76 research outputs found
Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension
This article introduces Q methodology, an idea-sorting activity that can help Extension improve outreach and education on new and contentious issues. Q methodology is a helpful tool when Extension professionals are confronted with controversial or complex resource management challenges. Through the analysis of a simple card-sorting exercise, researchers can determine quantitatively and qualitatively how different issues combine to result in (a) an individual\u27s viewpoint on an issue and (b) groupings of different viewpoints within a community. We describe the basic approach to implementing Q methodology and suggest circumstances in which it can help facilitate Extension outreach and education
Density estimates of monarch butterflies overwintering in central Mexico
Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha−1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha−1 (95% CI [2.4–80.7] million ha−1); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha−1). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations
A functional definition to distinguish ponds from lakes and wetlands
Ponds are often identified by their small size and shallow depths, but the lack of a universal evidence-based definition hampers science and weakens legal protection. Here, we compile existing pond definitions, compare ecosystem metrics (e.g., metabolism, nutrient concentrations, and gas fluxes) among ponds, wetlands, and lakes, and propose an evidence-based pond definition. Compiled definitions often mentioned surface area and depth, but were largely qualitative and variable. Government legislation rarely defined ponds, despite commonly using the term. Ponds, as defined in published studies, varied in origin and hydroperiod and were often distinct from lakes and wetlands in water chemistry. We also compared how ecosystem metrics related to three variables often seen in waterbody definitions: waterbody size, maximum depth, and emergent vegetation cover. Most ecosystem metrics (e.g., water chemistry, gas fluxes, and metabolism) exhibited nonlinear relationships with these variables, with average threshold changes at 3.7 ± 1.8 ha (median: 1.5 ha) in surface area, 5.8 ± 2.5 m (median: 5.2 m) in depth, and 13.4 ± 6.3% (median: 8.2%) emergent vegetation cover. We use this evidence and prior definitions to define ponds as waterbodies that are small (< 5 ha), shallow (< 5 m), with < 30% emergent vegetation and we highlight areas for further study near these boundaries. This definition will inform the science, policy, and management of globally abundant and ecologically significant pond ecosystems.Fil: Richardson, David C.. State University of New York at New Paltz; Estados UnidosFil: Holgerson, Meredith A.. Cornell University; Estados UnidosFil: Farragher, Matthew J.. University of Maine; Estados UnidosFil: Hoffman, Kathryn K.. No especifíca;Fil: King, Katelyn B. S.. Michigan State University; Estados UnidosFil: Alfonso, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; ArgentinaFil: Andersen, Mikkel R.. No especifíca;Fil: Cheruveil, Kendra Spence. Michigan State University; Estados UnidosFil: Coleman, Kristen A.. University of York; Reino UnidoFil: Farruggia, Mary Jade. University of California at Davis; Estados UnidosFil: Fernandez, Rocio Luz. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hondula, Kelly L.. No especifíca;Fil: López Moreira Mazacotte, Gregorio A.. Leibniz - Institute of Freshwater Ecology and Inland Fisheries; AlemaniaFil: Paul, Katherine. No especifíca;Fil: Peierls, Benjamin L.. No especifíca;Fil: Rabaey, Joseph S.. University of Minnesota; Estados UnidosFil: Sadro, Steven. University of California at Davis; Estados UnidosFil: Sánchez, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Smyth, Robyn L.. No especifíca;Fil: Sweetman, Jon N.. State University of Pennsylvania; Estados Unido
