17 research outputs found
High-throughput marker discovery in melon using a self-designed oligo microarray
<p>Abstract</p> <p>Background</p> <p>Genetic maps constitute the basis of breeding programs for many agricultural organisms. The creation of these maps is dependent on marker discovery. Melon, among other crops, is still lagging in genomic resources, limiting the ability to discover new markers in a high-throughput fashion. One of the methods used to search for molecular markers is DNA hybridization to microarrays. Microarray hybridization of DNA from different accessions can reveal differences between them--single-feature polymorphisms (SFPs). These SFPs can be used as markers for breeding purposes, or they can be converted to conventional markers by sequencing. This method has been utilized in a few different plants to discover genetic variation, using Affymetrix arrays that exist for only a few organisms. We applied this approach with some modifications for marker discovery in melon.</p> <p>Results</p> <p>Using a custom-designed oligonucleotide microarray based on a partial EST collection of melon, we discovered 6184 putative SFPs between the parents of our mapping population. Validation by sequencing of 245 SFPs from the two parents showed a sensitivity of around 79%. Most SFPs (81%) contained single-nucleotide polymorphisms. Testing the SFPs on another mapping population of melon confirmed that many of them are conserved.</p> <p>Conclusion</p> <p>Thousands of new SFPs that can be used for genetic mapping and molecular-assisted breeding in melon were discovered using a custom-designed oligo microarray. A portion of these SFPs are conserved and can be used in different breeding populations. Although improvement of the discovery rate is still needed, this approach is applicable to many agricultural systems with limited genomic resources.</p
A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)
Background
A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS).
Results
Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org webcite), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm.
Conclusions
Even though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection).This work was supported in part by SNC Laboratoire ASL, Ruiter Seeds B.V., Enza Zaden B.V., Gautier Semences S.A., Nunhems B.V., Rijk Zwaan B.V., Sakata Seed Inc, Semillas Fito S. A., Seminis Vegetable Seeds Inc, Syngenta Seeds B. V., Takii and Company Ltd, Vilmorin & Cie S. A., and Zeraim Gedera Ltd (all of them as part of the support to the ICuGI); the grants AGL2009-12698-C02-02 from the Spanish "Ministerio de Ciencia e Innovacion" to AJM. NK lab was supported in part by Research Grant Award No. IS-4223-09C from BARD, the United States - Israel Binational Agricultural Research and Development Fund, and in part by Israel Science Foundation Grant No. 38606, De Ruiter Seeds, Enza Zaden, Keygene, Rijk Zwaan, Sakata Seed Corporation, Semillas Fito, Syngenta Seeds and Vilmorin Clause & Cie. AD was supported by a JAE-Doc contract from "Consejo Superior de Investigaciones Cientificas" (CSIC-Spain). MF was supported by a postdoctoral contract from CRAG. The research carried out at YX's laboratory was supported by Chinese funds (Grant No. 2008-Z42(3), 5100001, 2010AA101907).Díaz Bermúdez, A.; Fergany, M.; Formisano, G.; Ziarsolo, P.; Blanca Postigo, JM.; Fei, Z.; Staub, JE.... (2011). A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon. BMC Plant Biology. 11. https://doi.org/10.1186/1471-2229-11-111S1
Anchoring the consensus ICuGI genetic map to the melon (Cucumis melo L.) genome
Melon (Cucumis melo L.) genetic maps were compiled by the International Cucurbit Genomics Initiative (ICuGI) before the release of the melon genome. However, due to the use of different marker sets, the position of ICuGI markers in the genome remained unknown, complicating the integration of previous genetic mapping studies in the genome. We looked for the genome position of 870 simple sequence repeat and single nucleotide polymorphism (SNP) markers from the ICuGI map, locating 836 of them in the melon pseudochromosomes v3.5.1, and integrating them with previously available SNPs to reach a total of 1850 markers mapped in the genome sequence. The number of markers per scaffold ranged from 1 to 105, with an average of 13, thus improving on the previous studies in melon. Twenty-three of the markers mapped on virtual chromosome "0'', twelve of them being included in the ICuGI map, which could assist in the anchoring of some unanchored contigs and scaffolds. Genetic