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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Genomic Variability within an Organism Exposes Its Cell Lineage Tree

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

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

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

Simulation of MS Mutations and Reconstruction Score on Random Trees

<p>Two types of random trees with 32 leaves were generated, and MS stepwise mutations were simulated. Results of simulations of wild-type human using different numbers of MS loci are shown. The white line marks the perfect score limit (according to the Penny and Hendy tree comparison algorithm [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0010050#pcbi-0010050-b29" target="_blank">29</a>]). The results show that it is possible to accurately reconstruct the correct tree for trees of depth equivalent to human newborn and mouse newborn (marked by blue and green dots, respectively) using the entire set of MS loci. A mathematical analysis proves that any tree of depth 40 (equivalent to mouse newborn) can be reconstructed with no errors. Simulations with MS mutation rates of MMR-deficient organisms demonstrate that cell lineage reconstruction is possible with as few as 800 MS loci (the white line indicates the 0.95 score). The quality of reconstruction depends on the topology of the tree and its maximal depth, which together influence the signal-to-noise ratio.</p

Cell Lineage Concepts

<div><p>(A) Multicellular organism development can be represented by a rooted labeled binary tree called the organism cumulative cell lineage tree. Nodes (circles) represent cells (dead cells are crossed), and each edge (line) connects a parent with a daughter. The uncrossed leaves, marked blue, represent extant cells.</p><p>(B) Any cell sample (A–E) induces a subtree, which can be condensed by removing nonbranching internal nodes and labeling the edges with the number of cell divisions between the remaining nodes. The resulting tree is called the cell sample lineage tree.</p><p>(C) A small fraction of a genome accumulating substitution mutations (colored) is shown. Lineage analysis utilizes a representation of this small fraction, called the cell identifier. Phylogenetic analysis reconstructs the tree from the cell identifiers of the samples. If the topology of the cell sample lineage tree is known, reconstruction can be scored.</p><p>(D) Coincident mutations, namely two or more identical mutations that occur independently in different cell divisions (blue mutation in A and B), and silent cell divisions, namely cell divisions in which no mutation occurs (D–F), may result in incorrect (red edge) or incomplete (unresolved ternary red node) lineage trees. Excessive mutation rates might result in successive mutations (not shown), which cause the lineage information to be lost.</p></div

CCT Model System

<div><p>(A–C) A cell sample lineage tree with a predesigned topology is created by performing single-cell bottlenecks on all the nodes of the tree. Lineage analysis is performed on clones of the root and leaf cells. Three CCTs (A–C) were created using LS174T cells that display MS instability. All topologies were reconstructed precisely. Edge lengths are drawn in proportion to the output of the algorithm. Gray edges represent correct partitions according to the Penny and Hendy tree comparison algorithm [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0010050#pcbi-0010050-b29" target="_blank">29</a>], and their width represents the bootstrap value [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0010050#pcbi-0010050-b29" target="_blank">29</a>] (<i>n =</i> 1,000) of the edge. A minimal set of loci yielding perfect reconstruction was found for each CCT (each colored contour represents a different mutation shared by the encircled nodes; see also <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0010050#pcbi-0010050-sg002" target="_blank">Figure S2</a>).</p><p>(D) There is a linear correlation (<i>R</i>² = 0.955) between reconstructed and actual node depths.</p><p>(E) Reconstruction scores of CCTs A–C using random subsets of MS loci of increasing sizes (average of 500).</p></div

Automated Procedure for Lineage Tree Reconstruction

<p>The procedure accepts biological samples and PCR primers as input, and outputs a reconstructed lineage tree. It consists of a series of seven consecutive steps (numbered), during which the physical biological samples are “transformed” into digital data, which are then analyzed algorithmically. We built a hybrid in vitro/in silico automated system that performs steps 2–7 of the procedure (outlined), and used it to process DNA from tissue samples and single-cell clones. Incorporation of whole genome amplification techniques in the future may enable processing of single cells as well. For a detailed specification of the procedure, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0010050#pcbi-0010050-sd001" target="_blank">Protocol S1</a>.</p