Error, reproducibility and sensitivity : a pipeline for data processing of Agilent oligonucleotide expression arrays

Background Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2% of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log2 units ( 6% of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells

Classical Morphology of Plants as an Elementary Instance of Classical Invariant Theory

It has long been known that structural chemistry shows an intriguing correspondence with Classical Invariant Theory (CIT). Under this view, an algebraic binary form of the degree n corresponds to a chemical atom with valence n and each physical molecule or ion has an invariant-theoretic counterpart. This theory was developed using the Aronhold symbolical approach and the symbolical processes of convolution/transvection in CIT was characterized as a potential “accurate morphological method”. However, CIT has not been applied to the formal morphology of living organisms. Based on the morphological interpretation of binary form, as well as the process of convolution/transvection, the First and Second Fundamental Theorems of CIT and the Nullforms of CIT, we show how CIT can be applied to the structure of plants, especially when conceptualized as a series of plant metamers (phytomers). We also show that the weight of the covariant/invariant that describes a morphological structure is a criterion of simplicity and, therefore, we argue that this allows us to formulate a parsimonious method of formal morphology. We demonstrate that the “theory of axilar bud” is the simplest treatment of the grass seedling/embryo. Our interpretations also represent Troll's bauplan of the angiosperms, the principle of variable proportions, morphological misfits, the basic types of stem segmentation, and Goethe's principle of metamorphosis in terms of CIT. Binary forms of different degrees might describe any repeated module of plant organisms. As bacteria, invertebrates, and higher vertebrates are all generally shared a metameric morphology, wider implications of the proposed symmetry between CIT and formal morphology of plants are apparent

Initiation of T cell signaling by CD45 segregation at 'close contacts'.

It has been proposed that the local segregation of kinases and the tyrosine phosphatase CD45 underpins T cell antigen receptor (TCR) triggering, but how such segregation occurs and whether it can initiate signaling is unclear. Using structural and biophysical analysis, we show that the extracellular region of CD45 is rigid and extends beyond the distance spanned by TCR-ligand complexes, implying that sites of TCR-ligand engagement would sterically exclude CD45. We also show that the formation of 'close contacts', new structures characterized by spontaneous CD45 and kinase segregation at the submicron-scale, initiates signaling even when TCR ligands are absent. Our work reveals the structural basis for, and the potent signaling effects of, local CD45 and kinase segregation. TCR ligands have the potential to heighten signaling simply by holding receptors in close contacts.The authors thank R.A. Cornall, M.L. Dustin and P.A. van der Merwe for comments on the manuscript and S. Ikemizu for useful discussions about the structure. We also thank W. Lu and T. Walter for technical support with protein expression and crystallization, the staff at Diamond Light Source beamlines I02, I03 and I04-1 (proposal mx10627) and European Synchrotron Radiation Facility beamlines ID23EH1 and ID23EH2 for assistance at the synchrotrons, G. Sutton for assistance with MALS experiments, and M. Fritzsche for advice on the calcium analysis. This work was funded by the Wellcome Trust (098274/Z/12/Z to S.J.D.; 090532/Z/09/Z to R.J.C.G.; 090708/Z/09/Z to D.K.), the UK Medical Research Council (G0700232 to A.R.A.), the Royal Society (UF120277 to S.F.L.) and Cancer Research UK (C20724/A14414 to C.S.; C375/A10976 to E.Y.J.). The Oxford Division of Structural Biology is part of the Wellcome Trust Centre for Human Genetics, Wellcome Trust Core Award Grant Number 090532/Z/09/Z. We acknowledge financial support from Instruct, an ESFRI Landmark Project. The OPIC electron microscopy facility was funded by a Wellcome Trust JIF award (060208/Z/00/Z).This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/ni.339

Estimating Grizzly and Black Bear Population Abundance and Trend in Banff National Park Using Noninvasive Genetic Sampling

We evaluated the potential of two noninvasive genetic sampling methods, hair traps and bear rub surveys, to estimate population abundance and trend of grizzly (Ursus arctos) and black bear (U. americanus) populations in Banff National Park, Alberta, Canada. Using Huggins closed population mark-recapture models, we obtained the first precise abundance estimates for grizzly bears ( = 73.5, 95% CI = 64–94 in 2006;  = 50.4, 95% CI = 49–59 in 2008) and black bears ( = 62.6, 95% CI = 51–89 in 2006;  = 81.8, 95% CI = 72–102 in 2008) in the Bow Valley. Hair traps had high detection rates for female grizzlies, and male and female black bears, but extremely low detection rates for male grizzlies. Conversely, bear rubs had high detection rates for male and female grizzlies, but low rates for black bears. We estimated realized population growth rates, lambda, for grizzly bear males ( = 0.93, 95% CI = 0.74–1.17) and females ( = 0.90, 95% CI = 0.67–1.20) using Pradel open population models with three years of bear rub data. Lambda estimates are supported by abundance estimates from combined hair trap/bear rub closed population models and are consistent with a system that is likely driven by high levels of human-caused mortality. Our results suggest that bear rub surveys would provide an efficient and powerful means to inventory and monitor grizzly bear populations in the Central Canadian Rocky Mountains

APOBEC3A Is a Specific Inhibitor of the Early Phases of HIV-1 Infection in Myeloid Cells

Myeloid cells play numerous roles in HIV-1 pathogenesis serving as a vehicle for viral spread and as a viral reservoir. Yet, cells of this lineage generally resist HIV-1 infection when compared to cells of other lineages, a phenomenon particularly acute during the early phases of infection. Here, we explore the role of APOBEC3A on these steps. APOBEC3A is a member of the APOBEC3 family that is highly expressed in myeloid cells, but so far lacks a known antiviral effect against retroviruses. Using ectopic expression of APOBEC3A in established cell lines and specific silencing in primary macrophages and dendritic cells, we demonstrate that the pool of APOBEC3A in target cells inhibits the early phases of HIV-1 infection and the spread of replication-competent R5-tropic HIV-1, specifically in cells of myeloid origins. In these cells, APOBEC3A affects the amount of vDNA synthesized over the course of infection. The susceptibility to the antiviral effect of APOBEC3A is conserved among primate lentiviruses, although the viral protein Vpx coded by members of the SIVSM/HIV-2 lineage provides partial protection from APOBEC3A during infection. Our results indicate that APOBEC3A is a previously unrecognized antiviral factor that targets primate lentiviruses specifically in myeloid cells and that acts during the early phases of infection directly in target cells. The findings presented here open up new venues on the role of APOBEC3A during HIV infection and pathogenesis, on the role of the cellular context in the regulation of the antiviral activities of members of the APOBEC3 family and more generally on the natural functions of APOBEC3A

The Consensus Molecular Subtypes of Colorectal Cancer

Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use -- https://www.nature.com/authors/policies/license.html#termsColorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC - with clear biological interpretability - and the basis for future clinical stratification and subtype-based targeted interventions

Comprehensive molecular characterization of the hippo signaling pathway in cancer

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional “omic” data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era