Computational Biology, Molecular Biology
Janelia Research Campus
Dr. Rivas is a principal scientist at the Janelia Farm Research Campus.
Elena Rivas uses probabilistic modeling to make technological contributions to improving the analysis of biological sequences.
While scientists often talk about genetics as the language of DNA, computational biologist Elena Rivas has made the metaphor the basis of her life in the lab. Rivas searches bacterial genomes for undiscovered genes using a kind of computer method first developed by linguists to try to describe language in formal mathematical terms. Beyond modeling the complexities of human grammar, the method has also proved useful for the identification of certain structural genes that have been overlooked by previous gene-hunting tools.
The genes Rivas seeks churn out noncoding RNA, RNA molecules that do not make protein. In the world of genes and proteins, RNA is a scientific Cinderella story. Once thought to be strictly a slavish transmitter of information, fetching instructions from the double-helix manual and delivering them to the protein-making machinery to make proteins, discoveries in the last 20 years have shown that certain classes of RNA can perform their own cellular feats. The most celebrated recent example, the powerful phenomenon of RNA silencing—in which short bits of RNA can reduce or block specific gene activity—has raced from the first demonstration in worms to clinical trials for the treatment of eye disease and respiratory infections in less than 10 years.
Other important types of RNA may be eluding scientists, who, until recently, discovered and studied new kinds of RNA exclusively in the laboratory. Rivas plugs the information revealed in those kinds of studies into her computer programs to find other unknown RNA lurking in genomes. While she has so far focused on the humble bacteria, Rivas expects to sharpen the accuracy of her method at Janelia so that it can be applied to the more complicated genomes of multicellular creatures, such as mice, rats, and people.
Rivas trained and worked as a particle physicist in the United States and her native Spain. About 10 years ago, while she was job hunting and uninspired by the possibilities in physics, she applied to medical school. To fill up the year between being accepted and the start of class, she took a job in the lab of Sean Eddy at Washington University in St. Louis. Eventually, she abandoned her plans for medical school.
Fundamental problems in molecular biology can be solved with the same logic she applied to quantum physics, Rivas said. The shared strategy requires a computational approach to break down the problem into smaller pieces, order them according to importance, and plug in all the rules—in this case, those of RNA folding.
RNA is transcribed from its genes as a single strand of nucleic acid units. Like the subatomic boson particles Rivas once studied, these nucleic acids don't like to be alone. The compulsion for certain bases to pair up into characteristic structures helps Rivas find hidden RNA. The RNA strand is dragged and crimped into hairpin folds known as "stem loops" when a short sequence of bases finds a reflected string of mates nearby. One of the algorithms Rivas uses to search for those short mirror-image complementary sequences started its career describing a linguisitic palindrome, a word or a verse that reads the same forward and backward.
The program Rivas has developed, QRNA, also leverages the evolutionary power of comparative genome sequences to amplify the notoriously weak signal of noncoding RNA. In other work that echoes both the operational aspects of quantum field theory and another type of grammar hierarchy, she depicted another kind of RNA structure known as a pseudoknot. Here, a stray piece of the RNA strand threads along the unpaired bases in the eye of a hairpin turn. "Along with identifying new RNA genes, we'd like to create a bunch of tools to catalogue them the way that others have identified and catalogued protein-coding genes."
At Janelia, she anticipates finding new applications for her techniques, such as with the RNA in neurons. "I don't know neurobiology," she said. "That's a little scary."
Rivas already has the research-centered work life that other researchers, such as lab head Eddy, who is now both her husband and colleague, are seeking at Janelia. "My major reason [for going to Janelia] is being able to be in contact with people that have different problems in mind and that have different ways of reasoning," she said. "It can be a refreshing change. It was that way almost 10 years ago when I switched to computational biology, and I'm sure it will be refreshing now whether or not it materializes in a new shift of research direction for me."