Data-driven hypothesis weighting increases detection power in genome-scale multiple testing.

Hypothesis weighting improves the power of large-scale multiple testing. We describe independent hypothesis weighting (IHW), a method that assigns weights using covariates independent of the P-values under the null hypothesis but informative of each test's power or prior probability of the null hypothesis (http://www.bioconductor.org/packages/IHW). IHW increases power while controlling the false discovery rate and is a practical approach to discovering associations in genomics, high-throughput biology and other large data sets.

Landscape of nuclear transport receptor cargo specificity.

Nuclear transport receptors (NTRs) recognize localization signals of cargos to facilitate their passage across the central channel of nuclear pore complexes (NPCs). About 30 different NTRs constitute different transport pathways in humans and bind to a multitude of different cargos. The exact cargo spectrum of the majority of NTRs, their specificity and even the extent to which active nucleocytoplasmic transport contributes to protein localization remains understudied because of the transient nature of these interactions and the wide dynamic range of cargo concentrations. To systematically map cargo-NTR relationships in situ, we used proximity ligation coupled to mass spectrometry (BioID). We systematically fused the engineered biotin ligase BirA* to 16 NTRs. We estimate that a considerable fraction of the human proteome is subject to active nuclear transport. We quantified the specificity and redundancy in NTR interactions and identified transport pathways for cargos. We extended the BioID method by the direct identification of biotinylation sites. This approach enabled us to identify interaction interfaces and to discriminate direct versus piggyback transport mechanisms. Data are available via ProteomeXchange with identifier PXD007976.

miR-16 and miR-125b are involved in barrier function dysregulation through the modulation of claudin-2 and cingulin expression in the jejunum in IBS with diarrhoea.

OBJECTIVE: Micro-RNAs (miRNAs) play a crucial role in controlling intestinal epithelial barrier function partly by modulating the expression of tight junction (TJ) proteins. We have previously shown differential messenger RNA (mRNA) expression correlated with ultrastructural abnormalities of the epithelial barrier in patients with diarrhoea-predominant IBS (IBS-D). However, the participation of miRNAs in these differential mRNA-associated findings remains to be established. Our aims were (1) to identify miRNAs differentially expressed in the small bowel mucosa of patients with IBS-D and (2) to explore putative target genes specifically involved in epithelial barrier function that are controlled by specific dysregulated IBS-D miRNAs. DESIGN: Healthy controls and patients meeting Rome III IBS-D criteria were studied. Intestinal tissue samples were analysed to identify potential candidates by: (a) miRNA-mRNA profiling; (b) miRNA-mRNA pairing analysis to assess the co-expression profile of miRNA-mRNA pairs; (c) pathway analysis and upstream regulator identification; (d) miRNA and target mRNA validation. Candidate miRNA-mRNA pairs were functionally assessed in intestinal epithelial cells. RESULTS: IBS-D samples showed distinct miRNA and mRNA profiles compared with healthy controls. TJ signalling was associated with the IBS-D transcriptional profile. Further validation of selected genes showed consistent upregulation in 75% of genes involved in epithelial barrier function. Bioinformatic analysis of putative miRNA binding sites identified hsa-miR-125b-5p and hsa-miR-16 as regulating expression of the TJ genes CGN (cingulin) and CLDN2 (claudin-2), respectively. Consistently, protein expression of CGN and CLDN2 was upregulated in IBS-D, while the respective targeting miRNAs were downregulated. In addition, bowel dysfunction, perceived stress and depression and number of mast cells correlated with the expression of hsa-miR-125b-5p and hsa-miR-16 and their respective target proteins. CONCLUSIONS: Modulation of the intestinal epithelial barrier function in IBS-D involves both transcriptional and post-transcriptional mechanisms. These molecular mechanisms include miRNAs as master regulators in controlling the expression of TJ proteins and are associated with major clinical symptoms.

A high-throughput ChIP-Seq for large-scale chromatin studies.

We present a modified approach of chromatin immuno-precipitation followed by sequencing (ChIP-Seq), which relies on the direct ligation of molecular barcodes to chromatin fragments, thereby permitting experimental scale-up. With Bar-ChIP now enabling the concurrent profiling of multiple DNA-protein interactions, we report the simultaneous generation of 90 ChIP-Seq datasets without any robotic instrumentation. We demonstrate that application of Bar-ChIP to a panel of Saccharomyces cerevisiae chromatin-associated mutants provides a rapid and accurate genome-wide overview of their chromatin status. Additionally, we validate the utility of this technology to derive novel biological insights by identifying a role for the Rpd3S complex in maintaining H3K14 hypo-acetylation in gene bodies. We also report an association between the presence of intragenic H3K4 tri-methylation and the emergence of cryptic transcription in a Set2 mutant. Finally, we uncover a crosstalk between H3K14 acetylation and H3K4 methylation in this mutant. These results show that Bar-ChIP enables biological discovery through rapid chromatin profiling at single-nucleosome resolution for various conditions and protein modifications at once.

