Soil electrical resistivity at different water contents in an integrated crop-livestock-forest system in Brazil.

Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16-20 2017

Diversity in Expression of Phosphorus (P) Responsive Genes in Cucumis melo L

Phosphorus (P) is a major limiting nutrient for plant growth in many soils. Studies in model species have identified genes involved in plant adaptations to low soil P availability. However, little information is available on the genetic bases of these adaptations in vegetable crops. In this respect, sequence data for melon now makes it possible to identify melon orthologues of candidate P responsive genes, and the expression of these genes can be used to explain the diversity in the root system adaptation to low P availability, recently observed in this species

Towards a TILLING platform for functional genomics in Piel de Sapo melons

Background The availability of genetic and genomic resources for melon has increased significantly, but functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis melons, but not for inodorus melons, the other main commercial group. Results A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1 mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point mutations were found for the seven gene targets, six of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the Phytoene desaturase gene, which is involved in carotenoid biosynthesis. Conclusions The TILLING approach was successful at providing new mutations in the genetic background of Piel de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic and breeding studies.González, M.; Xu, M.; Esteras Gómez, C.; Roig Montaner, MC.; Monforte Gilabert, AJ.; Troadec, C.; Pujol, M.... (2011). Towards a TILLING platform for functional genomics in Piel de sapo melons. BMC Research Notes. 4(289):289-299. doi:10.1186/1756-0500-4-289S2892994289The International Cucurbit Genomics Initiative (ICuGI). [ http://www.icugi.org ]González-Ibeas D, Blanca J, Roig C, González-To M, Picó B, Truniger V, Gómez P, Deleu W, Caño-Delgado A, Arús P, Nuez F, García-Mas J, Puigdomènech P, Aranda MA: MELOGEN: an EST database for melon functional genomics. BMC Genomics. 2007, 8: 306-10.1186/1471-2164-8-306.Fita A, Picó B, Monforte A, Nuez F: Genetics of Root System Architecture Using Near-isogenic Lines of Melon. J Am Soc Hortic Sci. 2008, 133: 448-458.Fernandez-Silva I, Eduardo I, Blanca J, Esteras C, Picó B, Nuez F, Arús P, Garcia-Mas J, Monforte AJ: Bin mapping of genomic and EST-derived SSRs in melon (Cucumis melo L.). Theor Appl Genet. 2008, 118: 139-150. 10.1007/s00122-008-0883-3.Deleu W, Esteras C, Roig C, González-To M, Fernández-Silva I, Blanca J, Aranda MA, Arús P, Nuez F, Monforte AJ, Picó MB, Garcia-Mas J: A set of EST-SNPs for map saturation and cultivar identification in melon. BMC Plant Biol. 2009, 9: 90-10.1186/1471-2229-9-90.Mascarell-Creus A, Cañizares J, Vilarrasa J, Mora-García S, Blanca J, González-Ibeas D, Saladié M, Roig C, Deleu W, Picó B, López-Bigas N, Aranda MA, Garcia-Mas J, Nuez F, Puigdomènech P, Caño-Delgado A: An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.). BMC Genomics. 2009, 10: 467-10.1186/1471-2164-10-467.Blanca JM, Cañizares J, Ziarsolo P, Esteras C, Mir G, Nuez F, Garcia-Mas J, Pico B: Melon transcriptome characterization. SSRs and SNPs discovery for high throughput genotyping across the species. Plant Genome. 2011, 4 (2): 118-131. 10.3835/plantgenome2011.01.0003.González VM, Benjak A, Hénaff EM, Mir G, Casacuberta JM, Garcia-Mas J, Puigdomènech P: Sequencing of 6.7 Mb of the melon genome using a BAC pooling strategy. BMC Plant Biology. 2010, 10: 246-10.1186/1471-2229-10-246.Moreno E, Obando JM, Dos-Santos N, Fernández-Trujillo JP, Monforte AJ, Garcia-Mas J: Candidate genes and QTLs for fruit ripening and softening in melon. Theor Appl Genet. 2007, 116: 589-602.Essafi A, Díaz-Pendón JA, Moriones E, Monforte AJ, Garcia-Mas J, Martín-Hernández AM: Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theor Appl Genet. 2009, 118: 275-284. 10.1007/s00122-008-0897-x.Comai L, Henikoff S: TILLING: practical single-nucleotide mutation discovery. Plant J. 2006, 45: 684-94. 