A new view of electrochemistry at highly oriented pyrolytic graphite

Major new insights on electrochemical processes at graphite electrodes are reported, following extensive investigations of two of the most studied redox couples, Fe(CN)64–/3– and Ru(NH3)63+/2+. Experiments have been carried out on five different grades of highly oriented pyrolytic graphite (HOPG) that vary in step-edge height and surface coverage. Significantly, the same electrochemical characteristic is observed on all surfaces, independent of surface quality: initial cyclic voltammetry (CV) is close to reversible on freshly cleaved surfaces (>400 measurements for Fe(CN)64–/3– and >100 for Ru(NH3)63+/2+), in marked contrast to previous studies that have found very slow electron transfer (ET) kinetics, with an interpretation that ET only occurs at step edges. Significantly, high spatial resolution electrochemical imaging with scanning electrochemical cell microscopy, on the highest quality mechanically cleaved HOPG, demonstrates definitively that the pristine basal surface supports fast ET, and that ET is not confined to step edges. However, the history of the HOPG surface strongly influences the electrochemical behavior. Thus, Fe(CN)64–/3– shows markedly diminished ET kinetics with either extended exposure of the HOPG surface to the ambient environment or repeated CV measurements. In situ atomic force microscopy (AFM) reveals that the deterioration in apparent ET kinetics is coupled with the deposition of material on the HOPG electrode, while conducting-AFM highlights that, after cleaving, the local surface conductivity of HOPG deteriorates significantly with time. These observations and new insights are not only important for graphite, but have significant implications for electrochemistry at related carbon materials such as graphene and carbon nanotubes

Genome-wide BAC-end sequencing of Cucumis melo using two BAC libraries

<p>Abstract</p> <p>Background</p> <p>Although melon (<it>Cucumis melo </it>L.) is an economically important fruit crop, no genome-wide sequence information is openly available at the current time. We therefore sequenced BAC-ends representing a total of 33,024 clones, half of them from a previously described melon BAC library generated with restriction endonucleases and the remainder from a new random-shear BAC library.</p> <p>Results</p> <p>We generated a total of 47,140 high-quality BAC-end sequences (BES), 91.7% of which were paired-BES. Both libraries were assembled independently and then cross-assembled to obtain a final set of 33,372 non-redundant, high-quality sequences. These were grouped into 6,411 contigs (4.5 Mb) and 26,961 non-assembled BES (14.4 Mb), representing ~4.2% of the melon genome. The sequences were used to screen genomic databases, identifying 7,198 simple sequence repeats (corresponding to one microsatellite every 2.6 kb) and 2,484 additional repeats of which 95.9% represented transposable elements. The sequences were also used to screen expressed sequence tag (EST) databases, revealing 11,372 BES that were homologous to ESTs. This suggests that ~30% of the melon genome consists of coding DNA. We observed regions of microsynteny between melon paired-BES and six other dicotyledonous plant genomes.</p> <p>Conclusion</p> <p>The analysis of nearly 50,000 BES from two complementary genomic libraries covered ~4.2% of the melon genome, providing insight into properties such as microsatellite and transposable element distribution, and the percentage of coding DNA. The observed synteny between melon paired-BES and six other plant genomes showed that useful comparative genomic data can be derived through large scale BAC-end sequencing by anchoring a small proportion of the melon genome to other sequenced genomes.</p

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Universidad y sociedad: comunicación e integración en empresas e instituciones públicas y organizaciones no lucrativas. Nuevos avances

Depto. de Teorías y Análisis de la ComunicaciónFac. de Ciencias de la InformaciónFALSEsubmitte

