Differences in breast cancer risk after benign breast disease by type of screening diagnosis

Neoplàsies de mama; Detecció precoç del càncer; Factors de riscNeoplasias de mama; Detección precoz del cáncer; Factores de riesgoBreast neoplasms; Early cancer detection; Risk factorsIntroduction: We aimed to assess differences in breast cancer risk across benign breast disease diagnosed at prevalent or incident screens. Materials and methods: We conducted a retrospective cohort study with data from 629,087 women participating in a long-standing population-based breast cancer screening program in Spain. Each benign breast disease was classified as non-proliferative, proliferative without atypia, or roliferative with atypia, and whether it was diagnosed in a prevalent or incident screen. We used partly conditional Cox hazard regression to estimate the adjusted hazard ratios of the risk of breast cancer. Results: Compared with women without benign breast disease, the risk of breast cancer was significantly higher (p-value ¼ 0.005) in women with benign breast disease diagnosed in an incident screen (aHR, 2.67; 95%CI: 2.24e3.19) than in those with benign breast disease diagnosed in a prevalent screen (aHR, 1.87; 95%CI: 1.57e2.24). The highest risk was found in women with a proliferative benign breast disease with atypia (aHR, 4.35; 95%CI: 2.09e9.08, and 3.35; 95%CI: 1.51e7.40 for those diagnosed at incident and prevalent screens, respectively), while the lowest was found in women with non-proliferative benign breast disease (aHR, 2.39; 95%CI: 1.95e2.93, and 1.63; 95%CI: 1.32e2.02 for those diagnosed at incident and prevalent screens, respectively). Conclusion: Our study showed that the risk of breast cancer conferred by a benign breast disease differed according to type of screen (prevalent or incident). To our knowledge, this is the first study to analyse the impact of the screening type on benign breast disease prognosisThis study was supported by grants from Instituto de Salud Carlos III FEDER (grant numbers: PI15/00098 and PI17/00047), and by the Research Network on Health Services in Chronic Diseases (RD12/0001/0015

First presence of Macaca sylvanus at the late Early Pleistocene of Barranc de la Boella (La Mina locality, Francolí Basin, NE Iberia)

This research has been funded by Ministerio de Ciencia e Innovación, PID2021-122356NB-I00. D.F. is supported by the Ayuda del Programa de Formación de Profesorado Universitario (FPU20/03389) and is a Ph.D. student at the Programa de Doctorado en Biología at the Universidad Complutense de Madrid. A.E. is supported by H2020-MSCA-IF project No. 891529 (3DFOSSILDIET). A.P. is supported by the LATEUROPE project (Grant agreement ID 101052653) that has received funding from the European Research Council (ERC) under the European Union’s HORIZON1.1 research program. The Barranc de la Boella fieldwork is supported by the Ajuntament de la Canonja and Departament de Cultura of Generalitat de Catalunya (ARQ001SOL-186-2022). The Institut Català de Paleoecologia Humana i Evolució Social (IPHESCERCA) has received financial support from the Spanish Ministry of Science and Innovation through the ‘María de Maeztu’ program for Units of Excellence (CEX2019-000945-M).This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 89152

A reevaluation of the key factors that influence tomato fruit softening and integrity

The softening of fleshy fruits, such as tomato (Solanum lycopersicum), during ripening is generally reported to result principally from disassembly of the primary cell wall and middle lamella. However, unsuccessful attempts to prolong fruit firmness by suppressing the expression of a range of wall-modifying proteins in transgenic tomato fruits do not support such a simple model. 'Delayed Fruit Deterioration' (DFD) is a previously unreported tomato cultivar that provides a unique opportunity to assess the contribution of wall metabolism to fruit firmness, since DFD fruits exhibit minimal softening but undergo otherwise normal ripening, unlike all known nonsoftening tomato mutants reported to date. Wall disassembly, reduced intercellular adhesion, and the expression of genes associated with wall degradation were similar in DFD fruit and those of the normally softening 'Ailsa Craig'. However, ripening DFD fruit showed minimal transpirational water loss and substantially elevated cellular turgor. This allowed an evaluation of the relative contribution and timing of wall disassembly and water loss to fruit softening, which suggested that both processes have a critical influence. Biochemical and biomechanical analyses identified several unusual features of DFD cuticles and the data indicate that, as with wall metabolism, changes in cuticle composition and architecture are an integral and regulated part of the ripening program. A model is proposed in which the cuticle affects the softening of intact tomato fruit both directly, by providing a physical support, and indirectly, by regulating water status

Unraveling a Neanderthal palimpsest from a zooarcheological and taphonomic perspective

Practically all archeological assemblages are palimpsests. In spite of the high temporal resolution of Abric Romaní site, level O, dated to around 55 ka, is not an exception. This paper focuses on a zooarcheological and taphonomic analysis of this level, paying special attention to spatial and temporal approaches. The main goal is to unravel the palimpsest at the finest possible level by using different methods and techniques, such as archeostratigraphy, anatomical and taxonomical identification, taphonomic analysis, faunal refits and tooth wear analysis. The results obtained are compared to ethnoarcheological data so as to interpret site structure. In addition, activities carried out over different time spans (from individual episodes to long-term behaviors) are detected, and their spatial extent is explored, allowing to do inferences on settlement dynamics. This leads us to discuss the temporal and spatial scales over which Neanderthals carried out different activities within the site, and how they can be studied through the archeological record

Xyloglucan endotransglucosylase and cell wall extensibility

Transgenic tomato hypocotyls with altered levels of an XTH gene were used to study how XET activity could affect the hypocotyl growth and cell wall extensibility. Transgenic hypocotyls showed significant over-expression (line 13) or co-suppression (line 33) of the SlXTH1 in comparison with the wild type, with these results being correlated with the results on specific soluble XET activity, suggesting that SlXTH1 translates mainly for a soluble XET isoenzyme. A relationship between XET activity and cell wall extensibility was found, and the highest total extensibility was located in the apical hypocotyl segment of the over-expressing SlXTH1 line, where the XET-specific activity and hypocotyl growth were also highest compared with the wild line

Comparative transcriptional profiling analysis of developing melon (Cucumis melo L.) fruit from climacteric and non-climacteric varieties

