A Proteogenomic Approach to Unravel New Proteins Encoded in the Leishmania donovani (HU3) Genome.

The high-throughput proteomics data generated by increasingly more sensible mass spectrometers greatly contribute to our better understanding of molecular and cellular mechanisms operating in live beings. Nevertheless, proteomics analyses are based on accurate genomic and protein annotations, and some information may be lost if these resources are incomplete. Here, we show that most proteomics data may be recovered by interconnecting genomics and proteomics approaches (i.e., following a proteogenomic strategy), resulting, in turn, in an improvement of gene/protein models. In this study, we generated proteomics data from Leishmania donovani (HU3 strain) promastigotes that allowed us to detect 1908 proteins in this developmental stage on the basis of the currently annotated proteins available in public databases. However, when the proteomics data were searched against all possible open reading frames existing in the L. donovani genome, twenty new protein-coding genes could be annotated. Additionally, 43 previously annotated proteins were extended at their N-terminal ends to accommodate peptides detected in the proteomics data. Also, different post-translational modifications (phosphorylation, acetylation, methylation, among others) were found to occur in a large number of Leishmania proteins. Finally, a detailed comparative analysis of the L. donovani and Leishmania major experimental proteomes served to illustrate how inaccurate conclusions can be raised if proteomes are compared solely on the basis of the listed proteins identified in each proteome. Finally, we have created data entries (based on freely available repositories) to provide and maintain updated gene/protein models. Raw data are available via ProteomeXchange with the identifier PXD051920.

Identifying PE2 and PE5 Proteins from Existing Mass Spectrometry Data Using pFind.

The Chromosome-Centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome. Currently, the human proteome still contains approximately 2000 PE2-PE5 proteins, referring to annotated coding genes that lack sufficient protein-level evidence. During the past 10 years, it has been increasingly difficult to identify PE2-PE5 proteins in C-HPP approaches due to the limited occurrence. Therefore, we proposed that reanalyzing massive MS data sets in repository with newly developed algorithms may increase the occurrence of the peptides of these proteins. In this study, we downloaded 1000 MS data sets via the ProteomeXchange database. Using pFind software, we identified peptides referring to 1788 PE2-PE5 proteins. Among them, 11 PE2 and 16 PE5 proteins were identified with at least 2 peptides, and 12 of them were identified using 2 peptides in a single data set, following the criteria of the HPP guidelines. We found translation evidence for 16 of the 11 PE2 and 16 PE5 proteins in our RNC-seq data, supporting their existence. The properties of the PE2 and PE5 proteins were similar to those of the PE1 proteins. Our approach demonstrated that mining PE2 and PE5 proteins in massive data repository is still worthy, and multidata set peptide identifications may support the presence of PE2 and PE5 proteins or at least prompt additional studies for validation. Extremely high throughput could be a solution to finding more PE2 and PE5 proteins.

Comprehensive characterization of extracellular vesicles produced by environmental (Neff) and clinical (T4) strains of Acanthamoeba castellanii.

