A phylogenetic approach to mapping cell fate

Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development

Mutations are acquired frequently, such that each cell's genome inscribes its history of cell divisions. Common genomic alterations involve loss of heterozygosity (LOH). LOH accumulates throughout the genome, offering large encoding capacity for inferring cell lineage. Using only single-cell RNA sequencing (scRNA-seq) of mouse brain cells, we found that LOH events spanning multiple genes are revealed as tracts of monoallelically expressed, constitutionally heterozygous single-nucleotide variants (SNVs). We simultaneously inferred cell lineage and marked developmental time points based on X chromosome inactivation and the total number of LOH events while identifying cell types from gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. This type of retrospective analysis could be incorporated into scRNA-seq pipelines and, compared with experimental approaches for determining lineage in model organisms, is applicable where genetic engineering is prohibited, such as humans.

Applications of Single-Cell DNA Sequencing

Over the past decade, genomic analyses of single cells-the fundamental units of life-have become possible. Single-cell DNA sequencing has shed light on biological questions that were previously inaccessible across diverse fields of research, including somatic mutagenesis, organismal development, genome function, and microbiology. Single-cell DNA sequencing also promises significant future biomedical and clinical impact, spanning oncology, fertility, and beyond. While single-cell approaches that profile RNA and protein have greatly expanded our understanding of cellular diversity, many fundamental questions in biology and important biomedical applications require analysis of the DNA of single cells. Here, we review the applications and biological questions for which single-cell DNA sequencing is uniquely suited or required. We include a discussion of the fields that will be impacted by single-cell DNA sequencing as the technology continues to advance.

High-throughput dense reconstruction of cell lineages

The first meeting exclusively dedicated to the 'High-throughput dense reconstruction of cell lineages' took place at Janelia Research Campus (Howard Hughes Medical Institute) from 14 to 18 April 2019. Organized by Tzumin Lee, Connie Cepko, Jorge Garcia-Marques and Isabel Espinosa-Medina, this meeting echoed the recent eruption of new tools that allow the reconstruction of lineages based on the phylogenetic analysis of DNA mutations induced during development. Combined with single-cell RNA sequencing, these tools promise to solve the lineage of complex model organisms at single-cell resolution. Here, we compile the conference consensus on the technological and computational challenges emerging from the use of the new strategies, as well as potential solutions.

Lineage analysis by microsatellite loci deep sequencing in mice

Lineage analysis is the identification of all the progeny of a single progenitor cell, and has become particularly useful for studying developmental processes and cancer biology. Here, we propose a novel and effective method for lineage analysis that combines sequence capture and next-generation sequencing technology. Genome-wide mononucleotide and dinucleotide microsatellite loci in eight samples from two mice were identified and used to construct phylogenetic trees based on somatic indel mutations at these loci, which were unique enough to distinguish and parse samples from different mice into different groups along the lineage tree. For example, biopsies from the liver and stomach, which originate from the endoderm, were located in the same clade, while samples in kidney, which originate from the mesoderm, were located in another clade. Yet, tissue with a common developmental origin may still contain cells of a mixed ancestry. This genome-wide approach thus provides a non-invasive lineage analysis method based on mutations that accumulate in the genomes of opaque multicellular organism somatic cells. Mol. Reprod. Dev. 83: 387-391, 2016. © 2016 Wiley Periodicals, Inc.

Insect phylogenomics

Phylogenomics, the integration of phylogenetics with genome data, has emerged as a powerful approach to study the evolution and systematics of species. Recently, several studies employing phylogenomic tools have provided better insights into insect evolution. Next-generation sequencing methods are now increasingly used by entomologists to generate genomic and transcript sequences of various insect species and strains. These data provide opportunities for comparative genomics and large-scale multigene phylogenies of diverse lineages of insects. Phy-logenomic investigations help us to better understand systematic and evolutionary relationships of insect species that play important roles as herbivores, predators, detritivores, pollinators and disease vectors. It is important that we critically assess the prospects and limitations of phylogenomic methods. In this review, I describe the current status, outline the major challenges and remark on potential future applications of phylogenomic tools in studying insect systematics and evolution.

