Chloroplast cold-resistance is mediated by the acidic domain of the RNA binding protein CP31A

Chloroplast RNA metabolism is characterized by long-lived mRNAs that undergo a multitude of post-transcriptional processing events. Chloroplast RNA accumulation responds to environmental cues, foremost light and temperature. A large number of nuclear-encoded RNA-binding proteins (RBPs) are required for chloroplast RNA metabolism, but we do not yet know how chloroplast RBPs convert abiotic signals into gene expression changes. Previous studies showed that the chloroplast ribonucleoprotein 31A (CP31A) is required for the stabilization of multiple chloroplast mRNAs in the cold, and that the phosphorylation of CP31A at various residues within its N-terminal acidic domain (AD) can alter its affinity for RNA in vitro. Loss of CP31A leads to cold sensitive plants that exhibit bleached tissue at the center of the vegetative rosette. Here, by applying RIP-Seq, we demonstrated that CP31A shows increased affinity for a large number of chloroplast RNAs in vivo in the cold. Among the main targets of CP31A were RNAs encoding subunits of the NDH complex and loss of CP31A lead to reduced accumulation of ndh transcripts. Deletion analyses revealed that cold-dependent RNA binding and cold resistance of chloroplast development both depend on the AD of CP31A. Together, our analysis established the AD of CP31A as a key mediator of cold acclimation of the chloroplast transcriptome

Electric fields and valence band offsets at strained [111] heterojunctions

[111] ordered common atom strained layer superlattices (in particular the common anion GaSb/InSb system and the common cation InAs/InSb system) are investigated using the ab initio full potential linearized augmented plane wave (FLAPW) method. We have focused our attention on the potential line-up at the two sides of the homopolar isovalent heterojunctions considered, and in particular on its dependence on the strain conditions and on the strain induced electric fields. We propose a procedure to locate the interface plane where the band alignment could be evaluated; furthermore, we suggest that the polarization charges, due to piezoelectric effects, are approximately confined to a narrow region close to the interface and do not affect the potential discontinuity. We find that the interface contribution to the valence band offset is substantially unaffected by strain conditions, whereas the total band line-up is highly tunable, as a function of the strain conditions. Finally, we compare our results with those obtained for [001] heterojunctions.Comment: 18 pages, Latex-file, to appear in Phys.Rev.

DDX54 regulates transcriptome dynamics during DNA damage response

The cellular response to genotoxic stress is mediated by a well-characterized network of DNA surveillance pathways. The contribution of posttranscriptional gene regulatory networks to the DNA damage response (DDR) has not been extensively studied. Here, we systematically identified RNA-binding proteins differentially interacting with polyadenylated transcripts upon exposure of human breast carcinoma cells to ionizing radiation (IR). Interestingly, more than 260 proteins including many nucleolar proteins showed increased binding to poly(A) RNA in IR-exposed cells. The functional analysis of DDX54, a candidate genotoxic stress responsive RNA helicase, revealed that this protein is an immediate-to-early DDR regulator required for the splicing efficacy of its target IR-induced pre-mRNAs. Upon IR exposure, DDX54 acts by increased interaction with a well-defined class of pre-mRNAs which harbor introns with weak acceptor splice sites, as well as by protein-protein contacts within components of U2 snRNP and spliceosomal B complex, resulting in lower intron retention and higher processing rates of its target transcripts. Since DDX54 promotes survival after exposure to IR its expression and/or mutation rate may impact DDR-related pathologies. Our work indicates the relevance of many uncharacterized RBPs potentially involved in the DDR

Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets

Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Here we present an exome-wide rare genetic variant association study for 30 biomarkers in 191,640 individuals in the UK Biobank. We perform gene-based association tests for separate functional variant categories to increase interpretability and identify 201 significant gene-biomarker associations, which include novel associations such as GIGYF1 with diabetes markers. In addition to performing gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for missense variants, splicing and the binding of RNA-binding proteins. For these tests we present a powerful and computationally efficient combination of the likelihood-ratio and score tests that found 32% more associations than the score test alone. Kernel-based tests identified 12-31% more associations than their gene-based collapsing counterparts with large overlaps, and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use this approach to identify potential novel gain of function variants in PIEZO1, and interpret a position-specific association of ABCA1-variants with inflammation marker CRP. Our results show the benefits of separately investigating different functional mechanisms when performing rare-variant association tests, and highlight the strengths of biomarker panels for large biobanks

Comprehensive analysis of the base composition around the transcription start site in Metazoa

BACKGROUND: The transcription start site of a metazoan gene remains poorly understood, mostly because there is no clear signal present in all genes. Now that several sequenced metazoan genomes have been annotated, we have been able to compare the base composition around the transcription start site for all annotated genes across multiple genomes. RESULTS: The most prominent feature in the base compositions is a significant local variation in G+C content over a large region around the transcription start site. The change is present in all animal phyla but the extent of variation is different between distinct classes of vertebrates, and the shape of the variation is completely different between vertebrates and arthropods. Furthermore, the height of the variation correlates with CpG frequencies in vertebrates but not in invertebrates and it also correlates with gene expression, especially in mammals. We also detect GC and AT skews in all clades (where %G is not equal to %C or %A is not equal to %T respectively) but these occur in a more confined region around the transcription start site and in the coding region. CONCLUSIONS: The dramatic changes in nucleotide composition in humans are a consequence of CpG nucleotide frequencies and of gene expression, the changes in Fugu could point to primordial CpG islands, and the changes in the fly are of a totally different kind and unrelated to dinucleotide frequencies

