New technologies enable single-cell transcriptome analysis, mapping genome-wide expression across the human body. Here, we present an extended analysis of protein-coding genes in all major human tissues and organs, combining single-cell and bulk transcriptomics. To enhance transcriptome depth, 31 tissues were analyzed using a pooling method, identifying 557 unique cell clusters, manually annotated by marker gene expression. Genes were classified by body-wide expression and validated through antibody-based profiling. All results are available in the updated open-access Single Cell Type section of the Human Protein Atlas for genome-wide exploration of genes, proteins, and their spatial distribution in cells.

A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.

Cell lines are valuable resources as model for human biology and translational medicine. It is thus important to explore the concordance between the expression in various cell lines vis-à-vis human native and disease tissues. In this study, we investigate the expression of all human protein-coding genes in more than 1,000 human cell lines representing 27 cancer types by a genome-wide transcriptomics analysis. The cell line gene expression is compared with the corresponding profiles in various tissues, organs, single-cell types and cancers. Here, we present the expression for each cell line and give guidance for the most appropriate cell line for a given experimental study. In addition, we explore the cancer-related pathway and cytokine activity of the cell lines to aid human biology studies and drug development projects. All data are presented in an open access cell line section of the Human Protein Atlas to facilitate the exploration of all human protein-coding genes across these cell lines.

Pigs are valuable large animal models for biomedical and genetic research, but insights into the tissue- and cell-type-specific transcriptome and heterogeneity remain limited. By leveraging single-cell RNA sequencing, we generate a multiple-organ single-cell transcriptomic map containing over 200,000 pig cells from 20 tissues/organs. We comprehensively characterize the heterogeneity of cells in tissues and identify 234 cell clusters, representing 58 major cell types. In-depth integrative analysis of endothelial cells reveals a high degree of heterogeneity. We identify several functionally distinct endothelial cell phenotypes, including an endothelial to mesenchymal transition subtype in adipose tissues. Intercellular communication analysis predicts tissue- and cell type-specific crosstalk between endothelial cells and other cell types through the VEGF, PDGF, TGF-beta, and BMP pathways. Regulon analysis of single-cell transcriptome of microglia in pig and 12 other species further identifies MEF2C as an evolutionally conserved regulon in the microglia. Our work describes the landscape of single-cell transcriptomes within diverse pig organs and identifies the heterogeneity of endothelial cells and evolutionally conserved regulon in microglia.

Background: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. Results: An open-access pig expression map (www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. Conclusions: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource (www.rnaatlas.org), including a comparison to the expression of human orthologs.

A central aim of fundamental research is to create conditions necessary for fueling further research and innovation. Our understanding of basic biology is central for future developments of tools for diagnosing, monitoring, and treating disease. This doctoral thesis focuses on mapping the mammalian protein-coding gene expression in healthy cells and tissues, and annotation of genes based on their expression patterns, specificity, location, and function. This has in large part been achieved by using large scale transcriptomic and proteomic profiling to describe the gene expression landscape that defines the identities of the great diversity of cells present in mammals. Characterization of gene expression across different tissues and cell types provide fundamental tools to enable the exploration, summary, and ultimately, the annotation of the mammalian proteome, which is still incomplete.

The studies comprising this thesis have contributed to the Human Protein Atlas, an online open-access portal for proteomic and transcriptomic data, with the aim to profile each human protein-coding gene to create a spatial map of the molecular organization of the human body, providing basic tools for the scientific community. Paper I comprises an effort to catalogue all proteins that are actively secreted from cells; defining the human secretome. Paper II entails the deep characterization and annotation of the protein-coding transcriptome of 18 peripheral immune cell types. Paper III describes the, to date, most comprehensive tissue-based transcriptomic profiling of protein-coding genes in 98 tissues of the increasingly important model animal pig. Paper IV extends previous tissue-based maps of the human protein-coding genome by integration of 13 single cell transcriptome datasets. Paper V explores the human protein-coding genome in a clustering-based annotation of co-expressed genes across single cells and tissues to provide a framework for finding previously unknown functional relationships between genes by the principle of “guilt-by-association”.

In summary, the work described here entails a small contribution to the grand effort of spatially mapping proteins across tissues and cell types, for building a framework of biological knowledge that can lead to increased understanding of the constituents that make us humans.

