TRIM7 catalyzes the ubiquitination of multiple substrates with unrelated biological functions. This cross-reactivity is at odds with the specificity usually displayed by enzymes, including ubiquitin ligases. Here we show that TRIM7′s extreme substrate promiscuity is due to a highly unusual binding mechanism, in which the PRYSPRY domain captures any ligand with a C-terminal helix that terminates in a hydrophobic residue followed by a glutamine. Many of the non-structural proteins found in RNA viruses contain C-terminal glutamines as a result of polyprotein cleavage by 3C protease. This viral processing strategy generates novel substrates for TRIM7 and explains its ability to inhibit Coxsackie virus and norovirus replication. In addition to viral proteins, cellular proteins such as glycogenin have evolved C-termini that make them a TRIM7 substrate. The ‘helix-ΦQ’ degron motif recognized by TRIM7 is reminiscent of the N-end degron system and is found in ~1% of cellular proteins. These features, together with TRIM7′s restricted tissue expression and lack of immune regulation, suggest that viral restriction may not be its physiological function.

Translation of aberrant mRNAs can cause ribosomes to stall, leading to collisions with trailing ribosomes. Collided ribosomes are specifically recognised by ZNF598 to initiate protein and mRNA quality control pathways. Here we found using quantitative proteomics of collided ribosomes that EDF1 is a ZNF598-independent sensor of ribosome collisions. EDF1 stabilises GIGYF2 at collisions to inhibit translation initiation in cis via 4EHP. The GIGYF2 axis acts independently of the ZNF598 axis, but each pathway's output is more pronounced without the other. We propose that the widely conserved and highly abundant EDF1 monitors the transcriptome for excessive ribosome density, then triggers a GIGYF2-mediated response to locally and temporarily reduce ribosome loading. Only when collisions persist is translation abandoned to initiate ZNF598-dependent quality control. This tiered response to ribosome collisions would allow cells to dynamically tune translation rates while ensuring fidelity of the resulting protein products.

Understanding the molecular basis of adaptation to the environment is a central question in evolutionary biology, yet linking detected signatures of positive selection to molecular mechanisms remains challenging. Here we demonstrate that combining sequence-based phylogenetic methods with structural information assists in making such mechanistic interpretations on a genomic scale. Our integrative analysis shows that positively selected sites tend to colocalize on protein structures and that positively selected clusters are found in functionally important regions of proteins, indicating that positive selection can contravene the well-known principle of evolutionary conservation of functionally important regions. This unexpected finding, along with our discovery that positive selection acts on structural clusters, opens previously unexplored strategies for the development of better models of protein evolution. Remarkably, proteins where we detect the strongest evidence of clustering belong to just two functional groups: Components of immune response and metabolic enzymes. This gives a coherent picture of pathogens and xenobiotics as important drivers of adaptive evolution of mammals.

The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab-or protocol-specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein-coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation or recombination among viral lineages. We suggest how samples can be screened and problematic variants removed, and we plan to regularly inform the scientific community with our updated results as more SARS-CoV-2 genome sequences are shared (https://virological.org/t/issues-with-sars-cov-2-sequencing-data/473 and https://virological.org/t/masking-strategies-for-sars-cov-2-alignments/480). We also develop tools for comparing and visualizing differences among very large phylogenies and we show that consistent clade- and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.

Class F receptors are considered valuable therapeutic targets due to their role in human disease, but structural changes accompanying receptor activation remain unexplored. Employing population and cancer genomics data, structural analyses, molecular dynamics simulations, resonance energy transfer-based approaches and mutagenesis, we identify a conserved basic amino acid in TM6 in Class F receptors that acts as a molecular switch to mediate receptor activation. Across all tested Class F receptors (FZD4,5,6,7, SMO), mutation of the molecular switch confers an increased potency of agonists by stabilizing an active conformation as assessed by engineered mini G proteins as conformational sensors. Disruption of the switch abrogates the functional interaction between FZDs and the phosphoprotein Dishevelled, supporting conformational selection as a prerequisite for functional selectivity. Our studies reveal the molecular basis of a common activation mechanism conserved in all Class F receptors, which facilitates assay development and future discovery of Class F receptor-targeting drugs.

Understanding the molecular basis of adaptation to the environment is a central question in evolutionary biology, yet linking detected signatures of positive selection to molecular mechanisms remains challenging. Here we demonstrate that combining sequence-based phylogenetic methods with structural information assists in making such mechanistic interpretations on a genomic scale. Our integrative analysis shows that positively selected sites tend to co-localise on protein structures and that positively selected clusters are found in functionally important regions of proteins, indicating that positive selection can contravene the well-known principle of evolutionary conservation of functionally important regions. This unexpected finding, along with our discovery that positive selection acts on structural clusters, opens new strategies for the development of better models of protein evolution. Remarkably, proteins where we detect the strongest evidence of clustering belong to just two functional groups: components of immune response and metabolic enzymes. This gives a coherent picture of immune response and xenobiotic metabolism as the drivers of adaptive evolution of mammals.

The genetic basis of most human disease cannot be explained by common variants. One solution to this ‘missing heritability problem’ may be rare missense variants, which are individually scarce but collectively abundant. However, the phenotypic impact of rare variants is under-appreciated as gene function is normally studied in the context of a single ‘wild-type’ sequence. Here, we explore the impact of naturally occurring missense variants in the human population on the cytosolic antibody receptor TRIM21, using volunteer cells with variant haplotypes, CRISPR gene editing and functional reconstitution. In combination with data from a panel of computational predictors, the results suggest that protein robustness and purifying selection ensure that function is remarkably well-maintained despite coding variation.

