate whether the presence of additional CLL driver mutations in cancer subclones harboring a BTKC481S mutation accelerates subclone expansion. In addition, we sought to determine whether BTK-mutated subclones exhibit distinct transcriptomic behavior when compared to other cancer subclones. To achieve these goals, we employ our recently published method (Qiao et al. 2024) that combines bulk DNA sequencing and single-cell RNA sequencing (scRNA-seq) data to genotype individual cells for the presence or absence of subclone-defining mutations. While the most common approach for scRNA-seq includes short-read sequencing, transcript coverage is limited due to the vast majority of the reads being concentrated at the priming end of the transcript. Here, we utilized MAS-seq, a long-read scRNAseq technology, to substantially increase transcript coverage across the entire length of the transcripts and expand the set of informative mutations to link cells to cancer subclones in six CLL patients who acquired BTKC481S mutations during BTK inhibitor treatment. We found that BTK-mutated subclones often acquire additional mutations in CLL driver genes, leading to faster subclone proliferation. When examining subclone-specific gene expression, we found that in one patient, BTK-mutated subclones are transcriptionally distinct from the rest of the malignant B cell population with an overexpression of CLL-relevant genes.
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Affiliation(s)
- Gage S Black
- Department of Human Genetics, University of Utah, Salt Lake City, UT
| | - Xiaomeng Huang
- Department of Human Genetics, University of Utah, Salt Lake City, UT
| | - Yi Qiao
- Department of Human Genetics, University of Utah, Salt Lake City, UT
| | - Philip Moos
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT
| | - Deepa Sampath
- Department of Hematopoietic Biology and Malignancy, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | - Gabor T Marth
- Department of Human Genetics, University of Utah, Salt Lake City, UT
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Adkins-Threats M, Huang YZ, Mills JC. Highlights of how single-cell analyses are illuminating differentiation and disease in the gastric corpus. Am J Physiol Gastrointest Liver Physiol 2024; 326:G205-G215. [PMID: 38193187 PMCID: PMC11211037 DOI: 10.1152/ajpgi.00164.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/18/2023] [Accepted: 12/23/2023] [Indexed: 01/10/2024]
Abstract
Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique to identify novel cell markers, developmental trajectories, and transcriptional changes during cell differentiation and disease onset and progression. In this review, we highlight recent scRNA-seq studies of the gastric corpus in both human and murine systems that have provided insight into gastric organogenesis, identified novel markers for the various gastric lineages during development and in adults, and revealed transcriptional changes during regeneration and tumorigenesis. Overall, by elucidating transcriptional states and fluctuations at the cellular level in healthy and disease contexts, scRNA-seq may lead to better, more personalized clinical treatments for disease progression.
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Affiliation(s)
- Mahliyah Adkins-Threats
- Section of Gastroenterology, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
| | - Yang-Zhe Huang
- Section of Gastroenterology, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
- Graduate School of Biomedical Sciences, Cancer and Cell Biology Program, Baylor College of Medicine, Houston, Texas, United States
| | - Jason C Mills
- Section of Gastroenterology, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas, United States
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, United States
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6
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Wang Y, Armendariz D, Wang L, Zhao H, Xie S, Hon GC. Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.20.567880. [PMID: 38045327 PMCID: PMC10690208 DOI: 10.1101/2023.11.20.567880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.
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Affiliation(s)
- Yihan Wang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences
| | | | - Lei Wang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences
| | - Huan Zhao
- Cecil H. and Ida Green Center for Reproductive Biology Sciences
| | - Shiqi Xie
- Cecil H. and Ida Green Center for Reproductive Biology Sciences
- Current address: Genentech, 1 DNA Way, South San Francisco, CA 94080, USA
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences
- Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology, Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390
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Pu T, Peddle A, Zhu J, Tejpar S, Verbandt S. Neoantigen identification: Technological advances and challenges. Methods Cell Biol 2023; 183:265-302. [PMID: 38548414 DOI: 10.1016/bs.mcb.2023.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.
