Search

Summary Short tandem repeats (STRs) are highly abundant in the human genome, but existing approaches for accurate genotyping of STRs are limited. Here, we describe a protocol for duplex molecular inversion probes for high-throughput and cost-effective STR enrichment. We have successfully tested panels targeting as many as 50K STRs in several thousands of genomic samples (e.g., HeLa cells, Du145 cells, leukemia cells, melanoma cells). However, because the protocol is plate based, the sample size is limited to a few thousand. For complete details on the use and execution of this protocol, please refer to Tao et al. (2021)., Graphical abstract, Highlights • This protocol enable us to enrich tens of thousands of STR from single-cell WGA • The protocol can easily deployed in any labs with generic equipment • The highly mutable STR panel is generic across human samples • The panels are highly customizable to include SNV targets like cancer hotspots and flexible from dozens of targets to over 50K targets; probes for different panels can be combined in one reaction, Short tandem repeats (STRs) are highly abundant in the human genome, but existing approaches for accurate genotyping of STRs are limited. Here, we describe a protocol for duplex molecular inversion probes for high-throughput and cost-effective STR enrichment. We have successfully tested panels targeting as many as 50K STRs in several thousands of genomic samples (e.g., HeLa cells, Du145 cells, leukemia cells, melanoma cells). However, because the protocol is plate based, the sample size is limited to a few thousand.

Advances in biochemical technologies have led to a boost in the field of single cell genomics. Observation of the genome at a single cell resolution is currently achieved by pre-amplification using whole genome amplification (WGA) techniques that differ by their biochemical aspects and as a result by biased amplification of the original molecule. Several comparisons between commercially available single cell dedicated WGA kits (scWGA) were performed, however, these comparisons are costly, were only performed on selected scWGA kit and more notably, are limited by the number of analyzed cells, making them limited for reproducibility analysis. We benchmarked an economical assay to compare all commercially available scWGA kits that is based on targeted sequencing of thousands of genomic regions, including highly mutable genomic regions (microsatellites), from a large cohort of human single cells (125 cells in total). Using this approach, we could analyze the genome coverage, the reproducibility of genome coverage and the error rate of each kit. Our experimental design provides an affordable and reliable comparative assay that simulates a real single cell experiment. Results demonstrate the needfor a dedicated kit selection depending on the desired single cell assay.

September 12, 2020COVID-19 is a viral respiratory illness, caused by the SARS-CoV-2 virus with frequent symptoms of fever and shortness of breath [1]. COVID-19 has a high mortality rate among elders. The virus has spread world-wide, leading to shut-down of many countries around the globe with the aim of stopping the spread of the disease. To date, there are uncertainties regarding the main factors in the disease spread, so sever social distancing measures and broad testing are required in order to protect the population at risk. With the increasing spread of the virus, there is growing fraction of the general population that may be immune to COVID-19, following infection. This immunised cohort can be uncovered via large-scale screening for the SARS-CoV-2 (Corona) virus and/or its antibodies. We propose that this immune cohort be deployed as a buffer between the general population and the population most at risk from the disease. Here we show that under a broad range of realistic scenarios deploying such an immunized buffer between the general population and the population at risk may lead to a dramatic reduction in the number of deaths from the disease. This provides an impetus for: screening for the SARS-CoV-2 virus and/or its antibodies on the largest scale possible, and organizing at the family, community, national and international levels to protect vulnerable populations by deploying immunized buffers between them and the general population wherever possible.Declarations of interestnone

Summary The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.

Summary Cell lineage analysis aims to uncover the developmental history of an organism back to its cell of origin. Recently, novel in vivo methods utilizing genome editing enabled important insights into the cell lineages of animals. In contrast, human cell lineage remains restricted to retrospective approaches, which still lack resolution and cost-efficient solutions. Here, we demonstrate a scalable platform based on short tandem repeats targeted by duplex molecular inversion probes. With this human cell lineage tracing method, we accurately reproduced a known lineage of DU145 cells and reconstructed lineages of healthy and metastatic single cells from a melanoma patient who matched the anatomical reference while adding further refinements. This platform allowed us to faithfully recapitulate lineages of developmental tissue formation in healthy cells. In summary, our lineage discovery platform can profile informative somatic mutations efficiently and provides solid lineage reconstructions even in challenging low-mutation-rate healthy single cells., Graphical abstract, Highlights • A human cell lineage discovery platform based on somatic STR mutations • The platform has been validated with a high resolution of ex vivo cell lineage tree • A melanoma lineage tree inferred from STR agrees with sampling location • Lineage trees of healthy cells support separation of embryonic germ layers, Motivation Human cell lineage trees can provide answers to the most profound open questions in human biology and medicine. Obtaining this knowledge is a long journey worth taking. We pioneered the concept, the mathematical foundations, and the implementation of the human cell lineage discovery method utilizing naturally acquired microsatellite mutations by individual cells, to reconstruct trees among human cells. We kept improving its power. From 128 microsatellites per cell to 2,000, we have now reached a panel of over 50,000 loci, barcoded and sequenced cost effectively. Retrieving this unprecedented amount of microsatellite data would enable precise cell lineage tree reconstruction., Tao et al. present a biological-computational cell lineage discovery platform that enables efficient acquisition of tens of thousands of short tandem repeat targets in human single cells and tailored cell lineage reconstruction with its integrated bioinformatic pipeline and database management system.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

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.

