DNA-Chip Analyzer (dChip)

BBX21 Integrates Brassinosteroid Biosynthesis and Signaling in the Inhibition of Hypocotyl Growth under Shade

B-Box-containing zinc finger transcription factors (BBX) are involved in light-mediated growth, affecting processes such as hypocotyl elongation in Arabidopsis thaliana. However, the molecular and hormonal framework that regulates plant growth through BBX proteins is incomplete. Here, we demonstrate that BBX21 inhibits the hypocotyl elongation through the brassinosteroid (BR) pathway. BBX21 reduces the sensitivity to 24-epiBL, a synthetic active BR, principally at very low concentrations in simulated shade. The biosynthesis profile of BRs showed that two active BR-brassinolide and 28-homobrassinolide-and 8 of 11 intermediates can be repressed by BBX21 under white light (WL) or simulated shade. Furthermore, BBX21 represses the expression of CYTOCHROME P450 90B1 (DWF4/CYP90B1), BRASSINOSTEROID-6-OXIDASE 1 (BR6OX1, CYP85A1) and BR6OX2 (CYP85A2) genes involved in the BR biosynthesis in WL while specifically promoting DWF4 and PHYB ACTIVATION TAGGED SUPPRESSOR 1 (CYP2B1/BAS1) expression in WL supplemented with far-red (WL + FR), a treatment that simulates shade. In addition, BBX21 represses BR signaling genes, such as PACLOBUTRAZOL RESISTANCE1 (PRE1), PRE3 and ARABIDOPSIS MYB-LIKE 2 (MYBL2), and auxin-related and expansin genes, such as INDOLE-3-ACETIC ACID INDUCIBLE 1 (IAA1), IAA4 and EXPANSIN 11 in short-term shade. By a genetic approach, we found that BBX21 acts genetically upstream of BRASSINAZOLE-RESISTANT 1 (BZR1) for the promotion of DWF4 and BAS1 gene expression in shade. We propose that BBX21 integrates the BR homeostasis and shade-light signaling, allowing the fine-tuning of hypocotyl elongation in Arabidopsis.

Higher-order correction of persistent batch effects in correlation networks

MOTIVATION

Systems biology analyses often use correlations in gene expression profiles to infer co-expression networks that are then used as input for gene regulatory network inference or to identify functional modules of co-expressed or putatively co-regulated genes. While systematic biases, including batch effects, are known to induce spurious associations and confound differential gene expression analyses (DE), the impact of batch effects on gene co-expression has not been fully explored. Methods have been developed to adjust expression values, ensuring conditional independence of mean and variance from batch or other covariates for each gene, resulting in improved fidelity of DE analysis. However, such adjustments do not address the potential for spurious differential co-expression (DC) between groups. Consequently, uncorrected, artifactual DC can skew the correlation structure, leading to the identification of false, non-biological associations, even when the input data are corrected using standard batch correction.

RESULTS

In this work, we demonstrate the persistence of confounders in covariance after standard batch correction using synthetic and real-world gene expression data examples. We then introduce Co-expression Batch Reduction Adjustment (COBRA), a method for computing a batch-corrected gene co-expression matrix based on estimating a conditional covariance matrix. COBRA estimates a reduced set of parameters expressing the co-expression matrix as a function of the sample covariates, allowing control for continuous and categorical covariates. COBRA is computationally efficient, leveraging the inherently modular structure of genomic data to estimate accurate gene regulatory associations and facilitate functional analysis for high-dimensional genomic data.

AVAILABILITY AND IMPLEMENTATION

COBRA is available under the GLP3 open source license in R and Python in netZoo (https://netzoo.github.io).

Characterization of the effects of outliers on ComBat harmonization for removing inter-site data heterogeneity in multisite neuroimaging studies

Data harmonization is a key step widely used in multisite neuroimaging studies to remove inter-site heterogeneity of data distribution. However, data harmonization may even introduce additional inter-site differences in neuroimaging data if outliers are present in the data of one or more sites. It remains unclear how the presence of outliers could affect the effectiveness of data harmonization and consequently the results of analyses using harmonized data. To address this question, we generated a normal simulation dataset without outliers and a series of simulation datasets with outliers of varying properties (e.g., outlier location, outlier quantity, and outlier score) based on a real large-sample neuroimaging dataset. We first verified the effectiveness of the most commonly used ComBat harmonization method in the removal of inter-site heterogeneity using the normal simulation data, and then characterized the effects of outliers on the effectiveness of ComBat harmonization and on the results of association analyses between brain imaging-derived phenotypes and a simulated behavioral variable using the simulation datasets with outliers. We found that, although ComBat harmonization effectively removed the inter-site heterogeneity in multisite data and consequently improved the detection of the true brain-behavior relationships, the presence of outliers could damage severely the effectiveness of ComBat harmonization in the removal of data heterogeneity or even introduce extra heterogeneity in the data. Moreover, we found that the effects of outliers on the improvement of the detection of brain-behavior associations by ComBat harmonization were dependent on how such associations were assessed (i.e., by Pearson correlation or Spearman correlation), and on the outlier location, quantity, and outlier score. These findings help us better understand the influences of outliers on data harmonization and highlight the importance of detecting and removing outliers prior to data harmonization in multisite neuroimaging studies.

Identification of oncogenic signaling pathways associated with the dimorphic metabolic dysregulations in gastric cancer subtypes

Metabolic dysregulations have been identified as intrinsic hallmarks of cancer cells. Investigations of altered metabolic processes, in the context of the associated oncogenic signaling pathways are expected to pave way for the development of targeted cancer therapeutics. We have recently identified the enrichment of glucose and glutamine metabolism in a subset of intestinal subtype gastric tumors at the level of expression of genes, gene sets and the occurrence of metabolites. On the other hand, glucose transport, glucan and fatty acid metabolism were enriched in a subset of diffuse subtype gastric tumors. In the current study, along with glucose metabolism, mTOR, HSP90, MYC, E2F, P53 and proteasome pathways were found enriched in a subset of intestinal subtype and a part of MSI subtype gastric tumors. On the other hand, along with fatty acid metabolism, the oncogenic pathway KRAS was found to be enriched in a subset of GS tumors among diffuse subtype gastric tumors. Thus, oncogenic signaling pathways associated with two distinct metabolic rewiring which differentially occurs between major gastric cancer subtypes were identified. These pathways seem the potential targets to differentially target these gastric cancer subtypes. Exploratory integrative genomic analyses reveal HSP90 inhibitors, AKT/mTOR inhibitors, and cell cycle inhibitors as potential agents to target the gastric tumors with the rewired glucose metabolism and MEK/MAPK inhibitors as suitable drug candidates to target the diffuse subtype tumors with the dysregulated fatty acid metabolism. This observation would pave way for the selective and targeted use of signaling pathway modulators for targeted and stratified gastric cancer therapeutics.