Characterization of tomato Cycling Dof Factors reveals conserved and new functions in the control of flowering time and abiotic stress responses
[EN] DNA binding with One Finger (DOF) transcription factors are involved in multiple aspects of plant growth and development but their precise roles in abiotic stress tolerance are largely unknown. Here we report a group of five tomato DOF genes, homologous to Arabidopsis Cycling DOF Factors (CDFs), that function as transcriptional regulators involved in responses to drought and salt stress and flowering-time control in a gene-specific manner. SlCDF15 are nuclear proteins that display specific binding with different affinities to canonical DNA target sequences and present diverse transcriptional activation capacities in vivo. SlCDF15 genes exhibited distinct diurnal expression patterns and were differentially induced in response to osmotic, salt, heat, and low-temperature stresses. Arabidopsis plants overexpressing SlCDF1 or SlCDF3 showed increased drought and salt tolerance. In addition, the expression of various stress-responsive genes, such as COR15, RD29A, and RD10, were differentially activated in the overexpressing lines. Interestingly, overexpression in Arabidopsis of SlCDF3 but not SlCDF1 promotes late flowering through modulation of the expression of flowering control genes such as CO and FT. Overall, our data connect SlCDFs to undescribed functions related to abiotic stress tolerance and flowering time through the regulation of specific target genes and an increase in particular metabolites.This work was supported by grants from Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA; project numbers: 2009-0004-C01, 2012-0008-C01), the Spanish Ministry of Science and Innovation (project number: BIO2010-14871), and the MERIT Project (FP7 ITN2010-264474). ARC was supported by a pre-doctoral fellowship from the INIA. The authors would like to thank Mar Gonzalez and Victor Carrasco for technical assistance and Dr Pablo Gonzalez-Melendi for technical handling of the confocal microscope. We also thank Eugenio Grau for technical assistance with RT-PCR analyses.Corrales, A.; González Nebauer, S.; Carrillo, L.; Fernández Nohales, P.; Marques Signes, J.; Renau Morata, B.; Granell, A.... (2014). Characterization of tomato Cycling Dof Factors reveals conserved and new functions in the control of flowering time and abiotic stress responses. Journal of Experimental Botany. 65(4):995-1012. https://doi.org/10.1093/jxb/ert451S9951012654AbuQamar, S., Luo, H., Laluk, K., Mickelbart, M. V., & Mengiste, T. (2009). Crosstalk between biotic and abiotic stress responses in tomato is mediated by theAIM1transcription factor. The Plant Journal, 58(2), 347-360. doi:10.1111/j.1365-313x.2008.03783.xAlonso, R., Oñate-Sánchez, L., Weltmeier, F., Ehlert, A., Diaz, I., Dietrich, K., … Dröge-Laser, W. (2009). A Pivotal Role of the Basic Leucine Zipper Transcription Factor bZIP53 in the Regulation of Arabidopsis Seed Maturation Gene Expression Based on Heterodimerization and Protein Complex Formation. The Plant Cell, 21(6), 1747-1761. doi:10.1105/tpc.108.062968Altschul, S. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. doi:10.1093/nar/25.17.3389An, H. (2004). CONSTANS acts in the phloem to regulate a systemic signal that induces photoperiodic flowering of Arabidopsis. Development, 131(15), 3615-3626. doi:10.1242/dev.01231Artimo, P., Jonnalagedda, M., Arnold, K., Baratin, D., Csardi, G., de Castro, E., … Stockinger, H. (2012). ExPASy: SIB bioinformatics resource portal. Nucleic Acids Research, 40(W1), W597-W603. doi:10.1093/nar/gks400Atherton, J. G., & Harris, G. P. (1986). Flowering. The Tomato Crop, 167-200. doi:10.1007/978-94-009-3137-4_4Bailey, T. L., Boden, M., Buske, F. A., Frith, M., Grant, C. E., Clementi, L., … Noble, W. S. (2009). MEME SUITE: tools for motif discovery and searching. Nucleic Acids Research, 37(Web Server), W202-W208. doi:10.1093/nar/gkp335Ben-Naim, O., Eshed, R., Parnis, A., Teper-Bamnolker, P., Shalit, A., Coupland, G., … Lifschitz, E. (2006). The CCAAT binding factor can mediate interactions between CONSTANS-like proteins and DNA. The Plant Journal, 46(3), 462-476. doi:10.1111/j.1365-313x.2006.02706.xBEUVE, N., RISPAIL, N., LAINE, P., CLIQUET, J.-B., OURRY, A., & LE DEUNFF, E. (2004). Putative role of gamma -aminobutyric acid (GABA) as a long-distance signal in up-regulation of nitrate uptake in Brassica napus L. Plant, Cell and Environment, 27(8), 1035-1046. doi:10.1111/j.1365-3040.2004.01208.xBlumwald, E. (2000). Sodium transport and salt tolerance in plants. Current Opinion in Cell Biology, 12(4), 431-434. doi:10.1016/s0955-0674(00)00112-5Bombarely, A., Menda, N., Tecle, I. Y., Buels, R. M., Strickler, S., Fischer-York, T., … Mueller, L. A. (2010). The Sol Genomics Network (solgenomics.net): growing tomatoes using Perl. Nucleic Acids Research, 39(Database), D1149-D1155. doi:10.1093/nar/gkq866Bressan, R., Bohnert, H., & Zhu, J.-K. (2009). Abiotic Stress Tolerance: From Gene Discovery in Model Organisms to Crop Improvement. Molecular Plant, 2(1), 1-2. doi:10.1093/mp/ssn097Calvert, A. (1959). Effect of the Early Environment on the Development of Flowering in Tomato II. Light and Temperature Interactions. Journal of Horticultural Science, 34(3), 154-162. doi:10.1080/00221589.1959.11513954Carmel-Goren, L., Liu, Y. S., Lifschitz, E., & Zamir, D. (2003). TheSELF-PRUNINGgene family in tomato. Plant Molecular Biology, 52(6), 1215-1222. doi:10.1023/b:plan.0000004333.96451.11Chaves, M. M., Flexas, J., & Pinheiro, C. (2008). Photosynthesis under drought and salt stress: regulation mechanisms from whole plant to cell. Annals of Botany, 103(4), 551-560. doi:10.1093/aob/mcn125Claussen, W. (2005). Proline as a measure of stress in tomato plants. Plant Science, 168(1), 241-248. doi:10.1016/j.plantsci.2004.07.039Clough, S. J., & Bent, A. F. (1998). Floral dip: a simplified method forAgrobacterium-mediated transformation ofArabidopsis thaliana. The Plant Journal, 16(6), 735-743. doi:10.1046/j.1365-313x.1998.00343.xCuartero, J., & Fernández-Muñoz, R. (1998). Tomato and salinity. Scientia Horticulturae, 78(1-4), 83-125. doi:10.1016/s0304-4238(98)00191-5Czechowski, T., Stitt, M., Altmann, T., Udvardi, M. K., & Scheible, W.-R. (2005). Genome-Wide Identification and Testing of Superior Reference Genes for Transcript Normalization in Arabidopsis. Plant Physiology, 139(1), 5-17. doi:10.1104/pp.105.063743Diaz, I., Vicente-Carbajosa, J., Abraham, Z., Martinez, M., Isabel-La Moneda, I., & Carbonero, P. (2002). The GAMYB protein from barley interacts with the DOF transcription factor BPBF and activates endosperm-specific genes during seed development. The Plant Journal, 29(4), 453-464. doi:10.1046/j.0960-7412.2001.01230.xDieleman, J. A., & Heuvelink, E. (1992). Factors affecting the number of leaves preceding the first inflorescence in the tomato. Journal of Horticultural Science, 67(1), 1-10. doi:10.1080/00221589.1992.11516214Farrant, J. M., & Moore, J. P. (2011). Programming desiccation-tolerance: from plants to seeds to resurrection plants. Current Opinion in Plant Biology, 14(3), 