Capturing how RNA polymerase enzymes kick off transcription

On scales too small for our eyes to see, the business of life happens through the making of proteins, which impart to our cells both structure and function. Cellular proteins get their marching orders from genetic instructions encoded in DNA, whose sequences are first copied and made into RNA in a multi-step process called transcription.

Research collaboration at Colorado State University specializes in high-resolution fluorescence microscopy and computational modeling to visualize and describe such stuff-of-life processes in exquisite detail, in real-time, at the level of single genes. Now, scientists led by postdoctoral researcher Linda Forero-Quintero have, for the first time, observed early RNA transcription dynamics by recording where, when and how RNA polymerase enzymes kick off transcription by binding to a DNA sequence.

The breakthrough technology has countless possible outshoots; these include sharpening understanding of basic biological processes, to unveiling the genetic underpinnings of certain diseases.

"This is the first time someone has looked at RNA polymerase phosphorylation dynamics in a single-copy gene," said Forero, who is a postdoctoral researcher co-advised by Tim Stasevich, Monfort Professor and associate professor in biochemistry, and Brian Munsky, associate professor in chemical and biological engineering. In the past, such early transcription activity could only be visualized using gene arrays, which are artificial structures composed of hundreds of copies of a gene and not commonly found in the cell nucleus.

Stasevich and Munsky lead a collaboration funded by the W.M. Keck Foundation and the National Institute of General Medical Sciences (through two Maximizing Investigators' Research Awards) that's seeking to unveil and quantify real-time genetic expression in living, single cells. Forero, who works in both labs under the auspices of the collaboration, had previously studied proteins and transporters in cell membranes associated with neurological conditions.

Early transcription activity

Forero et al. designed a method using an established mammalian cell line, engineered fluorescent antibody fragments, and a custom super-resolution microscope to capture the process of early transcription in vivid colors: blue, green, and red. More specifically, they observed the start of the transcription cycle that happens when the RNA polymerase II (RNAP2) transcription enzyme becomes phosphorylated or decorated with phosphate groups, on its amino acid tail.

"The interdisciplinary science here is a fantastic blending of new experimental capabilities and a new approach for mechanistic computational modeling of single-cell dynamics, both of which are very novel in their respective fields," said Munsky, who supervises the computational aspects of the collaboration.

In the lab, the researchers loaded their antibody fragments into an established mammalian cell line containing a reporter gene that when transcribed, is lit up by a fluorescently tagged protein. The antibody fragments, which Stasevich helped develop several years ago, are tagged with fluorescent molecules that light up their specific targets in the RNAP2 tail. Using these tagging technologies together, the researchers could distinguish three distinct steps in the transcription cycle, marked by different colors. The images obtained with this system translate into fluorescent intensity fluctuation. The researchers then used those signals to interpret the spatiotemporal organization of RNAP2 phosphorylation throughout the transcription cycle at a single-copy gene.

New information via a computational model

Munsky's team led by graduate student William Raymond took Forero and Stasevich's microscopy data and translated it into a computational model based on stochastic differential equations. By fitting this statistical model to reproduce all the experimental results, the computational team then extended their analyses to glean new mechanistic and quantitative information about the different molecules and their states through the transcription process.

For example, they estimated how many individual RNA polymerase molecules collect to form transient clusters in the region of the DNA's promoter, how long these clusters persist, and how, when, and where the polymerases distribute themselves along with the DNA. They found, for example, that each burst of transcription activity produces a cluster of between five and 40 RNA polymerases to form around the promoter region of the gene, of which 46% eventually succeed to transcribe RNA. They also found that each RNA takes approximately five minutes to be fully transcribed and processed prior to release.

Forero says the technology has far-reaching potential, especially combined with newer technologies like CRISPR, in which specific genes can be singled out and manipulated. Choosing a certain gene of interest, say one implicated in a disease, and applying the CSU researchers' real-time readout of the transcription cycle, could then allow researchers to watch disease processes happening at the activity level of single genes.

"The ability to resolve the spatial and temporal dynamics of the transcription cycle, in one gene, is the most exciting aspect of this work," Forero said.

The first three years of survey data use observations of 226 million galaxies over 1/8 of the sky

In 29 new academic papers, the Dark Energy Survey examines the largest-ever maps of galaxy distribution and shapes, extending more than 7 billion light-years across the Universe. The extraordinarily precise analysis, which includes data from the survey's first three years, contributes to the most powerful test of the current best model of the Universe, the standard cosmological model. However, hints remain from earlier DES data, and other experiments that matter in the Universe today are a few percent less clumpy than predicted.

New results from the Dark Energy Survey (DES) use the largest-ever sample of galaxies observed over nearly one-eighth of the sky to produce the most precise measurements to date of the Universe's composition and growth. 

