The Heterotrimeric Laminin Coiled-Coil Domain Exerts Anti-Adhesive Effects and Induces a Pro-Invasive Phenotype

Laminins are large heterotrimeric cross-shaped extracellular matrix glycoproteins with terminal globular domains and a coiled-coil region through which the three chains are assembled and covalently linked. Laminins are key components of basement membranes, and they serve as attachment sites for cell adhesion, migration and proliferation. In this work, we produced a recombinant fragment comprising the entire laminin coiled-coil of the α1-, β1-, and γ1-chains that assemble into a stable heterotrimeric coiled-coil structure independently of the rest of the molecule. This domain was biologically active and not only failed to serve as a substrate for cell attachment, spreading and focal adhesion formation but also inhibited cell adhesion to laminin when added to cells in a soluble form at the time of seeding. Furthermore, gene array expression profiling in cells cultured in the presence of the laminin coiled-coil domain revealed up-regulation of genes involved in cell motility and invasion. These findings were confirmed by real-time quantitative PCR and zymography assays. In conclusion, this study shows for the first time that the laminin coiled-coil domain displays anti-adhesive functions and has potential implications for cell migration during matrix remodeling

Fat Oxidation, Fitness and Skeletal Muscle Expression of Oxidative/Lipid Metabolism Genes in South Asians: Implications for Insulin Resistance?

<p><b>Background:</b> South Asians are more insulin resistant than Europeans, which cannot be fully explained by differences in adiposity. We investigated whether differences in oxidative capacity and capacity for fatty acid utilisation in South Asians might contribute, using a range of whole-body and skeletal muscle measures.</p> <p><b>Methodology/Principal Findings:</b> Twenty men of South Asian ethnic origin and 20 age and BMI-matched men of white European descent underwent exercise and metabolic testing and provided a muscle biopsy to determine expression of oxidative and lipid metabolism genes and of insulin signalling proteins. In analyses adjusted for age, BMI, fat mass and physical activity, South Asians, compared to Europeans, exhibited; reduced insulin sensitivity by 26% (p = 0.010); lower VO2max (40.6±6.6 vs 52.4±5.7 ml.kg−1.min−1, p = 0.001); and reduced fat oxidation during submaximal exercise at the same relative (3.77±2.02 vs 6.55±2.60 mg.kg−1.min−1 at 55% VO2max, p = 0.013), and absolute (3.46±2.20 vs 6.00±1.93 mg.kg−1.min−1 at 25 ml O2.kg−1.min−1, p = 0.021), exercise intensities. South Asians exhibited significantly higher skeletal muscle gene expression of CPT1A and FASN and significantly lower skeletal muscle protein expression of PI3K and PKB Ser473 phosphorylation. Fat oxidation during submaximal exercise and VO2max both correlated significantly with insulin sensitivity index and PKB Ser473 phosphorylation, with VO2max or fat oxidation during exercise explaining 10–13% of the variance in insulin sensitivity index, independent of age, body composition and physical activity.</p> <p><b>Conclusions/Significance:</b> These data indicate that reduced oxidative capacity and capacity for fatty acid utilisation at the whole body level are key features of the insulin resistant phenotype observed in South Asians, but that this is not the consequence of reduced skeletal muscle expression of oxidative and lipid metabolism genes.</p&gt

3,4-Methylenedioxymethamphetamine (MDMA) neurotoxicity in rats: a reappraisal of past and present findings

