Review

Phylodynamics for cell biologists

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Science  15 Jan 2021:
Vol. 371, Issue 6526, eaah6266
DOI: 10.1126/science.aah6266

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Ancestry and evolution in cell biology

Advances in experimental approaches for single-cell analysis allow in situ sequencing, genomic barcoding, and mapping of cell lineages within tissues and organisms. Large amounts of data have thus accumulated and present an analytical challenge. Stadler et al. recognized the need for conceptual and computational approaches to fully exploit these technological advances for the understanding of normal and disease states. The authors review ideas taken from phylodynamics of infectious disease and show how similar tree-building techniques can be applied to monitoring changes in somatic cell lineages for applications ranging from development and differentiation to cancer biology.

Science, this issue p. eaah6266

Structured Abstract

BACKGROUND

The birth, death, and diversification of individuals are events that drive biological processes across all scales. This is true whether the individuals in question represent nucleic acids, cells, whole organisms, populations, or species. The ancestral relationships of individuals can be visualized as branching trees or phylogenies, which are long-established representations in the fields of evolution, ecology, and epidemiology. Molecular phylogenetics is the discipline concerned with the reconstruction of such trees from gene or genome sequence data. The shape and size of such phylogenies depend on the past birth and death processes that generated them, and in phylodynamics, mathematical models are used to infer and quantify the dynamical behavior of biological populations from ancestral relationships.

New technological advances in genetics and cell biology have led to a growing body of data about the molecular state and ancestry of individual cells in multicellular organisms. Ideas from phylogenetics and phylodynamics are being applied to these data to investigate many questions in tissue formation and tumorigenesis.

ADVANCES

Trees offer a valuable framework for tracing cell division and change through time, beginning with individual ancestral stem cells or fertilized eggs and resulting in complex tissues, tumors, or whole organisms (see the figure). They also provide the basis for computational and statistical methods with which to analyze data from cell biology. Our Review explains how “tree-thinking” and phylodynamics can be beneficial to the interpretation of empirical data pertaining to the individual cells of multicellular organisms.

We summarize some recent research questions in developmental and cancer biology and briefly introduce the new technologies that allow us to observe the spatiotemporal histories of cell division and change. We provide an overview of the various and sometimes confusing ways in which graphical models, based on or represented by trees, have been applied in cell biology. To provide conceptual clarity, we outline four distinct graphical representations of the history of cell division and differentiation in multicellular organisms. We highlight that cells from an organism cannot be always treated as statistically independent observations but instead are often correlated because of phylogenetic history, and we explain how this can cause difficulties when attempting to infer dynamical behavior from experimental single-cell data. We introduce simple ecological null models for cell populations and illustrate some potential pitfalls in hypothesis testing and the need for quantitative phylodynamic models that explicitly incorporate the dependencies caused by shared ancestry.

OUTLOOK

We expect the rapid growth in the number of cell-level phylogenies to continue, a trend enhanced by ongoing technological advances in cell lineage tracing, genomic barcoding, and in situ sequencing. In particular, we anticipate the generation of exciting datasets that combine phenotypic measurements for individual cells (such as through transcriptome sequencing) with high-resolution reconstructions of the ancestry of the sampled cells. These developments will offer new ways to study developmental, oncogenic, and immunological processes but will require new and appropriate conceptual and computational tools. We discuss how models from phylogenetics and phylodynamics will benefit the interpretation of the data sets generated in the foreseeable future and will aid the development of statistical tests that exploit, and are robust to, cell shared ancestry. We hope that our discussion will initiate the integration of cell-level phylodynamic approaches into experimental and theoretical studies of development, cancer, and immunology. We sketch out some of the theoretical advances that will be required to analyze complex spatiotemporal cell dynamics and encourage explorations of these new directions. Powerful new statistical and computational tools are essential if we are to exploit fully the wealth of new experimental data being generated in cell biology.

Multicellular organisms develop from a single fertilized egg.

The division, apoptosis, and differentiation of cells can be displayed in a development tree, with the fertilized egg being the root of the tree. The development of any particular tissue within an organism can be traced as a subtree of the full developmental tree. Subtrees that represent cancer tumors or B cell clones may exhibit rapid growth and genetic change. Here, we illustrate the developmental tree of a human and expand the subtree representing haematopoiesis (blood formation) in the bone marrow. Stem cells in the bone marrow differentiate, giving rise to the numerous blood cell types in humans. The structure of the tree that underlies haematopoiesis and the formation of all tissues is unclear. Phylogenetic and phylodynamic tools can help to describe and statistically explore questions about this cell differentiation process.

Abstract

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how “tree thinking” is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

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