scholarly journals Inference of Single-Cell Phylogenies from Lineage Tracing Data

2019 ◽  
Author(s):  
Matthew G. Jones ◽  
Alex Khodaverdian ◽  
Jeffrey J. Quinn ◽  
Michelle M. Chan ◽  
Jeffrey A. Hussmann ◽  
...  

AbstractThe pairing of CRISPR/Cas9-based gene editing with massively parallel single-cell readouts now enables large-scale lineage tracing. However, the rapid growth in complexity of data from these assays has outpaced our ability to accurately infer phylogenetic relationships. To address this, we provide three resources. First, we introduce Cassiopeia - a suite of scalable and theoretically grounded maximum parsimony approaches for tree reconstruction. Second, we provide a simulation framework for evaluating algorithms and exploring lineage tracer design principles. Finally, we generate the most complex experimental lineage tracing dataset to date - consisting of 34,557 human cells continuously traced over 15 generations, 71% of which are uniquely marked - and use it for benchmarking phylogenetic inference approaches. We show that Cassiopeia outperforms traditional methods by several metrics and under a wide variety of parameter regimes, and provide insight into the principles for the design of improved Cas9-enabled recorders. Together these should broadly enable large-scale mammalian lineage tracing efforts. Cassiopeia and its benchmarking resources are publicly available at www.github.com/YosefLab/Cassiopeia.

2016 ◽  
Author(s):  
Jan Philipp Junker ◽  
Bastiaan Spanjaard ◽  
Josi Peterson-Maduro ◽  
Anna Alemany ◽  
Bo Hu ◽  
...  

A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism consisting of many cells. Although impressive progress has been made in lineage tracing using imaging approaches, analysis of vertebrate lineage trees has mostly been limited to relatively small subsets of cells. Here we present scartrace, a strategy for massively parallel clonal analysis based on Cas9 induced genetic scars in the zebrafish.


Cell Research ◽  
2021 ◽  
Author(s):  
Xiaofei Wang ◽  
Ran Zhou ◽  
Yanzhen Xiong ◽  
Lingling Zhou ◽  
Xiang Yan ◽  
...  

AbstractGlioblastoma (GBM) is an incurable and highly heterogeneous brain tumor, originating from human neural stem/progenitor cells (hNSCs/hNPCs) years ahead of diagnosis. Despite extensive efforts to characterize hNSCs and end-stage GBM at bulk and single-cell levels, the de novo gliomagenic path from hNSCs is largely unknown due to technical difficulties in early-stage sampling and preclinical modeling. Here, we established two highly penetrant hNSC-derived malignant glioma models, which resemble the histopathology and transcriptional heterogeneity of human GBM. Integrating time-series analyses of whole-exome sequencing, bulk and single-cell RNA-seq, we reconstructed gliomagenic trajectories, and identified a persistent NSC-like population at all stages of tumorigenesis. Through trajectory analyses and lineage tracing, we showed that tumor progression is primarily driven by multi-step transcriptional reprogramming and fate-switches in the NSC-like cells, which sequentially generate malignant heterogeneity and induce tumor phenotype transitions. We further uncovered stage-specific oncogenic cascades, and among the candidate genes we functionally validated C1QL1 as a new glioma-promoting factor. Importantly, the neurogenic-to-gliogenic switch in NSC-like cells marks an early stage characterized by a burst of oncogenic alterations, during which transient AP-1 inhibition is sufficient to inhibit gliomagenesis. Together, our results reveal previously undercharacterized molecular dynamics and fate choices driving de novo gliomagenesis from hNSCs, and provide a blueprint for potential early-stage treatment/diagnosis for GBM.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanping Long ◽  
Zhijian Liu ◽  
Jinbu Jia ◽  
Weipeng Mo ◽  
Liang Fang ◽  
...  

AbstractThe broad application of single-cell RNA profiling in plants has been hindered by the prerequisite of protoplasting that requires digesting the cell walls from different types of plant tissues. Here, we present a protoplasting-free approach, flsnRNA-seq, for large-scale full-length RNA profiling at a single-nucleus level in plants using isolated nuclei. Combined with 10x Genomics and Nanopore long-read sequencing, we validate the robustness of this approach in Arabidopsis root cells and the developing endosperm. Sequencing results demonstrate that it allows for uncovering alternative splicing and polyadenylation-related RNA isoform information at the single-cell level, which facilitates characterizing cell identities.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Peiran Zhang ◽  
Joseph Rufo ◽  
Chuyi Chen ◽  
Jianping Xia ◽  
Zhenhua Tian ◽  
...  

