花生SSR标记与农艺性状的相关性

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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(7): 1197-1204
ZHOU Jin-Chao, YANG Xin-Lei, CUI Shun-Li, HOU Ming-Yu, CHEN Huan-Ying, MU Guo-Jun, LIU Li-Feng. Correlation between SSR Markers and Agronomic Traits in Peanut (Arachis hypogaea L.) . Acta Agronomica Sinica, 2014, 40(7): 1197-1204 复制到剪切板

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花生SSR标记与农艺性状的相关性

周金超, 杨鑫雷, 崔顺立, 侯名语, 陈焕英, 穆国俊^*, 刘立峰^*

华北作物种质资源教育部重点实验室 / 河北省作物种质资源重点实验室 / 河北农业大学, 河北保定071001

^*通讯作者(Corresponding authors): 刘立峰, E-mail:liulifeng@hebau.edu.cn, Tel: 0312-7528136; 穆国俊, E-mail:mgj99999@126.com, Tel: 0312-7528410

第一作者联系方式: E-mail:zhoujinchao0230@163.com

收稿日期:2014-04-16

基金:本研究由国家现代农业产业技术体系建设专项(CARS-14), 高等学校博士学科点科研专项(20121302110002), 农业部引进国际先进农业科学技术计划(948计划)项目(2013-Z65)和河北省高等学校科学技术研究重点项目(ZD2010136)资助;

摘要

以农家品种四粒红和冀农黑3号构建的包含有251个家系的重组自交系(RIL)群体为材料, 在河北保定市和邯郸大名县两地进行表型鉴定, 利用Pearson’s相关和逐步多元回归分析了花生农艺性状之间及其与标记的相关性。结果表明, 多数农艺性状间存在显著或极显著相关, 其中相关性最高的为单株生产力和单株仁重(r=0.970), 其次是主茎高和第一侧枝长(r=0.918); 77个SSR标记与18个农艺性状显著相关, 每个性状相关标记数在2~16之间; 14个SSR标记与13个农艺性状关联, 解释的表型变异为5.2%~11.5%。以上结果为花生常规育种和分子标记辅助选择奠定了基础。

关键词: 花生; 重组自交系; 农艺性状; SSR; 相关

Correlation between SSR Markers and Agronomic Traits in Peanut (Arachis hypogaea L.)

ZHOU Jin-Chao, YANG Xin-Lei, CUI Shun-Li, HOU Ming-Yu, CHEN Huan-Ying, MU Guo-Jun^*, LIU Li-Feng^*

North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory of Crop Germplasm Resources of Hebei / Agricultural University of Hebei, Baoding 071001, China

Fund:

Abstract

A recombinant inbred line (RIL) population including 251 lines, derived from the cross between Silihong and Jinonghei 3 was used to study the correlations between SSR markers and agronomic traits. The phenotypese were evaluated in two locations of Baoding and Handan, Hebei Province. Pearson’s correlation and stepwise multiple linear regression analysis were conducted based on SSR and phenotyping data. The results showed that there were significant correlations among 18 agronomic traits, with the higher correlations between pod weight per plant and seed weight per plant (r = 0.970), as well as the height of main stem and length of first branches (r = 0.918). There existed significant correlation between SSR marker and agronomic trait with a average of 2-6 markers correlated with each agronomic trait. Fourteen SSR markers were associated with 13 agronomic traits with explanined phenotypic variances of 5.2%-11.5%. All these laid a solid foundation for peanut conventional breeding and molecular marker-assisted breeding programs.

Keyword: Peanut; Recombinant inbred line; Agronomic traits; SSR; Correlation

Show Figures

作物的许多农艺性状如产量、品质和抗逆性等大多属于数量性状, 遗传基础复杂, 易受环境影响。通过表型选择的传统育种方法改良农艺性状周期长, 选择效率低^{[ 1]}。随着分子生物学的飞速发展, 分子标记技术得到广泛应用, 通过筛选与目标性状紧密连锁的分子标记, 即分子标记辅助选择(marker-assisted selection, MAS)对目标性状进行改良, 可以加快育种进程, 提高育种效率^{[ 2]}。众多分子标记技术中, 简单序列重复标记技术(simple sequence repeat, SSR)以其检测容易、重复性高和稳定性好等优点已被广泛用于作物目标性状的遗传改良研究^{[ 3]}。由于花生基因组学研究如遗传图谱构建和基因定位等进展缓慢, 加之其栽培种间基因组高度保守, 导致花生品种间遗传多样性偏低。因此, 仍有学者认为分子育种, 如MAS很难在短期内用于花生各种性状的改良^{[ 4]}。基于上述花生分子遗传改良存在的问题, 使得鉴定标记与农艺性状间的连锁关系成为花生分子育种的必要手段。

目前, 利用覆盖全基因组的分子遗传连锁图和合适的分离群体进行连锁分析以及数量性状位点(quantitative trait locus, QTL)定位是解析植物数量性状遗传基础的主要方法^{[ 1]}, 并且在花生中已被广泛应用^{[ 5, 6, 7, 8, 9, 10, 11, 12]}。然而, 通过分离群体筛选目标性状的QTL存在一定的局限性, 由于不同实验室采用的群体类型、标记种类及数量和环境等诸多因素的干扰, 导致QTL定位结果重复性较低^{[ 13]}; 其次, QTL定位需要预先构建高分辨率连锁图谱, 而后才能进行标记与性状的连锁分析。前人的研究结果大都是通过复合区间作图法将目标性状相关QTL定位在包含2个或2个以上位点的标记区间。采用多元线性逐步回归的统计方法, 依据测验值的显著水平确定标记与性状间是否相互关联, 从而估算出单个标记对性状的贡献(即决定系数), 该方法已在水稻、棉花及白桦等植物中应用。例如, 徐云碧等^{[ 14]}在研究水稻农艺性状时, 计算了性状与标记间的相关系数, 在显著( P=0.05)和极显著( P=0.01)水平上获得了4个标记-性状的关联, 表明相关系数的方法同样可用于数量性状位点的分析和鉴定。Wu等^{[ 15]}在研究棉花的农艺性状时发现, 通过标记与性状的多元线性逐步回归分析, 获得50个AFLP标记与7个农艺性状呈显著相关, 其中1/4标记的贡献率在22%~93%之间。魏志刚等^{[ 16]}通过RFLP标记与性状值间的多元回归分析, 筛选出与白桦纤维长度显著相关的分子标记, 并成功应用于白桦纤维长度分子辅助育种。