We conducted a comprehensive comparative analysis of extracellular vesicles (EVs) from two Acanthamoeba castellanii strains, Neff (environmental) and T4 (clinical). Morphological analysis via transmission electron microscopy revealed slightly larger Neff EVs (average = 194.5 nm) compared to more polydisperse T4 EVs (average = 168.4 nm). Nanoparticle tracking analysis (NTA) and dynamic light scattering validated these differences. Proteomic analysis of the EVs identified 1,352 proteins, with 1,107 common, 161 exclusive in Neff, and 84 exclusively in T4 EVs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed distinct molecular functions and biological processes and notably, the T4 EVs enrichment in serine proteases, aligned with its pathogenicity. Lipidomic analysis revealed a prevalence of unsaturated lipid species in Neff EVs, particularly triacylglycerols, phosphatidylethanolamines (PEs), and phosphatidylserine, while T4 EVs were enriched in diacylglycerols and diacylglyceryl trimethylhomoserine, phosphatidylcholine and less unsaturated PEs, suggesting differences in lipid metabolism and membrane permeability. Metabolomic analysis indicated Neff EVs enrichment in glycerolipid metabolism, glycolysis, and nucleotide synthesis, while T4 EVs, methionine metabolism. Furthermore, RNA-seq of EVs revealed differential transcript between the strains, with Neff EVs enriched in transcripts related to gluconeogenesis and translation, suggesting gene regulation and metabolic shift, while in the T4 EVs transcripts were associated with signal transduction and protein kinase activity, indicating rapid responses to environmental changes. In this novel study, data integration highlighted the differences in enzyme profiles, metabolic processes, and potential origins of EVs in the two strains shedding light on the diversity and complexity of A. castellanii EVs and having implications for understanding host-pathogen interactions and developing targeted interventions for Acanthamoeba-related diseases.IMPORTANCEA comprehensive and fully comparative analysis of extracellular vesicles (EVs) from two Acanthamoeba castellanii strains of distinct virulence, a Neff (environmental) and T4 (clinical), revealed striking differences in their morphology and protein, lipid, metabolites, and transcripts levels. Data integration highlighted the differences in enzyme profiles, metabolic processes, and potential distinct origin of EVs from both strains, shedding light on the diversity and complexity of A. castellanii EVs, with direct implications for understanding host-pathogen interactions, disease mechanisms, and developing new therapies for the clinical intervention of Acanthamoeba-related diseases.

Protocol to target a promoter region in human embryonic kidney cells using the CRISPR-dCas9 system for single-locus proteomics.

The unbiased identification of less-abundant transcription factors, which direct the expression of a target gene, is technically challenging. Here, we present a protocol to analyze the locus-specific chromatin-regulating proteome using in situ capture of chromatin interactions by an inactive Cas9 (dCas9). We describe steps for designing guide RNAs and transfection, followed by precipitation of chromatin and associated proteins. In the last step, we describe the elution of DNA and proteins for PCR and mass spectrometric analysis, respectively. For complete details on the use and execution of this protocol, please refer to Alkhayer et al.1.

Nominating novel proteins for anxiety via integrating human brain proteomes and genome-wide association study.

BACKGROUND: The underlying pathogenesis of anxiety remain elusive, making the pinpointing of potential therapeutic and diagnostic biomarkers for anxiety paramount to its efficient treatment. METHODS: We undertook a proteome-wide association study (PWAS), fusing human brain proteomes from both discovery (ROS/MAP; N = 376) and validation cohorts (Banner; N = 152) with anxiety genome-wide association study (GWAS) summary statistics. Complementing this, we executed transcriptome-wide association studies (TWAS) leveraging human brain transcriptomic data from the Common Mind Consortium (CMC) to discern the confluence of genetic influences spanning both proteomic and transcriptomic levels. We further scrutinized significant genes through a suite of methodologies. RESULTS: We discerned 14 genes instrumental in the genesis of anxiety through their specific cis-regulated brain protein abundance. Out of these, 6 were corroborated in the confirmatory PWAS, with 4 also showing associations with anxiety via their cis-regulated brain mRNA levels. A heightened confidence level was attributed to 5 genes (RAB27B, CCDC92, BTN2A1, TMEM106B, and DOC2A), taking into account corroborative evidence from both the confirmatory PWAS and TWAS, coupled with insights from mendelian randomization analysis and colocalization evaluations. A majority of the identified genes manifest in brain regions intricately linked to anxiety and predominantly partake in lysosomal metabolic processes. LIMITATIONS: The limited scope of the brain proteome reference datasets, stemming from a relatively modest sample size, potentially curtails our grasp on the entire gamut of genetic effects. CONCLUSION: The genes pinpointed in our research present a promising groundwork for crafting therapeutic interventions and diagnostic tools for anxiety.

Multigenerational Effect of Heat Stress on the Drosophila melanogaster Sperm Proteome.