340-345. doi:10.1016/j.pbi.2011.03.018Fiehn, O., Kopka, J., Trethewey, R. N., & Willmitzer, L. (2000). Identification of Uncommon Plant Metabolites Based on Calculation of Elemental Compositions Using Gas Chromatography and Quadrupole Mass Spectrometry. Analytical Chemistry, 72(15), 3573-3580. doi:10.1021/ac991142iFornara, F., Panigrahi, K. C. S., Gissot, L., Sauerbrunn, N., Rühl, M., Jarillo, J. A., & Coupland, G. (2009). Arabidopsis DOF Transcription Factors Act Redundantly to Reduce CONSTANS Expression and Are Essential for a Photoperiodic Flowering Response. Developmental Cell, 17(1), 75-86. doi:10.1016/j.devcel.2009.06.015Gaquerel, E., Heiling, S., Schoettner, M., Zurek, G., & Baldwin, I. T. (2010). Development and Validation of a Liquid Chromatography−Electrospray Ionization−Time-of-Flight Mass Spectrometry Method for Induced Changes inNicotiana attenuataLeaves during Simulated Herbivory. Journal of Agricultural and Food Chemistry, 58(17), 9418-9427. doi:10.1021/jf1017737Gardiner, J., Sherr, I., & Scarpella, E. (2010). Expression of DOF genes identifies early stages of vascular development in Arabidopsis leaves. The International Journal of Developmental Biology, 54(8-9), 1389-1396. doi:10.1387/ijdb.093006jgGong, P., Zhang, J., Li, H., Yang, C., Zhang, C., Zhang, X., … Ye, Z. (2010). Transcriptional profiles of drought-responsive genes in modulating transcription signal transduction, and biochemical pathways in tomato. Journal of Experimental Botany, 61(13), 3563-3575. doi:10.1093/jxb/erq167Goodstein, D. M., Shu, S., Howson, R., Neupane, R., Hayes, R. D., Fazo, J., … Rokhsar, D. S. (2011). Phytozome: a comparative platform for green plant genomics. Nucleic Acids Research, 40(D1), D1178-D1186. doi:10.1093/nar/gkr944Gualberti, G., Papi, M., Bellucci, L., Ricci, I., Bouchez, D., Camilleri, C., … Vittorioso, P. (2002). Mutations in the Dof Zinc Finger Genes DAG2 and DAG1 Influence with Opposite Effects the Germination of Arabidopsis Seeds. The Plant Cell, 14(6), 1253-1263. doi:10.1105/tpc.010491Guindon, S., & Gascuel, O. (2003). A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood. Systematic Biology, 52(5), 696-704. doi:10.1080/10635150390235520Gullberg, J., Jonsson, P., Nordström, A., Sjöström, M., & Moritz, T. (2004). Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry. Analytical Biochemistry, 331(2), 283-295. doi:10.1016/j.ab.2004.04.037Guo, Y., Qin, G., Gu, H., & Qu, L.-J. (2009). Dof5.6/HCA2, a Dof Transcription Factor Gene, Regulates Interfascicular Cambium Formation and Vascular Tissue Development in Arabidopsis. The Plant Cell, 21(11), 3518-3534. doi:10.1105/tpc.108.064139Haupt-Herting, S., Klug, K., & Fock, H. P. (2001). A New Approach to Measure Gross CO2 Fluxes in Leaves. Gross CO2 Assimilation, Photorespiration, and Mitochondrial Respiration in the Light in Tomato under Drought Stress. Plant Physiology, 126(1), 388-396. doi:10.1104/pp.126.1.388Hernando-Amado, S., González-Calle, V., Carbonero, P., & Barrero-Sicilia, C. (2012). The family of DOF transcription factors in Brachypodium distachyon: phylogenetic comparison with rice and barley DOFs and expression profiling. BMC Plant Biology, 12(1), 202. doi:10.1186/1471-2229-12-202Hoekstra, F. A., Golovina, E. A., & Buitink, J. (2001). Mechanisms of plant desiccation tolerance. Trends in Plant Science, 6(9), 431-438. doi:10.1016/s1360-1385(01)02052-0Hoffman, N. E., Ko, K., Milkowski, D., & Pichersky, E. (1991). Isolation and characterization of tomato cDNA and genomic clones encoding the ubiquitin gene ubi3. Plant Molecular Biology, 17(6), 1189-1201. doi:10.1007/bf00028735Huang, Z., Zhang, Z., Zhang, X., Zhang, H., Huang, D., & Huang, R. (2004). Tomato TERF1 modulates ethylene response and enhances