The work was reported in two recent papers in Genome Research, published online on July 3 and Sept. 27.
“Our goal is to understand how regulatory information is encrypted and to learn which sequence variations contribute to medical risks,” says Andrew McCallion, Ph.D., associate professor of molecular and comparative pathobiology in the McKusick-Nathans Institute of Genetic Medicine at Hopkins.
“We give data to a computer and ‘teach it’ to distinguish between data that has no biological value versus data that has this or that biological value. It then establishes a set of rules, which allows it to look at new sets of data and apply what it learned. We’re basically sending our computers to school.”
These state-of-the-art “machine learning” techniques were developed by Michael Beer, Ph.D., assistant professor of biomedical engineering at the Johns Hopkins School of Medicine, and by Ivan Ovcharenko, Ph.D., at the National Center for Biotechnology Information. The researchers began both studies by creating “training sets” for their computers to “learn” from. These training sets were lists of DNA sequences taken from regions of the genome, called enhancers, that are known to increase the activity of particular genes in particular cells.
For the first of their studies, McCallion’s team created a training set of enhancer sequences specific to a particular region of the brain by compiling a list of 211 published sequences that had been shown, by various studies in mice and zebrafish, to be active in the development or function of that part of the brain.
For a second study, the team generated a training set through experiments of their own. They began with a purified population of mouse melanocytes, which are the skin cells that produce the pigment melanin that gives color to skin and absorbs harmful UV rays from the sun. The researchers used a technique called ChIP-seq (pronounced “chip seek”) to collect and sequence all of the pieces of DNA that were bound in those cells by special enhancer-binding proteins, generating a list of about 2,500 presumed melanocyte enhancer sequences.
Once the researchers had these two training sets for their computers, one specific to the brain and another to melanocytes, the computers were able to distinguish the features of the training sequences from the features of all other sequences in the genome, and create rules that defined one set from the other. Applying those rules to the whole genome, the computers were able to discover thousands of probable brain or melanocyte enhancer sequences that fit the features of the training sets.
In the brain study, the computers identified 40,000 probable brain enhancer sequences; for melanocytes, 7,500. Randomly testing a subset of each batch of sequences, the scientists found that more than 85 percent of the predicted enhancer sequences enhanced gene activity in the brain or in melanocytes, as expected, verifying the predictive power of their approach.
The researchers say that, in addition to identifying specific DNA sequences that control the genetic activity of a particular organ or cell type, these studies contribute to our understanding of enhancers in general and have validated an experimental approach that can be applied to many other biological questions as well.
Authors on the brain paper include Grzegorz Burzynski, Xylena Reed, Zachary Stine, Takeshi Matsui and Andrew McCallion from The Johns Hopkins University, and Leila Taher and Ivan Ovcharenko from the National Center for Biotechnology Information.
Authors on the melanocyte paper include David Gorkin, Dongwon Lee, Xylena Reed, Christopher Fletez-Brant, Seneca Bessling, Michael Beer and Andrew McCallion from The Johns Hopkins University, and Stacie Loftus and William Pavan from the National Human Genome Research Institute.
This work was supported by grants from the National Institute of Neurological Disorders and Stroke (NS062972), the National Human Genome Research Institute’s Intramural Research Program, the National Library of Medicine, the National Institute of General Medical Sciences (GM07814, GM071648), the National Science Foundation and the Searle Scholars Program.
Catherine Kolf | Newswise Science News
Cloud Formation: How Feldspar Acts as Ice Nucleus
09.12.2016 | Karlsruher Institut für Technologie
Closing the carbon loop
08.12.2016 | University of Pittsburgh
In recent years, lasers with ultrashort pulses (USP) down to the femtosecond range have become established on an industrial scale. They could advance some applications with the much-lauded “cold ablation” – if that meant they would then achieve more throughput. A new generation of process engineering that will address this issue in particular will be discussed at the “4th UKP Workshop – Ultrafast Laser Technology” in April 2017.
Even back in the 1990s, scientists were comparing materials processing with nanosecond, picosecond and femtosesecond pulses. The result was surprising:...
Have you ever wondered how you see the world? Vision is about photons of light, which are packets of energy, interacting with the atoms or molecules in what...
A multi-institutional research collaboration has created a novel approach for fabricating three-dimensional micro-optics through the shape-defined formation of porous silicon (PSi), with broad impacts in integrated optoelectronics, imaging, and photovoltaics.
Working with colleagues at Stanford and The Dow Chemical Company, researchers at the University of Illinois at Urbana-Champaign fabricated 3-D birefringent...
In experiments with magnetic atoms conducted at extremely low temperatures, scientists have demonstrated a unique phase of matter: The atoms form a new type of quantum liquid or quantum droplet state. These so called quantum droplets may preserve their form in absence of external confinement because of quantum effects. The joint team of experimental physicists from Innsbruck and theoretical physicists from Hannover report on their findings in the journal Physical Review X.
“Our Quantum droplets are in the gas phase but they still drop like a rock,” explains experimental physicist Francesca Ferlaino when talking about the...
The Max Planck Institute for Physics (MPP) is opening up a new research field. A workshop from November 21 - 22, 2016 will mark the start of activities for an innovative axion experiment. Axions are still only purely hypothetical particles. Their detection could solve two fundamental problems in particle physics: What dark matter consists of and why it has not yet been possible to directly observe a CP violation for the strong interaction.
The “MADMAX” project is the MPP’s commitment to axion research. Axions are so far only a theoretical prediction and are difficult to detect: on the one hand,...
16.11.2016 | Event News
01.11.2016 | Event News
14.10.2016 | Event News
08.12.2016 | Life Sciences
08.12.2016 | Physics and Astronomy
08.12.2016 | Materials Sciences