Methods for analysing lineage tracing datasets.
Ontology highlight
ABSTRACT:
SUBMITTER: Kostiou V
PROVIDER: S-EPMC8097194 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The kidney is a complex organ with over 30 different cell types, and understanding the lineage relationships between these cells is challenging. During nephrogenesis, a central question is how the coordinated morphogenesis, growth, and differentiation of distinct cell types leads to development of a functional organ. In mature kidney, understanding cell division and fate during injury, regeneration and aging are critical topics for understanding disease. Genetic lineage tracing offers a powerful tool to decipher cellular hierarchies in both development and disease because it allows the progeny of a single cell, or group of cells, to be tracked unambiguously. Recent advances in this field include the use of inducible recombinases, multicolor reporters, and mosaic analysis. In this review, we discuss lineage-tracing methods focusing on the mouse model system and consider the impact of these methods on our understanding of kidney biology and prospects for future application.
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Project description:Defining the pathways through which tumors progress is critical to our understanding and treatment of cancer. We do not routinely sample patients at multiple time points during the progression of their disease, and thus our research is limited to inferring progression a posteriori from the examination of a single tumor sample. Despite this limitation, inferring progression is possible because the tumor genome contains a natural history of the mutations that occur during the formation of the tumor mass. There are two approaches to reconstructing a lineage of progression: (1) inter-tumor comparisons, and (2) intra-tumor comparisons. The inter-tumor approach consists of taking single samples from large collections of tumors and comparing the complexity of the genomes to identify early and late mutations. The intra-tumor approach involves taking multiple samples from individual heterogeneous tumors to compare divergent clones and reconstruct a phylogenetic lineage. Here we discuss how these approaches can be used to interpret the current models for tumor progression. We also compare data from primary and metastatic copy number profiles to shed light on the final steps of breast cancer progression. Finally, we discuss how recent technical advances in single cell genomics will herald a new era in understanding the fundamental basis of tumor heterogeneity and progression.
| S-EPMC2904844 | biostudies-other
Project description:MotivationThe datasets generated by DNA methylation analyses are getting bigger. With the release of the HumanMethylationEPIC micro-array and datasets containing thousands of samples, analyses of these large datasets using R are becoming impractical due to large memory requirements. As a result there is an increasing need for computationally efficient methodologies to perform meaningful analysis on high dimensional data.ResultsHere we introduce the bigmelon R package, which provides a memory efficient workflow that enables users to perform the complex, large scale analyses required in epigenome wide association studies (EWAS) without the need for large RAM. Building on top of the CoreArray Genomic Data Structure file format and libraries packaged in the gdsfmt package, we provide a practical workflow that facilitates the reading-in, preprocessing, quality control and statistical analysis of DNA methylation data.We demonstrate the capabilities of the bigmelon package using a large dataset consisting of 1193 human blood samples from the Understanding Society: UK Household Longitudinal Study, assayed on the EPIC micro-array platform.Availability and implementationThe bigmelon package is available on Bioconductor (http://bioconductor.org/packages/bigmelon/). The Understanding Society dataset is available at https://www.understandingsociety.ac.uk/about/health/data upon request.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:AimsCultured cardiac explants produce a heterogeneous population of cells including a distinctive population of refractile cells described here as small round cardiac explant derived cells (EDCs). The aim of this study was to explore the source, morphology and cardiogenic potential of EDCs.MethodsTransgenic MLC2v-Cre/ZEG, and actin-eGFP mice were used for lineage-tracing of EDCs in vitro and in vivo. C57B16 mice were used as cell transplant recipients of EDCs from transgenic hearts, as well as for the general characterisation of EDCs. The activation of cardiac-specific markers were analysed by: immunohistochemistry with bright field and immunofluorescent microscopy, electron microscopy, PCR and RT-PCR. Functional engraftment of transplanted cells was further investigated with calcium transient studies.ResultsProduction of EDCs was highly dependent on the retention of blood-derived cells or factors in the cultured explants. These cells shared some characteristics of cardiac myocytes in vitro and survived engraftment in the adult heart in vivo. However, EDCs failed to differentiate into functional cardiac myocytes in vivo as demonstrated by the absence of stimulation-evoked intracellular calcium transients following transplantation into the peri-infarct zone.ConclusionsThis study highlights that positive identification based upon one parameter alone such as morphology or immunofluorescene is not adequate to identify the source, fate and function of adult cardiac explant derived cells.
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Project description:The invariant cell lineage and cell fate of Caenorhabditis elegans provide a unique opportunity to decode the molecular mechanisms of animal development. To exploit this opportunity, we have developed a system for automated cell lineage tracing during C. elegans embryogenesis, based on 3D, time-lapse imaging and automated image analysis. Using ubiquitously expressed histone-GFP fusion protein to label cells/nuclei and a confocal microscope, the imaging protocol captures embryogenesis at high spatial (31 planes at 1 microm apart) and temporal (every minute) resolution without apparent effects on development. A set of image analysis algorithms then automatically recognizes cells at each time point, tracks cell movements, divisions and deaths over time and assigns cell identities based on the canonical naming scheme. Starting from the four-cell stage (or earlier), our software, named starrynite, can trace the lineage up to the 350-cell stage in 25 min on a desktop computer. The few errors of automated lineaging can then be corrected in a few hours with a graphic interface that allows easy navigation of the images and the reported lineage tree. The system can be used to characterize lineage phenotypes of genes and/or extended to determine gene expression patterns in a living embryo at the single-cell level. We envision that this automation will make it practical to systematically decipher the developmental genes and pathways encoded in the genome of C. elegans.
