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During intestinal organogenesis, equipotent epithelial progenitors mature into phenotypically distinct stem cells that are responsible for life-long maintenance of the tissue. While the morphological changes associated with the transition are well-characterized, the molecular mechanisms underpinning the maturation process are not fully understood. Here, we leverage intestinal organoid cultures to profile transcriptional, chromatin accessibility, DNA methylation and 3D chromatin conformation landscapes defining fetal and adult epithelial cells. We observed prominent differences in gene expression and enhancer activity, accompanied by changes in 3D organization and local changes in DNA accessibility and methylation, between the two cellular states. Using integrative analyses, we identified sustained YAP transcriptional activity as a major gatekeeper of the immature fetal state. We found the YAP-associated transcriptional network to be regulated at various levels of chromatin organization, and likely to be coordinated by changes in extracellular matrix composition. Altogether, our work highlights the value of unbiased profiling of regulatory landscapes for the identification of key mechanisms underlying tissue maturation.

Pan-cancer Isoform Switches with Predicted Consequences.

Alternative usage of transcript isoforms from the same gene has been hypothesized as an important feature in cancers. However, differential usage of gene transcripts between conditions (isoform switching) has not been comprehensively characterized in and across cancer types. To this end, we developed methods for identification and visualization of isoform switches with predicted functional consequences. Using these methods, we characterized isoform switching in RNA-seq data from >5,500 cancer patients covering 12 solid cancer types. Isoform switches with potential functional consequences were common, affecting approximately 19% of multiple transcript genes. Among these, isoform switches leading to loss of DNA sequence encoding protein domains were more frequent than expected, particularly in pancancer switches. We identified several isoform switches as powerful biomarkers: 31 switches were highly predictive of patient survival independent of cancer types. Our data constitute an important resource for cancer researchers, available through interactive web tools. Moreover, our methods, available as an R package, enable systematic analysis of isoform switches from other RNA-seq datasets.Implications: This study indicates that isoform switches with predicted functional consequences are common and important in dysfunctional cells, which in turn means that gene expression should be analyzed at the isoform level.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/15/9/1206/F1.large.jpg. Mol Cancer Res; 15(9); 1206–20. ©2017 AACR.

Figure S1A: Extent of isoform switching across cancer types. Figure S1B: Extent of isoform switch usage in any cancer type. Figure S1C: Fraction of isoform switches with consequence. Figure S1D: Funtional enrichment analysis. Figure S1E: Global analysis of isoform fraction. Figure S2A: Extent of predicted functional consequences. Figure S2B: Background distribution of protein domain gain/loss. Figure S2C: Co-occurrence of consequences. Figure S2D: Definition of non-coding transcripts. Figure S2E: Difference in length of isoforms in an isoform switch. Figure S3A: Loss vs. gain of protein domain analysis. Figure S3B: Interaction network of genes involved in pan-cancer isoform switches. Figure S4: Figure S3B: Interaction network of genes involved in pan-cancer isoform switches. Figure S5A: Tools for identification of differential full-length isoform usage. Figure S5B: Isoform switch in insulin receptor. Figure S6A: Generation of high-qulaity data. Figure S6B: Assessment of CPAT cutoffs. Figure S6C. ORF prediction accuracy.

List of all samples from FANTOM5 CAGE data.

The expression changes of cancer related genes that were differentially expressed in FANTOM5 cancer cell lines (S1); Heatmaps showing the spectral count data corresponding to protein levels of selected genes in 90 colorectal cancers and 30 normal samples generated by Zhang et al (S2); Pan-cancer long non-coding RNAs and neighboring cancer associated genes (S3); ChIA-pet data show pan-cancer enhancers are physically associated with genes implicated in cancer (S4); The correlation between expression fold changes and the frequency of overlapping repetitive element (S5).

Description of additional methods and procedures used in the study.

