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There is a need for standardized validation methods for antibody specificity and selectivity. Recently, five alternative validation pillars were proposed to explore the specificity of research antibodies using methods with no need for prior knowledge about the protein target. Here, we show that these principles can be used in a streamlined manner for enhanced validation of research antibodies in Western blot applications. More than 6,000 antibodies were validated with at least one of these strategies involving orthogonal methods, genetic knockdown, recombinant expression, independent antibodies, and capture mass spectrometry analysis. The results show a path forward for efforts to validate antibodies in an application-specific manner suitable for both providers and users.

Antibodies are crucial for the study of human proteins and have been defined as one of the three pillars in the human chromosome-centric Human Proteome Project (C-HPP). In this article the chromosome-centric structure has been used to analyze the availability of antibodies as judged by the presence within the portal Antibodypedia, a database designed to allow comparisons and scoring of publicly available antibodies toward human protein targets. This public database displays antibody data from more than one million antibodies toward human protein targets. A summary of the content in this knowledge resource reveals that there exist more than 10 antibodies to over 70% of all the putative human genes, evenly distributed over the 24 human chromosomes. The analysis also shows that at present, less than 10% of the putative human protein-coding genes (n = 1882) predicted from the genome sequence lack antibodies, suggesting that focused efforts from the antibody-based and mass spectrometry-based proteomic communities should be encouraged to pursue the analysis of these missing proteins. We show that Antibodypedia may be used to track the development of available and validated antibodies to the individual chromosomes, and thus the database is an attractive tool to identify proteins with no or few antibodies yet generated.

Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ∼80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.

A gene-centric Human Proteome Project has been proposed to characterize the human protein-coding genes in a chromosome-centered manner to understand human biology and disease. Here, we report on the protein evidence for all genes predicted from the genome sequence based on manual annotation from literature (UniProt), antibody-based profiling in cells, tissues and organs and analysis of the transcript profiles using next generation sequencing in human cell lines of different origins. We estimate that there is good evidence for protein existence for 69% (n = 13985) of the human protein-coding genes, while 23% have only evidence on the RNA level and 7% still lack experimental evidence. Analysis of the expression patterns shows few tissue-specific proteins and approximately half of the genes expressed in all the analyzed cells. The status for each gene with regards to protein evidence is visualized in a chromosome-centric manner as part of a new version of the Human Protein Atlas ( www.proteinatlas.org ).