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Data availability: No new data were generated or analysed in support of this research. Copyright © The Author(s) 2022. GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function. Here, we present an update on the annotation of human and mouse genes, including developments in the tools, data, analyses and major collaborations which underpin this progress. For example, we report the creation of a set of non-canonical ORFs identified in GENCODE transcripts, the LRGASP collaboration to assess the use of long transcriptomic data to build transcript models, the progress in collaborations with RefSeq and UniProt to increase convergence in the annotation of human and mouse protein-coding genes, the propagation of GENCODE across the human pan-genome and the development of new tools to support annotation of regulatory features by GENCODE. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org. National Human Genome Research Institute of the National Institutes of Health [U41HG007234, R01HG004037]; Wellcome Trust [WT222155/Z/20/Z]; European Molecular Biology Laboratory. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding for open access charge: National Institutes of Health.

There are several non-steroidal intra-articular therapeutics (NSIATs) available for use by equine practitioners for the treatment of performance-limiting joint-related pathology. Information is limited on perceived clinical efficacy, recommended treatment protocols, and associated complications. Our objective with this cross-sectional survey was to investigate the current clinical usage of NSIATs by equine practitioners. An electronic cross-sectional convenience survey inquiring about the use of steroidal and NSIATS (platelet-rich plasma, autologous conditioned serum, autologous protein solution, cellular therapies, and polyacrylamide hydrogel) was distributed internationally to equine practitioners. A total of 353 surveys were completed. NSIATs were used by 87.5% of the participants. Corticosteroids and hyaluronic acid remain the intra-articular therapeutic of choice among practitioners, followed by autologous conditioned serum, and platelet-rich plasma and autologous conditioned protein. Polyacrylamide hydrogel was the least used. Practitioners were more likely to use NSIATs if their caseload was greater than 50% equine (P

From 2006 to 2008 The Canadian Institute in Greece sponsored the excavation of a Mycenaean chamber tomb cemetery at Ayia Sotira near Koutsomodi in the Nemea Valley. The five modest tombs excavated by the project were undoubtedly associated with the nearby settlement of Tsoungiza, and offer a picture of the mortuary practices associated with this settlement. The practices at Ayia Sotira describe both local funerary customs and more generally “Mycenaean” ones observable throughout Mainland Greece and the Aegean. Explanations for the local character are found in the economic conditions of the nearby settlement, in the local geology, and presumably local customs. These were documented through careful recovery of the stratigraphy and contents of the tombs, including paleobotanical, phytolith, organic residue, and micromorphological analysis. The remarkable similarity of these tombs and their contents to those excavated at neighboring Zygouries confirm the local character of chamber tomb inhumation. Yet comparison with other chamber tomb cemeteries, notably nearby Aidonia, but also with examples in the Corinthia, Argolid, and elsewhere, demonstrate the general features of a common “Mycenaean” practice. Overall, burial practices in the chamber tombs at Ayia Sotira fits our reconstruction of the inhabitants of Tsoungiza being incorporated into a social and political system dominated by the inhabitants of Mycenae during the LH IIIA2–B periods.

