{"id":797333,"date":"2026-10-09T19:50:14","date_gmt":"2026-10-09T19:50:14","guid":{"rendered":"https:\/\/www.newsbeep.com\/uk\/797333\/"},"modified":"2026-10-09T19:50:14","modified_gmt":"2026-10-09T19:50:14","slug":"how-does-life-unfold-a-landscape-metaphor-comes-into-its-own","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/uk\/797333\/","title":{"rendered":"How Does Life Unfold? A Landscape Metaphor Comes Into Its Own."},"content":{"rendered":"

By the middle of the 20th century, it had begun to seem that biology was almost solved. Charles Darwin\u2019s theory of evolution by natural selection explained how organisms change and adapt. The modern science of genetics showed how it works at the molecular scale. Genes governing the traits of organisms get passed down from parent to offspring, and random mutations create the variations from which natural selection picks the \u201cfittest.\u201d Natural selection and genetics fitted together in what the biologist Julian Huxley christened \u201cthe modern synthesis\u201d in his 1942 book<\/a>. Once it was shown in 1953 that the genes are encoded by DNA, the rest of biology looked like little more than piecing together details.<\/p>\n

But not everyone was satisfied. The British biologist Conrad Hal Waddington<\/a>, known to his friends and colleagues as Wad, thought this focus on genes was all very well. But it wasn\u2019t clear to him, or anyone else, exactly how genes shape the forms and features of organisms \u2014 how they reliably generate all the different tissues of the body, in all the right places, during embryonic development. Around the same time that Huxley unveiled the modern synthesis, Waddington presented a novel picture of how this might unfold.<\/p>\n

He visualized the developmental process as a landscape with hills and valleys that split every so often like those in a river network<\/a>. At the very top of the highest hill he imagined a ball, which represented a population of cells in their earliest embryonic form \u2014 what we now call stem or pluripotent cells, which have the potential to become any cell type. The progression of the cells towards their fates \u2014 to become, say, skin cells, muscle cells, or nerve cells \u2014 is like the ball rolling downhill through the landscape.<\/p>\n

When the ball reaches a branching point (bifurcation), the model\u2019s \u201cgravity\u201d pulls it to one track or the other: In scientific terms, it must differentiate. Through a particular sequence of such branching decisions, Waddington argued, cells specialize into their mature types, or fates, each expressing a particular set of genes. The cells are restricted to a small number of well-defined states because they are \u201ccanalized,\u201d in Waddington\u2019s lexicon: trapped and channeled by the sides of the valley. In this way, a limited number of cell types reliably arise from the activity of an army of genes.<\/p>\n

\"Portrait <\/p>\n

The biologist Conrad H. Waddington\u2019s prescient ideas shaped the modern understanding of gene regulation, epigenetics, and evolutionary developmental biology. He died in 1975.<\/p>\n

Walter Stoneman, National Portrait Gallery London<\/p>\n

Waddington\u2019s landscape has been \u201cremarkably useful as a conceptual scaffold,\u201d said James Briscoe<\/a>, a developmental biologist at the Francis Crick Institute in London. \u201cThe core ideas \u2014 that development is progressive, that cell states are distinct, that bifurcations represent [cell] fate decisions, that canalization implies robustness \u2014 all survive.\u201d<\/p>\n

\u201cThere\u2019s so much richness to some of the concepts Waddington was trying to share,\u201d said Susanne Rafelski<\/a>, a biochemist at the Institute for Stem Cell and Regenerative Medicine in Seattle.<\/p>\n

But the concept was more of a visual metaphor than a representation of an actual biological process. Or so it seemed. In the past several years, researchers have mapped out the real topography of cell-state spaces \u2014 in effect, Waddington\u2019s landscapes \u2014 from experimental data collected from many thousands of cells over the course of embryonic development. Those analyses are revealing that development is not a mere readout of a genetic program, but rather a dynamic process in which communities of cells build themselves, and the very landscape they navigate, by mutual negotiation and interaction, into an organism.<\/p>\n

This cartography of development is now helping researchers understand how identical cells in the early embryo develop into the distinct tissues and cell types of a complex organism. This matters enormously for regenerative medicine and stem-cell engineering, Briscoe said: \u201cIf you understand the landscape topology and know where the bifurcations lie, you can in principle design methods that steer cell populations to desired states with precision, rather than by trial and error.\u201d<\/p>\n

Waddington\u2019s metaphor, then, could be the key to understanding and reshaping possibilities for what cells, tissues, and embryos can be.<\/p>\n

Charting a Landscape<\/p>\n

In the 1940s, genetics and embryology were separate sciences; not everyone even believed that genes played a significant role in development. Yet Waddington\u2019s own experiments in embryology, and those of others, convinced him that the formation and patterning of tissues in an embryo were indeed controlled by genes. The cells of different tissues had different groups of genes activated in their chromosomes, he thought. A process of differentiation gradually specialized cells into skin cells, nerve cells, and so on.<\/p>\n

Waddington figured that the developmental pathways \u2014 for example, the formation of the neural tube from a layer of embryonic tissue called ectoderm, which ultimately develops into the central nervous system \u2014 are inevitable once the process has begun, just as water flowing down a river valley is constrained by its surroundings. The path might meander a little, but the valley keeps the river on course. Differentiation corresponds to the branching of a valley, and the final destinations are the mature cell types of the body.<\/p>\n

\"A <\/p>\n

Waddington\u2019s classic drawing of the epigenetic landscape. A ball, representing a pluripotent cell or population, is poised to roll downhill into valleys, each of which represent a specialized cell type, such as a blood cell, liver cell, or brain cell.<\/p>\n

