欢迎访问作物学报，今天是
作物学报

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)

RichHTML

20

PDF

469

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
[1] Zhang L W, Ibrahim A K, Niyitanga S, Zhang L M, Qi J M . Jute (Corchorus spp.) Breeding. Advances in Plant Breeding Strategies: Industrial and Food Crops, 2019. pp 85-113.
[2] 粟建光, 戴志刚, 杨泽茂, 唐蜻, 谢冬微, 陈基权, 许英, 徐建堂, 张利国, 龚友才, 宋宪友, 程超华, 邓灿辉 . 麻类作物特色资源的创新与利用. 植物遗传资源学报, 2019,20:11-19.
Su J G, Dai Z G, Yang Z M, Tang Q, Xie D W, Chen J Q, Xu Y, Xu J T, Zhang L G, Gong Y C, Song X Y, Cheng C H, Deng C H . Innovation and utilization of characteristic germplasm for bast fiber crops. J Plant Genet Resour, 2019,20:11-19 (in Chinese with English abstract).
[3] Mondal S, Hadapad A B, Hande P A, Badigannavar A M . Identification of quantitative trait loci for bruchid ( Caryedon serratus Olivier) resistance components in cultivated groundnut(Arachis hypogaea L.). Mol Breed, 2014,33:961-973.
doi: 10.1007/s11032-013-0011-1
[4] Crouzillat D, Phillips W, Fritz P J, Pétiard V . Quantitative trait loci analysis in Theobroma cacao using molecular markers. Inheritance of polygenic resistance to Phytophthora palmivora in two related cacao populations. Euphytica, 2000,114:25-36.
doi: 10.1023/A:1003994212394
[5] Banerjee S, Das M, Mir R R, Kundu A, Topdar N, Sarkar D, Sinha M K, Balyan H S, Gupta P K . Assessment of genetic diversity and population structure in a selected germplasm collection of 292 jute genotypes by microsatellite (SSR) markers. Mol Plant Breed, 2012,3:11-25.
[6] Liu S, Liu H, Wu A, Hou Y, An Y, Wei C . Construction of fingerprinting for tea plant ( Camellia sinensis) accessions using new genomic SSR markers. Mol Breed, 2017,37:93.
doi: 10.1007/s11032-017-0692-y
[7] Dachapak S, Somta P, Poonchaivilaisak S, Yimram T, Srinives P . Genetic diversity and structure of the zombi pea [Vigna vexillata(L.) A. Rich] gene pool based on SSR marker analysis. Genetica, 2017,145:189-200.
doi: 10.1007/s10709-017-9957-y pmid: 28233217
[8] Satya P, Chakraborty A, Jana S, Majumdar S, Karan M, Sarkar D, Datta S, Mitra J, Kar C, Karmakar P, Singh N . Identification of genic SSRs in jute ( Corchorus capsularis, Malvaceae) and development of markers for phenylpropanoid biosynthesis genes and regulatory genes. Plant Breed, 2017,136:784-797.
doi: 10.1111/pbr.2017.136.issue-5
[9] Tao A, Huang L, Wu G, Afshar R K, Qi J, Xu J, Fang P, Lin L, Zhang L, Lin P . High-density genetic map construction and QTLs identification for plant height in white jute ( Corchorus capsularis L.) using specific locus amplified fragment (SLAF) sequencing. BMC Genomics, 2017,18:355.
doi: 10.1186/s12864-017-3712-8 pmid: 28482802
[10] Lou Y, Hu L, Chen L, Sun X, Yang Y, Liu H, Xu Q . Association analysis of simple sequence repeat (SSR) markers with agronomic traits in tall fescue ( Festuca arundinacea Schreb.). PLoS One, 2015,10:e0133054.
doi: 10.1371/journal.pone.0133054 pmid: 26186338
[11] Prabhu D A, Ray J D, Singh S K, Valerio H V, Smith J R, Purcell L C, King A, Fritschi F B . Genome-wide association analysis of diverse soybean genotypes reveals novel markers for nitrogen traits. Plant Genome, 2015,8:1-15.