Stochasticity and stereotypy in the Ciona notochord

Fate mapping with single cell resolution has typically been confined to embryos with completely stereotyped development. The lineages giving rise to the 40 cells of the Ciona notochord are invariant, but the intercalation of those cells into a single-file column is not. Here we use genetic labeling methods to fate map the Ciona notochord with both high resolution and large sample sizes. We find that the ordering of notochord cells into a single column is not random, but instead shows a distinctive signature characteristic of mediolaterally-biased intercalation. We find that patterns of cell intercalation in the notochord are somewhat stochastic but far more stereotyped than previously believed. Cell behaviors vary by lineage, with the secondary notochord lineage being much more constrained than the primary lineage. Within the primary lineage, patterns of intercalation reflect the geometry of the intercalating tissue. We identify the latest point at which notochord morphogenesis is largely stereotyped, which is shortly before the onset of mediolateral intercalation and immediately after the final cell divisions in the primary lineage. These divisions are consistently oriented along the AP axis. Our results indicate that the interplay between stereotyped and stochastic cell behaviors in morphogenesis can only be assessed by fate mapping experiments that have both cellular resolution and large sample sizes.

Genome sequencing of normal cells reveals developmental lineages and mutational processes

The somatic mutations present in the genome of a cell accumulate over the lifetime of a multicellular organism. These mutations can provide insights into the developmental lineage tree, the number of divisions that each cell has undergone and the mutational processes that have been operative. Here we describe whole genomes of clonal lines derived from multiple tissues of healthy mice. Using somatic base substitutions, we reconstructed the early cell divisions of each animal, demonstrating the contributions of embryonic cells to adult tissues. Differences were observed between tissues in the numbers and types of mutations accumulated by each cell, which likely reflect differences in the number of cell divisions they have undergone and varying contributions of different mutational processes. If somatic mutation rates are similar to those in mice, the results indicate that precise insights into development and mutagenesis of normal human cells will be possible.

Comparing algorithms that reconstruct cell lineage trees utilizing information on microsatellite mutations

Organism cells proliferate and die to build, maintain, renew and repair it. The cellular history of an organism up to any point in time can be captured by a cell lineage tree in which vertices represent all organism cells, past and present, and directed edges represent progeny relations among them. The root represents the fertilized egg, and the leaves represent extant and dead cells. Somatic mutations accumulated during cell division endow each organism cell with a genomic signature that is unique with a very high probability. Distances between such genomic signatures can be used to reconstruct an organism's cell lineage tree. Cell populations possess unique features that are absent or rare in organism populations (e.g., the presence of stem cells and a small number of generations since the zygote) and do not undergo sexual reproduction, hence the reconstruction of cell lineage trees calls for careful examination and adaptation of the standard tools of population genetics. Our lab developed a method for reconstructing cell lineage trees by examining only mutations in highly variable microsatellite loci (MS, also called short tandem repeats, STR). In this study we use experimental data on somatic mutations in MS of individual cells in human and mice in order to validate and quantify the utility of known lineage tree reconstruction algorithms in this context. We employed extensive measurements of somatic mutations in individual cells which were isolated from healthy and diseased tissues of mice and humans. The validation was done by analyzing the ability to infer known and clear biological scenarios. In general, we found that if the biological scenario is simple, almost all algorithms tested can infer it. Another somewhat surprising conclusion is that the best algorithm among those tested is Neighbor Joining where the distance measure used is normalized absolute distance. We include our full dataset in Tables S1, S2, S3, S4, S5 to enable further analysis of this data by others.

Use of somatic mutations to quantify random contributions to mouse development

Background

The C. elegans cell fate map, in which the lineage of its approximately 1000 cells is visibly charted beginning from the zygote, represents a developmental biology milestone. Nematode development is invariant from one specimen to the next, whereas in mammals, aspects of development are probabilistic, and development exhibits variation between even genetically identical individuals. Consequently, a single defined cell fate map applicable to all individuals cannot exist.

Results

To determine the extent to which patterns of cell lineage are conserved between different mice, we have employed the recently developed method of “phylogenetic fate mapping” to compare cell fate maps in siblings. In this approach, somatic mutations arising in individual cells are used to retrospectively deduce lineage relationships through phylogenetic and—as newly investigated here—related analytical approaches based on genetic distance. We have cataloged genomic mutations at an average of 110 mutation-prone polyguanine (polyG) tracts for about 100 cells clonally isolated from various corresponding tissues of each of two littermates of a hypermutable mouse strain.

