Though scientists have begun to appreciate how alternative splicing adds a layer of complexity to brain processes that enable us to think and learn, exactly how alternative splicing is regulated during these processes -- and in some cases is uncontrolled (or dysregulated) to cause disease -- has remained elusive. The map provides the first comprehensive understanding of how alternative splicing works throughout the genome. The results have implications for a better understanding of such brain functions as learning and memory, neurological diseases and cancer biology.
"This finding is a significant advance in our understanding of splicing, and it suggests that it will be possible to understand how different splicing factors weave together to regulate complex patterns of genes, which in turn is relevant to generating complexity of function," says senior author Robert Darnell, professor and head of the Laboratory of Molecular Neuro-Oncology at Rockefeller and investigator at HHMI.
RNA splicing is the process by which the initial RNA copy of a gene, known as pre-mRNA, is pieced together to produce a mature mRNA that codes for cellular proteins. In alternative splicing, different pieces of this pre-mRNA, called exons, are stitched together to produce different mRNAs, and thus different proteins. The exon can be spliced in or out in a binary, computer-like fashion. By regulating alternative splicing cells can produce a wide variety of proteins from a finite number of genes. This capacity is believed to be critical to the complex workings of human cells such as those found in the neurons of the brain.
The researchers focused on a brain protein that binds to RNA called Nova. Darnell and his colleagues first identified Nova in 1993 as the target protein in a neurodegenerative disease termed POMA (paraneoplastic opsoclonus-myoclonus ataxia) that is also associated with several types of cancers. Since then the laboratory has focused on identifying RNA sequences -- and in particular, identifying alternatively spliced pre-mRNAs -- that Nova binds to. In the last three years, in work published in Science and Nature Genetics, the Darnell lab identified over 50 Nova-regulated alternatively spliced exons, using new techniques developed at Rockefeller specifically to find Nova RNA targets, and validating their results in "knockout" mice that were missing Nova.
In the new study, Darnell, with co-first authors Jernej Ule and Giovanni Stefani, took these 50 RNA transcripts and searched them for clusters of sequences they had previously identified as Nova binding sites through biochemical and, in collaboration with former Rockefeller University structural biologist Stephen Burley, X-ray crystallographic studies. Unexpectedly, this search revealed four discrete peaks where the binding clusters locate. Furthermore, the location of the peaks correlated with Nova's action on regulating whether the alternative exon is spliced in or out.
The researchers tested whether this RNA map was valid by asking whether it could predict how Nova would act on RNA transcripts that had yet to be discovered. They took a bioinformatics approach, using a database of all alternatively spliced RNAs compiled by co-authors Terry Gaasterland and Bahar Taneri, to search for new genes that had clusters of Nova binding sites. Of the 50 or so transcripts with such clusters, 30 turned out to be alternatively spliced in a Nova-dependent way. Of those, all 30 fit the rules of the RNA map.
"In other words, every transcript that we could predict as a Nova-regulated alternatively spliced RNA fit the prediction of this map," says Darnell. "Half of them were inhibited by Nova and half were enhanced in their exon use by Nova, and every one very cleanly fit the pattern."
The researchers also simulated alternative splicing in the test tube, mixing purified RNA and a splicing extract. When purified Nova was added to the extracts, it bound to the mRNA clusters, altering the outcome of the how the splicing machinery was able to assemble in a manner that again conformed to the predictions of the RNA map. In one case Nova blocked specific components of the splicing machinery, in another it enhanced the ability of this machinery to assemble the right way and use an alternatively spliced site that is otherwise poorly utilized.
By offering a global understanding of how alternative splicing works across the genome, the map has implications for the treatment of a growing list of human neurologic diseases in which RNA regulation, and particularly RNA splicing, has been implicated as the primary cause, including certain types of cancer and a number of brain and muscle disorders.
"Given that the complexity of the brain is orders and orders of magnitude more complex than the number of genes we have, one of the intriguing things about alternative splicing is that a relatively small number of regulatory splicing factors acting in concert on a single transcript can potentially generate a large number of different protein variants," says Darnell.
"There is a converging set of observations indicating that as neurologic diseases are better understood, alternative splicing is going to play an important role in generation of disease and therefore an important role in normal generation of cognitive function," he adds. "Our new work lays out an approach to developing a global understanding of how alternative splicing is regulated by one disease-associated protein, Nova, offering a route by which scientists may now be able to approach a number of diseases with a fresh start."
Finally, Darnell's work has shown that Nova is expressed in certain types of cancer cells. Cancer cells operate by dysregulating gene expression, and Darnell believes that further studies are needed to determine whether Nova is a cause of dysregulated gene expression at the level of alternative splicing in a cancer cell.
"The right splicing factor in the wrong environment could wreck havoc and change the quality of proteins in a tumor cell," he says.
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