Scientists from the University of Toronto’s Donnelly Centre have identified the minimum set of human genes necessary for survival. Using the CRISPR technology, the researchers switched off 18000 genes, one by one, to identify a core of 1500 essential genes. The study, published in Cell, identified different sets of genes crucial in different types of cancer, and paves the way to understanding the role of every single gene in the human body.
Twelve years ago, the human genome was fully sequenced. Despite having that information, the function of many of the 20000 genes was still unknown. It was quite clear that, in order to understand what every gene does, they would have to be individually switched off to test the resulting phenotype. Back then, however, the available technologies to “knock out” a gene were slow and/or not very precise. The arrival of the CRISPR/Cas9 technology changed the scenario: several research groups embarked on a race to turn genes off. Finally, the Toronto group publication was accompanied by a Science paper from Harvard and MIT researchers, concluding that around 10% of the human genes are vital. Most of the genes play roles in combination with other genes, and their loss is deleterious only in combination with the loss of other genes or in certain detrimental environmental conditions.
Switching genes off in different cancer cell lines
Professor Jason Moffat decided to do the same experiment -turning off all genes, one by one- in cell lines affected by different cancers -brain, retinal, ovarian, and colorectal. His team identify a different set of essential genes for every cancer type, which explains why anti-cancer drugs present very different efficacy depending on the cancer being treated. This study has pinpointed the genes that must be targeted in each cancer, advancing the design of effective drugs.
Thanks to the information extracted from the whole genome sequence, the power of in vitro cell line research and the accuracy of the new gene editing tools, scientists are closer to obtaining a full map of the correlation between DNA sequence variation and drug targets.