We have sequenced the human genome, the chicken, and the eggplant. That means we know the order of the bases that make up the specific organism’s DNA. But we don’t really know what we found. The job of almost all that DNA remains a mystery. Now a software program developed at the Hebrew University of Jerusalem can help us figure out what most of that enigmatic DNA really does. And then maybe, one day, we can find new ways to cure all sorts of nasty diseases.
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Say you have a test tube-full of DNA goop, fully sequenced and all, and no idea what it does. You can enter the sequence into the system to see if it appears in known genes in the animal or plant kingdom, explains the system’s inventor, Prof. Yuval Tabach.
If you find your sequence consistently associated with known genes for eye color, for instance, then you may assume it is associated with eye color.
The software is based on evolutionary profiling: how a gene changes through evolution.
Say our proto-mammal ancestor had a group of genes for whisker growth. Theoretically, all the species arising from that proto-mammal will have that group of genes – but the genes will have mutated in different ways in the different species over the eons. In species who lost their whiskers, these genes may become dysfunctional, degenerate and dormant. Still, the genes (if still there at all) should retain enough common features to be recognizable by the Tabach system.
Good and bad mutations
The whisker gene group would change from species to species through mutation, which simply means random change to the DNA.
The change may be benign and insignificant. It may be positive and make the creature better adapted to cope with the vicissitudes of life, and thus better positioned to breed more. When the mutation is “bad,” if the creature survives at all, it may well die before procreating, and the mutation will be lost (unless the mutation takes effect after maturity and procreation – take so-called “cancer genes”).
An example of a bad but non-lethal mutation is lactose intolerance. The results may be socially untenable but won’t kill you. An example of a fatal mutation might be, for instance, one that renders hemoglobin unable to fixate oxygen properly; that creature would not survive long after birth.
“Good” mutations are, for instance, the one that rendered a village in Italy better able to deal with “bad” cholesterol.
Ubiquitin, a protein associated with metabolic regulation, is an example of a gene that cannot tolerate mutation. Ubiquitin mutants are usually either very sickly, or dead.
But most genes are more “tolerant” of change. Take genes connected with vision. You probably like to see, but some species that evolved to live in caves, for instance, have lost their vision or even their eyes entirely through eons of evolution.
One result is that their genes coding for vision could become nonfunctional and degenerate. Yet their inactive vision genes retain enough similarity to actual functional vision genes to remain identifiable.
Now think of this backward. You find a genetic sequence in an eyeless scorpion and wonder what it does. You run the Tabach software on it, seeking that sequence in other life forms. Presto: You discover that other animals have this sequence – and that it’s in their vision genes. Ergo, this sequence has to do with vision. Yay.
The genetics of cancer
The implications for medicine will take some time to evolve, but they could be staggering.
Human DNA has 3 billion nucleotides (the building blocks of our genes), encoding oh about 20,000-25,000 genes. We know that at least some of these are so-called “cancer” genes – perfectly “good” genes that mutate and start to produce abnormal protein, or no protein when they should be producing some.
Most cancers are apparently caused by mutation – for instance, of a tumor-suppressor gene. Smoking is notorious for the damage it does to our DNA. But before addressing the genetic aspect of cancer in any useful way, it would be helpful to know which genes are involved.
“One project we did, with Carmit Levy of Tel Aviv University, was to identify additional genes related to myeloma (a cancer of the white blood cells)," says Tabach.
They did that by inputting a genetic sequence known to be related to myeloma and searching for it in other animal genomes. Next they followed the pattern of that gene – and found that down the evolutionary tree, the gene sequence always appeared together with a set of other genes, whose function had not been known.
Their conclusion: These other genes are related to myeloma. “The software checks the groups of genes through evolution to see whether the genes are always together,” Tabach says.
Light from dark chaos
Another breakthrough enabled by the Tabach software is the ability to find crucial genes that we, today, don’t even know exist.
Take the Krebs cycle, also called the “citric acid cycle,” a crucial part of cellular metabolism. It is crucial to all organisms that breathe oxygen. Think of it as a circular assembly line: If one worker fails at the job, the whole process doesn’t work. In short, a defect in the Krebs cycle causes disease, albeit extremely rarely; usually, Krebs’ cycle mutants simply die.
If a doctor identifies Krebs cycle disease in a person, but his Krebs cycle genes show no mutation – we assume there must be another gene that we haven’t identified that’s causing mitochondrial disease, Tabach explains. Identifying it in the 3-billion nucleotide genome is a mission so impossible that even Tom Cruise would balk – unless a logical shortcut is taken.
“When we input Krebs cycle genes into the software, we find other genes associated with the cycle somehow. It’s like guilt by association,” Tabach says.
Moreover, Krebs-cycle mutated protists that lost their mitochondria also lost all their Krebs cycle genes, he adds: “If you have genes that always appear together, then when one disappears, they all disappear – the conclusion is that the genes work together.”
Much like the Genome 10,000 project which deals with future species resurrection, Tabach stresses the unknown wonders of the genome.
“Some organisms have superpowers – for instance, resistance to cancer. Others live long lives or can survive being frozen for years on end,” says the Jerusalem professor. “Their abilities are coded in their genome.” We can take the cancer-resistant organisms and ask what traits they have in common that do not exist in other organisms, or that changed a lot from species to species, Tabach says. “We want to take all the organisms and understand the difference between organisms that have a specific superpower and the ones that don’t.”