Overpopulation of free-roaming and wildlife animals negatively affects economy and public health in many parts of the world. Contraceptive vaccines are viewed as a valuable option for reducing numbers of unwanted animals. This study develops vaccines for potential use in animal contraception exploiting a DNA platform. Objectives of the study were to generate DNA constructs directed against gonadotropin-releasing hormone receptor (GnRHR), a crucial molecular player in animal reproduction, and characterize them for ability to promote immune responses and suppression of reproductive parameters in vivo. DNA constructs were created to encode for a recombinant protein composed of two domains: GnRHR, the target antigen, and ubiquitin (Ub), a support protein. Ub-GnRHR constructs administered intramuscularly or intradermally or containing different promoters were compared. CMV and EF1α promoters were shown to be superior to CAG. In fertility trials, mice immunized intradermally with Ub-GnRHR construct driven by EF1α had a significantly lower number of fetuses. Importantly, the impaired fertility was achieved with a single DNA immunization and without the use of adjuvants. The study demonstrated for the first time that targeting the GnRH receptor with DNA-based vaccines could be a viable option for animal contraception.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org. We thank Tim Hubbard and Jennifer Harrow for their lead- ership in the GENCODE project from 2003-2016 as well as all groups and group members involved in the GENCODE project since its inception including the HAVANA manual annotation group formerly at Wellcome Sanger Institute now at EMBL-EBI (founder), the Guigo group at Centre for Genomic Regulation (founder), the Gerstein group at Yale (founder), the Center for Biomolecular Science & En- gineering at UCSC (founder), the Ensembl team at EMBL- EBI (joined 2007), the Kellis group at MIT (joined 2007), the Tress group at CNIO (joined 2007), the Choudhary group formerly at Wellcome Sanger Institute now at Insti- tute of Cancer Research (joined 2012), the Reymond group at University of Lausanne (2003–2017), the Antonarakis group at University of Geneva (2003–2007), the Wei group at Genome Institute of Singapore (2003–2007), the Gin- geras group at Affymetrix Ltd (2003–2007) and the Brent group at Washington University in St. Louis (2007–2012). Sí

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.

Reovirus (RT3D) is a naturally occurring double-stranded RNA oncolytic virus that has shown preclinical efficacy in a wide range of tumor types. Early phase clinical studies have shown that this agent has modest monotherapy efficacy and can safely be combined with cytotoxic chemotherapy regimens. In the current studies, we used a high-throughput drug screen approach of different targeted therapeutic agents with the aim of looking for potential viral sensitizers that could enhance RT3D tumor killing. BMN-673 (talazoparib), a clinically approved poly(ADP)-ribose polymerase 1 (PARP-1) inhibitor was identified as a top hit and found to sensitize profoundly to RT3D both in vitro and in vivo in human xenograft tumors in a nude mouse model. We found that RT3D activated cellular PARP1 and was associated with PARylation of cellular proteins, including components of the DISC-associated cell death machinery. Combined treatment with RT3D and talazoparib enhanced extrinsic apoptosis (amplified by autocrine/paracrine TNF-α and TRAIL signaling), NF-κB pathway activity and pro-inflammatory cytokine production (CCL5/RANTES, CXCL8/IL8, CXCL1/GRO and CXCL10/IP10). Signaling was shown to be dependent on nucleic acid sensing mechanisms mediated by RIG-I and TLR3. We also found anti-tumour efficacy in an immunocompetent mouse model and this correlated with an increase in an immune response following combination treatment of RT3D and talazoparib. Our data provide a strong rationale for the combination of oncolytic RT3D with PARP1 inhibitors to exploit immunogenic response in cancer treatment. Citation Format: Joan N. Kyula, Victoria Roulstone, Richard Elliott, Harriet Whittock, Galabina Bozhanova, Martin McLaughlin, Malin Pedersen, Dragomir Krastev, Stephen Pettitt, Arnaud Legrand, Tencho Tenev, James Wright, Lu Yu, Jyoti Choudhary, Pascal Meier, Christopher J. Lord, Alan Melcher, Grey Wilkinson, Matt Coffey, Kevin J. Harrington. Talazoparib interacts with oncolytic reovirus to enhance death-inducing signaling complex (DISC)-mediated apoptosis and immune response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1932.

This paper proposes a new generic method to detect anomalies (i.e., statistical outliers) which can be used with a generative topic model. In this paper, we specify this method in the context of the Mixture-of-unigrams model, which is widely used in text mining. It is possible to detect anomalies with a topic model by applying a threshold to the likelihood. However, it is challenging to choose the threshold since the choice needs to consider both the similarities of the topics and the length of documents. This paper describes a new intuitive method to detect anomalies which simply manipulates the output of the trained model. Such an approach is anticipated to have parameters that are more intuitive to define for a given problem. To assess the utility of the proposed approach, we also present a use case involving identifying ships misreporting their ship-type using geo-location data from the Automatic Identification System (AIS) messages. We show that, if we train a model using data for one type of ship, it is possible to identify ships of another type as anomalous.

