PLoS Genetics最新文献

Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.

The chloroplast proteome is a dynamic mosaic of plastid- and nuclear-encoded proteins. Plastid protein homeostasis is maintained through the balance between de novo synthesis and proteolysis. Intracellular communication pathways, including the plastid-to-nucleus signalling and the protein homeostasis machinery, made of stromal chaperones and proteases, shape chloroplast proteome based on developmental and physiological needs. However, the maintenance of fully functional chloroplasts is costly and under specific stress conditions the degradation of damaged chloroplasts is essential to the maintenance of a healthy population of photosynthesising organelles while promoting nutrient redistribution to sink tissues. In this work, we have addressed this complex regulatory chloroplast-quality-control pathway by modulating the expression of two nuclear genes encoding plastid ribosomal proteins PRPS1 and PRPL4. By transcriptomics, proteomics and transmission electron microscopy analyses, we show that the increased expression of PRPS1 gene leads to chloroplast degradation and early flowering, as an escape strategy from stress. On the contrary, the overaccumulation of PRPL4 protein is kept under control by increasing the amount of plastid chaperones and components of the unfolded protein response (cpUPR) regulatory mechanism. This study advances our understanding of molecular mechanisms underlying chloroplast retrograde communication and provides new insights into cellular responses to impaired plastid protein homeostasis.

Organisms have evolved elaborate physiological pathways that regulate growth, proliferation, metabolism, and stress response. These pathways must be properly coordinated to elicit the appropriate response to an ever-changing environment. While individual pathways have been well studied in a variety of model systems, there remains much to uncover about how pathways are integrated to produce systemic changes in a cell, especially in dynamic conditions. We previously showed that deletion of Protein Kinase A (PKA) regulatory subunit BCY1 can decouple growth and metabolism in Saccharomyces cerevisiae engineered for anaerobic xylose fermentation, allowing for robust fermentation in the absence of division. This provides an opportunity to understand how PKA signaling normally coordinates these processes. Here, we integrated transcriptomic, lipidomic, and phospho-proteomic responses upon a glucose to xylose shift across a series of strains with different genetic mutations promoting either coupled or decoupled xylose-dependent growth and metabolism. Together, results suggested that defects in lipid homeostasis limit growth in the bcy1Δ strain despite robust metabolism. To further understand this mechanism, we performed adaptive laboratory evolutions to re-evolve coupled growth and metabolism in the bcy1Δ parental strain. The evolved strain harbored mutations in PKA subunit TPK1 and lipid regulator OPI1, among other genes, and evolved changes in lipid profiles and gene expression. Deletion of the evolved opi1 gene partially reverted the strain's phenotype to the bcy1Δ parent, with reduced growth and robust xylose fermentation. We suggest several models for how cells coordinate growth, metabolism, and other responses in budding yeast and how restructuring these processes enables anaerobic xylose utilization.

While it has been appreciated for decades that prophase-arrested oocytes are transcriptionally silenced on a global level, the molecular pathways that promote silencing have remained elusive. Previous work in C. elegans has shown that both topoisomerase II (TOP-2) and condensin II collaborate with the H3K9me heterochromatin pathway to silence gene expression in the germline during L1 starvation, and that the PIE-1 protein silences the genome in the P-lineage of early embryos. Here, we show that all three of these silencing systems, TOP-2/condensin II, H3K9me, and PIE-1, are required for transcriptional repression in oocytes. We find that H3K9me3 marks increase dramatically on chromatin during silencing, and that silencing is under cell cycle control. We also find that PIE-1 localizes to the nucleolus just prior to silencing, and that nucleolar dissolution during silencing is dependent on TOP-2/condensin II. Our data identify both the molecular components and the trigger for genome silencing in oocytes and establish a link between PIE-1 nucleolar residency and its ability to repress transcription.

Predicting phenotypes from genotypes is a fundamental task in quantitative genetics. With technological advances, it is now possible to measure multiple phenotypes in large samples. Multiple phenotypes can share their genetic component; therefore, modeling these phenotypes jointly may improve prediction accuracy by leveraging effects that are shared across phenotypes. However, effects can be shared across phenotypes in a variety of ways, so computationally efficient statistical methods are needed that can accurately and flexibly capture patterns of effect sharing. Here, we describe new Bayesian multivariate, multiple regression methods that, by using flexible priors, are able to model and adapt to different patterns of effect sharing and specificity across phenotypes. Simulation results show that these new methods are fast and improve prediction accuracy compared with existing methods in a wide range of settings where effects are shared. Further, in settings where effects are not shared, our methods still perform competitively with state-of-the-art methods. In real data analyses of expression data in the Genotype Tissue Expression (GTEx) project, our methods improve prediction performance on average for all tissues, with the greatest gains in tissues where effects are strongly shared, and in the tissues with smaller sample sizes. While we use gene expression prediction to illustrate our methods, the methods are generally applicable to any multi-phenotype applications, including prediction of polygenic scores and breeding values. Thus, our methods have the potential to provide improvements across fields and organisms.