10.1111/j.1365-313X.2006.02670.x.Cooper JL, Till BJ, Laport RG, Darlow MC, Kleffner JM, Jamai A, El-Mellouki T, Liu S, Ritchie R, Nielsen N, et al: TILLING to detect induced mutations in soybean. BMC Plant Biol. 2008, 8 (1): 9-10.1186/1471-2229-8-9.Dalmais M, Schmidt J, Le Signor C, Moussy F, Burstin J, Savois V, Aubert G, de Oliveira Y, Guichard C, Thompson R, Bendahmane A: UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biol. 2008, 9: R43-10.1186/gb-2008-9-2-r43.Dierking EC, Bilyeu KD: New sources of soybean meal and oil composition traits identified through TILLING. BMC Plant Biol. 2009, 9: 89-10.1186/1471-2229-9-89.Perry J, Brachmann A, Welham T, Binder A, Charpentier M, Groth M, Haage K, Markmann K, Wang TL, Parniske M: TILLING in Lotus japonicus identified large allelic series for symbiosis genes and revealed a bias in functionally defective ethyl methanesulfonate alleles toward glycine replacements. Plant Physiol. 2009, 151 (3): 1281-1291. 10.1104/pp.109.142190.Caldwell DG, McCallum N, Shaw P, Muehlbauer GJ, Marshall DF, Waugh R: A structured mutant population for forward and reverse genetics in Barley (Hordeum vulgare L.). Plant J. 2004, 40 (1): 143-150. 10.1111/j.1365-313X.2004.02190.x.Henikoff S, Bradley JT, Comai L: TILLING. Traditional mutagenesis meets functional genomics. Plant Physiol. 2004, 135: 630-636. 10.1104/pp.104.041061.Wu JL, Wu C, Lei C, Baraoidan M, Bordeos A, Madamba MR, Ramos-Pamplona M, Mauleon R, Portugal A, Ulat VJ, et al: Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics. Plant Mol Biol. 2005, 59 (1): 85-97. 10.1007/s11103-004-5112-0.Slade AJ, Fuerstenberg SI, Loeffler D, Steine MN, Facciotti D: A reverse genetic, nontransgenic approach to wheat crop improvement by TILLING. Nat Biotechnol. 2005, 23: 75-81. 10.1038/nbt1043.Till BJ, Cooper J, Tai TH, Colowit P, Greene EA, Henikoff S, Comai L: Discovery of chemically induced mutations in rice by TILLING. BMC Plant Biol. 2007, 7: 19-10.1186/1471-2229-7-19.Xin Z, Wang ML, Barkley NA, Burow G, Franks C, Pederson G, Burke J: Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population. BMC Plant Biol. 2008, 8: 103-10.1186/1471-2229-8-103.Dong C, Dalton-Morgan J, Vincent K, Sharp P: A modified TILLING method for wheat breeding. Plant Genome. 2009, 2: 39-47. 10.3835/plantgenome2008.10.0012.Sestili F, Botticella E, Bedo Z, Phillips A, Lafiandra D: Production of novel allelic variation for genes involved in starch biosynthesis through mutagenesis. Mol Breeding. 2010, 25: 145-154. 10.1007/s11032-009-9314-7.Watanabe S, Mizoguchi T, Aoki K, Kubo Y, Mori H, Imanishi S, Yamazaki Y, Shibata D, Ezura H: Ethylmethanesulfonate (EMS) mutagenesis of Solanum lycopersicum cv. Micro-Tom for large-scale mutant screens. Plant Biotech. 2007, 24: 33-38. 10.5511/plantbiotechnology.24.33.Elias R, Till BJ, Mba Ch, Al-Safadi B: Optimizing TILLING and Ecotilling techniques for potato (Solanum tuberosum L). BMC Res Notes. 2009, 2: 141-10.1186/1756-0500-2-141.Piron F, Nicolaı M, Minoıa S, Piednoir E, Moretti A, Salgues A, Zamir D, Caranta C, Bendahmane A: An induced mutation in tomato eIF4E leads to immunity to two Potyviruses. PLoS ONE. 2010, 5 (6): e11313-10.1371/journal.pone.0011313.Himelblau E, Gilchrist EJ, Buono K, Bizell C, Mentzer L, Vogelzang R, Osborn T, Amasino RM, Parkin IAP, Haughn : Forward and reverse genetics of papid cycling Brassica oleracea. Theor Appl Genet. 2009, 118: 953-961. 10.1007/s00122-008-0952-7.Stephenson P, Baker D, Girin T, Perez A, Amoah S, King GJ, Østergaard L: A rich TILLING resource for studying gene function in Brassica rapa. BMC Plant Biol. 2010, 10: 62-10.1186/1471-2229-10-62.Pitrat M: Melon (Cucumis melo L.). Handbook of Crop Breeding Vol I. Vegetables. Edited by: Prohens J, Nuez F. 2008, New York:Springer, 283-315.Dahmani-Mardas F, Troadec Ch, Boualem A, Leveque S, Alsadon AA, Aldoss AA, Dogimont C, Bendahman A: Engineering Melon Plants with Improved Fruit Shelf Life Using the TILLING Approach. PLoS ONE. 2010, 5: e15776-10.1371/journal.pone.0015776.Nieto C, Piron F, Dalmais M, Marco CF, Moriones E, Gómez-Guillamón ML, Truniger V, Gómez P, Garcia-Mas J, Aranda MA, Bendahmane A: EcoTILLING for the identification of allelic variants of melon eIF4E, a factor that controls virus susceptibility. BMC Plant Biol. 2007, 7: 34-10.1186/1471-2229-7-34.Qin G, Gu H, Ma L, Peng Y, Deng XW, Chen Z, Qu LJ: Disruption of phytoene desaturase gene results in albino and dwarf phenotypes in Arabidopsis by impairing chlorophyll, carotenoid, and gibberellin biosynthesis. Cell Res. 2007, 17: 471-482. 