Alternative polyadenylation diversifies post-transcriptional regulation by selective RNA-protein interactions.

Recent research has uncovered extensive variability in the boundaries of transcript isoforms, yet the functional consequences of this variation remain largely unexplored. Here, we systematically discriminate between the molecular phenotypes of overlapping coding and non-coding transcriptional events from each genic locus using a novel genome-wide, nucleotide-resolution technique to quantify the half-lives of 3' transcript isoforms in yeast. Our results reveal widespread differences in stability among isoforms for hundreds of genes in a single condition, and that variation of even a single nucleotide in the 3' untranslated region (UTR) can affect transcript stability. While previous instances of negative associations between 3' UTR length and transcript stability have been reported, here, we find that shorter isoforms are not necessarily more stable. We demonstrate the role of RNA-protein interactions in conditioning isoform-specific stability, showing that PUF3 binds and destabilizes specific polyadenylation isoforms. Our findings indicate that although the functional elements of a gene are encoded in DNA sequence, the selective incorporation of these elements into RNA through transcript boundary variation allows a single gene to have diverse functional consequences.

Signal identification for rare and weak features: higher criticism or false discovery rates?

Signal identification in large-dimensional settings is a challenging problem in biostatistics. Recently, the method of higher criticism (HC) was shown to be an effective means for determining appropriate decision thresholds. Here, we study HC from a false discovery rate (FDR) perspective. We show that the HC threshold may be viewed as an approximation to a natural class boundary (CB) in two-class discriminant analysis which in turn is expressible as the FDR threshold. We demonstrate that in a rare-weak setting in the region of the phase space where signal identification is possible, both thresholds are practicably indistinguishable, and thus HC thresholding is identical to using a simple local FDR cutoff. The relationship of the HC and CB thresholds and their properties are investigated both analytically and by simulations, and are further compared by the application to four cancer gene expression data sets.

The changing career paths of PhDs and postdocs trained at EMBL.

Individuals with PhDs and postdoctoral experience in the life sciences can pursue a variety of career paths. Many PhD students and postdocs aspire to a permanent research position at a university or research institute, but competition for such positions has increased. Here, we report a time-resolved analysis of the career paths of 2284 researchers who completed a PhD or a postdoc at the European Molecular Biology Laboratory (EMBL) between 1997 and 2020. The most prevalent career outcome was Academia: Principal Investigator (636/2284=27.8% of alumni), followed by Academia: Other (16.8%), Science-related Non-research (15.3%), Industry Research (14.5%), Academia: Postdoc (10.7%) and Non-science-related (4%); we were unable to determine the career path of the remaining 10.9% of alumni. While positions in Academia (Principal Investigator, Postdoc and Other) remained the most common destination for more recent alumni, entry into Science-related Non-research, Industry Research and Non-science-related positions has increased over time, and entry into Academia: Principal Investigator positions has decreased. Our analysis also reveals information on a number of factors - including publication records - that correlate with the career paths followed by researchers.

Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake.

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL ("human double knock-outs") plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions.

Recent high-throughput transcription factor (TF) binding assays revealed that TF cooperativity is a widespread phenomenon. However, a global mechanistic and functional understanding of TF cooperativity is still lacking. To address this, here we introduce a statistical learning framework that provides structural insight into TF cooperativity and its functional consequences based on next generation sequencing data. We identify DNA shape as driver for cooperativity, with a particularly strong effect for Forkhead-Ets pairs. Follow-up experiments reveal a local shape preference at the Ets-DNA-Forkhead interface and decreased cooperativity upon loss of the interaction. Additionally, we discover many functional associations for cooperatively bound TFs. Examination of the link between FOXO1:ETV6 and lymphomas reveals that their joint expression levels improve patient clinical outcome stratification. Altogether, our results demonstrate that inter-family cooperative TF binding is driven by position-specific DNA readout mechanisms, which provides an additional regulatory layer for downstream biological functions.

A post-translational modification signature defines changes in soluble tau correlating with oligomerization in early stage Alzheimer's disease brain.