The early infantile epileptic encephalopathies (EIEE) are a group of rare, severe neurodevelopmental disorders, where even the most thorough sequencing studies leave 60-65% of patients without a molecular diagnosis. Here, we explore the incompleteness of transcript models used for exome and genome analysis as one potential explanation for lack of current diagnoses. Therefore, we have updated the GENCODE gene annotation for 191 epilepsy-associated genes, using human brain-derived transcriptomic libraries and other data to build 3,550 novel putative transcript models. The extended transcriptional footprint of these genes allowed for 294 intronic or intergenic variants, found in human mutation databases, to be reclassified as exonic, while a further 70 intronic variants were reclassified as splice-site proximal. Using SCN1A as a case study due to its close phenotype/genotype correlation with Dravet syndrome, we screened 122 people with Dravet syndrome, or a similar phenotype, with a panel of novel exon sequences representing eight established genes and identified two de novo SCN1A variants that now, through improved gene annotation can be ascribed to residing among novel exons. These two (from 122 screened patients, 1.6%) new molecular diagnoses carry significant clinical implications. Furthermore, we identified a previously-classified SCN1A intronic Dravet-associated variant that now lies within a deeply conserved novel exon. Our findings illustrate the potential gains of thorough gene annotation in improving diagnostic yields for genetic disorders. We would expect to find new molecular diagnoses in our 191 genes that were originally suspected by clinicians for patients, with a negative diagnosis.

Proteogenomics leverages information derived from proteomic data to improve genome annotations. Of particular interest are "novel" peptides that provide direct evidence of protein expression for genomic regions not previously annotated as protein-coding. We present a modular, automated data analysis pipeline aimed at detecting such "novel" peptides in proteomic data sets. This pipeline implements criteria developed by proteomics and genome annotation experts for high-stringency peptide identification and filtering. Our pipeline is based on the OpenMS computational framework; it incorporates multiple database search engines for peptide identification and applies a machine-learning approach (Percolator) to post-process search results. We describe several new and improved software tools that we developed to facilitate proteogenomic analyses that enhance the wealth of tools provided by OpenMS. We demonstrate the application of our pipeline to a human testis tissue data set previously acquired for the Chromosome-Centric Human Proteome Project, which led to the addition of five new gene annotations on the human reference genome.

The correlation between mechanical properties from the equine articular cartilage and signalment was investigated. Fresh articular cartilage of fetlock, carpus, and stifle were harvested from 12 deceased horses with information on the breed, age, sex, and weight within 4 h of euthanasia for measurements. Seven indentation tests at different normalized displacements of 10, 20, 30, 35, 40, 45, and 50% of the cartilage thickness were performed with a spherical probe indenting at 0.1 mm/s velocity. The solid matrix of the cartilage was found to follow a hyper-elastic material behavior defined by Ogden; the solid phase aggregate modulus ( E a ), hyperelastic material constant ( α ), and fluid load fraction ( F ′) of the cartilage were characterized. The characterized material properties were statistically analyzed using a mixed model ANOVA and Scheffe's test to check the correlation between the properties and signalment variables (breed, age, sex, and weight). There were correlations between both the solid phase aggregate modulus and age ( p p p p

Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, including human cell lines and human and mouse tissues. This method predicts the protein expression values with average R 2 scores between 0.46 and 0.54, which is significantly better than predictions based on correlations using the RNA expression data alone. Moreover, it is demonstrated that the derived models can be "transferred" across experiments and species. For instance, the model derived from human tissues gave a R 2 = 0.51 when applied to mouse tissue data. It is concluded that protein abundances generated in label-free MS experiments can be computationally predicted using functional annotated attributes and can be used to highlight aberrant protein abundance values.