10.1038/cr.2007.40.Codons Optimized to Deliver Deleterious Lesions (CODDLe). [ http://www.proweb.org/input ]Lasserre E, Bouquin T, Hernández JA, Bull J, Pech JC, Balague C: Structure and expression of three genes encoding ACC oxidase homologs from melon (Cucumis melo L.). Mol Gen Genet. 1996, 251 (1): 81-90.Giovannoni JJ: Fruit ripening mutants yield insights into ripening control. Curr Opin Plant Biol. 2007, 10: 1-7. 10.1016/j.pbi.2006.11.012.Davuluri GR, van Tuinen A, Mustilli AC, Manfredonia A, Newman R, Burgess D, Brummell DA, King SR, Palys J, Uhlig J, Pennings HMJ, Bowler C: Manipulation of DET1 expression in tomato results in photomorphogenic phenotypes caused by post-transcriptional gene silencing. Plant J. 2004, 40: 344-354. 10.1111/j.1365-313X.2004.02218.x.Wei S, Li X, Gruber MI, Li R, Zhou R, Zebarjadi A, Hannoufa A: RNAi-mediated suppression of DET1 alters the levels of carotenoids and sinapate esters in seeds of Brassica napus. J Agric Food Chem. 2009, 57 (12): 5326-5333. 10.1021/jf803983w.Wang TW, Zhang CG, Wu W, Nowack LM, Madey E, Thompson JE: Antisense suppression of deoxyhypusine synthase in tomato delays fruit softening and alters growth and development DHS mediates the first of two sequential enzymatic reactions that activate eukaryotic translation initiation factor-5A. Plant Physiol. 2005, 138: 1372-1382. 10.1104/pp.105.060194.Ng PC, Henikoff S: SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31 (13): 3812-3814. 10.1093/nar/gkg509.Guzman P, Ecker JR: Exploiting the triple response of Arabidopsis to identify ethylene-related mutants. The Plant Cell. 1990, 2: 513-523.Henikoff S, Comai L: Single-nucleotide mutations for plant functional genomics. Ann Rev Plant Biol. 2003, 54: 375-401. 10.1146/annurev.arplant.54.031902.135009.Greene EA, Codomo CA, Taylor NE, Henikoff JG, Till BJ, Reynolds SH, Enns LC, Burtner C, Johnson JE, Odden AR, et al: Spectrum of chemically induced mutations from a large-scale reverse genetic screen in Arabidopsis. Genetics. 2003, 164 (2): 731-740.Britt AB: DNA damage and repair in plants. Annu Rev Plant Physiol Plant Mol Biol. 1996, 47: 75-100. 10.1146/annurev.arplant.47.1.75.Truniger V, Nieto C, González-Ibeas D, Aranda M: Mechanism of plant eIF4E-mediated resistance against a Carmovirus (Tombusviridae): cap-independent translation of a viral RNA controlled in cis by an (a)virulence determinant. Plant J. 2008, 56 (5): 716-727. 10.1111/j.1365-313X.2008.03630.x.Gao Z, Johansen E, Eyers S, Thomas CL, Ellis THN, Maule AJ: The potyvirus recessive resistance gene, sbm1, identifies a novel role for translation initiation factor eIF4E in cell-to-cell trafficking. Plant J. 2004, 40 (3): 376-385. 10.1111/j.1365-313X.2004.02215.x.Kang BC, Yeam I, Frantz JD, Murphy JF, Jahn MM: The pvr1 locus in Capsicum encodes a translation initiation factor eIF4E that interacts with Tobacco etch virus VPg. Plant J. 2005, 42 (3): 392-405. 10.1111/j.1365-313X.2005.02381.x.Ruffel S, Gallois J, Lesage M, Caranta C: The recessive potyvirus resistance gene pot-1 is the tomato orthologue of the pepper pvr2-eiF4 genes. Mol Genet Genom. 2005, 274 (4): 346-353. 10.1007/s00438-005-0003-x.Nicaise V, German-Retana S, Sanjuán R, Dubrana MP, Mazier M, Maisonneuve B, Candresse T, Caranta C, LeGall O: The Eukaryotic Translation Initiation Factor 4E Controls Lettuce Susceptibility to the Potyvirus Lettuce mosaic virus1. Plant Physiol. 2003, 132: 1272-1282. 10.1104/pp.102.017855.Esteras C, Pascual L, Saladie M, Dogimont C, Garcia-Mas J, Nuez F, Picó B: Use of Ecotilling to identify natural allelic variants of melon candidate genes involved in fruit ripening. Proceedings Plant GEM8 Lisbon. 2009Levin I, Frankel P, Gilboa N, Tanny S, Lalazar A: The tomato dark green mutation is a novel allele of the tomato homolog of the DEETIOLATED1 gene. Theor Appl Genet. 2003, 106: 454-460.Kolotilin I, Koltai H, Tadmor Y, Bar-Or C, Reuveni M, Meir A, Nahon S, Shlomo S, Chen L, I Levin: Transcriptional profiling of high pigment-2dg tomato mutant links early fruit plastid biogenesis with its overproduction of phytonutrients. Plant Physiol. 2007, 145: 389-401. 10.1104/pp.107.102962