TET1 Directs Chondrogenic Differentiation by Regulating SOX9 Dependent Activation of Col2a1 and Acan In Vitro

Skeletal development is a tightly orchestrated process in which cartilage and bone differentiation are intricately intertwined. Recent studies have highlighted the contribution of epigenetic modifications and their writers to skeletal development. Methylated cytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the Ten-eleven-translocation (TET) enzymes leading to demethylation. We have previously demonstrated that 5hmC is stably accumulated on lineage-specific genes that are activated during in vitro chondrogenesis in the ATDC5 chondroprogenitors. Knockdown (KD) of Tet1 via short-hairpin RNAs blocked ATDC5 chondrogenic differentiation. Here, we aimed to provide the mechanistic basis for TET1 function during ATDC5 differentiation. Transcriptomic analysis of Tet1 KD cells demonstrated that 54% of downregulated genes were SOX9 targets, suggesting a role for TET1 in mediating activation of a subset of the SOX9 target genes. Using genome-wide mapping of 5hmC during ATDC5 differentiation, we found that 5hmC is preferentially accumulated at chondrocyte-specific class II binding sites for SOX9, as compared with the tissue-agnostic class I sites. Specifically, we find that SOX9 is unable to bind to Col2a1 and Acan after Tet1 KD, despite no changes in SOX9 levels. Finally, we compared this KD scenario with the genetic loss of TET1 in the growth plate using Tet1 ^-/- embryos, which are approximately 10% smaller than their WT counterparts. In E17.5 Tet1 ^-/- embryos, loss of SOX9 target gene expression is more modest than upon Tet1 KD in vitro. Overall, our data suggest a role for TET1-mediated 5hmC deposition in partly shaping an epigenome conducive for SOX9 function. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Occurrence of differing metabolic dysregulations, a glucose driven and another fatty acid centric in gastric cancer subtypes

Gastric cancer is one of the most common cancers and ranks third in cancer-related deaths across globe. Cancer cells are known to take advantage of the altered metabolic processes to sustain their survival, proliferation, and cancer progression. In this investigation, we explored the available genome-wide expression profiles of few hundreds of gastric tumors and non-cancerous gastric tissues and analyzed in the context of metabolic pathways. Gastric tumors were investigated for the metabolic processes related to glucose metabolism, glucose transport, glutamine metabolism, and fatty acid metabolism, by metabolic pathway-focused gene set enrichment analysis. Notably, all glucose metabolism and glutamine metabolism-related gene sets were found enriched in intestinal subtype gastric tumors. On the other hand, the gene sets related to glucose transport and glucan (glycan) metabolisms are enriched in diffuse subtype gastric tumors. Strikingly, fatty acid metabolisms, fatty acid transport, and fat differentiation-related signatures are also highly activated in diffuse subtype gastric tumors. Exploration of the recently established metabolome profile of the massive panel of cell lines also revealed the metabolites of glucose and fatty acid metabolic pathways to show the differing abundance across gastric cancer subtypes. The subtype-specific metabolic rewiring and the existence of two distinct metabolic dysregulations involving glucose and fatty acid metabolism in gastric cancer subtypes have been identified. The identified differing metabolic dysregulations would pave way for the development of targeted therapeutic strategies for the gastric cancer subtypes.

Cumulus provides cloud-based data analysis for large-scale single-cell and single-nucleus RNA-seq

Massively parallel single-cell and single-nucleus RNA sequencing has opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so is the need for computational pipelines for scaled analysis. Here we developed Cumulus-a cloud-based framework for analyzing large-scale single-cell and single-nucleus RNA sequencing datasets. Cumulus combines the power of cloud computing with improvements in algorithm and implementation to achieve high scalability, low cost, user-friendliness and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.

Foxn4 is a temporal identity factor conferring mid/late-early retinal competence and involved in retinal synaptogenesis

During development, neural progenitors change their competence states over time to sequentially generate different types of neurons and glia. Several cascades of temporal transcription factors (tTFs) have been discovered in Drosophila to control the temporal identity of neuroblasts, but the temporal regulation mechanism is poorly understood in vertebrates. Mammalian retinal progenitor cells (RPCs) give rise to several types of neuronal and glial cells following a sequential yet overlapping temporal order. Here, by temporal cluster analysis, RNA-sequencing analysis, and loss-of-function and gain-of-function studies, we show that the Fox domain TF Foxn4 functions as a tTF during retinogenesis to confer RPCs with the competence to generate the mid/late-early cell types: amacrine, horizontal, cone, and rod cells, while suppressing the competence of generating the immediate-early cell type: retinal ganglion cells (RGCs). In early embryonic retinas, Foxn4 inactivation causes down-regulation of photoreceptor marker genes and decreased photoreceptor generation but increased RGC production, whereas its overexpression has the opposite effect. Just as in Drosophila, Foxn4 appears to positively regulate its downstream tTF Casz1 while negatively regulating its upstream tTF Ikzf1. Moreover, retina-specific ablation of Foxn4 reveals that it may be indirectly involved in the synaptogenesis, establishment of laminar structure, visual signal transmission, and long-term maintenance of the retina. Together, our data provide evidence that Foxn4 acts as a tTF to bias RPCs toward the mid/late-early cell fates and identify a missing member of the tTF cascade that controls RPC temporal identities to ensure the generation of proper neuronal diversity in the retina.

Discriminant Analysis of Lung Cancer Using Nonlinear Clustering of Copy Numbers

Background: Patient survival is not optimal for non-small cell lung cancer (NSCLC) patients, recurrence rate is high, and hence, early detection is crucial to increase the patient's survival. Gene-cancer mapping intends to discover associated genes with cancers and due to advances in high-throughput genotyping, screening for disease loci on a genome-wide scale is now possible. DNA copy numbers can potentially be used to identify cancer from normal cells in early detection of cancer.Methods: We use a nonlinear clustering method, so-called kernel K-means to separate cancer from normal samples. Kernel K-means is applied to the copy numbers obtained for each chromosome to cluster 63 paired cancer-blood samples (total of 126 samples) into two groups. Clustering performance is evaluated using true and false-positive rates, true and false-negative rates, and a nonlinear criterion, normalized mutual information (NMI).Results: Copy numbers of paired cancer-blood samples for 63 NSCLC patients are used in this study. Kernel K-means was applied to cluster 126 samples in two groups using copy numbers on each chromosome separately. The clustering results for 22 chromosomes are evaluated and discriminant power of them in identifying cancer is computed. We identified the top five and bottom five chromosomes based on their discriminant power.Conclusions: The results reveal high discriminant power of chromosomes 8, 5, 1, 3, and 19 for identifying cancer with the highest sensitivity of 75% yielded by chromosome 5. Bottom 5 chromosomes 9, 6, 4, 13, and 21 show low discriminant power with the accuracy of below 54% where true cancer and normal samples are grouped into substantially overlapping groups using copy numbers. This indicates the similarities of copy numbers obtained for cancer and normal samples on these chromosomes.

Managing batch effects in microbiome data

Microbial communities have been increasingly studied in recent years to investigate their role in ecological habitats. However, microbiome studies are difficult to reproduce or replicate as they may suffer from confounding factors that are unavoidable in practice and originate from biological, technical or computational sources. In this review, we define batch effects as unwanted variation introduced by confounding factors that are not related to any factors of interest. Computational and analytical methods are required to remove or account for batch effects. However, inherent microbiome data characteristics (e.g. sparse, compositional and multivariate) challenge the development and application of batch effect adjustment methods to either account or correct for batch effects. We present commonly encountered sources of batch effects that we illustrate in several case studies. We discuss the limitations of current methods, which often have assumptions that are not met due to the peculiarities of microbiome data. We provide practical guidelines for assessing the efficiency of the methods based on visual and numerical outputs and a thorough tutorial to reproduce the analyses conducted in this review.

Requirement of the Mowat-Wilson Syndrome Gene Zeb2 in the Differentiation and Maintenance of Non-photoreceptor Cell Types During Retinal Development

Mutations in the human transcription factor gene ZEB2 cause Mowat-Wilson syndrome, a congenital disorder characterized by multiple and variable anomalies including microcephaly, Hirschsprung disease, intellectual disability, epilepsy, microphthalmia, retinal coloboma, and/or optic nerve hypoplasia. Zeb2 in mice is involved in patterning neural and lens epithelia, neural tube closure, as well as in the specification, differentiation and migration of neural crest cells and cortical neurons. At present, it is still unclear how Zeb2 mutations cause retinal coloboma, whether Zeb2 inactivation results in retinal degeneration, and whether Zeb2 is sufficient to promote the differentiation of different retinal cell types. Here, we show that during mouse retinal development, Zeb2 is expressed transiently in early retinal progenitors and in all non-photoreceptor cell types including bipolar, amacrine, horizontal, ganglion, and Müller glial cells. Its retina-specific ablation causes severe loss of all non-photoreceptor cell types, cell fate switch to photoreceptors by retinal progenitors, and elevated apoptosis, which lead to age-dependent retinal degeneration, optic nerve hypoplasia, synaptic connection defects, and impaired ERG (electroretinogram) responses. Moreover, overexpression of Zeb2 is sufficient to promote the fate of all non-photoreceptor cell types at the expense of photoreceptors. Together, our data not only suggest that Zeb2 is both necessary and sufficient for the differentiation of non-photoreceptor cell types while simultaneously inhibiting the photoreceptor cell fate by repressing transcription factor genes involved in photoreceptor specification and differentiation, but also reveal a necessity of Zeb2 in the long-term maintenance of retinal cell types. This work helps to decipher the etiology of retinal atrophy associated with Mowat-Wilson syndrome and hence will impact on clinical diagnosis and management of the patients suffering from this syndrome.

Dissection of genetic regulation of compound inflorescence development in Medicago truncatula

Development of inflorescence architecture is controlled by genetic regulatory networks. TERMINAL FLOWER1 (TFL1), APETALA1 (AP1), LEAFY (LFY) and FRUITFULL (FUL) are core regulators for inflorescence development. To understand the regulation of compound inflorescence development, we characterized mutants of corresponding orthologous genes, MtTFL1, MtAP1, SINGLE LEAFLET1 (SGL1) and MtFULc, in Medicago truncatula, and analyzed expression patterns of these genes. Results indicate that MtTFL1, MtFULc, MtAP1 and SGL1 play specific roles in identity determination of primary inflorescence meristems, secondary inflorescence meristems, floral meristems and common primordia, respectively. Double mutation of MtTFL1 and MtFULc transforms compound inflorescences to simple flowers, whereas single mutation of MtTFL1 changes the inflorescence branching pattern from monopodial to sympodial. Double mutant mtap1sgl1 completely loses floral meristem identity. We conclude that inflorescence architecture in M. truncatula is controlled by spatiotemporal expression of MtTFL1, MtFULc, MtAP1 and SGL1 through reciprocal repression. Although this regulatory network shares similarity with the pea model, it has specificity in regulating inflorescence architecture in Mtruncatula This study establishes M. truncatula as an excellent genetic model for understanding compound inflorescence development in related legume crops.

The Effect of Aromatic Hydrocarbon Receptor on the Phenotype of the Hepa 1c1c7 Murine Hepatoma Cells in the Absence of Dioxin

The aromatic hydrocarbon receptor (AhR) mediates biological responses to certain exogenous ligands, such as the environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), and has also been demonstrated to modulate the cell cycle and differentiated state of several cell lines independently of exogenous ligands. In this study, we used DNA micorarray analysis to elucidate the profile of genes responsive to the expression of unliganded AhR by re-introducing AhR into an AhR-deficient mouse derivative (c19) of the mouse hepatoma cell line Hepa1c1c7. 22 gene products were up-regulated and 8 were down-regulated two-fold or more in c19 cells infected with a retroviral vector expressing mouse AhR. Surprisingly, expression of genes involved in cell proliferation or differentiation were not affected by introduction of AhR. AhR also did not restore expression of the albumin gene in c19 cells. Introduction of AhR into c12, a similar AhR-defective mouse hepatoma cell line, also did not restore albumin expression, and furthermore, did not lead to changes in cellular morphology or cell cycle parameters. These observations fail to support the notion that unliganded AhR regulates proliferation and differentiation of liver-derived cells.

Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC

PURPOSE

To evaluate the prognostic value and molecular basis of a CT-derived pleural contact index (PCI) in early stage non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

We retrospectively analysed seven NSCLC cohorts. A quantitative PCI was defined on CT as the length of tumour-pleura interface normalised by tumour diameter. We evaluated the prognostic value of PCI in a discovery cohort (n = 117) and tested in an external cohort (n = 88) of stage I NSCLC. Additionally, we identified the molecular correlates and built a gene expression-based surrogate of PCI using another cohort of 89 patients. To further evaluate the prognostic relevance, we used four datasets totalling 775 stage I patients with publically available gene expression data and linked survival information.

RESULTS

At a cutoff of 0.8, PCI stratified patients for overall survival in both imaging cohorts (log-rank p = 0.0076, 0.0304). Extracellular matrix (ECM) remodelling was enriched among genes associated with PCI (p = 0.0003). The genomic surrogate of PCI remained an independent predictor of overall survival in the gene expression cohorts (hazard ratio: 1.46, p = 0.0007) adjusting for age, gender, and tumour stage.

CONCLUSIONS

CT-derived pleural contact index is associated with ECM remodelling and may serve as a noninvasive prognostic marker in early stage NSCLC.

KEY POINTS

• A quantitative pleural contact index (PCI) predicts survival in early stage NSCLC. • PCI is associated with extracellular matrix organisation and collagen catabolic process. • A multi-gene surrogate of PCI is an independent predictor of survival. • PCI can be used to noninvasively identify patients with poor prognosis.

JunD/AP-1 Antagonizes the Induction of DAPK1 To Promote the Survival of v-Src-Transformed Cells

The increase in AP-1 activity is a hallmark of cell transformation by tyrosine kinases. Previously, we reported that blocking AP-1 using the c-Jun dominant negative mutant TAM67 induced senescence, adipogenesis, or apoptosis in v-Src-transformed chicken embryo fibroblasts (CEFs) whereas inhibition of JunD by short hairpin RNA (shRNA) specifically induced apoptosis. To investigate the role of AP-1 in Src-mediated transformation, we undertook a gene profiling study to characterize the transcriptomes of v-Src-transformed CEFs expressing either TAM67 or the JunD shRNA. Our study revealed a cluster of 18 probe sets upregulated exclusively in response to AP-1/JunD impairment and v-Src transformation. Four of these probe sets correspond to genes involved in the interferon pathway. One gene in particular, death-associated protein kinase 1 (DAPK1), is a C/EBPβ-regulated mediator of apoptosis in gamma interferon (IFN-γ)-induced cell death. Here, we show that inhibition of DAPK1 abrogates cell death in v-Src-transformed cells expressing the JunD shRNA. Chromatin immunoprecipitation data indicated that C/EBPβ was recruited to the DAPK1 promoter while the expression of a dominant negative mutant of C/EBPβ abrogated the induction of DAPK1 in response to the inhibition of AP-1. In contrast, as determined by chromatin immunoprecipitation (ChIP) assays, JunD was not detected on the DAPK1 promoter under any conditions, suggesting that JunD promotes survival by indirectly antagonizing the expression of DAPK1 in v-Src transformed cells.

IMPORTANCE

Transformation by the v-Src oncoprotein causes extensive changes in gene expression in primary cells such as chicken embryo fibroblasts. These changes, determining the properties of transformed cells, are controlled in part at the transcriptional level. Much attention has been devoted to transcription factors such as AP-1 and NF-κB and the control of genes associated with a more aggressive phenotype. In this report, we describe a novel mechanism of action determined by the JunD component of AP-1, a factor enhancing cell survival in v-Src-transformed cells. We show that the loss of JunD results in the aberrant activation of a genetic program leading to cell death. This program requires the activation of the tumor suppressor death-associated protein kinase 1 (DAPK1). Since DAPK1 is phosphorylated and inhibited by v-Src, these results highlight the importance of this kinase and the multiple mechanisms controlled by v-Src to antagonize the tumor suppressor function of DAPK1.