Conclusions

We find that during mouse development, muscle and fat arise from a mixed progenitor cell pool in the germ layer, but, contrastingly, vascular endothelium in brain derives from a smaller source of progenitor cells. Additionally, formation of tissue primordia is marked by establishment of left and right lateral compartments, with restricted cell migration between divisions. We quantitatively demonstrate that development represents a combination of stochastic and deterministic events, offering insight into how chance influences normal development and may give rise to birth defects.

Cell lineage analysis of acute leukemia relapse uncovers the role of replication-rate heterogeneity and microsatellite instability

Human cancers display substantial intratumoral genetic heterogeneity, which facilitates tumor survival under changing microenvironmental conditions. Tumor substructure and its effect on disease progression and relapse are incompletely understood. In the present study, a high-throughput method that uses neutral somatic mutations accumulated in individual cells to reconstruct cell lineage trees was applied to hundreds of cells of human acute leukemia harvested from multiple patients at diagnosis and at relapse. The reconstructed cell lineage trees of patients with acute myeloid leukemia showed that leukemia cells at relapse were shallow (divide rarely) compared with cells at diagnosis and were closely related to their stem cell subpopulation, implying that in these instances relapse might have originated from rarely dividing stem cells. In contrast, among patients with acute lymphoid leukemia, no differences in cell depth were observed between diagnosis and relapse. In one case of chronic myeloid leukemia, at blast crisis, most of the cells at relapse were mismatch-repair deficient. In almost all leukemia cases, > 1 lineage was observed at relapse, indicating that diverse mechanisms can promote relapse in the same patient. In conclusion, diverse relapse mechanisms can be observed by systematic reconstruction of cell lineage trees of patients with leukemia.

Cell lineage analysis of the mammalian female germline

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote). We show that, in the reconstructed mouse cell lineage trees, oocytes form clusters that are separate from hematopoietic and mesenchymal stem cells, both in young and old mice, indicating that these populations belong to distinct lineages. Furthermore, while cumulus cells sampled from different ovarian follicles are distinctly clustered on the reconstructed trees, oocytes from the left and right ovaries are not, suggesting a mixing of their progenitor pools. We also observed an increase in oocyte depth with mouse age, which can be explained either by depth-guided selection of oocytes for ovulation or by post-natal renewal. Overall, our study sheds light on substantial novel aspects of female germline preservation and development.

Many aspects of mammalian female germline development during embryogenesis and throughout adulthood are either unknown or under debate. In this study we applied a novel method for the reconstruction of cell lineage trees utilizing microsatellite mutations, accumulated during mouse life, in oocytes and other cells, sampled from young and old mice. Analysis of the reconstructed cell lineage trees shows that oocytes are clustered separately from bone-marrow derived cells, that oocytes from different ovaries share common progenitors, and that oocyte depth (number of cell divisions since the zygote) increases significantly with mouse age.

Sparse and combinatorial neuron labelling

Sparse, random labelling of individual cells is a key approach to study brain circuit organisation and development. An array of methods based on genetic engineering now complements older methods such as Golgi staining, facilitating analysis while providing higher information content. Increasingly refined expression strategies based on transcriptional modulators and site-specific recombinases are used to distribute markers or combinations of markers within specific neuronal subsets. Several trends are emerging: first, increasing labelling density with multiplexed markers to allow more cells to be reliably distinguished; second, using labels to report lineage relationships among defined cells in addition to anatomy; third, coupling cell labelling with genetic manipulations that reveal or perturb cell function. These strategies offer new opportunities for characterizing the fine scale architecture of neuronal circuits, and understanding lineage and functional relations among their cellular components in normal or experimental situations.

Muscle-bound primordial stem cells give rise to myofiber-associated myogenic and non-myogenic progenitors

Myofiber cultures give rise to myogenic as well as to non-myogenic cells. Whether these myofiber-associated non-myogenic cells develop from resident stem cells that possess mesenchymal plasticity or from other stem cells such as mesenchymal stem cells (MSCs) remain unsolved. To address this question, we applied a method for reconstructing cell lineage trees from somatic mutations to MSCs and myogenic and non-myogenic cells from individual myofibers that were cultured at clonal density.