and physical distance comparison showed a good collinearity between them, confirming the quality of the ICuGI map. A higher recombination rate was also usually found at the ends of the chromosomes, whereas a drastic reduction was observed in the putative pericentromeric regions. Quantitative trait loci (QTL) previously located in the ICuGI map were also anchored in the genome. This work offers the opportunity to supplement the genetic maps available up to now with the genomic resources resulting from the melon genome sequencing to facilitate comparative mapping in melon between past and new studies, and to overcome some of the current limitations in QTL gene identification.This work was funded in part by the project AGL2012-40130-C02-02 from Spanish Ministry of Economy and Competitiveness (MINECO) to AJM.Díaz Bermúdez, A.; Forment Millet, JJ.; Argyris, JM.; Fukino, N.; Tzuri, G.; Harel-Beja, R.; Katzir, N.... (2015). Anchoring the consensus ICuGI genetic map to the melon (Cucumis melo L.) genome. Molecular Breeding. 35(10):1-7. https://doi.org/10.1007/s11032-015-0381-7S173510Argyris JM, Ruiz-Herrera A, Madriz-Masis P, Sanseverino W, Morata J, Pujol M, Ramos-Onsins SE, Garcia-Mas J (2015) Use of targeted SNP selection for an improved anchoring of the melon (Cucumis melo L.) scaffold genome assembly. BMC Genomics 16:4Burger Y, Sa’ar U, Paris HS, Lewinsohn E, Katzir N, Tadmor Y, Schaffer AA (2006) Genetic variability for valuable fruit quality traits in Cucumis melo. Isr J Plant Sci 54:233–242Cuevas HE, Staub JE, Simon PW, Zalapa JE, McCreight JD (2008) Mapping of genetic loci that regulate quantity of beta-carotene in fruit of US Western Shipping melon (Cucumis melo L.). Theor Appl Genet 117:1345–1359Danin-Poleg Y, Reis N, Tzuri G, Katzir N (2001) Development and characterization of microsatellite markers in Cucumis. Theor Appl Genet 102:61–72Diaz A, Fergany M, Formisano G, Ziarsolo P, Blanca J, Fei ZJ, Staub JE, Zalapa JE, Cuevas HE, Dace G, Oliver M, Boissot N, Dogimont C, Pitrat M, Hofstede R, van Koert P, Harel-Beja R, Tzuri G, Portnoy V, Cohen S, Schaffer A, Katzir N, Xu Y, Zhang HY, Fukino N, Matsumoto S, Garcia-Mas J, Monforte AJ (2011) A consensus linkage map for molecular markers and quantitative trait loci associated with economically important traits in melon (Cucumis melo L.). BMC Plant Biol 11:111Diaz A, Zarouri B, Fergany M, Eduardo I, Alvarez JM, Pico B, Monforte AJ (2014) Mapping and introgression of QTL involved in fruit shape transgressive segregation into ‘Piel de Sapo’ melon (Cucumis melo L.). PLoS One 9:e104188Eduardo I, Arus P, Monforte AJ, Obando J, Fernandez-Trujillo JP, Martinez JA, Alarcon AL, Alvarez JM, van der Knaap E (2007) Estimating the genetic architecture of fruit quality traits in melon using a genomic library of near isogenic lines. J Am Soc Hort Sci 132:80–89Fernandez-Silva I, Eduardo I, Blanca J, Esteras C, Pico B, Nuez F, Arus P, Garcia-Mas J, Monforte AJ (2008) Bin mapping of genomic and EST-derived SSRs in melon (Cucumis melo L.). Theor Appl Genet 118:139–150Fernandez-Trujillo JP, Picó P, Garcia-Mas J, Álvarez JM, Monforte AJ (2011) Breeding for fruit quality in melon. In: Jenks MA, Bebeli PJ (eds) Breeding for fruit quality. Wiley-Blackwell, West Sussex, pp 261–275Fukino N, Ohara T, Monforte AJ, Sugiyama M, Sakata Y, Kunihisa M, Matsumoto S (2008) Identification of QTLs for resistance to powdery mildew and SSR markers diagnostic for powdery mildew resistance genes in melon (Cucumis melo L.). Theor Appl Genet 118:165–175Garcia-Mas J, Benjak A, Sanseverino W, Bourgeois M, Mir G, Gonzalez VM, Henaff E, Camara F, Cozzuto L, Lowy E, Alioto T, Capella-Gutierrez S, Blanca J, Canizares J, Ziarsolo P, Gonzalez-Ibeas D, Rodriguez-Moreno L, Droege M, Du L, Alvarez-Tejado M, Lorente-Galdos B, Mele M, Yang LM, Weng YQ, Navarro A, Marques-Bonet T, Aranda MA, Nuez F, Pico B, Gabaldon T, Roma G, Guigo R, Casacuberta JM, Arus P, Puigdomenech P (2012) The genome of melon (Cucumis melo L.). Proc Natl Acad Sci USA 109:11872–11877Goff SA, Schnable JC, Feldmann KA (2014) The evolution of plant gene and genome sequencing. In: Paterson AH (ed) Genomes of herbaceous land plants. Academic Press, London, pp 47–90Gonzalo MJ, Oliver M, Garcia-Mas J, Monfort A, Dolcet-Sanjuan R, Katzir N, Arus P, Monforte AJ (2005) Simple-sequence repeat (SSR) markers used in merging linkage maps of melon (Cucumis melo L.). 