Convergence of CONSTITUTIVE PHOTOMORPHOGENESIS 1 and PHYTOCHROME INTERACTING FACTOR signalling during shade avoidance

Shade-avoidance responses require CONSTITUTIVE PHOTOMORPHOGENESIS 1 (COP1) but the mechanisms of action of COP1 under shade have not been elucidated. Using simulated shade and control conditions, we analysed: the transcriptome and the auxin levels of cop1 and phytochrome interacting factor 1 (pif1) pif3 pif4 pif5 (pifq) mutants; the dynamics of ELONGATED HYPOCOTYL 5 (HY5) and LONG HYPOCOTYL IN FAR-RED (HFR1) proteins; and the epistatic relationships between cop1 and pif3, pif4, pif5, hy5 and hfr1 mutations in Arabidopsis thaliana. Despite severely impaired shade-avoidance responses, only a few genes that responded to shade in the wild-type failed to do so in cop1. Shade enhanced the convergence between cop1 and pifq transcriptomes, mainly on shade-avoidance marker genes. Shade failed to increase auxin levels in cop1. Residual shade avoidance in cop1 was not further reduced by the pif3, pif4 or pif5 mutations, suggesting convergent pathways. HFR1 stability decreased under shade in a COP1-dependent manner but shade increased HY5 stability. The cop1 mutant retains responses to shade and is more specifically impaired in shade avoidance. COP1 promotes the degradation of HFR1 under shade, thus increasing the ability of PIFs to control gene expression, increase auxin levels and promote stem growth.

Identification and evolution of the orphan genes in the domestic silkworm, Bombyx mori

Orphan genes (OGs) which have no recognizable homology to any sequences in other species could contribute to the species specific adaptations. In this study, we identified 738 OGs in the silkworm genome. About 31% of the silkworm OGs is derived from transposable elements, and 5.1% of the silkworm OGs emerged from gene duplication followed by divergence of paralogs. Five de novo silkworm OGs originated from non-coding regions. Microarray data suggested that most of the silkworm OGs were expressed in limited tissues. RNA interference experiments suggested that five de novo OGs are not essential to the silkworm, implying that they may contribute to genetic redundancy or species-specific adaptation. Our results provide some new insights into the evolutionary significance of the silkworm OGs.

Dermcidin exerts its oncogenic effects in breast cancer via modulation of ERBB signaling

Background

We previously identified dermicidin (DCD), which encodes a growth and survival factor, as a gene amplified and overexpressed in a subset of breast tumors. Patients with DCD-positive breast cancer have worse prognostic features. We therefore searched for specific molecular signatures in DCD-positive breast carcinomas from patients and representative cell lines.

Methods

DCD expression was evaluated by qRT-PCR, immunohistochemical and immunoblot assays in normal and neoplastic tissues and cell lines. To investigate the role of DCD in breast tumorigenesis, we analyzed the consequences of its downregulation in human breast cancer cell lines using three specific shRNA lentiviral vectors. Genes up- and down-regulated by DCD were identified using Affymetrix microarray and analyzed by MetaCore Platform.

Results

We identified DCD splice variant (DCD-SV) that is co-expressed with DCD in primary invasive breast carcinomas and in other tissue types and cell lines. DCD expression in breast tumors from patients with clinical follow up data correlated with high histological grade, HER2 amplification and luminal subtype. We found that loss of DCD expression led to reduced cell proliferation, resistance to apoptosis, and suppressed tumorigenesis in immunodeficient mice. Network analysis of gene expression data revealed perturbed ERBB signaling following DCD shRNA expression including changes in the expression of ERBB receptors and their ligands.

Conclusions

These findings imply that DCD promotes breast tumorigenesis via modulation of ERBB signaling pathways. As ERBB signaling is also important for neural survival, HER2+ breast tumors may highjack DCD’s neural survival-promoting functions to promote tumorigenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1022-6) contains supplementary material, which is available to authorized users.

High-temporal-resolution view of transcription and chromatin states across distinct metabolic states in budding yeast

Under continuous, glucose-limited conditions, budding yeast exhibit robust metabolic cycles associated with major oscillations of gene expression. How such fluctuations are linked to changes in chromatin status is not well understood. Here we examine the correlated genome-wide transcription and chromatin states across the yeast metabolic cycle at unprecedented temporal resolution, revealing a 'just-in-time supply chain' by which components from specific cellular processes such as ribosome biogenesis become available in a highly coordinated manner. We identify distinct chromatin and splicing patterns associated with different gene categories and determine the relative timing of chromatin modifications relative to maximal transcription. There is unexpected variation in the chromatin modification and expression relationship, with histone acetylation peaks occurring with varying timing and 'sharpness' relative to RNA expression both within and between cycle phases. Chromatin-modifier occupancy reveals subtly distinct spatial and temporal patterns compared to those of the modifications themselves.

Evaluation of copy number variation detection for a SNP array platform

Background

Copy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform.

We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the “gold standard”. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the “gold standard”. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package.

Results

Simply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest.

Conclusion

We found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling.

The radial nuclear positioning of genes correlates with features of megabase-sized chromatin domains

A nonrandom radial nuclear organization of genes has been well documented. This study provides further evidence that radial positioning depends on features of corresponding ∼1 Mbp chromatin domains (CDs), which represent the basic units of higher-order chromatin organization. We performed a quantitative three-dimensional analysis of the radial nuclear organization of three genes located on chromosome 1 in a DG75 Burkitt lymphoma-derived cell line. Quantitative real-time polymerase chain reaction revealed similar transcription levels for the three selected genes, whereas the total expression strength (TES) calculated as the sum of transcription of all genes annotated within a surrounding window of about 1 Mbp DNA differed for each region. Radial nuclear position of the studied CDs correlated with TES, i.e., the domain with the highest TES occupied the most interior position. Positions of CDs with stable TES values were stably maintained even under experimental conditions, resulting in genome-wide changes of the expression levels of many other genes. Our results strongly support the hypothesis that knowledge of the local chromatin environment is essential to predict the radial nuclear position of a gene.

Forkhead box N4 (Foxn4) activates Dll4-Notch signaling to suppress photoreceptor cell fates of early retinal progenitors

The generation of diverse neuronal types and subtypes from multipotent progenitors during development is crucial for assembling functional neural circuits in the adult central nervous system. During mouse retinogenesis, early retinal progenitors give rise to several cell types, including ganglion, amacrine, horizontal, cone, and rod cells. It is unknown at present how each of these fates is selected from the multiple neuronal fates available to the early progenitor. By using a combination of bioinformatic, genetic, and biochemical approaches, we investigated the mechanism by which Foxn4 selects the amacrine and horizontal cell fates from multipotential retinal progenitors. These studies indicate that Foxn4 has an intrinsic activity to suppress the alternative photoreceptor cell fates of early retinal progenitors by selectively activating Dll4-Notch signaling. Gene expression and conditional ablation analyses reveal that Dll4 is directly activated by Foxn4 via phylogenetically conserved enhancers and that Dll4 can partly mediate the Foxn4 function by serving as a major Notch ligand to expand the progenitor pool and limit photoreceptor production. Our data together define a Foxn4-mediated molecular and signaling pathway that underlies the suppression of alternative cell fates of early retinal progenitors.