Our analyses show that (i) in addition to myogenic progenitors, myofibers also harbor non-myogenic progenitors of a distinct, yet close, lineage; (ii) myofiber-associated non-myogenic and myogenic cells share the same muscle-bound primordial stem cells of a lineage distinct from bone marrow MSCs; (iii) these muscle-bound primordial stem-cells first part to individual muscles and then differentiate into myogenic and non-myogenic stem cells.

Colon stem cell and crypt dynamics exposed by cell lineage reconstruction

Stem cell dynamics in vivo are often being studied by lineage tracing methods. Our laboratory has previously developed a retrospective method for reconstructing cell lineage trees from somatic mutations accumulated in microsatellites. This method was applied here to explore different aspects of stem cell dynamics in the mouse colon without the use of stem cell markers. We first demonstrated the reliability of our method for the study of stem cells by confirming previously established facts, and then we addressed open questions. Our findings confirmed that colon crypts are monoclonal and that, throughout adulthood, the process of monoclonal conversion plays a major role in the maintenance of crypts. The absence of immortal strand mechanism in crypts stem cells was validated by the age-dependent accumulation of microsatellite mutations. In addition, we confirmed the positive correlation between physical and lineage proximity of crypts, by showing that the colon is separated into small domains that share a common ancestor. We gained new data demonstrating that colon epithelium is clustered separately from hematopoietic and other cell types, indicating that the colon is constituted of few progenitors and ruling out significant renewal of colonic epithelium from hematopoietic cells during adulthood. Overall, our study demonstrates the reliability of cell lineage reconstruction for the study of stem cell dynamics, and it further addresses open questions in colon stem cells. In addition, this method can be applied to study stem cell dynamics in other systems.

The study of stem cell and tissue dynamics in vivo is often carried out by lineage tracing methods that depend on the presence of specific markers and on the availability of stem cells. In the current study, we applied a novel method for the reconstruction of cell lineage trees from microsatellite mutations accumulated during mouse life. We focused on the intestinal epithelium, since its stem cells were intensively studied by various tracing methods that clarified many aspects of their dynamics. We first showed the reliability of our method by confirming three previously established facts: the existence of “monoclonal conversion,” the absence of an immortal strand mechanism in colon stem cells, and the separation of the colon into small domains each with a common ancestor. We also answered a few open questions, showing that the colon's lineage is separated from other lineages such as the hematopoietic and pancreatic lineages. Overall, our work presents a new approach for the study of stem cell dynamics and can similarly be used for studying stem cell dynamics in other systems.

Next-generation sequencing in aging research: emerging applications, problems, pitfalls and possible solutions

Recent technological advances that allow faster and cheaper DNA sequencing are now driving biological and medical research. In this review, we provide an overview of state-of-the-art next-generation sequencing (NGS) platforms and their applications, including in genome sequencing and resequencing, transcriptional profiling (RNA-Seq) and high-throughput survey of DNA-protein interactions (ChIP-Seq) and of the epigenome. Particularly, we focus on how new methods made possible by NGS can help unravel the biological and genetic mechanisms of aging, longevity and age-related diseases. In the same way, however, NGS platforms open discovery not available before, they also give rise to new challenges, in particular in processing, analyzing and interpreting the data. Bioinformatics and software issues plus statistical difficulties in genome-wide studies are discussed, as well as the use of targeted sequencing to decrease costs and facilitate statistical analyses. Lastly, we discuss a number of methods to gather biological insights from massive amounts of data, such as functional enrichment, transcriptional regulation and network analyses. Although in the fast-moving field of NGS new platforms will soon take center stage, the approaches made possible by NGS will be at the basis of molecular biology, genetics and systems biology for years to come, making them instrumental for research on aging.

Phylogenetic analysis of developmental and postnatal mouse cell lineages

Fate maps depict how cells relate together through past lineage relationships, and are useful tools for studying developmental and somatic processes. However, with existing technologies, it has not been possible to generate detailed fate maps of complex organisms such as the mouse. We and others have therefore proposed a novel approach, "phylogenetic fate mapping," where patterns of somatic mutation carried by the individual cells of an animal are used to retrospectively deduce lineage relationships through phylogenetic inference. Here, we have cataloged genomic polymorphisms at 324 mutation-prone polyguanine tracts for nearly 300 cells isolated from a single mouse, and have explored the cells' lineage relationships both phylogenetically and through a network-based approach. We present a model of mouse embryogenesis, where an early period of substantial cell mixing is followed by more coherent growth of clones later. We find that cells from certain tissues have greater numbers of close relatives in other specific tissues than expected from chance, suggesting that those populations arise from a similar pool of ancestral lineages. Finally, we have investigated the dynamics of cell turnover (the frequency of cell loss and replacement) in postnatal tissues. This work offers a longitudinal study of developmental lineages, from conception to adulthood, and provides insight into basic questions of mouse embryology as well as the somatic processes that occur after birth.

