月季品种分子鉴定与遗传关系分析
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摘要
植物品种保护是一种新型的知识产权，主要宗旨是保护育种者合理权益。植物品种保护在不断发展的过程中也面临一些问题，与结合现代生物技术成为了未来植物品种保护实践工作的重要主题，分子标记技术在植物新品种保护中有着广阔的应用前景。本研究首先应用了现有的植物新品种DUS测试体系中的形态学性状调查方法分析月季栽培品种，其次采用SSR和AFLP分子标记技术开展了月季栽培品种分子鉴定研究和不同月季栽培群体的遗传关系分析，初步建立了以SSR标记为技术基础的月季栽培品种分子鉴定体系，为将来SSR标记应用于月季品种侵权繁殖材料的快速鉴定、已知品种和授权品种DNA指纹数据库构建等工作奠定技术基础并完成前期数据积累；也为未来月季新品种培育、种质资源保存等工作提供科学依据，主要研究结果：
1.参考蔷薇属DUS测试指南，通过田间调查方法，研究了DUS测试性状在杂交茶香月季，微型月季以及多花月季群体间的表型多样性。研究结果显示：43个DUS测试性状共检测出162个等位变异，每个性状上等位变异范围为1~14，变异数均值为3.767；多态性位点（性状）数量为40，多态性比率为93.02%；有效等位变异数量介于1~7.365，均值为2.358；Shannon’s信息指数介于0~2.274之间，平均值为0.895。Nei’s遗传多样度平均值为0.487，变幅介于0~0.864之间。聚类分析和主成份分析结果表明，不同园艺组月季品种间遗传差异较大，但是也存在品种渗透现象。
2. SSR标记多态性分析结果表明：41个位点上共检测到460个等位基因变异，等位基因变异数量介于为2~19个，平均每个位点等位基因数为11.2个；17个基因组SSR平均每个等位位点产生13.6个等位基因，24个EST-SSR平均每个位点产生9.5个等位基因；有效等位基因数量介于1.994~8.286，位点Rw55E12有效等位基因数量最多为8.286；41个SSR位点的等位基因表现型数量介于3~92之间；多态性信息含量变化范围在0.498~0.864之间。结果表明筛选的SSR位点具有良好的多态性，基因组SSR多态性高于EST-SSR。
3.基于SSR标记的月季品种分子鉴定结果表明：41个位点品种鉴定分辨率存在明显差异，41个位点的特异等位基因表现型数目介于0~67之间，单位点品种特殊等位基因表型数量最多的是位点Rw10M24，最少的是H1F03；41个位点的品种鉴别力Dj范围介于0.315~0.988，品种鉴别力最小的是位点H1F03，品种鉴别力最大的是位点CTG623和Rw55E12。Rosa ‘Twenty Fifth’和Rosa ‘Peter Beals’，Rosa ‘Mary Rose’和Rosa ‘WinchesterCathedral’以及中国古老月季‘绿萼’和Rosa ‘Old Blush’在41个SSR位点上具有相同等位基因表型。而区分其余品种最少需要3个SSR位点，如位点RA013a，RA043a与Rw5D11组合，位点P1，Rw8B8与Rw59A12组合，位点Rw10M24，Rw5D11与位点CTG21组合等。研究结果显示，芽变品种与原始品种的SSR指纹具有高度一致性，而杂交月季品种之间SSR指纹差异明显。
4.基于SSR标记的不同园艺组月季品种遗传关系研究结果显示：聚类分析将月季品种大致分为6类，第I聚类群主要包括了13个中国月季(Rosa ‘Chinas’)以及少数灌木月季(Rosa ‘Shrub’)；第Ⅱ聚类群以杂交茶香月季(Rosa ‘Hybrid Tea’)为主；第Ⅲ聚类群包含3个杂交茶香月季，2个灌木月季，1个多花月季和藤本月季；第Ⅳ聚类群以矮灌木小花月季(Rosa ‘Polyantha’)和灌木月季为主，还包含杂交玫瑰(Rosa rugosa)；第Ⅴ聚类群包含多数灌木月季；第Ⅵ聚类群由杂交茶香月季和微型月季(Rosa ‘Mininature’)组成。结果表明起源相同，亲缘关系较近的品种聚为一类，聚类结果与传统园艺分类之间具有较好的相似性。表型遗传差异与基于SSR标记的分子遗传差异相关性分析结果显示，两者之间存在弱相关，相关系数r为0.321。
5.基于AFLP月季品种鉴定和遗传关系分析结果显示，14对AFLP引物组合共扩增出1803条片段，其中多态性片段1727条，多态性比率为95.78%；品种间Dice遗传距离范围介于0.111~0.631之间，结果表明基于AFLP分子标记技术，使用遗传距离进行品种分子鉴定是有效、可行的；具有相同杂交亲本的品种和亲缘关系近的品种之间遗传距离小，也证实了AFLP是用于品种鉴定有效检测方法。基于AFLP的聚类分析和主成份分析结果与SSR标记结果类似，不同园艺组月季之间遗传差异较大，而且组内遗传变异明显。基于AFLP标记和SSR标记遗传距离矩阵间相关性分析结果显示，两者间存在弱相关，相关性系数r为0.323。
6.基于微卫星标记的9个遗传相似系数比较结果显示，9个遗传相似系数之间的相关系数介于0.735~1.000之间；共表型相关系数rc介于0.835~0.923；基于不同遗传相似系数的聚类树状图之间的CIc指数范围介于0.404~1.000之间，结果表明选择不同的遗传相似系数进行聚类分析，结果差异较大；不同遗传相似系数的S统计值介于17.19~27.92%之间，Russel and Rao系数的S值最低为17.19%，Russel and Rao等四个系数的拟合优度处于同一个水平。综合考虑SSR标记特性、Kruskal判定标准、相似系数计算原理等因素，并结合聚类分析和谱系分析比较结果，研究认为Dice系数、Jaccard系数、Ochiai系数比较适用于月季SSR遗传分析，其次是Simple Matching系数；而在遗传分析中最好避免使用Russel and Rao系数，Yule系数，Phi系数，Hamann系数。
Plant variety protection (PVP) is a novel system of intellectual property rights protection，which is aimed to protect the right of plant breeders. Some problems were emerged in theprocess of development of PVP, such as rapid identification of origin of plant materials,reducing the cycle of variety test, and molecular biology techniques become the most importanttools in practical operations of PVP. The potential applications of molecular marker techniquesare promising in PVP system. In this study, firstly morphological traits