[12] Islam M S, Saito J A, Emdad E M, Ahmed B, Islam M M, Halim A, Hossen Q M, Hossain M Z, Ahmed R, Hossain M S, Kabir S M, Khan M S, Khan M M, Hasan R, Aktar N, Honi U, Islam R, Rashid M M, Wan X, Hou S, Haque T, Azam M S, Moosa M M, Elias S M, Hasan A M, Mahmood N, Shafiuddin M, Shahid S, Shommu N S, Jahan S, Roy S, Chowdhury A, Akhand A I, Nisho G M, Uddin K S, Rabeya T, Hoque S M, Snigdha A R, Mortoza S, Matin S A, Islam M K, Lashkar M Z, Zaman M, Yuryev A, Uddin M K, Rahman M S, Haque M S, Alam M M, Khan H, Alam M . Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants, 2017,3:16223.
doi: 10.1038/nplants.2016.223 pmid: 28134914
[13] 姚嘉瑜, 张立武, 赵捷, 徐益, 祁建民, 张列梅 . 黄麻全基因组SSR鉴定与特征分析. 作物学报, 2019,45:14-21.
Yao J Y, Zhang L W, Zhao J, Xu Y, Qi J M, Zhang L M . Evaluation and characteristic analysis of SSRs from the whole genome of jute ( Corchorus capsularis). Acta Agron Sin, 2019,45:14-21 (in Chinese with English abstract).
[14] 张彬, 李金秀, 王震, 冯浩, 李金榜 . 小麦主要农艺性状的相关性及聚类分析. 作物杂志, 2018, ( 3):57-60.
Zhang B, Li J X, Wang Z, Feng H, Li J B . Correlation and cluster analysis of agronomic traits in wheat lines. Crops, 2018, ( 3):57-60 (in Chinese with English abstract).
[15] 殷冬梅, 李拴柱, 崔党群 . 花生主要农艺性状的相关性及聚类分析. 中国油料作物学报, 2010,32:212-216.
Yin D M, Li S Z, Cui D Q . Agronomic character and cluster analysis of peanut cultivar. Chin J Oil Crop Sci, 2010,32:212-216 (in Chinese with English abstract).
[16] Ghosh R K, Sreewongchai T, Nakasathien S, Phumichai C . Phenotypic variation and the relationships among jute ( Corchorus species) genotypes using morpho-agronomic traits and multivariate analysis. Aust J Crop Sci, 2013,7:830.
[17] Zhang L W, Yuan M H, Tao A F, Xu J T, Lin L H, Fang P P, Qi J M . Genetic structure and relationship analysis of an association population in jute ( Corchorus spp.) evaluated by SSR markers. PLoS One, 2015,10:e0128195.
doi: 10.1371/journal.pone.0128195 pmid: 26035301
[18] 张立武, 袁民航, 何雄威, 刘星, 方平平, 林荔辉, 陶爱芬, 徐建堂, 祁建民 . GenBank数据库中黄麻EST-SSR标记的开发及其通用性评价. 作物学报, 2014,40:1213-1219.
doi: 10.3724/SP.J.1006.2014.01213
Zhang L W, Yuan M H, He X W, Liu X, Fang P P, Lin L H, Tao A F, Xu J T, Qi J M . Development and universality evaluation of EST-SSR markers from GenBank in jute. Acta Agron Sin, 2014,40:1213-1219 (in Chinese with English abstract).
[19] Zhang L L, Gao Z Z, Wan X B, Xu Y, Zhang L M, Tao A F, Fang P P, Qi J M, Zhang L W . Development of novel small indel markers in jute ( Corchorus spp.). Trop Plant Biol, 2017,10:169-176.
doi: 10.1007/s12042-017-9193-8
[20] 粟建光 . 黄麻种质资源描述规范和数据标准. 北京: 中国农业出版社, 2005. pp 7-27.
Su J G. Descriptors and Data Standard for Jute (Corchorus olitorius L. & Corchorus capsularis L.). Beijing: China Agriculture Press, 2005. pp 7-27(in Chinese).