Maternal immune system activation (MIA) during pregnancy can disrupt the fetal environment, causing postnatal susceptibility to disorders. How the placenta and the fetus respond to acute MIA over time is unknown. Here, we characterized the response to acute maternal pulmonary inflammation across time in maternal and fetal organs using multi-omics. Unlike maternal organs which mounted strong innate immune responses, the placenta upregulated tissue-integrity genes, likely to prevent fetal exposure to infections, and downregulated growth-associated genes. Subsequently, the placenta upregulated biosynthesis and endoplasmic reticulum stress genes in order to return to homeostasis. These responses likely protected the fetus, since we observed no immune response in fetal liver. Instead, likely due to nutrient depletion, the fetal liver displayed metabolic adaptations, including increases in lipids containing docosahexaenoic acid, crucial for fetal brain development. Our study shows, for the first time, the integrated temporal response to pulmonary MIA across maternal and fetal organs.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy with minimal treatment options and a global rise in prevalence. PDAC is characterized by frequent driver mutations including KRAS and TP53 (p53), and a dense, acidic tumor microenvironment (TME). The relation between genotype and TME in PDAC development is unknown. Strikingly, when wild type (WT) Panc02 PDAC cells were adapted to growth in an acidic TME and returned to normal pH to mimic invasive cells escaping acidic regions, they displayed a strong increase of aggressive traits such as increased growth in 3-dimensional (3D) culture, adhesion-independent colony formation and invasive outgrowth. This pattern of acidosis-induced aggressiveness was observed in 3D spheroid culture as well as upon organotypic growth in matrigel, collagen-I and combination thereof, mimicking early and later stages of PDAC development. Acid-adaptation-induced gain of cancerous traits was further increased p53 knockout (KO), but only in specific extracellular matrix (ECM) compositions. Akt- and Transforming growth factor-β (TGFβ) signaling, as well as expression of the Na+/H+ exchanger NHE1, were increased by acid adaptation. Whereas Akt inhibition decreased spheroid growth regardless of treatment and genotype, stimulation with TGFβI increased growth of WT control spheroids, and inhibition of TGFβ signaling tended to limit growth under acidic conditions only. Our results indicate that a complex crosstalk between tumor acidosis, ECM composition and genotype contributes to PDAC development. The findings may guide future strategies for acidosis-targeted therapies.

Immune responses triggered by pathogen-associated molecular patterns (PAMPs) are key to pathogen defense, but drivers and stabilizers of the growth-to-defense genetic reprogramming remain incompletely understood in plants. Here, we report a time-course study of the establishment of PAMP-triggered immunity (PTI) using cap analysis of gene expression. We show that around 15% of all transcription start sites (TSSs) rapidly induced during PTI define alternative transcription initiation events. From these, we identify clear examples of regulatory TSS change via alternative inclusion of target peptides or domains in encoded proteins, or of upstream open reading frames in mRNA leader sequences. We also find that 60% of PAMP response genes respond earlier than previously thought. In particular, a cluster of rapidly and transiently PAMP-induced genes is enriched in transcription factors (TFs) whose functions, previously associated with biological processes as diverse as abiotic stress adaptation and stem cell activity, appear to converge on growth restriction. Furthermore, examples of known potentiators of PTI, in one case under direct mitogen-activated protein kinase control, support the notion that the rapidly induced TFs could constitute direct links to PTI signaling pathways and drive gene expression changes underlying establishment of the immune state.

The harsh environments in poorly perfused tumor regions have been proposed to select for traits that may drive cancer aggressiveness. Here, we tested the hypothesis that tumor acidosis interacts with driver mutations to exacerbate cancer hallmarks, including drug resistance, in pancreatic cancer. We gradually adapted mouse organoids from normal pancreatic duct (mN) and early PDAC (mP, with KRAS G12V mutation and +/- p53 knockout), from pH 7.4 (physiological level) to 6.7, representing acidic tumor niches. Acid adaptation rewired organoid transcriptional activity, increased viability and, strikingly, increased Gemcitabine- and Erlotinib resistance. Importantly, this response only occurred in organoids expressing wild-type p53 and was most pronounced when acid-adapted cells were returned to physiological pH (mimicking increased perfusion or invasion). While the acid adaptation transcriptional change was overall not highly similar to that induced by drug adaptation of the organoids, acid adaptation induced expression of cytidine deaminase (Cda) and ribonucleotide reductase regulatory subunit M2 (Rrm2), both associated with Gemcitabine resistance, and inhibition of these proteins partially restored Gemcitabine sensitivity. Thus, adaptation to the acidic tumor microenvironment increases drug resistance even after cells leave this niche, and this is in part dependent on acid-adaptation-induced transcriptional upregulation ofCdaandRrm2.