[EN] Background: In climacteric fruit-bearing species, the onset of fruit ripening is marked by a transient rise in respiration rate and autocatalytic ethylene production, followed by rapid deterioration in fruit quality. In non-climacteric species, there is no increase in respiration or ethylene production at the beginning or during fruit ripening. Melon is unusual in having climacteric and non-climacteric varieties, providing an interesting model system to compare both ripening types. Transcriptomic analysis of developing melon fruits from Védrantais and Dulce (climacteric) and Piel de sapo and PI 161375 (non-climacteric) varieties was performed to understand the molecular mechanisms that differentiate the two fruit ripening types. Results: Fruits were harvested at 15, 25, 35 days after pollination and at fruit maturity. Transcript profiling was performed using an oligo-based microarray with 75 K probes. Genes linked to characteristic traits of fruit ripening were differentially expressed between climacteric and non-climacteric types, as well as several transcription factor genes and genes encoding enzymes involved in sucrose catabolism. The expression patterns of some genes in PI 161375 fruits were either intermediate between. Piel de sapo and the climacteric varieties, or more similar to the latter. PI 161375 fruits also accumulated some carotenoids, a characteristic trait of climacteric varieties. Conclusions: Simultaneous changes in transcript abundance indicate that there is coordinated reprogramming of gene expression during fruit development and at the onset of ripening in both climacteric and non-climacteric fruits. The expression patterns of genes related to ethylene metabolism, carotenoid accumulation, cell wall integrity and transcriptional regulation varied between genotypes and was consistent with the differences in their fruit ripening characteristics. There were differences between climacteric and non-climacteric varieties in the expression of genes related to sugar metabolism suggesting that they may be potential determinants of sucrose content and post-harvest stability of sucrose levels in fruit. Several transcription factor genes were also identified that were differentially expressed in both types, implicating them in regulation of ripening behaviour. The intermediate nature of PI 161375 suggested that classification of melon fruit ripening behaviour into just two distinct types is an over-simplification, and that in reality there is a continuous spectrum of fruit ripening behaviourWe wish to thank Marta Casado for assistance with qRT-PCR analysis, Anna Orozco and Rosa Rodriguez for help with carotenoid measurements, Kostas Alexiou for uploading the microarray data at GEO and Walter Sanseverino for obtaining the correspondence of the microarray contigs with the melon annotated genes. We thank Beatrice Encke and Nicole Krohn for technical help with the sugar analysis. We also thank Laura Pascual for a critical reading of the manuscript. MSa was supported by a JAE-Doc grant from the Spanish Ministry of Science. This work was supported by the Spanish Ministry of Science and Innovation (MICINN project GEN2006-27773-C2-1-E to JGM) and the German Federal Ministry of Education and Research (BMBF project 0313987 to MSt) within the framework of the EU Framework 6 ERA-NET Plant Genomics programme.Saladie, M.; Cañizares Sales, J.; Michael A. Phillips; Rodriguez Concepcion, M.; Larrigaudière, C.; Gibon, Y.; Stitt, M.... (2015). Comparative transcriptional profiling analysis of developing melon (Cucumis melo L.) fruit from climacteric and non-climacteric varieties. BMC Genomics. 16(440):1-20. https://doi.org/10.1186/s12864-015-1649-3S12016440McMurchie EJ, McGlasson WB, Eaks IL. Treatment of fruit with propylene gives information about the biogenesis of ethylene. Nature. 1972;237:235–6.Giovannoni JJ. Genetic regulation of fruit development and ripening. Plant Cell. 2004;16:S170–80.Yamaguchi M, Hughes DL, Yabumoto K, Jennings WG. Quality of cantaloupe muskmelons: Variability and attributes. Scientia Hort. 1977;6:59–70.Seymour GB, McGlasson WB. Melons. In: Seymour GB, Taylor JE, Tucker GA, editors. Biochemistry of fruit ripening. London: Chapman & Hall; 1993. p. 273-290.Pech JC, Balague C, Latché A, Bouzayen M. Post-harvest physiology of climacteric fruits: recent developments in the biosynthesis and action of ethylene. Sci Aliments. 1994;14:3–15.Latché A, Ayub RA, Martinez G, Guis M, Ben Amor M, Rombaldi CV, et al. Biosynthèse et mode d’action de l’hormone végétale éthylène. Fruits. 1995;50:379–96.Moore S, Payton P, Wright M, Tanksley S, Giovannoni J. Utilization of tomato microarrays for comparative gene expression analysis in the Solanaceae. J Exp Bot. 2005;56:2885–95.Giovannoni JJ. Fruit ripening mutants yield insights into ripening control. Curr Opin Plant Biol. 2007;10:283–9.Saladié M, Rose JKC, Cosgrove DJ, Catalá C. Characterization of a new xyloglucan endotransglucosylase/hydrolase (XTH) from ripening tomato fruit and implications for the diverse modes of enzymic action. Plant J. 2006;47:282–95.Stepanova AN, Alonso JM. Ethylene signalling and response: where different regulatory modules meet. Curr Opin Plant Sci. 2009;12:548–55.Alexander L, Grierson D. Ethylene biosynthesis and action in tomato: a model for climacteric fruit ripening. J Exp Bot. 2002;53:2039–55.Klee HJ. Ethylene signal transduction. Moving beyond Arabidopsis. Plant Physiol. 2004;135:660–7.Adams-Phillips L, Barry C, Giovannoni J. Signal transduction systems regulating fruit ripening. Trends Plant Sci. 2004;9:331–8.Vrebalov J, Ruezinsky D, Padmanabhan V, White R, Medrano D, Drake R, et al. A MADS-box gene necessary for fruit ripening at the tomato ripening-inhibitor (rin) locus. Science. 2002;296:343–6.Giovannoni JJ, Tanksley S, Vrebalov J, Noensie F. NOR gene compositions and methods for use thereof. US Patent 6762347_B1. July 13, 2004.Manning K, Tor M, Poole M, Hong Y, Thompson AJ, King GJ, et al. A naturally occurring epigenetic mutation in a gene encoding an SBP-box transcription factor inhibits tomato fruit ripening. Nat Genet. 2006;38:948–52.Itkin M, Seybold H, Breitel D, Rogachev I, Meir S, Aharoni A. TOMATO AGAMOUS-LIKE 1 is a component of the fruit ripening regulatory network. Plant J. 2009;60:1081–95.Lin Z, Hong Y, Yin M, Li C, Zhang K, Grierson D. A tomato HD-Zip homeobox protein, LeHB-1, plays an important role in floral organogenesis and ripening. Plant J. 2008;55:301–10.Chung M-Y, Vrebalov J, Alba R, Lee JM, McQuinn R, Chung J-D, et al. A tomato (Solanum lycopersicum) APETALA2/ERF gene, SlAP2a, is a negative regulator of fruit ripening. Plant J. 2011;64:936–47.Karlova R, Rosin FM, Busscher-Lange J, Parapunova V, Do PT, Fernie AR, et al. Transcriptome and metabolite profiling show that APETALA2a is a major regulator of tomato fruit ripening. Plant Cell. 2011;23:923–41.Seymour GB, Chapman NH, Chew BL, Rose JKC. Regulation of ripening and opportunities for control in tomato and other fruits. Plant Biotechnol J. 2013;11:269–78.Klee HJ, Giovannoni JJ. Genetics and control of tomato fruit ripening and quality attributes. Annu Rev Genet. 