A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.)
Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA p...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jones, E. S. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Schlagwörter: |
Single Nucleotide Polymorphism Single Nucleotide Polymorphism Marker |
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| Anmerkung: |
© Springer-Verlag 2007 |
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| Übergeordnetes Werk: |
Enthalten in: Theoretical and applied genetics - Berlin : Springer, 1929, 115(2007), 3 vom: 22. Mai, Seite 361-371 |
|---|---|
| Übergeordnetes Werk: |
volume:115 ; year:2007 ; number:3 ; day:22 ; month:05 ; pages:361-371 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00122-007-0570-9 |
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| Katalog-ID: |
SPR000956686 |
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| 100 | 1 | |a Jones, E. S. |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
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| 520 | |a Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. | ||
| 650 | 4 | |a Single Nucleotide Polymorphism |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Simple Sequence Repeat Marker |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Smith, J. S. C. |4 aut | |
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10.1007/s00122-007-0570-9 doi (DE-627)SPR000956686 (SPR)s00122-007-0570-9-e DE-627 ger DE-627 rakwb eng Jones, E. S. verfasserin aut A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2007 Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 Sullivan, H. aut Bhattramakki, D. aut Smith, J. S. C. aut Enthalten in Theoretical and applied genetics Berlin : Springer, 1929 115(2007), 3 vom: 22. Mai, Seite 361-371 (DE-627)27117563X (DE-600)1478966-8 1432-2242 nnns volume:115 year:2007 number:3 day:22 month:05 pages:361-371 https://dx.doi.org/10.1007/s00122-007-0570-9 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_101 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 115 2007 3 22 05 361-371 |
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10.1007/s00122-007-0570-9 doi (DE-627)SPR000956686 (SPR)s00122-007-0570-9-e DE-627 ger DE-627 rakwb eng Jones, E. S. verfasserin aut A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2007 Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 Sullivan, H. aut Bhattramakki, D. aut Smith, J. S. C. aut Enthalten in Theoretical and applied genetics Berlin : Springer, 1929 115(2007), 3 vom: 22. Mai, Seite 361-371 (DE-627)27117563X (DE-600)1478966-8 1432-2242 nnns volume:115 year:2007 number:3 day:22 month:05 pages:361-371 https://dx.doi.org/10.1007/s00122-007-0570-9 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_101 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 115 2007 3 22 05 361-371 |
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10.1007/s00122-007-0570-9 doi (DE-627)SPR000956686 (SPR)s00122-007-0570-9-e DE-627 ger DE-627 rakwb eng Jones, E. S. verfasserin aut A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2007 Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 Sullivan, H. aut Bhattramakki, D. aut Smith, J. S. C. aut Enthalten in Theoretical and applied genetics Berlin : Springer, 1929 115(2007), 3 vom: 22. Mai, Seite 361-371 (DE-627)27117563X (DE-600)1478966-8 1432-2242 nnns volume:115 year:2007 number:3 day:22 month:05 pages:361-371 https://dx.doi.org/10.1007/s00122-007-0570-9 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_101 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 115 2007 3 22 05 361-371 |
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10.1007/s00122-007-0570-9 doi (DE-627)SPR000956686 (SPR)s00122-007-0570-9-e DE-627 ger DE-627 rakwb eng Jones, E. S. verfasserin aut A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2007 Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 Sullivan, H. aut Bhattramakki, D. aut Smith, J. S. C. aut Enthalten in Theoretical and applied genetics Berlin : Springer, 1929 115(2007), 3 vom: 22. Mai, Seite 361-371 (DE-627)27117563X (DE-600)1478966-8 1432-2242 nnns volume:115 year:2007 number:3 day:22 month:05 pages:361-371 https://dx.doi.org/10.1007/s00122-007-0570-9 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_101 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 115 2007 3 22 05 361-371 |
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10.1007/s00122-007-0570-9 doi (DE-627)SPR000956686 (SPR)s00122-007-0570-9-e DE-627 ger DE-627 rakwb eng Jones, E. S. verfasserin aut A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2007 Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 Sullivan, H. aut Bhattramakki, D. aut Smith, J. S. C. aut Enthalten in Theoretical and applied genetics Berlin : Springer, 1929 115(2007), 3 vom: 22. Mai, Seite 361-371 (DE-627)27117563X (DE-600)1478966-8 1432-2242 nnns volume:115 year:2007 number:3 day:22 month:05 pages:361-371 https://dx.doi.org/10.1007/s00122-007-0570-9 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_101 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_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 115 2007 3 22 05 361-371 |
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Enthalten in Theoretical and applied genetics 115(2007), 3 vom: 22. Mai, Seite 361-371 volume:115 year:2007 number:3 day:22 month:05 pages:361-371 |
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S.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2007</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="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 2007</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single Nucleotide Polymorphism</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simple Sequence Repeat Marker</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single Nucleotide Polymorphism Marker</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single Nucleotide Polymorphism Locus</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single Nucleotide Polymorphism Discovery</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sullivan, H.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bhattramakki, D.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Smith, J. 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|
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Jones, E. S. |
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Jones, E. S. misc Single Nucleotide Polymorphism misc Simple Sequence Repeat Marker misc Single Nucleotide Polymorphism Marker misc Single Nucleotide Polymorphism Locus misc Single Nucleotide Polymorphism Discovery A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
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A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) Single Nucleotide Polymorphism (dpeaa)DE-He213 Simple Sequence Repeat Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Marker (dpeaa)DE-He213 Single Nucleotide Polymorphism Locus (dpeaa)DE-He213 Single Nucleotide Polymorphism Discovery (dpeaa)DE-He213 |
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misc Single Nucleotide Polymorphism misc Simple Sequence Repeat Marker misc Single Nucleotide Polymorphism Marker misc Single Nucleotide Polymorphism Locus misc Single Nucleotide Polymorphism Discovery |
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misc Single Nucleotide Polymorphism misc Simple Sequence Repeat Marker misc Single Nucleotide Polymorphism Marker misc Single Nucleotide Polymorphism Locus misc Single Nucleotide Polymorphism Discovery |
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misc Single Nucleotide Polymorphism misc Simple Sequence Repeat Marker misc Single Nucleotide Polymorphism Marker misc Single Nucleotide Polymorphism Locus misc Single Nucleotide Polymorphism Discovery |
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A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
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A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
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Jones, E. S. |
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Theoretical and applied genetics |
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Jones, E. S. Sullivan, H. Bhattramakki, D. Smith, J. S. C. |
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Elektronische Aufsätze |
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Jones, E. S. |
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10.1007/s00122-007-0570-9 |
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comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (zea mays l.) |
| title_auth |
A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
| abstract |
Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. © Springer-Verlag 2007 |
| abstractGer |
Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. © Springer-Verlag 2007 |
| abstract_unstemmed |
Abstract We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY®, and invasive cleavage detected by Invader® chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1–3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually. © Springer-Verlag 2007 |
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| title_short |
A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.) |
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https://dx.doi.org/10.1007/s00122-007-0570-9 |
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Sullivan, H. Bhattramakki, D. Smith, J. S. C. |
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| score |
7.3998156 |