RiboGalaxy: A Galaxy-based Web Platform for Ribosome Profiling Data Processing - 2023 Update.

Ribosome profiling (Ribo-Seq) captures a "snapshot" of ribosomes' locations at the entire transcriptome of a cell at sub-codon resolution providing insights into gene expression and enabling the discovery of novel translated regions. RiboGalaxy (https://ribogalaxy.genomicsdatascience.ie/), a Galaxy-based platform for processing Ribo-Seq data is a RiboSeq.Org (https://riboseq.org/) resource. RiboSeq.Org is an online gateway to a set of integrated tools for the processing and analysis of Ribo-Seq data. In this RiboGalaxy update we introduce changes to both the tools available on RiboGalaxy and to how the resource is managed on the backend. For example, in order to improve interoperability between Riboseq.Org resources, we added tools that link RiboGalaxy outputs with Trips-Viz and GWIPS-viz browsers for downstream analysis and visualisation. RiboGalaxy's backend now utilises Ansible configuration management which enhances its stability and jobs are executed within Singularity containers and are managed by Slurm, strengthening reproducibility and performance respectively.

Thousands of human non-AUG extended proteoforms lack evidence of evolutionary selection among mammals.

The synthesis of most proteins begins at AUG codons, yet a small number of non-AUG initiated proteoforms are also known. Here we analyse a large number of publicly available Ribo-seq datasets to identify novel, previously uncharacterised non-AUG proteoforms using Trips-Viz implementation of a novel algorithm for detecting translated ORFs. In parallel we analyse genomic alignment of 120 mammals to identify evidence of protein coding evolution in sequences encoding potential extensions. Unexpectedly we find that the number of non-AUG proteoforms identified with ribosome profiling data greatly exceeds those with strong phylogenetic support suggesting their recent evolution. Our study argues that the protein coding potential of human genome greatly exceeds that detectable through comparative genomics and exposes the existence of multiple proteins encoded by the same genomic loci.

Evolution of naturally arising SARS-CoV-2 defective interfering particles.

Defective interfering (DI) particles arise during virus propagation, are conditional on parental virus for replication and packaging, and interfere with viral expansion. There is much interest in developing DIs as anti-viral agents. Here we characterize DI particles that arose following serial passaging of SARS-CoV-2 at high multiplicity of infection. The prominent DIs identified have lost ~84% of the SARS-CoV-2 genome and are capable of attenuating parental viral titers. Synthetic variants of the DI genomes also interfere with infection and can be used as conditional, gene delivery vehicles. In addition, the DI genomes encode an Nsp1-10 fusion protein capable of attenuating viral replication. These results identify naturally selected defective viral genomes that emerged and stably propagated in the presence of parental virus.

Lack of evidence for ribosomal frameshifting in ATP7B mRNA decoding.

The research article describing the discovery of ribosomal frameshifting in the bacterial CopA gene also reported the occurrence of frameshifting in the expression of the human ortholog ATP7B based on assays using dual luciferase reporters. An examination of the publicly available ribosome profiling data and the phylogenetic analysis of the proposed frameshifting site cast doubt on the validity of this claim and prompted us to reexamine the evidence. We observed similar apparent frameshifting efficiencies as the original authors using the same type of vector that synthesizes both luciferases as a single polyprotein. However, we noticed anomalously low absolute luciferase activities from the N-terminal reporter that suggests interference of reporter activity or levels by the ATP7B test cassette. When we tested the same proposed ATP7B frameshifting cassette in a more recently developed reporter system in which the reporters are released without being included in a polyprotein, no frameshifting was detected above background levels.

Non-AUG translation initiation in mammals.

Recent proteogenomic studies revealed extensive translation outside of annotated protein coding regions, such as non-coding RNAs and untranslated regions of mRNAs. This non-canonical translation is largely due to start codon plurality within the same RNA. This plurality is often due to the failure of some scanning ribosomes to recognize potential start codons leading to initiation downstream-a process termed leaky scanning. Codons other than AUG (non-AUG) are particularly leaky due to their inefficiency. Here we discuss our current understanding of non-AUG initiation. We argue for a near-ubiquitous role of non-AUG initiation in shaping the dynamic composition of mammalian proteomes.

