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作物学报 ›› 2020, Vol. 46 ›› Issue (12): 1905-1913.doi: 10.3724/SP.J.1006.2020.04035

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

黄麻SSR标记与纤维产量性状的相关性

张力岚1,2,3(), 张列梅1(), 牛焕颖1, 徐益1,2,3, 李玉1,2,3, 祁建民1,2, 陶爱芬1,2, 方平平1,2, 张立武1,2,3,*()   

  1. 1福建农林大学农学院 / 作物遗传育种与综合利用教育部重点实验室 / 福建省作物设计育种重点实验室, 福建福州 350002
    2福建农林大学农业农村部东南黄红麻实验观测站 / 福建省麻类种质资源共享平台 / 福建省南方经济作物遗传育种与多用途开发国际科技合作基地, 福建福州 350002
    3福建农林大学海峡联合研究院基因组与生物技术中心, 福建福州 350002
  • 收稿日期:2020-02-16 接受日期:2020-04-15 出版日期:2020-05-11 网络出版日期:2020-11-25
  • 通讯作者: 张立武
  • 基金资助:
    国家自然科学基金项目(31771369);国家现代农业产业技术体系建设专项(CARS-19-E06)

Correlation between SSR markers and fiber yield related traits in jute (Corchorus spp.)

Li-Lan ZHANG1,2,3(), Lie-Mei ZHANG1(), Huan-Ying NIU1, Yi XU1,2,3, Yu LI1,2,3, Jian-Min QI1,2, Ai-Fen TAO1,2, Ping-Ping FANG1,2, Li-Wu ZHANG1,2,3,*()   

  1. 1Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding by Design / College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China
    2Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Fujian Public Platform for Germplasm Resources of Bast Fiber Crops / Fujian International Science and Technology Cooperation Base for Genetics, Breeding and Multiple Utilization Development of Southern Economic Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China
    3Center for Genomics and Biotechnology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China
  • Received:2020-02-16 Accepted:2020-04-15 Published:2020-05-11 Published online:2020-11-25
  • Contact: Li-Wu ZHANG
  • Supported by:
    National Natural Science Foundation of China(31771369);China Agriculture Research System(CARS-19-E06)

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摘要：

鉴定出与纤维产量相关性状连锁的SSR标记有助于黄麻纤维产量的分子标记辅助育种。本研究以311份黄麻种质资源为研究材料, 通过2016—2018年表型鉴定, 结合116对SSR引物扩增出397个SSR标记, 利用SPSS软件对SSR标记与纤维产量性状进行相关性分析。结果表明, 311份黄麻种质资源9个纤维产量性状的变异系数范围为13.05%~76.78%, 表现出广泛的遗传变异。农艺性状相关分析表明, 这些性状间存在极显著相关, 其中分枝高和节数的平均相关系数最高(r = 0.931), 其次是单株鲜皮重和单株鲜茎重(r = 0.781)、单株干皮重与单株鲜皮重(r = 0.779)。方差分析表明, 节数、分枝数、株高以及分枝高等性状在不同年份间相对稳定, 广义遗传力较高。进而通过皮尔逊相关法鉴定与纤维产量性状相关的SSR标记。每个性状与这些相关SSR标记逐步回归分析表明, 与纤维产量性状显著相关的标记有6个, 单个SSR标记的贡献率为3.9%~22.5%。这些结果将会加快黄麻设计育种进程。

关键词: 黄麻, 纤维产量, 农艺性状, SSR, 相关性, 回归分析

Abstract:

Simple sequence repeat (SSR) markers correlated to fiber yield traits would be a beneficial tool for molecular marker-assisted breeding in jute. In this study, 397 SSR markers were screened from 311 jute germplasms by the phenotype identification from 2016 to 2018 and 116 pairs of primers. The correlation analysis between SSR markers and fiber yield related traits by SPSS revealed that the range of the coefficient of variation related to 9 fiber traits was from 13.05% to 76.78%, indicating a comprehensive genetic variation. The correlation analysis of the agronomic traits showed that there were significantly correlations among these traits. The average correlation coefficient between branch height and nodes of main stem was the highest (r = 0.931), followed by the correlation coefficients (r = 0.781) of fresh bark weight per plant and fresh stem weight per plant and the coefficients (r = 0.779) of dry bark weight and fresh bark weight per plant. Analysis of variance (ANOVA) showed that the traits of main stem nodes, number of branches, plant height and branch height were relatively stable in different years with the higher broad heritability capacity. Furthermore, the SSR markers associated with fiber yield related traits were identified by Pearson correlation method. Stepwise regression analysis among each trait associated SSR markers indicated that there were six markers associated significantly with fiber yield related traits, and phenotypic variation explained by each SSR marker varied from 3.9% to 22.5%. These results will accelerate the development of molecular design breeding in jute.