Background Birth outcome disparities are particularly evident in Alabama and evidence has shown that including doulas in an interprofessional birth care team (IBCT) may improve these outcomes. Purpose The purpose of this study is to assess whether including doulas in the birth care team was associated with improved birth outcomes among low resource mothers in Alabama. Methods Doula supported birth outcomes in 2013–2014 (n = 120) were restrospectively compared to all 2014 Medicaid funded births in Jefferson County, Alabama (n = 3782). Results Doula supported births were associate with lower rates of epidural anesthesia and birth by cesarean as compared to the reference population (OR 3.0, 95% CI 2.1–4.4 and OR 1.8, 95% CI 1.1–2.9, respectively, for reference population). Doulas were also associated with a ten-fold increase in breastfeeding initiation (OR 10.5, 95% CI 5.4–23.2). Conclusions Doula support is associated with increased breastfeeding initiation and reduced rates of epidurals and cesareans among low resource mothers in Alabama.

In a 2018 paper posted to bioRxiv, Pertea et al. presented the CHESS database, a new catalog of human gene annotations that includes 1,178 new protein-coding predictions. These are based on evidence of transcription in human tissues and homology to earlier annotations in human and other mammals. Here, we reanalyze the evidence used by CHESS, and find that nearly all protein-coding predictions are false positives. We find that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein-coding predictions. More than half are homologous to only nine Alu-derived primate sequences corresponding to an erroneous and previously withdrawn Pfam protein domain. The entire set shows poor evolutionary conservation and PhyloCSF protein-coding evolutionary signatures indistinguishable from noncoding RNAs, indicating lack of protein-coding constraint. Only four predictions are supported by mass spectrometry evidence, and even those matches are inconclusive. Overall, the new protein-coding predictions are unsupported by any credible experimental or evolutionary evidence of function, result primarily from homology to genes incorrectly classified as protein-coding, and are unlikely to encode functional proteins.

Infection with Citrobacter rodentium triggers robust tissue damage repair responses, manifested by secretion of IL-22, in the absence of which mice succumbed to the infection. Of the main hallmarks of C. rodentium infection are colonic crypt hyperplasia (CCH) and dysbiosis. In order to colonize the host and compete with the gut microbiota, C. rodentium employs a type III secretion system (T3SS) that injects effectors into colonic intestinal epithelial cells (IECs). Once injected, the effectors subvert processes involved in innate immune responses, cellular metabolism and oxygenation of the mucosa. Importantly, the identity of the effector/s triggering the tissue repair response is/are unknown. Here we report that the effector EspO ,an orthologue of OspE found in Shigella spp, affects proliferation of IECs 8 and 14 days post C. rodentium infection as well as secretion of IL-22 from colonic explants. While we observed no differences in the recruitment of group 3 innate lymphoid cells (ILC3s) and T cells, which are the main sources of IL-22 at the early and late stages of C. rodentium infection respectively, infection with ΔespO was characterized by diminished recruitment of sub-mucosal neutrophils, which coincided with lower abundance of Mmp9 and chemokines (e.g. S100a8/9) in IECs. Moreover, mice infected with ΔespO triggered significantly lesser nutritional immunity (e.g. calprotectin, Lcn2) and expression of antimicrobial peptides (Reg3β, Reg3γ) compared to mice infected with WT C. rodentium. This overlapped with a decrease in STAT3 phosphorylation in IECs. Importantly, while the reduced CCH and abundance of antimicrobial proteins during ΔespO infection did not affect C. rodentium colonization or the composition of commensal Proteobacteria, they had a subtle consequence on Firmicutes subpopulations. EspO is the first bacterial virulence factor that affects neutrophil recruitment and secretion of IL-22, as well as expression of antimicrobial and nutritional immunity proteins in IECs., Author summary Citrobacter rodentium is a gold standard model to study pathogen-host-microbiome interactions. Two of the hallmarks of C. rodentium infection are colonic damage repair responses and colitis; symptoms that are shared with inflammatory bowel diseases in humans. The processes leading to tissue damage repair responses and the implicated bacterial virulence factors are still elusive. In this paper, we show that the C. rodentium type III secretion system effector EspO plays a major role in triggering damage healing responses, recruitment of neutrophils to the colonic villi, secretion of IL-22 from colonic explants and expression of IL-22 regulated genes in intestinal epithelial cells. This paper is the first to report a bacterial virulence factor that impacts on both intestinal epithelial cell proliferation and immune responses.

