| Multi-cellular organisms come in a plethora of shapes and forms, and their diversity is evident wherever we set our eyes upon. Despite their differences, all multi-cellular organisms share a common basic developmental pattern: they all originate from a single founder cell (the zygote), and develop through numerous binary cell divisions, a process which continues throughout adult life. This development is naturally represented by a binary tree, which we call the organism's cell lineage tree. This tree is similar to a genealogical tree describing the descent of a family, or to the "tree of life", depicting how species on Earth evolved. Lineage trees encapsulate a wealth of extremely interesting (say, for developmental biology) and useful (say, for disease treatment) information. Such a complete tree was only reconstructed for simple organisms such as the worm C. elegans, while lineage trees for higher organisms such as humans and mice are almost completely unknown due to inherent limitations in existing methods for lineage analysis. Although obtaining such complete information for such organisms may not be feasible, even partial knowledge of lineage trees may help solve fundamental open questions in biology and medicine.;At the outset of my PhD we (collaboration with Dan Frumkin) developed a new method for performing high-resolution cell lineage analysis in a non-invasive manner, applicable to humans and mice. The method is based on our discovery that somatic mutations accumulated during the normal development of an organism hold a record of the history of cell divisions. Cells with more common somatic mutations tend to share a longer common developmental path, analogously to species with more similar genomes which tend to share a longer common evolutionary path. Consequently, analysis of the DNA sequences of cells enables to reconstruct the lineage relations between these cells. In this part of the project, we developed the method, automated it, and proved its applicability and feasibility.;With a working method at hand, we approached researchers from various fields of biology in order to apply the method and address open questions in lineage analysis. Our first goal was to analyze cells of various types in mouse and get a first glimpse into what the mouse cell lineage tree looks like. We found that cells of different types are intermingled on the lineage tree, demonstrating that lineage and function are not necessarily tightly correlated. This finding, although consistent with existing data, may be counterintuitive to many biologists. Focusing on satellite cells (muscle stem cells), we found that satellite cells from the same muscle fiber (but not muscle) tend to share a common developmental path and are significantly clustered in the lineage tree. This finding sheds light on the basic question regarding the correlation between lineage and physical proximity, and may suggest a model for the developmental process of skeletal muscles.;We also developed a new method for estimating the depths of cells in living organisms (the depth of a cell is the number of divisions it underwent from the zygote). Although depth is a basic property of any cell, science was unable so far to provide even gross estimates for the depths of the vast majority of human and mouse cells. Applying the method in mice, we obtained for the first time depth data for many cell types, such as that stem cells are relatively shallow, muscle stem cells in mature muscle are mitotically quiescent, and B-cell progenitors divide on average about once per day. Knowing how deep cells are, holds the key to many fundamental open questions in biology and medicine, such as whether neurons in our brain can regenerate, or whether new oocytes are created in adult females.;This work marks the first steps toward our long term goals of the Human and Mouse Cell Lineage Projects, whose aims are to understand ever larger portions of the lineage trees of these organisms. |