Enhanced C/EBP binding to G·T mismatches facilitates fixation of CpG mutations in cancer and adult stem cells.

Somatic mutations in regulatory sites of human stem cells affect cell identity or cause malignant transformation. By mining the human genome for co-occurrence of mutations and transcription factor binding sites, we show that C/EBP binding sites are strongly enriched with [C > T]G mutations in cancer and adult stem cells, which is of special interest because C/EBPs regulate cell fate and differentiation. In vitro protein-DNA binding assay and structural modeling of the CEBPB-DNA complex show that the G·T mismatch in the core CG dinucleotide strongly enhances affinity of the binding site. We conclude that enhanced binding of C/EBPs shields CpG·TpG mismatches from DNA repair, leading to selective accumulation of [C > T]G mutations and consequent deterioration of the binding sites. This mechanism of targeted mutagenesis highlights the effect of a mutational process on certain regulatory sites and reveals the molecular basis of putative regulatory alterations in stem cells.

Genome-wide map of human and mouse transcription factor binding sites aggregated from ChIP-Seq data.

OBJECTIVES: Mammalian genomics studies, especially those focusing on transcriptional regulation, require information on genomic locations of regulatory regions, particularly, transcription factor (TF) binding sites. There are plenty of published ChIP-Seq data on in vivo binding of transcription factors in different cell types and conditions. However, handling of thousands of separate data sets is often impractical and it is desirable to have a single global map of genomic regions potentially bound by a particular TF in any of studied cell types and conditions. DATA DESCRIPTION: Here we report human and mouse cistromes, the maps of genomic regions that are routinely identified as TF binding sites, organized by TF. We provide cistromes for 349 mouse and 599 human TFs. Given a TF, its cistrome regions are supported by evidence from several ChIP-Seq experiments or several computational tools, and, as an optional filter, contain occurrences of sequence motifs recognized by the TF. Using the cistrome, we provide an annotation of TF binding sites in the vicinity of human and mouse transcription start sites. This information is useful for selecting potential gene targets of transcription factors and detecting co-regulated genes in differential gene expression data.

Exploring the pre-immune landscape of antigen-specific T cells.

BACKGROUND: Adaptive immune responses to newly encountered pathogens depend on the mobilization of antigen-specific clonotypes from a vastly diverse pool of naive T cells. Using recent advances in immune repertoire sequencing technologies, models of the immune receptor rearrangement process, and a database of annotated T cell receptor (TCR) sequences with known specificities, we explored the baseline frequencies of T cells specific for defined human leukocyte antigen (HLA) class I-restricted epitopes in healthy individuals. METHODS: We used a database of TCR sequences with known antigen specificities and a probabilistic TCR rearrangement model to estimate the baseline frequencies of TCRs specific to distinct antigens epitopespecificT-cells. We verified our estimates using a publicly available collection of TCR repertoires from healthy individuals. We also interrogated a database of immunogenic and non-immunogenic peptides is used to link baseline T-cell frequencies with epitope immunogenicity. RESULTS: Our findings revealed a high degree of variability in the prevalence of T cells specific for different antigens that could be explained by the physicochemical properties of the corresponding HLA class I-bound peptides. The occurrence of certain rearrangements was influenced by ancestry and HLA class I restriction, and umbilical cord blood samples contained higher frequencies of common pathogen-specific TCRs. We also identified a quantitative link between specific T cell frequencies and the immunogenicity of cognate epitopes presented by defined HLA class I molecules. CONCLUSIONS: Our results suggest that the population frequencies of specific T cells are strikingly non-uniform across epitopes that are known to elicit immune responses. This inference leads to a new definition of epitope immunogenicity based on specific TCR frequencies, which can be estimated with a high degree of accuracy in silico, thereby providing a novel framework to integrate computational and experimental genomics with basic and translational research efforts in the field of T cell immunology.

HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis.

We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.