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Nat Genet 41:1275–1281Leida C, Moser C, Esteras C, Sulpice R, Lunn JE, de Langen F, Monforte AJ, 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 16:28Monforte AJ, Oliver M, Gonzalo MJ, Alvarez JM, Dolcet-Sanjuan R, Arus P (2004) Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.). Theor Appl Genet 108:750–758Monforte AJ, Diaz A, Cano-Delgado A, van der Knaap E (2014) The genetic basis of fruit morphology in horticultural crops: lessons from tomato and melon. J Exp Bot 65:4625–4637Perin C, Hagen LS, Giovinazzo N, Besombes D, Dogimont C, Pitrat M (2002) Genetic control of fruit shape acts prior to anthesis in melon (Cucumis melo L.). Mol Genet Genomics 266:933–941Pitrat M (2008) Melon. In: Prohens J, Nuez F (eds) Handbook of plant breeding. Vegetable I. 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ETHQV6.3 is involved in melon climacteric fruit ripening and is encoded by a NAC domain transcription factor
Fruit ripening is divided into climacteric and non-climacteric types depending on the presence or absence of a transient rise in respiration rate and the production of autocatalytic ethylene. Melon is ideal for the study of fruit ripening, as both climacteric and non-climacteric varieties exist. Two introgressions of the non-climacteric accession PI 161375, encompassed in the QTLs ETHQB3.5 and ETHQV6.3, into the non-climacteric 'Piel de Sapo' background are able to induce climacteric ripening independently. We report that the gene underlying ETHQV6.3 is MELO3C016540 (CmNAC-NOR), encoding a NAC (NAM, ATAF1,2, CUC2) transcription factor that is closely related to the tomato NOR (non-ripening) gene. CmNAC-NOR was functionally validated through the identification of two TILLING lines carrying non-synonymous mutations in the conserved NAC domain region. In an otherwise highly climacteric genetic background, both mutations provoked a significant delay in the onset of fruit ripening and in the biosynthesis of ethylene. The PI 161375 allele of ETHQV6.3 is similar to that of climacteric lines of the cantalupensis type and, when introgressed into the non-climacteric 'Piel de Sapo', partially restores its climacteric ripening capacity. CmNAC-NOR is expressed in fruit flesh of both climacteric and non-climacteric lines, suggesting that the causal mutation may not be acting at the transcriptional level. The use of a comparative genetic approach in a species with both climacteric and non-climacteric ripening is a powerful strategy to dissect the complex mechanisms regulating the onset of fruit ripening
Identification and Localization of a Rickettsia sp. in Bemisia tabaci (Homoptera: Aleyrodidae)
Whiteflies (Homoptera: Aleyrodidae) are sap-sucking insects that harbor “Candidatus Portiera aleyrodidarum,” an obligatory symbiotic bacterium which is housed in a special organ called the bacteriome. These insects are also home for a diverse facultative microbial community which may include Hamiltonella, Arsenophonus, Fritchea, Wolbachia, and Cardinium spp. In this study, the bacteria associated with a B biotype of the sweet potato whitefly Bemisia tabaci were characterized using molecular fingerprinting techniques, and a Rickettsia sp. was detected for the first time in this insect family. Rickettsia sp. distribution, transmission and localization were studied using PCR and fluorescence in situ hybridizations (FISH). Rickettsia was found in all 20 Israeli B. tabaci populations screened but not in all individuals within each population. A FISH analysis of B. tabaci eggs, nymphs, and adults revealed a unique concentration of Rickettsia around the gut and follicle cells, as well as a random distribution in the hemolymph. We postulate that the Rickettsia enters the oocyte together with the bacteriocytes, leaves these symbiont-housing cells when the egg is laid, multiplies and spreads throughout the egg during embryogenesis and, subsequently, disperses throughout the body of the hatching nymph, excluding the bacteriomes. Although the role Rickettsia plays in the biology of the whitefly is currently unknown, the vertical transmission on the one hand and the partial within-population infection on the other suggest a phenotype that is advantageous under certain conditions but may be deleterious enough to prevent fixation under others
A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)
A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via markerassisted selection (MAS). - Results: Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genòmic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genòmic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm. - Conclusions: Even though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection)