Poly(A)-tail profiling reveals an embryonic switch in translational control

Poly(A) tails enhance the stability and translation of most eukaryotic mRNAs, but difficulties in globally measuring poly(A)-tail lengths have impeded greater understanding of poly(A)-tail function. Here, we describe poly(A)-tail length profiling by sequencing (PAL-seq) and apply it to measure tail lengths of millions of individual RNAs isolated from yeasts, cell lines, Arabidopsis leaves, mouse liver, and zebrafish and frog embryos. Poly(A)-tail lengths were conserved between orthologous mRNAs, with mRNAs encoding ribosomal proteins and other “housekeeping” proteins tending to have shorter tails. As expected, tail lengths were coupled to translational efficiency in early zebrafish and frog embryos. However, this strong coupling diminished at gastrulation and was absent in non-embryonic samples, indicating a rapid developmental switch in the nature of translational control. This switch complements an earlier switch to zygotic transcriptional control and explains why the predominant effect of microRNA-mediated deadenylation concurrently shifts from translational repression to mRNA destabilization

Function and regulation of poly(A)-tail length

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, June 2014.Cataloged from PDF version of thesis. "May 2014." Vita.Includes bibliographical references.Poly(A) tails are found at the 3' ends of nearly all eukaryotic messenger RNAs (mRNAs) and long non-coding RNAs. The presence of a poly(A) tail promotes translation and inhibits decay of an mRNA, with both effects mediated through poly(A)-binding protein. However, an understanding of the relationship between the length of a poly(A) tail and these aspects of mRNA metabolism has been limited, primarily because of the lack of a technology that provides high-resolution poly(A)-tail length measurements in a global manner. This dissertation describes a new, high-throughput-sequencing-based method (PAL-seq) that measures the tails of individual mRNA molecules by coupling a fluorescence-based readout of poly(A)-tail length with sequencing of the poly(A)-proximal region. Using PAL-seq, we have found that poly(A)-tail lengths exhibit a notably poor correlation with translational efficiency (as measured by ribosome profiling) across genes in nearly all systems we have examined. In contrast, early zebrafish and Xenopus laevis embryos display a striking correlation (Spearman R > 0.6) that disappears at gastrulation. This developmental uncoupling of tail length and translational efficiency explains the different outcomes of microRNA (miRNA)-mediated poly(A)-tail shortening in zebrafish embryos before and after gastrulation, with translational repression being the predominant effect before and mRNA destabilization after. We have also observed that poly(A)-tail lengths do not correlate positively with mRNA half-lives in mammalian cells, and that miRNAs do not promote any apparent tail shortening in this setting. Since these results could be explained by differences in deadenylation rates, we performed a kinetic analysis in which we captured newly-made mRNAs of different age ranges. The deadenylation rates that we calculated after measuring tails over time correlated strongly with mRNA half-lives (Spearman R < -0.6), reinforcing the notion that tail shortening leads to mRNA downregulation. When we repeated the timecourse with prior overexpression of a miRNA, we found that miRNAmediated tail shortening was generally modest, but of a magnitude not significantly different from that expected given the accompanying decreases in mRNA stability.by Alexander O. Subtelny.Ph. D

Predicting microRNA targeting efficacy in Drosophila

Background: MicroRNAs (miRNAs) are short regulatory RNAs that derive from hairpin precursors. Important for understanding the functional roles of miRNAs is the ability to predict the messenger RNA (mRNA) targets most responsive to each miRNA. Progress towards developing quantitative models of miRNA targeting in Drosophila and other invertebrate species has lagged behind that of mammals due to the paucity of datasets measuring the effects of miRNAs on mRNA levels. Results: We acquired datasets suitable for the quantitative study of miRNA targeting in Drosophila. Analyses of these data expanded the types of regulatory sites known to be effective in flies, expanded the mRNA regions with detectable targeting to include 5′ untranslated regions, and identified features of site context that correlate with targeting efficacy in fly cells. Updated evolutionary analyses evaluated the probability of conserved targeting for each predicted site and indicated that more than a third of the Drosophila genes are preferentially conserved targets of miRNAs. Based on these results, a quantitative model was developed to predict targeting efficacy in insects. This model performed better than existing models, and it drives the most recent version, v7, of TargetScanFly. Conclusions: Our evolutionary and functional analyses expand the known scope of miRNA targeting in flies and other insects. The existence of a quantitative model that has been developed and trained using Drosophila data will provide a valuable resource for placing miRNAs into gene regulatory networks of this important experimental organism. Keywords: Non-coding RNAs, miRNA target prediction, Post-transcriptional gene regulationNational Science Foundation (U.S.). Graduate Research Fellowship ProgramNational Institutes of Health (U.S.) (T32GM007753)National Institutes of Health (U.S.) (GM067031)National Institutes of Health (U.S.) (GM118135