DES images of the night sky using the 570-megapixel Dark Energy Camera on the National Science Foundation's Víctor M. Blanco 4-meter Telescope at Cerro Tololo Inter-American Observatory (CTIO) in Chile, a Program of NSF's NOIRLab. One of the most powerful digital cameras in the world, the Dark Energy Camera was designed specifically for DES. It was funded by the Department of Energy (DOE) and was built and tested at DOE's Fermilab.

Over the course of six years, from 2013 to 2019, DES used 30% of the time on the Blanco Telescope and surveyed 5000 square degrees -- almost one-eighth of the entire sky -- in 758 nights of observation, cataloging hundreds of millions of objects. The results announced today draw on data from the first three years -- 226 million galaxies observed over 345 nights -- to create the largest and most precise maps yet of the distribution of galaxies in the Universe at relatively recent epochs. The DES data were processed at the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign.

"NOIRLab is a proud host for and member of the DES collaboration," said Steve Heathcote, CTIO Associate Director. "Both during and after the survey, the Dark Energy Camera has been a popular choice for community and Chilean astronomers."

At present, the Dark Energy Camera is used for programs covering a huge range of science including cosmology. The Dark Energy Camera science archive, including DES Data Release 2 on which these results are based, is curated by the Community Science and Data Center (CSDC), a Program of NSF's NOIRLab. CSDC provides software systems, user services, and development initiatives to connect and support the scientific missions of NOIRLab's telescopes, including the Blanco telescope at CTIO.

Since DES studied nearby galaxies as well as those billions of light-years away, its maps provide both a snapshot of the current large-scale structure of the Universe and a view of how that structure has evolved over the past 7 billion years. 

Ordinary matter makes up only about 5% of the Universe. Dark energy, which cosmologists hypothesize drives the accelerating expansion of the Universe by counteracting the force of gravity, accounts for about 70%. The last 25% is dark matter, whose gravitational influence binds galaxies together. Both dark matter and dark energy remain invisible. DES seeks to illuminate their nature by studying how the competition between them shapes the large-scale structure of the Universe over cosmic time.

To quantify the distribution of dark matter and the effect of dark energy, DES relied mainly on two phenomena. First, on large scales galaxies are not distributed randomly throughout space but rather form a weblike structure that is due to the gravity of the dark matter. DES measured how this cosmic web has evolved over the history of the Universe. The galaxy clustering that forms the cosmic web, in turn, revealed regions with a higher density of dark matter.

Second, DES detected the signature of dark matter through weak gravitational lensing. As light from a distant galaxy travels through space, the gravity of both ordinary and dark matter in the foreground can bend its path, as if through a lens, resulting in a distorted image of the galaxy as seen from Earth. By studying how the apparent shapes of distant galaxies are aligned with each other and with the positions of nearby galaxies along the line of sight, DES scientists were able to infer the clumpiness of the dark matter in the Universe.

To test cosmologists' current model of the Universe, DES scientists compared their results with measurements from the European Space Agency's orbiting Planck observatory. Planck used light known as the cosmic microwave background to peer back to the early Universe, just 400,000 years after the Big Bang. The Planck data give a precise view of the Universe 13 billion years ago, and the standard cosmological model predicts how the dark matter should evolve to the present.

Combined with earlier results DES provides the most powerful test of the current best model of the Universe to date, and the results are consistent with the predictions of the standard model of cosmology. However, hints remain from DES and several previous galaxy surveys that the Universe today is a few percent less clumpy than predicted.

Ten regions of the sky were chosen as "deep fields" that the Dark Energy Camera imaged repeatedly throughout the survey. Stacking those images together allowed the scientists to glimpse more distant galaxies. The team then used the redshift information from the deep fields to calibrate the rest of the survey region. This and other advancements in measurements and modeling, coupled with a threefold increase in data compared to the first year, enabled the team to pin down the density and clumpiness of the Universe with unprecedented precision.

DES concluded its observations of the night sky in 2019. With the experience gained from analyzing the first half of the data, the team is now prepared to handle the complete dataset. The final DES analysis is expected to paint an even more precise picture of the dark matter and dark energy in the Universe.

The DES collaboration consists of over 400 scientists from 25 institutions in seven countries.

"The collaboration is remarkably young. It's tilted strongly in the direction of postdocs and graduate students who are doing a huge amount of this work," said DES Director and spokesperson Rich Kron, who is a Fermilab and University of Chicago scientist. "That's really gratifying. A new generation of cosmologists is being trained using the Dark Energy Survey."

The methods developed by the team have paved the way for future sky surveys such as the Rubin Observatory Legacy Survey of Space and Time. "DES shows that the era of big survey data has well and truly begun," notes Chris Davis, NSF's Program Director for NOIRLab. "DES on NSF's Blanco telescope has set the scene for the remarkable discoveries to come with Rubin Observatory over the coming decade."