RNA localization is a key determinant of neurite-enriched proteome

Protein subcellular localization is fundamental to the establishment of the body axis, cell migration, synaptic plasticity, and a vast range of other biological processes. Protein localization occurs through three mechanisms: protein transport, mRNA localization, and local translation. However, the relative contribution of each process to neuronal polarity remains unknown. Using neurons differentiated from mouse embryonic stem cells, we analyze protein and RNA expression and translation rates in isolated cell bodies and neurites genome-wide. We quantify 7323 proteins and the entire transcriptome, and identify hundreds of neurite-localized proteins and locally translated mRNAs. Our results demonstrate that mRNA localization is the primary mechanism for protein localization in neurites that may account for half of the neurite-localized proteome. Moreover, we identify multiple neurite-targeted non-coding RNAs and RNA-binding proteins with potential regulatory roles. These results provide further insight into the mechanisms underlying the establishment of neuronal polarity. Subcellular localization of RNAs and proteins is important for polarized cells such as neurons. Here the authors differentiate mouse embryonic stem cells into neurons, and analyze the local transcriptome, proteome, and translated transcriptome in their cell bodies and neurites, providing a unique resource for future studies on neuronal polarity

High Resolution Models of Transcription Factor-DNA Affinities Improve In Vitro and In Vivo Binding Predictions

Accurately modeling the DNA sequence preferences of transcription factors (TFs), and using these models to predict in vivo genomic binding sites for TFs, are key pieces in deciphering the regulatory code. These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices (PSSMs), which may match large numbers of sites and produce an unreliable list of target genes. Recently, protein binding microarray (PBM) experiments have emerged as a new source of high resolution data on in vitro TF binding specificities. PBM data has been analyzed either by estimating PSSMs or via rank statistics on probe intensities, so that individual sequence patterns are assigned enrichment scores (E-scores). This representation is informative but unwieldy because every TF is assigned a list of thousands of scored sequence patterns. Meanwhile, high-resolution in vivo TF occupancy data from ChIP-seq experiments is also increasingly available. We have developed a flexible discriminative framework for learning TF binding preferences from high resolution in vitro and in vivo data. We first trained support vector regression (SVR) models on PBM data to learn the mapping from probe sequences to binding intensities. We used a novel -mer based string kernel called the di-mismatch kernel to represent probe sequence similarities. The SVR models are more compact than E-scores, more expressive than PSSMs, and can be readily used to scan genomics regions to predict in vivo occupancy. Using a large data set of yeast and mouse TFs, we found that our SVR models can better predict probe intensity than the E-score method or PBM-derived PSSMs. Moreover, by using SVRs to score yeast, mouse, and human genomic regions, we were better able to predict genomic occupancy as measured by ChIP-chip and ChIP-seq experiments. Finally, we found that by training kernel-based models directly on ChIP-seq data, we greatly improved in vivo occupancy prediction, and by comparing a TF's in vitro and in vivo models, we could identify cofactors and disambiguate direct and indirect binding

Optimized mixed Markov models for motif identification

BACKGROUND: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challenging issue, largely due to limited availability of training samples. RESULTS: We introduce a novel and flexible model, the Optimized Mixture Markov model (OMiMa), and related methods to allow adjustment of model complexity for different motifs. In comparison with other leading methods, OMiMa can incorporate more than the NNSplice's pairwise dependencies; OMiMa avoids model over-fitting better than the Permuted Variable Length Markov Model (PVLMM); and OMiMa requires smaller training samples than the Maximum Entropy Model (MEM). Testing on both simulated and actual data (regulatory cis-elements and splice sites), we found OMiMa's performance superior to the other leading methods in terms of prediction accuracy, required size of training data or computational time. Our OMiMa system, to our knowledge, is the only motif finding tool that incorporates automatic selection of the best model. OMiMa is freely available at [1]. CONCLUSION: Our optimized mixture of Markov models represents an alternative to the existing methods for modeling dependent structures within a biological motif. Our model is conceptually simple and effective, and can improve prediction accuracy and/or computational speed over other leading methods

The BTB transcription factors ZBTB11 and ZFP131 maintain pluripotency by pausing POL II at pro-differentiation genes

In pluripotent cells, a delicate activation-repression balance maintains pro-differentiation genes ready for rapid activation. The identity of transcription factors (TFs) that specifically repress pro-differentiation genes remains obscure. By targeting ~1,700 TFs with CRISPR loss-of-function screen, we found that ZBTB11 and ZFP131 are required for embryonic stem cell (ESC) pluripotency. ZBTB11 and ZFP131 maintain promoter-proximally paused Polymerase II at pro-differentiation genes in ESCs. ZBTB11 or ZFP131 loss leads to NELF pausing factor release, an increase in H3K4me3, and transcriptional upregulation of genes associated with all three germ layers. Together, our results suggest that ZBTB11 and ZFP131 maintain pluripotency by preventing premature expression of pro-differentiation genes and present a generalizable framework to maintain cellular potency