[21] Kraakman A T, Wageningen A J, Niks R E, Stam P . Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics, 2004,168:435-446.
doi: 10.1534/genetics.104.026831 pmid: 15454555
[22] 杨洛淼, 孙健, 赵宏伟, 王敬国, 刘化龙, 邹德堂 . 不同年份冷水胁迫下水稻抽穗期和产量性状的QTL分析. 中国农业科学, 2016,49:3489-3503.
doi: 10.3864/j.issn.0578-1752.2016.18.003
Yang L M, Sun J, Zhao H W, Wang J G, Liu H L, Zou D T . QTL analysis of heading date and yield traits in japonica rice under cold water stress in different years. Sci Agric Sin, 2016,49:3489-3503 (in Chinese with English abstract).
[23] Karrakman A T, Nikes R E, Berg P M, Stam P, Eeuwijk F A . Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars. Genetics, 2004,168:435-446.
doi: 10.1534/genetics.104.026831 pmid: 15454555
[24] 司二静, 张宇, 汪军成, 孟亚雄, 李葆春, 马小乐, 尚勋武, 王化俊 . 大麦农艺性状与SSR标记的关联分析. 作物学报, 2015,41:1064-1072.
doi: 10.3724/SP.J.1006.2015.01064
Si R J, Zhang Y, Wang J C, Meng Y X, Li B C, Ma X L, Shang X W, Wang H J . Association analysis between SSR markers and agronomic traits in barley. Acta Agron Sin, 2015,41:1064-1072 (in Chinese with English abstract).
[25] Zhao J L, Wang H W, Zhang X C, Du X Y, Li A F, Kong L R . Association analysis of grain traits with SSR markers between Aegilops tauschii and hexaploid wheat(Triticum aestivum L.). J Integr Agric, 2015,14:1936-1948.
doi: 10.1016/S2095-3119(15)61070-X
[26] Abbasi Z, Majidi M M, Arzani A, Rajabi A, Mashayekhi P, Bocianowski J . Association of SSR markers and morpho- physiological traits associated with salinity tolerance in sugar beet ( Beta vulgaris L.). Euphytica, 2015,205:785-797.
doi: 10.1007/s10681-015-1408-1
[27] Fan C, Xing Y, Mao H, Lu T, Han B, Xu C, Li X, Zhang Q . GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet, 2006,112:1164-1171.
doi: 10.1007/s00122-006-0218-1
[28] Yue B, Xue W Y, Luo L J, Xing Y Z . QTL analysis for flag leaf characteristics and their relationships with yield and yield traits in rice. Acta Genet Sin, 2006,33:824-832.
doi: 10.1016/S0379-4172(06)60116-9 pmid: 16980129
[29] 祁建民, 卢浩然, 郑云雨, 王英娇 . 黄麻数量性状遗传关系分析. 作物学报, 1991,17:145-150.
Qi J M, Lu H R, Zheng Y Y, Wang Y J . Analysis on the genetic relationship of quantitative characters in jute ( Corchorus capsularis L.). Acta Agron Sin, 1991,17:145-150 (in Chinese with English abstract).
[30] 周金超, 杨鑫雷, 崔顺立, 侯名语, 陈焕英, 穆国俊, 刘立峰 . 花生SSR标记与农艺性状的相关性. 作物学报, 2014,40:1197-1204.
doi: 10.3724/SP.J.1006.2014.01197
Zhou J C, Yang X L, Cui S L, Hou M Y, Chen H Y, Mu G J, Liu L F . Correlation between SSR markers and agronomic traits in peanut ( Arachis hypogaea L.). Acta Agron Sin, 2014,40:1197-1204 (in Chinese with English abstract).
[31] 李丹阳, 刘凯歌, 卢济明, 杨鑫雷, 崔顺立, 穆国俊, 陈焕英, 刘立峰 . 花生SSR标记与品质性状的相关分析. 分子植物育种, 2017,15:2695-2701.
Li D Y, Liu K G, Lu J M, Yang X L, Cui S L, Mu G J, Chen H Y, Liu L F . Correlation analysis of SSR markers and quality traits in peanut ( Arachis hypogaea L.). Mol Plant Breed, 2017,15:2695-2701 (in Chinese with English abstract).