多元线性逐步回归法可以快速建立标记与性状之间的相关, 在花生分子育种研究上应用较少。因此, 本研究采用关联遗传学的研究方法, 筛选与农艺性状显著相关的SSR标记, 以期应用于花生农艺性状的分子标记辅助育种。

1 材料与方法

1.1 试验材料

以农家品种四粒红为母本, 黑花生品种冀农黑3号为父本杂交, 经过连续多代自交, 构建了包含251个家系的重组自交系群体。

1464对SSR引物序列来自Peanut Marker Database (http://marker.kazusa.or.jp/Peanut/marker/list/), 由生工生物工程(上海)有限公司合成。

1.2 花生基因组DNA的提取

取鲜嫩叶片约1 g, 采用CTAB法提取基因组DNA^{[ 17]}。在提取液中加入10% 3 mol L^-1的NaAc, 以降低样品糖分含量。用0.8%琼脂糖凝胶电泳检测DNA浓度和纯度, 并将母液浓度稀释至25 ng μL^-1, -20℃保存备用。

1.3 PCR扩增及SSR多态性检测

PCR扩增根据崔顺立等^{[ 18]}的方法并对其优化。PCR体系为15 μL, 含25 ng μL^-1模板2.5 μL, Premix Taq Version 2.0 (TaKaRa) 7.5 μL, 10 μmol μL^-1正、反引物各0.7 μL, ddH₂O 3.6 μL。反应程序如下: 94℃预变性5 min; 94℃变性45 s, 55℃复性45 s, 72℃延伸 1 min, 35个循环; 最后72℃延伸10 min; 4℃保存。PCR产物经8%非变性聚丙烯酰胺凝胶电泳, 检测标记的多态性。

1.4 表型性状的调查

2012年分别在河北农业大学育种中心(保定)和邯郸两地对构建的RIL群体进行种植和表型鉴定。行长1 m, 行距40 cm, 株距10 cm。重复1次, 管理同大田。依据姜慧芳等^{[ 19]}田间调查方法和标准。从每个株行随机取3株, 测定主茎高(height of main stem, HMS)、第一侧枝长(length of first branches, LFB)和总分枝数(total branching number, TNB)。从每个单株选择3个花生测定荚果长(pod length, PL)、荚果宽(pod width, PW)、荚果厚(pod thickness, PT)、种子长(seed length, SL)、种子宽(seed width, SW)、种子厚(seed thickness, ST)、荚果网纹(pod reticulation, PR)、果壳厚度(thickness of pod shell, TPS)。统计收获的3个单株的单株结果数(pod number per plant, PNP)、单株多粒果数(multi-seed number per plant, MSNP)、单株生产力(pod weight per plant, PWP)和单株仁重(seed weight per plant, SWP)等性状。其中, 选取5个典型饱满荚果, 测量果脊两侧最宽处为荚果宽, 取平均值; 测量果脊到腹缝的长度为荚果厚, 取平均值。测量两子叶最宽处为种子宽, 取平均值。测量两条缝之间最厚处为种子厚, 取平均值。测量果壳厚度与去纹果壳厚度之差为荚果网纹, 取平均值。统计收获的3个单株的多粒果数取平均值为单株多粒果数。

1.5 数据统计分析

采用Pearson’s相关分析( P≤0.05, P≤0.01), 计算各农艺性状之间的相关系数和性状与标记的关联程度。利用与农艺性状显著相关的SSR分子标记进行多元线性回归分析, 各个性状作为因变量, 各标记产生的基因型作为自变量。依据Kraakman等^{[ 20]}的逐步回归程序, 选择线性分析中的标记。本研究所有数据均由SPSS 17.0软件统计分析。

2 结果与分析

2.1 亲本及RIL群体农艺性状的遗传变异

四粒红和冀农黑3号间差异幅度较大、变化范围广且呈连续分布, 其中四粒红变异系数范围为3.67%~76.61%, 冀农黑3号变异系数范围为0~53.00%。各家系差异明显且存在超亲现象, 其变异范围为8.38%~87.73% (表1)。

表1 亲本及RIL群体农艺性状的遗传变异 Table 1 Variation of agronomic traits in parents and RIL population

性状 Trait	四粒红 Silihong		冀农黑3号 Jinonghei 3		RIL群体 RIL population
性状 Trait	平均值±标准差 Mean± SD	变异系数 CV (%)	平均值±标准差 Mean± SD	变异系数 CV (%)	平均值±标准差 Mean± SD	范围 Range	变异系数 CV (%)
荚果长 PL (mm)	38.61±3.61	9.35	39.51±3.88	9.83	33.60±4.25	20.70-45.71	12.65
荚果宽 PW (mm)	13.38±1.25	9.34	15.41±0.67	4.34	12.86±1.09	9.93-16.34	8.46
荚果厚 PT (mm)	13.71±1.24	9.05	16.12±0.98	6.09	13.86±1.27	11.04-19.38	9.13
荚果长/宽PL/W	2.91±0.39	13.28	2.56±0.22	8.39	2.68±0.41	1.82-4.79	15.34
种子长 SL (mm)	13.52±1.08	7.96	20.21±2.08	10.28	15.47±1.36	11.68-21.41	8.79
种子宽 SW (mm)	8.29±0.63	7.60	9.70±1.73	17.81	7.85±0.66	6.10-12.13	8.38
种子厚 ST (mm)	7.49±0.55	7.35	8.63±0.86	9.96	7.38±0.65	6.02-11.11	8.75
种子长/宽 SL/W	1.64±0.19	11.68	2.14±0.33	15.50	2.03±0.28	1.40-3.72	13.69
果壳厚度 TPS (mm)	1.07±0.18	16.96	1.64±0.30	18.04	1.08±0.23	0.55-1.84	21.57
荚果网纹 PR (mm)	0.17±0.13	76.61	0.37±0.19	53.00	0.23±0.09	0.08-0.66	39.80
单株结果数 PNP	14.67±2.08	14.19	17.00±3.74	22.01	13.46±4.27	5.00-38.50	31.75
单株多粒果数 MSNP	6.67±0.58	8.66	0	0	1.19±1.04	0-4.67	87.73
单株果重PWP (g)	20.96±4.58	21.83	30.37±6.64	21.86	12.88±4.25	3.36-28.37	32.99
单株仁重 SWP (g)	15.00±2.74	18.27	17.61±4.26	24.18	8.43±2.87	1.72-18.52	34.11
单株出仁率 SRP (%)	72.00±3.00	3.67	57.66±3.27	5.67	0.65±0.06	0.34-0.76	8.75
主茎高 HMS (cm)	53.00±13.21	24.92	43.50±10.21	23.48	38.71±8.54	17.00-76.67	22.07
侧枝长 LFB (cm)	63.67±16.97	26.65	48.33±10.31	21.33	46.48±9.92	22.50-86.33	21.35
总分枝数 TBN	5.33±1.37	25.62	8.00±1.10	13.69	6.05±1.86	3.67-17.67	30.78