The RNA exosome degrades transcripts in the nucleoplasm of mammalian cells. Its substrate specificity is mediated by two adaptors: the ‘nuclear exosome targeting (NEXT)’ complex and the ‘poly(A) exosome targeting (PAXT)’ connection. Previous studies have revealed some DNA/RNA elements that differ between the two pathways, but how informative these features are for distinguishing pathway targeting, or whether additional genomic features that are informative for such classifications exist, is unknown. Here, we leverage the wealth of available genomic data and develop machine learning models that predict exosome targets and subsequently rank the features the models use by their predictive power. As expected, features around transcript end sites were most predictive; specifically, the lack of canonical 3′ end processing was highly predictive of NEXT targets. Other associated features, such as promoter-proximal G/C content and 5′ splice sites, were informative, but only for distinguishing NEXT and not PAXT targets. Finally, we discovered predictive features not previously associated with exosome targeting, in particular RNA helicase DDX3X binding sites. Overall, our results demonstrate that nucleoplasmic exosome targeting is to a large degree predictable, and our approach can assess the predictive power of previously known and new features in an unbiased way.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Lacticaseibacillus rhamnosus GG is a widely marketed probiotic with well-documented probiotic properties. Previously, deletion of the mucus-adhesive spaCBA-srtC1 genes in dairy isolates was reported. In this study, we examined the genome preservation of industrially produced L. rhamnosus GG (DSM 33156) cofermented in yogurts. In total, DNA of 66 samples, including 60 isolates, was sequenced. Population samples and 59 isolates exhibited an intact genome. One isolate exhibited loss of spaCBA-srtC1. In addition, we examined phenotypes related to the probiotic properties of L. rhamnosus GG either from frozen pellets or cofermented in yogurt. L. rhamnosus GG from frozen pellets induced a response in intestinal barrier function in vitro, in contrast to frozen pellets of the starter culture. Yogurt matrix, containing only the starter culture, induced a response, but cofermentation with L. rhamnosus GG induced a higher response. Conversely, only the starter culture stimulated cytokine secretion in dendritic cells, and it was observed that the addition of L. rhamnosus GG to the starter culture reduced the response. We conclude that the L. rhamnosus GG genome is preserved in yogurt and that common in vitro probiotic effects of L. rhamnosus GG are observed when examined in the yogurt matrix. IMPORTANCE Lacticaseibacillus rhamnosus GG is a well-documented probiotic strain recognized for its high acid and bile tolerance and properties of adhesion to enterocytes and mucus. The strain exhibits SpaCBA pili, which have been demonstrated to play an important role in adhesion and therefore are relevant for persistence in the gastrointestinal tract. Recently we demonstrated that the genome and phenotypes of L. rhamnosus GG are preserved throughout an industrial production pipeline. However, as gene deletions in L. rhamnosus GG were previously reported for isolates from dairy products, a key question on the genomic stability of L. rhamnosus GG in a yogurt matrix remained. The aim of this study was to analyze genome stability and phenotypic characteristics of L. rhamnosus GG in yogurt. We found that the genome of L. rhamnosus GG is well conserved when the organism is cofermented in yogurt. Some phenotypic characteristics are consistent in all product matrixes, while other characteristics are modulated.

The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data.We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: (i) full-length RNA-seq for detection of splicing patterns and (ii) high-throughput 5' and 3' tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts. We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings and Saccharomyces cerevisiae cells as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the most commonly used community gene models, TAIR10 and Araport11 for A.thaliana and SacCer3 for S.cerevisiae. In particular, we identify multiple transient transcripts missing from the existing annotations. Our new annotations promise to improve the quality of A.thaliana and S.cerevisiae genome research.Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.