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.

Summary The intestinal epithelial cells (IECs) that line the gut form a robust line of defense against ingested pathogens. We investigated the impact of infection with the enteric pathogen Citrobacter rodentium on mouse IEC metabolism using global proteomic and targeted metabolomics and lipidomics. The major signatures of the infection were upregulation of the sugar transporter Sglt4, aerobic glycolysis, and production of phosphocreatine, which mobilizes cytosolic energy. In contrast, biogenesis of mitochondrial cardiolipins, essential for ATP production, was inhibited, which coincided with increased levels of mucosal O2 and a reduction in colon-associated anaerobic commensals. In addition, IECs responded to infection by activating Srebp2 and the cholesterol biosynthetic pathway. Unexpectedly, infected IECs also upregulated the cholesterol efflux proteins AbcA1, AbcG8, and ApoA1, resulting in higher levels of fecal cholesterol and a bloom of Proteobacteria. These results suggest that C. rodentium manipulates host metabolism to evade innate immune responses and establish a favorable gut ecosystem., Graphical Abstract, Highlights • C. rodentium infection disrupts mitochondrial bioenergetics • C. rodentium triggers aerobic glycolysis and production of phosphocreatine in vivo • Srebp2 and cholesterol biogenesis and efflux are activated by C. rodentium • C. rodentium triggers mucosal oxygenation and dysbiosis, Berger et al. reveal how C. rodentium infection manipulates host metabolism to evade innate immune responses and establish a favorable gut ecosystem. Binding of C. rodentium to the gut epithelium rewires cellular bioenergetics and cholesterol metabolism, altering the composition of the gut microbiota and processes involved in fighting infection.

Degenerative joint disease (DJD) or osteoarthritis in the equine is largely a result of biomechanical stressors that result in inflammation within the joint, which with continual exposure, leads to progressive degeneration. A myriad of therapies are available for treatment of horses with DJD including nonsteroidal anti-inflammatory drugs, corticosteroids, physiological modifiers, and biological therapies. C-phycocyanin, a protein-bound pigment found in blue-green algae, has been shown to have anti-inflammatory and antioxidant properties and is available as a diet supplement in people, dogs, and horses. Forty-one horses with naturally occurring lameness as a result of DJD were selected for this study. In a blinded study, horses were randomly assigned to either the commercial or placebo product that was fed once daily for 12 months. At selected time points, lameness evaluation was performed through objective gait analysis. Previous medical records for management of lameness were reviewed for all enrolled horses. No statistically significant differences existed within or between the two groups when gait was evaluated objectively nor within individual horses between time points. Review of medical records found that five treated horses had a decreased in frequency of intra-articular injection of corticosteroids. Although this study did not find statistically significant improvement of lameness with oral daily supplementation of C-phycocyanin in equine athletes, there appeared to be a trend of improvement in lameness during the loading period and a decrease in frequency of administration of intra-articular corticosteroids. Further investigations using a higher dose seem warranted.