Gene expression changes in normal haematopoietic cells

The complexity of the healthy haematopoietic system is immense, and as such, one must understand the biology driving normal haematopoietic expression profiles when designing experiments and interpreting expression data that involve normal cells. This article seeks to present an organised approach to the use and interpretation of gene profiling in normal haematopoiesis and broadly illustrates the challenges of selecting appropriate controls for high-throughput expression studies.

Human DNA polymerase eta is required for common fragile site stability during unperturbed DNA replication

Human DNA polymerase eta (Pol eta) modulates susceptibility to skin cancer by promoting translesion DNA synthesis (TLS) past sunlight-induced cyclobutane pyrimidine dimers. Despite its well-established role in TLS synthesis, the role of Pol eta in maintaining genome stability in the absence of external DNA damage has not been well explored. We show here that short hairpin RNA-mediated depletion of Pol eta from undamaged human cells affects cell cycle progression and the rate of cell proliferation and results in increased spontaneous chromosome breaks and common fragile site expression with the activation of ATM-mediated DNA damage checkpoint signaling. These phenotypes were also observed in association with modified replication factory dynamics during S phase. In contrast to that seen in Pol eta-depleted cells, none of these cellular or karyotypic defects were observed in cells depleted for Pol iota, the closest relative of Pol eta. Our results identify a new role for Pol eta in maintaining genomic stability during unperturbed S phase and challenge the idea that the sole functional role of Pol eta in human cells is in TLS DNA damage tolerance and/or repair pathways following exogenous DNA damage.

Cell lineage analysis of a mouse tumor

Revealing the lineage relations among cancer cells can shed light on tumor growth patterns and metastasis formation, yet cell lineages have been difficult to come by in the absence of a suitable method. We previously developed a method for reconstructing cell lineage trees from genomic variability caused by somatic mutations. Here, we apply the method to cancer and reconstruct, for the first time, a lineage tree of neoplastic and adjacent normal cells obtained by laser microdissection from tissue sections of a mouse lymphoma. Analysis of the reconstructed tree reveals that the tumor initiated from a single founder cell, approximately 5 months before diagnosis, that the tumor grew in a physically coherent manner, and that the average number of cell divisions accumulated in cancerous cells was almost twice than in adjacent normal lung epithelial cells but slightly less than the expected figure for normal B lymphocytes. The cells were also genotyped at the TP53 locus, and neoplastic cells were found to share a common mutation, which was most likely present in a heterozygous state. Our work shows that the ability to obtain data regarding the physical appearance, precise anatomic position, genotypic profile, and lineage position of single cells may be useful for investigating cancer development, progression, and interaction with the microenvironment.

Estimating cell depth from somatic mutations

The depth of a cell of a multicellular organism is the number of cell divisions it underwent since the zygote, and knowing this basic cell property would help address fundamental problems in several areas of biology. At present, the depths of the vast majority of human and mouse cell types are unknown. Here, we show a method for estimating the depth of a cell by analyzing somatic mutations in its microsatellites, and provide to our knowledge for the first time reliable depth estimates for several cells types in mice. According to our estimates, the average depth of oocytes is 29, consistent with previous estimates. The average depth of B cells ranges from 34 to 79, linearly related to the mouse age, suggesting a rate of one cell division per day. In contrast, various types of adult stem cells underwent on average fewer cell divisions, supporting the notion that adult stem cells are relatively quiescent. Our method for depth estimation opens a window for revealing tissue turnover rates in animals, including humans, which has important implications for our knowledge of the body under physiological and pathological conditions.