in DUS test wasinvestigated to evaluate phenotypic diversity of rose varieties; secondly SSR and AFLPmarkers were used to identify rose varieties and analyze genetic relationships among thevarieties. A preliminary identification system for rose varieties was established using SSRmarkers. It can be used for rapid identification of propagating materials for infringement cases,moreover it is an ideal approach to construction databases of DNA profiles of commonknowledge and protected varieties. Analysis of genetic relationship could supply some supplyscientific evidence for rose variety breeding and conservation of germplasm resource.
1. According to the Rosa guideline for the conduct of test for DUS, the phonotypicaldiversity of Rosa ‘Hybrid Tea’, Rosa ‘Miniature’ and Rosa ‘Floribunda’ was investigated bymeans of field surveys. The result showed that162allele variants were detected in43traits, thenumber of allels in each trait ranged from1to14with an average of3.767; the number ofpolymorphic trait (loci) was40, the ratio of polymorphism is93.02%; the number of effectivealleles per locus ranged from1to7.365with an average of2.358; Shannon information indexranged from0to2.274with an average of0.895and Nei’s genetic diversity index ranged from0to0.864with an average of0.487. The cluster analysis and principal component analysisindicated that genetic variation was evident among different horticultural rose groups, but afew varieties were overlapped among different horticultural groups.
2. Analysis of polymorphism in SSR loci showed that460allele variants were detected in41SSR loci, the number of alleles at each locus ranged from2to19with an average of11.2; the average number of allele variants was13.6at17genomic SSR loci, and9.5at24EST-SSRloci; the number of effective alleles ranged from1.994to8.286at41loci, the greatest numberwas found at locus Rw55E12; the number of allelic phenotypes range from3to92, the valueof polymorphic information content ranged from0.498~0.864. It indicated that thepolymorphism of SSR locus was reliable, and genomic SSR was superior to EST-SSR.
3. Molecular identification of rose varieties based on SSR marker showed that thediscriminating power was flexible at41SSR loci; the number of unique allelic phenotypesrange from0to67, and the largest was at Rw10M24, the least was at H1F03, the value of Djranged from0.315~0.988, the loci with largest values were CTG623and Rw55E12, the leastwas H1F03; three pairs of rose varieties shared the same allelic phenotype at41SSR loci,respectively; three SSR loci were necessary to discriminate the rest rose varieties completely atleast, such as combination of RA013a，RA043a and Rw5D11, combination of P1，Rw8B8andRw59A12, and combination of Rw10M24，Rw5D11and CTG21. It was found that the SSRDNA profiles were identical between the original rose variety and its mutatant varieties, andthe divergence of SSR DNA profiles among hybrid varieties was obvious. It was suggested thatSSR molecular marker are feasible in rapid identification of plant varieties.