RATIONALE: 3,4-Methylenedioxymethamphetamine (MDMA) is a widely abused illicit drug. In animals, high-dose administration of MDMA produces deficits in serotonin (5-HT) neurons (e.g., depletion of forebrain 5-HT) that have been interpreted as neurotoxicity. Whether such 5-HT deficits reflect neuronal damage is a matter of ongoing debate. OBJECTIVE: The present paper reviews four specific issues related to the hypothesis of MDMA neurotoxicity in rats: (1) the effects of MDMA on monoamine neurons, (2) the use of “interspecies scaling” to adjust MDMA doses across species, (3) the effects of MDMA on established markers of neuronal damage, and (4) functional impairments associated with MDMA-induced 5-HT depletions. RESULTS: MDMA is a substrate for monoamine transporters, and stimulated release of 5-HT, NE, and DA mediates effects of the drug. MDMA produces neurochemical, endocrine, and behavioral actions in rats and humans at equivalent doses (e.g., 1–2 mg/kg), suggesting that there is no reason to adjust doses between these species. Typical doses of MDMA causing long-term 5-HT depletions in rats (e.g., 10–20 mg/kg) do not reliably increase markers of neurotoxic damage such as cell death, silver staining, or reactive gliosis. MDMA-induced 5-HT depletions are accompanied by a number of functional consequences including reductions in evoked 5-HT release and changes in hormone secretion. Perhaps more importantly, administration of MDMA to rats induces persistent anxiety-like behaviors in the absence of measurable 5-HT deficits. CONCLUSIONS: MDMA-induced 5-HT depletions are not necessarily synonymous with neurotoxic damage. However, doses of MDMA which do not cause long-term 5-HT depletions can have protracted effects on behavior, suggesting even moderate doses of the drug may pose risks

Alzheimer disease models and human neuropathology: similarities and differences

Animal models aim to replicate the symptoms, the lesions or the cause(s) of Alzheimer disease. Numerous mouse transgenic lines have now succeeded in partially reproducing its lesions: the extracellular deposits of Aβ peptide and the intracellular accumulation of tau protein. Mutated human APP transgenes result in the deposition of Aβ peptide, similar but not identical to the Aβ peptide of human senile plaque. Amyloid angiopathy is common. Besides the deposition of Aβ, axon dystrophy and alteration of dendrites have been observed. All of the mutations cause an increase in Aβ 42 levels, except for the Arctic mutation, which alters the Aβ sequence itself. Overexpressing wild-type APP alone (as in the murine models of human trisomy 21) causes no Aβ deposition in most mouse lines. Doubly (APP × mutated PS1) transgenic mice develop the lesions earlier. Transgenic mice in which BACE1 has been knocked out or overexpressed have been produced, as well as lines with altered expression of neprilysin, the main degrading enzyme of Aβ. The APP transgenic mice have raised new questions concerning the mechanisms of neuronal loss, the accumulation of Aβ in the cell body of the neurons, inflammation and gliosis, and the dendritic alterations. They have allowed some insight to be gained into the kinetics of the changes. The connection between the symptoms, the lesions and the increase in Aβ oligomers has been found to be difficult to unravel. Neurofibrillary tangles are only found in mouse lines that overexpress mutated tau or human tau on a murine tau −/− background. A triply transgenic model (mutated APP, PS1 and tau) recapitulates the alterations seen in AD but its physiological relevance may be discussed. A number of modulators of Aβ or of tau accumulation have been tested. A transgenic model may be analyzed at three levels at least (symptoms, lesions, cause of the disease), and a reading key is proposed to summarize this analysis

Purinergic signalling and immune cells

This review article provides a historical perspective on the role of purinergic signalling in the regulation of various subsets of immune cells from early discoveries to current understanding. It is now recognised that adenosine 5'-triphosphate (ATP) and other nucleotides are released from cells following stress or injury. They can act on virtually all subsets of immune cells through a spectrum of P2X ligand-gated ion channels and G protein-coupled P2Y receptors. Furthermore, ATP is rapidly degraded into adenosine by ectonucleotidases such as CD39 and CD73, and adenosine exerts additional regulatory effects through its own receptors. The resulting effect ranges from stimulation to tolerance depending on the amount and time courses of nucleotides released, and the balance between ATP and adenosine. This review identifies the various receptors involved in the different subsets of immune cells and their effects on the function of these cells