The effect of the parental environment on offspring through non-DNA sequence-based mechanisms, such as DNA methylation, chromatin modifications, noncoding RNAs, and proteins, could only be established after the conception of "epigenetics". These effects are now broadly referred to as multigenerational epigenetic effects. Despite accumulating evidence of male gamete-mediated multigenerational epigenetic inheritance, little is known about the factors that underlie heat stress-induced multigenerational epigenetic inheritance via the male germline in Drosophila. In this study, we address this gap by utilizing an established heat stress paradigm in Drosophila and investigating its multigenerational effect on the sperm proteome. Our findings indicate that multigenerational heat stress during the early embryonic stage significantly influences proteins in the sperm associated with translation, chromatin organization, microtubule-based processes, and the generation of metabolites and energy. Assessment of life-history traits revealed that reproductive fitness and stress tolerance remained unaffected by multigenerational heat stress. Our study offers initial insights into the chromatin-based epigenetic mechanisms as a plausible means of transmitting heat stress memory through the male germline in Drosophila. Furthermore, it sheds light on the repercussions of early embryonic heat stress on male reproductive potential. The data sets from this study are available at the ProteomeXchange Consortium under the identifier PXD037488.

AlphaFind: discover structure similarity across the proteome in AlphaFold DB.

AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using a machine learning model to find the most similar structures. This indexing approach and the 3D feature extraction method used by AlphaFind have both demonstrated remarkable scalability to large datasets as well as to large protein structures. The web application itself has been designed with a focus on clarity and ease of use. The searcher accepts any valid UniProt ID, Protein Data Bank ID or gene symbol as input, and returns a set of similar protein chains from AlphaFold DB, including various similarity metrics between the query and each of the retrieved results. In addition to the main search functionality, the application provides 3D visualizations of protein structure superpositions in order to allow researchers to instantly analyze the structural similarity of the retrieved results. The AlphaFind web application is available online for free and without any registration at https://alphafind.fi.muni.cz.

ProtVar: mapping and contextualizing human missense variation.

Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.

Natural proteome diversity links aneuploidy tolerance to protein turnover.

Accessing the natural genetic diversity of species unveils hidden genetic traits, clarifies gene functions and allows the generalizability of laboratory findings to be assessed. One notable discovery made in natural isolates of Saccharomyces cerevisiae is that aneuploidy-an imbalance in chromosome copy numbers-is frequent1,2 (around 20%), which seems to contradict the substantial fitness costs and transient nature of aneuploidy when it is engineered in the laboratory3-5. Here we generate a proteomic resource and merge it with genomic1 and transcriptomic6 data for 796 euploid and aneuploid natural isolates. We find that natural and lab-generated aneuploids differ specifically at the proteome. In lab-generated aneuploids, some proteins-especially subunits of protein complexes-show reduced expression, but the overall protein levels correspond to the aneuploid gene dosage. By contrast, in natural isolates, more than 70% of proteins encoded on aneuploid chromosomes are dosage compensated, and average protein levels are shifted towards the euploid state chromosome-wide. At the molecular level, we detect an induction of structural components of the proteasome, increased levels of ubiquitination, and reveal an interdependency of protein turnover rates and attenuation. Our study thus highlights the role of protein turnover in mediating aneuploidy tolerance, and shows the utility of exploiting the natural diversity of species to attain generalizable molecular insights into complex biological processes.

New insights into the hypothalamic-pituitary-thyroid axis: a transcriptome- and proteome-wide association study.