Tau is a microtubule-binding protein that can receive various post-translational modifications (PTMs) including phosphorylation, methylation, acetylation, glycosylation, nitration, sumoylation and truncation. Hyperphosphorylation of tau is linked to its aggregation and the formation of neurofibrillary tangles (NFTs), which are a hallmark of Alzheimer's disease (AD). While more than 70 phosphorylation sites have been detected previously on NFT tau, studies of oligomeric and detergent-soluble tau in human brains during the early stages of AD are lacking. Here we apply a comprehensive electrochemiluminescence ELISA assay to analyze twenty-five different PTM sites as well as tau oligomerization in control and sporadic AD brain. The samples were classified as Braak stages 0-I, II or III-IV, corresponding to the progression of microscopically detectable tau pathology throughout different brain regions. We found that soluble tau multimers are strongly increased at Braak stages III-IV in all brain regions under investigation, including the temporal cortex, which does not contain NFTs or misfolded oligomers at this stage of pathology. We additionally identified five phosphorylation sites that are specifically and consistently increased across the entorhinal cortex, hippocampus and temporal cortex in the same donors. Three of these sites correlate with tau multimerization in all three brain regions, but do not overlap with the epitopes of phospho-sensitive antibodies commonly used for the immunohistochemical detection of NFTs. Our results thus suggest that soluble multimers are characterized by a small set of specific phosphorylation events that differ from those dominating in mature NFTs. These findings shed light on early PTM changes of tau during AD pathogenesis in human brains.

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts.

A challenge in solving the genotype-to-phenotype relationship is to predict a cell's metabolome, believed to correlate poorly with gene expression. Using comparative quantitative proteomics, we found that differential protein expression in 97 Saccharomyces cerevisiae kinase deletion strains is non-redundant and dominated by abundance changes in metabolic enzymes. Associating differential enzyme expression landscapes to corresponding metabolomes using network models provided reasoning for poor proteome-metabolome correlations; differential protein expression redistributes flux control between many enzymes acting in concert, a mechanism not captured by one-to-one correlation statistics. Mapping these regulatory patterns using machine learning enabled the prediction of metabolite concentrations, as well as identification of candidate genes important for the regulation of metabolism. Overall, our study reveals that a large part of metabolism regulation is explained through coordinated enzyme expression changes. Our quantitative data indicate that this mechanism explains more than half of metabolism regulation and underlies the interdependency between enzyme levels and metabolism, which renders the metabolome a predictable phenotype.

Gain of CTCF-Anchored Chromatin Loops Marks the Exit from Naive Pluripotency.

The genome of pluripotent stem cells adopts a unique three-dimensional architecture featuring weakly condensed heterochromatin and large nucleosome-free regions. Yet, it is unknown whether structural loops and contact domains display characteristics that distinguish embryonic stem cells (ESCs) from differentiated cell types. We used genome-wide chromosome conformation capture and super-resolution imaging to determine nuclear organization in mouse ESC and neural stem cell (NSC) derivatives. We found that loss of pluripotency is accompanied by widespread gain of structural loops. This general architectural change correlates with enhanced binding of CTCF and cohesins and more pronounced insulation of contacts across chromatin boundaries in lineage-committed cells. Reprogramming NSCs to pluripotency restores the unique features of ESC domain topology. Domains defined by the anchors of loops established upon differentiation are enriched for developmental genes. Chromatin loop formation is a pervasive structural alteration to the genome that accompanies exit from pluripotency and delineates the spatial segregation of developmentally regulated genes.

voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

Metabolic shifts in residual breast cancer drive tumor recurrence.

Tumor recurrence is the leading cause of breast cancer-related death. Recurrences are largely driven by cancer cells that survive therapeutic intervention. This poorly understood population is referred to as minimal residual disease. Here, using mouse models that faithfully recapitulate human disease together with organoid cultures, we have demonstrated that residual cells acquire a transcriptionally distinct state from normal epithelium and primary tumors. Gene expression changes and functional characterization revealed altered lipid metabolism and elevated ROS as hallmarks of the cells that survive tumor regression. These residual cells exhibited increased oxidative DNA damage, potentiating the acquisition of somatic mutations during hormonal-induced expansion of the mammary cell population. Inhibition of either cellular fatty acid synthesis or fatty acid transport into mitochondria reduced cellular ROS levels and DNA damage, linking these features to lipid metabolism. Direct perturbation of these hallmarks in vivo, either by scavenging ROS or by halting the cyclic mammary cell population expansion, attenuated tumor recurrence. Finally, these observations were mirrored in transcriptomic and histological signatures of residual cancer cells from neoadjuvant-treated breast cancer patients. These results highlight the potential of lipid metabolism and ROS as therapeutic targets for reducing tumor recurrence in breast cancer patients.

