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      Crosstalk between codon optimality and cis-regulatory elements dictates mRNA stability

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          Abstract

          Background

          The regulation of messenger RNA (mRNA) stability has a profound impact on gene expression dynamics during embryogenesis. For example, in animals, maternally deposited mRNAs are degraded after fertilization to enable new developmental trajectories. Regulatory sequences in 3′ untranslated regions (3′UTRs) have long been considered the central determinants of mRNA stability. However, recent work indicates that the coding sequence also possesses regulatory information. Specifically, translation in cis impacts mRNA stability in a codon-dependent manner. However, the strength of this mechanism during embryogenesis, as well as its relationship with other known regulatory elements, such as microRNA, remains unclear.

          Results

          Here, we show that codon composition is a major predictor of mRNA stability in the early embryo. We show that this mechanism works in combination with other cis-regulatory elements to dictate mRNA stability in zebrafish and Xenopus embryos as well as in mouse and human cells. Furthermore, we show that microRNA targeting efficacy can be affected by substantial enrichment of optimal (stabilizing) or non-optimal (destabilizing) codons. Lastly, we find that one microRNA, miR-430, antagonizes the stabilizing effect of optimal codons during early embryogenesis in zebrafish.

          Conclusions

          By integrating the contributions of different regulatory mechanisms, our work provides a framework for understanding how combinatorial control of mRNA stability shapes the gene expression landscape.

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          Most cited references64

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                arb@stowers.org
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                5 January 2021
                5 January 2021
                2021
                : 22
                : 14
                Affiliations
                [1 ]GRID grid.250820.d, ISNI 0000 0000 9420 1591, Stowers Institute for Medical Research, ; 1000 E 50th St, Kansas City, MO 64110 USA
                [2 ]Present Address: National Laboratory of Genomics for Biodiversity (LANGEBIO), Unit of Advanced Genomics, 36824 Irapuato, Mexico
                [3 ]GRID grid.9486.3, ISNI 0000 0001 2159 0001, Present Address: Instituto de Fisiología Celular, , Universidad Nacional Autónoma de México, ; 04510 México City, Mexico
                [4 ]GRID grid.412016.0, ISNI 0000 0001 2177 6375, Department of Molecular and Integrative Physiology, , University of Kansas Medical Center, ; 3901 Rainbow Blvd, Kansas City, KS 66160 USA
                Author information
                http://orcid.org/0000-0002-2251-5174
                Article
                2251
                10.1186/s13059-020-02251-5
                7783504
                33402205
                a281011a-bee1-497b-b61e-73ceeab5903c
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 28 May 2020
                : 17 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007795, Stowers Institute for Medical Research;
                Funded by: Pew Charitable Trusts (US)
                Award ID: Pew Innovation Fund
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM136849
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Genetics
                codon optimality,microrna,mir-430,m6a,zebrafish,xenopus
                Genetics
                codon optimality, microrna, mir-430, m6a, zebrafish, xenopus

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