MicroRNAs Cause Accelerated Decay of Short-Tailed Target mRNAs

© 2019 Elsevier Inc. MicroRNAs (miRNAs) specify the recruitment of deadenylases to mRNA targets. Despite this recruitment, we find that miRNAs have almost no effect on steady-state poly(A)-tail lengths of their targets in mouse fibroblasts, which motivates the acquisition of pre-steady-state measurements of the effects of miRNAs on tail lengths, mRNA levels, and translational efficiencies. Effects on translational efficiency are minimal compared to effects on mRNA levels, even for newly transcribed target mRNAs. Effects on target mRNA levels accumulate as the mRNA population approaches steady state, whereas effects on tail lengths peak for recently transcribed target mRNAs and then subside. Computational modeling of this phenomenon reveals that miRNAs cause not only accelerated deadenylation of their targets but also accelerated decay of short-tailed target molecules. This unanticipated effect of miRNAs largely prevents short-tailed target mRNAs from accumulating despite accelerated target deadenylation. The net result is a nearly imperceptible change to the steady-state tail-length distribution of targeted mRNAs

Predicting microRNA targeting efficacy in Drosophila

Abstract Background MicroRNAs (miRNAs) are short regulatory RNAs that derive from hairpin precursors. Important for understanding the functional roles of miRNAs is the ability to predict the messenger RNA (mRNA) targets most responsive to each miRNA. Progress towards developing quantitative models of miRNA targeting in Drosophila and other invertebrate species has lagged behind that of mammals due to the paucity of datasets measuring the effects of miRNAs on mRNA levels. Results We acquired datasets suitable for the quantitative study of miRNA targeting in Drosophila. Analyses of these data expanded the types of regulatory sites known to be effective in flies, expanded the mRNA regions with detectable targeting to include 5′ untranslated regions, and identified features of site context that correlate with targeting efficacy in fly cells. Updated evolutionary analyses evaluated the probability of conserved targeting for each predicted site and indicated that more than a third of the Drosophila genes are preferentially conserved targets of miRNAs. Based on these results, a quantitative model was developed to predict targeting efficacy in insects. This model performed better than existing models, and it drives the most recent version, v7, of TargetScanFly. Conclusions Our evolutionary and functional analyses expand the known scope of miRNA targeting in flies and other insects. The existence of a quantitative model that has been developed and trained using Drosophila data will provide a valuable resource for placing miRNAs into gene regulatory networks of this important experimental organism

Ribosomal Synthesis of <i>N</i>-Methyl Peptides

<i>N</i>-Methyl amino acids (<i>N</i>-Me AAs) are a common component of nonribosomal peptides (NRPs), a class of natural products from which many clinically important therapeutics are obtained. <i>N</i>-Me AAs confer peptides with increased conformational rigidity, membrane permeability, and protease resistance. Hence, these analogues are highly desirable building blocks in the ribosomal synthesis of unnatural peptide libraries, from which functional, NRP-like molecules may be identified. By supplementing a reconstituted Escherichia coli translation system with specifically aminoacylated total tRNA that has been chemically methylated, we have identified three <i>N-</i>Me AAs (<i>N</i>-Me Leu, <i>N</i>-Me Thr, and <i>N</i>-Me Val) that are efficiently incorporated into peptides by the ribosome. Moreover, we have demonstrated the synthesis of peptides containing up to three <i>N</i>-Me AAs, a number comparable to that found in many NRP drugs. With improved incorporation efficiency and translational fidelity, it may be possible to synthesize combinatorial libraries of peptides that contain multiple <i>N-</i>Me AAs. Such libraries could be subjected to in vitro selection methods to identify drug-like, high-affinity ligands for protein targets of interest

The Dynamics of Cytoplasmic mRNA Metabolism

© 2019 Elsevier Inc. For all but a few mRNAs, the dynamics of metabolism are unknown. Here, we developed an experimental and analytical framework for examining these dynamics for mRNAs from thousands of genes. mRNAs of mouse fibroblasts exit the nucleus with diverse intragenic and intergenic poly(A)-tail lengths. Once in the cytoplasm, they have a broad (1000-fold) range of deadenylation rate constants, which correspond to cytoplasmic lifetimes. Indeed, with few exceptions, degradation appears to occur primarily through deadenylation-linked mechanisms, with little contribution from either endonucleolytic cleavage or deadenylation-independent decapping. Most mRNA molecules degrade only after their tail lengths fall below 25 nt. Decay rate constants of short-tailed mRNAs vary broadly (1000-fold) and are larger for short-tailed mRNAs that have previously undergone more rapid deadenylation. This coupling helps clear rapidly deadenylated mRNAs, enabling the large range in deadenylation rate constants to impart a similarly large range in stabilities. mRNA decay helps determine the extent of mRNA accumulation and ultimately the amount of protein produced. The dynamics of mRNA decay—involving tail-length shortening and then decay of the mRNA body—are largely unknown. Eisen et al. use high-throughput methods to uncover these dynamics for thousands of endogenous mRNAs