Ribosomal footprinting and RNASeq in two strains of yeast and their diploid hybrid
ABSTRACT: Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosomal footprinting to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes, more than half as many as showed genetic differences in mRNA levels. Similarly, allele specific measurements in the diploid hybrid between the two strains found roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, strong effects on translation were rare, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. Across all expressed genes, there was a tendency for translation to more often reinforce than buffer mRNA differences, resulting in footprint differences with greater magnitudes than the mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains. Overall, genetic variation clearly influences translation, but primarily does so by subtly modulating differences in mRNA levels. Translation does not appear to create strong discrepancies between genetic influences on mRNA and protein levels. Ribsosomal footprinting and RNASeq in the two yeast strains BY and RM as well as their diploid hybrid. We generated one library each for the BY and RM parents, and two libraries (biological replicates) for the hybrid data.
Project description:Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a 10-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5'-untranslated regions. Collectively, our results provide a framework for executing and interpreting ribosome-profiling studies and reveal key features of translational control in yeast. Ribosome-footprint profiling and RNA-seq (total RNA, poly(A) selected, RiboMinus treated, or Ribo-Zero treated) from log-phase S. cerevisiae. The study includes a reanalysis of the two Samples from GSE53313. The reanalyzed data is linked to the Series record.
Project description:Elucidating the extent and consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding and chromatin have been explored, little is known about global variation in translation and its genetic determinants among humans. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA levels, translation, and protein abundance suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy - many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation. Ribosome profiling and RNA sequencing experiments from human lymphoblastoid cells
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.
Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation. We measured level of translation transcriptome-wide in lymphoblastoid cell lines derived from 72 HapMap Yoruba individuals using ribosome profiling assay, for which we have transcript level, protein level (62 out of 72) and genotype information collected.
Project description:Gene expression levels are determined by the balance between rates of mRNA transcription and decay, and genetic variation in either of these processes can result in heritable differences in transcript abundance. Although the genetics of gene expression has been the subject of intense interest, the contribution of heritable variation in mRNA decay rates to gene expression variation has received far less attention. To this end, we developed a novel statistical framework and measured allele-specific differences in mRNA decay rates in a diploid yeast hybrid created by mating two genetically diverse parental strains. In total, we estimate that 31% of genes exhibit allelic differences in mRNA decay rate, of which 350 can be identified at a false discovery rate of 10%. Genes with significant allele-specific differences in mRNA decay rate have higher levels of polymorphism compared to other genes, with all gene regions contributing to allelic differences in mRNA decay rate. Strikingly, we find widespread evidence for compensatory evolution, such that variants influencing transcriptional initiation and decay having opposite effects, suggesting steady-state gene expression levels are subject to pervasive stabilizing selection. Our results demonstrate that heritable differences in mRNA decay rates are widespread, and are an important target for natural selection to maintain or fine-tune steady-state gene expression levels. We measured rates of allele-specific mRNA decay (ASD) in a diploid yeast produced by mating two genetically diverse haploid Saccharomyces cerevisiae strains: the laboratory strain BY4716 (BY), which is isogenic to the reference sequence strain S288C, and the wild Californian vineyard strain RM11-1a (RM). Briefly, we introduced rpb1-1, a temperature sensitive mutation in an RNA polymerase II subunit, to each of the haploid yeast strains, mated the strains, and grew the resulting hybrid diploid to mid-log phase at 24 °C, before rapidly shifting the culture to 37 °C to inhibit transcription. RNA-seq was performed on culture samples taken at 0, 6, 12, 18, 24, and 42 minutes subsequent to the temperature shift. To identify ASD, we used transcribed polymorphisms to distinguish between parental transcripts, and compared the relative levels of transcript abundance over the time course. Note, this experimental design internally controls for trans-acting regulatory variation as well as environmental factors. Under the null hypothesis of no ASD, the proportion of reads from the BY transcript (p_BY = N_BY / (N_BY + N_RM)) observed over the time course remains unchanged. However, genes with ASD will exhibit an increasing or decreasing proportion of BY reads as a function of time. In total, we measured ASD from three independent biological replicates.
Project description:Though sequence differences between alleles are often limited to a few polymorphisms, these differences can cause large and widespread allelic variation at the expression level. Such allele-specific expression (ASE) has been extensively explored at the level of transcription but not translation. Here we measured ASE in the diploid yeast Candida albicans at both the transcriptional and translational levels using RNA-seq and ribosome profiling, respectively. Since C. albicans is an obligate diploid, our analysis isolates ASE arising from cis elements in a natural, non-hybrid organism, where allelic effects reflect evolutionary forces. Importantly, we find that ASE arising from translation is of a similar magnitude as transcriptional ASE, both in terms of the number of genes affected and the magnitude of the bias. We further observe coordination between ASE at the levels of transcription and translation for single genes. Specifically, reinforcing relationships—where transcription and translation favor the same allele—are more frequent than expected by chance, consistent with selective pressure tuning ASE at multiple regulatory steps. Finally, we parameterize alleles based on a range of properties and find that SNP location and predicted mRNA-structure stability are associated with translational ASE in cis. Since this analysis probes more than 4,000 allelic pairs spanning a broad range of variations, our data provide a genome-wide view into the relative impacts of cis elements that regulate translation. Two biological replicates of WT Candida albicans ribosome profiling and RNA-seq
Project description:Translational control of gene expression plays essential roles in cellular stress responses and organismal development by enabling rapid, selective, and localized control of protein production. Translational regulation depends on context-dependent differences in the protein output of mRNAs, but the key mRNA features that distinguish efficiently translated mRNAs are largely unknown. Here we comprehensively determined the RNA-binding preferences of the initiation factor eIF4G to assess whether this core translation initiation factor has intrinsic sequence preferences that contribute to preferential translation of specific mRNAs. Overall design: Ribosome footprint profiling of eIF4G depleted yeast cells
Project description:During translation elongation, the ribosome ratchets along its mRNA template, incorporating each new amino acid and translocating from one codon to the next. The elongation cycle requires dramatic structural rearrangements of the ribosome. We show here that deep sequencing of ribosome-protected mRNA fragments reveals not only the position of each ribosome but also, unexpectedly, its particular stage of the elongation cycle. Sequencing reveals two distinct populations of ribosome footprints, 28-30 nucleotides and 20-22 nucleotides long, representing translating ribosomes in distinct states, differentially stabilized by specific elongation inhibitors. We find that the balance of small and large footprints varies by codon and is correlated with translation speed. The ability to visualize conformational changes in the ribosome during elongation, at single-codon resolution, provides a new way to study the detailed kinetics of translation and a new probe with which to identify the factors that affect each step in the elongation cycle. Ribosome profiling, or sequencing of ribosome-protected mRNA fragments, in yeast. We assay ribosome footprint sizes and positions in three conditions: untreated yeast (3 replicates) and yeast treated with translation inhibitors cycloheximide (2 replicates) and anisomycin (2 biological replicates, one technical replicate). We also treat yeast with 3-aminotriazole to measure the effect of limited histidine tRNAs on ribosome footprint size and distribution (two treatment durations).
Project description:Copy number variants (CNVs) represent a substantial source of genomic variation in vertebrates, but the zebrafish reference genome has no annotated CNV information. We developed a zebrafish CNV map using 80 zebrafish genomes from laboratory strains (AB, Tubingen, and WIK) and one native population, identifying 6,080 CNV elements. Overlapping or adjacent CNVs account for 14.6% of the genome, representing four times the CNV levels from other vertebrates including humans. Highest intra-specific CNV levels were observed for Tubingen, a common laboratory strain due to high fecundity. Tubingen variation likely represents higher initial population size and composite population founders initiating the laboratory strain. Extensive zebrafish CNVs, along with associated phenotypic impacts, advocates for increased usage of isogenic strains for genetic studies intended for human disease translation. Overall design: 7 full sib adult hybrid fish used for expression Quantatitive Trait Loci (eQLT) analysis to support CNV affects on gene expresion in zebrafish.
Project description:Genetic variation governs protein expression through both transcriptional and post-transcriptional processes. To investigate this relationship, we combined a multiplexed, mass spectrometry-based method for protein quantification with an emerging mouse model harboring extensive genetic variation from 8 founder strains. We collected genome-wide mRNA and protein profiling measurements to link genetic variation to protein expression differences in livers from 192 diversity outcross mice. We observed nearly 3,700 protein-level quantitative trait loci (pQTL) with an equal proportion of proteins regulated directly by their cognate mRNA as uncoupled from their transcript. Our analysis reveals an extensive array of at least five models for genetic variant control of protein abundance including direct protein-to-protein associations that act to achieve stoichiometric balance of functionally related enzymes and subunits of multimeric complexes.