Mapping genome-wide data to human subtelomeres has been problematic due to the incomplete assembly and challenges of low-copy repetitive DNA elements. Here, we provide updated human subtelomere sequence assemblies that were extended by filling telomere-adjacent gaps using clone-based resources. A bioinformatic pipeline incorporating multiread mapping for annotation of the updated assemblies using short-read data sets was developed and implemented. Annotation of subtelomeric sequence features as well as mapping of CTCF and cohesin binding sites using ChIP-seq data sets from multiple human cell types confirmed that CTCF and cohesin bind within 3 kb of the start of terminal repeat tracts at many, but not all, subtelomeres. CTCF and cohesin co-occupancy were also enriched near internal telomere-like sequence (ITS) islands and the nonterminal boundaries of subtelomere repeat elements (SREs) in transformed lymphoblastoid cell lines (LCLs) and human embryonic stem cell (ES) lines, but were not significantly enriched in the primary fibroblast IMR90 cell line. Subtelomeric CTCF and cohesin sites predicted by ChIP-seq using our bioinformatics pipeline (but not predicted when only uniquely mapping reads were considered) were consistently validated by ChIP-qPCR. The colocalized CTCF and cohesin sites in SRE regions are candidates for mediating long-range chromatin interactions in the transcriptrich SRE region. A public browser for the integrated display of short-read sequence-based annotations relative to key subtelomere features such as the start of each terminal repeat tract, SRE identity and organization, and subtelomeric gene models was established.
SUMMARYAnts are an emerging model system for neuroepigenetics, as embryos with virtually identical genomes develop into different adult castes that display diverse physiology, morphology, and behavior. Although a number of ant genomes have been sequenced to date, their draft quality is an obstacle to sophisticated analyses of epigenetic gene regulation. We reassembled de novo high-quality genomes for two ant species, Camponotus floridanus and Harpegnathos saltator. Using long reads enabled us to span large repetitive regions and improve genome contiguity, leading to comprehensive and accurate protein-coding annotations that facilitated the identification of a Gp-9-like gene as differentially expressed in Harpegnathos castes. The new assemblies also enabled us to annotate long non-coding RNAs in ants, revealing caste-, brain-, and developmental-stage-specific long non-coding RNAs (lncRNAs) in Harpegnathos. These upgraded genomes, along with the new gene annotations, will aid future efforts to identify epigenetic mechanisms of phenotypic and behavioral plasticity in ants.
The majority of oncogenic drivers are intracellular proteins, thus constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes1. However, most cancers have a modest mutational burden that is insufficient to generate responses using neoantigen-based therapies2,3. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks4. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins that are essential for tumourigenesis and focus on targeting the unmutated peptide QYNPIRTTF, discovered on HLA-A*24:02, which is derived from the neuroblastoma dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (CARs) using a counter-panning strategy with predicted potentially cross-reactive peptides. We further hypothesized that peptide-centric CARs could recognize peptides on additional HLA allotypes when presented in a similar manner. Informed by computational modelling, we showed that PHOX2B peptide-centric CARs also recognize QYNPIRTTF presented by HLA-A*23:01 and the highly divergent HLA-B*14:02. Finally, we demonstrated potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that peptide-centric CARs have the potential to vastly expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and widen the population of patients who would benefit from such therapy by breaking conventional HLA restriction.
Long intergenic noncoding RNAs (lincRNAs) have emerged as important modulators of cellular functions. Most lincRNAs are not conserved among mammals, raising the fundamental question of whether nonconserved adipose-expressed lincRNAs are functional. To address this, we performed deep RNA sequencing of gluteal subcutaneous adipose tissue from 25 healthy humans. We identified 1001 putative lincRNAs expressed in all samples through de novo reconstruction of noncoding transcriptomes and integration with existing lincRNA annotations. One hundred twenty lincRNAs had adipose-enriched expression, and 54 of these exhibited peroxisome proliferator-activated receptor γ (PPARγ) or CCAAT/enhancer binding protein α (C/EBPα) binding at their loci. Most of these adipose-enriched lincRNAs (~85%) were not conserved in mice, yet on average, they showed degrees of expression and binding of PPARγ and C/EBPα similar to those displayed by conserved lincRNAs. Most adipose lincRNAs differentially expressed ( = 53) in patients after bariatric surgery were nonconserved. The most abundant adipose-enriched lincRNA in our subcutaneous adipose data set, , was nonconserved, up-regulated in adipose depots of obese individuals, and markedly induced during in vitro human adipocyte differentiation. We demonstrated that interacts with heterogeneous nuclear ribonucleoprotein U (hnRNPU) and insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) at distinct subcellular locations to regulate adipocyte differentiation and lipogenesis.
Here we present a free interactive web tool to process and visualize proteomics datasets with a single click. GiaPronto can process all proteomics quantification methods, i.e. labelfree, SILAC and isobaric labeling, and analyze post-translational modifications (PTMs). The software performs normalization and statistics, assists determination of regulated proteins, biomarkers and Gene Ontology (GO) enrichment, and provides high resolution images and tables for further data analysis. We foresee that GiaPronto will become the most rapid and simple tool for assessing data quality and determining most relevant features of proteomic datasets. GiaPronto is available at giapronto.diskinlab.org.
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