HisAK70: Progress towards a vaccine against different forms of leishmaniosis

Background: Leishmania major and Leishmania infantum are among the main species that are responsible for cutaneous leishmaniosis (CL) and visceral leishmaniosis (VL), respectively. The leishmanioses represent the second-largest parasitic killer in the world after malaria. Recently, we succeeded in generating a plasmid DNA (pCMV-HISA70m2A) and demonstrated that immunized mice were protected against L. major challenge. The efficacy of the DNA-vaccine was further enhanced by the inclusion of KMP-11 antigen into the antibiotic-free plasmid pVAX1-asd. Methods: Here, we describe the use of a HisAK70 DNA-vaccine encoding seven Leishmania genes (H2A, H2B, H3, H4, A2, KMP11 and HSP70) for vaccination of mice to assess the induction of a resistant phenotype against VL and CL. Results: HisAK70 was successful in vaccinated mice, resulting in a high amount of efficient sterile hepatic granulomas associated with a hepatic parasite burden fully resolved in the VL model; and resulting in 100 % inhibition of parasite visceralization in the CL model. Conclusions: The results suggest that immunization with the HisAK70 DNA-vaccine may provide a rapid, suitable, and efficient vaccination strategy to confer cross-protective immunity against VL and CL.This work was partially supported by grants from the Spanish Ministry of Economy and Competitiveness (AGL2010-17394 and AGL2013-44100R) and PLATESA (P2013/ABI-2906) from the Comunidad de Madrid (Spain).Peer Reviewe

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

Background: Mature-fruit abscission (MFA) in fleshy-fruit is a genetically controlled process with mechanisms that, contrary to immature-fruit abscission, has not been fully characterized. Here, we use pyrosequencing to characterize the transcriptomes of melon abscission zone (AZ) at three stages during AZ-cell separation in order to understand MFA control at an early stage of AZ-activation. Principal Findings: The results show that by early induction of MFA, the melon AZ exhibits major gene induction, while by late induction of MFA, melon AZ shows major gene repression. Although some genes displayed similar regulation in both early and late induction of abscission, such as EXT1-EXT4, EGase1, IAA2, ERF1, AP2D15, FLC, MADS2, ERAF17, SAP5 and SCL13 genes, the majority had different expression patterns. This implies that time-specific events occur during MFA, and emphasizes the value of characterizing multiple time-specific abscission transcriptomes. Analysis of gene-expression from these AZs reveal that a sequential induction of cell-wall-degrading genes is associated with the upregulation of genes involved in endo and exocytosis, and a shift in plant-hormone metabolism and signaling genes during MFA. This is accompanied by transcriptional activity of small-GTPases and synthaxins together with tubulins, dynamins, V-type ATPases and kinesin-like proteins potentially involved in MFA signaling. Early events are potentially controlled by down-regulation of MADS-box, AP2/ERF and Aux/IAA transcription-factors, and up-regulation of homeobox, zinc finger, bZIP, and WRKY transcription-factors, while late events may be controlled by up-regulation of MYB transcription-factors. Significance: Overall, the data provide a comprehensive view on MFA in fleshy-fruit, identifying candidate genes and pathways associated with early induction of MFA. Our comprehensive gene-expression profile will be very useful for elucidating gene regulatory networks of the MFA in fleshy-fruit

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

X chromosome inactivation does not necessarily determine the severity of the phenotype in Rett syndrome patients

Rett syndrome (RTT) is a severe neurological disorder usually caused by mutations in the MECP2 gene. Since the MECP2 gene is located on the X chromosome, X chromosome inactivation (XCI) could play a role in the wide range of phenotypic variation of RTT patients; however, classical methylation-based protocols to evaluate XCI could not determine whether the preferentially inactivated X chromosome carried the mutant or the wild-type allele. Therefore, we developed an allele-specific methylation-based assay to evaluate methylation at the loci of several recurrent MECP2 mutations. We analyzed the XCI patterns in the blood of 174 RTT patients, but we did not find a clear correlation between XCI and the clinical presentation. We also compared XCI in blood and brain cortex samples of two patients and found differences between XCI patterns in these tissues. However, RTT mainly being a neurological disease complicates the establishment of a correlation between the XCI in blood and the clinical presentation of the patients. Furthermore, we analyzed MECP2 transcript levels and found differences from the expected levels according to XCI. Many factors other than XCI could affect the RTT phenotype, which in combination could influence the clinical presentation of RTT patients to a greater extent than slight variations in the XCI pattern