PL: pod length; PW: pod width; PT: pod thickness; PL/W: pod length/width; SL: seed length; SW: seed width; ST: seed thickness; SL/W: seed length/width; TPS: thickness of pod shell; PR: pod reticulation; PNP: pod number per plant; MSNP: multi-seed number per plant; PWP: pod weight per plant; SWP: seed weight per plant; SRP: shelling percentage per plant; HMS: height of main stem; LFB: length of first branches, TBN: total branching number.

表1 亲本及RIL群体农艺性状的遗传变异 Table 1 Variation of agronomic traits in parents and RIL population

2.2 农艺性状间的相关性

由表2可以看出, 荚果长与荚果宽、荚果厚度、荚果长宽比、种子长、种子厚度、种子长宽比、果壳厚度、单株多粒果数、单株生产力、单株仁重、主茎高和第一侧枝长呈正相关且达到极显著水平( P≤0.01), 而与荚果网纹显著相关( P≤0.05)。其中相关性最高为单株生产力和单株仁重( r=0.970), 其次是主茎高和第一侧枝长( r=0.918), 荚果宽和荚果厚度( r=0.806)。10个农艺荚果性状均与单株生产力呈不同程度极显著正相关。荚果宽与荚果厚( r=0.806)、果壳厚度( r=0.620) 和种子长( r=0.519)呈显著正相关。单株结果数、单株多粒果数和单株生产力分别与单株仁重( r=0.758, r=0.491, r=0.970)呈极显著正相关。单株生产力与单株仁重分别与主茎高、第一侧枝长呈极显著正相关。单株结果数与总分枝数呈极显著相关( r=0.165)。荚果长/宽、果壳厚度、单株多粒果数均与产量性状(果重、仁重、出仁率)呈不同程度的极显著正相关。由此看出, 多个农艺性状都对单株生产力有影响, 对这些性状的直接选择, 将对单株生产力有所改变^{[ 21]}。

表2 农艺性状间相关性系数 Table 2 Correlation coefficients among agronomic traits

2.3 SSR标记与农艺性状的相关性

经过1464对SSR引物的双亲多态性筛选, 获得多态性引物139对, 多态率为10.5%。SSR标记和农艺性状的相关分析表明(表3)多个标记与单一性状相关, 其中, 2个与荚果长相关, 14个与荚果宽相关, 12个与荚果厚相关, 2个与荚果长宽比相关, 5个与种子长相关, 12个与种子宽相关, 4个与种子厚相关, 5个与种子长宽比相关, 14个与果壳厚度相关, 2个与荚果网纹相关, 6个与单株结果数相关, 9个与单株多粒果数相关, 7个与单株生产力相关, 4个与单株仁重相关, 16个与单株出仁率相关, 13个与主茎高相关, 12个与第一侧枝长相关, 6个与总分枝数相关。另外, 部分SSR标记与多个农艺性状相关联。标记AhTE0561与荚果宽( r=0.164)、荚果厚( r=0.163)、果壳厚度( r=0.185)、第一侧枝长( r=0.170)、单株生产力( r=0.129)和主茎高 ( r=0.155)均呈显著正相关, 推测携带标记AhTE0561的花生品种, 其荚果宽、荚果厚、果壳厚度、单株生产力、第一侧枝长和主茎高等性状将有一定程度的提高。标记GM2638与荚果网纹( r= -0.158)、单株结果数( r= -0.140)、单株生产力( r= -0.163)和单株仁重( r= -0.168)均呈显著负相关, 推测携带标记GM2638的花生其网纹比较浅, 单株结果数、单株生产力和单株仁重将会相对较低。

表3 部分SSR标记和农艺性状之间的相关系数 Table 3 Correlation coefficients between partial SSR markers and agronomic traits

