美洲黑杨群体结构分析及核心种质库构建

doi:10.11707/j.1001-7488.20200908

摘要/Abstract

摘要：

目的: 利用SSR分子标记技术研究美洲黑杨种质资源的群体结构，构建美洲黑杨核心种质资源库，为美洲黑杨种质资源的科学管理、高效利用和有效保护提供理论依据。方法: 利用15对SSR引物，分析美洲黑杨6个种源23个采样点的338个个体的遗传结构。应用GeneAlEx 6.503等软件计算等位基因数(N_a)、有效等位基因数(N_e)、Shannon's信息多样性指数(I)、观测杂合度(H_o)、Nei's遗传多样性指数(H)和多态信息含量(PIC)等遗传参数，并进行主坐标(PCoA)分析。采用分组的逐步聚类方法结合位点等位基因数目最大化法和位点稀有等位基因优先相结合的取样策略构建核心种质库，并在核心种质库的基础上补充种质个体使等位基因保留比例达到100.00%，形成优化核心种质库。通过对相关遗传参数的t检验和PCoA分析验证核心种质库和优化核心种质库的有效性。结果: 美洲黑杨群体结构研究结果表明6个种源群体被划分为3大类型，即分布在圣劳伦斯河流域的Que种源的个体和哥伦比亚河流域的Was种源个体归为一类；分布在密西西比河中下游流域的种源个体(Mis、Lou、Ten)大致归为一类；分布在密西西比河上游的Iow种源的个体单独分为一类。基于群体结构分组筛选出19份核心种质，占原始种质的5.62%，等位基因数的保留比例为79.83%，N_e、I、H_o、H、PIC遗传参数的保留比例分别为102.75%、103.39%、125.31%、104.72%和105.27%，通过t检验和PCoA分析表明核心种质库具有代表性。通过在核心种质库中添加包含缺失等位变异基因的15个补充种质，构建包括34个个体的优化核心种质库，取样比例为10.06%，等位基因保留比例为100.00%，其他遗传参数N_e、I、H_o、H、PIC的保留比例分别为107.94%、110.93%、119.48%、107.52%和109.19%，t检验和PCoA分析结果均表明优化核心种质库的遗传多样性与原始种质库之间没有显著差异，包含的遗传信息优于核心种质库。结论: 美洲黑杨种质资源群体的6个种源分为三大类型：北方型美洲黑杨(Que、Was)、中间型美洲黑杨(Iow)和南方型美洲黑杨(Mis、Lou、Ten)。通过多种策略相结合构建的核心种质库和优化核心种质库的遗传多样性与原始种质库之间不存在显著差异，能够良好地代表美洲黑杨资源群体的遗传多样性。构建的优化核心种质库在保留原始种质库更多遗传多样性信息的基础上，去除遗传冗余，有利于美洲黑杨资源的有效保护和科学利用，为杨树育种工作奠定基础。

关键词: 美洲黑杨, 群体结构, 核心种质库

Abstract:

Objective: SSR markers were employed for an analysis of population structure of a collection of germplasm resources of Populus deltoides,and a core collection of the germplasm resources was constructed in order to provide a theoretical basis for scientific management,efficient utilization and effective protection of germplasm resources of the species. Method: The genetic structure of 338 individual trees of P. deltoides collected at 23 sampling sites of 6 provenances were analyzed using 15 pairs of SSR primers. Genetic diversity parameters such as number of alleles (N_a),effective number of alleles (N_e),Shannon's information index (I),observed heterozygosity (H_o),Nei's diversity index (H),polymorphic information content (PIC) were calculated by GeneAlEx 6.503 and other software. And the principal coordinates (PCoA) analysis was also carried out. The core collection was constructed by using the method of grouping and stepwise clustering,combining with the method of maximizing the number of alleles and the sampling strategy of rare allele priority. More individuals were added in the core collection to capture 100.00% of the alleles forming an optimized core collection. The validity of the core collection and the optimized core collection was verified by t-test and PCoA analysis. Result: The population structure showed that six provenances were divided into three types:the individuals originated from St. Lawrence River Basin (Que) and Columbia River Basin (Was) were classified as one group,while those from the middle and lower Mississippi River Basin (Mis,Lou,Ten) were classified as another group,and those of the Iow provenance from the upper Mississippi River were into one group. Based on the population structure,19 core germplasms were screened,accounting for 5.62% of the original collection,the retention rates of N_a,N_e,I,H_o,H,PIC were 79.83%,102.75%,103.39%,125.31%,104.72% and 105.27%,respectively. t-test and PCoA analysis showed that the core collection was representative. By adding 15 individuals with missing alleles to the core collection,the optimized core collection including 34 individuals was constructed,and the sampling ratio was 10.06%. The retention rates of N_a,N_e,I,H_o,H,PIC were 100.00%,107.94%,110.93%,119.48%,107.52% and 109.19%,respectively. The results of t-test and PCoA analysis showed that there was no significant difference between the genetic diversity of the optimized core collection and the original collection,and the genetic information of the response was better than that of the core collection. Conclusion: The six provenances of P. deltoides resources were divided into three types:North-type (Que,Was),Middle-type (Iow) and South-type (Lou,Ten,Mis). There was no significant difference between the genetic diversity of the core collection and the optimized core collection constructed by multiple strategies and the original collection,which could well represent the genetic diversity of the resource population of P. deltoides. On the basis of preserving genetic diversity information of the original collection,the optimized core collection could remove the genetic redundancy. The results were beneficial to the effective protection and scientific utilization of P. deltoides resources and laid a solid foundation for poplar breeding.

