Publicado
Unraveling the molecules hidden in the gray shadows of quantitative disease resistance to pathogens
Descifrando las moléculas ocultas en las sombras grises de la resistencia cuantitativa a patógenos
DOI:
https://doi.org/10.15446/abc.v23n1.66487Palabras clave:
breeding, complex traits, genome, gene expression, plant immunity, quantitative disease resistance (QDR), quantitative trait loci (QTL). (en)expresión génica, fitomejoramiento, genoma, inmunidad vegetal, loci de caracteres cuantitativos, rasgos complejos, resistencia cuantitativa a enfermedades. (es)
Descargas
One of the most challenging questions in plant breeding and molecular plant pathology research is what are the genetic and molecular bases of quantitative disease resistance (QDR)?. The scarce knowledge of how this type of resistance works has hindered plant breeders to fully take advantage of it. To overcome these obstacles new methodologies for the study of quantitative traits have been developed. Approaches such as genetic mapping, identification of quantitative trait loci (QTL) and association mapping, including candidate gene approach and genome wide association studies, have been historically undertaken to dissect quantitative traits and therefore to study QDR. Additionally, great advances in quantitative phenotypic data collection have been provided to improve these analyses. Recently, genes associated to QDR have been cloned, leading to new hypothesis concerning the molecular bases of this type of resistance. In this review we present the more recent advances about QDR and corresponding application, which have allowed postulating new ideas that can help to construct new QDR models. Some of the hypotheses presented here as possible explanations for QDR are related to the expression level and alternative splicing of some defense-related genes expression, the action of “weak alleles” of R genes, the presence of allelic variants in genes involved in the defense response and a central role of kinases or pseudokinases. With the information recapitulated in this review it is possible to conclude that the conceptual distinction between qualitative and quantitative resistance may be questioned since both share important components.
Una de las preguntas más desafiantes del fitomejoramiento y de la fitopatología molecular es ¿cuáles son las bases genéticas y moleculares de la resistencia cuantitativa a enfermedades?. El escaso conocimiento de cómo este tipo de resistencia funciona ha obstaculizado que los fitomejoradores la aprovecharlo plenamente. Para superar estos obstáculos se han desarrollado nuevas metodologías para el estudio de rasgos cuantitativos. Los enfoques como el mapeo genético, la identificación de loci de rasgos cuantitativos (QTL) y el mapeo por asociaciones, incluyendo el enfoque de genes candidatos y los estudios de asociación amplia del genoma, se han llevado a cabo históricamente para describir rasgos cuantitativos y por lo tanto para estudiar QDR. Además, se han proporcionado grandes avances en la obtención de datos fenotípicos cuantitativos para mejorar estos análisis. Recientemente, algunos genes asociados a QDR han sido clonados, lo que conduce a nuevas hipótesis sobre las bases moleculares de este tipo de resistencia. En esta revisión presentamos los avances más recientes sobre QDR y la correspondiente aplicación, que han permitido postular nuevas ideas que pueden ayudar a construir nuevos modelos. Algunas de las hipótesis presentadas aquí como posibles explicaciones para QDR están relacionadas con el nivel de expresión y el splicing alternativo de algunos genes relacionados con la defensa, la acción de "alelos débiles" de genes R, la presencia de variantes alélicas en los genes implicados en la respuesta de defensa y un papel central de quinasas o pseudoqinasas. Con la información recapitulada en esta revisión es posible concluir que la distinción conceptual entre resistencia cualitativa y cuantitativa puede ser cuestionada ya que ambos comparten importantes componentes.
Referencias
Afzal AJ, Wood AJ, Lightfoot DA. Plant receptor-like serine threonine kinases: roles in signaling and plant defense. Mol Plant Microbe Interact. 2008;21:507-517. Doi:10.1094/MPMI-21-5-0507.
Ansorge WJ. Next-generation DNA sequencing techniques. New biotechnology. 2009;25:195-203. Doi:10.1016/j.nbt.2008.12.009.
Araus JL, Cairns JE. Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci. 2014;19:52-61. Doi:10.1016/j.tplants.2013.09.008
Arruda MP, Brown P, Brown-Guedira G, Krill A, Thurber C, Merrill K, Foresman B, Kolb F. Genome-wide association mapping of fusarium head blight resistance in wheat using genotyping-by-sequencing. The Plant Genome. 2016;9(1). Doi:10.3835/plantgenome2015.04.0028
Baker NR. Chlorophyll fluorescence: a probe of photosynthesis in vivo. Annu Rev Plant Biol. 2008;59:89-113. Doi:10.1146/annurev.arplant.59.032607.092759
Basu PS, Srivastava M, Singh P, Porwal P, Kant R, Singh J. High-precision phenotyping under controlled versus natural environments. In. Phenomics in Crop Plants: Trends, Options and Limitations. Springer: India; 2015. p. 27-40.