SummaryAssessing the extent to which genomic alterations compromise the integrity of the proteome is fundamental in identifying the mechanisms that shape cancer heterogeneity. We have used isobaric labelling and tribrid mass spectrometry to characterize the proteomic landscapes of 50 colorectal cancer cell lines and to decipher the relationships between genomic and proteomic variation. The robust quantification of 12,000 proteins and 27,000 phosphopeptides revealed how protein symbiosis translates to a co-variome which is subjected to a hierarchical order and exposes the collateral effects of somatic mutations on protein complexes. Targeted depletion of key chromatin modifiers confirmed the transmission of variation and the directionality as characteristics of protein interactions. Protein level variation was leveraged to build drug response predictive models towards a better understanding of pharmacoproteomic interactions in colorectal cancer. Overall, we provide a deep integrative view of the molecular structure underlying the variation of colorectal cancer cells.HighlightsThe cancer cell functional “co-variome” is a strong attribute of the proteome.Mutations can have a direct impact on protein levels of chromatin modifiers.Transmission of genomic variation is a characteristic of protein interactions.Pharmacoproteomic models are strong predictors of response to DNA damaging agents.AbbreviationsCOREADColorectal AdenocarcinomaIMACImmobilized Metal ion Affinity ChromatographyROCReceiver Operating CharacteristicAUCArea Under the CurveWGCNAWeighted Correlation Network AnalysisCNACopy Number AlterationSOMSelf-Organizing MapQTLQuantitative Trait LociMSIMicrosatellite InstabilityCPSColorectal Proteomic Subtypes

Summary Assessing the impact of genomic alterations on protein networks is fundamental in identifying the mechanisms that shape cancer heterogeneity. We have used isobaric labeling to characterize the proteomic landscapes of 50 colorectal cancer cell lines and to decipher the functional consequences of somatic genomic variants. The robust quantification of over 9,000 proteins and 11,000 phosphopeptides on average enabled the de novo construction of a functional protein correlation network, which ultimately exposed the collateral effects of mutations on protein complexes. CRISPR-cas9 deletion of key chromatin modifiers confirmed that the consequences of genomic alterations can propagate through protein interactions in a transcript-independent manner. Lastly, we leveraged the quantified proteome to perform unsupervised classification of the cell lines and to build predictive models of drug response in colorectal cancer. Overall, we provide a deep integrative view of the functional network and the molecular structure underlying the heterogeneity of colorectal cancer cells., Graphical Abstract, Highlights • The cancer cell “co-variome” recapitulates functional protein associations • Loss-of-function mutations can impact protein levels beyond mRNA regulation • The consequences of genomic alterations can propagate through protein interactions • We provide insight into the molecular organization of colorectal cancer cells, Roumeliotis et al. use in-depth proteomics to assess the impact of genomic alterations on protein networks in colorectal cancer cell lines. Cell-line-specific network signatures are inferred de novo by protein quantification profiles and ultimately expose the collateral and transcript-independent effects of detrimental mutations on protein complexes.

Identification and quantification of proteins by shotgun proteomics experiments is underpinned by the use of accurate masses and fragmentation patterns generated by tandem mass spectrometry. Assigning peptide sequences to tandem MS data is supported by a plethora of informatics tools. The majority of spectral identification software report arbitrary fitness scores reflecting the quality of a match, however, valid statistical metrics must be used to make sense of these scores and attribute a confidence to the peptide identifications. Accurately estimating the error and devising filtering routines to minimise incorrect and random identifications is essential for making valid and reproducible conclusions about the biology of the sample being analysed. This chapter discusses the statistical approaches used to evaluate and validate shotgun proteomics peptide to spectrum matches and provides a summary of software available for this purpose.

Complete annotation of the human genome is indispensable for medical research. The GENCODE consortium strives to provide this, augmenting computational and experimental evidence with manual annotation. The rapidly developing field of proteogenomics provides evidence for the translation of genes into proteins and can be used to discover and refine gene models. However, for both the proteomics and annotation groups, there is a lack of guidelines for integrating this data. Here we report a stringent workflow for the interpretation of proteogenomic data that could be used by the annotation community to interpret novel proteogenomic evidence. Based on reprocessing of three large-scale publicly available human data sets, we show that a conservative approach, using stringent filtering is required to generate valid identifications. Evidence has been found supporting 16 novel protein-coding genes being added to GENCODE. Despite this many peptide identifications in pseudogenes cannot be annotated due to the absence of orthogonal supporting evidence., Identifying and annotating functional elements in the human genome remains a challenging but important task. Here the authors propose a priority annotation score to rank identifications and suggest how proteogenomics evidence can be interpreted and what additional information substantiates protein-coding potential for annotation.

