摘要
高产优质育种是我国棉花育种的主要目标。寻找与目标性状关联的分子标记,可克服常规育种的盲目性,提高分子标记辅助选择育种的准确性。本研究对118份陆地棉种质资源的衣分、单铃重、单株铃数及子指等4个产量相关性状进行2年2点的表型鉴定,并利用覆盖全基因组的、有多态性的214对SSR标记进行标记与性状的关联分析。结果表明:118份材料的4个产量相关性状表型变异丰富,平均变异系数的变幅在6.1%~19.1%之间,且在各环境中表现较为稳定;基因型分析表明,214对标记共检测到460个等位变异,基因多样性指数平均为0.5151,PIC值平均为0.4587,表明该批标记具有较多的等位变异数和较高的基因多样性;群体结构分析表明该批材料可分为4个亚群,且各类群中材料与地理来源无对应关系;关联分析结果显示,在显著条件下(-log10P>1.3,P<0.05),共有39个标记位点能够在2个及2个以上的环境中同时检测到,其中有4个标记位点同时与2个以上性状相关联,进一步比较发现,有7个位点与前人研究结果一致,其余32个位点为新发现的位点。研究结果可为陆地棉产量性状遗传改良的分子标记辅助选择提供理论依据。
Improving cotton yield and fiber quality is a major breeding goal for Chinese upland cotton. Discovery molecular markers associated with the target traits can overcome the blindness of conventional breeding and improve the accuracy of molecular marker assisted selection breeding. In this study,a diversity panel consisting of118 upland cotton accessions was grown in four different environments,and the yield-related traits including lint percentage（ LP）,boll weight（ BW）,bolls per plant（ BN） and seed index（ SI） were measured,and 214 polymorphic SSR markers of covering the whole genome were performed in association mapping. Molecular marker data and four phenotypic traits were analyzed by the method of MLM（ mixed linear model） in Tassel 5. 0 on the basis of population structure,analysis loci with elite allelic variation and typical materials carrying elite alleles were identified based on phenotypic effect values. The results were showed： 118 upland cotton accessions were rich in phenotypic variation,the mean coefficients of variance（ CV） ranged from 6. 1%-19. 1%,and were more stable in different environments.The average value of skewness coefficient were between 0. 8-0. 9 and average values of kurtosis coefficient were between 1. 0-2. 6. The results showed that phenotypic variation was in normal distribution. Genotyping was performed with genome-wide Simple Sequence Repeats（ SSRs）,a total of 214 markers were polymorphic and generated460 allele loci,the average genetic diversity index were 0. 5151 with range from 0. 0333 to 0. 8725,and polymor-phism information content（ PIC） were 0. 4587 with range from 0. 0328 to 0. 8594. Then 99 markers,accounting for46. 3% of the total,their genetic diversity index and PIC were both more than average together. The results indicated that the alleles and the genetic diversity were larger in upland cotton accessions. 118 cotton varieties were divided into 4 subgroups by analysis of population structure,there was no corresponding relation between each kind of group of accessions and the geographical regions. Association analysis results were showed that 39 marker loci were detected at least two of the four environments（-log10 P〉1. 3,P〈0. 05）. 14 marker loci were associated in LP with explained variance rang from 3. 29% to 9. 1%,with an average of 5. 37%. 8 marker loci were associated in BW with explained variance range from 3. 68% to 9. 56%,with an average of 5. 88%. 5 marker loci were associated in BN with explained variance range from 3. 74% to 5. 77%,with an average of 4. 44% and 12 marker loci were associated in SI with explained variance range from 3. 49% to 11. 14%,with an average of 5. 91%,respectively.The four marker loci of 39 associated markers were associated with more than two traits simultaneously. For example,JESPR065 a was simultaneously associated with BW and SI,and NAU1169 c was simultaneously associated with LP and SI. The seven marker loci（ CIR0183,JESPR0153,NAU3308,NAU6094,NAU3201,NAU1167,NAU3995）were coincident with previous studies,and 32 were identified as new association markers. The results were excellent genetic resources for future cotton breeding and could provide a theoretical basis for molecular assisted selection of upland cotton about yield traits.
出处
《植物遗传资源学报》
CAS
CSCD
北大核心
2017年第4期720-727,共8页
Journal of Plant Genetic Resources
基金
新疆生产建设兵团博士资金(2013BB001)
国家自然科学基金(31260340)
关键词
陆地棉
产量性状
分子标记
关联分析
upland cotton
yield traits
molecular marker
association analysis
作者简介
第一作者主要从事棉花分子育种研究。E-mail：cottonwj@126．com
主要从事棉花遗传育种研究。E—mail：dcg318@163．com
通信作者：余渝，主要从事棉花遗传育种研究。E-mail：xjyuyu021@sohu．com