2011;45:41–59.Bemer M, Karlova R, Ballester AR, Tikunov YM, Bovy AG, Wolters-Arts M, et al. The tomato FRUITFUL homologs TDR4/FUL1 and MBP7/FUL2 regulate ethylene-Independent aspects of fruit ripening. Plant Cell. 2012;24:4437–51.Fujisawa M, Shima Y, Higuchi N, Nakano T, Koyama Y, Kasumi T, et al. Direct targets of the tomato-ripening regulator RIN identified by transcriptome and chromatin immunoprecipitation analyses. Planta. 2012;235:1107–22.Kumar R, Sharma MK, Kapoor S, Tyagi AK, Sharma A. Transcriptome analysis of rin mutant fruit and in silico analysis of promoters of differentially regulated genes provides insight into LeMADS-RIN-regulated ethylene-dependent as well as ethylene-independent aspects of ripening in tomato. Mol Genet Genom. 2012;287:189–203.Zhong S, Fei Z, Chen Y-R, Zheng Y, Huang M, Vrebalov J, et al. Single-base resolution methylomes of tomato fruit development reveal epigenome modifications associated with ripening. Nat Biotechnol. 2013;31:154–9.Wilkinson JQ, Lanahan MB, Conner TW, Klee HJ. Identification of mRNAs with enhanced expression in ripening strawberry fruit using polymerase chain reaction differential display. Plant Mol Biol. 1995;27:1097–108.Manning K. Isolation of a set of ripening-related genes from strawberry: Their identification and possible relationship to fruit quality traits. Planta. 1998;205:622–31.Aharoni A, Keizer LC, Bouwmeester HJ, Sun Z, Alvarez-Huerta M, Verhoeven HA, et al. Identification of the SAAT gene involved in strawberry flavor biogenesis by use of DNA microarrays. Plant Cell. 2000;12:647–62.Osorio S, Alba R, Nikoloski Z, Kochevenko A, Fernie AR, Giovannoni JJ. Integrative comparative analyses of transcript and metabolite profiles from pepper and tomato ripening and development stages uncovers species-specific patterns of network regulatory behavior. Plant Physiol. 2012;159:1713–29.Ezura H, Owino WO. Melon ripening and ethylene. Plant Sci. 2008;175:121–9.Pech JC, Bouzayen M, Latché A. Climacteric fruit ripening: ethylene-dependent and independent regulation of ripening pathways in melon fruit. Plant Sci. 2008;175:114–20.Vegas J, Garcia-Mas J, Monforte AJ. Interaction between QTLs induces an advance in ethylene biosynthesis during melon fruit ripening. Theor Appl Genet. 2013;126:1531–44.Lyons JM, Pratt HK, McGlasson WB. Ethylene production, respiration, and internal gas concentrations in cantaloupe fruits at various stages of maturity. Plant Physiol. 1962;37:31–26.Hadfield KA, Dang T, Guis M, Pech JC, Bouzayen M, Bennett AB. Characterization of ripening-regulated cDNAs and their expression in ethylene-suppressed Charentais melon fruit. Plant Physiol. 2000;122:977–83.Ayub R, Guis M, Ben Amor M, Gillot L, Roustan JP, Latché A, et al. Expression of ACC oxidase antisense gene inhibits ripening of cantaloupe melon fruits. Nat Biotechnol. 1996;14:862–6.Monforte AJ, Oliver M, Gonzalo MJ, Alvarez JM, Dolcet-Sanjuan R, Arus P. Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.). Theor Appl Genet. 2004;108:750–8.Cuevas HE, Staub JE, Simon PW, Zalapa JE. A consensus linkage map identifies genomic regions controlling fruit maturity and beta-carotene-associated flesh color in melon (Cucumis melo L.). Theor Appl Genet. 2009;119:741–56.Bian W, Barsan C, Egea I, Purgatto E, Chervin C, Zouine M, et al. Metabolic and molecular events occurring during chromoplast biogenesis. J Bot. 2011;10:1–13.Pratt HK, Goeschl JD, Martin FW. Fruit growth and development, ripening, and role of ethylene in honey dew muskmelon. J Am Soc Hortic Sci. 1977;102:203–10.Lester GE, Dunlap JR. Physiological-changes during development and ripening of perlita muskmelon fruits. Sci Hortic. 1985;26:323–31.Rose JKC, Hadfield KA, Labavitch JM, Bennett AB. Temporal sequence of cell wall disassembly in rapidly ripening melon fruit. Plant Physiol. 1998;117:345–61.Nishiyama K, Guis M, Rose JK, Kubo Y, Bennett KA, Wangjin L, et al. Ethylene regulation of fruit softening and cell wall disassembly in Charentais melon. J Exp Bot. 2007;58:1281–90.Portnoy V, Diber A, Pollock S, Karchi H, Lev S, Tzuri G, et al. Use of non-normalized, non-amplified cDNA for 454-based RNA sequencing of fleshy melon fruit. Plant Genome. 2011;4:1.Dai N, Cohen S, Portnoy V, Tzuri G, Harel-Beja R, Pompan-Lotan M, et al. Metabolism of soluble sugars in developing melon fruit: a global transcriptional view of the metabolic transition to sucrose accumulation. Plant Mol Biol. 2011;76:1–18.Corbacho J, Romojaro F, Pech JC, Latché A, Gomez-Jimenez MC. Transcriptomic events involved in melon mature-fruit abscission comprise the sequential induction of cell-wall degrading genes coupled to a stimulation of endo and exocytosis. PLoS One. 2013;8:e58363.Mascarell-Creus A, Cañizares J, Vilarrasa-Blasi J, Mora-García S, Blanca J, Gonzalez-Ibeas D, et al. 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:e467.Garcia-Mas J, Benjak A, Sanseverino W, Bourgeois M, Mir G, Gonzalez VM, et al. The genome of melon (Cucumis melo L.). Proc Natl Acad Sci U S A. 2012;109:11872–7.Gonzalez-Ibeas D, Cañizares J, Aranda MA. Microarray analysis shows that recessive resistance to Watermelon mosaic virus in melon is associated with the induction of defense response genes. Mol Plant Microbe Interact. 2012;25:107–18.Roig C, Fita A, Ríos G, Hammond JP, Nuez F, Picó B. Root transcriptional responses of two melon genotypes with contrasting resistance to Monosporascus cannonballus (Pollack et Uecker) infection. BMC Genomics. 2012;13:601–12.Conesa A, Nueda MJ, Ferrer A, Talón M. MaSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments. Bioinformatics. 2006;22:1096–102.Al-Shahrour F, Díaz-Uriarte R, Dopazo J. FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics. 2004;20:578–80.Pilati S, Perazzolli M, Malossini A, Cestaro A, Demattè L, Fontana P, et al. Genome-wide transcriptional analysis of grapevine berry ripening reveals a set of genes similarly modulated during three seasons and the occurrence of an oxidative burst at vèraison. BMC Genomics. 2007;8:428.Miki T, Yamamoto M, Nakagawa H, Ogura N, Mori H, Imaseki H, et al. Nucleotide sequence of a cDNA for 1-aminocyclopropane-1-carboxylate synthase from melon fruits. Plant Physiol. 