All the cells in our body are descendants of a single cell – the fertilized egg. Some cells are relatively close descendants, having undergone a small number of cell divisions, while other cells may be hundreds or even thousands of divisions deep. So far, science was unable to provide even gross estimates for the depths of the vast majority of human and mouse cells. In this study, we show that precise depth estimates of cells can be obtained from the analysis of non-hazardous mutations that spontaneously accumulate during normal development. The concept behind the method is simple: deeper cells tend to acquire more mutations and “drift away” from the original DNA sequence of the fertilized egg. Knowing how deep cells are is the key to many fundamental open questions in biology and medicine, such as whether neurons in our brain can regenerate, or whether new eggs are created in adult females.

Reconstruction of cell lineage trees in mice

The cell lineage tree of a multicellular organism represents its history of cell divisions from the very first cell, the zygote. A new method for high-resolution reconstruction of parts of such cell lineage trees was recently developed based on phylogenetic analysis of somatic mutations accumulated during normal development of an organism. In this study we apply this method in mice to reconstruct the lineage trees of distinct cell types. We address for the first time basic questions in developmental biology of higher organisms, namely what is the correlation between the lineage relation among cells and their (1) function, (2) physical proximity and (3) anatomical proximity. We analyzed B-cells, kidney-, mesenchymal- and hematopoietic-stem cells, as well as satellite cells, which are adult skeletal muscle stem cells isolated from their niche on the muscle fibers (myofibers) from various skeletal muscles. Our results demonstrate that all analyzed cell types are intermingled in the lineage tree, indicating that none of these cell types are single exclusive clones. We also show a significant correlation between the physical proximity of satellite cells within muscles and their lineage. Furthermore, we show that satellite cells obtained from a single myofiber are significantly clustered in the lineage tree, reflecting their common developmental origin. Lineage analysis based on somatic mutations enables performing high resolution reconstruction of lineage trees in mice and humans, which can provide fundamental insights to many aspects of their development and tissue maintenance.

Amplification of multiple genomic loci from single cells isolated by laser micro-dissection of tissues

BACKGROUND

Whole genome amplification (WGA) and laser assisted micro-dissection represent two recently developed technologies that can greatly advance biological and medical research. WGA allows the analysis of multiple genomic loci from a single genome and has been performed on single cells from cell suspensions and from enzymatically-digested tissues. Laser micro-dissection makes it possible to isolate specific single cells from heterogeneous tissues.

RESULTS

Here we applied for the first time WGA on laser micro-dissected single cells from stained tissue sections, and developed a protocol for sequentially performing the two procedures. The combined procedure allows correlating the cell's genome with its natural morphology and precise anatomical position. From each cell we amplified 122 genomic and mitochondrial loci. In cells obtained from fresh tissue sections, 64.5% of alleles successfully amplified to approximately 700000 copies each, and mitochondrial DNA was amplified successfully in all cells. Multiplex PCR amplification and analysis of cells from pre-stored sections yielded significantly poorer results. Sequencing and capillary electrophoresis of WGA products allowed detection of slippage mutations in microsatellites (MS), and point mutations in P53.

CONCLUSION

Comprehensive genomic analysis of single cells from stained tissue sections opens new research opportunities for cell lineage and depth analyses, genome-wide mutation surveys, and other single cell assays.

Phylogenetic fate mapping: theoretical and experimental studies applied to the development of mouse fibroblasts

Mutations are an inevitable consequence of cell division. Similarly to how DNA sequence differences allow inferring evolutionary relationships between organisms, we and others have recently demonstrated how somatic mutations may be exploited for phylogenetically reconstructing lineages of individual cells during development in multicellular organisms. However, a problem with such "phylogenetic fate maps" is that they cannot be verified experimentally; distinguishing actual lineages within clonal populations requires direct observation of cell growth, as was used to construct the fate map of Caenorhabditis elegans, but is not possible in higher organisms. Here we employ computer simulation of mitotic cell division to determine how factors such as the quantity of cells, mutation rate, and the number of examined marker sequences contribute to fidelity of phylogenetic fate maps and to explore statistical methods for assessing accuracy. To experimentally evaluate these factors, as well as for the purpose of investigating the developmental origins of connective tissue, we have produced a lineage map of fibroblasts harvested from various organs of an adult mouse. Statistical analysis demonstrates that the inferred relationships between cells in the phylogenetic fate map reflect biological information regarding the origin of fibroblasts and is suggestive of cell migration during mesenchymal development.