The nervous system contains trillions of neurons, each forming thousands of synaptic connections. It has been suggested that this complex connectivity is determined by a synaptic “adhesive code,” where connections are dictated by a variable set of cell surface proteins, combinations of which form neuronal addresses. The estimated number of neuronal addresses is orders of magnitude smaller than the number of neurons. Here, we show that the limited number of addresses dictates constraints on the possible neuronal network topologies. We show that to encode arbitrary networks, in which each neuron can potentially connect to any other neuron, the number of neuronal addresses needed scales linearly with network size. In contrast, the number of addresses needed to encode the wiring of geometric networks grows only as the square root of network size. The more efficient encoding in geometric networks is achieved through the reutilization of the same addresses in physically independent portions of the network. We also find that ordered geometric networks, in which the same connectivity patterns are iterated throughout the network, further reduce the required number of addresses. We demonstrate our findings using simulated networks and the C. elegans neuronal network. Geometric neuronal connectivity with recurring connectivity patterns have been suggested to confer an evolutionary advantage by saving biochemical resources on the one hand and reutilizing functionally efficient neuronal circuits. Our study suggests an additional advantage of these prominent topological features—the facilitation of the ability to genetically encode neuronal networks given constraints on the number of addresses.

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., Author Summary The history of an organism's cells, from a single cell until any particular moment in time, can be captured by a cell lineage tree. Many fundamental open questions in biology and medicine, such as which cells give rise to metastases, whether oocytes and beta cells renew, and what is the role of stem cells in brain development and maintenance, are in fact questions about the structure and dynamics of that tree. Random mutations that occur during cell division endow each organism cell with an almost unique genomic signature. Distances between signatures capture distances in the cell lineage tree, and can be used to reconstruct that tree. On this basis, our lab developed a method for cell lineage reconstruction utilizing a panel of about 120 microsatellites. In this work, we use a large dataset of microsatellite mutations from many cells that we collected in our lab in the last few years, in order to test the performance of different distance measures and tree reconstruction algorithms. We found that the best method is not the one that gives the most accurate estimates of the mean distance, but rather the one with the lowest variance.

FMS-like tyrosine kinase 3 receptor–internal tandem duplication (FLT3-ITD) commonly occurs in acute myeloid leukemia and is considered rare in acute lymphocytic leukemia. Acute leukemia has poor prognosis, mainly due to relapse. Standard FLT3-ITD diagnostic techniques are based on genomic polymerase chain reaction and have recently incorporated GeneScan (Applied Biosystems, Foster City, CA) to identify variations of the FLT3 gene. As this is an average-based assay utilized in a heterogeneous leukemic cell population, we hypothesized that cells of acute leukemia, considered FLT3-ITD-negative by standard methods, could possess a fraction of FLT3-ITD-positive cells. The present study employed single cell mutation analysis to evaluate the FLT3-ITD status in newly diagnosed acute myeloid leukemia (n = 5) and acute lymphocytic leukemia (n = 3) patients. A total of 541 single leukemic cells and 36 mononuclear cells from healthy volunteers were analyzed. Seven patients, considered FLT3-ITD-negative according to bulk DNA analysis, appeared to possess a small fraction of FLT3-ITD-positive cells based on single cell analysis. Moreover, this approach revealed the heterogeneity of the tumor as evident by different FLT3-ITD mutations present in the same patient. The presence of a minor clone carrying FLT3-ITD in almost all patients tested provides evidence that this lesion is a common late event in leukemogenesis. Additionally, 3 relapsed patients demonstrated loss of heterozygosity of the normal allele, affecting 25%–100% of the cells found to be FLT3-ITD-positive. Though further clinical testing is warranted, these findings may have implications on the prognostic significance of FLT3-ITD and the use of targeted therapy.

The Author Contributions are incorrect. They should be: Conceived the experiments: TBY GL. Designed the experiments: TB TBY GL. Performed the experiments: TB GL TBY. Analyzed the data: TB TBY GL YM. Wrote the paper: TBY TB ES.

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.