Introduction: Thyroid hormones have systemic effects on the human body and play a key role in the development and function of virtually all tissues. They are regulated via the hypothalamic-pituitary-thyroid (HPT) axis and have a heritable component. Using genetic information, we applied tissue-specific transcriptome-wide association studies (TWAS) and plasma proteome-wide association studies (PWAS) to elucidate gene products related to thyrotropin (TSH) and free thyroxine (FT4) levels. Results: TWAS identified 297 and 113 transcripts associated with TSH and FT4 levels, respectively (25 shared), including transcripts not identified by genome-wide association studies (GWAS) of these traits, demonstrating the increased power of this approach. Testing for genetic colocalization revealed a shared genetic basis of 158 transcripts with TSH and 45 transcripts with FT4, including independent, FT4-associated genetic signals within the CAPZB locus that were differentially associated with CAPZB expression in different tissues. PWAS identified 18 and ten proteins associated with TSH and FT4, respectively (HEXIM1 and QSOX2 with both). Among these, the cognate genes of five TSH- and 7 FT4-associated proteins mapped outside significant GWAS loci. Colocalization was observed for five plasma proteins each with TSH and FT4. There were ten TSH and one FT4-related gene(s) significant in both TWAS and PWAS. Of these, ANXA5 expression and plasma annexin A5 levels were inversely associated with TSH (PWAS: P = 1.18 × 10-13, TWAS: P = 7.61 × 10-12 (whole blood), P = 6.40 × 10-13 (hypothalamus), P = 1.57 × 10-15 (pituitary), P = 4.27 × 10-15 (thyroid)), supported by colocalizations. Conclusion: Our analyses revealed new thyroid function-associated genes and prioritized candidates in known GWAS loci, contributing to a better understanding of transcriptional regulation and protein levels relevant to thyroid function.

Global Proteomic Analysis Reveals Alterations in Differentially Expressed Proteins between Cardiopathic Lamin A/C Mutations.

Lamin A/C (LMNA) is an important component of nuclear lamina. Mutations cause arrhythmia, heart failure, and sudden cardiac death. While LMNA-associated cardiomyopathy typically has an aggressive course that responds poorly to conventional heart failure therapies, there is variability in severity and age of penetrance between and even within specific mutations, which is poorly understood at the cellular level. Further, this heterogeneity has not previously been captured to mimic the heterozygous state, nor have the hundreds of clinical LMNA mutations been represented. Herein, we have overexpressed cardiopathic LMNA variants in HEK cells and utilized state-of-the-art quantitative proteomics to compare the global proteomic profiles of (1) aggregating Q353 K alone, (2) Q353 K coexpressed with WT, (3) aggregating N195 K coexpressed with WT, and (4) nonaggregating E317 K coexpressed with WT to help capture some of the heterogeneity between mutations. We analyzed each data set to obtain the differentially expressed proteins (DEPs) and applied gene ontology (GO) and KEGG pathway analyses. We found a range of 162 to 324 DEPs from over 6000 total protein IDs with differences in GO terms, KEGG pathways, and DEPs important in cardiac function, further highlighting the complexity of cardiac laminopathies. Pathways disrupted by LMNA mutations were validated with redox, autophagy, and apoptosis functional assays in both HEK 293 cells and in induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) for LMNA N195 K. These proteomic profiles expand our repertoire for mutation-specific downstream cellular effects that may become useful as druggable targets for personalized medicine approach for cardiac laminopathies.

Proteome partitioning constraints in long-term laboratory evolution.

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters. Here, we ask whether this same framework, operating at a level between genotype and fitness, informs physiological changes that occur on evolutionary timescales. Using a strain adapted to growth in glucose minimal medium, we find that the proteome is substantially remodeled over 40 000 generations. The most striking change is an apparent increase in enzyme efficiency, particularly in the enzymes of lower-glycolysis. We propose that deletion of metabolic flux-sensing regulation early in the adaptation results in increased enzyme saturation and can account for the observed proteome remodeling.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast.

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

AlphaFun: Structural-Alignment-Based Proteome Annotation Reveals why the Functionally Unknown Proteins (uPE1) Are So Understudied.

With the rapid expansion of sequencing of genomes, the functional annotation of proteins becomes a bottleneck in understanding proteomes. The Chromosome-centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome and find functional annotations for them. However, until now there are still 1137 identified human proteins without functional annotation, called uPE1 proteins. Sequence alignment was insufficient to predict their functions, and the crystal structures of most proteins were unavailable. In this study, we demonstrated a new functional annotation strategy, AlphaFun, based on structural alignment using deep-learning-predicted protein structures. Using this strategy, we functionally annotated 99% of the human proteome, including the uPE1 proteins and missing proteins, which have not been identified yet. The accuracy of the functional annotations was validated using the known-function proteins. The uPE1 proteins shared similar functions to the known-function PE1 proteins and tend to express only in very limited tissues. They are evolutionally young genes and thus should conduct functions only in specific tissues and conditions, limiting their occurrence in commonly studied biological models. Such functional annotations provide hints for functional investigations on the uPE1 proteins. This proteome-wide-scale functional annotation strategy is also applicable to any other species.