[1] 陈小红, 林元香, 王倩, 丁敏, 王海岗, 陈凌, 高志军, 王瑞云, 乔治军. 基于高基元SSR构建黍稷种质资源的分子身份证[J]. 作物学报, 2022, 48(4): 908-919.
[2] 张霞, 于卓, 金兴红, 于肖夏, 李景伟, 李佳奇. 马铃薯SSR引物的开发、特征分析及在彩色马铃薯材料中的扩增研究[J]. 作物学报, 2022, 48(4): 920-929.
[3] 杨昕, 林文忠, 陈思远, 杜振国, 林杰, 祁建民, 方平平, 陶爱芬, 张立武. 黄麻双生病毒CoYVV的分子鉴定和抗性种质筛选[J]. 作物学报, 2022, 48(3): 624-634.
[4] 郭艳春, 姚嘉瑜, 张镕斌, 陈思远, 何青垚, 陶爱芬, 方平平, 祁建民, 张列梅, 张立武. 中国黄麻炭疽病病原菌的分离鉴定及系统发育分析[J]. 作物学报, 2022, 48(3): 770-777.
[5] 赵雪, 周顺利. 玉米抗茎倒伏能力相关性状与评价研究进展[J]. 作物学报, 2022, 48(1): 15-26.
[6] 赵婧, 孟凡钢, 于德彬, 邱强, 张鸣浩, 饶德民, 丛博韬, 张伟, 闫晓艳. 不同磷效率大豆农艺性状与磷/铁利用率对磷素的响应[J]. 作物学报, 2021, 47(9): 1824-1833.
[7] 王琰琰, 王俊, 刘国祥, 钟秋, 张华述, 骆铮珍, 陈志华, 戴培刚, 佟英, 李媛, 蒋勋, 张兴伟, 杨爱国. 基于SSR标记的雪茄烟种质资源指纹图谱库的构建及遗传多样性分析[J]. 作物学报, 2021, 47(7): 1259-1274.
[8] 高震, 梁效贵, 张莉, 赵雪, 杜雄, 崔彦宏, 周顺利. 不同时期灌溉对华北平原春玉米穗粒数的影响[J]. 作物学报, 2021, 47(7): 1324-1331.
[9] 邓妍, 王娟玲, 王创云, 赵丽, 张丽光, 郭虹霞, 郭红霞, 秦丽霞, 王美霞. 生物菌肥与无机肥配施对藜麦农艺性状、产量性状及品质的影响[J]. 作物学报, 2021, 47(7): 1383-1390.
[10] 罗兰, 雷丽霞, 刘进, 张瑞华, 金桂秀, 崔迪, 黎毛毛, 马小定, 赵正武, 韩龙植. 利用东乡普通野生稻染色体片段置换系定位产量相关性状QTL[J]. 作物学报, 2021, 47(7): 1391-1401.
[11] 韩贝, 王旭文, 李保奇, 余渝, 田琴, 杨细燕. 陆地棉种质资源抗旱性状的关联分析[J]. 作物学报, 2021, 47(3): 438-450.
[12] 刘少荣, 杨扬, 田红丽, 易红梅, 王璐, 康定明, 范亚明, 任洁, 江彬, 葛建镕, 成广雷, 王凤格. 基于农艺及品质性状与SSR标记的青贮玉米品种遗传多样性分析[J]. 作物学报, 2021, 47(12): 2362-2370.
[13] 郭艳春, 张力岚, 陈思远, 祁建民, 方平平, 陶爱芬, 张列梅, 张立武. 黄麻应用核心种质的DNA分子身份证构建[J]. 作物学报, 2021, 47(1): 80-93.
[14] 陶爱芬,游梓翊,徐建堂,林荔辉,张立武,祁建民,方平平. 基于黄麻转录组序列SNP位点的CAPS标记开发与验证[J]. 作物学报, 2020, 46(7): 987-996.
[15] 王恒波,祁舒婷,陈姝琦,郭晋隆,阙友雄. 甘蔗栽培种单倍体基因组SSR位点的发掘与应用[J]. 作物学报, 2020, 46(4): 631-642.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2