摘要
为了建立快速可视化检测绵羊生长分化因子9基因(Growth differentiation factor 9,GDF9)G1突变的方法,针对绵羊GDF9基因G1突变设计扩增阻滞突变系统(Amplification refractory mutation system,ARMS)特异性引物,并在其下游引物3′端的第2—4位碱基处设计额外的错配以筛选特异性最佳的引物对,将改良的ARMS与核酸染料SYBR GreenⅠ结合,可视化检测GDF9基因G1突变。结果显示,改良的ARMS特异性引物能够区分突变型和野生型,通过整合改良的ARMS与SYBR GreenⅠ可视化检测G1突变,发现已知突变型样本显示亮绿色,而已知野生型样本显示橙黄色,两者颜色变化明显。采用建立的可视化检测绵羊GDF9基因G1突变的方法检测25个小尾寒羊样本,结果表明,该方法能够准确区分绵羊GDF9基因G1突变的野生型和突变型,其检测结果与测序结果相符,准确度高达100%。可见,建立的可视化检测方法可用于检测绵羊GDF9基因G1突变。
In order to establish a rapid and visual method for detecting the G1 mutation of growth differentiation factor 9 gene(GDF9)in sheep,an amplification refractory mutation system(ARMS)specific primer pair for the G1 mutation of the GDF9 gene was designed,and additional mismatches at the 2nd to 4th bases at the 3′end of the downstream primers were designed respectively to screen for primer pair with the best specificity.The G1 mutation of the GDF9 gene was visually detected by combining the improved ARMS with the nucleic acid dye SYBR GreenⅠ.The results showed that the improved ARMS specific primers could distinguish between mutant genotype and wild type.The G1 mutation was visually detected by integrating the improved ARMS and SYBR GreenⅠ.It was found that the known mutant genotype sample showed bright green,while the known wild type sample showed orange yellow,and the color of the two changed significantly.Twenty five small tail Han sheep samples were detected by the established method for visually detecting the G1 mutation of the GDF9 gene in sheep,and the results revealed that the method could distinguish the wild type and mutant genotype of the G1 mutation of the GDF9 gene in sheep accurately.The detection results were consistent with the sequencing results,and the accuracy was as high as 100%.Therefore,the established visual detection method can be used to detect the G1 mutation of the GDF9 gene in sheep.
作者
刘莉
姚瑞
徐越仁
李慧向
张梦丹
胡圣伟
LIU Li;YAO Rui;XU Yueren;LI Huixiang;ZHANG Mengdan;HU Shengwei(College of Life Sciences,Shihezi University,Shihezi 832003,China)
出处
《河南农业科学》
北大核心
2020年第8期136-142,共7页
Journal of Henan Agricultural Sciences
基金
国家自然科学基金项目(31660644)
新疆生产建设兵团国际科技合作计划项目(2018BC011)。