The widespread application of sequencing technologies, used for example to obtain data from healthy individuals or patient cohorts, has led to the identification of numerous mutations, the effect of which remains largely unclear. Therefore, developing approaches allowing accurate in‐silico prediction of mutation effects is becoming increasingly important. In their recent study, Beltrao and colleagues (Wagih et al, 2018) describe an integrative approach for determining the effects of mutations from the perspective of protein structure, conservation and transcription factor binding. This allows for predicting the mechanisms underlying the most impactful variants rather than just identifying these variants. Developing approaches for in‐silico prediction of mutation effects is important for interpreting sequence variants. In their recent work, Beltrao et al (Wagih et al, 2018) describe an integrative approach for determining the effects of mutations from the perspective of protein structure, conservation and transcription factor binding.

Significance Viral-based delivery vectors have huge potential in the treatment of human disease. Adenoviral vectors specifically have proven highly efficacious in delivering corrected genes, as part of gene therapy, and vaccine epitopes for treating cancer and infectious disease. A principal obstacle to their widespread use is that antibodies potently neutralize them, limiting treatment to naïve patients. How antibodies block adenovirus-based transduction has long remained a mystery because, even though they prevent transgene expression, they do not prevent transgene delivery into target tissue. Here we show that the cytosolic antibody receptor TRIM21 is responsible for intercepting adenoviral gene therapy and vaccine vectors and neutralizing them. Gene KO of TRIM21 or a single-antibody mutation that prevents interaction is sufficient to restore transgene expression.

The poly(A) tail, co-transcriptionally added to most eukaryotic RNAs, plays an important role in post-transcriptional regulation through modulating mRNA stability and translational efficiency. The length of the poly(A) tail is dynamic, decreasing or increasing in response to various stimuli through the action of enzymatic complexes, and changes in tail length are exploited in regulatory pathways implicated in various biological processes. To date, assessment of poly(A) tail length has mostly relied on protocols targeting only a few transcripts. We present PASP (‘ p oly( A ) tail s equencing p rotocol’), a whole-transcriptome approach to measure tail lengths — including a computational pipeline implementing all necessary analyses. PASP uses direct Illumina sequencing of cDNA fragments obtained through G-tailing of poly(A)-selected mRNA followed by fragmentation and reverse transcription. Analysis of reads corresponding to spike-in poly(A) tracts of known length indicated that mean tail lengths can be confidently measured, given sufficient coverage. We further explored the utility of our approach by comparing tail lengths estimated from wild type and Δ ccr4-1/pan2 mutant yeasts. The yeast whole-transcriptome tail length distributions showed high consistency between biological replicates, and the expected upward shift in tail lengths in the mutant samples was detected. This suggests that PASP is suitable for the assessment of global polyadenylation status in yeast. The correlation of per-transcript mean tail lengths between biological and technical replicates was low (higher between mutant samples). Both, however, reached high values after filtering for transcripts with greater coverage. We also compare our results with those of other methods. We identify a number of improvements that could be used in future PASP experiments and, based on our results, believe that direct sequencing of poly(A) tails can become the method of choice for studying polyadenylation using the Illumina platform

Human protein-protein interaction networks are critical to understanding cell biology and interpreting genetic and genomic data, but are challenging to produce in individual large-scale experiments. We describe a general computational framework that through data integration and quality control provides a scored human protein-protein interaction network (InWeb_IM). Juxtaposed with five comparable resources, InWeb_IM has 2.8 times more interactions (~585K) and a superior functional signal showing that the added interactions reflect real cellular biology. InWeb_IM is a versatile resource for accurate and cost-efficient functional interpretation of massive genomic datasets illustrated by annotating candidate genes from >4,700 cancer genomes and genes involved in neuropsychiatric diseases.

In mammals, DNA methylation profiles vary substantially between tissues. Recent genome-scale studies report that blood displays a highly distinctive methylomic profile from other somatic tissues. In this study, we sought to understand why blood DNA methylation state is so different to the one found in other tissues. We found that whole blood contains approximately twice as many tissue-specific differentially methylated positions (tDMPs) than any other somatic tissue examined. Furthermore, a large subset of blood tDMPs showed much lower levels of methylation than tDMPs for other tissues. Surprisingly, these regions of low methylation in blood show no difference regarding genomic location, genomic content, evolutionary rates, or histone marks when compared to other tDMPs. Our results reveal why blood displays a distinctive methylation profile relative to other somatic tissues. In the future, it will be important to study how these blood specific tDMPs are mechanistically involved in blood-specific functions.

, (2014); 345 Science et al. Lu Chen progenitors Transcriptional diversity during lineage commitment of human blood This copy is for your personal, non-commercial use only. clicking here. colleagues, clients, or customers by , you can order high-quality copies for your If you wish to distribute this article to others here. following the guidelines can be obtained by Permission to republish or repurpose articles or portions of articles ): September 25, 2014 www.sciencemag.org (this information is current as of The following resources related to this article are available online at http://www.sciencemag.org/content/345/6204/1251033.full.html version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag.org/content/suppl/2014/09/24/345.6204.1251033.DC1.html can be found at: Supporting Online Material http://www.sciencemag.org/content/345/6204/1251033.full.html#related found at: can be related to this article A list of selected additional articles on the Science Web sites http://www.sciencemag.org/content/345/6204/1251033.full.html#ref-list-1 , 38 of which can be accessed free: cites 85 articles This article http://www.sciencemag.org/cgi/collection/immunology Immunology subject collections: This article appears in the following

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.

In line with the importance of RNA-seq, the bioinformatics community has produced numerous data analysis tools incorporating methods to correct sample-specific biases. However, few advanced simulation tools exist to enable benchmarking of competing correction methods. We introduce the first framework to reproduce the properties of individual RNA-seq runs and, by applying it on several datasets, we demonstrate the importance of accounting for sample-specificity in realistic simulations.