摘要
以陕西省野生丹参为材料利用正交设计对MSAP预扩增和选择性扩增体系中关键因素优化筛选,以建立适合丹参的MSAP反应体系,并用于5个野生丹参居群表观遗传多样性分析.结果表明:25μL MSAP双酶切反应体系中加入EcoRⅠ和MspⅠ各10 U,37℃酶切8 h,酶切较充分;最佳预扩增反应体系25μL,包含连接产物2.5μL,Mg2+(25 mmol/L)1.0μL,dNTPs(2.5 mmol/L)2.0μL,Taq酶(5 U/μL)0.4μL,上下游引物E00/HM00(50ng/μL)各1.0μL;最佳选择性扩增反应体系25μL,包含稀释100倍的预扩增产物1.5μL,Mg2+(25 mmol/L)2.0μL,dNTPs(2.5 mmol/L)2.0μL,Taq酶(5 U/μL)0.1μL,上下游引物E-ACG/HM-CAA(50 ng/μL)各0.8μL.选用5对引物组合对5个野生丹参居群的50个单株进行表观遗传多样性分析,平均DNA甲基化多态性谱带为95.48%;UPGMA聚类分析结果表明,50个丹参单株在相似性系数0.58处可分为3大类.
The MSAP-PCR system was optimized through orthogonal design on several factors in its genomic DNA MSAP-PCR pre-amplification and selective amplification system with the wild immature leaves of Salvia miltiorrhiza from Shaanxi.The best reaction system of MSAP was obtained.Restriction digestion of genomic DNA was performed by using two restriction enzymes,around 500 ng DNA digested with 10 units of both EcoRⅠ and MspⅠ enzymes in a reaction volume of 25 μL,and incubated at 37℃ for 8 h.The 25 μL preamplification reaction mixture contained the follow factors,such as Mg2＋（25 mmol/L）1.0 μL,dNTPs（2.5 mmol/L）2.0 μL,DNA template 2.5 μL,Taq DNA polymerase（5 U/μL）0.4 μL,Primers E00/HM00 1.0 μL（50 ng/μL）,respectively.The pre-amplification products were diluted 100 times for the selective amplification.The 25 μL selective amplification reaction mixture contained Mg2＋（25 mmol/L）2.0 μL,dNTPs（2.5 mmol/L）2.0 μL,DNA template 1.5 μL,Taq DNA polymerase（5 U/μL）0.1 μL,Primers E-ACG/HM-CAA（50 ng/μL） 0.8 μL respectively.Five primers screened out from 88 primer combinations according to the reaction system as above were used for MSAP analysis.The result showed that the percentage of DNA polymorphic bands was 95.48%.When the coefficient was 0.58,50 individuals of S.miltiorrhiza can be clustered into three groups by Unweighted Pair Group Method.
出处
《西北植物学报》
CAS
CSCD
北大核心
2011年第5期920-928,共9页
Acta Botanica Boreali-Occidentalia Sinica
基金
陕西省自然科学基金(SJ08C227)
中央高校基本科研业务费(GK201002026)
关键词
丹参
MSAP分子标记
正交优化
遗传多样性
Salvia miltiorrhiza
MSAP molecular marker reaction
orthogonal optimization
genetic diversity