Recommendations of the Global Multiple System Atrophy Research Roadmap Meeting

Multiple system atrophy (MSA) is a rare neurodegenerative disorder with substantial knowledge gaps despite recent gains in basic and clinical research. In order to make further advances, concerted international collaboration is vital. In 2014, an international meeting involving leaders in the field and MSA advocacy groups was convened in Las Vegas, Nevada, to identify critical research areas where consensus and progress was needed to improve understanding, diagnosis, and treatment of the disease. Eight topic areas were defined: pathogenesis, preclinical modeling, target identification, endophenotyping, clinical measures, imaging biomarkers, nonimaging biomarkers, treatments/trial designs, and patient advocacy. For each topic area, an expert served as a working group chair and each working group developed priority-ranked research recommendations with associated timelines and pathways to reach the intended goals. In this report, each groups' recommendations are provided

Circulating free testosterone and risk of aggressive prostate cancer: Prospective and Mendelian randomisation analyses in international consortia

Previous studies had limited power to assess the associations of testosterone with aggressive disease as a primary endpoint. Further, the association of genetically predicted testosterone with aggressive disease is not known. We investigated the associations of calculated free and measured total testosterone and sex hormone-binding globulin (SHBG) with aggressive, overall and early-onset prostate cancer. In blood-based analyses, odds ratios (OR) and 95% confidence intervals (CI) for prostate cancer were estimated using conditional logistic regression from prospective analysis of biomarker concentrations in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group (up to 25 studies, 14 944 cases and 36 752 controls, including 1870 aggressive prostate cancers). In Mendelian randomisation (MR) analyses, using instruments identified using UK Biobank (up to 194 453 men) and outcome data from PRACTICAL (up to 79 148 cases and 61 106 controls, including 15 167 aggressive cancers), ORs were estimated using the inverse-variance weighted method. Free testosterone was associated with aggressive disease in MR analyses (OR per 1 SD = 1.23, 95% CI = 1.08-1.40). In blood-based analyses there was no association with aggressive disease overall, but there was heterogeneity by age at blood collection (OR for men aged <60 years 1.14, CI = 1.02-1.28; Phet = .0003: inverse association for older ages). Associations for free testosterone were positive for overall prostate cancer (MR: 1.20, 1.08-1.34; blood-based: 1.03, 1.01-1.05) and early-onset prostate cancer (MR: 1.37, 1.09-1.73; blood-based: 1.08, 0.98-1.19). SHBG and total testosterone were inversely associated with overall prostate cancer in blood-based analyses, with null associations in MR analysis. Our results support free testosterone, rather than total testosterone, in the development of prostate cancer, including aggressive subgroups