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, ∼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. [Cancer Res 2008;68(14):5924–31]

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 ~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.

A system based on RNA can perform simple logical computations within a living cell, marking a step toward programming cell behavior.

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., Author Summary 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.

Abstract 178 Introduction: Leukemic cells are heterogeneous in many ways, and specifically in replication rates. Dormancy and quiescence particularly among leukemia stem cells (LSCs) have been suggested to play a pivotal role in leukemia resistance to chemotherapy. This has been suggested in chronic leukemia, but never proven in acute leukemia, where most cancer cells divide frequently, and it is not known which subpopulation causes relapse. Cell lineage analysis of single leukemia cells can describe the variable kinetics of leukemia subpopulations by studying the evolutionary genetic changes between diagnosis and relapse in the same patient, and hence potentially pinpoint the relapse population already at diagnosis. In the current study a novel methodology was used in order to describe the evolutionary history of single leukemia cells. The reconstruction of phylogenetic trees from single cells can shed light of the relative number of replications of each cell (depth), and the diversity and heterogeneity of the tumor. Method: Phylogenetic analysis was applied to single cells from peripheral blood of two acute myeloid leukemia (AML) patients (n≂F40 cells from each patient), sampled at diagnosis and relapse. Leukemia and T cells were separated by FACS. T cells, which were not part of the malignant AML clone served for the validation of sorting. Single cells underwent whole genome amplification followed by PCR reactions amplifying 120 microsatellite (MS) loci, using a high throughput robotic and computer aided systems. As MSs accumulate genetic variation during replication, the phylogenetic tree of the malignancies can be reconstructed from the genetic changes in MSs between the cells and the application of a neighbor joining algorithm. The relative depth of cells was calculated from the genetic distance of each cell from the root of the tree, which was designated as the median value of all cells for a specific MS. Result: In the reconstructed cell lineage trees of both AML patients (L1 n=41 leukemia cells; L2 n=43 leukemia cells), cells at relapse were shallow compared to cells at diagnosis, implying that they originate from cells that divided rarely prior to relapse (p Conclusion: A novel single cell phylogenetic approach applied to AML cells uncovered the role of dormancy and LSCs in AML relapse. As chemotherapy preferentially targets rapidly-dividing cells, dormant cells are positively selected to resist chemotherapy at least in some AML patients. In such cases, in order to prevent relapse, leukemia therapy must also target such rarely-dividing leukemia cells. We have further demonstrated that LSCs are genetically correlated to the rarely dividing cells at relapse. The ability of cell lineage analysis to identify rarely dividing cells and correlate them to LSCs and possibly to normal stem cells already at diagnosis may enable their characterization and hence the design of improved targeted and personalized therapy for leukemia and other types of cancer with similar relapse mechanisms. Furthermore, this evolutionary-based approach can also shed more light on the diversity of leukemia in a time scale and uncover other chemotherapy resistance mechanisms. Phylogenetic trees of leukemia single cells at diagnosis and relapse from 2 AML patients. a, L1: Left – reconstructed lineage tree of CD33+ CD4+ CD15- peripheral blood (PB) individual leukemia cells at diagnosis (full, n=14); and relapse (blank, n=27) for patient L1; The root was determined by calculation of the median signal of all cells. Right - comparison of median depth between cells at diagnosis (full) and relapse (blank), (p Disclosures: No relevant conflicts of interest to declare.

Synaptic wiring of neurons in Caenorhabditis elegans is largely invariable between animals. It has been suggested that this feature stems from genetically encoded molecular markers that guide the neurons in the final stage of synaptic formation. Identifying these markers and unraveling the logic by which they direct synapse formation is a key challenge. Here, we address this task by constructing a probabilistic model that attempts to explain the neuronal connectivity diagram of C. elegans as a function of the expression patterns of its neurons. By only considering neuron pairs that are known to be connected by chemical or electrical synapses, we focus on the final stage of synapse formation, in which neurons identify their designated partners. Our results show that for many neurons the neuronal expression map of C. elegans can be used to accurately predict the subset of adjacent neurons that will be chosen as its postsynaptic partners. Notably, these predictions can be achieved using the expression patterns of only a small number of specific genes that interact in a combinatorial fashion., Authors Summary Synaptic wiring in the nematode Caenorhabditis elegans is largely invariant between individuals, suggesting that this wiring is genetically encoded. This is in essence the chemoaffinity hypothesis suggested by Roger Sperry. However, proving this hypothesis in model organisms and detecting the identities of the genes that determine the presence or absence of synaptic connections is a major challenge. C. elegans provides a unique opportunity to examine this hypothesis due to the availability of both its neuronal wiring diagram and neuronal gene expression map. In this study we show that the neuronal gene expression profiles can be used to predict the subset of adjacent neurons that each neuron will connect to with good accuracy. We further identify a small set of putative genes on both sides of the synapses that interact in a combinatorial fashion and mediate the neuronal partner selection process. The modular design in which a small set of components is reutilized throughout the network is common with other known biological systems and raises the possibility of a similar design in neuronal networks of more complex organisms.