Functional Outcomes and Quality of Life After Radical Prostatectomy Only Versus a Combination of Prostatectomy with Radiation and Hormonal Therapy.

BACKGROUND: While the optimal use and timing of secondary therapy after radical prostatectomy (RP) remain controversial, there are limited data on patient-reported outcomes following multimodal therapy. OBJECTIVE: To assess the impact of additional radiation therapy (RT) and/or androgen deprivation therapy (ADT) on urinary continence, potency, and quality of life (QoL) after RP. DESIGN, SETTING, AND PARTICIPANTS: Among 13150 men who underwent RP from 1992 to 2013, 905 received RP + RT, 407 RP + ADT and 688 RP + RT + ADT. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: Urinary function, sexual function, and overall QoL were evaluated annually using self-administered validated questionnaires. Propensity score-matched and bootstrap analyses were performed, and the distributions for all functional outcomes were analyzed as a function of time after RP. RESULTS AND LIMITATIONS: Patients who received RP + RT had a 4% higher overall incontinence rate 3 yr after surgery, and 1% higher rate for severe incontinence (>3 pads/24h) compared to matched RP-only patients. ADT further increased the overall and severe incontinence rates by 4% and 3%, respectively, compared to matched RP + RT patients. RP + RT was associated with an 18% lower rate of potency compared to RP alone, while RP + RT + ADT was associated with a further 17% reduction compared to RP + RT. Additional RT reduced QoL by 10% and additional ADT by a further 12% compared to RP only and RP + RT, respectively. The timing of RT after RP had no influence on continence, but adjuvant compared to salvage RT was associated with significantly lower potency (37% vs 45%), but higher QoL (60% vs 56%). Limitations of our study include the observational study design and potential for selection bias in the treatments received. CONCLUSIONS: Secondary RT and ADT after RP have an additive negative influence on urinary function, potency, and QoL. Patients with high-risk disease should be counseled before RP on the potential net impairment of functional outcomes due to multimodal treatment. PATIENT SUMMARY: Men with high-risk disease choosing surgery upfront should be counseled on the potential need for additional radiation and or androgen deprivation, and the potential net impairment of functional outcomes arising from multimodal treatment.

An end to end workflow for differential gene expression using Affymetrix microarrays.

In this article, we walk through an end-to-end Affymetrix microarray differential expression workflow using Bioconductor packages. This workflow is directly applicable to current "Gene'' type arrays, e.g.the HuGene or MoGene arrays, but can easily be adapted to similar platforms. The data analyzed here is a typical clinical microarray data set that compares inflamed and non-inflamed colon tissue in two disease subtypes. For each disease, the differential gene expression between inflamed- and non-inflamed colon tissue was analyzed. We will start from the raw data CEL files, show how to import them into a Bioconductor ExpressionSet, perform quality control and normalization and finally differential gene expression (DE) analysis, followed by some enrichment analysis.

DChIPRep, an R/Bioconductor package for differential enrichment analysis in chromatin studies.

The genome-wide study of epigenetic states requires the integrative analysis of histone modification ChIP-seq data. Here, we introduce an easy-to-use analytic framework to compare profiles of enrichment in histone modifications around classes of genomic elements, e.g. transcription start sites (TSS). Our framework is available via the user-friendly R/Bioconductor package DChIPRep. DChIPRep uses biological replicate information as well as chromatin Input data to allow for a rigorous assessment of differential enrichment. DChIPRep is available for download through the Bioconductor project at http://bioconductor.org/packages/DChIPRep. Contact. DChIPRep@gmail.com.

Landscape and Dynamics of Transcription Initiation in the Malaria Parasite Plasmodium falciparum.

A comprehensive map of transcription start sites (TSSs) across the highly AT-rich genome of P. falciparum would aid progress toward deciphering the molecular mechanisms that underlie the timely regulation of gene expression in this malaria parasite. Using high-throughput sequencing technologies, we generated a comprehensive atlas of transcription initiation events at single-nucleotide resolution during the parasite intra-erythrocytic developmental cycle. This detailed analysis of TSS usage enabled us to define architectural features of plasmodial promoters. We demonstrate that TSS selection and strength are constrained by local nucleotide composition. Furthermore, we provide evidence for coordinate and stage-specific TSS usage from distinct sites within the same transcription unit, thereby producing transcript isoforms, a subset of which are developmentally regulated. This work offers a framework for further investigations into the interactions between genomic sequences and regulatory factors governing the complex transcriptional program of this major human pathogen.