基于SSR分子标记的山地刺槐克隆生长空间格局分析

doi:10.11707/j.1001-7488.LYKX20220483

摘要/Abstract

摘要：

目的: 以河北省平泉市黄土梁子林场刺槐林为研究对象，验证已开发刺槐SSR引物的多态性，探究刺槐萌蘖分布格局，为人工促进刺槐林萌蘖更新提供理论依据。方法: 在河北省平泉市黄土梁子林场选取3块刺槐萌蘖现象明显的样地，利用9对SSR引物对125株刺槐进行亲缘关系鉴定，采用传统样地调查法和可变尺度的相邻格子法划分5个取样尺度(5 m×5 m、5 m×10 m、10 m×10 m、10 m×15 m、20 m×30 m)，计算偏离指数(C)以及其t检验、Cassie指标(CA)、平均拥挤度(m*)、负二项指数(K)、Green指数(GI)和聚块性指标(PAI)6个格局判定参数，判断山地刺槐格局和规模。结果: 9对引物对样地内刺槐表现出良好多态性，平均多态信息含量为0.76。3块样地内，共有73个基因型，鉴定出76个克隆分株。刺槐萌蘖分布格局随取样尺度增大聚集格局逐渐减弱，尺度由小到大分布格局由集群分布到随机分布，在5 m×5 m尺度下具有最强聚集格局规模。结论: 基于SSR分子标记与生态学调查相结合，探索萌蘖扩散格局研究新方法，阐明山地刺槐萌蘖分布格局，对刺槐萌蘖更新理论有了进一步理解。无干扰状态下，刺槐林经历采伐后萌蘖分布格局为聚集分布。萌蘖植株在小范围聚集分布会造成基因型单一，不利于种群多样性，建议对距离过近影响正常生长发育的个体进行疏伐，缓解竞争关系，提高林分质量。

关键词: 刺槐, SSR, 萌蘖, 分布格局

Abstract:

Objective: This study was carried out in black locust (Robinia pseudoacacia) forest in Huangtuliangzi, Pingquan City, Hebei Province, China, to verify the polymorphism of developed SSR primers of black locust, explore the distribution pattern of black locust sprouts, and provide a theoretical basis for artificial promotion of sprouting regeneration of black locust forests. Method: Three sample plots with obvious sprouting of black locust were selected in Huangtuliangzi forest farm of Pingquan City, Hebei Province. The genetic relationship of 125 black locust strains was identified by using 9 pairs of SSR primers. The traditional sample plot investigation method and the adjacent lattice method with variable scales were used to divide five sampling scales (5 m×5 m, 5 m×10 m, 10 m×10 m, 10 m×15 m, 20 m×30 m), calculate the deviation index (C) and its t-test, Cassie index (CA), average congestion (m*), negative binomial index (K), green index (GI) and agglomeration index (PAI), and then judge the pattern and scale. Result: The 9 pairs of primers had high polymorphism, and the average polymorphism information content was 0.76. In the three plots, a total of 73 genotypes, and 76 clonal ramets of black locust were identified. The distribution pattern of black locust clonal ramets from the cluster distribution tended to random distribution with the increase of sampling scale. The cluster distribution was the strongest when the sampling scale at 5 m×5 m. Conclusion: Based on the combination of SSR molecular markers and ecological investigation, this study explored a new method for studying the sprout distribution pattern, clarified the sprout distribution pattern of mountain black locust, and further understood the sprout regeneration theory of black locust. The distribution pattern of sprouts of black locust forest after felling is cluster distribution under no disturbance condition. The concentration and distribution of sprouting plants in a small area will result in a single genotype, which is not conducive to population diversity. It is suggested to make thinning of individuals that are too close to each other and affect normal growth and development, in order to ease competition and improve stand quality.

Key words: Robinia pseudoacacia, SSR, sprouting tillers, distribution pattern.

中图分类号:

蔡天润,郭佳,王紫怡,宋亚欣,张淑敏,杨敏生,张军. 基于SSR分子标记的山地刺槐克隆生长空间格局分析[J]. 林业科学, 2023, 59(6): 19-27.

Tianrun Cai,Jia Guo,Ziyi Wang,Yaxin Song,Shumin Zhang,Minsheng Yang,Jun Zhang. Spatial Pattern Analysis of Clonal Growth of Robinia pseudoacacia in Mountainous Areas Based on SSR Molecular Markers[J]. Scientia Silvae Sinicae, 2023, 59(6): 19-27.

