Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics

Abstract

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 ϳ80% 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. Molecular & Cellular Proteomics 13: 10.1074/mcp.M113.035600, 397-406, 2014.Central questions in human biology relate to how cells, tissues, and organs differ in the expression of genes and proteins and what consequences the global expression pattern has for the phenotype of various cells with different functions in the body. Therefore, the annotation of the human protein-coding genes with regards to the spatial, temporal, and functional space represents one of the greatest challenges in human biology (1). Important questions related to this are how many of the genes actually code for functional proteins, how many are expressed in a tissue-specific manner, and how many proteins have "housekeeping" functions and are therefore expressed in all cells? These questions have a major impact not only on efforts to try to understand human biology, but also for applied medical research, such as pharmaceutical drug development and biomarker discovery in the field of translational medicine.Several efforts have been initiated in the aftermath of the genome project to systematically annotate the putative protein-coding part of the human genome. Genome annotation efforts, such as Ensembl (2) and RefSeq (3), have provided an increasingly accurate map with at present ϳ20,000 proteincoding genes. Similarly, the ENCODE consortium has been launched to provide an integrated encyclopedia of DNA eleFrom the ‡Science for Life Laboratory, KTH -Royal Institute of Technology, SE-171 21 Stockholm, Sweden; §Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden; ¶Department

Generation and characterization of a high affinity anti-human FcRn antibody, rozanolixizumab, and the effects of different molecular formats on the reduction of plasma IgG concentration

“…The expression of FcRn in multiple tissues was consistent with published data. 40-44 There was good concordance of staining patterns between humans and cynomolgus monkeys (results not shown), providing further evidence (together with the comparable binding and pharmacology data) that the cynomolgus monkey was the most relevant species to assess the safety of rozanolixizumab prior to the first-in-human study.…”

Effects of maternal nutrition on the expression of genomic imprinted genes in ovine fetuses

“…Although it was nearly negligible in the brain and kidney, it was highly expressed in the lung in ovine fetuses (Figure 7). Such expression was also observed in human tissues [41]. …”

The landscape of human mutually exclusive splicing

“…To validate the predicted MXE candidates, we made use of over 15 billion publically available RNA‐Seq reads, selecting 515 samples comprising 31 tissues and organs, 12 cell lines and seven developmental stages (Barbosa‐Morais et al , 2012; Djebali et al , 2012; Tilgner et al , 2012; Xue et al , 2013; Yan et al , 2013; Fagerberg et al , 2014; Dataset EV1). The data were chosen to encompass common and rare potential splice events in a broad range of tissues, cell types and embryonic stages.…”

“…To understand the expression patterns of MXEs, we conducted a differential inclusion analysis using the Human Protein Atlas (Fagerberg et al , 2014), Embryonic Development (Yan et al , 2013) and ENCODE datasets (Djebali et al , 2012). Of the 1,399 MXEs, 608 MXEs (345 unique genes), 573 MXEs (389 unique genes) and 552 MXEs (330 unique genes) are differentially expressed, respectively (adjusted P ‐value < 0.05; Fig 3A, Appendix Figs S23–S26, Dataset EV5 and EV6).…”