Summary Pluripotent embryonic stem cells (ESCs) constitute an essential cellular niche sustained by epigenomic and transcriptional regulation. Any role of post-transcriptional processes remains less explored. Here, we identify a link between nuclear RNA levels, regulated by the poly(A) RNA exosome targeting (PAXT) connection, and transcriptional control by the polycomb repressive complex 2 (PRC2). Knockout of the PAXT component ZFC3H1 impairs mouse ESC differentiation. In addition to the upregulation of bona fide PAXT substrates, Zfc3h1−/− cells abnormally express developmental genes usually repressed by PRC2. Such de-repression is paralleled by decreased PRC2 binding to chromatin and low PRC2-directed H3K27 methylation. PRC2 complex stability is compromised in Zfc3h1−/− cells with elevated levels of unspecific RNA bound to PRC2 components. We propose that excess RNA hampers PRC2 function through its sequestration from DNA. Our results highlight the importance of balancing nuclear RNA levels and demonstrate the capacity of bulk RNA to regulate chromatin-associated proteins., Graphical Abstract, Highlights • Depletion of ZFC3H1 in mouse ESCs results in differentiation defects • PRC2 target genes are deregulated in Zfc3h1−/− cells • Chromatin binding of PRC2 and H3K27me3 is reduced in Zfc3h1−/− cells • Increased binding of RNA impairs PRC2 complex stability, ZFC3H1 targets pA+ RNA for decay by the nuclear RNA exosome. Garland et al. report a disruptive relationship between excess RNA and PRC2 upon depletion of ZFC3H1 in mouse ESCs. In such conditions, RNA is bound by PRC2 components, which show reduced binding to chromatin and fellow PRC2 proteins.

Background 5′-end sequencing assays, and Cap Analysis of Gene Expression (CAGE) in particular, have been instrumental in studying transcriptional regulation. 5′-end methods provide genome-wide maps of transcription start sites (TSSs) with base pair resolution. Because active enhancers often feature bidirectional TSSs, such data can also be used to predict enhancer candidates. The current availability of mature and comprehensive computational tools for the analysis of 5′-end data is limited, preventing efficient analysis of new and existing 5′-end data. Results We present CAGEfightR, a framework for analysis of CAGE and other 5′-end data implemented as an R/Bioconductor-package. CAGEfightR can import data from BigWig files and allows for fast and memory efficient prediction and analysis of TSSs and enhancers. Downstream analyses include quantification, normalization, annotation with transcript and gene models, TSS shape statistics, linking TSSs to enhancers via co-expression, identification of enhancer clusters, and genome-browser style visualization. While built to analyze CAGE data, we demonstrate the utility of CAGEfightR in analyzing nascent RNA 5′-data (PRO-Cap). CAGEfightR is implemented using standard Bioconductor classes, making it easy to learn, use and combine with other Bioconductor packages, for example popular differential expression tools such as limma, DESeq2 and edgeR. Conclusions CAGEfightR provides a single, scalable and easy-to-use framework for comprehensive downstream analysis of 5′-end data. CAGEfightR is designed to be interoperable with other Bioconductor packages, thereby unlocking hundreds of mature transcriptomic analysis tools for 5′-end data. CAGEfightR is freely available via Bioconductor: bioconductor.org/packages/CAGEfightR .

Background The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data. Results We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: (i) full-length RNA-seq for detection of splicing patterns and (ii) high-throughput 5′ and 3′ tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts. We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings and Saccharomyces cerevisiae cells as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the most commonly used community gene models, TAIR10 and Araport11 for A.thaliana and SacCer3 for S.cerevisiae. In particular, we identify multiple transient transcripts missing from the existing annotations. Our new annotations promise to improve the quality of A.thaliana and S.cerevisiae genome research. Conclusions Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.