标记 Marker	PL	PW	PT	PL/W	SL	SW	ST	SL/W	TPS
GM2638	-0.037	0.051	0.025	-0.089	-0.06	-0.038	-0.158^*	0.023	-0.018
AhTE0561	0.080	0.164^**	0.163^**	0.012	0.055	0.096	-0.031	0.013	0.185^**
Ah3TC38C01	-0.041	-0.005	-0.103	-0.059	-0.107	-0.100	-0.062	-0.008	0.044
S54	-0.069	-0.031	0.049	-0.064	0.036	0.038	-0.049	-0.023	-0.025
seq2E06	-0.013	0.076	-0.019	-0.167^**	0.031	0.112	0.028	-0.063	0.104
gi_0832	0.091	0.127^*	0.172^**	-0.024	0.092	0.046	0.057	0.014	0.061
seq9A7_2	-0.042	0.044	0.075	-0.060	-0.085	0.069	0.048	-0.158^*	0.042
pPGSseq18C5	0.050	0.110	0.060	-0.041	0.114	0.211^**	0.006	-0.098	0.062
GM1996	0.071	0.089	0.113	-0.024	0.003	0.079	0.033	-0.012	-0.009
RN9C02	0.121	-0.025	-0.017	0.044	0.043	-0.035	-0.107	-0.001	-0.034
GM1502	0.006	0.155^*	0.125^*	-0.114	0.012	0.152^*	0.045	-0.057	0.112
EM_152	0.040	0.083	0.005	-0.041	0.026	0.165^**	0.030	-0.075	-0.039
pPGPseq3B8	0.080	0.140^*	0.135^*	-0.017	0.117	0.152^*	0.017	-0.039	0.137^*
TC4G10	0.087	0.052	0.119	0.000	0.031	0.114	-0.084	-0.112	-0.001
Ah-394	0.076	0.072	0.051	0.001	0.001	-0.018	0.002	-0.046	0.079
标记 Marker	PR	PNP	MSNP	PWP	SWP	SRP	HMS	LFB	TBN
GM2638	0.059	-0.140^*	-0.049	-0.163^**	-0.168^**	0.016	0.011	0.011	0.109
AhTE0561	0.078	0.080	0.071	0.129^*	0.087	-0.117	0.155^*	0.170^**	0.008
Ah3TC38C01	0.118	0.128^*	0.037	0.051	0.015	-0.047	-0.038	-0.054	0.051
S54	0.023	-0.064	-0.052	-0.078	-0.039	0.211^**	0.049	0.055	0.007
seq2E06	0.082	-0.067	-0.040	-0.025	-0.026	0.039	0.031	0.044	0.070
gi_0832	0.114	-0.056	-0.067	-0.035	-0.039	0.074	0.126^*	0.095	0.101
seq9A7_2	0.005	0.186^**	-0.076	0.124^*	0.116	-0.054	-0.045	-0.008	0.055
pPGSseq18C5	0.083	-0.040	0.006	0.044	0.069	0.119	0.052	0.046	-0.166^**
GM1996	0.008	0.099	0.141^*	0.107	0.119	-0.007	-0.119	-0.102	-0.084
RN9C02	0.057	0.042	0.192^**	0.053	0.076	0.117	0.082	0.048	-0.073
GM1502	0.025	-0.035	-0.001	0.013	0.004	-0.019	0.006	-0.027	-0.138^*
EM_152	-0.049	-0.015	-0.058	-0.021	-0.024	0.031	0.055	0.041	-0.068
pPGPseq3B8	0.166^**	0.029	-0.072	0.050	0.054	0.055	0.153^*	0.172^**	-0.070
TC4G10	0.048	0.142^*	0.023	0.132^*	0.163^**	0.135^*	0.114	0.143^*	-0.006
Ah-394	0.018	0.006	0.167^**	0.044	0.041	-0.075	0.053	0.059	-0.071

^*,^**分别为0.05和0.01的显著水平; PL; 荚果长; PW; 荚果宽; PT; 荚果厚; PL/W; 荚果长宽比; SL; 种子长; SW; 种子宽; ST; 种子厚; SL/W; 种子长宽比; TPS; 果壳厚度; PR; 荚果网纹; PNP; 单株结果数; MSNP; 单株多粒果数; PWP; 单株生产力; SWP; 单株仁重; SRP; 单株出仁率; HMS; 主茎高; LFB; 第一侧枝长; TBN; 总分枝数。

^*,^**significant at 0.05 and 0.01 probability levels, respectively; PL: pod length; PW: pod width; PT: pod thickness; PL/W: pod length/width; SL: seed length; SW: seed width; ST: seed thickness; SL/W: seed length/width; TPS: thickness of pod shell; PR: pod reticulation; PNP: pod number per plant; MSNP: multi-seed number per plant; PWP: pod weight per plant; SWP: seed weight per plant; SRP: shelling percentage per plant; HMS: height of main stem; LFB: length of first branches; TBN: total branching number.

表3 部分SSR标记和农艺性状之间的相关系数 Table 3 Correlation coefficients between partial SSR markers and agronomic traits

2.4 SSR标记与农艺性状的多元线性逐步回归分析

获得了14个标记与13个农艺性状关联, 贡献率 R²的范围在5.2%~11.5%之间(表4)。其中标记ARS754、Ah3TC38C01对花生荚果长所解释的总变异范围为5.2%~8.5%, 标记GM2638对荚果宽和单株出仁率所解释的变异分别为6.2%和7.7%, 标记GM1996、S54和seq2E06对荚果厚所解释的变异的范围是5.4%~6.1%, 标记GM2137对荚果长/宽、种子长和种子宽所解释的变异分别为11.5%、9.6%和7.7%。标记Ah3TC38C01对花生荚果网纹所解释的变异为5.4%, 标记GM1878、RM13A12对果壳厚度所解释的总变异为5.5%~10.0%。与产量密切相关的标记seq9A7_2、gi_0832和GM2638分别对单株生产力、单株仁重和单株出仁率所解释的总变异为6.5%、6.9%和7.7%, 与花生植株性状相关的标记AhTE0561对第一侧枝长所解释的表型变异为5.7%。标记GM1878、pPGSseq18C5、RM13A12和gi_0832对总分枝数所解释的表型变异范围为6.1%~ 8.9%。表2中与性状显著相关的SSR标记与逐步回归分析后的部分标记部分一致。例如, 标记AhTE0561与第一侧枝长, 标记pPGSseq18C5和总分枝数, 标记TC11A04和种子宽, 标记RM13A12和果壳厚度均呈极显著相关, 同样还有标记seq9A7_2与单株生产力, 标记GM1878与总分枝数呈显著相关。未获得与种子厚、种子长宽比、单株结果数、单株多粒果数和主茎高相关的SSR标记。

表4 SSR标记和农艺性状之间的多元逐步回归分析 Table 4 Stepwise multiple regression analysis between SSR markers and agronomic traits

3 讨论

许多复杂的数量性状可通过数理统计分析法将其剖分为若干离散的孟德尔因子进行研究, 进而将数量性状位点(QTL)锚定于染色体的特定位置, 并确定其与周围基因或标记间相互关系。利用单一标记为基础的方法检测QTL时, 常用的分析统计指标为均值或方差, 通过比较基因型位点表达性状的均值或方差, 对均值进行 t测验或对方差进行 F测验, 依据测验值的显著水平确定标记与性状间相互关联的可能性。Wu等^{[ 15]}通过标记与性状的多元线性逐步回归分析, 获得50个AFLP标记与7个棉花农艺性状显著相关, 其中1/4标记的贡献率在22%~93%之间, 此结果与其QTL研究吻合。杨鑫雷等^{[ 22]}通过标记与性状的逐步多元回归分析, 建立了两者的关联关系, 并且所解释的总变异率最高达30%。例如, 标记EM_245与多个性状存在显著的相互关联, 并且与杨鑫雷等^{[ 22]}的QTL定位结果一致。由此说明, 采用多元逐步回归分析法可快速、准确地分析标记与性状的关联关系。本研究利用相同的统计方法, 表明农艺性状之间存在显著或极显著相关, 相似性程度最高的为单株生产力和单株仁重, 相关系数为0.970。77个SSR标记与18个农艺性状显著或极显著相关, 标记数量最多的性状为单株出仁率, 最少的为荚果长、荚果长宽比和荚果网纹, 变化范围为2~16个。Pearson’s相关分析表明, 1~2个标记能够影响多个性状的表现, 并与性状建立显著的相关, 进而通过标记与性状的多元逐步回归分析, 建立两者的关联关系, 并且所解释的总变异率的变化范围为5.2%~11.5%。

与目前较为广泛应用的基于最大似然统计的复合区间作图法相比, 逐步多元线性回归方法是利用标记与性状的回归分析, 通过决定系数( R²)的大小, 来确定标记与性状的紧密程度, 可快速确定标记与性状是否存在显著关联关系, 消除复合区间作图时QTL区段两侧标记的影响, 提高QTL定位的准确性。此方法可以对任何单独的分子标记进行相关性分析, 无需构建高密度的遗传连锁图谱, 就可以找到与目标性状相关联的标记, 可用于MAS辅助选择育种, 提高优良性状的选择效率, 缩短育种进程, 为花生的遗传改良提供理论依据。随着遗传连锁图谱标记的不断增加, 这类方法的效率也将有很大的提高, 将成为育种家普遍接受的研究方法。

4 结论

18个农艺性状间存在不同程度的相关性, 其中10个农艺性状与产量相关性状极显著相关。77个SSR标记与18个农艺性状相关, 每个性状相关的标记数在2~16之间。标记与农艺性状的多元逐步回归分析获得14个标记与13个性状关联, 贡献率范围为5.2%~11.5%, 为花生农艺性状的分子标记辅助选择奠定了基础。

The authors have declared that no competing interests exist.

作者已声明无竞争性利益关系。

参考文献

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2002

0.0

... 通过表型选择的传统育种方法改良农艺性状周期长, 选择效率低^[1] ...

... 目前, 利用覆盖全基因组的分子遗传连锁图和合适的分离群体进行连锁分析以及数量性状位点(quantitative trait locus, QTL)定位是解析植物数量性状遗传基础的主要方法^[1], 并且在花生中已被广泛应用^{[5,6,7,8,9,10,11,12]} ...

2002

1.175

0.0

... 随着分子生物学的飞速发展, 分子标记技术得到广泛应用, 通过筛选与目标性状紧密连锁的分子标记, 即分子标记辅助选择(marker-assisted selection, MAS)对目标性状进行改良, 可以加快育种进程, 提高育种效率^[2] ...

1996

3.251

0.0

... 众多分子标记技术中, 简单序列重复标记技术(simple sequence repeat, SSR)以其检测容易、重复性高和稳定性好等优点已被广泛用于作物目标性状的遗传改良研究^[3] ...

2009

0.0

1.667

. 2009, 35:395-402 DOI:10.3724/SP.J.1006.2009.00395

Construction of genetic linkage map in peanut (Arachis hypogaea L.) cultivars

Crops Research Institute, GuangdongAcademy of Agricultural Sciences,Guangzhou 510640,China

Molecular genetic map is a fundamental organizational tool for genomic research. However, a comprehensive genetic linkage map for peanut cultivars has not yet been developed due to extremely low levels of DNA polymorphisms in cultivated peanut. In this study, 184 recombinant inbred lines (RIL), derived from a cross between two Spanish type peanut cultivars (Yueyou 13 × Fu95-5), were used as mapping population. A total of 652 pairs of genomic-SSR primers and 392 pairs of EST-SSR primers were used to detect the polymorphisms between the parental cultivars. Of them, 121 SSR primer pairs amplified 123 segregating loci and were selected to analyze the RIL population. A genetic linkage map consisting of 108 SSR loci (102 genomic-SSR and 6 EST-SSR) in 20 linkage groups and covers 568 cM with an average distance of 6.45 cM of intermaker was constructed. By comparing the SSR genetic map of Arachis (A. duranensis × A. stenosperma) with AA genome, 11 linkage groups in the linkage map constructed in this study were confirmed to have homology with 6 linkage groups of wild peanut species.

花生栽培种品种间分子多态性相对缺乏, 至今未构建出较完整的分子遗传图谱。本研究以粤油13和阜95-5为亲本, 通过杂交构建包含184个F6重组自交系的遗传作图群体。采用652对genomic-SSR引物和392对EST-SSR引物对亲本进行多态性检测, 从中筛选出121对多态性引物, 在亲本中共检测到123个多态性位点。利用作图群体对多态性SSR位点进行遗传连锁分析, 获得包含108个SSR标记(102个genomic-SSR标记和6个EST-SSR标记), 涉及20个连锁群, 总长568 cM, 平均图距为6.45 cM的花生栽培种遗传图谱。与前人构建的花生野生种(A. duranensis × A. stenosperma, AA genome)SSR遗传图谱比较, 初步确定本研究构建的遗传图谱中有11个连锁群与野生种遗传图谱的6个连锁群存在同源关系。

... 因此, 仍有学者认为分子育种, 如MAS很难在短期内用于花生各种性状的改良^[4] ...

2010

0.0

0.951

. 2010, 25(6):81-86

Construction of AFLP genetic linkage map and detection of QTLs for bacterial wilt resistance in peanut (Arachis hypogaea L.)