Work in humans and mice highlights the role of tryptophan metabolism in the immunopathogenesis of typhoid fever, offering novel insight into clinical disease., Enteric fever, caused by Salmonella enterica serovar Typhi, is an important public health problem in resource-limited settings and, despite decades of research, human responses to the infection are poorly understood. In 41 healthy adults experimentally infected with wild-type S. Typhi, we detected significant cytokine responses within 12 h of bacterial ingestion. These early responses did not correlate with subsequent clinical disease outcomes and likely indicate initial host–pathogen interactions in the gut mucosa. In participants developing enteric fever after oral infection, marked transcriptional and cytokine responses during acute disease reflected dominant type I/II interferon signatures, which were significantly associated with bacteremia. Using a murine and macrophage infection model, we validated the pivotal role of this response in the expression of proteins of the host tryptophan metabolism during Salmonella infection. Corresponding alterations in tryptophan catabolites with immunomodulatory properties in serum of participants with typhoid fever confirmed the activity of this pathway, and implicate a central role of host tryptophan metabolism in the pathogenesis of typhoid fever.

Accurate statistical evaluation of sequence database peptide identifications from tandem mass spectra is essential in mass spectrometry based proteomics experiments. These statistics are dependent on accurately modelling random identifications. The target-decoy approach has risen to become the de facto approach to calculating FDR in proteomic datasets. The main principle of this approach is to search a set of decoy protein sequences that emulate the size and composition of the target protein sequences searched whilst not matching real proteins in the sample. To do this, it is commonplace to reverse or shuffle the proteins and peptides in the target database. However, these approaches have their drawbacks and limitations. A key confounding issue is the peptide redundancy between target and decoy databases leading to inaccurate FDR estimation. This inaccuracy is further amplified at the protein level and when searching large sequence databases such as those used for proteogenomics. Here, we present a unifying hybrid method to quickly and efficiently generate decoy sequences with minimal overlap between target and decoy peptides. We show that applying a reversed decoy approach can produce up to 5% peptide redundancy and many more additional peptides will have the exact same precursor mass as a target peptide. Our hybrid method addresses both these issues by first switching proteolytic cleavage sites with preceding amino acid, reversing the database and then shuffling any redundant sequences. This flexible hybrid method reduces the peptide overlap between target and decoy peptides to about 1% of peptides, making a more robust decoy model suitable for large search spaces. We also demonstrate the anti-conservative effect of redundant peptides on the calculation of q-values in mouse brain tissue data.

The purpose of this Article is to examine existing case law on implied covenants in oil and gas leases in the Appalachian Basin states, identify gaps in case law, and as far as reasonably possible, to predict the issues that might be litigated in the future in light of the rush to develop the Marcellus Shale and Utica Shale formations.

This study presents a revised methodology for the excavation and analysis of the stratigraphy in Mycenaean chamber tombs and other multi-use burials. For our excavation of chamber tombs at Ayia Sotira and Barnavos, Nemea, we followed a geoarchaeological approach to provide details about the process of backfilling and re-opening of the tombs and to identify the location, number, and slope of these re-openings. In the studied fill of tomb entrance corridors (dromoi) at Ayia Sotira we observed a suite of sedimentary structures based on field and micromorphological observations. These are attributed to grain flow and debris fall processes associated with the formation of small piles during the shoveling of debris into the tomb. During ancient re-opening of the tombs extensive planar erosional surfaces were produced, occasionally associated with a basal stone line feature and an abrupt change in the degree of compaction. Constructed plastered floors were identified in the dromoi and the chambers during both the initial opening and the subsequent re-openings of the tombs. The proposed geoarchaeological analysis will enable the reconstruction of complex histories of mortuary practices and their social meanings. Moreover, this analysis shows that some anthropogenic processes of sediment accumulation can be analyzed and interpreted with paradigms of natural processes. Therefore, it provides a framework for understanding other types of earthworks that involve digging and filling.

The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories. publishedVersion