CLICK ON weeks 0 - 40 and follow along every 2 weeks of fetal development
Developmental biology - RNA|
A Scientific Dating Game: RNA Matchmakers
"We're trying to understand how proteins achieve a remarkable selectivity for certain RNAs. Usually, people have looked at this problem on a case-by-case basis. We believe, by analyzing millions of variants of RNA at one time, we will reveal fundamentals of how RNA-binding proteins recognize what they're seeking."
RNA stands for ribonucleic acid, a type of small molecule similar in structure to DNA, the genetic blueprint for building and maintaining a living organism. While DNA stays inside the nucleus of a cell, strands of RNA move freely outside of the nucleus carrying copies of DNA instructions to make proteins.
Depending on their structure, some RNAs play roles beyond being messenger. They bind to proteins and regulate how genes function (aka expression) or act as catalysts to various processes. Healthy outcomes of RNA-protein interactions rely on correct reactions - faulty interactions can produce developmental problems - some fatal. All of these encounters are poorly understood, partly due to the vast number of potential interactions.
"For even a short piece of RNA, there are about as many combinations as there are stars in our galaxy."
Predicting the Pieces
Faruck Morcos PhD, has developed powerful statistical methods to handle these immense volumes of data being transferred. His calculations can quantify a trillion possible RNA structures revealing which ones are better candidates for functional interaction. He describes his method as allowing a team of researchers to predict adjacent pieces from contextual clues.
"Using clever approximations, we can essentially solve a problem that had been computationally impossible."
RNA–protein interactions permeate biology. Transcription, translation, and splicing all hinge on the recognition of structured RNA elements by RNA-binding proteins. Models of RNA–protein interactions are generally limited to short linear motifs and structures because of the vast sequence sampling required to access longer elements. Here, we develop an integrated approach that calculates global pairwise interaction scores from in vitro selection and high-throughput sequencing. We examine four RNA-binding proteins of phage, viral, and human origin. Our approach reveals regulatory motifs, discriminates between regulated and non-regulated RNAs within their native genomic context, and correctly predicts the consequence of mutational events on binding activity. We design binding elements that improve binding activity in cells and infer mutational pathways that reveal permissive versus disruptive evolutionary trajectories between regulated motifs. These coupling landscapes are broadly applicable for the discovery and characterization of protein–RNA recognition at single nucleotide resolution.
Authors: Qin Zhou, Nikesh Kunder, José Alberto De la Paz, Alexandra E. Lasley, Vandita D. Bhat, Faruck Morcos and Zachary T. Campbell.
Graduate molecular biology student Qin Zhou MS'16 is the lead author of the paper. Other authors include graduate students Vandita Bhat, Alexa Lasley and Nikesh Kunder, and undergraduate José Alberto De La Paz.
The research was funded by the National Institutes of Health and startup funds provided by the University.
Return to top of page
Sagittarius Star Cloud in the constellation Sagittarius, the telescopic field of view contains many small, dense clouds of dust and nebulae toward the center of the Milky Way. Image Credit: Roberto Colombari, NASA.