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.

microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented sensitivity, but the computational task of accurately identifying the miRNAs in the background of sequenced RNAs remains challenging. For this purpose, we have designed miRDeep2, a substantially improved algorithm which identifies canonical and non-canonical miRNAs such as those derived from transposable elements and informs on high-confidence candidates that are detected in multiple independent samples. Analyzing data from seven animal species representing the major animal clades, miRDeep2 identified miRNAs with an accuracy of 98.6–99.9% and reported hundreds of novel miRNAs. To test the accuracy of miRDeep2, we knocked down the miRNA biogenesis pathway in a human cell line and sequenced small RNAs before and after. The vast majority of the >100 novel miRNAs expressed in this cell line were indeed specifically downregulated, validating most miRDeep2 predictions. Last, a new miRNA expression profiling routine, low time and memory usage and user-friendly interactive graphic output can make miRDeep2 useful to a wide range of researchers.

Caenorhabditis elegans is one of the most prominent model systems for embryogenesis. However, it has been impractical to collect large amounts of precisely staged embryos. Thus, early C. elegans embryogenesis has not been amenable to most modern high-throughput genomics or biochemistry assays. To overcome this problem, we devised a method to collect large amounts of staged C. elegans embryos by Fluorescent Activated Cell Sorting (termed eFACS). eFACS can in principle be applied to all embryonic stages. As a proof of principle we show that a single eFACS run routinely yields tens of thousands of almost perfectly staged one-cell embryos. Since the earliest embryonic events are driven by post-transcriptional regulation, we combined eFACS with next-generation sequencing to profile the embryonic expression of small, non-coding RNAs. We discovered complex and orchestrated changes in the expression between and within almost all classes of small RNAs, including miRNAs and 26G-RNAs, during embryogenesis.

Balanced chromosome rearrangements (BCRs) can cause genetic diseases by disrupting or inactivating specific genes, and the characterization of breakpoints in disease-associated BCRs has been instrumental in the molecular elucidation of a wide variety of genetic disorders. However, mapping chromosome breakpoints using traditional methods, such as in situ hybridization with fluorescent dye-labeled bacterial artificial chromosome clones (BAC-FISH), is rather laborious and time-consuming. In addition, the resolution of BAC-FISH is often insufficient to unequivocally identify the disrupted gene. To overcome these limitations, we have performed shotgun sequencing of flow-sorted derivative chromosomes using “next-generation” (Illumina/Solexa) multiplex sequencing-by-synthesis technology. As shown here for three different disease-associated BCRs, the coverage attained by this platform is sufficient to bridge the breakpoints by PCR amplification, and this procedure allows the determination of their exact nucleotide positions within a few weeks. Its implementation will greatly facilitate large-scale breakpoint mapping and gene finding in patients with disease-associated balanced translocations.

Mechanisms controlling human multipotent mesenchymal (stromal) stem cell (hMSC) differentiation into osteoblasts or adipocytes are poorly understood. We have previously demonstrated that Wnt signaling in hMSC enhanced osteoblast differentiation and inhibited adipogenesis by comparing two hMSC cell lines overexpressing mutated forms of the Wnt co-receptor LRP5: T253I (hMSC-LRP5 T253 ) and T244M (hMSC-LRP5 T244 ) conducting high and low level of Wnt signaling, respectively. To explore the underlying molecular mechanisms, we compared gene expression profiles of hMSC-LRP5 T253 and hMSC-LRP5 T244 treated with Wnt3a using whole genome expression microarrays and found that TNFRSF19 is differentially up-regulated between the two cells lines. Bioinformatic analysis and dual luciferase assay of its promoter revealed that TNFRSF19 transcript 2 (TNFRSF19.2) is a target of canonical Wnt signaling. Knocking down TNFRSF19 in hMSC-LRP5 T253 cells decreased Wnt3a-induced osteoblast differentiation marker alkaline phosphate activity and its overexpression in hMSC-LRP5 T244 cells increased alkaline phosphate activity. In addition, TNFRSF19 was negatively regulated by adipogenic transcription factor CCAAT/enhancer-binding proteins (C/EBP). Knocking down TNFRSF19 in hMSC-LRP5 T253 cells or its overexpression in hMSC-LRP5 T244 cells significantly increased or decreased adipogenesis, respectively. In conclusion, we revealed a novel function of TNFRSF19 as a factor mediating differentiation signals that determine the hMSC differentiating fate into osteoblasts or adipocytes.