Global Taxonomic Diversity of Anomodonts (Tetrapoda, Therapsida) and the Terrestrial Rock Record Across the Permian-Triassic Boundary

The end-Permian biotic crisis (∼252.5 Ma) represents the most severe extinction event in Earth's history. This paper investigates diversity patterns in Anomodontia, an extinct group of therapsid synapsids (‘mammal-like reptiles’), through time and in particular across this event. As herbivores and the dominant terrestrial tetrapods of their time, anomodonts play a central role in assessing the impact of the end-Permian extinction on terrestrial ecosystems. Taxonomic diversity analysis reveals that anomodonts experienced three distinct phases of diversification interrupted by the same number of extinctions, i.e. an end-Guadalupian, an end-Permian, and a mid-Triassic extinction. A positive correlation between the number of taxa and the number of formations per time interval shows that anomodont diversity is biased by the Permian-Triassic terrestrial rock record. Normalized diversity curves indicate that anomodont richness continuously declines from the Middle Permian to the Late Triassic, but also reveals all three extinction events. Taxonomic rates (origination and extinction) indicate that the end-Guadalupian and end-Permian extinctions were driven by increased rates of extinction as well as low origination rates. However, this pattern is not evident at the final decline of anomodont diversity during the Middle Triassic. Therefore, it remains unclear whether the Middle Triassic extinction represents a gradual or abrupt event that is unique to anomodonts or more common among terrestrial tetrapods. The end-Permian extinction represents the most distinct event in terms of decline in anomodont richness and turnover rates

Derivation of risk based wipe surface screening levels for industrial scenarios

The environmental characterization of building interiors and other surfaces has generally been performed with wipe-sampling because it is a non-destructive technique. There is no consensus, however, as to the interpretation of the results of wipe-sampling. Specifically, there is not a standardized method to determine if chemicals found at sampled levels pose a threat to human health. A methodology was developed, based on acceptable health risk levels, to derive screening levels for evaluating wipe-sampling results pertaining to industrial scenarios. The methodology was based on the United States Environmental Protection Agency (USEPA) Region IX Preliminary Remediation Goal (PRG) approach; a multi-exposure methodology commonly used for evaluating soil concentrations. PRGs are the USEPA determined health based goals for soil preliminary remediation efforts. Probabilistic techniques were used to conduct a sensitivity analysis of the methodology to determine which variables drive the ultimate screening levels. Discrete values were then selected based on standard industrial scenarios common to the US Army. The wipe surface screening levels reported are for use as preliminary guidelines which help to determine whether further sampling or cleanup are necessary. The levels are not meant as cleanup or compliance criteria

