陆地棉叶片叶绿素含量与SSR标记的关联分析及优异等位变异的挖掘

doi:10.3864/j.issn.0578-1752.2017.18.001

摘要/Abstract

摘要： 【目的】筛选与陆地棉叶片叶绿素含量性状相关联的分子标记，挖掘其优异等位变异及典型材料，为陆地棉分子标记辅助育种提供技术支持。【方法】在3年6个环境中，对185份陆地棉品种（系）组成的自然群体进行倒4叶叶绿素相对含量（soil and plant analyzer development，SPAD）的测定，每年分3个时期（打顶后0、10和20 d）。采用PowerMarker 3.25软件计算各位点的多态性信息含量，以分析群体的遗传多样性。利用STRUCTURE 2.3.4软件计算群体结构矩阵（Q），利用TASSEL 3.0软件计算亲属关系矩阵（K），通过GLM（general linear model，Q）和MLM（mixed linear model，Q+K）2种方法，同时对SPAD与SSR标记进行关联分析。依据计算的等位位点表型效应值，挖掘优异的等位变异及典型材料。【结果】137对SSR多态性引物共扩增出355个等位变异，平均每对引物扩增到2.6个多态性位点，PIC平均值为0.67，变化范围为0.01—0.95，高度多态性引物（PIC＞0.5）占85%，其中PIC最高的标记为HAU2146（PIC=0.95）和NAU2083（PIC=0.93）。当?K取得最大值时，K=2，因此，将185份陆地棉材料划分为2个亚群。通过GLM方法共检测到22个显著性位点（P＜0.001），表型变异解释率为5.28%—10.85%，平均为7.24%，贡献率最高的等位变异位点是SWU0529a（R²=10.85%）和NAU998c（R² =10.48%）；通过MLM方法共检测到17个显著性位点（P＜0.01），表型变异解释率为3.72%—8.58%，平均为4.72%，贡献率最高的等位变异位点是SWU0923b（R²=8.06%）和SWU0662d（R²=6.74%）；2种方法共同检测到的显著性位点有12个，等位变异NAU998c在3个时期2种方法能同时被检测到。通过等位变异的表型效应分析，找到2个增效效应最大的等位变异（HAU3318b和SWU0987b），利用找到的等位变异对材料进行筛选，获得携带2个增效效应等位变异的材料53份，2个增效效应位点都未检测到的材料有46份，统计结果显示，在打顶后10和20 d 2个时期，53份材料的SPAD均值显著高于46份材料的SAPD均值。【结论】检测到12个与SPAD值相关的显著性位点，并挖掘到2个增效效应优异等位变异，获得携带优异等位变异的载体材料53份，获得携带2个优异等位变异的典型材料1份。

关键词: 陆地棉, 叶绿素, SSR, 关联分析, 优异等位变异

Abstract: 【Objective】The objective of this study is to detect the SSR markers associated with leaf chlorophyll content and explore the alleles and their typical materials in upland cotton. The results will be helpful for molecular marker-assisted breeding.【Method】The natural population including 185 upland cotton accessions were planted at two different places in 3 years and the data of leaf chlorophyll content were recorded at 3 stages (0, 10 and 20 days after topping) every year. In analysis the polymorphism information of population structure, Power Marker 3.25 software was used to estimate the polymorphism information content (PIC). The structure of the natural population was analyzed using STRUCTURE 2.3.4 software and the kinship was estimated using TASSEL 3.0 software. Then the data were associated with 137 SSR markers by GLM (general linear model, Q) and MLM (mixed linear model, Q+K). The superior alleles were exploited and the phenotypic effects of total alleles were found.【Result】 Totally 355 polymorphic alleles were found with 137 SSR markers and 2.6 alleles were revealed with each marker in average ranged from 0.01-0.95. The 85% of total alleles were highly polymorphic primers (PIC＞0.5). HAU2146 (PIC=0.95) and NAU2083 (PIC=0.93) kept the maximum PIC. According to the results of STRUCTURE software, K value was 2 when ΔK was the max so the cultivars were divided into 2 populations. A total of 22 alleles found by GLM method significantly at the level of P＜0.001 which explained 5.28%-10.85% of the phenotypic variance and the mean value was 7.24%. SWU0529a (R² =10.85%) and NAU998c (R²=10.48%) kept the max value. Meanwhile, 17 alleles were found by MLM method significantly at the level of P＜0.01 which explained 3.72%-8.58% of the phenotypic variance and the mean value was 4.72%. SWU0923b (R²=8.06%) and SWU0662d (R²=6.74%) kept the max value. A total of 12 alleles were revealed by GLM method and MLM method in common, and NAU998c was significantly at 3 stages by GLM and MLM methods. Two positive alleles (HAU3318b and SWU0987b) were revealed over the estimated phenotypic effects. The 53 carrier materials of two positive alleles kept higher SPAD value in average than the 46 materials carried none of two positive alleles in 10 and 20 days after topping.【Conclusion】A total of 12 alleles associated significantly with leaf chlorophyll of upland cotton were found, and then two positive superior alleles, 53 carrier materials and one typical materials were revealed.

Key words: upland cotton, chlorophyll, SSR, association analysis, superior allele

刘其宝，李黎贝，张驰，宿俊吉，魏恒玲，王寒涛，喻树迅. 陆地棉叶片叶绿素含量与SSR标记的关联分析及优异等位变异的挖掘[J]. 中国农业科学, 2017, 50(18): 3439-3449.

LIU QiBao, LI LiBei, ZHANG Chi, SU JunJi, WEI HengLing, WANG HanTao, YU ShuXun. Association Analysis of Leaf Chlorophyll Content with SSR Markers and Exploration of Superior Alleles in Upland Cotton[J]. Scientia Agricultura Sinica, 2017, 50(18): 3439-3449.

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