Bauriegel E, Herppich WB. Hyperspectral and chlorophyll fluorescence imaging for early detection of plant diseases, with special reference to Fusarium spec. infections on wheat. Agriculture 2014;4:32-57. Doi:10.3390/agriculture4010032
Benson JM, Poland JA, Benson BM, Stromberg EL, Nelson RJ. Resistance to gray leaf spot of maize: genetic architecture and mechanisms elucidated through nested association mapping and near-isogenic line analysis. PLoS Genet. 2015;11(13):e1005045. Doi:10.1371/journal.pgen.1005045
Bonierbale MW, Plaisted RL, Tanksley SD. RFLP maps based on a common set of clones reveal modes of chromosomal evolution in potato and tomato. Genetics. 1988;120:1095-103.
Bozsó Z, Maunoury N, Szatmari A, Mergaert P, Ott P, Zsíros L, Szabó E, Kondorosi E, Klement Z. Transcriptome analysis of a bacterially induced basal and hypersensitive response of Medicago truncatula. Plant Mol Biol. 2009;70(6):627-46. Doi:10.1007/s11103-009-9496-8
Bozso Z, Ott PG, Kaman-Toth E, Bognar GF, Pogany M, Szatmari A. Overlapping yet response-specific transcriptome alterations characterize the nature of tobacco-Pseudomonas syringae interactions. Front. Plant Sci. 2016;7(251). Doi: 10.3389/fpls.2016.00251
Brachi B, Morris GP, Borevitz JO. Genome-wide association studies in plants: the missing heritability is in the field. Genome Biol. 2011;12(10):232. Doi:10.1186/gb-2011-12-10-232
Brun H, Chèvre AM, Fitt BD, Powers S, Besnard A, Ermel L, Huteau V, et al. Quantitative resistance increases the durability of qualitative resistance to Leptosphaeria maculans in Brassica napus. New Phytol. 2010;185(1):285-99. Doi:10.1111/j.1469-8137.2009.03049.x
Bryant RR, Mcgrann GR, Mitchell AR, Schoonbeek H, Boyd L, Uauy C, Dorling S, Ridout C. A change in temperature modulates defence to yellow (stripe) rust in wheat line UC1041 independently of resistance gene Yr36. BMC Plant Biol. 2014; 14(1):10. Doi: 10.1186/1471-2229-14-10
Bustamam M, Tabien R, Suwarno A, Abalos M, Kadir T, Ona L, Bernardo M, et al. Asian rice biotechnology network: Improving popular cultivars through marker-assisted backcrossing by the NARES. Proceedings of the Poster presented at the international rice congress. 2002. p. 16-20.
Cavanagh C, Morell M, Mackay I, Powell W. From mutations to MAGIC: resources for gene discovery, validation and delivery in crop plants. Curr Opin Plant Biol. 2008;11(2):215-221. Doi:10.1016/j.pbi.2008.01.002
Collard B, Jahufer M, Brouwer J, Pang E. An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts. Euphytica. 2005;142:169-196. Doi:10.1007/s10681-005-1681-5
Cook DE, Mesarich CH, Thomma BP. Understanding plant immunity as a surveillance system to detect invasion. Annu Rev Phytopathol. 2015;53,541-563. Doi:10.1146/annurev-phyto-080614-120114
Corwin JA, Copeland D, Feusier J, Subedy A, Eshbaugh R, Palmer C, Maloof J, Kliebenstein D. The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics. PLoS Genet. 2016;12(2):e1005789. Doi:10.1371/journal.pgen.1005789
Cui H, Tsuda K, Parker JE. Effector-triggered immunity: from pathogen perception to robust defense. Annu Rev Plant Biol. 2015;66:487-511. Doi:10.1146/annurev-arplant-050213-040012
Chisholm ST, Coaker G, Day B, Staskawicz BJ. Host-microbe interactions: shaping the evolution of the plant immune response. Cell. 2006;124(4):803-814. Doi:10.1016/j.cell.2006.02.008
De Smet I, Voss U, Jurgens G, Beeckman T. Receptor-like kinases shape the plant. Nat Cell Biol. 2009;11(10):1166-1173. Doi:10.1038/ncb1009-1166
Dinesh-Kumar SP, Baker BJ. Alternatively spliced N resistance gene transcripts: their possible role in tobacco mosaic virus resistance. Proc Natl Acad Sci USA. 2000;97(4):1908-1913. Doi:10.1073/pnas.020367497
Druka A, Potokina E, Luo Z, et al. Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley. Theor Appl Genet. 2008;117(2):261-272. Doi:10.1007/s00122-008-0771-x
El-Soda M, Malosetti M, Zwaan BJ, Koornneef M, Aarts MG. Genotype x environment interaction QTL mapping in plants: lessons from Arabidopsis. Trends Plant Sci. 2014;19(6):390-398. Doi:10.1016/j.tplants.2014.01.001
Falconer DS, Mackay TFC. Introduction to Quantitative Genetics London, UK: Prentice Hall; 1996. p. 56-70.