From The Strategy of the Genes by C.H. Waddington<\/p>\n

Waddington visualized this as a landscape in drawings, but they had \u201cno grounding in physical reality,\u201d wrote Scott Gilbert, a developmental biologist at Swarthmore College in Pennsylvania, in a 1991 essay in Biology & Philosophy<\/a>. They were useful schematics for thinking about the problem of development, and nothing more.<\/p>\n

\u201cWithout mathematical content,\u201d Briscoe said, the metaphor \u201ccould not distinguish between alternative mechanisms, make quantitative predictions, or be falsified.\u201d As a result, he said, Waddington\u2019s landscape \u201chas sometimes become a clich\u00e9 rather than a meaningful explanation.\u201d<\/p>\n

What, for example, determines the topography of the hills and valleys? In his 1957 book The Strategy of the Genes<\/a>, Waddington depicted the landscape as he figured it might look from underneath: as a sheet that is tugged into shape by a network of ropes attached to pegs. The pegs represented individual genes, and the ropes their effects on development. Expressing a particular gene \u2014 turning it into its corresponding protein \u2014 is like pulling on its ropes to change the shape of the sheet.<\/p>\n

\"A <\/p>\n

What determines the landscape\u2019s shape? Waddington sketched a network of pegs and ropes beneath the rolling hills; the pegs are genes, and the ropes are their interconnections. Together they shape the landscape above and represent what we now call gene regulatory networks.<\/p>\n

From The Strategy of the Genes by C.H. Waddington<\/p>\n

It\u2019s rather more complex than that, Waddington realized, because the ropes are connected in a network. Any one of them might influence the landscape at several points, and any given point on the landscape might be attached to several ropes.<\/p>\n

These hidden connections correspond to what researchers now call gene regulatory networks: interactions among genes whereby an increase in the expression of one might change, or regulate, the activity of others. Herein lies the cryptic complexity of development. A given process, such as formation of the neural tube, might be influenced by many interacting genes; there\u2019s no simple relationship between genes (genotype) and the developmental landscape that determines form (phenotype). Gene regulatory networks mediate between them.<\/p>\n

It makes no sense, then, to look for genes dedicated to creating specific tissues, organs, or structures in a whole organism, which is one reason Waddington\u2019s metaphor proved useful. The landscape image was \u201cvaluable in providing an alternative to a purely gene-centric view of development,\u201d Briscoe said. By emphasizing the landscape\u2019s shape, it pointed \u201ctoward system-level properties that cannot be read off from any single gene.\u201d<\/p>\n

Given that the channels and spheres had no physical reality, what was an embryologist supposed to do with them?<\/p>\n

Scott Gilbert, Swarthmore College<\/p>\n

Gene regulation wasn\u2019t understood when Waddington first devised his landscape and rope network. A few years later, in the early 1960s, it became clear that one gene could turn another on or off<\/a>. Researchers, such as the complexity theorist Stuart Kauffman, began to construct simple mathematical models of the networks of gene interactions. But too little was then known about real gene networks to connect abstract theory to experiment. \u201cGiven that the channels and spheres had no physical reality,\u201d Gilbert wrote, \u201cwhat was an embryologist supposed to do with them?\u201d<\/p>\n

Answers have begun to emerge over the past two decades thanks to new experimental tools for characterizing cell states. Biologists are now finally becoming able to map experimental data to a real mathematical landscape for differentiation and show just how prescient Waddington was.<\/p>\n

Fated Attractors<\/p>\n

One way to define the state of a given cell in an embryo is by the expression levels of its genes. These levels can now be measured simultaneously in many cells using a technique called single-cell RNA sequencing, which supplies a snapshot of all the different RNA molecules each cell contains. An RNA molecule (or transcript) is a kind of copy of a gene used to translate it into a functional protein, and generally, more RNA transcripts means higher expression of that gene. Each cell type is characterized by particular gene-expression settings, which are inherited when a cell divides. This ensures that a liver cell will stay a liver cell as it progresses through an organism\u2019s development process.<\/p>\n

In principle, RNA-sequencing data can be modeled as a high-dimensional mathematical space in which each axis denotes the number of RNA transcripts of a single gene. Such a plot, with maybe thousands of dimensions to represent thousands of genes, is impossible to visualize, but it can be mathematically projected onto a space with fewer dimensions, usually just two, to produce something like the shadow of a complex 3D object.<\/p>\n

On such a plot, called a UMAP (uniform manifold approximation and projection)<\/a>, different cell types appear as clusters of points \u2014 blood cells cluster together, say, as do cells of the muscle or forebrain \u2014 as they share a gene expression profile. Cell lineages follow paths through this map as development proceeds. When the data is mapped through time \u2014 in what\u2019s known as a network flow model \u2014 it looks very much like a population of cells rolling through a Waddington-like landscape, being channeled along valleys that lead to basins that correspond to distinct cell types.<\/p>\n","protected":false},"excerpt":{"rendered":"By the middle of the 20th century, it had begun to seem that biology was almost solved. Charles…\n","protected":false},"author":2,"featured_media":797334,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[59,102,56,54,55],"class_list":["post-797333","post","type-post","status-publish","format-standard","has-post-thumbnail","category-health","tag-gb","tag-health","tag-uk","tag-united-kingdom","tag-unitedkingdom"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/797333","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=797333"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/797333\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/797334"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=797333"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=797333"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=797333"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}