青枯病抗性分子标记能为花生抗青枯病育种提供辅助选择技术,以抗青枯病品种远杂9102与感病品种Chico杂交构建的重组自交系群体(RIL)为材料,用66对具多态性的引物(EcoR I/Mse I引物组合35对,Mlu I/Mse I引物组合14对,Pst I/Mse I引物组合17对)对其进行扩增,共检测到324个多态性位点.应用JoinMap(R)3.0软件对这些多态性位点进行遗传连锁分析,构建了一张栽培种花生的AFLP遗传连锁图.该图谱包含98个AFLP标记,涉及20个连锁群,覆盖总距离285 cM,标记间平均图距为2.90 cM.结合RIL群体的青枯病抗性鉴定结果,利用分析软件QTLNetwork(R)2.0共检测到与青枯病抗性相关的3个QTL(qBW'J、qBW'2和qBW'3).其中,qBW'1和qBW'2均位于第4连锁群,qBW'3位于第14连锁群.这3个QTL形成2对具有加性×加性上位性互作效应的QTL区段(qBW'1/qBW'3和qBW'2/qBW'3),贡献率分别为12.81%和16.56%,共解释青枯病抗性总变异的21.62%.

2010

3.658

0.0

. 2010, 121:971-984 DOI:10.1007/s00122-010-1366-x

A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.)

1.University of Agricultural Sciences (UAS), Krishinagar, Dharwad, 580 005 Karnataka India 2.International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, 502 324 Andhra Pradesh India 3.Genomics towards Gene Discovery Sub Programme, Generation Challenge Programme (GCP), c/o CIMMYT, Int APDO, Postal 6-641, 06600 Mexico, DF, Mexico

Late leaf spot (LLS) and rust are two major foliar diseases of groundnut (Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTL_rust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing.

2011

0.0

2011

2.463

0.0

2012

3.251

0.0

. 2012, 30:757-772 DOI:10.1007/s11032-011-9660-0

Quantitative trait locus analysis and construction of consensus genetic map for drought tolerance traits based on three recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.)

<li>1.International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, 502 324, India</li><li>2.Institute of Science and Technology, Jawaharlal Nehru Technological University Hyderabad (JNTUH), Greater Hyderabad, 500 085, India</li><li>3.Directorate of Groundnut Research (DGR), Junagadh, 362 001, India</li><li>4.University of Agricultural Sciences, Dharwad, 580 005, India</li><li>5.The University of Georgia, Athens, GA, 30602, USA</li><li>6.CGIAR-Generation Challenge Programme (GCP), c/o CIMMYT, 06600, Mexico, DF, Mexico</li>

Abstract
Groundnut (Arachis hypogaea L.) is an important food and cash crop grown mainly in semi-arid tropics (SAT) regions of the world where drought is the major constraint on productivity. With the aim of understanding the genetic basis and identification of quantitative trait loci (QTL) for drought tolerance, two new recombinant inbred line (RIL) mapping populations, namely ICGS 76 × CSMG 84-1 (RIL-2) and ICGS 44 × ICGS 76 (RIL-3), were used. After screening of 3,215 simple sequence repeat (SSR) markers on the parental genotypes of these populations, two new genetic maps were developed with 119 (RIL-2) and 82 (RIL-3) SSR loci. Together with these maps and the reference map with 191 SSR loci based on TAG 24 × ICGV 86031 (RIL-1), a consensus map was constructed with 293 SSR loci distributed over 20 linkage groups, spanning 2,840.8 cM. As all these three populations segregate for drought-tolerance-related traits, a comprehensive QTL analysis identified 153 main effect QTL (M-QTL) and 25 epistatic QTL (E-QTL) for drought-tolerance-related traits. Localization of these QTL on the consensus map provided 16 genomic regions that contained 125 QTL. A few key genomic regions were selected on the basis of the QTL identified in each region, and their expected role in drought adaptation is also discussed. Given that no major QTL for drought adaptation were identified, novel breeding approaches such as marker-assisted recurrent selection (MARS) and genomic selection (GS) approaches are likely to be the preferred approaches for introgression of a larger number of QTL in order to breed drought-tolerant groundnut genotypes.

2012

0.0

0.95

. 2012, 34:311-315

Identification of QTLs for important quality traits in cultivated peanut (Arachis hypogaea L.)

以郑8903×豫花4号的215个重组自交系群体（RILs）为材料，采用2008年原阳种植材料(F8)的品质检测数据，运用WinQTLCart 2.5软件进行与花生蛋白质、脂肪及脂肪酸含量相关的QTLs定位分析。研究结果显示，检测到2个与蛋白质含量相关的QTLs，遗传贡献率分别为4.82%和9.66%；2个与脂肪含量相关的QTLs，遗传贡献率分别为5.25%和8.24%。与油酸、亚油酸、硬脂酸和山嵛酸含量相关的QTL各检测到1个，遗传贡献率分别为5.13%、8.28%、24.14%和7.88%；2个与花生酸含量相关的QTLs，遗传贡献率分别为7.12%和18.32%。

2012

3.251

0.0

. 2012, 30:773-788 DOI:10.1007/s11032-011-9661-z

Quantitative trait locus analysis and construction of consensus genetic map for foliar disease resistance based on two recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.)