osmotic stress tolerance by activating expression of downstream genes. FEBS Letters, 573(1-3), 110-116. doi:10.1016/j.febslet.2004.07.064HUSSEY, G. (1963). Growth and Development in the Young Tomato: I. THE EFFECT OF TEMPERATURE AND LIGHT INTENSITY ON GROWTH OF THE SHOOT APEX AND LEAF PRIMORDIA. Journal of Experimental Botany, 14(2), 316-325. doi:10.1093/jxb/14.2.316Imaizumi, T. (2005). FKF1 F-Box Protein Mediates Cyclic Degradation of a Repressor of CONSTANS in Arabidopsis. Science, 309(5732), 293-297. doi:10.1126/science.1110586IWAMOTO, M., HIGO, K., & TAKANO, M. (2009). Circadian clock- and phytochrome-regulated Dof-like gene,Rdd1, is associated with grain size in rice. Plant, Cell & Environment, 32(5), 592-603. doi:10.1111/j.1365-3040.2009.01954.xJang, S., Marchal, V., Panigrahi, K. C. S., Wenkel, S., Soppe, W., Deng, X.-W., … Coupland, G. (2008). Arabidopsis COP1 shapes the temporal pattern of CO accumulation conferring a photoperiodic flowering response. The EMBO Journal, 27(8), 1277-1288. doi:10.1038/emboj.2008.68Jones, M. L. (2013). Mineral nutrient remobilization during corolla senescence in ethylene-sensitive and -insensitive flowers. AoB Plants, 5(0), plt023-plt023. doi:10.1093/aobpla/plt023Karimi, M., Depicker, A., & Hilson, P. (2007). Recombinational Cloning with Plant Gateway Vectors. Plant Physiology, 145(4), 1144-1154. doi:10.1104/pp.107.106989Kerepesi, I., & Galiba, G. (2000). Osmotic and Salt Stress-Induced Alteration in Soluble Carbohydrate Content in Wheat Seedlings. Crop Science, 40(2), 482. doi:10.2135/cropsci2000.402482xKinet, J. M. (1977). Effect of light conditions on the development of the inflorescence in tomato. Scientia Horticulturae, 6(1), 15-26. doi:10.1016/0304-4238(77)90074-7Kirby, J., & Kavanagh, T. A. (2002). NAN fusions: a synthetic sialidase reporter gene as a sensitive and versatile partner for GUS. The Plant Journal, 32(3), 391-400. doi:10.1046/j.1365-313x.2002.01422.xKloosterman, B., Abelenda, J. A., Gomez, M. del M. C., Oortwijn, M., de Boer, J. M., Kowitwanich, K., … Bachem, C. W. B. (2013). Naturally occurring allele diversity allows potato cultivation in northern latitudes. Nature, 495(7440), 246-250. doi:10.1038/nature11912Konishi, M., & Yanagisawa, S. (2007). Sequential activation of two Dof transcription factor gene promoters during vascular development in Arabidopsis thaliana. Plant Physiology and Biochemistry, 45(8), 623-629. doi:10.1016/j.plaphy.2007.05.001Krohn, N. M., Yanagisawa, S., & Grasser, K. D. (2002). Specificity of the Stimulatory Interaction between Chromosomal HMGB Proteins and the Transcription Factor Dof2 and Its Negative Regulation by Protein Kinase CK2-mediated Phosphorylation. Journal of Biological Chemistry, 277(36), 32438-32444. doi:10.1074/jbc.m203814200Kurai, T., Wakayama, M., Abiko, T., Yanagisawa, S., Aoki, N., & Ohsugi, R. (2011). Introduction of the ZmDof1 gene into rice enhances carbon and nitrogen assimilation under low-nitrogen conditions. Plant Biotechnology Journal, 9(8), 826-837. doi:10.1111/j.1467-7652.2011.00592.xKushwaha, H., Gupta, S., Singh, V. K., Rastogi, S., & Yadav, D. (2010). Genome wide identification of Dof transcription factor gene family in sorghum and its comparative phylogenetic analysis with rice and Arabidopsis. Molecular Biology Reports, 38(8), 5037-5053. doi:10.1007/s11033-010-0650-9Lakhssassi, N., Doblas, V. G., Rosado, A., del Valle, A. E., Posé, D., Jimenez, A. J., … Botella, M. A. (2012). The Arabidopsis TETRATRICOPEPTIDE THIOREDOXIN-LIKE Gene Family Is Required for Osmotic Stress Tolerance and Male Sporogenesis. Plant Physiology, 158(3), 1252-1266. doi:10.1104/pp.111.188920Lee, H. E., Shin, D., Park, S. R., Han, S.-E., Jeong, M.-J., Kwon, T.-R., … Byun, M.-O. (2007). Ethylene responsive element binding protein 1 (StEREBP1) from Solanum tuberosum increases tolerance to abiotic stress in transgenic potato plants. Biochemical and Biophysical Research Communications, 353(4), 863-868. doi:10.1016/j.bbrc.2006.12.095Lijavetzky, D., Carbonero, P., & Vicente-Carbajosa, J. (2003). BMC Evolutionary Biology, 3(1), 17. doi:10.1186/1471-2148-3-17Livak, K. J., & Schmittgen, T. D. (2001). Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method. Methods, 25(4), 402-408. doi:10.1006/meth.2001.1262Mackay, J. P., & Crossley, M. (1998). Zinc fingers are sticking together. Trends in Biochemical Sciences, 23(1), 1-4. doi:10.1016/s0968-0004(97)01168-7Mena, M., Vicente-Carbajosa, J., Schmidt, R. J., & Carbonero, P. (1998). An endosperm-specific DOF protein from barley, highly conserved in wheat, binds to and activates transcription from the prolamin-box of a native B-hordein promoter in barley endosperm. The Plant Journal, 16(1), 53-62. doi:10.1046/j.1365-313x.1998.00275.xMizoguchi, T., Wright, L., Fujiwara, S., Cremer, F., Lee, K., Onouchi, H., … Coupland, G. (2005). Distinct Roles of GIGANTEA in Promoting Flowering and Regulating Circadian Rhythms in Arabidopsis. The Plant Cell, 17(8), 2255-2270. doi:10.1105/tpc.105.033464Moreno-Risueno, M. Á., Martínez, M., Vicente-Carbajosa, J., & Carbonero, P. (2006). The family of DOF transcription factors: from green unicellular algae to vascular plants. Molecular Genetics and Genomics, 277(4), 379-390. doi:10.1007/s00438-006-0186-9Moreno-Risueno, M. Á., Díaz, I., Carrillo, L., Fuentes, R., & Carbonero, P. (2007). The HvDOF19 transcription factor mediates the abscisic acid-dependent repression of hydrolase genes in germinating barley aleurone. The Plant Journal, 51(3), 352-365. doi:10.1111/j.1365-313x.2007.03146.xMurashige, T., & Skoog, F. (1962). A Revised Medium for Rapid Growth and Bio Assays with Tobacco Tissue Cultures. Physiologia Plantarum, 15(3), 473-497. doi:10.1111/j.1399-3054.1962.tb08052.xNakagawa, T., Kurose, T., Hino, T., Tanaka, K., Kawamukai, M., Niwa, Y., … Kimura, T. (2007). Development of series of gateway binary vectors, pGWBs, for realizing efficient construction of fusion genes for plant transformation. Journal of Bioscience and Bioengineering, 104(1), 34-41. doi:10.1263/jbb.104.34Oñate-Sánchez, L., & Vicente-Carbajosa, J. (2008). DNA-free RNA isolation protocols for Arabidopsis thaliana, including seeds and siliques. BMC Research Notes, 1(1), 93. doi:10.1186/1756-0500-1-93ORELLANA, S., YAÑEZ, M., ESPINOZA, A., VERDUGO, I., GONZÁLEZ, E., RUIZ-LARA, S., & CASARETTO, J. A. (2010). The transcription factor SlAREB1 confers drought, salt stress tolerance and regulates biotic and abiotic stress-related genes in tomato. Plant, Cell & Environment, 33(12), 2191-2208. doi:10.1111/j.1365-3040.2010.02220.xPapi, M., Sabatini, S., Altamura, M. M., Hennig, L., Schäfer, E., Costantino, P., & Vittorioso, P. (2002). Inactivation of the Phloem-Specific Dof Zinc Finger GeneDAG1 Affects Response to Light and Integrity of the Testa of Arabidopsis Seeds. Plant Physiology, 128(2), 411-417. doi:10.1104/pp.010488Pinheiro, C., & Chaves, M. M. (2010). Photosynthesis and drought: can we make metabolic connections from available data? Journal of Experimental Botany, 62(3), 869-882. doi:10.1093/jxb/erq340Pnueli, L. (2001). Tomato SP-Interacting Proteins Define a Conserved Signaling System That Regulates Shoot Architecture and Flowering. THE PLANT CELL ONLINE, 13(12), 2687-2702. doi:10.1105/tpc.13.12.2687Rajasekaran, L. R., Aspinall, D., & Paleg, L. G. (2000). Physiological mechanism of tolerance of Lycopersicon spp. exposed to salt stress. Canadian Journal of Plant Science, 80(1), 151-159. doi:10.4141/p99-003Rizhsky, L., Liang, H., Shuman, J., Shulaev, V., Davletova, S., & Mittler, R. (2004). When Defense Pathways Collide. The Response of Arabidopsis to a Combination of Drought and Heat Stress. Plant Physiology, 134(4), 1683-1696. doi:10.1104/pp.103.033431Rueda-López, M., Crespillo, R., Cánovas, F. M., & Ávila, C. (2008). Differential regulation of two glutamine synthetase genes by a single Dof transcription factor. The Plant Journal, 56(1), 73-85. doi:10.1111/j.1365-313x.2008.03573.xSawa, M., Nusinow, D. A., Kay, S. A., & Imaizumi, T. (2007). FKF1 and GIGANTEA Complex Formation Is Required for Day-Length Measurement in Arabidopsis. Science, 318(5848), 261-265. doi:10.1126/science.1146994Seki, M., Umezawa, T., Urano, K., & Shinozaki, K. (2007). Regulatory metabolic networks in drought stress responses. Current Opinion in Plant Biology, 10(3), 296-302. doi:10.1016/j.pbi.2007.04.014Shannon, M. C., & Grieve, C. M. (1998). Tolerance of vegetable crops to salinity. Scientia Horticulturae, 78(1-4), 5-38. doi:10.1016/s0304-4238(98)00189-7Shaw, L. M., McIntyre, C. L., Gresshoff, P. M., & Xue, G.-P. (2009). Members of the Dof transcription factor family in Triticum aestivum are associated with light-mediated gene regulation. Functional & Integrative Genomics, 9(4), 485-498. doi:10.1007/s10142-009-0130-2Shelp, B. J., Bown, A. W., & Faure, D. (2006). Extracellular γ-Aminobutyrate Mediates Communication between Plants and Other Organisms. Plant Physiology, 142(4), 1350-1352. doi:10.1104/pp.106.088955Shelp, B. (1999). Metabolism and functions of gamma-aminobutyric acid. Trends in Plant Science, 4(11), 446-452. doi:10.1016/s1360-1385(99)01486-7Skirycz, A., Jozefczuk, S., Stobiecki, M., Muth, D., Zanor, M. I., Witt, I., & Mueller-Roeber, B. (2007). Transcription factor AtDOF4;2 affects phenylpropanoid metabolism in Arabidopsis thaliana. New Phytologist, 175(3), 425-438. doi:10.1111/j.1469-8137.2007.02129.xSkirycz, A., Reichelt, M., Burow, M., Birkemeyer, C., Rolcik, J., Kopka, J., … Witt, I. (2006). DOF transcription factor AtDof1.1 (OBP2) is part of a regulatory network controlling glucosinolate biosynthesis in Arabidopsis. The Plant Journal, 47(1), 10-24. doi:10.1111/j.1365-313x.2006.02767.xSuárez-López, P., Wheatley, K., Robson, F., Onouchi, H., Valverde, F., & Coupland, G. (2001). CONSTANS mediates between the circadian clock and the control of flowering in Arabidopsis. Nature, 410(6832), 1116-1120. doi:10.1038/35074138Sun, S.-J., Guo, S.-Q., Yang, X., Bao, Y.-M., Tang, H.-J., Sun, H., … Zhang, H.-S. (2010). Functional analysis of a novel Cys2/His2-type zinc finger protein involved in salt tolerance in rice. Journal of Experimental Botany, 61(10), 2807-2818. doi:10.1093/jxb/erq120Takada, S., & Goto, K. (2003). TERMINAL FLOWER2, an Arabidopsis Homolog of HETEROCHROMATIN PROTEIN1, Counteracts the Activation of FLOWERING LOCUS T by CONSTANS in the Vascular Tissues of Leaves to Regulate Flowering Time. The Plant Cell, 15(12), 2856-2865. doi:10.1105/tpc.016345Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S. (2011). MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution, 28(10), 2731-2739. doi:10.1093/molbev/msr121Thompson, J. (1997). The CLUSTAL_X windows
Analysis of the common genetic component of large-vessel vasculitides through a meta- Immunochip strategy
Giant cell arteritis (GCA) and Takayasu's arteritis (TAK) are major forms of large-vessel vasculitis (LVV) that share clinical features. To evaluate their genetic similarities, we analysed Immunochip genotyping data from 1,434 LVV patients and 3,814 unaffected controls. Genetic pleiotropy was also estimated. The HLA region harboured the main disease-specific associations. GCA was mostly associated with class II genes (HLA-DRB1/HLA-DQA1) whereas TAK was mostly associated with class I genes (HLA-B/MICA). Both the statistical significance and effect size of the HLA signals were considerably reduced in the cross-disease meta-analysis in comparison with the analysis of GCA and TAK separately. Consequently, no significant genetic correlation between these two diseases was observed when HLA variants were tested. Outside the HLA region, only one polymorphism located nearby the IL12B gene surpassed the study-wide significance threshold in the meta-analysis of the discovery datasets (rs755374, P?=?7.54E-07; ORGCA?=?1.19, ORTAK?=?1.50). This marker was confirmed as novel GCA risk factor using four additional cohorts (PGCA?=?5.52E-04, ORGCA?=?1.16). Taken together, our results provide evidence of strong genetic differences between GCA and TAK in the HLA. Outside this region, common susceptibility factors were suggested, especially within the IL12B locus
A genome-wide association study identifies risk alleles in plasminogen and P4HA2 associated with giant cell arteritis
Giant cell arteritis (GCA) is the most common form of vasculitis in individuals older than 50 years in Western countries. To shed light onto the genetic background influencing susceptibility for GCA, we performed a genome-wide association screening in a well-powered study cohort. After imputation, 1,844,133 genetic variants were analysed in 2,134 cases and 9,125 unaffected controls from ten independent populations of European ancestry. Our data confirmed HLA class II as the strongest associated region (independent signals: rs9268905, P = 1.94E-54, per-allele OR = 1.79; and rs9275592, P = 1.14E-40, OR = 2.08). Additionally, PLG and P4HA2 were identified as GCA risk genes at the genome-wide level of significance (rs4252134, P = 1.23E-10, OR = 1.28; and rs128738, P = 4.60E-09, OR = 1.32, respectively). Interestingly, we observed that the association peaks overlapped with different regulatory elements related to cell types and tissues involved in the pathophysiology of GCA. PLG and P4HA2 are involved in vascular remodelling and angiogenesis, suggesting a high relevance of these processes for the pathogenic mechanisms underlying this type of vasculitis
The James Webb Space Telescope Mission
Twenty-six years ago a small committee report, building on earlier studies,
expounded a compelling and poetic vision for the future of astronomy, calling
for an infrared-optimized space telescope with an aperture of at least .
With the support of their governments in the US, Europe, and Canada, 20,000
people realized that vision as the James Webb Space Telescope. A
generation of astronomers will celebrate their accomplishments for the life of
the mission, potentially as long as 20 years, and beyond. This report and the
scientific discoveries that follow are extended thank-you notes to the 20,000
team members. The telescope is working perfectly, with much better image
quality than expected. In this and accompanying papers, we give a brief
history, describe the observatory, outline its objectives and current observing
program, and discuss the inventions and people who made it possible. We cite
detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space
Telescope Overview, 29 pages, 4 figure
Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
The Global Burden of Diseases, Injuries and Risk Factors 2017 includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. METHODS: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting
Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)
Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning
- …