Molecular architecture of a miRNA-regulated 3' UTR

Animal genomes contain hundreds of microRNAs (miRNAs), small regulatory RNAs that control gene expression by binding to complementary sites in target mRNAs. Some rules that govern miRNA/target interaction have been elucidated but their general applicability awaits further experimentation on a case-by-case basis. We use here an assay system in transgenic nematodes to analyze the interaction of the Caenorhabditis elegans lsy-6 miRNA with 3' UTR sequences. In contrast to many previously described assay systems used to analyze miRNA/target interactions, our assay system operates within the cellular context in which lsy-6 normally functions, a single neuron in the nervous system of C. elegans. Through extensive mutational analysis, we define features in the known and experimentally validated target of lsy-6, the 3' UTR of the cog-1 homeobox gene, that are required for a functional miRNA/target interaction. We describe that both in the context of the cog-1 3' UTR and in the context of heterologous 3' UTRs, one or more seed matches are not a reliable predictor for a functional miRNA/target interaction. We rather find that two nonsequence specific contextual features beyond miRNA target sites are critical determinants of miRNA-mediated 3' UTR regulation. The contextual features reside 3' of lsy-6 binding sites in the 3' UTR and act in a combinatorial manner; mutation of each results in limited defects in 3' UTR regulation, but a combinatorial deletion results in complete loss of 3' UTR regulation. Together with two lsy-6 sites, these two contextual features are capable of imparting regulation on a heterologous 3' UTR. Moreover, the contextual features need to be present in a specific configuration relative to miRNA binding sites and could either represent protein binding sites or provide an appropriate structural context. We conclude that a given target site resides in a 3' UTR context that evolved beyond target site complementarity to support regulation by a specific miRNA. The large number of 3' UTRs that we analyzed in this study will also be useful to computational biologists in designing the next generation of miRNA/target prediction algorithms.     

The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2′-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA–RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.     

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.     

Statistical fluctuations in processes of gene expression regulation: consideration of the problem from point of view of statistical mechanics

The regulation of gene expression is a basic problem of biology. In some cases, the gene activity is regulated by specific binding of regulatory proteins to DNA. In terms of statistical mechanics, this binding is described as the process of adsorption of ligands on the one-dimensional lattice and has a probability nature. As a random physical process, the adsorption of regulatory proteins on DNA introduces a noise to the regulation of gene activity. We derived equations, which make it possible to estimate this noise in the case of the binding of the lac repressor to the operator and showed that these estimates correspond to experimental data. Many ligands are able to bind nonspecifically to DNA. Nonspecific binding is characterized by a lesser equilibrium constant but a greater number of binding sites on the DNA, as compared with specific binding. Relations are presented, which enable one to estimate the probability of the binding of a ligand on a specific site and on nonspecific sites on DNA. The competition between specific and nonspecific binding of regulatory proteins plays a great role in the regulation of gene activity. Similar to the one-dimensional "lattice gas" of particles, ligands adsorbed on DNA produce "one-dimensional" pressure on proteins located at the termini of free regions of DNA. This pressure, an analog of osmotic pressure, may be of importance in processes leading to changes in chromatin structure and activation of gene expression.     

A complex regulatory DNA element associated with a major histocompatibility complex class I gene consists of both a silencer and an enhancer.

A novel regulatory element which contributes to the regulation of quantitative, tissue-specific differences in gene expression has been found between -771 and -676 bp upstream of the major histocompatibility complex (MHC) class I gene, PD1. Molecular dissection of this element reveals the presence of two overlapping functional activities: an enhancer and a silencer. Distinct nuclear factors bind to the overlapping enhancer and silencer DNA sequence elements within the regulatory domain. The levels of factors binding the silencer DNA sequence in different cell types are inversely related to levels of class I expression; in contrast, factors binding the enhancer DNA sequence can be detected in all cells. In cultured cell lines, inhibition of protein synthesis leads to the rapid loss of silencer complexes, with a concomitant increase in both enhancer complexes and MHC class I RNA. From these data, we conclude that a labile silencer factor competes with a constitutively expressed, stable enhancer factor for overlapping DNA-binding sites; the relative abundance of the silencer factor contributes to establishing steady-state levels of MHC class I gene expression.