4. The result of analysis of different horticultural rose groups showed that all sampleswere divided into six groups. The first group included13varieties of Rosa ‘Chinas’ and a fewones of Rosa ‘Shrub’; the second group was mainly made up of the varieties of Rosa ‘Hybridtea’; the third group consisted of a few varieties of Rosa ‘Hybrid Tea’, Rosa ‘Floribunda’, Rosa‘Shrub’ and Rosa ‘Climber’; the forth group included those of Rosa ‘Polyantha’ and some ofRosa ‘Shrub’; the fifth group consisted of most varieties of Rosa ‘Shrub’; the sixth groupincluded those of Rosa ‘Mininature’ and Rosa ‘Hybrid Tea’. It was suggested that commonorigin and related rose varieties be clustered together based on SSR molecular markers. Theresult of clustering and principal components analysis based on molecular markers was similarto horticultural group in part. The result of correlation analysis between morphological dataand SSR data showed weak correlation, with a correlation coefficient of0.321.
5. The result of variety identification and analysis of genetic relationship showed that1803DNA fragments were amplified in14primer combinations,1727fragments werepolymorphic, and percentage of polymorphic bands was93.02%; pairwise Dice dissimilarityin rose varieties ranged from0.111to0.631, it suggested that the genetic dissimilarity based onAFLP markers can be used for variety identification. The genetic dissimilarity of full-sibsfamily variety and related variety was small, which confirmed that AFLP is an effective tool forvariety identification. The result of clustering and principal components analysis based onAFLP markers was similar to the result on SSR markers; genetic divergence betweenhorticultural groups was distinct, but genetic differences in horticultural group was present.Correlation analysis indicated that there was a weak correlation between AFLP marker data andSSR marker data, with a correlation coefficient of0.323.
6. Comparison of different genetic similarity coefficients based on microsatellite markersshowed, pairwise correlation coefficient ranged from0.735to1.000; cophenetic correlationcoefficient ranged from0.835to0.923; consensus fork index (CIc) between differentdendrograms which were constructed by different genetic similarity coefficients ranged from0.404to1.000, it indicated that the result of clustering varied according to different coefficients.The value of STRESS ranged from17.19~27.92%, Russell and Rao coefficient, Dicecoefficient, Jaccard coefficient and Ochiai coefficient were at the same level. Considering suchcharacteristics as molecular markers, analysis of goodness of fit, algorithm of coefficients, andcomparison between result of clustering and lineage analysis, it was suggested that Dicecoefficient, Jaccard coefficient and Ochiai coefficient are most appropriate for genetic analysisbased on microsatellite data from roses, and the next appropriate was the Simple Matchingcoefficient. Russell and Rao coefficient, Yule coefficient, Hamann coefficient and Phicoefficient should be avoided as much as possible.