Key words: Populus deltoides, population structure, core collection

中图分类号:

陈存,丁昌俊,张静,李波,褚延广,苏晓华,黄秦军. 美洲黑杨群体结构分析及核心种质库构建[J]. 林业科学, 2020, 56(9): 67-76.

Cun Chen,Changjun Ding,Jing Zhang,Bo Li,Yanguang Chu,Xiaohua Su,Qinjun Huang. Population Structure Analysis and Core Collection Construction of Populus deltoides[J]. Scientia Silvae Sinicae, 2020, 56(9): 67-76.

图/表 7

表1

表2

图1

表3

表4

表5

图2

参考文献 0

	丁浩, 郑唐春, 梁德洋, 等. 一种简易高效提取多种植物纯净DNA的方法. 植物研究, 2015. 35 (3): 457- 461.
	Ding H , Zheng T C , Liang D Y , et al. A simple and efficient method of DNA extraction from different plant samples. Bulletin of Botanical Research, 2015. 35 (3): 457- 461.
	杜庆章, 王博文, 王保垒, 等. 毛白杨木材形成功能基因内SSR标记的开发及评价. 林业科学, 2010. 46 (11): 8- 15.
	Du Q Z , Wang B W , Wang B L , et al. Development and evaluation of simple sequence repeat (SSR) loci from functional genes involved in wood formation in Populus tomentosa. Scientia Silvae Sinicae, 2010. 46 (11): 8- 15.
	顾晓振. 2016.我国辣椒种质资源遗传多样性分析及核心种质构建的研究.北京:中国农业科学院硕士学位论文.
	Gu X Z. 2016. The research of genetic diversity of pepper (Capsicum spp.) germplasms of China and core collection construction. Beijing: MS thesis of Academy of Agricultural Sciences.[in Chinese]
	黄烈健, 苏晓华, 张香华, 等. 与杨树木材密度、纤维性状相关的SSR分子标记. 遗传学报, 2004. 31 (3): 299- 304.
	Huang L J , Su X H , Zhang X H , et al. SSR molecular markers related to wood density and fibre traits in poplar. Acta Genetica Sinica, 2004. 31 (3): 299- 304.
	李洪果, 许基煌, 杜红岩, 等. 基于等位基因最大化法初步构建杜仲核心种质. 林业科学, 2018a. 54 (2): 42- 51.
	Li H G , Xu J H , Du H Y , et al. Preliminary construction of core collection of Eucommia ulmoides based on allele number maximization strategy. Scientia Silvae Sinicae, 2018a. 54 (2): 42- 51.
	李洪果, 杜红岩, 贾宏炎, 等. 利用表型性状构建杜仲雄性资源核心种质. 分子植物育种, 2018b. 16 (2): 591- 601.
	Li H G , Du H Y , Jia H Y , et al. Establishment of male core collection of Eucommia ulmoides based on phenotypic traits. Molecular Plant Breeding, 2018b. 16 (2): 591- 601.
	李文文, 黄秦军, 丁昌俊, 等. 南方型和北方型美洲黑杨幼苗光合作用的日季节变化. 林业科学研究, 2010. 23 (2): 227- 233.
	Li W W , Huang Q J , Ding C J , et al. Studies on photosynthetic characteristics of South-and North-typed Populus deltoides younglings. Forest Research, 2010. 23 (2): 227- 233.
	李秀兰, 贾继文, 王军辉, 等. 灰楸形态多样性分析及核心种质初步构建. 植物遗传资源学报, 2013. 14 (2): 243- 248.
	Li X L , Jia J W , Wang J H , et al. Morphological diversity analysis and preliminary construction of core collection of Catalpa fargesii Bureau. Journal of Plant Genetic Resources, 2013. 14 (2): 243- 248.
	倪茂磊. 2011.美洲黑杨遗传多样性分析与核心种质库构建.南京:南京林业大学硕士学位论文.
	Ni M L. 2011. Analysis of genetic diversity and construction of primary core collection of Populous deltoides. Nanjing: MS thesis of Nanjing Forestry University.[in Chinese]