<li>1.International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, 502 324, India</li><li>2.Department of Genetics and Plant Breeding, University of Agricultural Sciences, Dharwad, 580 005, India</li><li>3.Department of Biotechnology, University of Agricultural Sciences, Dharwad, 580 005, India</li><li>4.Department of Plant Pathology, University of Agricultural Sciences, Dharwad, 580 005, India</li><li>5.Directorate of Groundnut Research (DGR), Junagadh, 362 001, India</li><li>6.The University of Georgia, Athens, GA, 30602, USA</li><li>7.CGIAR-Generation Challenge Programme (GCP), c/o CIMMYT, Mexico, DF, 06600, Mexico</li>

Abstract
Late leaf spot (LLS) and rust have the greatest impact on yield losses worldwide in groundnut (Arachis hypogaea L.). With the objective of identifying tightly linked markers to these diseases, a total of 3,097 simple sequence repeats (SSRs) were screened on the parents of two recombinant inbred line (RIL) populations, namely TAG 24 × GPBD 4 (RIL-4) and TG 26 × GPBD 4 (RIL-5), and segregation data were obtained for 209 marker loci for each of the mapping populations. Linkage map analysis of the 209 loci resulted in the mapping of 188 and 181 loci in RIL-4 and RIL-5 respectively. Using 143 markers common to the two maps, a consensus map with 225 SSR loci and total map distance of 1,152.9 cM was developed. Comprehensive quantitative trait locus (QTL) analysis detected a total of 28 QTL for LLS and 15 QTL for rust. A major QTL for LLS, namely QTL_LLS01 (GM1573/GM1009-pPGPseq8D09), with 10.27–62.34% phenotypic variance explained (PVE) was detected in all the six environments in the RIL-4 population. In the case of rust resistance, in addition to marker IPAHM103 identified earlier, four new markers (GM2009, GM1536, GM2301 and GM2079) showed significant association with the major QTL (82.96% PVE). Localization of 42 QTL for LLS and rust on the consensus map identified two candidate genomic regions conferring resistance to LLS and rust. One region present on linkage group AhXV contained three QTL each for LLS (up to 67.98% PVE) and rust (up to 82.96% PVE). The second candidate genomic region contained the major QTL with up to 62.34% PVE for LLS. Molecular markers associated with the major QTL for resistance to LLS and rust can be deployed in molecular breeding for developing groundnut varieties with enhanced resistance to foliar diseases.

2012

4.354

0.0

. 2012, 12:26- DOI:10.1186/1471-2229-12-26

Fostered and left behind alleles in peanut: interspecific QTL mapping reveals footprints of domestication and useful natural variation for breeding

<li>1.Cirad, UMR AGAP, TA A108/3, Avenue Agropolis, Montpellier, F-34398, France</li><li>2.ISRA/Ceraas, Route de Khombole, BP 3320, Thiès Escale, Senegal</li><li>3.Embrapa Recursos Genéticos e Biotecnologia, C.P. 02372, CEP 70.770-900, Brasilia, DF, Brazil</li><li>4.Universidade de Brasília, Campus Universitário, CEP 70.910-900, Brasília, DF, Brazil</li>

2003

0.0

. 2003, 23(4):14-18

Status quo and tendency in construction of forest frees genetic linkage maps

林木具有世代长、高度杂合、遗传负荷大等遗传特性,使其遗传图谱研究不同于其他物种.高质量林木遗传图谱,可进行林木近缘树种比较图谱研究,了解林木的基因组结构和进化历程,进行有效QTL定位研究及开展林木复杂性状的标记辅助选择.目前林木作图存在着群体较小,构建的图谱和定位的QTL存在连锁平衡,以及作图策略未充分考虑林木的遗传学特性等问题.扩大作图群体、选择高度保守的标记系统以及研究适合林木作图的理论和方法将有助于林木基因组研究向纵深发展.

... 然而, 通过分离群体筛选目标性状的QTL存在一定的局限性, 由于不同实验室采用的群体类型、标记种类及数量和环境等诸多因素的干扰, 导致QTL定位结果重复性较低^[13] ...

1994

0.0

... 例如, 徐云碧等^[14]在研究水稻农艺性状时, 计算了性状与标记间的相关系数, 在显著(P=0 ...

2007

1.643

0.0

. 2007, 153:153-163 DOI:10.1007/s10681-006-9250-0

AFLP marker associations with agronomic and fiber traits in cotton

1.Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762, USA 2.Crop Science Research Laboratory, USDA-ARS, P.O. Box 5367, Mississippi State, MS 39762, USA 3.Bayer Cotton Seed International, Leland, MS 38756, USA

DNA markers linked with major QTL contributing to traits of importance will be a useful tool for cotton (Gossypium spp.) genetics and breeding. We crossed four photoperiod-sensitive accessions of cotton, G. hirsutum L., with a cultivar, selected day-neutral plants and backcrossed four times to each of the four photoperiod-sensitive accessions, selecting day-neutral plants at each generation. The day-neutral plants from the first cross and the four backcross generations were advanced to the F₆. These 20 day-neutral lines and four cultivars were grown in two environments at Mississippi State, MS and scored for seven agronomic and fiber quality traits. They were also scored for AFLP markers using a bulk sample of leaves from each of 24 lines. More than 50 AFLP markers were associated with the seven traits with fewer markers associated with fiber than agronomic traits. However, one to four markers were associated with 22–93% of the phenotypic variability of each of the seven traits. The results suggest that selected markers could be used in marker assisted selection (MAS) in crosses designed to use alleles from exotic accessions or cultivars to develop elite breeding lines for cotton improvement.

... Wu等^[15]在研究棉花的农艺性状时发现, 通过标记与性状的多元线性逐步回归分析, 获得50个AFLP标记与7个农艺性状呈显著相关, 其中1/4标记的贡献率在22%~93%之间 ...

... Wu等^[15]通过标记与性状的多元线性逐步回归分析, 获得50个AFLP标记与7个棉花农艺性状显著相关, 其中1/4标记的贡献率在22%~93%之间, 此结果与其QTL研究吻合 ...

2006

0.0

1.23

... 魏志刚等^[16]通过RFLP标记与性状值间的多元回归分析, 筛选出与白桦纤维长度显著相关的分子标记, 并成功应用于白桦纤维长度分子辅助育种 ...

2008

0.0

. 2008, 37(1):29-31

Genome DNA extracted with CTAB method and its use for SSR and SRAP

本试验采用相对简单快捷的CTAB法提取花生总DNA,并应用于SSR和SRAP扩增分析,结果表明,所提取花生DNA中RNA含量高,但完全可以满足SSR标记和SRAP标记分析要求.

... 2 花生基因组DNA的提取取鲜嫩叶片约1 g, 采用CTAB法提取基因组DNA^[17] ...