Inheritance of resistance to downy mildew (Pseudoperonospora cubensis) in muskmelon (Cucumis melo). II. Generation means analysis of 5 genitors

The contribution of the generation means analysis described by Mather and Jinks to the genetic analysis of resistance to downy mildew caused by Pseudoperonospora cubensis in muskmelon (Cucumis melo L) was examined. Five melon cultivars with high to moderate levels of resistance to P cubensis were crossed with 3 susceptible cultivars to develop F1, F2 and back-cross generations. Weighted least-square regression analysis indicated that the majority of the variation could be explained by additive effects (84-99%); epistasis effects are the second-most important effects (explaining at most 8%). Dominance ratio, heritability and number of effective factors could be estimated in the crosses that did not exhibit epistasis. All these genetic parameters showed an important variation among the 15 crosses studied. Analysis of the results led to the proposal of a breeding strategy for the resistance character.Hérédité de la résistance au mildiou (Pseudoperonospora cubensis) chez le melon (Cucumis melo). II. Analyse métrique de 5 géniteurs. L'apport de l'analyse métrique (Mather et Jinks, 1971) dans l'étude de la génétique de la résistance du melon (Cucumis melo) au mildiou (Pseudoperonospora cubensis) est évalué. Cinq cultivars de melon, avec des niveaux de résistance modéré à élevé, ont été croisés à 3 variétés sensibles : les générations F1, F2 et les back-cross par les 2 parents ont été obtenues. La régression pondérée des moyennes des différentes générations sur un modèle génétique théorique indique que la majorité de la variation est expliquée par les effets additifs (81-99%). Les effets d'épistasie sont la deuxième plus importante cause de variation (expliquant au maximum 8% du total). Les ratios de dominance, les héritabilités et le nombre de facteurs effectifs ont pu être estimés dans les croisements ne montrant pas d'effets épistatiques. Tous ces paramètres génétiques sont très variables entre les 15 croisements étudiés. L'analyse des résultats conduit à l'élaboration d'une stratégie de sélection pour le caractère de résistance considéré

Inheritance of resistance to downy mildew (Pseudoperonospora cubensis) in muskmelon (Cucumis melo). II : generation means analysis of 5 genitors

The contribution of the generation means analysis described by Mather and Jinks to the genetic analysis of resistance to downy mildew caused by Pseudoperonospora cubensis in muskmelon (Cucumis melo L) was examined. Five melon cultivars with high to moderate levels of resistance to P cubensis were crossed with 3 susceptible cultivars to develop F1, F2 and back-cross generations. Weighted least-square regression analysis indicated that the majority of the variation could be explained by additive effects (84-99%); epistasis effects are the second-most important effects (explaining at most 8%). Dominance ratio, heritability and number of effective factors could be estimated in the crosses that did not exhibit epistasis. All these genetic parameters showed an important variation among the 15 crosses studied. Analysis of the results led to the proposal of a breeding strategy for the resistance character.L’apport de l’analyse métrique (Mather et Jinks, 1971) dans l’étude de la génétique de la résistance du melon (Cucumis melo) au mildiou (Pseudoperonospora cubensis) est évalué. Cinq cultivars de melon, avec des niveaux de résistance modéré à élevé, ont été croisés à 3 variétés sensibles : les générations F1, F2 et les back-cross par les 2 parents ont été obtenues. La régression pondérée des moyennes des différentes générations sur un modèle génétique théorique indique que la majorité de la variation est expliquée par les effets additifs (81-99%). Les effets d’épistasie sont la deuxième plus importante cause de variation (expliquant au maximum 8% du total). Les ratios de dominance, les héritabilités et le nombre de facteurs effectifs ont pu être estimés dans les croisements ne montrant pas d’effets épistatiques. Tous ces paramètres génétiques sont très variables entre les 15 croisements étudiés. L’analyse des résultats conduit à l’élaboration d’une stratégie de sélection pour le caractère de résistance considéré

Génétique et création de nouvelles variétés de légumes

National audienc