Gladstone NOW: The Campaign Join Us on the Journey✕
Scientists at the Gladstone Institutes have invented a new way to read and interpret the human genome. The computational method, called TargetFinder, can predict where non-coding DNA—the DNA that does not code for proteins—interacts with genes. This technology helps researchers connect mutations in the so-called genomic “dark matter” with the genes they affect, potentially revealing new therapeutic targets for genetic disorders.
In the study, published in Nature Genetics, the researchers looked at fragments of non-coding DNA called enhancers. Enhancers act like an instruction manual for a gene, dictating when and where a gene is turned on. Genes can be separated from their enhancers by long stretches of DNA that contain many other genes.
“Most genetic mutations that are associated with disease occur in enhancers, making them an incredibly important area of study,” said senior author Katherine Pollard, PhD, a senior investigator at the Gladstone Institutes. “Before now, we struggled to understand how enhancers find the distant genes they act upon.”
Scientists originally believed that enhancers mostly affect the gene nearest to them. However, the new study revealed that, on a strand of DNA, enhancers can be millions of letters away from the gene they influence, skipping over the genes in between. When an enhancer is far away from the gene it affects, the two connect by forming a three-dimensional loop, like a bow on the genome.
Using machine learning technology, the researchers analyzed hundreds of existing datasets from six different cell types to look for patterns in the genome that identify where a gene and enhancer interact. They discovered several patterns that exist on the loops that connect enhancers to genes. This pattern accurately predicted whether a gene-enhancer interaction occurred 85 percent of the time.
“It’s remarkable that we can predict complex three-dimensional interactions from relatively simple data,” said first author Sean Whalen, PhD, a biostatistician at Gladstone. “No one had looked at the information stored on loops before, and we were surprised to discover how important that information is.”
Performing experiments in the lab to identify all of these gene-enhancer interactions can take millions of dollars and years of research. The new computational approach is a much cheaper and less time-consuming way to identify gene-enhancer connections in the genome. The technology also provides insight into how DNA loops form and how they might break in disease. The scientists have offered all of the code and data from TargetFinder online for free.
“Our ability to predict the gene targets of enhancers so accurately enables us to link mutations in enhancers to the genes they target,” said Pollard. “Having that link is the first step towards using these connections to treat diseases.
Gladstone scientists are moving quickly to respond to the coronavirus outbreak. Help us end this pandemic.
A new study in Nature Genetics expands our understanding of immune regulation and autoimmunity—with findings that could also be used in the development of cancer immunotherapies.
News Release Autoimmune Diseases Cancer Genomic Immunology Parker Institute for Cancer Immunotherapy Marson Lab Pollard Lab Ye Lab AI CRISPR/Gene EditingA team of researchers from Gladstone Institutes and UC San Francisco combined high-throughput experiments and machine learning to analyze more than 100,000 sequences in human brain cells.
News Release Research (Publication) Data Science and Biotechnology Pollard Lab AI Big Data Developmental Biology Disease Models Genomics Human GeneticsA search for the brightest minds in cancer and AI led Hope and Sanjit Biswas to give in their own backyard.
Philanthropy Donor Stories Cancer Biswas Center for Transformative Computational Cancer Biology Data Science and Biotechnology Pollard Lab AI Big Data