Missing value imputation for epistatic MAPs

<p>Abstract</p> <p>Background</p> <p>Epistatic miniarray profiling (E-MAPs) is a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. An effective method for imputing interactions would therefore increase the types of possible analysis, as well as increase the potential to identify novel functional interactions between gene pairs. Several methods have been developed to handle missing values in microarray data, but it is unclear how applicable these methods are to E-MAP data because of their pairwise nature and the significantly larger number of missing values. Here we evaluate four alternative imputation strategies, three local (Nearest neighbor-based) and one global (PCA-based), that have been modified to work with symmetric pairwise data.</p> <p>Results</p> <p>We identify different categories for the missing data based on their underlying cause, and show that values from the largest category can be imputed effectively. We compare local and global imputation approaches across a variety of distinct E-MAP datasets, showing that both are competitive and preferable to filling in with zeros. In addition we show that these methods are effective in an E-MAP from a different species, suggesting that pairwise imputation techniques will be increasingly useful as analogous epistasis mapping techniques are developed in different species. We show that strongly alleviating interactions are significantly more difficult to predict than strongly aggravating interactions. Finally we show that imputed interactions, generated using nearest neighbor methods, are enriched for annotations in the same manner as measured interactions. Therefore our method potentially expands the number of mapped epistatic interactions. In addition we make implementations of our algorithms available for use by other researchers.</p> <p>Conclusions</p> <p>We address the problem of missing value imputation for E-MAPs, and suggest the use of symmetric nearest neighbor based approaches as they offer consistently accurate imputations across multiple datasets in a tractable manner.</p

IVOA Recommendation: VOResource: an XML Encoding Schema for Resource Metadata Version 1.03

This document describes an XML encoding standard for IVOA Resource Metadata, referred to as VOResource. This schema is primarily intended to support interoperable registries used for discovering resources; however, any application that needs to describe resources may use this schema. In this document, we define the types and elements that make up the schema as representations of metadata terms defined in the IVOA standard, Resource Metadata for the Virtual Observatory [Hanicsh et al. 2004]. We also describe the general model for the schema and explain how it may be extended to add new metadata terms and describe more specific types of resources

Improved functional overview of protein complexes using inferred epistatic relationships

<p>Abstract</p> <p>Background</p> <p>Epistatic Miniarray Profiling(E-MAP) quantifies the net effect on growth rate of disrupting pairs of genes, often producing phenotypes that may be more (negative epistasis) or less (positive epistasis) severe than the phenotype predicted based on single gene disruptions. Epistatic interactions are important for understanding cell biology because they define relationships between individual genes, and between sets of genes involved in biochemical pathways and protein complexes. Each E-MAP screen quantifies the interactions between a logically selected subset of genes (e.g. genes whose products share a common function). Interactions that occur between genes involved in different cellular processes are not as frequently measured, yet these interactions are important for providing an overview of cellular organization.</p> <p>Results</p> <p>We introduce a method for combining overlapping E-MAP screens and inferring new interactions between them. We use this method to infer with high confidence 2,240 new strongly epistatic interactions and 34,469 weakly epistatic or neutral interactions. We show that accuracy of the predicted interactions approaches that of replicate experiments and that, like measured interactions, they are enriched for features such as shared biochemical pathways and knockout phenotypes. We constructed an expanded epistasis map for yeast cell protein complexes and show that our new interactions increase the evidence for previously proposed inter-complex connections, and predict many new links. We validated a number of these in the laboratory, including new interactions linking the SWR-C chromatin modifying complex and the nuclear transport apparatus.</p> <p>Conclusion</p> <p>Overall, our data support a modular model of yeast cell protein network organization and show how prediction methods can considerably extend the information that can be extracted from overlapping E-MAP screens.</p

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor-positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observedwith PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PRmodulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER+/PR+ breast cancers should be explored

miR-17 overexpression in cystic fibrosis airway epithelial cells decreases interleukin-8 production.