Flor HH. Host-parasite interaction in flax rust—Its genetics and other implications. Phytopathology. 1955;45:680–685. Doi:10.1016/S0065-2660(08)60498-8
Fu D, Uauy C, Distelfeld A, Blechl A, Epstein L, Chen Z, Sela H, et al. A kinase-START gene confers temperature-dependent resistance to wheat stripe rust. Science. 2009;23(5919):1357-1360. Doi:10.1126/science.1166289
Fukuoka S, Saka N, Koga H, Ono K, Shimizu T, Ebana K, Hayashi N, Takahashi A, Hirochika H, Okuno K, Yano M. Loss of function of a proline-containing protein confers durable disease resistance in rice. Science. 2009;325(5943):998-1001. Doi:10.1126/science.1175550
Gautami B, Foncéka D, Pandey MK, Moretzsohn M, Sujay V, Qin H, Hong Y. An international reference consensus genetic map with 897 marker loci based on 11 mapping populations for tetraploid groundnut (Arachis hypogaea L.). PLoS ONE. 2012;7(7):e41213. Doi:10.1371/journal.pone.0041213
Giannakopoulou A, Steele JF, Segretin ME, Bozkurt T, Zhou J, Robatzek S, Banfield M, Pais M, Kamoun S. Tomato I2 immune receptor can be engineered to confer partial resistance to the oomycete Phytophthora infestans in addition to the fungus Fusarium oxysporum. Mol Plant Microbe Interact. 2015;28(12):1316-1329.
Doi:10.1094/MPMI-07-15-0147-R
Glazier AM, Nadeau JH, Aitman TJ. Finding genes that underlie complex traits. Science. 2002;298(5602):2345-2349. Doi:10.1126/science.1076641
Griffiths AJ. An introduction to genetic analysis. Macmillan. 2005. p. 61-67.
Gutiérrez L, Germán S, Pereyra S, Hayes PM, Pérez CA, Capettini F, Locatelli A, et al. Multi-environment multi-QTL association mapping identifies disease resistance QTL in barley germplasm from Latin America. Theor Appl Genet. 2015;128(3);501-516. Doi:10.1007%2Fs00122-014-2448-y
Heffner EL, Sorrells ME, Jannink J-L. Genomic selection for crop improvement. Crop Science. 2009;49(1):1-12. Doi:10.2135/cropsci2008.08.0512
Helentjaris T, Weber D, Wright S. Identification of the genomic locations of duplicate nucleotide sequences in maize by analysis of restriction fragment length polymorphisms. Genetics. 1988;118(2):353-363.
Hematy K, Hofte H. Novel receptor kinases involved in growth regulation. Curr Opin Plant Biol. 2008;11(3):321-328. Doi:10.1016/j.pbi.2008.02.008
Houterman PM, Ma L, Van Ooijen G, de Vroomen M, Cornelissen B, Takken F, Rep M. The effector protein Avr2 of the xylem-colonizing fungus Fusarium oxysporum activates the tomato resistance protein I-2 intracellularly. Plant J. 2009;58(6):970-978. Doi:10.1111/j.1365-313X.2009.03838.x
Huard-Chauveau C, Perchepied L, Debieu M, Rivas S, Kroj T, Kars I, Bergelson J, Roux F, Roby D. An atypical kinase under balancing selection bonfers broad-spectrum disease resistance in Arabidopsis. PLoS Genet. 2013;9(9):e1003766. Doi:10.1371/journal.pgen.1003766
Iquira E, Humira S, François B. Association mapping of QTLs for sclerotinia stem rot resistance in a collection of soybean plant introductions using a genotyping by sequencing (GBS) approach. BMC Plant Biol. 2015;15(1):5. Doi:10.1186/s12870-014-0408-y
Johnson R. Genetic Background of Durable Resistance. In: Lamberti F, Waller JM, Graaff NA, editors. Durable Resistance in Crops. Boston, MA: Springer New York; 1983. p. 5-26.
Jones JD, Dangl JL. The plant immune system. Nature. 2006;444(7117):323. Doi:10.1038/nature05286
Kou Y, Wang S. Broad-spectrum and durability: understanding of quantitative disease resistance. Curr Opin Plant Biol. 2010;13(2):181-185. Doi:10.1016/j.pbi.2009.12.010
Krattinger SG, Lagudah ES, Spielmeyer W, Singh RP, Huerta-Espino J, McFadden H, Bossolini E, Selter LL, Keller B. A putative ABC transporter confers durable resistance to multiple fungal pathogens in wheat. Science. 2009;323(5919):1360-1363. Doi:10.1126/science.1166453
Kushalappa AC, Yogendra KN, Karre S. Plant innate immune response: qualitative and quantitative resistance. Crit Rev Plant Sci. 2016;35(1):38-55. Doi:10.1080/07352689.2016.1148980
Lopez C. Descifrando las bases moleculares de la resistencia cuantitativa. Acta biol Col. 2011;16(2):3-14.
Mackay TFC, Stone EA, Ayroles JF. The genetics of quantitative traits: challenges and prospects. Nat Rev Genet. 2009;10(8):565. Doi: 10.1038/nrg2612
Mahlein A-K, Steiner U, Hillnhütter C, Dehne H-W, Oerke E-C. Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases. Plant Methods. 2012;8(1):3. Doi:10.1186/1746-4811-8-3
Miklas PN, Kelly JD, Beebe SE, Blair MW. Common bean breeding for resistance against biotic and abiotic stresses: from classical to MAS breeding. Euphytica. 2006;147(1-2):105-131. Doi:10.1007/s10681-006-4600-5
Mittler R, Blumwald E. Genetic engineering for modern agriculture: challenges and perspectives. Annu Rev Plant Biol. 2010;61:443-462. Doi:10.1146/annurev-arplant-042809-112116
Mutka AM, Bart RS. Image-based phenotyping of plant disease symptoms. Front Plant Sci. 2015;5:734. Doi: 10.3389/fpls.2014.00734
Mutka AM, Fentress SJ, Sher JW, Berry J, Pretz C, Nusinow D, Bart R. Quantitative, image-based phenotyping methods provide insight into spatial and temporal dimensions of plant disease. Plant Physiol. 2016;172(2):650-660. Doi:10.1104/pp.16.00984
Narusaka M, Shirasu K, Noutoshi Y, Kubo Y, Shiraishi T, Iwabuchi M, Narusaka Y. RRS1 and RPS4 provide a dual Resistance-gene system against fungal and bacterial pathogens. Plant J. 2009;60(2):218-226. Doi:10.1111/j.1365-313X.2009.03949.x
Navabi A, Singh RP, Huerta-Espino J, Tewari JP. Phenotypic association of adult-plant resistance to leaf and stripe rusts in wheat. Can J Plant Pathol. 2005;27(3):396-403. Doi:10.1080/07060660509507238
Navarro L, Zipfel C, Rowland O, Keller I, Robatzek S, Boller T, Jones JD. The transcriptional innate immune response to flg22. Interplay and overlap with Avr gene-dependent defense responses and bacterial pathogenesis. Plant Physiol. 2004;135(2):1113-1128. Doi:10.1104/pp.103.036749
Niks RE, Qi X, Marcel TC. Quantitative resistance to biotrophic filamentous plant pathogens: concepts, misconceptions, and mechanisms. Annu Rev Phytopathol. 2015;53:445-470. Doi:10.1146/annurev-phyto-080614-115928
Ntare B, Williams J. Heritability and genotype x environment interaction for yield and components of a yield model in segregating population of groundnut under semi-arid conditions. Afr Crop Sci. 1998;6:119-127.
Olukolu BA, Tracy WF, Wisser R, De Vries B, Balint-Kurti PJ. A genome-wide association study for partial resistance to maize common rust. Phytopathology. 2016;106(7):745-751. Doi:10.1094/PHYTO-11-15-0305-R
Parniske M. Arbuscular mycorrhiza: the mother of plant root endosymbioses. Nat Rev Micro. 2008;6(10):763-775. Doi:10.1038/nrmicro1987
Phillips RL, Vasil IK. DNA-based markers in plants. Springer Science & Business Media. 2013. p. 55-56
Poland JA, Balint-Kurti PJ, Wisser RJ, Pratt RC, Nelson RJ. Shades of gray: the world of quantitative disease resistance. Trends Plant Sci. 2009;14(1):21-29. Doi:10.1016/j.tplants.2008.10.006
Rafalski A. Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol. 2002;5(2):94-100. Doi:10.1016/S1369-5266(02)00240-6
Roux F, Noël L, Rivas S, Roby D. ZRK atypical kinases: emerging signaling components of plant immunity. New Phytologist. 2014a;203(3):713-716. Doi:10.1111/nph.12841
Roux F, Voisin D, Badet T, Balagué C, Barlet X, Huard-Chauveau C, Roby D, Raffaele S. Resistance to phytopathogens e tutti quanti: placing plant quantitative disease resistance on the map. Mol Plant Pathol. 2014b;15(5):427-432. Doi:10.1111/mpp.12138
Sadhu MJ, Bloom JS, Day L, Kruglyak L. CRISPR-directed mitotic recombination enables genetic mapping without crosses. Science. 2016;352(6289):1113-1116. Doi:10.1126/science.aaf5124
Salvi S, Tuberosa R. The crop QTLome comes of age. Curr Opin Biotechnol. 2015;32:179-185. Doi:10.1016/j.copbio.2015.01.001
Santner A, Estelle M. Recent advances and emerging trends in plant hormone signalling. Nature. 2009;459(7250):1071. Doi:10.1038/nature08122
Sax K. The association of size differences with seed-coat pattern and pigmentation in Phaseolus vulgaris. Genetics. 1923;8:552-60.
Schwessinger B, Zipfel C. News from the frontline: recent insights into PAMP-triggered immunity in plants. Curr Opin Plant Biol. 2008;11(4):389-395. Doi:10.1016/j.pbi.2008.06.001
Segretin ME, Pais M, Franceschetti M, Chaparro-Garcia A, Bos JI, Banfield MJ, Kamoun S. et al. Single amino acid mutations in the potato immune receptor R3a expand response to Phytophthora effectors. Mol Plant Microbe Interact. 2014;27(7):624-637. Doi:10.1094/MPMI-02-14-0040-R
Sehgal D. Advances in Molecular Breeding of Pearl Millet. In: Molecular Breeding for Sustainable Crop Improvement. Springer; 2016. p. 397-419.
Soriano JM, Royo C. Dissecting the genetic architecture of leaf rust resistance in wheat by QTL meta-analysis. Phytopathology. 2015;105(12):1585-1593. Doi:10.1094/PHYTO-05-15-0130-R
Soto JC, Ortiz JF, Perlaza-Jiménez L, Vásquez AX, Lopez-Lavalle LA, Mathew B, Léon J, Bernal AJ, Ballvora A, López CE. A genetic map of cassava (Manihot esculenta Crantz) with integrated physical mapping of immunity-related genes. BMC Genomics. 2015;16(1):190. Doi:10.1186/s12864-015-1397-4
St. Clair DA. Quantitative disease resistance and quantitative resistance loci in breeding. Annu Rev Phytopathol. 2010;48:247-268. Doi:10.1146/annurev-phyto-080508-081904
Stephens A, Lombardi M, Cogan NO, Forster J, Hobson K, Materne M, Kaur S. Genetic marker discovery, intraspecific linkage map construction and quantitative trait locus analysis of Ascochyta blight resistance in chickpea (Cicer arietinum L.). Molecular Breeding. 2014;33(2):297-313. Doi:10.1007/s11032-013-9950-9
Summers R, Brown J. Constraints on breeding for disease resistance in commercially competitive wheat cultivars. Plant Pathology. 2013;62(S1):115-121. Doi:10.1111/ppa.12165
Tanksley SD, Medina-Filho H, Rick CM. Use of naturally-occurring enzyme variation to detect and map genes controlling quantitative traits in an interspecific backcross of tomato. Heredity. 1982;49:11-25.