Freshwater genome-reduced bacteria exhibit pervasive episodes of adaptive stasis.

The emergence of bacterial species is rooted in their inherent potential for continuous evolution and adaptation to an ever-changing ecological landscape. The adaptive capacity of most species frequently resides within the repertoire of genes encoding the secreted proteome (SP), as it serves as a primary interface used to regulate survival/reproduction strategies. Here, by applying evolutionary genomics approaches to metagenomics data, we show that abundant freshwater bacteria exhibit biphasic adaptation states linked to the eco-evolutionary processes governing their genome sizes. While species with average to large genomes adhere to the dominant paradigm of evolution through niche adaptation by reducing the evolutionary pressure on their SPs (via the augmentation of functionally redundant genes that buffer mutational fitness loss) and increasing the phylogenetic distance of recombination events, most of the genome-reduced species exhibit a nonconforming state. In contrast, their SPs reflect a combination of low functional redundancy and high selection pressure, resulting in significantly higher levels of conservation and invariance. Our findings indicate that although niche adaptation is the principal mechanism driving speciation, freshwater genome-reduced bacteria often experience extended periods of adaptive stasis. Understanding the adaptive state of microbial species will lead to a better comprehension of their spatiotemporal dynamics, biogeography, and resilience to global change.

Yak genome database: a multi-omics analysis platform.

BACKGROUND: The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION: The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION: This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

TOPMed imputed genomics enhances genomic atlas of the human proteome in brain, cerebrospinal fluid, and plasma.

Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community.

Integrated Transcriptome and Proteome Analysis Reveals the Regulatory Mechanism of Root Growth by Protein Disulfide Isomerase in Arabidopsis.

Protein disulfide isomerase (PDI, EC 5.3.4.1) is a thiol-disulfide oxidoreductase that plays a crucial role in catalyzing the oxidation and rearrangement of disulfides in substrate proteins. In plants, PDI is primarily involved in regulating seed germination and development, facilitating the oxidative folding of storage proteins in the endosperm, and also contributing to the formation of pollen. However, the role of PDI in root growth has not been previously studied. This research investigated the impact of PDI gene deficiency in plants by using 16F16 [2-(2-Chloroacetyl)-2,3,4,9-tetrahydro-1-methyl-1H-pyrido[3,4-b]indole-1-carboxylic acid methyl ester], a small-molecule inhibitor of PDI, to remove functional redundancy. The results showed that the growth of Arabidopsis roots was significantly inhibited when treated with 16F16. To further investigate the effects of 16F16 treatment, we conducted expression profiling of treated roots using RNA sequencing and a Tandem Mass Tag (TMT)-based quantitative proteomics approach at both the transcriptomic and proteomic levels. Our analysis revealed 994 differentially expressed genes (DEGs) at the transcript level, which were predominantly enriched in pathways associated with "phenylpropane biosynthesis", "plant hormone signal transduction", "plant-pathogen interaction" and "starch and sucrose metabolism" pathways. Additionally, we identified 120 differentially expressed proteins (DEPs) at the protein level. These proteins were mainly enriched in pathways such as "phenylpropanoid biosynthesis", "photosynthesis", "biosynthesis of various plant secondary metabolites", and "biosynthesis of secondary metabolites" pathways. The comprehensive transcriptome and proteome analyses revealed a regulatory network for root shortening in Arabidopsis seedlings under 16F16 treatment, mainly involving phenylpropane biosynthesis and plant hormone signal transduction pathways. This study enhances our understanding of the significant role of PDIs in Arabidopsis root growth and provides insights into the regulatory mechanisms of root shortening following 16F16 treatment.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.