More than the genes: How noncoding DNA controls cell types for vision

Noncoding DNA
Non-coding RNA (ncRNA) profiling can be used to identify parts of DNA that determine how cells in the eye develop. One such region, highlighted here in green in a developing mouse retina, directs cells to grow into rods; the red areas are for cones.

DNA contains the instructions for every component, function, and life cycle of each individual cell. The DNA library is expansive and vast, but all cells in our body use the same template. So, how is it that different cells within our bodies can use the same DNA, or genome, to make so many different cell types? How can the same instructions direct the cells of the heart, of the eye, and of every other part of our bodies?

New research from geneticists Carlos Perez-Cervantes and Linsin Smith in the lab of Ivan Moskowitz, MD, PhD, at the University of Chicago have developed a new way to identify the parts of DNA that control how one cell type is made instead of another. Their new approach helps to identify something called cis-regulatory elements, a noncoding part of the genome (described below) that determines the differences between cell types of the body.

Regulating your DNA

The “central dogma” of biology is that genes in DNA are transcribed into a messenger RNA molecule, which cells can translate into proteins and then be used for a variety of functions. How then does a cell regulate which proteins to produce in each cell type? One way that cells accomplish this is by controlling which genes are turned on in a given cell through regions of DNA called cis-regulatory elements, or “enhancers.”

Enhancers are regions of DNA away from genes that are also transcribed into RNA, but these RNA molecules will not be a template for proteins and are known as non-coding RNAs. What controls the enhancers to turn on genes in some cells and off in others? Typically, a protein known as a transcription factor binds to enhancers in the DNA. These regions will produce non-coding RNAs that can help the transcription factors to start, increase, or decrease the expression of a nearby gene.

While cis-regulatory elements can help us understand how cells regulate genes, enhancers are hard to identify. Work from the Moskowitz lab and others has focused on how the non-coding RNAs made by enhancers influence what genes are being turned on or off to make a certain cell type. “People like to think of genes as either being on or off, like a light switch, but instead, enhancers are more like a dimmer,” said Smith, a graduate student in the Committee on Genetics, Genomics, and Systems Biology. “We often don’t know how the transcription factor controls the dimmers. Looking at the non-coding RNAs can really help us to understand this process.”

Determining an eye’s fate through noncoding regions

To understand where cis-regulatory elements are and what they do, it’s important to look at them in a context where you can easily test their function. In their new study, Perez-Cervantes and Smith use genetic tools to identify and look at enhancers in rods and cones, the two major cell types that provide vision. Rods are cells which provide vision in low light scenarios, so you can see at night, for example. Conversely, cone cells provide vision in bright light, such as a sunny day outside, and also color vision. In mice and humans, cone cells make up a much smaller number of cells in the mature eye, which has made it hard to study and understand how they control genes differently from rods.

People like to think of genes as either being on or off, like a light switch, but instead, enhancers are more like a dimmer. 

Moskowitz, one of the senior authors on the new study published in the journal Development, wanted to look at how enhancers change in activity when one cell type is changed into another cell type. They decided to do this study in the mouse retina by comparing the non-coding RNA produced from enhancer regions in a rod versus a cone cell. Since the mouse retina is mostly rod cells, the researchers needed a way to study cone cells easily too. Working with collaborators Joe Corbo, MD, PhD (Washington University in St. Louis) and Connie Cepko, PhD (Harvard University) they could study a mouse with mostly cone cells by deleting a single transcription factor, Nrl. By sequencing and comparing the non-coding RNAs from retinas composed of mostly rods or mostly cones, the researchers could look for enhancers that were active in either rod or cone cells and hope to find regions that controlled one cell type to develop over the other.

Identifying noncoding RNAs was not enough. The researchers wanted to know if the non-coding RNAs they identified reflected the actual activity of the DNA regions in the retina itself. Using retinas from developing mice, they looked at whether the potential enhancers were active in either rod or cone cells. To do this, they inserted the potential enhancer in front of a marker gene that produces a protein that generates fluorescent light when imaged on a microscope. From starting with thousands of possible regions, the researchers used non-coding RNAs to find the enhancers that accurately showed cell type specific patterns: enhancers with non-coding RNAs made in rods were found to be active in rods rather than cones while those with non-coding RNAs made in cones were shown to be active in cones.

“The non-coding RNA approach is providing unexpected insight,” Moskowitz said. “The ability of this approach to predict enhancer function is providing opportunities for new studies. For example, we are currently examining how new enhancers turn on during arrhythmias in the heart and during diabetes in the pancreas. It’s a very exciting time for the lab.”

In addition to the work being done by Moskowitz and his lab looking at non-coding RNAs and enhancers with this method, this research can help scientists to use the non-coding RNA identification method for finding enhancers in many different cell types. This may help advance how we understand the development of the eyes, and many other biological systems.

“There’s a lot of things you can learn from the noncoding transcriptome,” Perez-Cervantes, a bioinformatician in the Department of Pediatrics, said. “This method really hones in on the functional drivers of cell type specific gene expression. I can see this being applied to broad areas of human genetics in the future.”