Analysis of tanshinone IIA induced cellular apoptosis in leukemia cells by genome-wide expression profiling

BACKGROUND

Tanshinone IIA (Tan IIA) is a diterpene quinone extracted from the root of Salvia miltiorrhiza, a Chinese traditional herb. Although previous studies have reported the anti-tumor effects of Tan IIA on various human cancer cells, the underlying mechanisms are not clear. The current study was undertaken to investigate the molecular mechanisms of Tan IIA's apoptotic effects on leukemia cells in vitro.

METHODS

The cytotoxicity of Tan IIA on different types of leukemia cell lines was evaluated by the 3-[4,5-dimethylthiazol-2,5]-diphenyl tetrazolium bromide (MTT) assay on cells treated without or with Tan IIA at different concentrations for different time periods. Cellular apoptosis progression with and without Tan IIA treatment was analyzed by Annexin V and Caspase 3 assays. Gene expression profiling was used to identify the genes regulated after Tan IIA treatment and those differentially expressed among the five cell lines. Confirmation of these expression regulations was carried out using real-time quantitative PCR and ELISA. The antagonizing effect of a PXR inhibitor L-SFN on Tan IIA treatment was tested using Colony Forming Unit Assay.

RESULTS

Our results revealed that Tan IIA had different cytotoxic activities on five types of leukemia cells, with the highest toxicity on U-937 cells. Tan IIA inhibited the growth of U-937 cells in a time- and dose-dependent manner. Annexin V and Caspase-3 assays showed that Tan IIA induced apoptosis in U-937 cells. Using gene expression profiling, 366 genes were found to be significantly regulated after Tan IIA treatment and differentially expressed among the five cell lines. Among these genes, CCL2 was highly expressed in untreated U-937 cells and down-regulated significantly after Tan IIA treatment in a dose-dependent manner. RT-qPCR analyses validated the expression regulation of 80% of genes. Addition of L-sulforaphane (L-SFN), an inhibitor of Pregnane×receptor (PXR) significantly attenuated Tan IIA's effects using colony forming assays.

CONCLUSIONS

Tan IIA has significant growth inhibition effects on U-937 cells through the induction of apoptosis. And Tan IIA-induced apoptosis might result from the activation of PXR, which suppresses the activity of NF-κB and lead to the down-regulation of CCL2 expression.

Discovering transcription factor regulatory targets using gene expression and binding data

MOTIVATION

Identifying the target genes regulated by transcription factors (TFs) is the most basic step in understanding gene regulation. Recent advances in high-throughput sequencing technology, together with chromatin immunoprecipitation (ChIP), enable mapping TF binding sites genome wide, but it is not possible to infer function from binding alone. This is especially true in mammalian systems, where regulation often occurs through long-range enhancers in gene-rich neighborhoods, rather than proximal promoters, preventing straightforward assignment of a binding site to a target gene.

RESULTS

We present EMBER (Expectation Maximization of Binding and Expression pRofiles), a method that integrates high-throughput binding data (e.g. ChIP-chip or ChIP-seq) with gene expression data (e.g. DNA microarray) via an unsupervised machine learning algorithm for inferring the gene targets of sets of TF binding sites. Genes selected are those that match overrepresented expression patterns, which can be used to provide information about multiple TF regulatory modes. We apply the method to genome-wide human breast cancer data and demonstrate that EMBER confirms a role for the TFs estrogen receptor alpha, retinoic acid receptors alpha and gamma in breast cancer development, whereas the conventional approach of assigning regulatory targets based on proximity does not. Additionally, we compare several predicted target genes from EMBER to interactions inferred previously, examine combinatorial effects of TFs on gene regulation and illustrate the ability of EMBER to discover multiple modes of regulation.

AVAILABILITY

All code used for this work is available at http://dinner-group.uchicago.edu/downloads.html.

Identification of genomic deletions spanning the PCDH19 gene in two unrelated girls with intellectual disability and seizures

Recently, missense and truncating mutations in the gene PCDH19 have been reported to cause female-restricted epilepsy with mental retardation (EFMR). EFMR (MIM#300088) is an X-linked disorder characterized by early onset seizures and intellectual disability (ID). Interestingly, unlike typical X-linked mode of inheritance, the phenotype is restricted to females, and males are unaffected carriers. PCDH19 is highly expressed in brain, and the encoded protein belongs to the cadherin superfamily. Here we report two unrelated female patients with deletions spanning PCDH19 identified by copy number variation (CNV) analysis and validated by qPCR. In one, we have identified a 3 Mb interstitial deletion at Xq21.33-q22.1 which spans PCDH19, LOC442459 & TNMD. This patient had her first seizure at 8 months old, and also has ID and aggressive behavior. In another female patient we identified a de novo 603 kb heterozygous deletion in a female patient with fits (since 1 year of age), ID, hyperactivity and aggressive behavior. The deletion spans the entire PCDH19 gene (also TNMD, SRPX2, TSPAN6 and SYTL4). In conclusion, our results suggest that deletions at PCDH19 also cause EFMR.

Bayesian hierarchical mixture modeling to assign copy number from a targeted CNV array

Accurate assignment of copy number at known copy number variant (CNV) loci is important for both increasing understanding of the structural evolution of genomes as well as for carrying out association studies of copy number with disease. As with calling SNP genotypes, the task can be framed as a clustering problem but for a number of reasons assigning copy number is much more challenging. CNV assays have lower signal-to-noise ratios than SNP assays, often display heavy tailed and asymmetric intensity distributions, contain outlying observations and may exhibit systematic technical differences among different cohorts. In addition, the number of copy-number classes at a CNV in the population may be unknown a priori. Due to these complications, automatic and robust assignment of copy number from array data remains a challenging problem. We have developed a copy number assignment algorithm, CNVCALL, for a targeted CNV array, such as that used by the Wellcome Trust Case Control Consortium's recent CNV association study. We use a Bayesian hierarchical mixture model that robustly identifies both the number of different copy number classes at a specific locus as well as relative copy number for each individual in the sample. This approach is fully automated which is a critical requirement when analyzing large numbers of CNVs. We illustrate the methods performance using real data from the Wellcome Trust Case Control Consortium's CNV association study and using simulated data.

SNP and gene networks construction and analysis from classification of copy number variations data

BACKGROUND

Detection of genomic DNA copy number variations (CNVs) can provide a complete and more comprehensive view of human disease. It is interesting to identify and represent relevant CNVs from a genome-wide data due to high data volume and the complexity of interactions.

RESULTS

In this paper, we incorporate the DNA copy number variation data derived from SNP arrays into a computational shrunken model and formalize the detection of copy number variations as a case-control classification problem. More than 80% accuracy can be obtained using our classification model and by shrinkage, the number of relevant CNVs to disease can be determined. In order to understand relevant CNVs, we study their corresponding SNPs in the genome and a statistical software PLINK is employed to compute the pair-wise SNP-SNP interactions, and identify SNP networks based on their P-values. Our selected SNP networks are statistically significant compared with random SNP networks and play a role in the biological process. For the unique genes that those SNPs are located in, a gene-gene similarity value is computed using GOSemSim and gene pairs that have similarity values being greater than a threshold are selected to construct gene networks. A gene enrichment analysis show that our gene networks are functionally important.Experimental results demonstrate that our selected SNP and gene networks based on the selected CNVs contain some functional relationships directly or indirectly to disease study.

CONCLUSIONS

Two datasets are given to demonstrate the effectiveness of the introduced method. Some statistical and biological analysis show that this shrunken classification model is effective in identifying CNVs from genome-wide data and our proposed framework has a potential to become a useful analysis tool for SNP data sets.

