Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai
Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders....
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Haiying [verfasserIn] Wang, Hui [verfasserIn] Guo, Shaogui [verfasserIn] Ren, Yi [verfasserIn] Gong, Guoyi [verfasserIn] Weng, Yiqun [verfasserIn] Xu, Yong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Euphytica - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952, 186(2011), 2 vom: 06. Nov., Seite 329-342 |
|---|---|
| Übergeordnetes Werk: |
volume:186 ; year:2011 ; number:2 ; day:06 ; month:11 ; pages:329-342 |
| Links: |
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| DOI / URN: |
10.1007/s10681-011-0574-z |
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| Katalog-ID: |
SPR01241915X |
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| 245 | 1 | 0 | |a Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
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| 520 | |a Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. | ||
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| 700 | 1 | |a Weng, Yiqun |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Yong |e verfasserin |4 aut | |
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10.1007/s10681-011-0574-z doi (DE-627)SPR01241915X (SPR)s10681-011-0574-z-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Zhang, Haiying verfasserin aut Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 Wang, Hui verfasserin aut Guo, Shaogui verfasserin aut Ren, Yi verfasserin aut Gong, Guoyi verfasserin aut Weng, Yiqun verfasserin aut Xu, Yong verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 186(2011), 2 vom: 06. Nov., Seite 329-342 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:186 year:2011 number:2 day:06 month:11 pages:329-342 https://dx.doi.org/10.1007/s10681-011-0574-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 186 2011 2 06 11 329-342 |
| spelling |
10.1007/s10681-011-0574-z doi (DE-627)SPR01241915X (SPR)s10681-011-0574-z-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Zhang, Haiying verfasserin aut Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 Wang, Hui verfasserin aut Guo, Shaogui verfasserin aut Ren, Yi verfasserin aut Gong, Guoyi verfasserin aut Weng, Yiqun verfasserin aut Xu, Yong verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 186(2011), 2 vom: 06. Nov., Seite 329-342 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:186 year:2011 number:2 day:06 month:11 pages:329-342 https://dx.doi.org/10.1007/s10681-011-0574-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 186 2011 2 06 11 329-342 |
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10.1007/s10681-011-0574-z doi (DE-627)SPR01241915X (SPR)s10681-011-0574-z-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Zhang, Haiying verfasserin aut Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 Wang, Hui verfasserin aut Guo, Shaogui verfasserin aut Ren, Yi verfasserin aut Gong, Guoyi verfasserin aut Weng, Yiqun verfasserin aut Xu, Yong verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 186(2011), 2 vom: 06. Nov., Seite 329-342 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:186 year:2011 number:2 day:06 month:11 pages:329-342 https://dx.doi.org/10.1007/s10681-011-0574-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 186 2011 2 06 11 329-342 |
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10.1007/s10681-011-0574-z doi (DE-627)SPR01241915X (SPR)s10681-011-0574-z-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Zhang, Haiying verfasserin aut Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 Wang, Hui verfasserin aut Guo, Shaogui verfasserin aut Ren, Yi verfasserin aut Gong, Guoyi verfasserin aut Weng, Yiqun verfasserin aut Xu, Yong verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 186(2011), 2 vom: 06. Nov., Seite 329-342 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:186 year:2011 number:2 day:06 month:11 pages:329-342 https://dx.doi.org/10.1007/s10681-011-0574-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 186 2011 2 06 11 329-342 |
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10.1007/s10681-011-0574-z doi (DE-627)SPR01241915X (SPR)s10681-011-0574-z-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Zhang, Haiying verfasserin aut Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 Wang, Hui verfasserin aut Guo, Shaogui verfasserin aut Ren, Yi verfasserin aut Gong, Guoyi verfasserin aut Weng, Yiqun verfasserin aut Xu, Yong verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 186(2011), 2 vom: 06. Nov., Seite 329-342 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:186 year:2011 number:2 day:06 month:11 pages:329-342 https://dx.doi.org/10.1007/s10681-011-0574-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 186 2011 2 06 11 329-342 |
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Enthalten in Euphytica 186(2011), 2 vom: 06. Nov., Seite 329-342 volume:186 year:2011 number:2 day:06 month:11 pages:329-342 |
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Enthalten in Euphytica 186(2011), 2 vom: 06. Nov., Seite 329-342 volume:186 year:2011 number:2 day:06 month:11 pages:329-342 |
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Fingerprinting Genetic diversity Microsatellites Watermelon |
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Zhang, Haiying @@aut@@ Wang, Hui @@aut@@ Guo, Shaogui @@aut@@ Ren, Yi @@aut@@ Gong, Guoyi @@aut@@ Weng, Yiqun @@aut@@ Xu, Yong @@aut@@ |
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Matsum. & Nakai</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. 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|
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Zhang, Haiying |
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Zhang, Haiying ddc 630 bkl 48.58 misc Fingerprinting misc Genetic diversity misc Microsatellites misc Watermelon Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
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630 640 ASE 48.58 bkl Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai Fingerprinting (dpeaa)DE-He213 Genetic diversity (dpeaa)DE-He213 Microsatellites (dpeaa)DE-He213 Watermelon (dpeaa)DE-He213 |
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ddc 630 bkl 48.58 misc Fingerprinting misc Genetic diversity misc Microsatellites misc Watermelon |
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ddc 630 bkl 48.58 misc Fingerprinting misc Genetic diversity misc Microsatellites misc Watermelon |
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Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
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Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
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Zhang, Haiying Wang, Hui Guo, Shaogui Ren, Yi Gong, Guoyi Weng, Yiqun Xu, Yong |
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identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, citrullus lanatus thunb. matsum. & nakai |
| title_auth |
Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
| abstract |
Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. |
| abstractGer |
Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. |
| abstract_unstemmed |
Abstract Watermelon, Citrullus lanatus Thunb. Matsum. & Nakai is an important vegetable crop worldwide. Due to its narrow genetic base, detection and utilization of the genetic variations, cultivar identification and increasing genetic diversity are some important tasks for watermelon breeders. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for these purposes. In the present study, a core set of 23 highly informative SSR markers was developed for watermelon genetic diversity analysis. Based on whole genome sequencing of 17 watermelon inbred lines, we identified 3.9 million single nucleotide polymorphisms (SNPs) which were used to construct a SNP-based dendrogram for the 17 lines. Meanwhile, from the sequenced genome, 13,744 SSRs were developed, of which 704 were placed on a high-resolution watermelon linkage map. To develop the core set SSR markers, 78 of the 704 mapped SSRs were selected as the candidate markers. Using the SNP-based dendrogram as calibration, 23 SSR markers evenly distributed across the genome were identified as the core marker set for watermelon genetic diversity analysis. Each marker was able to detect 2–7 alleles with polymorphism information content values ranging from 0.45 to 0.82. The dendrograms of 17 watermelon lines based on SNPs, the base set of 78 SSRs and the core set of 23 SSRs were highly consistent. The utility of this core set SSRs was demonstrated in 100 commercial watermelon cultivars and elite lines, which could be placed into six clusters that were largely consistent with previous classification based on morphology and parentage data. This core set of SSR markers should be very useful for genotyping and genetic variation analysis in watermelon. |
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Identification and validation of a core set of microsatellite markers for genetic diversity analysis in watermelon, Citrullus lanatus Thunb. Matsum. & Nakai |
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| score |
7.4001083 |