Ett centralt mål för grundvetenskap är att skapa förutsättningar för framtida forskning och innovation. Vår förståelse för grundläggande biologi är essentiell för utveckling av verktyg för diagnosticering, uppföljning, och behandling av sjukdomar. Denna avhandling fokuserar på kartläggningen av det proteinkodande genuttrycket hos däggdjur i friska celler och vävnader, samt annoteringen av gener baserat på deras uttrycksmönster, specificitet, lokalisering, och funktion. Detta har till stor del uppnåtts genom storskalig transkriptomik- och proteomik-baserad profilering för att beskriva de genuttrycksmönster som definierar de identiteter den stora mångfalden av celler som finns i däggdjur. Karaktäriseringen av genuttryck bland vävnader och celltyper utgör viktiga verktyg för att möjliggöra utforskning, sammanställande, och slutligen, annoteringen av däggdjurs proteom som fortfarande är ofullständig. 

Studierna som utgör denna avhandling har bidragit till the Human Protein Atlas; en online-portal med fri tillgång för proteomik- och transkriptomikdata, med en målsättning att beskriva uttrycket av samtliga proteinkodande gener. Genom att skapa en karta av den molekylära organiseringen av människokroppen utgör detta projekt ett väsentligt verktyg för forskning. Artikel I utgör en katalogisering av alla proteiner som aktivt sekreteras från celler, för att definiera det mänskliga sekretomet. Artikel II handlar om en djup karaktärisering och annotering av det proteinkodande transkriptomet hos 18 perifera immuncelltyper. Artikel III beskriver den, till dagens datum, mest omfattande vävnadsbaserade kartan av proteinkodande gener i 98 vävnader i gris, som har blivit en allt viktigare modellorganism. Artikel IV utvidgar de tidigare vävnadsbaserade kartor av det proteinkodande genomet, genom att integrera 13 encellstranskriptomik-dataset. Artikel V utforskar det mänskliga proteinkodande genomet i en klustringsbaserad annotering av samuttryckta gener, för att bygga ett ramverk för att hitta tidigare okända funktionella samband mellan gener, enligt principen av ”associationsskuld”.

Arbetet beskrivet här utgör ett bidrag till det omfattande arbetet att kartlägga proteiners lokalisering i vävnader och celler, för att bygga ett ramverk av biologisk kunskap som kan leda till ökad förståelse för komponenterna som gör oss till människor. 

Advances in molecular profiling have opened up the possibility to map the expression of genes in cells, tissues, and organs in the human body. Here, we combined single-cell transcriptomics analysis with spatial antibody-based protein profiling to create a high-resolution single-cell type map of human tissues. An open access atlas has been launched to allow researchers to explore the expression of human protein-coding genes in 192 individual cell type clusters. An expression specificity classification was performed to determine the number of genes elevated in each cell type, allowing comparisons with bulk transcriptomics data. The analysis highlights distinct expression clusters corresponding to cell types sharing similar functions, both within the same organs and between organs.

Background: Preterm birth and its complications are the primary cause of death among children under the age of 5. Among the survivors, morbidity both perinatally and later in life is common. The dawn of novel technical platforms for comprehensive and sensitive analysis of protein profiles in blood has opened up new possibilities to study both health and disease with significant clinical accuracy, here used to study the preterm infant and the physiological changes of the transition from intrauterine to extrauterine life. Methods: We have performed in-depth analysis of the protein profiles of 14 extremely preterm infants using longitudinal sampling. Medical variables were integrated with extensive profiling of 448 unique protein targets. Results: The preterm infants have a distinct unified protein profile in blood directly at birth regardless of clinical background; however, the pattern changed profoundly postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age. Clusters of proteins depending on temporal trend were identified. Conclusion: The protein profiles and the temporal trends here described will contribute to the understanding of the physiological changes in the intrauterine−extrauterine transition, which is essential to adjust early-in-life interventions to prone a normal development in the vulnerable preterm infants. Impact: We have performed longitudinal and in-depth analysis of the protein profiles of 14 extremely preterm infants using a novel multiplex protein analysis platform.The preterm infants had a distinct unified protein profile in blood directly at birth regardless of clinical background.The pattern changed dramatically postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age.Certain clusters of proteins were identified depending on their temporal trend, including several liver and immune proteins.The study contributes to the understanding of the physiological changes in the intrauterine−extrauterine transition. 

Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of LDHB during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. Significance: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.

The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.