1.参考蔷薇属DUS测试指南，通过田间调查方法，研究了DUS测试性状在杂交茶香月季，微型月季以及多花月季群体间的表型多样性。研究结果显示：43个DUS测试性状共检测出162个等位变异，每个性状上等位变异范围为1~14，变异数均值为3.767；多态性位点（性状）数量为40，多态性比率为93.02%；有效等位变异数量介于1~7.365，均值为2.358；Shannon’s信息指数介于0~2.274之间，平均值为0.895。Nei’s遗传多样度平均值为0.487，变幅介于0~0.864之间。聚类分析和主成份分析结果表明，不同园艺组月季品种间遗传差异较大，但是也存在品种渗透现象。
2. SSR标记多态性分析结果表明：41个位点上共检测到460个等位基因变异，等位基因变异数量介于为2~19个，平均每个位点等位基因数为11.2个；17个基因组SSR平均每个等位位点产生13.6个等位基因，24个EST-SSR平均每个位点产生9.5个等位基因；有效等位基因数量介于1.994~8.286，位点Rw55E12有效等位基因数量最多为8.286；41个SSR位点的等位基因表现型数量介于3~92之间；多态性信息含量变化范围在0.498~0.864之间。结果表明筛选的SSR位点具有良好的多态性，基因组SSR多态性高于EST-SSR。
3.基于SSR标记的月季品种分子鉴定结果表明：41个位点品种鉴定分辨率存在明显差异，41个位点的特异等位基因表现型数目介于0~67之间，单位点品种特殊等位基因表型数量最多的是位点Rw10M24，最少的是H1F03；41个位点的品种鉴别力Dj范围介于0.315~0.988，品种鉴别力最小的是位点H1F03，品种鉴别力最大的是位点CTG623和Rw55E12。Rosa ‘Twenty Fifth’和Rosa ‘Peter Beals’，Rosa ‘Mary Rose’和Rosa ‘WinchesterCathedral’以及中国古老月季‘绿萼’和Rosa ‘Old Blush’在41个SSR位点上具有相同等位基因表型。而区分其余品种最少需要3个SSR位点，如位点RA013a，RA043a与Rw5D11组合，位点P1，Rw8B8与Rw59A12组合，位点Rw10M24，Rw5D11与位点CTG21组合等。研究结果显示，芽变品种与原始品种的SSR指纹具有高度一致性，而杂交月季品种之间SSR指纹差异明显。
4.基于SSR标记的不同园艺组月季品种遗传关系研究结果显示：聚类分析将月季品种大致分为6类，第I聚类群主要包括了13个中国月季(Rosa ‘Chinas’)以及少数灌木月季(Rosa ‘Shrub’)；第Ⅱ聚类群以杂交茶香月季(Rosa ‘Hybrid Tea’)为主；第Ⅲ聚类群包含3个杂交茶香月季，2个灌木月季，1个多花月季和藤本月季；第Ⅳ聚类群以矮灌木小花月季(Rosa ‘Polyantha’)和灌木月季为主，还包含杂交玫瑰(Rosa rugosa)；第Ⅴ聚类群包含多数灌木月季；第Ⅵ聚类群由杂交茶香月季和微型月季(Rosa ‘Mininature’)组成。结果表明起源相同，亲缘关系较近的品种聚为一类，聚类结果与传统园艺分类之间具有较好的相似性。表型遗传差异与基于SSR标记的分子遗传差异相关性分析结果显示，两者之间存在弱相关，相关系数r为0.321。
5.基于AFLP月季品种鉴定和遗传关系分析结果显示，14对AFLP引物组合共扩增出1803条片段，其中多态性片段1727条，多态性比率为95.78%；品种间Dice遗传距离范围介于0.111~0.631之间，结果表明基于AFLP分子标记技术，使用遗传距离进行品种分子鉴定是有效、可行的；具有相同杂交亲本的品种和亲缘关系近的品种之间遗传距离小，也证实了AFLP是用于品种鉴定有效检测方法。基于AFLP的聚类分析和主成份分析结果与SSR标记结果类似，不同园艺组月季之间遗传差异较大，而且组内遗传变异明显。基于AFLP标记和SSR标记遗传距离矩阵间相关性分析结果显示，两者间存在弱相关，相关性系数r为0.323。
6.基于微卫星标记的9个遗传相似系数比较结果显示，9个遗传相似系数之间的相关系数介于0.735~1.000之间；共表型相关系数rc介于0.835~0.923；基于不同遗传相似系数的聚类树状图之间的CIc指数范围介于0.404~1.000之间，结果表明选择不同的遗传相似系数进行聚类分析，结果差异较大；不同遗传相似系数的S统计值介于17.19~27.92%之间，Russel and Rao系数的S值最低为17.19%，Russel and Rao等四个系数的拟合优度处于同一个水平。综合考虑SSR标记特性、Kruskal判定标准、相似系数计算原理等因素，并结合聚类分析和谱系分析比较结果，研究认为Dice系数、Jaccard系数、Ochiai系数比较适用于月季SSR遗传分析，其次是Simple Matching系数；而在遗传分析中最好避免使用Russel and Rao系数，Yule系数，Phi系数，Hamann系数。
Plant variety protection (PVP) is a novel system of intellectual property rights protection，which is aimed to protect the right of plant breeders. Some problems were emerged in theprocess of development of PVP, such as rapid identification of origin of plant materials,reducing the cycle of variety test, and molecular biology techniques become the most importanttools in practical operations of PVP. The potential applications of molecular marker techniquesare promising in PVP system. In this study, firstly morphological traits in DUS test wasinvestigated to evaluate phenotypic diversity of rose varieties; secondly SSR and AFLPmarkers were used to identify rose varieties and analyze genetic relationships among thevarieties. A preliminary identification system for rose varieties was established using SSRmarkers. It can be used for rapid identification of propagating materials for infringement cases,moreover it is an ideal approach to construction databases of DNA profiles of commonknowledge and protected varieties. Analysis of genetic relationship could supply some supplyscientific evidence for rose variety breeding and conservation of germplasm resource.