Key words: jute, fiber yield, agronomic traits, SSR, correlation, regression analysis

表1

黄麻9个纤维产量相关性状的统计分析"

性状
Trait		 年份
Year		 平均值±标准差
Mean ± SD		 最大值
Maximum		 最小值
Minimum		 变异系数
CV (%)		 遗传多样性指数
Shannon-Wiener index
株高PH (cm) 2016 331.97±43.33 459.10 43.33 13.05 1.89
2017 334.69±51.40 482.90 51.40 15.36 2.10
2018 384.37±64.21 514.90 64.21 16.71 2.40
分枝高BH (cm) 2016 110.35±72.04 352.00 6.57 65.29 2.32
2017 106.62±67.36 391.40 4.10 63.17 2.34
2018 170.23±82.87 427.90 5.33 48.68 2.62
茎粗SD (mm) 2016 18.26±2.42 23.72 2.42 13.27 1.82
2017 20.44±3.30 28.96 3.30 16.16 2.23
2018 20.88±3.31 28.37 3.31 15.83 2.17
鲜皮厚FBT (mm) 2016 1.33±0.23 2.00 0.23 17.21 1.95
2017 1.29±0.25 2.02 0.25 19.24 2.08
2018 1.17±0.32 2.05 0.32 27.53 2.46
节数NMS (个) 2016 18.82±13.48 50.30 1.00 71.63 2.11
2017 19.02±14.38 78.70 1.00 75.61 2.23
2018 26.37±14.76 81.33 1.00 55.96 2.48
分枝数NB (个) 2016 19.15±13.81 55.20 2.10 72.12 2.19
2017 20.55±17.41 74.00 1.50 84.73 2.38
2018 18.75±14.39 70.30 2.20 76.78 2.28
单株鲜茎重FSW (g) 2016 682.18±244.1 1462.00 71.75 35.79 2.23
2017 611.51±206.6 1266.00 64.00 33.79 2.14
2018 598.62±231.7 1380.00 97.00 38.71 2.23
单株鲜皮重FBW (g) 2016 172.8±66.20 421.00 43.50 38.31 2.34
2017 131.35±66.09 394.00 7.50 50.31 2.37
2018 128.71±70.57 330.00 8.00 54.83 2.49
单株干皮重DBW (g) 2016 42.92±14.95 141.00 14.95 34.84 1.52
2017 39.32±19.02 110.00 4.00 48.38 1.93
2018 31.00±16.84 104.00 6.00 54.31 1.78

表2

黄麻9个纤维产量性状的方差分析"

性状
Trait		 差异源
Source		 自由度
DF		 总方差
SS		 均方
MS		 P值
P-value		 广义遗传力
Broad-sense capacity
株高PH 年份Years 2 197,483.34 98,741.67 <0.01 -
品种Varieties 310 2,018,314.68 6,510.69 <0.01 0.81
分枝高BH 年份Years 2 533,367.61 266,683.80 <0.01 -
品种Varieties 310 3,902,352.97 12,588.24 <0.01 0.78
茎粗SD 年份Years 2 461.51 230.76 <0.01 -
品种Varieties 310 5,529.13 17.84 <0.01 0.71
鲜皮厚FBT 年份Years 2 4.90 2.45 <0.01 -
品种Varieties 310 35.52 0.11 <0.01 0.61
节数NMS 年份Years 2 8,788.61 4,394.31 <0.01 -
品种Varieties 310 149,702.87 482.91 <0.01 0.82
分枝数NB 年份Years 2 480.19 240.09 0.019 -
品种Varieties 310 187,378.60 604.45 <0.01 0.90
单株鲜茎重FSW 年份Years 2 1,291,406.03 645,703.01 <0.01 -
品种Varieties 310 28,003,667.06 90,334.41 <0.01 0.72
单株鲜皮重FBW 年份Years 2 270,421.30 135,210.65 <0.01 -
品种Varieties 310 2,529,200.96 8,158.71 <0.01 0.72
单株干皮重DBW 年份Years 2 10,322.48 5,161.24 <0.01 -
品种Varieties 310 104,444.51 336.92 <0.01 0.70

表3

黄麻9个纤维产量相关性状的不同年份间相关分析"

年份Year 性状
Trait		 2016 2017
2017 株高PH 0.727**
分枝高BH 0.835**
茎粗SD 0.489**
鲜皮厚FBT 0.328**
节数NMS 0.774**
分枝数NB 0.806**
单株鲜茎重FSW 0.458**
单株鲜皮重FBW 0.541**
单株干皮重DBW 0.307**
2018 株高PH 0.684** 0.741**
分枝高BH 0.597** 0.626**
茎粗SD 0.344** 0.474**
鲜皮厚FBT 0.177* 0.381**
节数NMS 0.625** 0.635**
分枝数NB 0.725** 0.771**
单株鲜茎重FSW 0.368** 0.370**
单株鲜皮重FBW 0.396** 0.528**
单株干皮重DBW 0.267** 0.398**

表4

黄麻9个纤维产量性状的相关分析"