AbstractThe ability to precisely manipulate nano-objects on a large scale can enable the fabrication of materials and devices with tunable optical, electromagnetic, and mechanical properties. However, the dynamic, parallel manipulation of nanoscale colloids and materials remains a significant challenge. Here, we demonstrate acoustoelectronic nanotweezers, which combine the precision and robustness afforded by electronic tweezers with versatility and large-field dynamic control granted by acoustic tweezing techniques, to enable the massively parallel manipulation of sub-100 nm objects with excellent versatility and controllability. Using this approach, we demonstrated the complex patterning of various nanoparticles (e.g., DNAs, exosomes, ~3 nm graphene flakes, ~6 nm quantum dots, ~3.5 nm proteins, and ~1.4 nm dextran), fabricated macroscopic materials with nano-textures, and performed high-resolution, single nanoparticle manipulation. Various nanomanipulation functions, including transportation, concentration, orientation, pattern-overlaying, and sorting, have also been achieved using a simple device configuration. Altogether, acoustoelectronic nanotweezers overcome existing limitations in nano-manipulation and hold great potential for a variety of applications in the fields of electronics, optics, condensed matter physics, metamaterials, and biomedicine.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vidya C. Sinha ◽  
Amanda L. Rinkenbaugh ◽  
Mingchu Xu ◽  
Xinhui Zhou ◽  
Xiaomei Zhang ◽  
...  

AbstractThere is an unmet clinical need for stratification of breast lesions as indolent or aggressive to tailor treatment. Here, single-cell transcriptomics and multiparametric imaging applied to a mouse model of breast cancer reveals that the aggressive tumor niche is characterized by an expanded basal-like population, specialization of tumor subpopulations, and mixed-lineage tumor cells potentially serving as a transition state between luminal and basal phenotypes. Despite vast tumor cell-intrinsic differences, aggressive and indolent tumor cells are functionally indistinguishable once isolated from their local niche, suggesting a role for non-tumor collaborators in determining aggressiveness. Aggressive lesions harbor fewer total but more suppressed-like T cells, and elevated tumor-promoting neutrophils and IL-17 signaling, disruption of which increase tumor latency and reduce the number of aggressive lesions. Our study provides insight into tumor-immune features distinguishing indolent from aggressive lesions, identifies heterogeneous populations comprising these lesions, and supports a role for IL-17 signaling in aggressive progression.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fang Wang ◽  
Qihan Wang ◽  
Vakul Mohanty ◽  
Shaoheng Liang ◽  
Jinzhuang Dou ◽  
...  

AbstractWe present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Menglong Chen ◽  
Hui Shi ◽  
Shixue Gou ◽  
Xiaomin Wang ◽  
Lei Li ◽  
...  

Abstract Background Mutations in the DMD gene encoding dystrophin—a critical structural element in muscle cells—cause Duchenne muscular dystrophy (DMD), which is the most common fatal genetic disease. Clustered regularly interspaced short palindromic repeat (CRISPR)-mediated gene editing is a promising strategy for permanently curing DMD. Methods In this study, we developed a novel strategy for reframing DMD mutations via CRISPR-mediated large-scale excision of exons 46–54. We compared this approach with other DMD rescue strategies by using DMD patient-derived primary muscle-derived stem cells (DMD-MDSCs). Furthermore, a patient-derived xenograft (PDX) DMD mouse model was established by transplanting DMD-MDSCs into immunodeficient mice. CRISPR gene editing components were intramuscularly delivered into the mouse model by adeno-associated virus vectors. Results Results demonstrated that the large-scale excision of mutant DMD exons showed high efficiency in restoring dystrophin protein expression. We also confirmed that CRISPR from Prevotella and Francisella 1(Cas12a)-mediated genome editing could correct DMD mutation with the same efficiency as CRISPR-associated protein 9 (Cas9). In addition, more than 10% human DMD muscle fibers expressed dystrophin in the PDX DMD mouse model after treated by the large-scale excision strategies. The restored dystrophin in vivo was functional as demonstrated by the expression of the dystrophin glycoprotein complex member β-dystroglycan. Conclusions We demonstrated that the clinically relevant CRISPR/Cas9 could restore dystrophin in human muscle cells in vivo in the PDX DMD mouse model. This study demonstrated an approach for the application of gene therapy to other genetic diseases.


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