1995;107:297–8.Yamamoto M, Miki T, Ishiki Y, Fujinami K, Yanagisawa Y, Nakagawa H, et al. The synthesis of ethylene in melon fruit during the early stage of ripening. Plant Cell Physiol. 1995;36:591–59.Lehman A, Black R, Ecker JR. HOOKLESS1, an ethylene response gene, is required for differential cell elongation in the Arabidopsis hypocotyl. Cell. 1996;85:183–94.Elitzur T, Vrebalov J, Giovannoni JJ, Goldschmidt EE, Friedman H. The regulation of MADS-box gene expression during ripening of banana and their regulatory interaction with ethylene. J Exp Bot. 2010;61(5):1523–35.Yang Y, Wu Y, Pirrello J, Regad F, Bouzayen M, Deng W, et al. Silencing Sl-EBF1 and Sl-EBF2 expression causes constitutive ethylene response phenotype, accelerated plant senescence, and fruit ripening in tomato. J Exp Bot. 2010;61(3):697–708.Tanaka R, Oster U, Kruse E, Rudiger W, Grimm B. Reduced activity of geranylgeranyl reductase leads to loss of chlorophyll and tocopherol and to partially geranylgeranylated chlorophyll in transgenic tobacco plants expressing antisense RNA for geranylgeranyl reductase. Plant Physiol. 1999;120:695–704.Kim J, DellaPenna D. Defining the primary route for lutein synthesis in plants: the role of Arabidopsis carotenoid beta-ring hydroxylase CYP97A3. Proc Natl Acad Sci U S A. 2006;103:3474–9.Welsch R, Maass D, Voegel T, Dellapenna D, Beyer P. Transcription factor RAP2.2 and its interacting partner SINAT2: stable elements in the carotenogenesis of Arabidopsis leaves. Plant Physiol. 2007;145:1073–85.Neta-Sharir I, Isaacson T, Lurie S, Weiss D. Dual role for tomato heat shock protein 21: protecting photosystem II from oxidative stress and promoting color changes during fruit maturation. Plant Cell. 2005;17:1829–38.Li L, Paolillo DJ, Parthasarathy MV, Dimuzio EM, Garvin DF. A novel gene mutation that confers abnormal patterns of beta-carotene accumulation in cauliflower (Brassica oleracea var. botrytis). Plant J. 2001;26:59–67.Lu S, Van Eck J, Zhou X, Lopez AB, Halloran DM, Cosman KM, et al. The cauliflower Or gene encodes a DnaJ cysteine-rich domain-containing protein that mediates high levels of beta-carotene accumulation. Plant Cell. 2006;18:3594–605.Akhtar MS, Goldschmidt EE, John I, Rodoni S, Matile P, Grierson D. Altered patterns of senescence and ripening in gf, a stay-green mutant of tomato. J Exp Bot. 1999;50(336):1115–22.Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, et al. TM4: a free, open-source system for microarray data management and analysis. Biotechniques. 2003;34:374–8.Lohse M, Nunes-Nesi A, Krüger P, Nagel A, Hannemann J, Giorgi FM, et al. Robin: an intuitive wizard application for R-based expression microarray quality assessment and analysis. Plant Physiol. 2010;153:642–51.Thimm O, Bläsing O, Gibon Y, Nagel A, Meyer S, Krüger P, et al. MapMan: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J. 2004;37:914–39.Usadel B, Poree F, Nagel A, Lohse M, Czedik-Eysenberg A, Stitt M. A guide to using MapMan to visualize and compare omics data in plants: a case study in the crop species, maize. Plant Cell Environ. 2009;32:1211–29.Costa F, Alba R, Schouten H, Soglio V, Gianfranceschi L, Serra S, et al. Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening. BMC Plant Biol. 2010;10:229.Zhang C, Yu X, Ayre BG, Turgeon R. The origin and composition of cucurbit “phloem” exudate. Plant Physiol. 2012;158:1873–82.Rose JKC, Saladié M, Catalá C. The plot thickens: new perspectives of primary cell wall modification. Current Opin Plant Biol. 2004;7:296–301.Manning K. Changes in gene-expression during strawberry fruit ripening and their regulation by auxin. Planta. 1994;194:62–8.Saladié M, Wright LP, Garcia-Mas J, Rodriguez-Concepcion M, Phillips MA. The 2-C-methylerithritol 4-phosphate pathway in melon is regulated by specialized isoforms for the first and last steps. J Exp Bot. 2014;65:5077–92.Périn C, Gomez-Jimenez M, Hagen L, Dogimont C, Pech JC, Latché A, et al. Molecular and genetic characterization of a non-climacteric phenotype in melon reveals two loci conferring altered ethylene response in fruit. Plant Physiol. 2002;129:300–9.Eduardo I, Arús P, Monforte AJ. Development of a genomic library of near isogenic lines (NILs) in melon (Cucumis melo L.) from the exotic accession PI161375. Theor Appl Genet. 2005;112:139–48.Stitt M, McLilley R, Gerhardt R, Heldt HW. Metabolite levels in specific cells and subcellular compartments of plant leaves. Meth Enzymol. 1989;174:518–52.Ibdah M, Azulay Y, Portnoy V, Wasserman B, Bar E, Meir A, et al. Functional characterization of CmCCD1, a carotenoid cleavage dioxygenase from melon. Phytochemistry. 2006;67:1579–89.Rodriguez-Concepcion M, Fores O, Martinez-Garcia JF, Gonzalez V, Phillips MA, Ferrer A, et al. Distinct light-mediated pathways regulate the biosynthesis and exchange of isoprenoid precursors during Arabidopsis seedling development. Plant Cell. 2004;16:144–56.Fraser PD, Pinto MES, Holloway DE, Bramley PM. Application of high-performance liquid chromatography with photodiode array detection to the metabolic profiling of plant isoprenoids. Plant J. 2000;24:551–8.Burns J, Fraser PD, Bramley PM. Identification and quantification of carotenoids, tocopherols and chlorophylls in commonly consumed fruits and vegetables. Phytochemistry. 2003;62:939–47.Taylor KL, Brackenridge AE, Vivier MA, Oberholster A. High-performance liquid chromatography profiling of the major carotenoids in Arabidopsis thaliana leaf tissue. J Chromatogr A. 2006;1121:83–91.Hartigan JA, Wong MA. A k-means clustering algorithm. Appl Stat. 1979;28:100–8.Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002;3:0034.1.Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper - Excel-based tool using pair-wise correlations. Biotechnol Lett. 2004;26:509–15.Gonzalez-Ibeas D, Blanca J, Roig C, González-To M, Picó B, Truniger V, et al. MELOGEN: An EST database for melon functional genomics. BMC Genomics. 2007;8:306.Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001;29:e45.Masoudi-Nejad A, Goto S, Jauregui R, Ito M, Kawashima S, Moriya Y, et al. EGENES: transcriptome-based plant database of genes with metabolic pathway information and expressed sequence tag indices in KEGG. Plant Physiol. 2007;144:857–66.Usadel B, Nagel A, Thimm O, Redestig H, Blaesing OE, Palacios-Rojas N, et al. Extension of the visualisation tool MapMan to allow statistical analysis of arrays, display of corresponding genes and comparison with known responses. Plant Physiol. 2005;138:1195–204.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Stat Methodol. 1995;57:289–300

