摘要
本研究选用15对SSR引物对18个桉树品系的基因组DNA进行扩增。结果表明,15个SSR标记共检测到54个等位片段,其中,等位片段最多的位点是eSSR1145n2(8个等位片段)和Embra40(7个等位片段),最少的位点是eSSR1125(3个等位片段)和Embra49(2个等位片段)。平均每位点的等位片段(NA)、期望杂合度(He)以及多态信息量(PIC)分别为5.4、0.370和0.539。通过关联分析,发现高感桉树品系独有的等位基因主要集中在Embra77、eSSR410、eSSR0620、eSSR0845n及eSSR1145n2这5个位点上,而高抗桉树品系特有的等位基因则集中在Embra49、Embra53、Embra77、Embra87及eSSR1145n2这5个位点上。高感组以GA为主要拷贝单元,CT及GAA次之;高抗组以AG占优势,CT次之。按UPGMA法对18个品系进行聚类树状分析,将1~8号桉树品系各归为一类,9~18桉树品系则归为同一类。本研究中获得的高感和高抗特有的微卫星标记位点,可为下一步确定标记所在连锁群位置,获取有效关联基因提供有力基础。
In this study, 15 pairs of SSR primers were used to amplify the genomic DNA from 18 Eucalyptus strains. 54 alleles were detected in 15 SSR markers. Most frequent alleles were detected in eSSR1145n2 (8 alleles) and Embra40 (7 alleles), while least alleles were detected in eSSR1125 (3 alleiic fragments) and Embra49 (2 allelic fragments). The mean allele (NA), expected heterozygosity (He) and polymorphic information (PIC) of each locus were 5.4, 0.370 and 0.539, respectively. Through correlation analysis, we found that unique alleles of high-sensitivity Eucalyptus were mainly located in Embra77, eSSR410, eSSR0620, eSSR0845n and eSSR1145n2, while unique alleles of high-resistance Eucalyptus were mainly located in Embra49, Embra53, Embra77, Embra87 and eSSR1145n2. The high-sensitivity group took GA as the main copy unit, followed by CT and GAA; the high-resistance group took AG as the dominant, followed by CT. Cluster analysis of 18 strains was carried out through UPGMA method. Eucalyptus of No.l-8 were classified into one class and Eucalyptus of 9-18 were classified into the same class. The high-sensitivity and high-resistance specific microsatellite markers obtained in this study could provide a strong basis for determining the location of linkage groups and obtaining effective association genes.
出处
《基因组学与应用生物学》
CAS
CSCD
北大核心
2017年第4期1660-1666,共7页
Genomics and Applied Biology
基金
广西自然基金-青年基金项目(2014GXNSFBA118107)
广西林科院基本业务费-林科201404号
广西优良用材林资源培育实验室自主课题-13-A-03-01共同资助
关键词
SSR
枝瘿姬小蜂
等位片段
关联分析
聚类树状分析
SSR, Leptocybe invasa, Allelic fragment, Correlation analysis, Cluster tree analysis