N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimized miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses were calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.

BackgroundBaleen whales (Mysticeti) are the largest animals on earth and their evolutionary history has been studied in detail, but some relationships still remain contentious. In particular, reconstructing the phylogenetic position of the gray whales (Eschrichtiidae) has been complicated by evolutionary processes such as gene flow and incomplete lineage sorting (ILS). Here, whole-genome sequencing data of the extant baleen whale radiation allowed us to identify transposable element (TE) insertions in order to perform phylogenomic analyses and measure germline insertion rates of TEs. Baleen whales exhibit the slowest nucleotide substitution rate among mammals, hence we additionally examined the evolutionary insertion rates of TE insertions across the genomes.ResultsIn eleven whole-genome sequences representing the extant radiation of baleen whales, we identified 91,859 CHR-SINE insertions that were used to reconstruct the phylogeny with different approaches as well as perform evolutionary network analyses and a quantification of conflicting phylogenetic signals. Our results indicate that the radiation of rorquals and gray whales might not be bifurcating. The morphologically derived gray whales are placed inside the rorqual group, as the sister-species to humpback and fin whales. Detailed investigation of TE insertion rates confirm that a mutational slow down in the whale lineage is present but less pronounced for TEs than for nucleotide substitutions.ConclusionsWhole genome sequencing based detection of TE insertions showed that the speciation processes in baleen whales represent a rapid radiation. Large genome-scale TE data sets in addition allow to understand retrotransposition rates in non-model organisms and show the potential for TE calling methods to study the evolutionary history of species.Electronic supplementary materialThe online version of this article (10.1186/s13100-018-0143-2) contains supplementary material, which is available to authorized users.

BackgroundCells have evolved quality control mechanisms to ensure protein homeostasis by detecting and degrading aberrant mRNAs and proteins. A common source of aberrant mRNAs is premature polyadenylation, which can result in non-functional protein products. Translating ribosomes that encounter poly(A) sequences are terminally stalled, followed by ribosome recycling and decay of the truncated nascent polypeptide via ribosome-associated quality control.ResultsHere, we demonstrate that the conserved RNA-binding E3 ubiquitin ligase Makorin Ring Finger Protein 1 (MKRN1) promotes ribosome stalling at poly(A) sequences during ribosome-associated quality control. We show that MKRN1 directly binds to the cytoplasmic poly(A)-binding protein (PABPC1) and associates with polysomes. MKRN1 is positioned upstream of poly(A) tails in mRNAs in a PABPC1-dependent manner. Ubiquitin remnant profiling and in vitro ubiquitylation assays uncover PABPC1 and ribosomal protein RPS10 as direct ubiquitylation substrates of MKRN1.ConclusionsWe propose that MKRN1 mediates the recognition of poly(A) tails to prevent the production of erroneous proteins from prematurely polyadenylated transcripts, thereby maintaining proteome integrity.

1Cells have evolved quality control mechanisms to ensure protein homeostasis by 2 detecting and degrading aberrant mRNAs and proteins. A common source of aberrant 3 mRNAs is premature polyadenylation, which can result in non-functional protein 4 products. Translating ribosomes encountering poly(A) sequences are terminally 5 stalled, followed by ribosome recycling and decay of the truncated nascent polypeptide 6 via the ribosome-associated quality control (RQC). Here, we demonstrate that the 7 conserved RNA-binding E3 ubiquitin ligase Makorin Ring Finger Protein 1 (MKRN1) 8 promotes ribosome stalling at poly(A) sequences during RQC. We show that MKRN1 9 is positioned upstream of A-rich stretches and poly(A) tails in mRNAs through an 10 interaction with the cytoplasmic poly(A)-binding protein (PABP). We uncover PABP, 11 ribosomal protein RPS10, and additional translational regulators as main ubiquitylation 12 substrates of MKRN1. Consequently, we propose that MKRN1 serves as a first line of 13 poly(A) recognition at the mRNA level to prevent production of erroneous proteins, thus 14 maintaining proteome integrity. 15 Keywords 16 MKRN1, ubiquitylation, RNA binding, ribosome-associated quality control, RQC, 17 poly(A), iCLIP, ubiquitin remnant profiling, translation 18 PABP-interacting motif 2 (PAM2 motif) in rat neurons (Miroci et al. 2012). 61 Nevertheless, the RNA binding specificity and functional role of MKRN1 in human cells 62 remained largely elusive. 63Here, we introduce MKRN1 as a novel factor in RQC. MKRN1 is recruited to A-rich 64 sequences in mRNAs in a PABP-dependent manner, where it acts as a first line of 65 defence against poly(A) translation. MKRN1 depletion abrogates ribosome stalling in 66 reporter assays, accompanied by reduced ubiquitylation of RQC-related proteins. We 67