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引物 Primer	正向引物序列 Forward primer sequence 5’→3’	反向引物序列 Reverse primer sequence 5’→3’	目的片段长度 Target fragment length/ bp	解链温度 Melting temperature(T_m)/ ℃
Rp-01	TGCAGAAAGAGAAAGCAGAGG	CCGAACCCTTTCTGGTTAGTC	140	53
Rp-04	CTCGTGATGATGGTGTTGATG	AATGGTCCAAACAACACGAAG	146	55
Rp-05	CCTTGCACATTTATCCCAGAA	CGACCTCGATCTTTTCTTGTG	158	55
Rp-06	TGGACAAAACATCATCGTGTG	CTCTCTTCTTTCTGCCCCTCA	147	55
Rp-12	AAGAGTCATCACGGAGACCAA	GGAGTCCAATTAAGTGCGAGA	150	55
Rp-15	TTAACTAATGCGGCGAGAAGA	GAGAGGAAGTGTGCGAAACAA	119	49
Rp-28	CTTGGTCTAGAAAGTCCTGCT	GGTCATCAAGGTTAGTTGGAT	151	55
Rp-32	CCACGTGGTTCTTCAAACATT	CAACAACAACCCACAAACACA	163	53
Rp-37	TGTCGTCATTTTATTTTACCC	CTCACCCTTTTTATTTCCATT	152	55

指标 Index	公式 Formula	判定标准 Judgment criteria
指标 Index	公式 Formula	集群分布 Cluster distribution	随机分布 Random distribution	均匀分布 Uniform distribution
偏离指数 Deviation index( C )	$C=S^2 / \bar{X} $ t检验 t-test： $t=(C-1) / \sqrt{[2 /(n-1)] }$ 自由度 Degree of freedom: n?1， t>t_0.05时达到显著水平 t>t_0.05reaching a significant level	C>1	C=1	C<1
负二项指数 Negative binomial distribution parameters( K )	$ K=\bar{X}^2 /\left(S^2-\bar{X}\right)$	K>0	K>8	K<0
Cassie 指标 Cassie index(CA)	CA=1/K	CA>0	CA=0	CA<0
平均拥挤度 Mean crowding( m*)	$m^*=C+\bar{X}-1 $	$m^{*} / \bar{X} > 1$	$m^* / \bar{X}=1 $	$m^* / \bar{X}<1 $
Green 指数 Green index(GI)	GI=(C?1)/(n?1)	GI>0	GI=0	GI<0
聚块性指标 Patchiness index(PAI)	PAI=1+1/K	PAI>1	PAI=1	PAI<1

引物 Primers	等位基因数目 No. of alleles	有效等位基因数目 No. of effective alleles	香农指数 Shannon's index	实际杂合度 Observed heterozygosity	预期杂合度 Expected heterozygosity	多态信息含量 Polymorphism information content	基因辨别能力 Probability of discrimination
RP-01	6	3.09	1.43	0.39	0.68	0.77	0.68
RP-04	7	6.26	1.89	0.49	0.84	0.90	0.84
RP-05	8	4.46	1.69	0.52	0.78	0.85	0.78
RP-06	9	4.71	1.72	0.38	0.79	0.88	0.79
RP-12	8	3.53	1.50	0.18	0.72	0.77	0.72
RP-15	4	2.15	1.02	0.30	0.53	0.60	0.53
RP-28	6	5.28	1.71	0.67	0.81	0.85	0.81
RP-32	6	2.26	1.00	0.07	0.56	0.56	0.56
RP-37	6	2.17	1.10	0.48	0.54	0.66	0.54
平均	5.89	4.19	1.52	0.33	0.74	0.76	0.74

样地 Plot	刺槐总数 Number of trees	有萌蘖刺槐数量 Number of cloned ramet genotypes	萌蘖刺槐总数 Total number of clone ramets	无萌蘖刺槐数量 Number of genotypes without clones	基因型总数 Number of genotypes	萌蘖刺槐占比 Proportion of cloned plants (%)
S1	33	6	18	15	21	54.6
S2	54	12	34	20	32	63.0
S3	38	6	24	14	20	63.2
总计 Total	125	24	76	49	73	60.8
均值 Average	41.67	8	25.33	16.33	26.33	60.2

格局参数 Pattern parameters	取样尺度 Sampling scale/
格局参数 Pattern parameters	5 m×5 m	5 m×10 m	10 m×10 m	10 m×15 m	20 m×30 m
单元数量 Unit number	83	41	19	13	3
偏离指数 Deviation index( C )	2.083	2.038	2.028	1.535	2.579
t	6.935*	4.643*	3.083*	1.311	1.579
t_0.05	1.989	2.026	2.110	2.201	4.303
负二项指数 Negative binomial distribution parameters( K )	0.845	1.786	3.892	10.926	16.044
Cassie指标 Cassie index(CA)	1.183	0.560	0.257	0.092	0.062
平均拥挤度 Mean crowding( m*)	1.999	2.892	5.028	6.381	26.912
Green指数 Green index	0.013	0.026	0.057	0.045	0.789
聚块性指标(GI) Patchiness index(PAI)	2.183	1.560	1.257	1.092	1.062
分布类型 Distribution type	集群分布 Cluster	集群分布 Cluster	集群分布 Cluster	随机分布Random	随机分布Random