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Affiliation(s)
- Ting Pu
- Digestive Oncology Unit, KULeuven, Leuven, Belgium
| | | | - Jingjing Zhu
- de Duve Institute, Université catholique de Louvain, Brussels, Belgium
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8
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Glass MR, Waxman EA, Yamashita S, Lafferty M, Beltran A, Farah T, Patel NK, Matoba N, Ahmed S, Srivastava M, Drake E, Davis LT, Yeturi M, Sun K, Love MI, Hashimoto-Torii K, French DL, Stein JL. Cross-site reproducibility of human cortical organoids reveals consistent cell type composition and architecture. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.28.550873. [PMID: 37546772 PMCID: PMC10402155 DOI: 10.1101/2023.07.28.550873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Background Reproducibility of human cortical organoid (hCO) phenotypes remains a concern for modeling neurodevelopmental disorders. While guided hCO protocols reproducibly generate cortical cell types in multiple cell lines at one site, variability across sites using a harmonized protocol has not yet been evaluated. We present an hCO cross-site reproducibility study examining multiple phenotypes. Methods Three independent research groups generated hCOs from one induced pluripotent stem cell (iPSC) line using a harmonized miniaturized spinning bioreactor protocol. scRNA-seq, 3D fluorescent imaging, phase contrast imaging, qPCR, and flow cytometry were used to characterize the 3 month differentiations across sites. Results In all sites, hCOs were mostly cortical progenitor and neuronal cell types in reproducible proportions with moderate to high fidelity to the in vivo brain that were consistently organized in cortical wall-like buds. Cross-site differences were detected in hCO size and morphology. Differential gene expression showed differences in metabolism and cellular stress across sites. Although iPSC culture conditions were consistent and iPSCs remained undifferentiated, primed stem cell marker expression prior to differentiation correlated with cell type proportions in hCOs. Conclusions We identified hCO phenotypes that are reproducible across sites using a harmonized differentiation protocol. Previously described limitations of hCO models were also reproduced including off-target differentiations, necrotic cores, and cellular stress. Improving our understanding of how stem cell states influence early hCO cell types may increase reliability of hCO differentiations. Cross-site reproducibility of hCO cell type proportions and organization lays the foundation for future collaborative prospective meta-analytic studies modeling neurodevelopmental disorders in hCOs.
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Affiliation(s)
- Madison R Glass
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Elisa A Waxman
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Satoshi Yamashita
- Center for Neuroscience Research, Children's National Hospital, Washington, DC
| | - Michael Lafferty
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alvaro Beltran
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tala Farah
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Niyanta K Patel
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Nana Matoba
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Sara Ahmed
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Mary Srivastava
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Emma Drake
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Liam T Davis
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Meghana Yeturi
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Kexin Sun
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Departments of Pediatrics, and Pharmacology & Physiology, School of Medicine and Health Sciences, The George Washington University, Washington, DC
| | - Kazue Hashimoto-Torii
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Deborah L French
- Center for Cellular and Molecular Therapeutics, The Children's Hospital of Philadelphia, Philadelphia, PA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Jason L Stein
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Armendariz DA, Sundarrajan A, Hon GC. Breaking enhancers to gain insights into developmental defects. eLife 2023; 12:e88187. [PMID: 37497775 PMCID: PMC10374278 DOI: 10.7554/elife.88187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.
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Affiliation(s)
- Daniel A Armendariz
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Anjana Sundarrajan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, United States
- Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States
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Gao CF, Vaikuntanathan S, Riesenfeld SJ. Dissection and Integration of Bursty Transcriptional Dynamics for Complex Systems. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.13.544828. [PMID: 37398022 PMCID: PMC10312759 DOI: 10.1101/2023.06.13.544828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
RNA velocity estimation is a potentially powerful tool to reveal the directionality of transcriptional changes in single-cell RNA-seq data, but it lacks accuracy, absent advanced metabolic labeling techniques. We developed a novel approach, TopicVelo, that disentangles simultaneous, yet distinct, dynamics by using a probabilistic topic model, a highly interpretable form of latent space factorization, to infer cells and genes associated with individual processes, thereby capturing cellular pluripotency or multifaceted functionality. Focusing on process-associated cells and genes enables accurate estimation of process-specific velocities via a master equation for a transcriptional burst model accounting for intrinsic stochasticity. The method obtains a global transition matrix by leveraging cell topic weights to integrate process-specific signals. In challenging systems, this method accurately recovers complex transitions and terminal states, while our novel use of first-passage time analysis provides insights into transient transitions. These results expand the limits of RNA velocity, empowering future studies of cell fate and functional responses.
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Affiliation(s)
| | | | - Samantha J Riesenfeld
- Institute for Biophysical Dynamics, University of Chicago, IL
- Pritzker School of Molecular Engineering, University of Chicago, IL
- Department of Medicine, University of Chicago, IL
- Committee on Immunology, University of Chicago, IL
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11
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You Y, Prawer YDJ, De Paoli-Iseppi R, Hunt CPJ, Parish CL, Shim H, Clark MB. Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE. Genome Biol 2023; 24:66. [PMID: 37024980 PMCID: PMC10077662 DOI: 10.1186/s13059-023-02907-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE .
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Affiliation(s)
- Yupei You
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Yair D J Prawer
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Ricardo De Paoli-Iseppi
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Cameron P J Hunt
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Clare L Parish
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Heejung Shim
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Michael B Clark
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia.
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12
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Xu D, Tang L, Kapranov P. Complexities of mammalian transcriptome revealed by targeted RNA enrichment techniques. Trends Genet 2023; 39:320-333. [PMID: 36681580 DOI: 10.1016/j.tig.2022.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 12/27/2022] [Accepted: 12/30/2022] [Indexed: 01/21/2023]
Abstract
Studies using highly sensitive targeted RNA enrichment methods have shown that a large portion of the human transcriptome remains to be discovered and that most of the genome is transcribed in a complex, interleaved fashion characterized by a complex web of transcripts emanating from protein coding and noncoding loci. These results resonate with those from single-cell transcriptome profiling endeavors that reveal the existence of multiple novel, cell type-specific transcripts and clearly demonstrate that our understanding of the complexities of the human transcriptome is far from being complete. Here, we review the current status of the targeted RNA enrichment techniques, their application to the discovery of novel cell type-specific transcripts, and their impact on our understanding of the human genome and transcriptome.
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Affiliation(s)
- Dongyang Xu
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen 361021, China
| | - Lu Tang
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen 361021, China
| | - Philipp Kapranov
- Institute of Genomics, School of Medicine, Huaqiao University, 668 Jimei Road, Xiamen 361021, China.
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Peng X, Dorman KS. Accurate estimation of molecular counts from amplicon sequence data with unique molecular identifiers. Bioinformatics 2023; 39:6971842. [PMID: 36610988 PMCID: PMC9891248 DOI: 10.1093/bioinformatics/btad002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 11/16/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023] Open
Abstract
MOTIVATION Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during polymerase chain reaction (PCR) and sequencing. One solution attaches unique molecular identifiers (UMIs) to sample sequences before amplification. Counting UMIs instead of sequences provides unbiased estimates of abundance. While modern methods improve over naïve counting by UMI identity, most do not account for UMI reuse or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences. RESULTS We introduce Deduplication and Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological amplicon sequences and accurately estimate their deduplicated abundance. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods. AVAILABILITY AND IMPLEMENTATION Source code is available at https://github.com/DormanLab/AmpliCI. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xiyu Peng
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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Lan T, Hutvagner G, Zhang X, Liu T, Wong L, Li J. Density-based detection of cell transition states to construct disparate and bifurcating trajectories. Nucleic Acids Res 2022; 50:e122. [PMID: 36124665 PMCID: PMC9757071 DOI: 10.1093/nar/gkac785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/22/2022] [Accepted: 09/01/2022] [Indexed: 12/24/2022] Open
Abstract
Tree- and linear-shaped cell differentiation trajectories have been widely observed in developmental biologies and can be also inferred through computational methods from single-cell RNA-sequencing datasets. However, trajectories with complicated topologies such as loops, disparate lineages and bifurcating hierarchy remain difficult to infer accurately. Here, we introduce a density-based trajectory inference method capable of constructing diverse shapes of topological patterns including the most intriguing bifurcations. The novelty of our method is a step to exploit overlapping probability distributions to identify transition states of cells for determining connectability between cell clusters, and another step to infer a stable trajectory through a base-topology guided iterative fitting. Our method precisely re-constructed various benchmark reference trajectories. As a case study to demonstrate practical usefulness, our method was tested on single-cell RNA sequencing profiles of blood cells of SARS-CoV-2-infected patients. We not only re-discovered the linear trajectory bridging the transition from IgM plasmablast cells to developing neutrophils, and also found a previously-undiscovered lineage which can be rigorously supported by differentially expressed gene analysis.