Earliest Olduvai hominins exploited unstable environments ~ 2 million years ago

Rapid environmental change is a catalyst for human evolution, driving dietary innovations, habitat diversification, and dispersal. However, there is a dearth of information to assess hominin adaptions to changing physiography during key evolutionary stages such as the early Pleistocene. Here we report a multiproxy dataset from Ewass Oldupa, in the Western Plio-Pleistocene rift basin of Olduvai Gorge (now Oldupai), Tanzania, to address this lacuna and offer an ecological perspective on human adaptability two million years ago. Oldupai’s earliest hominins sequentially inhabited the floodplains of sinuous channels, then river-influenced contexts, which now comprises the oldest palaeolake setting documented regionally. Early Oldowan tools reveal a homogenous technology to utilise diverse, rapidly changing environments that ranged from fern meadows to woodland mosaics, naturally burned landscapes, to lakeside woodland/palm groves as well as hyper-xeric steppes. Hominins periodically used emerging landscapes and disturbance biomes multiple times over 235,000 years, thus predating by more than 180,000 years the earliest known hominins and Oldowan industries from the Eastern side of the basin.Introduction Results - Stratigraphy and archaeology - Early Oldowan ecology at ~ 2 Ma Discussion Methods - Biomarkers - Energy dispersive X-ray fluorescence - Excavation - Fauna - Mineral geochemistry - Phytolith analysis - Pollen and microcharcoal - Stable carbon and oxygen isotope analysis of faunal dental enamel - Stone tool

The Early Acheulean technology of Barranc de la Boella (Catalonia, Spain)

Since 2007, excavations at Barranc de la Boella (Tarragona, Catalonia, Spain) have revealed three localities with rich archaeo-paleontological assemblages: La Mina, El Forn and Pit 1. Palaeontology, palaeomagnetism and cosmogenic analyses have dated these localities to close to 1 Ma. The presence of Mammuthus meridionalis, Hippopotamus antiquus, Stephanorhinus cf. hundsheimensis, Mimomys savini and Victoriamys chalinei stand out in the sample of macro and micro-mammals. The lithic assemblages from the three sites are made up of percussion cobbles, choppers, chopper-cores, cores, simple flakes, and some retouched flakes: mainly denticulates and notches. In the case of the El Forn and Pit 1 localities, two large cutting tools have been recovered: a cleaver-like tool and a pick made of hard-wearing schist. The lithic assemblage of Pit 1, which includes several refitting lithic sets, is closely associated with the remains of a young-adult Mammuthus meridionalis, in a clear butchering site context. This evidence suggests that Barranc de la Boella is the oldest European Early Acheulean site, and one of the oldest butchering site on the subcontinent during the late Early Pleistocene. The study of the variability among these three localities in similar environmental conditions, together with information from other sites, are discussed in order to gain further knowledge about the appearance of the Acheulean in Europe, and its continuity or discontinuity in relation to pre-existing technologies.Since 2007, excavations at Barranc de la Boella (Tarragona, Catalonia, Spain) have revealed three localities with rich archaeo-paleontological assemblages: La Mina, El Forn and Pit 1. Palaeontology, palaeomagnetism and cosmogenic analyses have dated these localities to close to 1 Ma. The presence of Mammuthus meridionalis, Hippopotamus antiquus, Stephanorhinus cf. hundsheimensis, Mimomys savini and Victoriamys chalinei stand out in the sample of macro and micro-mammals. The lithic assemblages from the three sites are made up of percussion cobbles, choppers, chopper-cores, cores, simple flakes, and some retouched flakes: mainly denticulates and notches. In the case of the El Forn and Pit 1 localities, two large cutting tools have been recovered: a cleaver-like tool and a pick made of hard-wearing schist. The lithic assemblage of Pit 1, which includes several refitting lithic sets, is closely associated with the remains of a young-adult Mammuthus meridionalis, in a clear butchering site context. This evidence suggests that Barranc de la Boella is the oldest European Early Acheulean site, and one of the oldest butchering site on the subcontinent during the late Early Pleistocene. The study of the variability among these three localities in similar environmental conditions, together with information from other sites, are discussed in order to gain further knowledge about the appearance of the Acheulean in Europe, and its continuity or discontinuity in relation to pre-existing technologies

Seasonal pattern of apoplastic solute accumulation and loss of cell turgor during ripening of Vitis vinifera fruit under field conditions

Using a novel pressure membrane (PM) apparatus for the extraction of apoplastic fluid from field-grown grape (Vitis vinifera L.) berries, our hypothesis that significant apoplast solutes accumulate at the beginning of the ripening process (i.e. veraison), and that this accumulation might contribute to progressive berry softening due to a progressive loss of mesocarp cell turgor pressure (P) was tested. It was necessary to correct the solute potential (Ψs) of fluid collected with the PM for dilution due to the presence of a dead volume in the apparatus, but after correction, the Ψs obtained with the PM agreed with that obtained by low speed centrifugation. A clear decline in fruit apoplastic solute potential (ψSA) began approximately 10 d prior to fruit coloration, and it was found to be coincident with a decline in mesocarp cell P and fruit elasticity (E). By late in fruit development when berry growth ceased (90 d after anthesis), both apoplast and fruit Ψs reached almost –4 MPa. These results support the hypothesis that a decrease in ψSA is responsible for the observed loss in mesocarp cell P, and is the mechanistic cause of berry softening

QTL Analyses in Multiple Populations Employed for the Fine Mapping and Identification of Candidate Genes at a Locus Affecting Sugar Accumulation in Melon (Cucumis melo L.)