Analysis of the melon (Cucumis melo) small RNAome by high-throughput pyrosequencing

Abstract Background Melon (Cucumis melo L.) is a commercially important fruit crop that is cultivated worldwide. The melon research community has recently benefited from the determination of a complete draft genome sequence and the development of associated genomic tools, which have allowed us to focus on small RNAs (sRNAs). These are short, non-coding RNAs 21-24 nucleotides in length with diverse physiological roles. In plants, they regulate gene expression and heterochromatin assembly, and control protection against virus infection. Much remains to be learned about the role of sRNAs in melon. Results We constructed 10 sRNA libraries from two stages of developing ovaries, fruits and photosynthetic cotyledons infected with viruses, and carried out high-throughput pyrosequencing. We catalogued and analysed the melon sRNAs, resulting in the identification of 26 known miRNA families (many conserved with other species), the prediction of 84 melon-specific miRNA candidates, the identification of trans-acting siRNAs, and the identification of chloroplast, mitochondrion and transposon-derived sRNAs. In silico analysis revealed more than 400 potential targets for the conserved and novel miRNAs. Conclusion We have discovered and analysed a large number of conserved and melon-specific sRNAs, including miRNAs and their potential target genes. This provides insight into the composition and function of the melon small RNAome, and paves the way towards an understanding of sRNA-mediated processes that regulate melon fruit development and melon-virus interactions.This work was supported by grants AGL2009-07552/AGR, BIO2006-13107 (Ministerio de Ciencia e Innovación, Spain) and MELONOMICS (Fundación Genoma España, Spain).Peer Reviewe

Syntenic relationships between cucumber (Cucumis sativus L.) and melon (C. melo L.) chromosomes as revealed by comparative genetic mapping

<p>Abstract</p> <p>Background</p> <p>Cucumber, <it>Cucumis sativus </it>L. (2n = 2 × = 14) and melon, <it>C. melo </it>L. (2n = 2 × = 24) are two important vegetable species in the genus <it>Cucumis </it>(family Cucurbitaceae). Both species have an Asian origin that diverged approximately nine million years ago. Cucumber is believed to have evolved from melon through chromosome fusion, but the details of this process are largely unknown. In this study, comparative genetic mapping between cucumber and melon was conducted to examine syntenic relationships of their chromosomes.</p> <p>Results</p> <p>Using two melon mapping populations, 154 and 127 cucumber SSR markers were added onto previously reported F₂- and RIL-based genetic maps, respectively. A consensus melon linkage map was developed through map integration, which contained 401 co-dominant markers in 12 linkage groups including 199 markers derived from the cucumber genome. Syntenic relationships between melon and cucumber chromosomes were inferred based on associations between markers on the consensus melon map and cucumber draft genome scaffolds. It was determined that cucumber Chromosome 7 was syntenic to melon Chromosome I. Cucumber Chromosomes 2 and 6 each contained genomic regions that were syntenic with melon chromosomes III+V+XI and III+VIII+XI, respectively. Likewise, cucumber Chromosomes 1, 3, 4, and 5 each was syntenic with genomic regions of two melon chromosomes previously designated as II+XII, IV+VI, VII+VIII, and IX+X, respectively. However, the marker orders in several syntenic blocks on these consensus linkage maps were not co-linear suggesting that more complicated structural changes beyond simple chromosome fusion events have occurred during the evolution of cucumber.</p> <p>Conclusions</p> <p>Comparative mapping conducted herein supported the hypothesis that cucumber chromosomes may be the result of chromosome fusion from a 24-chromosome progenitor species. Except for a possible inversion, cucumber Chromosome 7 has largely remained intact in the past nine million years since its divergence from melon. Meanwhile, many structural changes may have occurred during the evolution of the remaining six cucumber chromosomes. Further characterization of the genomic nature of <it>Cucumis </it>species closely related to cucumber and melon might provide a better understanding of the evolutionary history leading to modern cucumber.</p