The transcriptomics of an experimentally evolved plant-virus interaction

[EN] Models of plant-virus interaction assume that the ability of a virus to infect a host genotype depends on the matching between virulence and resistance genes. Recently, we evolved tobacco etch potyvirus (TEV) lineages on different ecotypes of Arabidopsis thaliana, and found that some ecotypes selected for specialist viruses whereas others selected for generalists. Here we sought to evaluate the transcriptomic basis of such relationships. We have characterized the transcriptomic responses of five ecotypes infected with the ancestral and evolved viruses. Genes and functional categories differentially expressed by plants infected with local TEV isolates were identified, showing heterogeneous responses among ecotypes, although significant parallelism existed among lineages evolved in the same ecotype. Although genes involved in immune responses were altered upon infection, other functional groups were also pervasively over-represented, suggesting that plant resistance genes were not the only drivers of viral adaptation. Finally, the transcriptomic consequences of infection with the generalist and specialist lineages were compared. Whilst the generalist induced very similar perturbations in the transcriptomes of the different ecotypes, the perturbations induced by the specialist were divergent. Plant defense mechanisms were activated when the infecting virus was specialist but they were down-regulated when infecting with generalist.We thank Francisca de la Iglesia and Paula Agudo for excellent technical assistance and our labmates for useful discussions and suggestions. This work was supported by grants BFU2012-30805 from the Spanish Ministry of Economy and Competitiveness (MINECO), PROMETEOII/2014/021 from Generalitat Valenciana and EvoEvo (ICT610427) from the European Commission 7th Framework Program to SFE, and grant PROMETEOII/2014/025 to JD. JMC was supported by a JAE-doc postdoctoral contract from CSIC. JH was recipient of a predoctoral contract from MINECO.Hillung, J.; García-García, F.; Dopazo, J.; Cuevas Torrijos, JM.; Elena Fito, SF. (2016). The transcriptomics of an experimentally evolved plant-virus interaction. Scientific Reports. 6:1-19. https://doi.org/10.1038/srep24901S1196Duffy, S., Shackelton, L. A. & Holmes, E. C. Rates of evolutionary change in viruses: patterns and determinants. Nat. Rev. Genet. 9, 267–276 (2008).Parrish, C. R. et al. Cross-species virus transmission and the emergence of new epidemic diseases. Microbiol. Mol. Biol. Rev. 72, 457–470 (2008).Holmes, E. C. The comparative genomics of viral emergence. Proc. Natl. Acad. Sci. USA 107, 1742–1746 (2010).Sanjuán, R., Nebot, M. R., Chirico, N., Mansky, L. M. & Belshaw, R. Viral mutation rates. J. Virol. 84, 9733–9748 (2010).Elena, S. F. et al. The evolutionary genetics of emerging plant RNA viruses. Mol. Plant-Microbe Interact. 24, 287–293 (2011).Holmes, E. C. The evolutionary genetics of emerging viruses. Annu. Rev. Ecol. Evol. Syst. 40, 353–372 (2009).Domingo, E. Mechanisms of viral emergence. Vet. Res. 41, 38 (2010).King, K. C. & Lively, C. M. Does genetic diversity limit disease spread in natural host populations? Heredity 109, 199–203 (2012).Kearney, C. M., Thomson, M. J. & Roland, K. E. Genome evolution of Tobacco mosaic virus populations during long-term passaging in a diverse range of hosts. Arch. Virol. 144, 1513–1526 (1999).Tan, Z. et al. Mutations in Turnip mosaic virus genomes that have adapted to Raphanus sativus . J. Gen. Virol. 88, 501–510 (2005).Rico, P., Ivars, P., Elena, S. F. & Hernández, C. Insights into the selective pressures restricting Pelargonium flower break virus genome variability: evidence for host adaptation. J. Virol. 80, 8124–8132 (2006).Wallis, C. M. et al. Adaptation of Plum pox virus to a herbaceous host (Pisum sativum) following serial passages. J. Gen. Virol. 