Genome Architecture

“Politeness,” Francis Crick once remarked, “is the poison of all good collaboration in science”¹. Crick was not advocating rudeness for its own sake, but candour — the belief that scientific progress depends on the ability to challenge explanations early, openly, and without regard to hierarchy. That ethic shaped the early culture of molecular biology, including the environment in which he himself worked at the MRC Laboratory of Molecular Biology. It is in that spirit that I want to reflect on the trajectory of three-dimensional genome organisation: a field that has advanced with remarkable speed, and now faces the productive discomfort of its next set of questions.

After working on mobile DNA — elements that move, rewire, and rearrange genomes — I joined the LMB to work on three-dimensional genome organisation in yeast. This felt like a natural progression: from investigating how individual DNA elements can be mobilised, we were now asking how complete genomes are arranged in space.

In 2002, Job Dekker, together with Karsten Rippe, Martijn Dekker and Nancy Kleckner, published a deceptively simple method in Science to map genomic proximity in live cells, titled Capturing Chromosome Conformation ². This soon became abbreviated to 3C, the name bearer and originator of a family of related techniques. What followed were 4C (Circularised Chromosome Conformation Capture), 5C (Carbon Copy Chromosome Conformation Capture), and eventually Hi-C, which did away with the numbering altogether and, at the time, represented the most advanced approach available.

In 2010, a complete genome had been mapped in three dimensions for the first time³: that of the small but foundational model organism Saccharomyces cerevisiae, commonly known as baker’s or brewer’s yeast — the same yeast that humankind has used for millennia to bake bread and make beer.

That paper landed on my desk when I joined the LMB, and we set out to understand the data in greater depth by introducing more biology into the analysis. The structure was available for all to see and explore — but what it told us about how the organism functioned was still unclear. Did this structure matter at all? Or was it simply fascinating to look at — which it undeniably was. My colleagues and I began to ask that question in earnest.

We were, of course, not alone. What started as an off-shoot project in Nancy Kleckner’s lab at Harvard soon became a genuine scientific field: 3D Genome Organisation. Research centres emerged in Seattle, Munich, Utrecht, and Amsterdam. Over the following years, this list grew to include Cambridge, Göttingen, Berlin, and Oxford among several others.

It was an exhilarating time to be doing science. We were beginning to integrate multiple molecular layers — transcriptomics, histone modifications, chromatin states — and to relate them, for the first time, to three-dimensional genome organisation. Structure and function no longer had to be inferred in isolation. The interplay between the physical nature of biological systems and the dynamics that animate them has always been where the most revealing experiments lie — and where some of the most fundamental insights into what makes living systems live tend to emerge.

What followed was an intense period of exploration and application. High-throughput assays made it possible to collect data at unprecedented scale. Parallel DNA sequencing, chip-based technologies to map protein–DNA interactions, and increasingly sophisticated computational pipelines produced vast datasets rich in signal — still waiting to be interpreted.

The pace of methodological innovation was such that our weekly seminars were often devoted to new techniques rather than new biological findings. Entire seminar series were devoted to following experimental advances — new ways of measuring gene expression, genomic proximity, protein occupancy, and chromosome dynamics. It was a remarkable moment: the tools were advancing faster than our collective ability to digest the data and confer function.

The field stabilised at the descriptive layer faster than its control layer.

By now, more than a decade and a half after the first whole-genome 3D structure of a eukaryote was published, the field has convincingly succeeded in establishing genome architecture as a real and consequential structure of importance. We have identified disease-linked enhancers, opening new avenues for target discovery. We have followed structural changes during development, helping to pinpoint regions essential for normal growth that also play roles in dysregulation and cancer and identified regulatory regions altered in neuronal diseases.

The questions that follow are no longer whether genome architecture matters — that much has been settled. The challenge now, and the one that will define the field’s impact on medicine, is to understand how these architectural states are regulated, tuned, and altered by molecular mechanisms.

This is where Crick’s insistence on candour remains relevant. Agreeing with him does not mean rejecting collaboration or collegiality; it means accepting that difficult questions must be asked before explanations become too comfortable. Scientific progress depends on that friction.

Max Delbrück, a contemporary of Crick, was famously sceptical of explanations that stabilised too quickly¹. His instinct remains instructive as genome architecture moves from exploration to application: description is not the endpoint, but the starting point for understanding how biological systems work.

Answering that question will elevate the value of mapping, as it will complete its trajectory: carrying architectural insight across the bridge from description to control, and from understanding to intervention.