Nitrogen metabolism and gene expression landscape in maritime pine

This work was supported by the ProCoGen grant (FP7-KBBE-2011-5) and by the MicroNUpE grant (BIO2015-73512-JIN).Maritime pine (Pinus pinaster Aiton) is one the most important conifer species in the southwestern Mediterranean region because of its economic and environmental potential. For this reason, a work program in functional genomics has been developed in the frame of the ProCoGen project. One objective was to complete the knowledge about P. pinaster transcriptome with the tissue-specific localization of the gene expression of the low accumulated transcripts in sharper regions (Cañas et al. 2017). In order to reach these objectives total RNA was obtained from isolated tissues through laser capture microdissection (LCM). Due to the limiting amount from these extracts, the RNA samples were reverse-transcribed and the resultant cDNA amplified using our CRA+ protocol (Cañas et al. 2014). The obtained reads were assembled to improve the previous reference transcriptome. Reads were mapped against this transcriptome and the read accounts analyzed in order to found gene co-expression networks using the WGCNA software. These results have allowed us the characterization of nitrogen metabolism in maritime pine during the seedling stage stablishing relationships between the different components. This include the identification of new genes with low or very localized expression as occurred for the PpGS1c gene encoding a new cytosolic glutamine synthetase. From this starting point, we are developing a new project, MicroNUpE, to identify and study the genes involved in ammonium uptake and regulation in different root tissues that will be isolated through LCM. Cañas et al. (2017). Plant J, doi:10.1111/tpj.13617. Cañas et al. (2014). Tree Physiol, 34:1278-1288.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

On the gene expression landscape of cancer

A principal component analysis of the TCGA data for 15 cancer localizations unveils the following qualitative facts about tumors: 1) The state of a tissue in gene expression space may be described by a few variables. In particular, there is a single variable describing the progression from a normal tissue to a tumor. 2) Each cancer localization is characterized by a gene expression profile, in which genes have specific weights in the definition of the cancer state. There are no less than 2500 differentially-expressed genes, which lead to power-like tails in the expression distribution functions. 3) Tumors in different localizations share hundreds or even thousands of differentially expressed genes. There are 6 genes common to the 15 studied tumor localizations. 4) The tumor region is a kind of attractor. Tumors in advanced stages converge to this region independently of patient age or genetic variability. 5) There is a landscape of cancer in gene expression space with an approximate border separating normal tissues from tumors

Probing the endosperm gene expression landscape in Brassica napus

<p>Abstract</p> <p>Background</p> <p>In species with exalbuminous seeds, the endosperm is eventually consumed and its space occupied by the embryo during seed development. However, the main constituent of the early developing seed is the liquid endosperm, and a significant portion of the carbon resources for the ensuing stages of seed development arrive at the embryo through the endosperm. In contrast to the extensive study of species with persistent endosperm, little is known about the global gene expression pattern in the endosperm of exalbuminous seed species such as crucifer oilseeds.</p> <p>Results</p> <p>We took a multiparallel approach that combines ESTs, protein profiling and microarray analyses to look into the gene expression landscape in the endosperm of the oilseed crop <it>Brassica napus</it>. An EST collection of over 30,000 entries allowed us to detect close to 10,000 unisequences expressed in the endosperm. A protein profile analysis of more than 800 proteins corroborated several signature pathways uncovered by abundant ESTs. Using microarray analyses, we identified genes that are differentially or highly expressed across all developmental stages. These complementary analyses provided insight on several prominent metabolic pathways in the endosperm. We also discovered that a transcription factor <it>LEAFY COTYLEDON </it>(<it>LEC1</it>) was highly expressed in the endosperm and that the regulatory cascade downstream of <it>LEC1 </it>operates in the endosperm.</p> <p>Conclusion</p> <p>The endosperm EST collection and the microarray dataset provide a basic genomic resource for dissecting metabolic and developmental events important for oilseed improvement. Our findings on the featured metabolic processes and the <it>LEC1 </it>regulatory cascade offer new angles for investigation on the integration of endosperm gene expression with embryo development and storage product deposition in seed development.</p