[EN] Sugar content is the major determinant of both fruit quality and consumer acceptance in melon (Cucumis melo L), and is a primary target for crop improvement. Nearisogenic lines (NILs) derived from the intraspecific cross between a "Piel de Sapo" (PS) type and the exotic cultivar "Songwhan Charmi" (SC), and several populations generated from the cross of PS x Ames 24294 ("Trigonus"), a wild melon, were used to identify QTL related to sugar and organic acid composition. Seventy-eight QTL were detected across several locations and different years, with three important clusters related to sugar content located on chromosomes 4, 5, and 7. Two PS x SC NILs (SC5-1 and SC5-2) sharing a common genomic interval of 1.7Mb at the top of chromosome 5 contained QTL reducing soluble solids content (SSC) and sucrose content by an average of 29 and 68%, respectively. This cluster collocated with QTL affecting sugar content identified in other studies in lines developed from the PS x SC cross and supported the presence of a stable consensus locus involved in sugar accumulation that we named SUCQSC5.1. QTL reducing soluble solids and sucrose content identified in the "Trigonus" mapping populations, as well as QTL identified in previous studies from other ssp. agrestis sources, collocated with SUCQSC5.1, suggesting that they may be allelic and implying a role in domestication. In subNILs derived from the PS x SC5-1 cross, SUCQSC5.1 reduced SSC and sucrose content by an average of 18 and 34%, respectively, and was fine-mapped to a 56.1 kb interval containing four genes. Expression analysis of the candidate genes in mature fruit showed differences between the subNILs with PS alleles that were "high" sugar and SC alleles of "low" sugar phenotypes for MELO3C014519, encoding a putative BEL1-like homeodomain protein. Sequence differences in the gene predicted to affect protein function were restricted to SC and other ssp. agrestis cultivar groups. These results provide the basis for further investigation of genes affecting sugar accumulation in melon.This work was supported by the Spanish Ministry of Economy and Competitivity grants AGL2015-64625-C2-1-R and PIM2010PKB-00691, Centro de Excelencia Severo Ochoa 2016-2020 and the CERCA Programme/Generalitat de Catalunya to JG, AGL2015-64625-C2-R to AJM. AD was supported by a Jae-Doc contract from CSIC.Argirys, J.; Diaz, A.; Ruggieri, V.; Fernandez, M.; Jahrmann, T.; Gibon, Y.; Picó Sirvent, MB.... (2017). QTL Analyses in Multiple Populations Employed for the Fine Mapping and Identification of Candidate Genes at a Locus Affecting Sugar Accumulation in Melon (Cucumis melo L.). Frontiers in Plant Science. 8:1-20. https://doi.org/10.3389/fpls.2017.01679S1208Argyris, J. M., Pujol, M., Martín-Hernández, A. M., & Garcia-Mas, J. (2015). Combined use of genetic and genomics resources to understand virus resistance and fruit quality traits in melon. Physiologia Plantarum, 155(1), 4-11. doi:10.1111/ppl.12323Argyris, J. M., Ruiz-Herrera, A., Madriz-Masis, P., Sanseverino, W., Morata, J., Pujol, M., … Garcia-Mas, J. (2015). Use of targeted SNP selection for an improved anchoring of the melon (Cucumis melo L.) scaffold genome assembly. BMC Genomics, 16(1), 4. doi:10.1186/s12864-014-1196-3Ariizumi, T., Higuchi, K., Arakaki, S., Sano, T., Asamizu, E., & Ezura, H. (2011). Genetic suppression analysis in novel vacuolar processing enzymes reveals their roles in controlling sugar accumulation in tomato fruits. Journal of Experimental Botany, 62(8), 2773-2786. doi:10.1093/jxb/erq451Bartley, G. E., & Ishida, B. K. (2003). BMC Plant Biology, 3(1), 4. doi:10.1186/1471-2229-3-4Beaulieu, J. C., Lea, J. M., Eggleston, G., & Peralta-Inga, Z. (2003). Sugar and Organic Acid Variations in Commercial Cantaloupes and Their Inbred Parents. Journal of the American Society for Horticultural Science, 128(4), 531-536. doi:10.21273/jashs.128.4.0531Bencivenga, S., Simonini, S., Benková, E., & Colombo, L. (2012). The Transcription Factors BEL1 and SPL Are Required for Cytokinin and Auxin Signaling During Ovule Development in Arabidopsis. The Plant Cell, 24(7), 2886-2897. doi:10.1105/tpc.112.100164Bermúdez, L., Urias, U., Milstein, D., Kamenetzky, L., Asis, R., Fernie, A. R., … Rossi, M. (2008). A candidate gene survey of quantitative trait loci affecting chemical composition in tomato fruit. Journal of Experimental Botany, 59(10), 2875-2890. doi:10.1093/jxb/ern146Brenner, W. G., Ramireddy, E., Heyl, A., & Schmülling, T. (2012). Gene Regulation by Cytokinin in Arabidopsis. Frontiers in Plant Science, 3. doi:10.3389/fpls.2012.00008Burger, Y., Sa’ar, U., Distelfeld, A., Katzir, N., Yeselson, Y., Shen, S., & Schaffer, A. A. (2003). Development of Sweet Melon (Cucumis melo) Genotypes Combining High Sucrose and Organic Acid Content. Journal of the American Society for Horticultural Science, 128(4), 537-540. doi:10.21273/jashs.128.4.0537Burger, Y., & Schaffer, A. A. (2007). The Contribution of Sucrose Metabolism Enzymes to Sucrose Accumulation in Cucumis melo. Journal of the American Society for Horticultural Science, 132(5), 704-712. doi:10.21273/jashs.132.5.704Burglin, T. R. (1997). Analysis of TALE superclass homeobox genes (MEIS, PBC, KNOX, Iroquois, TGIF) reveals a novel domain conserved between plants and animals. Nucleic Acids Research, 25(21), 4173-4180. doi:10.1093/nar/25.21.4173Castro, G. E., Perpiñá, G., Esteras, C., Monforte, A. J., & Picó, M. B. (2017). A new introgression line collection to improve ‘Piel de Sapo’ melons. Acta Horticulturae, (1151), 81-86. doi:10.17660/actahortic.2017.1151.14Chen, H., Banerjee, A. K., & Hannapel, D. J. (2004). The tandem complex of BEL and KNOX partners is required for transcriptional repression ofga20ox1. The Plant Journal, 38(2), 276-284. doi:10.1111/j.1365-313x.2004.02048.xChen, H., Rosin, F. M., Prat, S., & Hannapel, D. J. (2003). Interacting Transcription Factors from the Three-Amino Acid Loop Extension Superclass Regulate Tuber Formation. Plant Physiology, 132(3), 