年份
Year		 株高
PH		 分枝高
BH		 茎粗
SD		 鲜皮厚
FBT		 节数
NMS		 分枝数
NB		 单株鲜茎重
FSW		 单株鲜皮重
FBW
分枝高
BH		 2016 0.018
2017 0.302**
2018 0.398**
茎粗
SD		 2016 0.537** 0.102
2017 0.715** 0.176**
2018 0.542** 0.215**
鲜皮厚
FBT		 2016 0.370** 0.063 0.751**
2017 0.519** 0.074 0.728**
2018 0.385** 0.055 0.688**
节数
NMS		 2016 0.098 0.959** 0.104 0.087
2017 0.214** 0.927** 0.115 0.039
2018 0.282** 0.908** 0.159** 0.055
分枝数
NB		 2016 0.547** -0.667** 0.321** 0.234** -0.706**
2017 0.442** -0.510** 0.437** 0.411** -0.553**
2018 0.468** -0.435** 0.262** 0.358** -0.508**
单株鲜茎重
FSW		 2016 0.509** 0.291** 0.715** 0.634** 0.309** 0.535**
2017 0.596** 0.169** 0.741** 0.646** 0.190** 0.495**
2018 0.709** 0.054 0.662** 0.644** 0.001 0.551**
单株鲜皮重
FBW		 2016 0.607** 0.027 0.798** 0.695** 0.059 0.480** 0.816**
2017 0.730** 0.202** 0.783** 0.700** 0.158** 0.424** 0.717**
2018 0.703** 0.241** 0.671** 0.660** 0.168** 0.384** 0.809**
单株干皮重
DBW		 2016 0.522** 0.020 0.529** 0.535** 0.025 0.299** 0.609** 0.714**
2017 0.797** 0.195** 0.730** 0.615** 0.140* 0.458** 0.654** 0.883**
2018 0.666** 0.382** 0.422** 0.355** 0.399** 0.302** 0.702** 0.740**

表5

部分SSR标记和9个纤维产量性状间的相关系数"

标记
Marker		 株高
PH		 分枝高
BH		 节数
NMS		 茎粗
SD		 鲜皮厚
FBT		 分枝数
NB		 单株鲜茎重
FSW		 单株鲜皮重
FBW		 单株干皮重
DBW
CoSSR068 -0.120* -0.090 -0.160 -0.07 -0.04 -0.020 -0.110 -0.110 -0.100
CoSSR119 -0.010 -0.240** 0.130** 0.031 0.15* 0.130* 0.052 0.020 0.007
CoSSR100 0.051 -0.090 0.280 -0.022 -0.02 0.028 0.028 -0.004 -0.020
CoEMS250 -0.020 -0.020 0.030 -0.021 0.045 0.029 -0.010 -0.012 0.018
CoEMS474 -0.160** -0.090 -0.020 -0.045 -0.04 -0.020 -0.010 -0.120** -0.130*
CoSSR099 0.131* -0.070 0.130* -0.072 -0.04 0.133* 0.111 0.0370 0.110
CoSSR094 0.147** -0.170** 0.200** 0.195** 0.22** 0.200** 0.174** 0.213** 0.065
CoSSR090 -0.140 -0.150* 0.023 -0.170** -0.11 0.023 -0.090 -0.130* -0.104
CcID066 0.127* -0.160** 0.170* -0.120* -0.04 0.130* 0.076 -0.023 0.049
CcID167 0.176** -0.100 0.180** 0.190** 0.30** 0.180** 0.168** 0.294** 0.230**
CoSSR133 0.147* -0.070 0.140* 0.099 0.13* 0.140* 0.088 0.090 0.014
CoSSR086 0.208** -0.120* 0.210** 0.255** 0.33** 0.210** 0.226** 0.324** 0.190**
CoSSR164 0.081 0.092 0.095 -0.180** -0.10 -0.100 -0.050 -0.012 0.031
CcSSR019 0.215** -0.140* 0.241 0.245** 0.34** 0.240** 0.243** 0.327** 0.217**
CcSSR045 -0.110* -0.210* 0.063 -0.160** -0.15** -0.060 -0.100 -0.105 -0.080

表6

SSR标记与纤维产量相关性状之间的多元逐步回归分析"

性状
Trait		 SSR标记
SSR marker		 贡献率
Phenotypic variation explained, R2 (%)		 标准回归系数
Standardized regression coefficients
株高PH CcID102 19.9 -0.316
分枝高BH CoSSR179 12.1 0.347
茎粗SD CoSSR015 13.1 0.361
鲜皮厚FBT Juph059 22.5 0.475
节数NMS CoSSR179 11.1 -0.333
分枝数NB CcID102 3.9 0.197
单株鲜茎重FSW CoSSR305 15.3 0.391
单株鲜皮重FBW CoSSR192 20.2 -0.449
单株干皮重DBW CoSSR192 7.1 -0.266
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