Gene expression landscape of sdh-deficient gastrointestinal stromal tumors

Background: About 20–40% of gastrointestinal stromal tumors (GISTs) lacking KIT/PDGFRA mutations show defects in succinate dehydrogenase (SDH) complex. This study uncovers the gene expression profile (GEP) of SDH-deficient GIST in order to identify new signaling pathways or molecular events actionable for a tailored therapy. Methods: We analyzed 36 GIST tumor samples, either from formalin-fixed, paraf-fin-embedded by microarray or from fresh frozen tissue by RNA-seq, retrospectively collected among KIT-mutant and SDH-deficient GISTs. Pathway analysis was performed to highlight enriched and depleted transcriptional signatures. Tumor microenvironment and immune profile were also evaluated. Results: SDH-deficient GISTs showed a distinct GEP with respect to KIT-mutant GISTs. In particular, SDH-deficient GISTs were characterized by an increased expression of neural markers and by the activation of fibroblast growth factor receptor signaling and several biological pathways related to invasion and tumor progression. Among them, hypoxia and epithelial-to-mesenchymal transition emerged as features shared with SDH-deficient pheochromocytoma/paraganglioma. In addition, the study of immune landscape revealed the depletion of tumor microenvironment and inflammation gene signatures. Conclusions: This study provides an update of GEP in SDH-deficient GISTs, highlighting differences and similarities compared to KIT-mutant GISTs and to other neoplasm carrying the SDH loss of function. Our findings add a piece of knowledge in SDH-deficient GISTs, shedding light on their putative histology and on the dysregulated biological processes as targets of new therapeutic strategies

Cancer cells exploit an orphan RNA to drive metastatic progression.

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3' end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non-cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies

A novel approach to single-cell analysis reveals intrinsic differences in immune marker expression in unstimulated BALB/c and C57BL/6 macrophages

The origin of functional heterogeneity among macrophages, key innate immune system components, is still debated. While mouse strains differ in their immune responses, the range of gene expression variation among their pre-stimulation macrophages is unknown. With a novel approach to scRNA-seq analysis, we reveal the gene expression variation in unstimulated macrophage populations from BALB/c and C57BL/6 mice. We show that intrinsic strain-to-strain differences are detectable before stimulation and we place the unstimulated single cells within the gene expression landscape of stimulated macrophages. C57BL/6 mice show stronger evidence of macrophage polarization than BALB/c mice, which may contribute to their relative resistance to pathogens. Our computational methods can be generally adopted to uncover biological variation between cell populations

The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition

Introduction: Gene expression data derived from clinical cancer specimens provide an opportunity to characterize cancer-specific transcriptional programs. Here, we present an analysis delineating a correlation-based gene expression landscape of breast cancer that identifies modules with strong associations to breast cancer-specific and general tumor biology. Methods: Modules of highly connected genes were extracted from a gene co-expression network that was constructed based on Pearson correlation, and module activities were then calculated using a pathway activity score. Functional annotations of modules were experimentally validated with an siRNA cell spot microarray system using the KPL-4 breast cancer cell line, and by using gene expression data from functional studies. Modules were derived using gene expression data representing 1,608 breast cancer samples and validated in data sets representing 971 independent breast cancer samples as well as 1,231 samples from other cancer forms. Results: The initial co-expression network analysis resulted in the characterization of eight tightly regulated gene modules. Cell cycle genes were divided into two transcriptional programs, and experimental validation using an siRNA screen showed different functional roles for these programs during proliferation. The division of the two programs was found to act as a marker for tumor protein p53 (TP53) gene status in luminal breast cancer, with the two programs being separated only in luminal tumors with functional p53 (encoded by TP53). Moreover, a module containing fibroblast and stroma-related genes was highly expressed in fibroblasts, but was also up-regulated by overexpression of epithelial-mesenchymal transition factors such as transforming growth factor beta 1 (TGF-beta1) and Snail in immortalized human mammary epithelial cells. Strikingly, the stroma transcriptional program related to less malignant tumors for luminal disease and aggressive lymph node positive disease among basal-like tumors. Conclusions: We have derived a robust gene expression landscape of breast cancer that reflects known subtypes as well as heterogeneity within these subtypes. By applying the modules to TP53-mutated samples we shed light on the biological consequences of non-functional p53 in otherwise low-proliferating luminal breast cancer. Furthermore, as in the case of the stroma module, we show that the biological and clinical interpretation of a set of co-regulated genes is subtype-dependent