Pre-processing optimization of RNA immunoprecipitation microarray data

Pre-mRNA splicing is an essential step in the post-transcriptional gene expression control involving protein-splicing factors like U2AF, which is exported to the cytoplasm and implicated in additional cellular functions. Identification of U2AF-associated mRNAs under native conditions was performed by immunoprecipitation and hybridization to Affymetrix GeneChip. Normalization and gene selection methods were performed, but the results were not reliable as they were different for different procedures, mainly because more than 20% of the mRNAs detected are differently enriched and the common normalization methods are based on small differences between them. We implemented a background correction method inspired in a non-specific hybridization method used for pre-processing data from ChIP-Chip technology. In this work, linear regression models are used to model in each array the non-specific hybridization, accounting for interactions between each three consecutive nucleotides into the probe sequence. Every probe intensity on the array was standardized using its predicted intensity and the probes' variance for similar predicted intensities. The standardized probe intensity values showed no need for further normalization and could be directly compared. We propose a probe set score, and a probe set enrichment value (ENRval) and its respective p-value for gene enrichment selection.

Gene expression analysis of dendritic cells that prevent diabetes in NOD mice: analysis of chemokines and costimulatory molecules

We have demonstrated previously that BM-derived DCs can prevent diabetes development and halt progression of insulitis in NOD mice, the mouse model of type 1 diabetes. The DC population that was most effective in this therapy had a mature phenotype, expressed high levels of costimulatory molecules, and secreted low levels of IL-12p70. The protective DC therapy induced Treg and Th2 cells in vitro and in vivo. Microarray analysis of therapeutic and nontherapeutic DC populations revealed differences in the expression of OX40L, CD200, Ym-1, CCL2, and CCL5, which could play important roles in the observed DC-mediated therapy. The unique pattern of costimulatory molecules and chemokines expressed by the therapeutic DCs was confirmed by flow cytometry and ELISA. Using a novel cell-labeling and (19)F NMR, we observed that the chemokines secreted by the therapeutic DCs altered the migration of diabetogenic Th1 cells in vivo and attracted Th2 cells. These results suggest that the therapeutic function of DCs is mediated by a combination of costimulatory and chemokine properties that results in the attraction of diabetogenic Th1 and the induction of Th2 and/or Treg differentiation.

Genetic and expression analysis of cattle identifies candidate genes in pathways responding to Trypanosoma congolense infection

African bovine trypanosomiasis caused by Trypanosoma sp., is a major constraint on cattle productivity in sub-Saharan Africa. Some African Bos taurus breeds are highly tolerant of infection, but the potentially more productive Bos indicus zebu breeds are much more susceptible. Zebu cattle are well adapted for plowing and haulage, and increasing their tolerance of trypanosomiasis could have a major impact on crop cultivation as well as dairy and beef production. We used three strategies to obtain short lists of candidate genes within QTL that were previously shown to regulate response to infection. We analyzed the transcriptomes of trypanotolerant N'Dama and susceptible Boran cattle after infection with Trypanosoma congolense. We sequenced EST libraries from these two breeds to identify polymorphisms that might underlie previously identified quantitative trait loci (QTL), and we assessed QTL regions and candidate loci for evidence of selective sweeps. The scan of the EST sequences identified a previously undescribed polymorphism in ARHGAP15 in the Bta2 trypanotolerance QTL. The polymorphism affects gene function in vitro and could contribute to the observed differences in expression of the MAPK pathway in vivo. The expression data showed that TLR and MAPK pathways responded to infection, and the former contained TICAM1, which is within a QTL on Bta7. Genetic analyses showed that selective sweeps had occurred at TICAM1 and ARHGAP15 loci in African taurine cattle, making them strong candidates for the genes underlying the QTL. Candidate QTL genes were identified in other QTL by their expression profile and the pathways in which they participate.

Light exerts multiple levels of influence on the Arabidopsis wound response

Light plays important roles in modulating plant responses to attack by pests and pathogens. Here, we test the hypothesis that darkness modifies the response to wounding, and examine possible mechanisms for such an effect. We investigated changes in the Arabidopsis transcriptome following a light-dark transition and the response to wounding either in the light or in the dark. The transcriptional response to the light-dark transition strongly resembles responses associated with carbon depletion. The dark shift and wound responses acted largely independently, but more complex interactions were identified at a number of levels. Darkness attenuates the overall transcriptional response to wounding, and we identified genes and physiological processes, such as anthocyanin accumulation, that exhibit light-dependent wound responses. Transcriptional activation of light-dependent wound-induced genes requires a chloroplast-derived signal originating from photosynthetic electron transport. We also present evidence of a role for the circadian clock in modifying wound responses. Our results show that darkness impacts on the wound response at a number of levels, which may imply differences in induced herbivore defences during the day and night.

hmChIP: a database and web server for exploring publicly available human and mouse ChIP-seq and ChIP-chip data

hmChIP is a database of genome-wide chromatin immunoprecipitation (ChIP) data in human and mouse. Currently, the database contains 2016 samples from 492 ChIP-seq and ChIP-chip experiments, representing a total of 170 proteins and 11 069 914 protein-DNA interactions. A web server provides interface for database query. Protein-DNA binding intensities can be retrieved from individual samples for user-provided genomic regions. The retrieved intensities can be used to cluster samples and genomic regions to facilitate exploration of combinatorial patterns, cell-type dependencies, and cross-sample variability of protein-DNA interactions.

AVAILABILITY

http://jilab.biostat.jhsph.edu/database/cgi-bin/hmChIP.pl.

Deformability-based cell classification and enrichment using inertial microfluidics

The ability to detect and isolate rare target cells from heterogeneous samples is in high demand in cell biology research, immunology, tissue engineering and medicine. Techniques allowing label-free cell enrichment or detection are especially important to reduce the complexity and costs towards clinical applications. Single-cell deformability has recently been recognized as a unique label-free biomarker for cell phenotype with implications for assessment of cancer invasiveness. Using a unique combination of fluid dynamic effects in a microfluidic system, we demonstrate high-throughput continuous label-free cell classification and enrichment based on cell size and deformability. The system takes advantage of a balance between deformability-induced and inertial lift forces as cells travel in a microchannel flow. Particles and droplets with varied elasticity and viscosity were found to have separate lateral dynamic equilibrium positions due to this balance of forces. We applied this system to successfully classify various cell types using cell size and deformability as distinguishing markers. Furthermore, using differences in dynamic equilibrium positions, we adapted the system to conduct passive, label-free and continuous cell enrichment based on these markers, enabling off-chip sample collection without significant gene expression changes. The presented method has practical potential for high-throughput deformability measurements and cost-effective cell separation to obtain viable target cells of interest in cancer research, immunology, and regenerative medicine.

Overlapping and distinct pRb pathways in the mammalian auditory and vestibular organs

Retinoblastoma gene (Rb1) is required for proper cell cycle exit in the developing mouse inner ear and its deletion in the embryo leads to proliferation of sensory progenitor cells that differentiate into hair cells and supporting cells. In a conditional hair cell Rb1 knockout mouse, Pou4f3-Cre-pRb(-/-), pRb(-/-) utricular hair cells differentiate and survive into adulthood whereas differentiation and survival of pRb(-/-) cochlear hair cells are impaired. To comprehensively survey the pRb pathway in the mammalian inner ear, we performed microarray analysis of (pRb(-/-) cochlea and utricle. The comparative analysis shows that the core pathway shared between pRb(-/-) cochlea and utricle is centered on E2F, the key pathway that mediates pRb function. A majority of differentially expressed genes and enriched pathways are not shared but uniquely associated with pRb(-/-) cochlea or utricle. In pRb(-/-) cochlea, pathways involved in early inner ear development such as Wnt/β-catenin and Notch were enriched, whereas pathways involving in proliferation and survival are enriched in pRb(-/-) utricle. Clustering analysis showed that the pRb(-/-) inner ear has characteristics of a younger control inner ear, an indication of delayed differentiation. We created a transgenic mouse model (ER-Cre-pRb(flox/flox)) in which Rb1 can be acutely deleted postnatally. Acute Rb1 deletion in the adult mouse fails to induce proliferation or cell death in inner ear, strongly indicating that Rb1 loss in these postmitotic tissues can be effectively compensated for, or that pRb-mediated changes in the postmitotic compartment result in events that are functionally irreversible once enacted. This study thus supports the concept that pRb-regulated pathways relevant to hair cell development, encompassing proliferation, differentiation and survival, act predominantly during early development.