2009

0.0

1.889

. 2009, 42:3346-3353

Genetic diversity of peanut landrace in hebei province revealed by SSR markers

(河北农业大学农学院/河北省作物种质资源重点实验室)

【Objective】 In order to assess the genetic diversity of peanut landraces from Hebei province and provide a theoretical basis for peanut breeding. 【Method】 Genetic diversity of 75 accessions of peanut landraces with different botanical types, collected from Hebei province, was evaluated by 20 SSR molecular markers. 【Result】 Sixty-five alleles were detected. The average number of alleles per locus was 3.25 with a range from 2 to 6. Total Shannon information index of per locus varied widely from 0.1680 (7G02) -1.3617 (PM15) with an average value of 0.5448; Total Nei’s genetic diversity index of Nei per locus varied widely from 0.3385 (7G02) -0.9013 (PM384) with an average value of 0.6458; The accessions of A. hypogaea showed higher genetic diversity than those of A. vulgaris and A. fastigiata. Cluster analysis with UPGMA showed that the materials tested could be divided into 2 groups: the first group was A. vulgaris and A. fastigiata group, the second was A. hypogaea group and the genetic relationship among these landraces was not in accord with their geographical origins. 【Conclusion】 The peanut landraces from Hebei province showed higher genetic diversity revealed by SSR markers.

【目的】揭示河北省花生地方品种的遗传多样性,为花生育种提供理论依据。【方法】利用20对SSR引物对75个河北省不同植物类型花生地方品种遗传多样性进行分析。【结果】共检测到65个等位基因,每个位点的等位基因变幅为2～6个,平均3.25个;平均Shannon信息指数为0.5448,变幅为0.1680(7G02)～1.3617(PM15);平均Nei基因多样性指数为0.6458,变幅为0.3385(7G02)～0.9013(PM384);普通型花生地方品种的遗传多样性明显大于多粒型和珍珠豆型。采用类平均法对欧氏距离进行聚类,可以将各地方品种分为两大类,第Ⅰ类群为珍珠豆型和多粒型花生地方品种,第Ⅱ类群为普通型花生地方品种,品种间的亲缘关系与地理来源关系不大。【结论】SSR检测结果表明,河北省花生地方品种的多样性程度较高。

... 3 PCR扩增及SSR多态性检测PCR扩增根据崔顺立等^[18]的方法并对其优化 ...

2006

0.0

... 依据姜慧芳等^[19]田间调查方法和标准 ...

2004

4.389

0.0

... 依据Kraakman等^[20]的逐步回归程序, 选择线性分析中的标记 ...

2010

0.0

0.95

. 2010, 32:212-216

Agronomic character and cluster analysis of peanut cultivars

应用DPS统计软件对18个花生品系的主要农艺性状的考种数据进行变异性、相关性和聚类分析。结果表明，主茎高、总分枝数、结果枝数、单株荚果数变异系数较大。主茎高与侧枝长、百果重与百仁重均呈极显著正相关；单株荚果产量与主茎高、侧枝长、总分枝数、结果枝数、单株果数、百果重、百仁重均呈正相关，与出米率呈负相关。18个花生品系因参与聚类的性状组合不同而聚类结果各异，综合性状的聚类在D2=5.91水平下分为4大类，其中第一类（1号和13号品系）和第四类（8、11、18）表现良好，值得推广种植。

... 由此看出, 多个农艺性状都对单株生产力有影响, 对这些性状的直接选择, 将对单株生产力有所改变^[21] ...

2013

0.0

1.462

. 2013, 25:211-216 DOI:1002-7807(2013)03-0211-06

AFLP marker association with important agronomic traits in cotton

1. North China Key Laboratory for Crop Germplasm Resources of Education Ministry / Key Laboratory of Crop Germplasm Resources of Hebei / Agricultural University of Hebei, Baoding, Hebei 071001, China; 2. School of Chemistry and Biological Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu 215009, China

In this study, we designed AFLP(Amplified fragment length polymorphism) markers associated with important agronomic traits using 91 BC₁F₂ plants derived from an interspecific cross between Gossypium hirsutum cv. CCRI 8 and G. barbadense cv. Pima 90-53. Ninety-one rows of BC₁F_2:3 plants were grown in the fields at Baoding suburban, Qingxian County, Hebei Province, China. The rows were scored for five yield traits-lint percentage, seed weight, boll weight, lint weight, and seed cotton weight, and five fiber quality traits-2.5% span length, micronaire, fiber uniformity, fiber elongation, and fiber strength. To provide a theoretical basis for marker-assisted selection, correlations between molecular markers and agronomic traits were tested by stepwise multiple linear regression analysis. Based on the regression analysis, 125 loci from 20 AFLP primer combinations were correlated with the 10 measured traits, although the correlations were only significant (P ≤0.05, P ≤0.01) for 15 loci from 4 primer pair combinations. In addition, six loci were associated with 6.2%-30% of the phenotypic variability observed in nine traits. Our results indicate that these AFLP markers should be useful for molecular marker-assisted selection in future cotton breeding.

以陆地棉（Gossypium hirsutum L.）品种中棉所8号和海岛棉（Gossypium barbadense L.）品种Pima 90-53杂交产生的包含91个单株的BC₁F₂群体及其衍生BC₁F_2:3群体为材料，利用逐步多元回归分析确定分子标记与重要农艺性状的相关关系，为分子标记辅助选择提供依据。试验材料分别种植在保定市郊和沧州青县两个点，每个株行考察衣分、子指、铃重、皮棉重、子棉重5个产量性状和2.5%纤维跨距长度、马克隆值、纤维整齐度、纤维伸长率、纤维比强度5个品质性状。以20对AFLP引物组合产生的125个位点对10个重要农艺性状进行多元线性回归分析，发现其中4对引物组合产生的15个位点与10个性状有着显著相关性（P≤0.05，P≤0.01），而后通过逐步多元回归分析获得6个位点，对9个农艺性状所解释的表型变异为6.2%～30%。结果表明，与9个农艺性状显著相关的6个AFLP位点可以用于未来的分子标记辅助育种计划。

... 杨鑫雷等^[22]通过标记与性状的逐步多元回归分析, 建立了两者的关联关系, 并且所解释的总变异率最高达30% ...

... 例如, 标记EM_245与多个性状存在显著的相互关联, 并且与杨鑫雷等^[22]的QTL定位结果一致 ...