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Affiliation(s)
- Tian Lan
- Data Science Institute and School of Computer Science, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Gyorgy Hutvagner
- School of Biomedical Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Xuan Zhang
- Data Science Institute and School of Computer Science, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Tao Liu
- Children’s Cancer Institute Australia for Medical Research, Randwick, NSW 2031, Australia
| | - Limsoon Wong
- School of Computing, National University of Singapore, 13 Computing Drive, 117417, Singapore
| | - Jinyan Li
- To whom correspondence should be addressed. Tel: +61 295149264; Fax: +61 295149264;
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15
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Lavorgna G, Tascini AS, Bertini A, Lanzaro F, Montorsi F, Alfano M, Salonia A. Single-cell transcriptome profiling reveals several LncRNAs differentially expressed in idiopathic germ cell aplasia. Front Cell Dev Biol 2022; 10:952518. [PMID: 36147743 PMCID: PMC9486010 DOI: 10.3389/fcell.2022.952518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/28/2022] [Indexed: 12/02/2022] Open
Abstract
Mechanisms underlying severe male infertility are still largely elusive. However, recently, a single-cell transcription study by our group identified several differentially expressed coding genes in all the somatic cell types in testes of patients with idiopathic germ cell aplasia (iGCA). Here, we leverage this work by extending the analysis also to the non-coding portion of the genome. As a result, we found that 43 LncRNAs were differentially expressed in the somatic cells of these patients. Interestingly, a significant portion of the overexpressed LncRNAs was found to be a target of TAF9B, a transcription factor known to be involved in germ cell survival. Moreover, several overexpressed LncRNAs were also found to be activated in a mouse model of Sertoli cells treated with bisphenol A, a widespread environmental contaminant, long suspected to impair male fertility. Finally, a literature search for MEG3, a maternally imprinted LncRNA overexpressed as well in our patients, found it to be involved, among other things, in obesity and inflammation, known comorbidities of iGCA, ultimately suggesting that our findings deepen the understanding of the molecular insights coupled not only to the pathogenesis, but also to the clinical course of this class of patients.
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Affiliation(s)
- Giovanni Lavorgna
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Giovanni Lavorgna, ; Massimo Alfano,
| | | | - Alessandro Bertini
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- University Vita-Salute San Raffaele, Milan, Italy
| | - Francesco Lanzaro
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- University Vita-Salute San Raffaele, Milan, Italy
| | - Francesco Montorsi
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- University Vita-Salute San Raffaele, Milan, Italy
| | - Massimo Alfano
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Giovanni Lavorgna, ; Massimo Alfano,
| | - Andrea Salonia
- Division of Experimental Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy
- University Vita-Salute San Raffaele, Milan, Italy
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Marin P, Jaquet A, Picarle J, Fablet M, Merel V, Delignette-Muller ML, Ferrarini MG, Gibert P, Vieira C. Phenotypic and Transcriptomic Responses to Stress Differ According to Population Geography in an Invasive Species. Genome Biol Evol 2021; 13:evab208. [PMID: 34505904 PMCID: PMC8483892 DOI: 10.1093/gbe/evab208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2021] [Indexed: 11/14/2022] Open
Abstract
Adaptation to rapid environmental changes must occur within a short-time scale. In this context, studies of invasive species may provide insights into the underlying mechanisms of rapid adaptation as these species have repeatedly encountered and adapted to novel environmental conditions. We investigated how invasive and noninvasive genotypes of Drosophila suzukii deal with oxidative stress at the phenotypic and molecular levels. We also studied the impact of transposable element (TE) insertions on the gene expression in response to stress. Our results show that flies from invasive areas (France and the United States) live longer in natural conditions than the ones from native Japanese areas. As expected, lifespan for all genotypes was significantly reduced following exposure to paraquat, but this reduction varied among genotypes (genotype-by-environment interaction) with invasive genotypes appearing more affected by exposure than noninvasive ones. A transcriptomic analysis of genotypes upon paraquat treatment detected many genes differentially expressed (DE). Although a small core set of genes were DE in all genotypes following paraquat exposure, much of the response of each genotype was unique. Moreover, we showed that TEs were not activated after oxidative stress and DE genes were significantly depleted of TEs. In conclusion, it is likely that transcriptomic changes are involved in the rapid adaptation to local environments. We provide new evidence that in the decade since the invasion from Asia, the sampled genotypes in Europe and the United States of D. suzukii diverged from the ones from the native area regarding their phenotypic and genomic response to oxidative stress.
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Affiliation(s)
- Pierre Marin
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Angelo Jaquet
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Justine Picarle
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Marie Fablet
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Vincent Merel
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Marie-Laure Delignette-Muller
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Mariana Galvão Ferrarini
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
- Université de Lyon, INSA-Lyon, INRAE, BF2I, UMR0203, Villeurbanne, France
| | - Patricia Gibert
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
| | - Cristina Vieira
- Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, Villeurbanne, France
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