88, 2839–2845 (2007).Agudelo-Romero, P., de la Iglesia, F. & Elena, S. F. The pleiotropic cost of host-specialization in tobacco etch potyvirus. Infect. Genet. Evol. 8, 806–814 (2008).Bedhomme, S., Lafforgue, G. & Elena, S. F. Multihost experimental evolution of a plant RNA virus reveals local adaptation and host-specific mutations. Mol. Biol. Evol. 29, 1481–1492 (2012).García-Arenal, F. & Fraile A. Trade-offs in host range evolution of plant viruses. Plant Pathol. 62, S2–S9. (2013).Calvo, M., Malinowski, T. & García, J. A. Single amino acid changes in the 6K1-CI region can promote the alternative adaptation of Prunus- and Nicotiana- propagated Plum pox virus C isolates to either host. Mol. Plant-Microbe Interact. 27, 136–149 (2014).Cuevas, J. M., Willemsen, A., Hillung, J., Zwart, M. P. & Elena, S. F. Temporal dynamics of intra-host molecular evolution for a plant RNA virus. Mol. Biol. Evol. 32, 1132–1147 (2015).Minicka, J., Rymelska, N., Elena, S. F., Czerwoniec, A. & Hasiów-Jaroszewska, B. Molecular evolution of Pepino mosaic virus during long-term passaging in different hosts and its impact on virus virulence. Ann. Appl. Biol. 166, 389–401 (2015).Agudelo-Romero, P., Carbonell, P., Pérez-Amador, M. A. & Elena, S. F. Virus adaptation by manipulation of host's gene expression. PLos ONE 3, e2397 (2008).Weigel, D. Natural variation in arabidopsis: from molecular genetics to ecological genomics. Plant Physiol. 158, 2–22 (2012).Mahajan, S. K., Chisholm, S. T., Whitham, S. A. & Carrington, J. C. Identification and characterization of a locus (RTM1) that restricts long-distance movement of Tobacco etch virus in Arabidopsis thaliana . Plant J. 14, 177–186 (1998).Whitham, S. A., Yamamoto, M. L. & Carrington, J. C. Selectable viruses and altered susceptibility mutants in Arabidopsis thaliana . Proc. Natl. Acad. Sci. USA 96, 772–777 (1999).Whitham, S. A., Anderberg, R. J., Chisholm, S. T. & Carrington, J. C. Arabidopsis RTM2 gene is necessary for specific restriction of Tobacco etch virus and encodes an unusual small heat shock-like protein. Plant Cell 12, 569–582 (2000).Chisholm, S. T., Mahajan, S. K., Whitham, S. A., Yamamoto, M. L. & Carrington, J. C. Cloning of the Arabidopsis RTM1 gene, which controls restriction of long-distance movement of Tobacco etch virus . Proc. Natl. Acad. Sci. USA 97, 489–494 (2000).Chisholm, S. T., Parra, M. A., Anderberg, R. J. & Carrington, J. C. Arabidopsis RTM1 and RTM2 genes function in phloem to restrict long-distance movement of Tobacco etch virus . Plant Physiol. 127, 1667–1675 (2001).Cosson, P. et al. RTM3, which controls long-distance movement of potyviruses, is a member of a new plant gene family encoding a MEPRIN and TRAF homology domain-containing protein. Plant Physiol. 154, 222–232 (2010).Cosson, P., Sofer, L., Schurdi-Levraud, V. & Revers, F. A member of a new plant gene family encoding a MEPRIN and TRAF homology (MATH) domain-containing protein is involved in restriction of long distance movement of plant viruses. Plant Signal. Behav. 5, 1321–1323 (2010).Agudelo-Romero P. et al. Changes in gene expression profile of Arabidopsis thaliana after infection with Tobacco etch virus . Virol. J. 5, 92 (2008).Lalić, J., Agudelo-Romero, P., Carrasco, P. & Elena, S. F. Adaptation of tobacco etch potyvirus to a susceptible ecotype of Arabidopsis thaliana capacitates it for systemic infection of resistant ecotypes. Phil. Trans. R. Soc. B 65, 1997–2008 (2010).Hillung, J., Cuevas, J. M. & Elena, S. F. Transcript profiling of different Arabidopsis thaliana ecotypes in response to tobacco etch potyvirus infection. Front. Microbiol. 3, 229 (2012).Hillung, J., Cuevas, J. M. & Elena, S. F. Evaluating the within-host fitness effects of mutations fixed during virus adaptation to different ecotypes of a new host. Phil. Trans. R. Soc. B 370, 20140292 (2015).Hillung, J., Cuevas, J. M., Valverde, S. & Elena, S. F. Experimental evolution of an emerging plant virus in host genotypes that differ in their susceptibility to infection. Evolution 68, 2467–2480 (2014).Sartor, M. A., Leikauf, G. D. & Medvedovic, M. LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data. Bioinformatics 25, 211–217 (2009).Montaner, D. & Dopazo, J. Multidimensional gene set analysis of genomic data. PLos ONE 5, e10348 (2010).Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLos ONE 6, e21800 (2011).Grennan, A. K. Regulation of starch metabolism in Arabidopsis leaves. Plant Physiol. 142, 1343–1345 (2006).Johnson, P. R. & Ecker, J. R. The ethylene gas signal transduction pathway: a molecular perspective. Annu. Rev. Genet. 32, 227–254 (1998).Wang, K. L., Li, H. & Ecker, J. R. Ethylene biosynthesis and signaling networks. Plant Cell 14, S131–S151 (2002).Binns, D. et al. QuickGO: a web-based tool for gene ontology searching. Bioinformatics 25, 3045–3046 (2009).Stintzi, A., Weber, H., Reymond, P., Browse, J. & Farmer, E. E. Plant defense in the absence of jasmonic acid: the role of cyclopentenones. Proc. Natl. Acad. Sci. USA 98, 12837–12842 (2001).Luna, E. et al. Callose deposition: a multifaceted plant defense response. Mol. Plant-Microbe Interact. 24, 183–193 (2011).Ghoshroy, S., Freedman, K., Lartey, R. & Citovsky, V. Inhibition of plant viral systemic infection by non-toxic concentrations of cadmium. Plant J. 13, 591–602 (1998).Hayashi, N. et al. Nef of HIV-1 interacts directly with calcium-bound calmodulin. Protein Sci. 11, 529–537 (2002).Zacharias, D. A., Violin, J. D., Newton, A. C. & Tsien, R. Y. Partitioning of lipic-modified monomeric GFPs into membrane microdomains of live cells. Science 296, 913–916 (2002).Rojas, M. R. et al. Functional analysis of proteins involved in movement of the monopartite begomovirus, Tomato yellow leaf curl virus. Virology 291, 110–125 (2001).Padmanabhan, M. S., Goregaoker, S. P., Golem, S., Shiferaw, H. & Culver, J. N. Interaction of the Tobacco mosaic virus replicase protein with the Aux/IAA protein PAP1/IAA26 is associated with disease development. J. Virol. 79, 2549–2558 (2005).Lurin, C. et al. Genome-wide analysis of Arabidopsis pentatricopeptide repeat proteins reveals their essential role in organelle biogenesis. Plant Cell 16, 2089–2103 (2004).Takenaka, M., Verbitskiy, D., Zehrmann, A. & Brennicke, A. Reverse genetic screening identifies five E-class PPR proteins involved in RNA editing in mitochondria of Arabidopsis thaliana . J. Biol. Chem. 285, 27122–27129 (2010).Gillissen, B. et al. A new family of high-affinity transporters for adenine, cytosine, and purine derivatives in Arabidopsis . Plant Cell 12, 291–300 (2000).Li, S., Fu, Q., Chen, L., Huang, W. & Yu, D. Arabidopsis thaliana WRKY25, WRKY26, and WRKY33 coordinate induction of plant thermotolerance. Planta 233, 1237–1252 (2011).Divol, F. et al. Involvement of the xyloglucan endotransglycosylase/hydrolases encoded by celery XTH1 and Arabidopsis XTH33 in the phloem response to aphids. Plant Cell. Environ. 30, 187–201 (2007).Vissenberg, K., Fry, S. C., Pauly, M., Höfte, H. & Verbelen, J. P. XTH acts at the microfibril-matrix interface during cell elongation. J. Exp. Bot. 56, 673–683 (2005).Ham, B. K., Li, G., Kang, B. H., Zeng, F. & Lucas, W. J. Overexpression of Arabidopsis plasmodesmata germin-like proteins disrupts root growth and development. Plant Cell 24, 3630–3648 (2012).Bae, M. S., Cho, E. J., Choi, E. Y. & Park, O. K. Analysis of the Arabidopsis nuclear proteome and its response to cold stress. Plant J. 36, 652–663 (2003).Zargar, S. M. et al. Correlation analysis of proteins responsive to Zn, Mn, or Fe deficiency in Arabidopsis roots based on iTRAQ analysis. Plant Cell Rep. 34, 157–166 (2015).Kleffmann, T. et al. The Arabidopsis thaliana chloroplast proteome reveals pathway abundance and novel protein functions. Curr. Biol. 14, 354–362 (2004).Zybailov, B. et al. Sorting signals, N-terminal modifications and abundance of the chloroplast proteome. PLos ONE 3, e1994 (2008).Wu, P. et al. Phosphate starvation triggers distinct alterations of gene expression in Arabidopsis roots and leaves. Plant Physiol. 