Trinucleotide hereditary diseases such as Huntington disease and Friedreich ataxia are cureless diseases associated with inheriting an abnormally large number of DNA trinucleotide repeats in a gene. The genes associated with different diseases are unrelated and harbor a trinucleotide repeat in different functional regions; therefore, it is striking that many of these diseases have similar correlations between their genotype, namely the number of inherited repeats and age of onset and progression phenotype. These correlations remain unexplained despite more than a decade of research. Although mechanisms have been proposed for several trinucleotide diseases, none of the proposals, being disease-specific, can account for the commonalities among these diseases. Here, we propose a universal mechanism in which length-dependent somatic repeat expansion occurs during the patient's lifetime toward a pathological threshold. Our mechanism uniformly explains for the first time to our knowledge the genotype–phenotype correlations common to trinucleotide disease and is well-supported by both experimental and clinical data. In addition, mathematical analysis of the mechanism provides simple explanations to a wide range of phenomena such as the exponential decrease of the age-of-onset curve, similar onset but faster progression in patients with Huntington disease with homozygous versus heterozygous mutation, and correlation of age of onset with length of the short allele but not with the long allele in Friedreich ataxia. If our proposed universal mechanism proves to be the core component of the actual mechanisms of specific trinucleotide diseases, it would open the search for a uniform treatment for all these diseases, possibly by delaying the somatic expansion process., Author Summary Trinucleotide diseases are a broad family of hereditary diseases characterized genetically by an expanded DNA region consisting of a repeated three-letter code. Patients inheriting such an abnormal DNA region experience sudden disease onset at an age that inversely depends on the size of the expanded region, followed by inevitable and highly predictable suffering and death. Despite more than a decade of research, the underlying mechanism of these diseases remains an enigma. Although the genes implicated with the various trinucleotide diseases are unrelated, and the defects in these genes occur in different parts of the DNA coding for the gene, the diseases' shared characteristics suggest a common mechanism underlies their root cause. We suggest a mechanism that uniformly explains how the inherited DNA repeats genetically encode the time of onset and the rate of progression of trinucleotide diseases. It suggests the disease manifests and progresses through the further expansion of the inherited abnormally expanded DNA region. It explains the clinical data of many diseases in this family, including previously unexplained onset-related phenomena. It also predicts that a general therapy for these diseases would be a drug or procedure that successfully interferes with the ongoing expansion of the disease trinucleotide repeat.

What is the lineage relation among the cells of an organism? The answer is sought by developmental biology, immunology, stem cell research, brain research, and cancer research, yet complete cell lineage trees have been reconstructed only for simple organisms such as Caenorhabditis elegans. We discovered that somatic mutations accumulated during normal development of a higher organism implicitly encode its entire cell lineage tree with very high precision. Our mathematical analysis of known mutation rates in microsatellites (MSs) shows that the entire cell lineage tree of a human embryo, or a mouse, in which no cell is a descendent of more than 40 divisions, can be reconstructed from information on somatic MS mutations alone with no errors, with probability greater than 99.95%. Analyzing all ~1.5 million MSs of each cell of an organism may not be practical at present, but we also show that in a genetically unstable organism, analyzing only a few hundred MSs may suffice to reconstruct portions of its cell lineage tree. We demonstrate the utility of the approach by reconstructing cell lineage trees from DNA samples of a human cell line displaying MS instability. Our discovery and its associated procedure, which we have automated, may point the way to a future “Human Cell Lineage Project” that would aim to resolve fundamental open questions in biology and medicine by reconstructing ever larger portions of the human cell lineage tree., Synopsis The human body is made of about 100 trillion cells, all of which are descendants of a single cell, the fertilized egg. The quest to understand their path of descent, called a cell lineage tree, is shared by many branches of biology and medicine, including developmental biology, immunology, stem cell research, brain research, and cancer research. So far, science has been able to determine the cell lineage tree of tiny organisms only, worms with a thousand cells or so. Our team has discovered that the mutations accumulated in each cell in our body during its normal development from the zygote carry sufficient information to reconstruct, in principle, cell lineage trees for large organisms, including humans. Inspired by this discovery, we developed an automated procedure for the reconstruction of cell lineage trees from DNA samples. A direct application of these results may include the analysis of the development of cancer. The results may also inspire a future “Human Cell Lineage Project,” whose aim would be to reconstruct an entire human cell lineage tree.