20th century genetics operated under Central Dogma. But its successor, genomics, has a messier story.
In the late 1990s and early 2000s, a swarm of newly coined words descended upon biology. Some, like proteome and transcriptome, were welcome additions. But -Omes of questionable usefulness kept popping up: Vitaminome. Secretome. Psychome. Sleepome. Many scientists felt the -Ome trend was getting out of hand.
The source of the fad wasn’t hard to pinpoint. The Human Genome Project, an effort to sequence all of the DNA in the human genome, had made genomics both trendy and prestigious, and researchers dreamt of getting in on the ground-floor of new genomics spin-off fields that would catalogue and decode other types of biomolecules. Naturally, these spin-offs were given similar sounding names with the suffix -ome or -omics.
The suffix traces back to the Greek word 'soma', which means body. It immigrated into biology parlance in 1888, when a German anatomist identified a clump of cellular structures that easily absorbed dye and named them 'chromosom'.
Since then, -ome has come to denote totality or wholeness; the genome consists of the total body of genes in the cell, the proteome includes all the proteins, and so on. Despite its estrangement from its Greek root , -ome not only caught on but became symbolic of a particular scientific approach. -Omics researchers aim to catalogue vast arrays of biological variation and identify the patterns within.
According to self-declared 'omicist' Jong Bhak, the -Omics proliferation was a direct result of the growing number of computer specialists entering biology. In a post called “The History of Omics” for the wiki page Omics.org, he argues that though -Omicses seem disparate on the surface, they share underlying approach. “They apply systems theories to the problems regarding the problem domains as complex systems to be understood by not only logics, but also with components' interactions and dynamics using computers,” Bhak wrote.
In other words, most -Omicses are forms of systems biology. Instead of trying to understand isolated genes, -Omics practitioners search for patterns in complex molecular systems.
The -Omicses are all young sciences, and most of them still orbit the original behemoth: genomics.
Like its siblings, genomics is a computer-driven field. Unlike traditional genetics, which studies just a few genes at a time, genomics deals in interactions between thousands of genes. Because of its systems-biology orientation, genomics exists quite happily alongside its spin-offs and labs which still practice traditional one-gene-at-a-time genetics.
Many people take genomics’ status as a scientific revolution for granted. The US National Human Genome Research Institute (NHGRI)’s website features a page touting their efforts in “Bringing the Genomic Revolution to the Public”. Gene sequencing’s role in personalised medicine has prompted academic papers, TEDTalks, and headlines about genomics’ potential to revolutionise medicine. Indeed, the genomics revolution is so imminent that many countries are beginning to mobilise research so that they won’t be left out.
However, most references to genomics’ alleged revolutionary stature refer to gene sequencing technology, not the scientific worldviews that inform how we use them.
When the idea of genes first debuted in 1909, scientists had no idea whether genes physically existed. They were simply theorising that traits might be separately heritable, as opposed to being a package deal. However, research soon established chromosomes as the bearers of heredity. 20th century genetics’ second act culminated in the discovery of DNA’s double helix in 1953.
But even with DNA’s structure in hand, researchers still didn’t understand how information in DNA nucleotides got put into action. Double helix co-discoverer Francis Crick pondered these questions often, and, on one evening in October 1956, he jotted down two sentences that would transform biology:
“The Central Dogma: ‘Once information has got into a protein it can’t get out again. Information here means the sequence of the amino acid residues, or other sequences related to it.’”
Crick would later refine Central Dogma, but the basic idea remained the same: Mutations in DNA and RNA could change proteins, but proteins could not alter DNA base pairs. When it came to gene expression, Central Dogma held that DNA was the beginning, RNA was the middle, and proteins were the end. Other chemicals that could potentially encode information were unimportant. Despite the near-total absence of experimental evidence backing up his new ‘dogma’, Crick presented the idea at a symposium in 1957 and officially published it in 1958.
The subsequent discovery of messenger RNAs, which carry protein templates from the nucleus to the ribosome, in 1961 shored up the Central Dogma’s status. It quickly became the dominant paradigm for molecular genetics.
In that same year, French biologists Francois Jacob and Jacques Monod found a potential loophole in Central Dogma: a bacterial protein could influence whether genes were transcribed into RNA. That protein didn’t change the DNA base pairs, but it did suggest that Central Dogma wasn’t the only player in the gene expression game. Nevertheless, Crick’s hypothesis stood and was soon written into textbooks.
But Jacob and Monod’s protein was only the first of many loopholes.
Over the next few years, researchers began to notice that smaller molecules could glom onto proteins and change what the protein did. Exactly what happened depended on which small molecule and which protein, but this ‘post-translational modification’ could make a huge difference in cell function. In 1977, researchers discovered that cells can also alter and abridge the RNA copies of genes before the RNA even leaves the nucleus, through a process called alternative splicing. These loopholes, along with several others, could shape which traits cells express. Though they didn’t directly contradict Central Dogma, they weren’t officially part of it, either.
Central Dogma pushed scientists to invent ways to decode DNA, RNA, and proteins. At first, sequencing DNA was massively laborious, but improvements to techniques by pioneers like Fred Sanger fueled more research. In the 1970s, researchers learned how to transplant or 'clone' genes from one organism to another. 1985 saw the invention of PCR, a technique that enabled scientists to sequence DNA faster and more accurately.