132, 1260–1271 (2003).Oh, S. A., Lee, S. Y., Chung, I. K., Lee, C. H. & Nam H. G. A senescence-associated gene of Arabidopsis thaliana is distinctively regulated during natural and artificially induced leaf senescence. Plant Mol. Biol. 30, 739–754 (1996).Schenk, P. M., Kazan, K., Rusu, A. G., Manners, J. M. & Maclean, D. J. The SEN1 gene of Arabidopsis is regulated by signals that link plant defence responses and senescence. Plant Physiol. Biochem. 43, 997–1005 (2005).Fernández-Calvino, L. et al. Activation of senescence-associated dark-inducible (DIN) genes during infection contributes to enhanced susceptibility to plant viruses. Mol. Plant Pathol. 17, 3–15 (2016).Vierstra, R. D. Proteolysis in plants: mechanisms and functions. Plant Mol. Biol. 32, 275–302 (1996).Bögre, L., Okrész, L., Henriques, R. & Anthony, R. G. Growth signalling pathways in Arabidopsis and the AGC protein kinases. Trends Plant Sci. 8, 424–431 (2003).An, L. et al. A zinc finger protein gene ZFP5 integrates phytohormone signalling to control root hair development in Arabidopsis . Plant J. 72, 474–490 (2012).Zhou, Z., An, L., Sun, L. & Gan, Y. ZFP5 encodes a functionally equivalent GIS protein to control trichome initiation. Plant Signal. Behav. 7, 28–30 (2012).Zhou, Z. et al. Zinc finger protein 5 is required for the control of trichome initiation by acting upstream of zinc finger protein 8 in Arabidopsis . Plant Physiol. 157, 673–682 (2011).Lee, D. J. et al. Genome-wide expression profiling of ARABIDOPSIS RESPONSE REGULATOR 7 (ARR7) overexpression in cytokinin response. Mol. Genet. Genomics 277, 115–137 (2007).Theologis, A. et al. Sequence and analysis of chromosome 1 of the plant Arabidopsis thaliana . Nature 408, 816–820 (2000).Heyndrickx, K. S. & Vandepoele, K. Systematic identification of functional plant modules through the integration of complementary data sources. Plant Physiol. 159, 884–901 (2012).Martinoia, E. et al. Multifunctionality of plant ABC transporter - more than just detoxifiers. Planta 214, 345–355 (2002).Kaneda, M. et al. ABC transporters coordinately expressed during lignification of Arabidopsis stems include a set of ABCBs associated with auxin transport. J. Exp. Bot. 62, 2063–2077 (2011).Alejandro, S. et al. AtABCG29 is a monolignol transporter involved in lignin biosynthesis. Curr. Biol. 22, 1207–1212 (2012).Riechmann, J. L. et al. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes. Science 290, 2105–2110 (2000).Ohashi-Ito, K. & Bergmann, D. C. Regulation of the Arabidopsis root vascular initial population by LONESOME HIGHWAY . Development 134, 2959–2968 (2007).Averyanov, A. Oxidative burst and plant disease resistance. Front. Biosci. 1, 142–152 (2009).Flury, P., Klauser, D., Schulze, B., Boller, T. & Bartels, S. The anticipation of danger: microbe-associated molecular pattern perception enhances AtPep-triggered oxidative burst. Plant Physiol. 161, 2023–2035 (2013).Tanaka, K., Nguyen, C. T., Liang, Y., Cao, Y. & Stacey, G. Role of LysM receptors in chitin-triggered plant innate immunity. Plant Signal. Behav. 8, e22598 (2013).Nakamura, K. & Matsuoka, K. Protein targeting to the vacuole in plant cells. Plant Physiol. 101, 1–5 (1993).Elena, S. F., Agudelo-Romero, P. & Lalić, J. The evolution of viruses in multi-host fitness landscapes. Open Virol. J. 3, 1–6 (2009).Bolstad, B. M., Irizarry, R. A., Astrand, M. & Speed, T. P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–193 (2003).Smyth, G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, 3 (2004).Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).Benjamini,Y. & Yekutieli, D. The control of the false discovery rate in multiple testing under dependency. Ann. Statist. 29, 1165–1188 (2001).Sneath, P. & Sokal, R. Numerical Taxonomy. ( W.H. Freeman, 1973).D'Haeseler, P. How does gene expression clustering work? Nat. Biotech. 23, 1499–1501 (2005).Suzuki, R. & Shimodaira, H. Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22, 1540–1542 (2006)