Interleukin (IL)-8 levels are higher than normal in cystic fibrosis (CF) airways, causing neutrophil infiltration and non-resolving inflammation. Overexpression of microRNAs that target IL-8 expression in airway epithelial cells may represent a therapeutic strategy for cystic fibrosis. IL-8 protein and mRNA were measured in cystic fibrosis and non-cystic fibrosis bronchoalveolar lavage fluid and bronchial brushings (n=20 per group). miRNAs decreased in the cystic fibrosis lung and predicted to target IL-8 mRNA were quantified in βENaC-transgenic, cystic fibrosis transmembrane conductance regulator (Cftr)-/- and wild-type mice, primary cystic fibrosis and non-cystic fibrosis bronchial epithelial cells and a range of cystic fibrosis versus non-cystic fibrosis airway epithelial cell lines or cells stimulated with lipopolysaccharide, Pseudomonas-conditioned medium or cystic fibrosis bronchoalveolar lavage fluid. The effect of miRNA overexpression on IL-8 protein production was measured. miR-17 regulates IL-8 and its expression was decreased in adult cystic fibrosis bronchial brushings, βENaC-transgenic mice and bronchial epithelial cells chronically stimulated with Pseudomonas-conditioned medium. Overexpression of miR-17 inhibited basal and agonist-induced IL-8 protein production in F508del-CFTR homozygous CFTE29o(-) tracheal, CFBE41o(-) and/or IB3 bronchial epithelial cells. These results implicate defective CFTR, inflammation, neutrophilia and mucus overproduction in regulation of miR-17. Modulating miR-17 expression in cystic fibrosis bronchial epithelial cells may be a novel anti-inflammatory strategy for cystic fibrosis and other chronic inflammatory airway diseases

The GATA1s isoform is normally down-regulated during terminal haematopoietic differentiation and over-expression leads to failure to repress MYB, CCND2 and SKI during erythroid differentiation of K562 cells

Background: Although GATA1 is one of the most extensively studied haematopoietic transcription factors little is currently known about the physiological functions of its naturally occurring isoforms GATA1s and GATA1FL in humans—particularly whether the isoforms have distinct roles in different lineages and whether they have non-redundant roles in haematopoietic differentiation. As well as being of general interest to understanding of haematopoiesis, GATA1 isoform biology is important for children with Down syndrome associated acute megakaryoblastic leukaemia (DS-AMKL) where GATA1FL mutations are an essential driver for disease pathogenesis. &lt;p/&gt;Methods: Human primary cells and cell lines were analyzed using GATA1 isoform specific PCR. K562 cells expressing GATA1s or GATA1FL transgenes were used to model the effects of the two isoforms on in vitro haematopoietic differentiation. &lt;p/&gt;Results: We found no evidence for lineage specific use of GATA1 isoforms; however GATA1s transcripts, but not GATA1FL transcripts, are down-regulated during in vitro induction of terminal megakaryocytic and erythroid differentiation in the cell line K562. In addition, transgenic K562-GATA1s and K562-GATA1FL cells have distinct gene expression profiles both in steady state and during terminal erythroid differentiation, with GATA1s expression characterised by lack of repression of MYB, CCND2 and SKI. &lt;p/&gt;Conclusions: These findings support the theory that the GATA1s isoform plays a role in the maintenance of proliferative multipotent megakaryocyte-erythroid precursor cells and must be down-regulated prior to terminal differentiation. In addition our data suggest that SKI may be a potential therapeutic target for the treatment of children with DS-AMKL

Analysis of SARS-CoV-2 antibody seroprevalence in Northern Ireland during 2020–2021

BackgroundWith the spread of SARS-CoV-2 impacting upon public health directly and socioeconomically, further information was required to inform policy decisions designed to limit virus spread during the pandemic. This study sought to contribute to serosurveillance work within Northern Ireland to track SARS-CoV-2 progression and guide health strategy.MethodsSera/plasma samples from clinical biochemistry laboratories were analysed for anti-SARS-CoV-2 antibodies. Samples were assessed using an Elecsys anti-SARS-CoV-2 or anti-SARS-CoV-2 S ECLIA (Roche) on an automated cobas e 801 analyser. Samples were also assessed via an anti-SARS-CoV-2 ELISA (Euroimmun). A subset of samples assessed via the Elecsys anti-SARS-CoV-2 ECLIA were subsequently analysed in an ACE2 pseudoneutralisation assay using a V-PLEX SARS-CoV-2 Panel 7 for IgG and ACE2 (Meso Scale Diagnostics).ResultsAcross three testing rounds (June–July 2020, November–December 2020 and June–July 2021 (rounds 1–3 respectively)), 4844 residual sera/plasma specimens were assayed for anti-SARS-CoV-2 antibodies. Seropositivity rates increased across the study, peaking at 11.6 % (95 % CI 10.4%–13.0 %) during round 3. Varying trends in SARS-CoV-2 seropositivity were noted based on demographic factors. For instance, highest rates of seropositivity shifted from older to younger demographics across the study period. In round 3, Alpha (B.1.1.7) variant neutralising antibodies were most frequently detected across age groups, with median concentration of anti-spike protein antibodies elevated in 50–69 year olds and anti-S1 RBD antibodies elevated in 70+ year olds, relative to other age groups.ConclusionsWith seropositivity rates of &lt;15 % across the assessment period, it can be concluded that the significant proportion of the Northern Ireland population had not yet naturally contracted the virus by mid-2021