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred.

AtBBX21 and COP1 genetically interact in the regulation of shade avoidance

Plants grown at high densities perceive the reduction in the ratio of red (R) to far-red (FR) light as a warning of competition. This light signal triggers morphological responses such as hypocotyl and stem elongation, and acceleration of flowering, which are known collectively as the shade-avoidance syndrome (SAS). Mutations in the photomorphogenic repressor COP1 suppress the SAS, but how COP1 modulates these responses is uncertain. We identified a new mutant with altered responses to natural shade, named lhus (long hypocotyl under shade). lhus seedlings have longer hypocotyls than wild-type under a low R:FR ratio, but not under sunlight or darkness. The lhus phenotype is due to a mutation affecting a B-box zinc finger transcription factor encoded by At1g75540, a gene previously reported as AtBBX21 that interacts with COP1 to control de-etiolation. Mutations in genes encoding other members of this protein family also result in impaired SAS regulation. Under short-term canopy shade, LHUS/BBX21 acts as positive regulator of SAS genes such as PAR1, HFR1, PIL1 and ATHB2. In contrast, global expression analysis of wild-type and lhus/bbx21 seedlings revealed that a large number of genes involved in hormonal signalling pathways are negatively regulated by LHUS/BBX21 in response to long-term canopy shade, and this observation fits well with the phenotype of lhus/bbx21 seedlings grown under a low R:FR ratio. Moreover, the bbx21 bbx22 double mutation restored the SAS in the cop1 background. We propose that LHUS/BBX21 and other B-box-containing proteins, such as BBX22, act downstream of COP1, and play a central role in early and long-term adjustment of the SAS in natural environments.

Efficacy of the multi-kinase inhibitor enzastaurin is dependent on cellular signaling context

The number of targeted small molecules being developed in oncology is increasing rapidly. Many of these are designed to inhibit multiple kinases, and thus the mechanisms of responsiveness and predictive biomarkers can be difficult to discern. In fact, with few exceptions, multi-kinase inhibitors are developed with limited mechanism-based patient selection. Enzastaurin is a multi-kinase inhibitor being studied in several malignancies that we hypothesized would be active in squamous cell carcinoma of the head and neck, because it inhibits classic and novel protein kinase C isoforms. Indeed, enzastaurin reduced the growth of SQ-20B and CAL27 tumor xenografts, decreased proliferation in these cell lines, inhibited putative target phosphorylation, and induced cell cycle arrest. Gene expression arrays confirmed that expression of cell cycle genes, including cyclins D and E, were significantly altered by exposure to enzastaurin. However, testing a panel of squamous cell carcinoma of the head and neck cell lines revealed variable sensitivity to enzastaurin, which correlated significantly with baseline cyclin D1 protein expression. Moreover, sensitivity and resistance could be reversed, respectively, by expression or depletion of cyclin D1. Furthermore, analysis of sensitive and resistant cell lines revealed distinct differences in cyclin D1 regulation. Enzastaurin modulated cyclin D1 synthesis through an Akt-regulated pathway in the former, whereas high-level CCND1 gene amplification was present in the latter. These results underscore the critical relevance of cellular signaling context in developing cancer therapies in general and suggest that enzastaurin in particular would be most effective in tumors where baseline cyclin D1 expression is low to moderate and physiologically regulated.

Low red/far-red ratios delay spike and stem growth in wheat

The responses to low red light/far-red light (R/FR) ratios simulating dense stands were evaluated in wheat (Triticum aestivum L) cultivars released at different times in the 20th century and consequently resulting from an increasingly prolonged breeding and selection history. While tillering responses to the R/FR ratio were unaffected by the cultivars, low R/FR ratios reduced grain yield per plant (primarily grain number and secondarily grain weight per plant) particularly in modern cultivars. Low R/FR ratios delayed spike growth and development, reduced the expression of spike marker genes, accelerated the development of florets already initiated, and reduced the number of fertile florets at anthesis. It is noteworthy that low R/FR ratios did not promote stem or leaf sheath growth and therefore the observed reduction of yield cannot be accounted for as a consequence of divergence of resources towards increased plant stature. It is proposed that the regulation of yield components by the R/FR ratio could help plants to adjust to the limited availability of resources under crop conditions.

Evaluating oligonucleotide properties for DNA microarray probe design

Most current microarray oligonucleotide probe design strategies are based on probe design factors (PDFs), which include probe hybridization free energy (PHFE), probe minimum folding energy (PMFE), dimer score, hairpin score, homology score and complexity score. The impact of these PDFs on probe performance was evaluated using four sets of microarray comparative genome hybridization (aCGH) data, which included two array manufacturing methods and the genomes of two species. Since most of the hybridizing DNA is equimolar in CGH data, such data are ideal for testing the general hybridization properties of almost all candidate oligonucleotides. In all our data sets, PDFs related to probe secondary structure (PMFE, hairpin score and dimer score) are the most significant factors linearly correlated with probe hybridization intensities. PHFE, homology and complexity score are correlating significantly with probe specificities, but in a non-linear fashion. We developed a new PDF, pseudo probe binding energy (PPBE), by iteratively fitting dinucleotide positional weights and dinucleotide stacking energies until the average residue sum of squares for the model was minimized. PPBE showed a better correlation with probe sensitivity and a better specificity than all other PDFs, although training data are required to construct a PPBE model prior to designing new oligonucleotide probes. The physical properties that are measured by PPBE are as yet unknown but include a platform-dependent component. A practical way to use these PDFs for probe design is to set cutoff thresholds to filter out bad quality probes. Programs and correlation parameters from this study are freely available to facilitate the design of DNA microarray oligonucleotide probes.

Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data

Background

Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools.

Results

We developed Survival Online (available at ), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses.

Conclusion

The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.

Using a mutual information-based site transition network to map the genetic evolution of influenza A/H3N2 virus

MOTIVATION

Mapping the antigenic and genetic evolution pathways of influenza A is of critical importance in the vaccine development and drug design of influenza virus. In this article, we have analyzed more than 4000 A/H3N2 hemagglutinin (HA) sequences from 1968 to 2008 to model the evolutionary path of the influenza virus, which allows us to predict its future potential drifts with specific mutations.

RESULTS

The mutual information (MI) method was used to design a site transition network (STN) for each amino acid site in the A/H3N2 HA sequence. The STN network indicates that most of the dynamic interactions are positioned around the epitopes and the receptor binding domain regions, with strong preferences in both the mutation sites and amino acid types being mutated to. The network also shows that antigenic changes accumulate over time, with occasional large changes due to multiple co-occurring mutations at antigenic sites. Furthermore, the cluster analysis by subdividing the STN into several subnetworks reveals a more detailed view about the features of the antigenic change: the characteristic inner sites and the connecting inter-subnetwork sites are both responsible for the drifts. A novel five-step prediction algorithm based on the STN shows a reasonable accuracy in reproducing historical HA mutations. For example, our method can reproduce the 2003-2004 A/H3N2 mutations with approximately 70% accuracy. The method also predicts seven possible mutations for the next antigenic drift in the coming 2009-2010 season. The STN approach also agrees well with the phylogenetic tree and antigenic maps based on HA inhibition assays.