1391-1404. doi:10.1104/pp.103.022434Cingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., … Ruden, D. M. (2012). A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly, 6(2), 80-92. doi:10.4161/fly.19695Cohen, S., Itkin, M., Yeselson, Y., Tzuri, G., Portnoy, V., Harel-Baja, R., … Schaffer, A. A. (2014). The PH gene determines fruit acidity and contributes to the evolution of sweet melons. Nature Communications, 5(1). doi:10.1038/ncomms5026Dai, N., Cohen, S., Portnoy, V., Tzuri, G., Harel-Beja, R., Pompan-Lotan, M., … Schaffer, A. A. (2011). Metabolism of soluble sugars in developing melon fruit: a global transcriptional view of the metabolic transition to sucrose accumulation. Plant Molecular Biology, 76(1-2), 1-18. doi:10.1007/s11103-011-9757-1Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., … DePristo, M. A. (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158. doi:10.1093/bioinformatics/btr330Del Amor, F. M., Martinez, V., & Cerdá, A. (1999). Salinity Duration and Concentration Affect Fruit Yield and Quality, and Growth and Mineral Composition of Melon Plants Grown in Perlite. HortScience, 34(7), 1234-1237. doi:10.21273/hortsci.34.7.1234Diaz, A., Fergany, M., Formisano, G., Ziarsolo, P., Blanca, J., Fei, Z., … Monforte, A. J. (2011). A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.). BMC Plant Biology, 11(1), 111. doi:10.1186/1471-2229-11-111Diaz, A., Forment, J., Argyris, J. M., Fukino, N., Tzuri, G., Harel-Beja, R., … Monforte, A. J. (2015). Anchoring the consensus ICuGI genetic map to the melon (Cucumis melo L.) genome. Molecular Breeding, 35(10). doi:10.1007/s11032-015-0381-7Díaz, A., Martín-Hernández, A. M., Dolcet-Sanjuan, R., Garcés-Claver, A., Álvarez, J. M., Garcia-Mas, J., … Monforte, A. J. (2017). Quantitative trait loci analysis of melon (Cucumis melo L.) domestication-related traits. Theoretical and Applied Genetics, 130(9), 1837-1856. doi:10.1007/s00122-017-2928-yDong, Y.-H., Yao, J.-L., Atkinson, R. G., Putterill, J. J., Morris, B. A., & Gardner, R. C. (2000). Plant Molecular Biology, 42(4), 623-633. doi:10.1023/a:1006301224125Dunnett, C. W. (1955). A Multiple Comparison Procedure for Comparing Several Treatments with a Control. Journal of the American Statistical Association, 50(272), 1096-1121. doi:10.1080/01621459.1955.10501294Eduardo, I., Arús, P., & Monforte, A. J. (2005). Development of a genomic library of near isogenic lines (NILs) in melon (Cucumis melo L.) from the exotic accession PI161375. Theoretical and Applied Genetics, 112(1), 139-148. doi:10.1007/s00122-005-0116-yEduardo, I., Arús, P., Monforte, A. J., Obando, J., Fernández-Trujillo, J. P., Martínez, J. A., … van der Knaap, E. (2007). Estimating the Genetic Architecture of Fruit Quality Traits in Melon Using a Genomic Library of Near Isogenic Lines. Journal of the American Society for Horticultural Science, 132(1), 80-89. doi:10.21273/jashs.132.1.80Esteras, C., Formisano, G., Roig, C., Díaz, A., Blanca, J., Garcia-Mas, J., … Picó, B. (2013). SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium. Theoretical and Applied Genetics, 126(5), 1285-1303. doi:10.1007/s00122-013-2053-5Farkas, I., Dombrádi, V., Miskei, M., Szabados, L., & Koncz, C. (2007). Arabidopsis PPP family of serine/threonine phosphatases. Trends in Plant Science, 12(4), 169-176. doi:10.1016/j.tplants.2007.03.003Fernandez-Silva, I., Moreno, E., Essafi, A., Fergany, M., Garcia-Mas, J., Martín-Hernandez, A. M., … Monforte, A. J. (2010). Shaping melons: agronomic and genetic characterization of QTLs that modify melon fruit morphology. Theoretical and Applied Genetics, 121(5), 931-940. doi:10.1007/s00122-010-1361-2Gao, Z., Petreikov, M., Zamski, E., & Schaffer, A. A. (1999). Carbohydrate metabolism during early fruit development of sweet melon (Cucumis melo ). Physiologia Plantarum, 106(1), 1-8. doi:10.1034/j.1399-3054.1999.106101.xGarcia-Mas, J., Benjak, A., Sanseverino, W., Bourgeois, M., Mir, G., Gonzalez, V. M., … Puigdomenech, P. (2012). The genome of melon (Cucumis melo L.). Proceedings of the National Academy of Sciences, 109(29), 11872-11877. doi:10.1073/pnas.1205415109Harel-Beja, R., Tzuri, G., Portnoy, V., Lotan-Pompan, M., Lev, S., Cohen, S., … Katzir, N. (2010). A genetic map of melon highly enriched with fruit quality QTLs and EST markers, including sugar and carotenoid metabolism genes. Theoretical and Applied Genetics, 121(3), 511-533. doi:10.1007/s00122-010-1327-4Hendriks, J. H. M., Kolbe, A., Gibon, Y., Stitt, M., & Geigenberger, P. (2003). ADP-Glucose Pyrophosphorylase Is Activated by Posttranslational Redox-Modification in Response to Light and to Sugars in Leaves of Arabidopsis and Other Plant Species. Plant Physiology, 133(2), 838-849. doi:10.1104/pp.103.024513Hu, B., Jin, J., Guo, A.-Y., Zhang, H., Luo, J., & Gao, G. (2014). GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics, 31(8), 1296-1297. doi:10.1093/bioinformatics/btu817Hubbard, N. L., Huber, S. C., & Pharr, D. M. (1989). Sucrose Phosphate Synthase and Acid Invertase as Determinants of Sucrose Concentration in Developing Muskmelon (Cucumis melo L.) Fruits. Plant Physiology, 91(4), 1527-1534. doi:10.1104/pp.91.4.1527Jelitto, T., Sonnewald, U., Willmitzer, L., Hajirezeai, M., & Stitt, M. (1992). Inorganic pyrophosphate content and metabolites in potato and tobacco plants expressing E. coli pyrophosphatase in their cytosol. Planta, 188(2), 238-244. doi:10.1007/bf00216819Kano, Y. (2006). Effect of Heating Fruit on Cell Size and Sugar Accumulation in Melon Fruit (Cucumis melo L.). HortScience, 41(6), 1431-1434. doi:10.21273/hortsci.41.6.1431Keurentjes, J. J. B., Bentsink, L., Alonso-Blanco, C., Hanhart, C. J., Blankestijn-De Vries, H., Effgen, S., … Koornneef, M. (2006). Development of a Near-Isogenic Line Population ofArabidopsis thalianaand Comparison of Mapping Power With a Recombinant Inbred Line Population. Genetics, 175(2), 891-905. doi:10.1534/genetics.106.066423Leida, C., Moser, C., Esteras, C., Sulpice, R., Lunn, J. E., de Langen, F., … Picó, B. (2015). Variability of candidate genes, genetic structure and association with sugar accumulation and climacteric behavior in a broad germplasm collection of melon (Cucumis melo L.). BMC Genetics, 16(1). doi:10.1186/s12863-015-0183-2Mascarell-Creus, A., Cañizares, J., Vilarrasa-Blasi, J., Mora-García, S., Blanca, J., Gonzalez-Ibeas, D., … Caño-Delgado, A. I. (2009). 