Immune responses triggered by pathogen-associated molecular patterns (PAMPs) are key to pathogen defense, but drivers of the genetic reprogramming required to reach the immune state remain incompletely understood in plants. Here, we report a time-course study of the establishment of PAMP-triggered immunity (PTI) using cap analysis of gene expression (CAGE). Our results show that as much as 15% of all PAMP response genes display alternative transcription initiation. In several cases, use of alternative TSSs may be regulatory as it determines inclusion of target peptides or protein domains, or occurrence of upstream open reading frames (uORFs) in mRNA leader sequences. We also find that 60% of PAMP-response genes respond much earlier than previously thought. In particular, a previously unnoticed cluster of rapidly and transiently PAMP-induced genes is enriched in transcription factors whose functions, previously associated with biological processes as diverse as abiotic stress adaptation and stem cell activity, appear to converge on growth restriction. Furthermore, some examples of known potentiators of PTI, in one case under direct MAP kinase control, support the notion that the rapidly induced transcription factors could constitute direct links to PTI signaling pathways and drive gene expression changes underlying establishment of the immune state.

Background: The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data. Results: We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: i) full-length RNA-seq for detection of splicing patterns and ii) high-throughput 5' and 3' tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts.We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the two most commonly used community gene models, TAIR10 and Araport11. In particular, we identify thousands of transient transcripts missing from the existing annotations. Our new annotation promises to improve the quality of A.thaliana genome research.Conclusions: Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.

Transposable elements (TEs) are widespread genetic parasites known to be kept under tight transcriptional control. Here, we describe a functional connection between the mouse-orthologous “nuclear exosome targeting” (NEXT) and “human silencing hub” (HUSH) complexes, involved in nuclear RNA decay and the epigenetic silencing of TEs, respectively. Knocking out the NEXT component ZCCHC8 in embryonic stem cells results in elevated TE RNA levels. We identify a physical interaction between ZCCHC8 and the MPP8 protein of HUSH and establish that HUSH recruits NEXT to chromatin at MPP8-bound TE loci. However, while NEXT and HUSH both dampen TE RNA expression, their activities predominantly affect shorter non-polyadenylated and full-length polyadenylated transcripts, respectively. Indeed, our data suggest that the repressive action of HUSH promotes a condition favoring NEXT RNA decay activity. In this way, transcriptional and post-transcriptional machineries synergize to suppress the genotoxic potential of TE RNAs.

The specific effects of administering live probiotics in the human gut are not well characterized. To this end, we investigated the immediate effect of Lactobacillus rhamnosus GG (LGG) in the jejunum of 27 healthy volunteers 2 h after ingestion using a combination of global RNA sequencing of human biopsies and bacterial DNA sequencing in a multi-visit, randomized, cross-over design (ClinicalTrials.gov number NCT03140878). While LGG was detectable in jejunum after 2 h in treated subjects, the gene expression response vs. placebo was subtle if assessed across all subjects. However, clustering analysis revealed that one-third of subjects exhibited a strong and consistent LGG response involving hundreds of genes, where genes related to B cell activation were upregulated, consistent with prior results in mice. Immunohistochemistry and single cell-based deconvolution analyses showed that this B cell signature likely is due to activation and proliferation of existing B cells rather than B cell immigration to the tissue. Our results indicate that the LGG strain has an immediate effect in the human gut in a subpopulation of individuals. In extension, our data strongly suggest that studies on in vivo probiotic effects in humans require large cohorts and must take individual variation into account.