AVAILABILITY

All code and data are available at http://ibi.zju.edu.cn/birdflu/.

Reciprocal effects of STAT5 and STAT3 in breast cancer

Breast cancer is often associated with inappropriate activation of transcription factors involved in normal mammary development. Two related transcription factors, signal transducer and activator of transcription (STAT) 5 and STAT3, play important and distinct roles in mammary development and both can be activated in breast cancer. However, the relative contribution of these STATs to mammary tumorigenesis is unknown. We have found that primary human breast tumors displaying activation of both STATs are more differentiated than those with STAT3 activation alone and display more favorable prognostic characteristics. To understand this difference, we have analyzed the effect of these STATs on gene regulation and phenotype of mammary carcinoma cells. STAT5 and STAT3 mediate opposing effects on several key target genes, with STAT5 exerting a dominant role. Using a model system of paired breast cancer cell lines, we found that coactivation of STAT5 and STAT3 leads to decreased proliferation and increased sensitivity to the chemotherapeutic drugs paclitaxel and vinorelbine compared with cells that have only STAT3 activation. Thus, STAT5 can modify the effects of STAT3 from the level of gene expression to cellular phenotype and analysis of the activation state of both STAT5 and STAT3 may provide important diagnostic and prognostic information in breast cancer.

Transcriptomic and network component analysis of glycerol kinase in skeletal muscle using a mouse model of glycerol kinase deficiency

Glycerol kinase (GK) is at the interface of fat and carbohydrate metabolism and has been linked to obesity and type 2 diabetes mellitus (T2DM). The purpose of this study was to investigate the role of GK in fat metabolism and insulin signaling in skeletal muscle (an important end organ tissue in T2DM). Microarray analysis determined that there were 525 genes that were differentially expressed (1.2-fold, p value<0.05) between knockout (KO) and wild-type (WT) mice. Quantitative PCR (qPCR) confirmed the differential expression of genes including glycerol kinase (Gyk), phosphatidylinositol 3-kinase regulatory subunit, polypeptide 1 (p85 alpha) (Pik3r1), insulin-like growth factor 1 (Igf1), and growth factor receptor bound protein 2-associated protein 1 (Gab1). Network component analysis demonstrated that transcription factor activities of myogenic differentiation 1 (MYOD), myogenic regulatory factor 5 (MYF5), myogenin (MYOG), nuclear receptor subfamily 4, group A, member 1 (NUR77) are decreased in the Gyk KO whereas the activity of paired box 3 (PAX3) is increased. The activity of MYOD was confirmed using a DNA binding assay. In addition, myoblasts from Gyk KO had less ability to differentiate into myotubes compared to WT myoblasts. These findings support our previous studies in brown adipose tissue and demonstrate that the role of Gyk in muscle is due in part to its non-metabolic (moonlighting) activities.

A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data

BACKGROUND

Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order to analyze microarray data. Two of the most known free analysis software packages are the R-based Bioconductor and dChip. The part of dChip software concerning the calculation and the analysis of gene expression has been modified to permit its execution on both cluster environments (supercomputers) and Grid infrastructures (distributed computing).This work is not aimed at replacing existing tools, but it provides researchers with a method to analyze large datasets without any hardware or software constraints.

RESULTS

An application able to perform the computation and the analysis of gene expression on large datasets has been developed using algorithms provided by dChip. Different tests have been carried out in order to validate the results and to compare the performances obtained on different infrastructures. Validation tests have been performed using a small dataset related to the comparison of HUVEC (Human Umbilical Vein Endothelial Cells) and Fibroblasts, derived from same donors, treated with IFN-alpha.Moreover performance tests have been executed just to compare performances on different environments using a large dataset including about 1000 samples related to Breast Cancer patients.

CONCLUSION

A Grid-enabled software application for the analysis of large Microarray datasets has been proposed. DChip software has been ported on Linux platform and modified, using appropriate parallelization strategies, to permit its execution on both cluster environments and Grid infrastructures. The added value provided by the use of Grid technologies is the possibility to exploit both computational and data Grid infrastructures to analyze large datasets of distributed data. The software has been validated and performances on cluster and Grid environments have been compared obtaining quite good scalability results.

Gene expression profiling reveals similarities between the in vitro and in vivo responses of immune effector cells to IFN-alpha

PURPOSE

The precise molecular targets of IFN-alpha therapy in the context of malignant melanoma are unknown but seem to involve signal transducers and activators of transcription 1 signal transduction within host immune effector cells. We hypothesized that the in vitro transcriptional response of patient peripheral blood mononuclear cells (PBMC) to IFN-alpha would be similar to the in vivo response to treatment with high-dose IFN-alpha.

EXPERIMENTAL DESIGN

The gene expression profiles of PBMCs and immune cell subsets treated in vitro with IFN-alpha were evaluated, as were PBMCs obtained from melanoma patients receiving adjuvant IFN-alpha.

RESULTS

Twenty-seven genes were up-regulated in PBMCs from normal donors after treatment with IFN-alpha in vitro for 18 hours (>2-fold, P < 0.001). A subset of these genes (in addition to others) was significantly expressed in IFN-alpha-treated T cells, natural killer cells, and monocytes. Analysis of gene expression within PBMCs from melanoma patients (n = 13) receiving high-dose IFN-alpha-2b (20 MU/m(2) i.v.) revealed significant up-regulation (>2-fold) of 21 genes (P < 0.001). Also, the gene expression profile of in vitro IFN-alpha-stimulated patient PBMCs was similar to that of PBMCs obtained from the same patient after IFN-alpha therapy.

CONCLUSIONS

This report is the first to describe the transcriptional response of T cells, natural killer cells, and monocytes to IFN-alpha and characterize the transcriptional profiles of PBMCs from melanoma patients undergoing IFN-alpha immunotherapy. In addition, it was determined that microarray analysis of patient PBMCs after in vitro stimulation with IFN-alpha may be a useful predictor of the in vivo response of immune cells to IFN-alpha immunotherapy.

Pheromone-regulated target genes respond differentially to MAPK phosphorylation of transcription factor Prf1

Pheromone signalling during mating is essential for pathogenicity of Ustilago maydis. The activity of the key transcription factor Prf1 is controlled at the transcriptional level and post-translationally by mitogen-activated protein kinase (MAPK) and protein kinase A (PKA) phosphorylation. However, the precise contribution of these regulatory mechanisms to the transcriptional output is unknown. Here, we genetically dissected the three levels of Prf1 regulation. We performed transcriptional profiling of respective mutants to identify and classify targets. This approach revealed that transcriptional regulation of prf1 had only minor influence on target gene expression stressing the importance of post-translational control. PKA regulation of Prf1 was sufficient to control expression of nine pheromone-responsive genes including the major transcription factor regulating pathogenicity. MAPK regulation was necessary for the pheromone response of a set of 57 genes. In 35 cases, pheromone responsiveness was completely lost, while in the remaining 22 cases regulation was alleviated. This indicated a novel level of complexity in MAPK signalling suggesting that target genes respond differentially to MAPK phosphorylation of the respective transcription factors.

Assays of MSCs with microarrays

The rapid development of microarray technology during the last decade has greatly expanded the ability to define the genes expressed in cells. This chapter will focus on describing the steps required for conducting successful microarray experiments with multipotential stromal cells (MSCs). A complete microarray experiment, using the Affymetrix system, will be described starting from experimental design and ending with examples of data analysis using the dChip program.