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Project description:The interplay of different cell types of origin and distinct oncogenic mutations may determine the tumor subtype. We have recently found that although both basal and luminal epithelial cells can initiate prostate tumorigenesis, the latter are more likely to undergo transformation in response to a range of oncogenic events.
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Project description:Leukocyte-like cells called hemocytes have key functions in Drosophila innate immunity. Three hemocyte types occur: plasmatocytes, crystal cells, and lamellocytes. In the absence of qimmune challenge, plasmatocytes are the predominant hemocyte type detected, while crystal cells and lamellocytes are rare. However, upon infestation by parasitic wasps, or in melanotic mutant strains, large numbers of lamellocytes differentiate and encapsulate material recognized as "non-self". Current models speculate that lamellocytes, plasmatocytes and crystal cells are distinct lineages that arise from a common prohemocyte progenitor. We show here that over-expression of the CoREST-interacting transcription factor Chn in plasmatocytes induces lamellocyte differentiation, both in circulation and in lymph glands. Lamellocyte increases are accompanied by the extinction of plasmatocyte markers suggesting that plasmatocytes are transformed into lamellocytes. Consistent with this, timed induction of Chn over-expression induces rapid lamellocyte differentiation within 18 hours. We detect double-positive intermediates between plasmatocytes and lamellocytes, and show that isolated plasmatocytes can be triggered to differentiate into lamellocytes in vitro, either in response to Chn over-expression, or following activation of the JAK/STAT pathway. Finally, we have marked plasmatocytes and show by lineage tracing that these differentiate into lamellocytes in response to the Drosophila parasite model Leptopilina boulardi. Taken together, our data suggest that lamellocytes arise from plasmatocytes and that plasmatocytes may be inherently plastic, possessing the ability to differentiate further into lamellocytes upon appropriate challenge.
| S-EPMC2988793 | biostudies-literature
Project description:BackgroundDespite a major research focus on clinical reasoning over the last several decades, a method of evaluating the clinical reasoning process that is both objective and comprehensive is yet to be developed.The aim of this study was to test whether a dual approach, using two measures of clinical reasoning, the Clinical Reasoning Problem (CRP) and the Script Concordance Test (SCT), provides a valid, reliable and targeted analysis of clinical reasoning characteristics to facilitate the development of diagnostic thinking in medical students.MethodsThree groups of participants, general practitioners, and third and fourth (final) year medical students completed 20 on-line clinical scenarios -10 in CRP and 10 in SCT format. Scores for each format were analysed for reliability, correlation between the two formats and differences between subject-groups.ResultsCronbach's alpha coefficient ranged from 0.36 for SCT 1 to 0.61 for CRP 2, Statistically significant correlations were found between the mean f-score of the CRP 2 and total SCT 2 score (0.69); and between the mean f-score for all CRPs and all mean SCT scores (0.57 and 0.47 respectively). The pass/fail rates of the SCT and CRP f-score are in keeping with the findings from the correlation analysis (i.e. 31% of students (11/35) passed both, 26% failed both, and 43% (15/35) of students passed one but not the other test), and suggest that the two formats measure overlapping but not identical characteristics. One-way ANOVA showed consistent differences in scores between levels of expertise with these differences being significant or approaching significance for the CRPs.ConclusionSCTs and CRPs are overlapping and complementary measures of clinical reasoning. Whilst SCTs are more efficient to administer, the use of both measures provides a more comprehensive appraisal of clinical skills than either single measure alone, and as such could potentially facilitate the customised teaching of clinical reasoning for individuals. The modest reliability of SCTs and CRPs in this study suggests the need for an increased number of items for testing. Further work is needed to determine the suitability of a combined approach for assessment purposes.
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Project description:Using genetic fate-mapping with Cux2-Cre and Cux2-CreERT2 mice we demonstrated that the neocortical ventricular zone (VZ) contains radial glial cells (RGCs) with restricted fate potentials (Franco et al., 2012). Using the same mouse lines, Guo et al. (2013) concluded that the neocortical VZ does not contain lineage-restricted RGCs. We now show that the recombination pattern in Cux2-Cre/CreERT2 mice depends on genetic background and breeding strategies. We provide evidence that Guo et al. likely reached different conclusions because they worked with transgenic sublines with drifted transgene expression patterns. In Cux2-Cre and Cux2-CreERT2 mice that recapitulate the endogenous Cux2 expression pattern, the vast majority of fate-mapped neurons express Satb2 but not Ctip2, confirming that a restricted subset of all neocortical projection neurons belongs to the Cux2 lineage. This Matters Arising paper is in response to Guo et al. (2013), published in Neuron. See also the Matters Arising Response paper by Eckler et al. (2015), published concurrently with this Matters Arising in Neuron.
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Project description:Here, we devised a cloning-free 3' knock-in strategy for zebrafish using PCR amplified dsDNA donors that avoids disrupting the targeted genes. The dsDNA donors carry genetic cassettes coding for fluorescent proteins and Cre recombinase in frame with the endogenous gene but separated from it by self-cleavable peptides. Primers with 5' AmC6 end-protections generated PCR amplicons with increased integration efficiency that were coinjected with preassembled Cas9/gRNA ribonucleoprotein complexes for early integration. We targeted four genetic loci (krt92, nkx6.1, krt4, and id2a) and generated 10 knock-in lines, which function as reporters for the endogenous gene expression. The knocked-in iCre or CreERT2 lines were used for lineage tracing, which suggested that nkx6.1 + cells are multipotent pancreatic progenitors that gradually restrict to the bipotent duct, whereas id2a + cells are multipotent in both liver and pancreas and gradually restrict to ductal cells. In addition, the hepatic id2a + duct show progenitor properties upon extreme hepatocyte loss. Thus, we present an efficient and straightforward knock-in technique with widespread use for cellular labelling and lineage tracing.
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