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

Lactobacillus rhamnosus GG is one of the most widely marketed and studied probiotic strains. In L. rhamnosus GG, the spaCBA-srtC1 gene cluster encodes pili, which are important for some of the probiotic properties of the strain. A previous study showed that the DNA sequence of the spaCBA-srtC1 gene cluster was not present in some L. rhamnosus GG variants isolated from liquid dairy products. To examine the stability of the L. rhamnosus GG genome in an industrial production process, we sequenced the genome of samples of L. rhamnosus GG (DSM 33156) collected at specific steps of the industrial production process, including the culture collection stock, intermediate fermentations, and final freeze-dried products. We found that the L. rhamnosus GG genome sequence was unchanged throughout the production process. Consequently, the spaCBA-srtC1 gene locus was intact and fully conserved in all 31 samples examined. In addition, different production batches of L. rhamnosus GG exhibited consistent phenotypes, including the presence of pili in final freeze-dried products, and consistent characteristics in in vitro assays of probiotic properties. Our data show that L. rhamnosus GG is highly stable in this industrial production process. IMPORTANCELactobacillus rhamnosus GG is one of the best-studied probiotic strains. One of the well-characterized features of the strain is the pili encoded by the spaCBA-srtC1 gene cluster. These pili are involved in persistence in the gastrointestinal tract and are important for the probiotic properties of L. rhamnosus GG. Previous studies demonstrated that the L. rhamnosus GG genome can be unstable under certain conditions and can lose the spaCBA-srtC1 gene cluster. Since in vitro studies have shown that the loss of the spaCBA-srtC1 gene cluster decreases certain L. rhamnosus GG probiotic properties, we assessed both the genomic stability and phenotypic properties of L. rhamnosus GG throughout an industrial production process. We found that neither genomic nor phenotypic changes occurred in the samples. Therefore, we demonstrate that L. rhamnosus GG retains the spaCBA-srtC1 cluster and exhibits excellent genomic and phenotypic stability in the specific industrial process examined here.

RNA polymerase II (RNAPII) transcription is crucial for gene expression. RNAPII density peaks at gene boundaries, associating these key regions for gene expression control with limited RNAPII movement. The connections between RNAPII transcription speed and gene regulation in multicellular organisms are poorly understood. Here, we directly modulate RNAPII transcription speed by point mutations in the second largest subunit of RNAPII in Arabidopsis thaliana. A RNAPII mutation predicted to decelerate transcription is inviable, while accelerating RNAPII transcription confers phenotypes resembling auto‐immunity. Nascent transcription profiling revealed that RNAPII complexes with accelerated transcription clear stalling sites at both gene ends, resulting in read‐through transcription. The accelerated transcription mutant NRPB2‐Y732F exhibits increased association with 5′ splice site (5′SS) intermediates and enhanced splicing efficiency. Our findings highlight potential advantages of RNAPII stalling through local reduction in transcription speed to optimize gene expression for the development of multicellular organisms., RNAPII mutations that accelerate transcription cause auto‐immunity‐like phenotypes, read‐through transcription at RNAPII stalling sites and enhanced splicing in Arabidopsis, indicating that controlled transcription speed is required for optimal gene expression and plant development.

Summary: Degradation of transcripts in human nuclei is primarily facilitated by the RNA exosome. To obtain substrate specificity, the exosome is aided by adaptors; in the nucleoplasm, those adaptors are the nuclear exosome-targeting (NEXT) complex and the poly(A) (pA) exosome-targeting (PAXT) connection. How these adaptors guide exosome targeting remains enigmatic. Employing high-resolution 3′ end sequencing, we demonstrate that NEXT substrates arise from heterogenous and predominantly pA− 3′ ends often covering kilobase-wide genomic regions. In contrast, PAXT targets harbor well-defined pA+ 3′ ends defined by canonical pA site use. Irrespective of this clear division, NEXT and PAXT act redundantly in two ways: (1) regional redundancy, where the majority of exosome-targeted transcription units produce NEXT- and PAXT-sensitive RNA isoforms, and (2) isoform redundancy, where the PAXT connection ensures fail-safe decay of post-transcriptionally polyadenylated NEXT targets. In conjunction, this provides a two-layered targeting mechanism for efficient nuclear sorting of the human transcriptome. : Wu et al. demonstrate that the nuclear exosome adaptor NEXT targets poly(A)− RNAs with poorly defined 3′ ends, whereas the PAXT connection targets poly(A)+ RNAs derived from canonical poly(A) sites. NEXT substrates become polyadenylated in the absence of NEXT, causing fail-safe RNA decay via PAXT. Keywords: nuclear RNA turnover, NEXT complex, PAXT connection, 3′ end sequencing, pA+/pA− RNA

JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.