1. According to the Rosa guideline for the conduct of test for DUS, the phonotypicaldiversity of Rosa ‘Hybrid Tea’, Rosa ‘Miniature’ and Rosa ‘Floribunda’ was investigated bymeans of field surveys. The result showed that162allele variants were detected in43traits, thenumber of allels in each trait ranged from1to14with an average of3.767; the number ofpolymorphic trait (loci) was40, the ratio of polymorphism is93.02%; the number of effectivealleles per locus ranged from1to7.365with an average of2.358; Shannon information indexranged from0to2.274with an average of0.895and Nei’s genetic diversity index ranged from0to0.864with an average of0.487. The cluster analysis and principal component analysisindicated that genetic variation was evident among different horticultural rose groups, but afew varieties were overlapped among different horticultural groups.
2. Analysis of polymorphism in SSR loci showed that460allele variants were detected in41SSR loci, the number of alleles at each locus ranged from2to19with an average of11.2; the average number of allele variants was13.6at17genomic SSR loci, and9.5at24EST-SSRloci; the number of effective alleles ranged from1.994to8.286at41loci, the greatest numberwas found at locus Rw55E12; the number of allelic phenotypes range from3to92, the valueof polymorphic information content ranged from0.498~0.864. It indicated that thepolymorphism of SSR locus was reliable, and genomic SSR was superior to EST-SSR.
3. Molecular identification of rose varieties based on SSR marker showed that thediscriminating power was flexible at41SSR loci; the number of unique allelic phenotypesrange from0to67, and the largest was at Rw10M24, the least was at H1F03, the value of Djranged from0.315~0.988, the loci with largest values were CTG623and Rw55E12, the leastwas H1F03; three pairs of rose varieties shared the same allelic phenotype at41SSR loci,respectively; three SSR loci were necessary to discriminate the rest rose varieties completely atleast, such as combination of RA013a，RA043a and Rw5D11, combination of P1，Rw8B8andRw59A12, and combination of Rw10M24，Rw5D11and CTG21. It was found that the SSRDNA profiles were identical between the original rose variety and its mutatant varieties, andthe divergence of SSR DNA profiles among hybrid varieties was obvious. It was suggested thatSSR molecular marker are feasible in rapid identification of plant varieties.
4. The result of analysis of different horticultural rose groups showed that all sampleswere divided into six groups. The first group included13varieties of Rosa ‘Chinas’ and a fewones of Rosa ‘Shrub’; the second group was mainly made up of the varieties of Rosa ‘Hybridtea’; the third group consisted of a few varieties of Rosa ‘Hybrid Tea’, Rosa ‘Floribunda’, Rosa‘Shrub’ and Rosa ‘Climber’; the forth group included those of Rosa ‘Polyantha’ and some ofRosa ‘Shrub’; the fifth group consisted of most varieties of Rosa ‘Shrub’; the sixth groupincluded those of Rosa ‘Mininature’ and Rosa ‘Hybrid Tea’. It was suggested that commonorigin and related rose varieties be clustered together based on SSR molecular markers. Theresult of clustering and principal components analysis based on molecular markers was similarto horticultural group in part. The result of correlation analysis between morphological dataand SSR data showed weak correlation, with a correlation coefficient of0.321.
5. The result of variety identification and analysis of genetic relationship showed that1803DNA fragments were amplified in14primer combinations,1727fragments werepolymorphic, and percentage of polymorphic bands was93.02%; pairwise Dice dissimilarityin rose varieties ranged from0.111to0.631, it suggested that the genetic dissimilarity based onAFLP markers can be used for variety identification. The genetic dissimilarity of full-sibsfamily variety and related variety was small, which confirmed that AFLP is an effective tool forvariety identification. The result of clustering and principal components analysis based onAFLP markers was similar to the result on SSR markers; genetic divergence betweenhorticultural groups was distinct, but genetic differences in horticultural group was present.Correlation analysis indicated that there was a weak correlation between AFLP marker data andSSR marker data, with a correlation coefficient of0.323.
6. Comparison of different genetic similarity coefficients based on microsatellite markersshowed, pairwise correlation coefficient ranged from0.735to1.000; cophenetic correlationcoefficient ranged from0.835to0.923; consensus fork index (CIc) between differentdendrograms which were constructed by different genetic similarity coefficients ranged from0.404to1.000, it indicated that the result of clustering varied according to different coefficients.The value of STRESS ranged from17.19~27.92%, Russell and Rao coefficient, Dicecoefficient, Jaccard coefficient and Ochiai coefficient were at the same level. Considering suchcharacteristics as molecular markers, analysis of goodness of fit, algorithm of coefficients, andcomparison between result of clustering and lineage analysis, it was suggested that Dicecoefficient, Jaccard coefficient and Ochiai coefficient are most appropriate for genetic analysisbased on microsatellite data from roses, and the next appropriate was the Simple Matchingcoefficient. Russell and Rao coefficient, Yule coefficient, Hamann coefficient and Phicoefficient should be avoided as much as possible.
引文
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