Non-linear Mendelian randomization is an extension to standard Mendelian randomization to explore the shape of the causal relationship between an exposure and outcome using an instrumental variable. A stratification approach to non-linear Mendelian randomization divides the population into strata and calculates separate instrumental variable estimates in each stratum. However, the standard implementation of stratification, referred to as the residual method, relies on strong parametric assumptions of linearity and homogeneity between the instrument and the exposure to form the strata. If these stratification assumptions are violated, the instrumental variable assumptions may be violated in the strata even if they are satisfied in the population, resulting in misleading estimates. We propose a new stratification method, referred to as the doubly-ranked method, that does not require strict parametric assumptions to create strata with different average levels of the exposure such that the instrumental variable assumptions are satisfied within the strata. Our simulation study indicates that the doubly-ranked method can obtain unbiased stratum-specific estimates and appropriate coverage rates even when the effect of the instrument on the exposure is non-linear or heterogeneous. Moreover, it can also provide unbiased estimates when the exposure is coarsened (that is, rounded, binned into categories, or truncated), a scenario that is common in applied practice and leads to substantial bias in the residual method. We applied the proposed doubly-ranked method to investigate the effect of alcohol intake on systolic blood pressure, and found evidence of a positive effect of alcohol intake, particularly at higher levels of alcohol consumption.

Retroviruses and closely related LTR retrotransposons export full-length, unspliced genomic RNA (gRNA) for packaging into virions and to serve as the mRNA encoding GAG and POL polyproteins. Because gRNA often includes splice acceptor and donor sequences used to splice viral mRNAs, retroelements must overcome host mechanisms that retain intron-containing RNAs in the nucleus. Here we examine gRNA expression in Cer1, an LTR retrotransposon in C. elegans which somehow avoids silencing and is highly expressed in germ cells. Newly exported Cer1 gRNA associates rapidly with the Cer1 GAG protein, which has structural similarity with retroviral GAG proteins. gRNA export requires CERV (C. elegans regulator of viral expression), a novel protein encoded by a spliced Cer1 mRNA. CERV phosphorylation at S214 is essential for gRNA export, and phosphorylated CERV colocalizes with nuclear gRNA at presumptive sites of transcription. By electron microscopy, tagged CERV proteins surround clusters of distinct, linear fibrils that likely represent gRNA molecules. Single fibrils, or groups of aligned fibrils, also localize near nuclear pores. During the C. elegans self-fertile period, when hermaphrodites fertilize oocytes with their own sperm, CERV concentrates in two nuclear foci that are coincident with gRNA. However, as hermaphrodites cease self-fertilization, and can only produce cross-progeny, CERV undergoes a remarkable transition to form giant nuclear rods or cylinders that can be up to 5 microns in length. We propose a novel mechanism of rod formation, in which stage-specific changes in the nucleolus induce CERV to localize to the nucleolar periphery in flattened streaks of protein and gRNA; these streaks then roll up into cylinders. The rods are a widespread feature of Cer1 in wild strains of C. elegans, but their function is not known and might be limited to cross-progeny. We speculate that the adaptive strategy Cer1 uses for the identical self-progeny of a host hermaphrodite might differ for heterozygous cross-progeny sired by males. For example, mating introduces male chromosomes which can have different, or no, Cer1 elements.

In prostate cancer, loss of the tumour suppressor gene, Retinoblastoma (Rb), and consequent activation of transcription factor E2F1 typically occurs at a late-stage of tumour progression. It appears to regulate a switch to an androgen-independent form of cancer, castration-resistant prostate cancer (CRPC), which frequently still requires androgen receptor (AR) signalling. We have previously shown that upon mating, binucleate secondary cells (SCs) of the Drosophila melanogaster male accessory gland (AG), which share some similarities with prostate epithelial cells, switch their growth regulation from a steroid-dependent to a steroid-independent form of Ecdysone Receptor (EcR) control. This physiological change induces genome endoreplication and allows SCs to rapidly replenish their secretory compartments, even when ecdysone levels are low because the male has not previously been exposed to females. Here, we test whether the Drosophila Rb homologue, Rbf, and E2F1 regulate this switch. Surprisingly, we find that excess Rbf activity reversibly suppresses binucleation in adult SCs. We also demonstrate that Rbf, E2F1 and the cell cycle regulators, Cyclin D (CycD) and Cyclin E (CycE), are key regulators of mating-dependent SC endoreplication, as well as SC growth in both virgin and mated males. Importantly, we show that the CycD/Rbf/E2F1 axis requires the EcR, but not ecdysone, to trigger CycE-dependent endoreplication and endoreplication-associated growth in SCs, mirroring changes seen in CRPC. Furthermore, Bone Morphogenetic Protein (BMP) signalling, mediated by the BMP ligand Decapentaplegic (Dpp), intersects with CycD/Rbf/E2F1 signalling to drive endoreplication in these fly cells. Overall, our work reveals a signalling switch, which permits rapid growth of SCs and increased secretion after mating, independently of previous exposure to females. The changes observed share mechanistic parallels with the pathological switch to hormone-independent AR signalling seen in CRPC, suggesting that the latter may reflect the dysregulation of a currently unidentified physiological process.