The question of how genomic information is expressed to determine phenotypes is of central importance for basic and translational life science research and has been studied by transcriptomic and proteomic profiling. Here, we review the relationship between protein and mRNA levels under various scenarios, such as steady state, long-term state changes, and short-term adaptation, demonstrating the complexity of gene expression regulation, especially during dynamic transitions. The spatial and temporal variations of mRNAs, as well as the local availability of resources for protein biosynthesis, strongly influence the relationship between protein levels and their coding transcripts. We further discuss the buffering of mRNA fluctuations at the level of protein concentrations. We conclude that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways.

Plant nucleotide binding/leucine-rich repeat (NLR) immune receptors are activated by pathogen effectors to trigger host defenses and cell death. Toll-interleukin 1 receptor domain NLRs (TNLs) converge on the ENHANCED DISEASE SUSCEPTIBILITY1 (EDS1) family of lipase-like proteins for all resistance outputs. In Arabidopsis (Arabidopsis thaliana) TNL-mediated immunity, AtEDS1 heterodimers with PHYTOALEXIN DEFICIENT4 (AtPAD4) transcriptionally induced basal defenses. AtEDS1 uses the same surface to interact with PAD4-related SENESCENCE-ASSOCIATED GENE101 (AtSAG101), but the role of AtEDS1-AtSAG101 heterodimers remains unclear. We show that AtEDS1-AtSAG101 functions together with N REQUIRED GENE1 (AtNRG1) coiled-coil domain helper NLRs as a coevolved TNL cell death-signaling module. AtEDS1-AtSAG101-AtNRG1 cell death activity is transferable to the Solanaceous species Nicotiana benthamiana and cannot be substituted by AtEDS1-AtPAD4 with AtNRG1 or AtEDS1-AtSAG101 with endogenous NbNRG1. Analysis of EDS1-family evolutionary rate variation and heterodimer structure-guided phenotyping of AtEDS1 variants and AtPAD4-AtSAG101 chimeras identify closely aligned ɑ-helical coil surfaces in the AtEDS1-AtSAG101 partner C-terminal domains that are necessary for reconstituted TNL cell death signaling. Our data suggest that TNL-triggered cell death and pathogen growth restriction are determined by distinctive features of EDS1-SAG101 and EDS1-PAD4 complexes and that these signaling machineries coevolved with other components within plant species or clades to regulate downstream pathways in TNL immunity.

An analysis is presented of the factors controlling the potential for the long-range transport (LRT) of persistent organic pollutants subject to degrading reactions and reversible transport to other environmental media. The approach adopted generalizes those developed previously by van Pul et al. and Bennett et al. to estimate a characteristic travel distance (CTD) or a "half-distance" (analogous to a half-life) for a substance present in a mobile medium such as air and subject to reversible transport to other media such as soil and water. For substances discharged to immobile media, such as pesticides to soil, an effective travel distance (ETD) is defined as the distance that, for example, 1% of the discharged chemical may be transported. It is shown that existing multimedia "box" models can be used to estimate CTD and that a simple relationship exists between CTD and overall environmental persistence, which can be displayed graphically. CTDs in air and water are calculated illustratively for 18 chemicals, and recommendations are made regarding ranking or grouping chemicals according to their potential for LRT.

Summary Lifespan is a remarkably diverse trait ranging from a few days to several hundred years in nature, but the mechanisms underlying the evolution of lifespan differences remain elusive. Here we de novo assemble a reference genome for the naturally short-lived African turquoise killifish, providing a unique resource for comparative and experimental genomics. The identification of genes under positive selection in this fish reveals potential candidates to explain its compressed lifespan. Several aging genes are under positive selection in this short-lived fish and long-lived species, raising the intriguing possibility that the same gene could underlie evolution of both compressed and extended lifespans. Comparative genomics and linkage analysis identify candidate genes associated with lifespan differences between various turquoise killifish strains. Remarkably, these genes are clustered on the sex chromosome, suggesting that short lifespan might have co-evolved with sex determination. Our study provides insights into the evolutionary forces that shape lifespan in nature.

Based on large-scale data for the yeast Saccharomyces cerevisiae (protein and mRNA abundance, translational status, transcript length), we investigate the relation of transcription, translation, and protein turnover on a genome-wide scale. We elucidate variations between different spatial cell compartments and functional modules by comparing protein-to-mRNA ratios, translational activity, and a novel descriptor for protein-specific degradation (protein half-life descriptor). This analysis helps to understand the cell's strategy to use transcriptional and posttranscriptional regulation mechanisms for managing protein levels. For instance, it is possible to identify modules that are subject to suppressed translation under normal conditions ("translation on demand"). In order to reduce inconsistencies between the datasets, we compiled a new reference mRNA abundance dataset and we present a novel approach to correct large microarray signals for a saturation bias. Accounting for ribosome density based on transcript length rather than ORF length improves the correlation of observed protein levels to translational activity. We discuss potential causes for the deviations of these correlations. Finally, we introduce a quantitative descriptor for protein degradation (protein half-life descriptor) and compare it to measured half-lives. The study demonstrates significant post-transcriptional control of protein levels for a number of different compartments and functional modules, which is missed when exclusively focusing on transcript levels. Molecular & Cellular Proteomics 3:1083-1092, 2004.Recent publication of high-throughput data of the yeast Saccharomyces cerevisiae (1-3) opens the possibility to analyze the relationship between protein abundance, mRNA levels, and translational status on a genome-wide scale. Often mRNA abundance is used as a surrogate for protein amounts. Most studies employing cDNA microarrays assume that a high transcription of an ORF correlates with a high abundance of the corresponding protein. Previous studies either could not find a correlation between protein and mRNA abundance (4) or the correlation was only weak (5-8). Greenbaum and coworkers (7) discuss three potential reasons for the lack of a perfect correlation between mRNA and protein levels: i) translational regulation, ii) difference of in vivo protein half-lives, and iii) the significant amount of experimental error including differences with respect to the experimental conditions. Understanding post-transcriptional regulation is crucial for correctly interpreting gene expression data. A full understanding of cell responses to external stimuli includes both transcription and translation regulation (6, 9, 10). It is important to distinguish processes regulating the overall translation (such as the total number or activity of available ribosomes) from protein-specific mechanisms of translation regulation (11-13). In addition to these translation-related mechanisms, selective degradation of proteins (protein turnover) regulates the cellula...

~200 words) 28 Plant intracellular nucleotide-binding/leucine-rich repeat (NLR) immune receptors are 29 activated by pathogen effectors to trigger host defenses and cell death. Toll-30 Interleukin1-receptor (TIR)-domain NLRs (TNLs) converge on the Enhanced Disease 31 Susceptibility1 (EDS1) family of lipase-like proteins for all resistance outputs. In 32 Arabidopsis TNL immunity, AtEDS1 heterodimers with Phytoalexin Deficient4 33 (AtPAD4) transcriptionally boost basal defense pathways. AtEDS1 uses the same 34 surface to interact with PAD4-related Senescence-Associated Gene101 (AtSAG101), 35 but the role of AtEDS1-AtSAG101 heterodimers was unclear. We show that AtEDS1-36 AtSAG101 function together with AtNRG1 coiled-coil domain helper NLRs as a 37 coevolved TNL cell death signaling module. AtEDS1-AtSAG101-AtNRG1 cell death 38 activity is transferable to the solanaceous species, Nicotiana benthamiana, and 39 cannot be substituted by AtEDS1-AtPAD4 with AtNRG1 or AtEDS1-AtSAG101 with 40 endogenous NbNRG1. Analysis of EDS1-family evolutionary rate variation and 41 heterodimer structure-guided phenotyping of AtEDS1 variants or AtPAD4-AtSAG101 42 chimeras identify closely aligned ɑ-helical coil surfaces in the AtEDS1-AtSAG101 43 partner C-terminal domains that are necessary for TNL cell death signaling. Our data 44 suggest that TNL-triggered cell death and pathogen growth restriction are determined 45 by distinctive features of EDS1-SAG101 and EDS1-PAD4 complexes and that these 46 signaling machineries coevolved with further components within plant species or 47 clades to regulate downstream pathways in TNL immunity. 48 49

BackgroundDietary restriction (DR), a reduction in food intake without malnutrition, increases most aspects of health during aging and extends lifespan in diverse species, including rodents. However, the mechanisms by which DR interacts with the aging process to improve health in old age are poorly understood. DNA methylation could play an important role in mediating the effects of DR because it is sensitive to the effects of nutrition and can affect gene expression memory over time.ResultsHere, we profile genome-wide changes in DNA methylation, gene expression and lipidomics in response to DR and aging in female mouse liver. DR is generally strongly protective against age-related changes in DNA methylation. During aging with DR, DNA methylation becomes targeted to gene bodies and is associated with reduced gene expression, particularly of genes involved in lipid metabolism. The lipid profile of the livers of DR mice is correspondingly shifted towards lowered triglyceride content and shorter chain length of triglyceride-associated fatty acids, and these effects become more pronounced with age.ConclusionsOur results indicate that DR remodels genome-wide patterns of DNA methylation so that age-related changes are profoundly delayed, while changes at loci involved in lipid metabolism affect gene expression and the resulting lipid profile.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1187-1) contains supplementary material, which is available to authorized users.