Going beyond genetic letters, the results could transform medicine.
Thanks to increasingly efficient and affordable gene sequencing technologies, we can now chart our genetic blueprint in unprecedented detail.
But what does each gene do? Of the roughly 20,000 genes that encode proteins, we’re only privy to a small fraction of their functions. The most studied genes are related to diseases. Many others hum along in the background, keeping our bodies running, but how exactly isn’t known.
An ambitious project now aims to decipher the functions of all genes.
Led by the National Institutes of Health, the MorPhiC Consortium is creating the first catalog of every gene function. Using multiple gene editing techniques, they plan to inhibit genes one-by-one to see how it changes behaviors in cells.
The project recently launched its initial phase to tackle 1,000 genes. The team is also building a data infrastructure to share findings and fact-check results.
The project offers a bird’s-eye view of how each gene—and their combinations—keeps our bodily functions humming along.
It’s the “next frontier” after the Human Genome Project, wrote the authors. These studies will tell us “how genes function alone or together to govern cellular processes” and ultimately alter our cells, tissues, and health.
The Code of Life
Our cells are buzzing biological cities that never sleep.
The city center is a structure shaped like a peach core that houses all our DNA. Diverse molecules whiz about inside the cell translating DNA messages into proteins. The body’s workhorses, proteins go on to direct metabolism, trigger immune defenses, and shuttle oxygen through the blood.
Insights into how genes function are hard-won victories. Traditionally, scientists studied a single gene—usually, one likely related to a disease—for years.
High-throughput DNA sequencing accelerated these studies by hunting down potentially detrimental gene variants, or “alleles.”
Alleles are different versions of the same gene but with a range of diverse physical consequences. Eye color is one example. Different alleles result in blue, brown, green, or other colored eyes. Genetic variants have also been found to increase the risk of Alzheimer’s disease—or protect against it.
Thanks to databases containing hundreds of thousands of genomes, it’s now possible to find different alleles associated with more than 5,000 health outcomes. By comparing the genomes of large populations of humans, such studies have located many genes related to disease. Other projects, such as the Roadmap Epigenomics Mapping Consortium and the Encyclopedia of DNA Elements Project, have provided insight into when and where genes turn on or off.
Even so, “half of human genes are barely mentioned” in scientific studies, wrote the authors. “It is estimated that 75 percent of all research on protein-coding genes has been focused on fewer than 10 percent of proteins.”
It’s a tough task to chart the rest of the genome. Genes function very differently in various cell types. Although most cells contain the same DNA blueprint, how the blueprint activates depends on the tissue. Hence, the same blueprint can guide cells towards completely different destinies—such as building our skeletons, hearts, and brains. The same gene, depending on context, can also have different effects throughout the body.
But without a thorough understanding of all gene functions, our current knowledge is “skewed” and “biased,” wrote the team.
An Expanded View
Enter the MorPhiC Consortium. The project, first launched in 2022 and now in full swing, will map how individual genes, or groups of related genes, work to build and govern our cells.
They hope to do this is by creating “null” alleles—essentially wiping out a gene’s function. Scientists have long used this method to screen individual genes related to various diseases, but MorPhiC is going big by applying the technique to the entire human genome.
The consortium is starting with an induced pluripotent stem cell line. These are adult cells that have been returned to a stem-cell-like state and can be expanded from there. Publicly available lines allow researchers to compare data from cells with an identical genetic background.
The consortium has turned to the gene-editing tool CRISPR to inhibit gene functions. Some methods directly edit genetic information; others shut off a gene without touching its code. Many include a “barcode” to track edits inside cells for validation.
Each of these methods “has a unique advantage, depending on which genes are being studied,” wrote the team. But standardizing their gene-editing strategy makes it easier to decode outcomes when shared with others in the collaboration.
The next step is linking genetic changes to the cell’s function. The consortium approved a range of tests to see what happens when a gene is turned off. These include, for example, sequencing RNA, proteins, and fats after each edit. The tests cover important aspects of a cell’s life, such as its ability to grow, regenerate, and transform into other cell types on demand. Although not comprehensive, they cover the main functions of a cell and how they could go wrong.
All the project’s centers use the same set of tests, the team wrote, although each institution may include additional screens.
Deactivating a gene isn’t easy. For quality control, each center will also dig into the cells’ transcriptome—that is, which genes are turned on—to ensure that the targeted gene is shut off. For further quality control, all teams will start by editing the same set of genes to verify procedures and share outcomes.
Data Central
Meanwhile, three centers are in the works to set up protocols for data analysis and validation. These will help store and standardize data, so it’s sharable across the project and scientific community.
The centers are also beginning to analyze data from different sources to see how different genes act together—for example, how one damaged gene can cause a cascading effect that alters other genetic functions, in turn changing metabolism, cell development, or immune responses. This data could potentially help “develop novel machine-learning frameworks” that can decipher how gene networks affect a cell’s life, wrote the authors.
The initial phase of MorPhic is expected to last five years, with each lab using the pluripotent stem cell system. However, the consortium is already looking ahead. One future goal is finding a test that can characterize genes with multiple functions in multiple cell types. Another stretch goal is to shut down multiple genes at the same time and see how they change a cell’s behavior.
“This large-scale effort will broadly improve our understanding of human genes and how they interact to govern normal human development and disease pathogenesis,” wrote the authors.
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* This article was originally published at Singularity Hub
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