SummaryGene expression is a multistep process that involves transcription, translation and turnover of mRNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here, we simultaneously measured mRNA and protein abundance and turnover by parallel metabolic pulse labeling for more than 5,000 genes in mammalian cells. While mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Employing a quantitative model we obtain the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stabilities shared functional properties, suggesting that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression obtained in this study provides a rich resource and helps understanding the underlying design principles.

Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes.

Protein-RNA interactions are fundamental to core biological processes, such as mRNA splicing, localization, degradation, and translation. We developed a photoreactive nucleotide-enhanced UV crosslinking and oligo(dT) purification approach to identify the mRNA-bound proteome using quantitative proteomics and to display the protein occupancy on mRNA transcripts by next-generation sequencing. Application to a human embryonic kidney cell line identified close to 800 proteins. To our knowledge, nearly one-third were not previously annotated as RNA binding, and about 15% were not predictable by computational methods to interact with RNA. Protein occupancy profiling provides a transcriptome-wide catalog of potential cis-regulatory regions on mammalian mRNAs and showed that large stretches in 3' UTRs can be contacted by the mRNA-bound proteome, with numerous putative binding sites in regions harboring disease-associated nucleotide polymorphisms. Our observations indicate the presence of a large number of mRNA binders with diverse molecular functions participating in combinatorial posttranscriptional gene-expression networks.

Posttranscriptional gene regulation relies on hundreds of RNA binding proteins (RBPs) but the function of most RBPs is unknown. The human RBP HuR/ELAVL1 is a conserved mRNA stability regulator. We used PAR-CLIP, a recently developed method based on RNA-protein crosslinking, to identify transcriptome-wide ∼26,000 HuR binding sites. These sites were on average highly conserved, enriched for HuR binding motifs and mainly located in 3' untranslated regions. Surprisingly, many sites were intronic, implicating HuR in mRNA processing. Upon HuR knockdown, mRNA levels and protein synthesis of thousands of target genes were downregulated, validating functionality. HuR and miRNA binding sites tended to reside nearby but generally did not overlap. Additionally, HuR knockdown triggered strong and specific upregulation of miR-7. In summary, we identified thousands of direct and functional HuR targets, found a human miRNA controlled by HuR, and propose a role for HuR in splicing.

MaxQuant is a quantitative proteomics software package designed for analyzing large mass spectrometric data sets. It is specifically aimed at high-resolution mass spectrometry (MS) data. Currently, Thermo LTQ-Orbitrap and LTQ-FT-ICR instruments are supported and Mascot is used as a search engine. This protocol explains step by step how to use MaxQuant on stable isotope labeling by amino acids in cell culture (SILAC) data obtained with double or triple labeling. Complex experimental designs, such as time series and drug-response data, are supported. A standard desktop computer is sufficient to fulfill the computational requirements. The workflow has been stress tested with more than 1,000 liquid chromatography/mass spectrometry runs in a single project. In a typical SILAC proteome experiment, hundreds of thousands of peptides and thousands of proteins are automatically and reliably quantified. Additional information for identified proteins, such as Gene Ontology, domain composition and pathway membership, is provided in the output tables ready for further bioinformatics analysis. The software is freely available at the MaxQuant home page.

Intron retention (IR) is widely recognized as a consequence of mis-splicing that leads to failed excision of intronic sequences from pre-messenger RNAs. Our bioinformatic analyses of transcriptomic and proteomic data of normal white blood cell differentiation reveal IR as a physiological mechanism of gene expression control. IR regulates the expression of 86 functionally related genes, including those that determine the nuclear shape that is unique to granulocytes. Retention of introns in specific genes is associated with downregulation of splicing factors and higher GC content. IR, conserved between human and mouse, led to reduced mRNA and protein levels by triggering the nonsense-mediated decay (NMD) pathway. In contrast to the prevalent view that NMD is limited to mRNAs encoding aberrant proteins, our data establish that IR coupled with NMD is a conserved mechanism in normal granulopoiesis. Physiological IR may provide an energetically favorable level of dynamic gene expression control prior to sustained gene translation.

Dendritic cell (DC) populations consist of multiple subsets that are essential orchestrators of the immune system. Technological limitations have so far prevented systems-wide accurate proteome comparison of rare cell populations in vivo. Here, we used high-resolution mass spectrometry-based proteomics, combined with label-free quantitation algorithms, to determine the proteome of mouse splenic conventional and plasmacytoid DC subsets to a depth of 5,780 and 6,664 proteins, respectively. We found mutually exclusive expression of pattern recognition pathways not previously known to be different among conventional DC subsets. Our experiments assigned key viral recognition functions to be exclusively expressed in CD4(+) and double-negative DCs. The CD8alpha(+) DCs largely lack the receptors required to sense certain viruses in the cytoplasm. By avoiding activation via cytoplasmic receptors, including retinoic acid-inducible gene I, CD8alpha(+) DCs likely gain a window of opportunity to process and present viral antigens before activation-induced shutdown of antigen presentation pathways occurs.

RNA-sequencing protocols can quantify gene expression regulation from transcription to protein synthesis. Ribosome profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. We have developed RiboTaper (available at https://ohlerlab.mdc-berlin.de/software/), a rigorous statistical approach that identifies translated regions on the basis of the characteristic three-nucleotide periodicity of Ribo-seq data. We used RiboTaper with deep Ribo-seq data from HEK293 cells to derive an extensive map of translation that covered open reading frame (ORF) annotations for more than 11,000 protein-coding genes. We also found distinct ribosomal signatures for several hundred upstream ORFs and ORFs in annotated noncoding genes (ncORFs). Mass spectrometry data confirmed that RiboTaper achieved excellent coverage of the cellular proteome. Although dozens of novel peptide products were validated in this manner, few of the currently annotated long noncoding RNAs appeared to encode stable polypeptides. RiboTaper is a powerful method for comprehensive de novo identification of actively used ORFs from Ribo-seq data.