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, 10(1), 467. doi:10.1186/1471-2164-10-467Maughan, P. J., Smith, S. M., & Raney, J. A. (2012). Utilization of Super BAC Pools and Fluidigm Access Array Platform for High-Throughput BAC Clone Identification: Proof of Concept. Journal of Biomedicine and Biotechnology, 2012, 1-7. doi:10.1155/2012/405940Monforte, A. J., Diaz, A., Caño-Delgado, A., & van der Knaap, E. (2013). The genetic basis of fruit morphology in horticultural crops: lessons from tomato and melon. Journal of Experimental Botany, 65(16), 4625-4637. doi:10.1093/jxb/eru017Monforte, A. J., Oliver, M., Gonzalo, M. J., Alvarez, J. M., Dolcet-Sanjuan, R., & Arús, P. (2003). Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.). Theoretical and Applied Genetics, 108(4), 750-758. doi:10.1007/s00122-003-1483-xMora-Garcia, S. (2004). Nuclear protein phosphatases with Kelch-repeat domains modulate the response to brassinosteroids in Arabidopsis. Genes & Development, 18(4), 448-460. doi:10.1101/gad.1174204Obando-Ulloa, J. M., Eduardo, I., Monforte, A. J., & Fernández-Trujillo, J. P. (2009). Identification of QTLs related to sugar and organic acid composition in melon using near-isogenic lines. Scientia Horticulturae, 121(4), 425-433. doi:10.1016/j.scienta.2009.02.023Paris, M. K., Zalapa, J. E., McCreight, J. D., & Staub, J. E. (2008). Genetic dissection of fruit quality components in melon (Cucumis melo L.) using a RIL population derived from exotic × elite US Western Shipping germplasm. Molecular Breeding, 22(3), 405-419. doi:10.1007/s11032-008-9185-3Park, S. O., Hwang, H. Y., & Crosby, K. M. (2009). A Genetic Linkage Map including Loci for Male Sterility, Sugars, and Ascorbic Acid in Melon. Journal of the American Society for Horticultural Science, 134(1), 67-76. doi:10.21273/jashs.134.1.67Pavan, S., Marcotrigiano, A. R., Ciani, E., Mazzeo, R., Zonno, V., Ruggieri, V., … Ricciardi, L. (2017). Genotyping-by-sequencing of a melon (Cucumis melo L.) germplasm collection from a secondary center of diversity highlights patterns of genetic variation and genomic features of different gene pools. BMC Genomics, 18(1). doi:10.1186/s12864-016-3429-0Perpiñá, G., Esteras, C., Gibon, Y., Monforte, A. J., & Picó, B. (2016). A new genomic library of melon introgression lines in a cantaloupe genetic background for dissecting desirable agronomical traits. BMC Plant Biology, 16(1). doi:10.1186/s12870-016-0842-0Pitrat, M. (s. f.). Melon. Vegetables I, 283-315. doi:10.1007/978-0-387-30443-4_9Reiser, L., Modrusan, Z., Margossian, L., Samach, A., Ohad, N., Haughn, G. W., & Fischer, R. L. (1995). The BELL1 gene encodes a homeodomain protein involved in pattern formation in the Arabidopsis ovule primordium. Cell, 83(5), 735-742. doi:10.1016/0092-8674(95)90186-8Ríos, P., Argyris, J., Vegas, J., Leida, C., Kenigswald, M., Tzuri, G., … Garcia-Mas, J. (2017). ETHQV6.3 is involved in melon climacteric fruit ripening and is encoded by a NAC domain transcription factor. The Plant Journal, 91(4), 671-683. doi:10.1111/tpj.13596Sagar, M., Chervin, C., Mila, I., Hao, Y., Roustan, J.-P., Benichou, M., … Zouine, M. (2013). SlARF4, an Auxin Response Factor Involved in the Control of Sugar Metabolism during Tomato Fruit Development. Plant Physiology, 161(3), 1362-1374. doi:10.1104/pp.113.213843Saladié, M., Cañizares, J., Phillips, M. A., Rodriguez-Concepcion, M., Larrigaudière, C., Gibon, Y., … Garcia-Mas, J. (2015). Comparative transcriptional profiling analysis of developing melon (Cucumis melo L.) fruit from climacteric and non-climacteric varieties. BMC Genomics, 16(1). doi:10.1186/s12864-015-1649-3Sanseverino, W., Hénaff, E., Vives, C., Pinosio, S., Burgos-Paz, W., Morgante, M., … Casacuberta, J. M. (2015). Transposon Insertions, Structural Variations, and SNPs Contribute to the Evolution of the Melon Genome. Molecular Biology and Evolution, 32(10), 2760-2774. doi:10.1093/molbev/msv152Sauvage, C., Segura, V., Bauchet, G., Stevens, R., Do, P. T., Nikoloski, Z., … Causse, M. (2014). Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits. Plant Physiology, 165(3), 1120-1132. doi:10.1104/pp.114.241521Sebastian, P., Schaefer, H., Telford, I. R. H., & Renner, S. S. (2010). Cucumber (Cucumis sativus) and melon (C. melo) have numerous wild relatives in Asia and Australia, and the sister species of melon is from Australia. Proceedings of the National Academy of Sciences, 107(32), 14269-14273. doi:10.1073/pnas.1005338107Stepansky, A., Kovalski, I., Schaffer, A. A., & Perl-Treves, R. (1999). Genetic Resources and Crop Evolution, 46(1), 53-62. doi:10.1023/a:1008636732481Wahl, V., Brand, L. H., Guo, Y.-L., & Schmid, M. (2010). The FANTASTIC FOUR proteins influence shoot meristem size in Arabidopsis thaliana. BMC Plant Biology, 10(1), 285. doi:10.1186/1471-2229-10-285Wang, J., Lin, M., Crenshaw, A., Hutchinson, A., Hicks, B., Yeager, M., … Ramakrishnan, R. (2009). High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays. BMC Genomics, 10(1), 561. doi:10.1186/1471-2164-10-561Yang, C.-J., Zhang, C., Lu, Y.-N., Jin, J.-Q., & Wang, X.-L. (2011). The Mechanisms of Brassinosteroids’ Action: From Signal Transduction to Plant Development. Molecular Plant, 4(4), 588-600. doi:10.1093/mp/ssr020Zeng, Z. B. (1993). Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proceedings of the National Academy of Sciences, 90(23), 10972-10976. doi:10.1073/pnas.90.23.10972Zhang, C., Yu, X., Ayre, B. G., & Turgeon, R. (2012). The Origin and Composition of Cucurbit «Phloem» Exudate. Plant Physiology, 158(4), 1873-1882. doi:10.1104/pp.112.194431Zhang, Y. (2008). I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, 9(1). doi:10.1186/1471-2105-9-4