Tao Y, Xie Z, Chen W, Glazebrook J, Chang HS, Han B, Zhu T, Zou G, Katagiri F. Quantitative nature of Arabidopsis responses during compatible and incompatible interactions with the bacterial pathogen Pseudomonas syringae. Plant Cell. 2003;15(2):317-330. Doi:10.1105/tpc.007591
Thoday JM. Location of Polygenes. Nature. 1961;191:368-370.
Turuspekov Y, Ormanbekova D, Rsaliev A, Abugalieva S. Genome-wide association study on stem rust resistance in Kazakh spring barley lines. BMC Plant Biol. 2016;16(1):6. Doi:10.1186/s12870-015-0686-z
Venuti S, Copetti D, Foria S, Falginella L, Hoffmann S, Bellin D, Cindrić P, et al. Historical introgression of the downy mildew resistance gene Rpv12 from the Asian species Vitis amurensis into grapevine varieties. Plos One. 2013;8(4):e61228. Doi:10.1371/journal.pone.0061228
Wang Y, Xu J, Deng D, Ding H, Bian Y, Yin Z, et al. A comprehensive meta-analysis of plant morphology, yield, stay-green, and virus disease resistance QTL in maize (Zea mays L.). Planta. 2016;243(2):459-471. Doi:10.1007/s00425-015-2419-9
Xiao S, Ellwood S, Calis O, Patrick E, Li T, Coleman M, Turner JG. Broad-spectrum mildew resistance in Arabidopsis thaliana mediated by RPW8. Science. 2001;291(5501):118-120. Doi:10.1126/science.291.5501.118
Xu Y, Crouch JH. Marker-assisted selection in plant breeding: from publications to practice. Crop Science. 2008;48(2):391-407. Doi:10.2135/cropsci2007.04.0191
Yang J, Jiang H, Yeh CT, Jeddeloh JA, Nettleton D, Schnable PS. Extreme‐phenotype genome‐wide association study (XP‐GWAS): a method for identifying trait‐associated variants by sequencing pools of individuals selected from a diversity panel. Plant J. 2015; 84(3):587-596. Doi:10.1111/tpj.13029
Zhang J, Yu J, Pei W, Li X, Said J, Song M, Sanogo S. Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton. BMC Genomics. 2015;16(1):577. Doi:10.1186/s12864-015-1682-2
Zhao BY, Ardales E, Brasset E, Claflin LE, Leach JE, Hulbert SH. The Rxo1/ Rba1 locus of maize controls resistance reactions to pathogenic and non-host bacteria. Theor Appl Genet. 2004;109(1):71-79.
Zhu C, Gore M, Buckler ES, Yu J. Status and prospects of association mapping in plants. Plant Genome. 2008;1(1):5-20. Doi:10.3835/plantgenome2008.02.0089
Zipfel C. Plant pattern-recognition receptors. Trends Immunol. 2014;35(7):345-351. Doi:10.1016/j.it.2014.05.004
Zuo W, Chao Q, Zhang N, Ye J, Tan Q, Li B, Xing Y, et al. A maize wall-associated kinase confers quantitative resistance to head smut. Nat Genet. 2015;47(2):151-157. Doi:10.1038/ng.3170
Dimensions
PlumX
Visitas a la página del resumen del artículo
Descargas
Cómo citar
Licencia
Derechos de autor 2017 Acta Biológica Colombiana
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
1. La aceptación de manuscritos por parte de la revista implicará, además de su edición electrónica de acceso abierto bajo licencia Attribution-NonCommercial-ShareAlike 4.0 (CC BY NC SA), la inclusión y difusión del texto completo a través del repositorio institucional de la Universidad Nacional de Colombia y en todas aquellas bases de datos especializadas que el editor considere adecuadas para su indización con miras a incrementar la visibilidad de la revista.
2. Acta Biológica Colombiana permite a los autores archivar, descargar y compartir, la versión final publicada, así como las versiones pre-print y post-print incluyendo un encabezado con la referencia bibliográfica del articulo publicado.
3. Los autores/as podrán adoptar otros acuerdos de licencia no exclusiva de distribución de la versión de la obra publicada (p. ej.: depositarla en un archivo telemático institucional o publicarla en un volumen monográfico) siempre que se indique la publicación inicial en esta revista.
4. Se permite y recomienda a los autores/as difundir su obra a través de Internet (p. ej.: en archivos institucionales, en su página web o en redes sociales cientificas como Academia, Researchgate; Mendelay) lo cual puede producir intercambios interesantes y aumentar las citas de la obra publicada. (Véase El efecto del acceso abierto).