Makorins are evolutionary conserved proteins that contain C 3 H-type zinc finger modules and a RING E3 ubiquitin ligase domain. In Drosophila, maternal Makorin 1 (Mkrn1) has been linked to embryonic patterning but the mechanism remained unsolved. Here, we show that Mkrn1 is essential for axis specification and pole plasm assembly by translational activation of oskar (osk). We demonstrate that Mkrn1 interacts with poly(A) binding protein (pAbp) and binds specifically to osk 3' UTR in a region adjacent to A-rich sequences. Using Drosophila S2R+ cultured cells we show that this binding site overlaps with a Bruno1 (Bru1) responsive element (BREs) that regulates osk translation. We observe increased association of the translational repressor Bru1 with osk mRNA upon depletion of Mkrn1, indicating that both proteins compete for osk binding. Consistently, reducing Bru1 dosage partially rescues viability and Osk protein level in ovaries from Mkrn1 females. We conclude that Mkrn1 controls embryonic patterning and germ cell formation by specifically activating osk translation, most likely by competing with Bru1 to bind to osk 3' UTR.

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Macrophages exert the primary cellular immune response. Pathogen components like bacterial lipopolysaccharides (LPS) stimulate macrophage migration, phagocytotic activity and cytokine expression. Previously, we identified the poly(A)+ RNA interactome of RAW 264.7 macrophages. Of the 402 RNA-binding proteins (RBPs), 32 were classified as unique in macrophages, including nineteen not reported to interact with nucleic acids before. Remarkably, P23 a HSP90 co-chaperone, also known as cytosolic prostaglandin E2 synthase (PTGES3), exhibited differential poly(A)+ RNA binding in untreated and LPS-induced macrophages. To identify mRNAs bound by P23 and to elucidate potential regulatory RBP functions in macrophages, we immunoprecipitated P23 from cytoplasmic extracts of cross-linked untreated and LPS-induced cells. RNAseq revealed that enrichment of 44 mRNAs was reduced in response to LPS. Kif15 mRNA, which encodes kinesin family member 15 (KIF15), a motor protein implicated in cytoskeletal reorganization and cell mobility was selected for further analysis. Noteworthy, phagocytic activity of LPS-induced macrophages was enhanced by P23 depletion. Specifically, in untreated RAW 264.7 macrophages, decreased P23 results in Kif15 mRNA destabilization, diminished KIF15 expression and accelerated macrophage migration. We show that the unexpected RBP function of P23 contributes to the regulation of macrophage phagocytotic activity and migration.

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing, such as RNA stability and translation. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites in the transcriptome with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present several experimental and computational innovations, that significantly improve transcriptome-wide detection of m6A sites. Based on the recently developed iCLIP2 protocol, the optimised miCLIP2 results in high-complexity libraries from less input material, which yields a more comprehensive representation of m6A sites. Next, we established a robust computational pipeline to identify true m6A sites from our miCLIP2 data. The analyses are calibrated with data from Mettl3 knockout cells to learn the characteristics of m6A deposition, including a significant number of m6A sites outside of DRACH motifs. In order to make these results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification.HighlightsmiCLIP2 produces complex libraries to map m6A RNA modificationsMettl3 KO miCLIP2 allows to identify Mettl3-dependent RNA modification sitesMachine learning predicts genuine m6A sites from human and mouse miCLIP2 data without Mettl3 KOm6A modifications frequently occur outside of DRACH motifs and associates with alternative splicing