An Always Correlated gene expression landscape for ovine skeletal muscle, lessons learnt from comparison with an “equivalent” bovine landscape

BACKGROUND: We have recently described a method for the construction of an informative gene expression correlation landscape for a single tissue, longissimus muscle (LM) of cattle, using a small number (less than a hundred) of diverse samples. Does this approach facilitate interspecies comparison of networks? FINDINGS: Using gene expression datasets from LM samples from a single postnatal time point for high and low muscling sheep, and from a developmental time course (prenatal to postnatal) for normal sheep and sheep exhibiting the Callipyge muscling phenotype gene expression correlations were calculated across subsets of the data comparable to the bovine analysis. An “Always Correlated” gene expression landscape was constructed by integrating the correlations from the subsets of data and was compared to the equivalent landscape for bovine LM muscle. Whilst at the high level apparently equivalent modules were identified in the two species, at the detailed level overlap between genes in the equivalent modules was limited and generally not significant. Indeed, only 395 genes and 18 edges were in common between the two landscapes. CONCLUSIONS: Since it is unlikely that the equivalent muscles of two closely related species are as different as this analysis suggests, within tissue gene expression correlations appear to be very sensitive to the samples chosen for their construction, compounded by the different platforms used. Thus users need to be very cautious in interpretation of the differences. In future experiments, attention will be required to ensure equivalent experimental designs and use cross-species gene expression platform to enable the identification of true differences between different species

The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment.

Understanding how differentiation programs originate from the gene-expression 'landscape' of hematopoietic stem cells (HSCs) is crucial for the development of new clinical therapies. We mapped the transcriptional dynamics underlying the first steps of commitment by tracking transcriptome changes in human HSCs and eight early progenitor populations. We found that transcriptional programs were extensively shared, extended across lineage-potential boundaries and were not strictly lineage affiliated. Elements of stem, lymphoid and myeloid programs were retained in multilymphoid progenitors (MLPs), which reflected a hybrid transcriptional state. By functional single cell analysis, we found that the transcription factors Bcl-11A, Sox4 and TEAD1 (TEF1) governed transcriptional networks in MLPs, which led to B cell specification. Overall, we found that integrated transcriptome approaches can be used to identify previously unknown regulators of multipotency and show additional complexity in lymphoid commitment

ZNF521 Enhances MLL-AF9-Dependent Hematopoietic Stem Cell Transformation in Acute Myeloid Leukemias by Altering the Gene Expression Landscape

Leukemias derived from the MLL-AF9 rearrangement rely on dysfunctional transcriptional networks. ZNF521, a transcription co-factor implicated in the control of hematopoiesis, has been proposed to sustain leukemic transformation in collaboration with other oncogenes. Here, we demonstrate that ZNF521 mRNA levels correlate with specific genetic aberrations: in particular, the highest expression is observed in AMLs bearing MLL rearrangements, while the lowest is detected in AMLs with FLT3-ITD, NPM1, or CEBPα double mutations. In cord blood-derived CD34(+) cells, enforced expression of ZNF521 provides a significant proliferative advantage and enhances MLL-AF9 effects on the induction of proliferation and the expansion of leukemic progenitor cells. Transcriptome analysis of primary CD34(+) cultures displayed subsets of genes up-regulated by MLL-AF9 or ZNF521 single transgene overexpression as well as in MLL-AF9/ZNF521 combinations, at either the early or late time points of an in vitro leukemogenesis model. The silencing of ZNF521 in the MLL-AF9 + THP-1 cell line coherently results in an impairment of growth and clonogenicity, recapitulating the effects observed in primary cells. Taken together, these results underscore a role for ZNF521 in sustaining the self-renewal of the immature AML compartment, most likely through the perturbation of the gene expression landscape, which ultimately favors the expansion of MLL-AF9-transformed leukemic clones