PCR’s speed opened up the option of sequencing genomes in their entirety. Buzz around a potential Human Genome Project began in the mid-1980s, the word genomics was allegedly coined over drinks in 1986, and in 1988, US Congress authorised the Department of Energy and the National Institutes of Health to start organising such an initiative.
The Human Genome Project officially commenced in 1991. Even with dozens of labs around the world working on the project, the HGP spurred the invention of faster sequencing techniques, including microarrays and shotgun sequencing. Computers played a vital role in recording, storing, and analysing sequencing data. Despite rivalries and behind-the-scenes drama, the HGP completed its genome draft ahead of schedule in 2001.
The Nature paper announcing the HGP’s initial results proudly heralded the arrival of a new field: “The last quarter of a century has been marked by a relentless drive to decipher first genes and then entire genomes, spawning the field of genomics.”
The 2001 draft genomes are the most prominent landmark in genomics’ history, but ironically, the HGP’s results underscored the importance of biomolecules outside of DNA. Going into the HGP, researchers thought the human genome might have as many as 100,000 genes. But the HGP only found about 30,000. Surely, observers reasoned, running a human body with distinct tissues in the heart, the brain, etc. would require more than a mere 30,000 proteins!
The explanation lay with the loopholes that researchers had begun to document in the 1970s. With help from RNA-splicing enzymes and protein-tagging molecules, cells can get hundreds of thousands of protein variants with varying functions and affinities out of just 20,000 genes.
These findings don’t disprove Central Dogma — far from it. If the Central Dogma didn’t work, then the sequencing techniques scientists developed based on it wouldn’t work either. But these findings did somewhat diminish the dogma’s centrality.
Where genetics was (and is) a science about the central dogma, genomics is a science about relationship dynamics between thousands of biomolecules. It replaces the idea of a stable genetic ‘essence’ with a dynamic, turbulent, and complex system of systems. Genomics hasn’t usurped genetics’ Central Dogma, so much as it has swallowed it. Though rife with loopholes, the Central Dogma throughline from DNA to RNA to protein is still a touchstone for understanding genes and traits.
However, genomics gives supporting characters － RNAs, alternate splices, small molecules — bigger roles in the story of gene expression. Physician and author Siddhartha Mukherjee sums up this idea eloquently in his 2016 book The Gene: An Intimate History, writing, “Of all the sciences, biology is the most lawless; there are few rules to begin with, and even fewer rules that are universal… We live in the loopholes of natural laws, seeking extensions, exceptions, and excuses.”
Several of genomics’ satellite disciplines focus on quantifying, cataloguing, and understanding these loophole processes, and, as such, they are part of the same computational systems biology paradigm that governs genomics. Few people argue that proteomics, perhaps the second-most prominent -Omics, is revolutionary in its own right, and that’s probably because, in some ways, proteomics and genomics are two parts of the same field.
However, the frenzy of DNA deciphering hasn’t abated. Thousands of species’ genomes have been sequenced. Massively parallel sequencing machines, which decode thousands of DNA fragments at a time, have allowed the pace of sequencing to keep accelerating while the cost continues to plummet.
What’s less clear is whether our ability to interpret genomes has kept up. Genomics has no central dogma of its own. Even now, nearly seventeen years after the publication of the HGP’s first draft, scientists still struggle to agree on the number of genes in the human genome. Some gene mutations have clear and obvious effects, but most don’t.
In the past 10 years, it’s become clear that precision medicine’s success will hinge not just on understanding DNA but also on understanding the protein and small molecule -Omics layers, so much so that some researchers have pushed to call this the “post-genomics” era. Genomics alone can tell us a lot, but, as Lateral’s founding editor Jack Scanlan noted in 2016, it can’t tell the whole story by itself.
Some have argued that genomics’ lack of clear rules means that it’s lacking as a paradigm. Hearing that heredity is too complicated for anyone to understand without help from a computer is not particularly comforting, especially for people who want their sciences to give them certainty.
Others have argued that since so many labs still focus on untangling the lives of just a few genes － i.e. some labs are still genetics labs －genomics has not been forceful enough in unseating its predecessor to count as a paradigm shift.
However, even though the -Omics approach coexists with more traditional genetics, the genomics mindset and the giant datasets it drives scientists to gather have transformed practically every field in biology. Phylogenomics, which reconstructs evolutionary history by comparing organisms’ genomes, is now a cornerstone of evolutionary biology and paleontology. Metagenomics, which sequences entire microbial ecosystems, has yielded profound insights into the lives of microbes. And synthetic biology, which uses genomic data as a repository of spare parts, promises to engineer life-saving solutions to the world’s problems.
Genomics and its cohorts are massively popular, and as the data collected so far support the idea of the cell as a semi-chaotic Rube Goldberg device, comprised of many overlapping smaller systems. Bioinformatics and systems biology logic look like they’re here to stay for the foreseeable feature.
So, I’d argue that genomics and its kin have, in fact, staged a fairly bloodless scientific revolution. But it’s not the accelerating pace of sequencing that makes them revolutionary; it’s the way -Omics push us to rethink what we think we know about genes and the worlds inside our cells.
Edited by Tessa Evans and Sam Vilkins