	彭婵, 樊孝萍, 苏晓华, 等. 基于SSR分子标记构建南方型美洲黑杨初级核心种质. 西北植物学报, 2019. 39 (2): 65- 72.
	Peng C , Fan X P , Su X H , et al. Construction of core collection in southern type of Populus deltoides using SSR markers. Acta Botanica Boreali-Occidentalia Sinica, 2019. 39 (2): 65- 72.
	苏晓华, 丁昌俊, 马常耕. 我国杨树育种的研究进展及对策. 林业科学研究, 2010. 23 (1): 31- 37.
	Su X H , Ding C J , Ma C G . Research progress and strategies of poplar breeding in China. Forest Research, 2010. 23 (1): 31- 37.
	王保垒, 王博文, 陈清清, 等. 杨树抗逆转录因子基因内SSR标记的开发. 林业科学, 2011. 47 (8): 67- 74.
	Wang B L , Wang B W , Chen Q Q , et al. Identification of SSR loci from transcription factor genes expressed under abiotic stresses in Populus. Scientia Silvae Sinicae, 2011. 47 (8): 67- 74.
	卫尊征, 杜庆章, 郭琦, 等. 小叶杨DREB同源基因内SSR的发现及群体结构分析. 植物学报, 2010. 45 (5): 556- 565.
	Wei Z Z , Du Q Z , Guo Q , et al. DREB gene and its application in analyzing population structure in Populus simonii. Bulletin of Botany, 2010. 45 (5): 556- 565.
	文亚峰, KentaroU, 韩文军, 等. 微卫星标记中的无效等位变异. 生物多样性, 2013. 21 (1): 117- 126.
	Wen Y F , Kentaro U , Han W J , et al. Null alleles in microsatellite markers. Biodiversity Science, 2013. 21 (1): 117- 126.
	张春雨. 2008.新疆野苹果(Malus sieversii)群体遗传结构与核心种质构建方法.泰安:山东农业大学博士学位论文.
	Zhang C Y. 2008. Population genetic structure and method of constructing core collection for Malus sieversii. Tai'an: PhD thesis of Shandong Agricultural University.[in Chinese]
	张香华, 苏晓华, 黄秦军, 等. 欧洲黑杨育种基因资源SSR多态性比较研究. 林业科学研究, 2006. 19 (4): 477- 483.
	Zhang X H , Su X H , Huang Q J , et al. Comparison of genetic variations of black poplar (Populus nigra L.) gene resource by microsatellite markers. Forest Research, 2006. 19 (4): 477- 483.
	张捷, 张萍, 李勤霞. 新疆野核桃核心种质的构建. 果树学报, 2018. 35 (2): 168- 176.
	Zhang J , Zhang P , Li Q X . Construction of core germplasm of Xinjiang wild walnut. Journal of Fruit Science, 2018. 35 (2): 168- 176.
	Belaj A , De La Rosa R , Lorite I J , et al. Usefulness of a new large set of high throughput EST-SNP markers as a tool for olive germplasm collection management. Frontiers in Plant Science, 2018. 9, 1320. doi: 10.3389/fpls.2018.01320
	Brown A H D . Core collections:a practical approach to genetic resources management. Genome, 1989. 31 (2): 818- 824. doi: 10.1139/g89-144
	Chen C , Chu Y G , Ding C J , et al. Genetic diversity and population structure of black cottonwood (Populus deltoides) revealed using simple sequence repeat markers. BMC Genetics, 2020. 21 (1): 2. doi: 10.1186/s12863-019-0805-1
	Du Q Z , Pan W , Xu B H , et al. Polymorphic simple sequence repeat (SSR) loci within cellulose synthase (PtoCesA) genes are associated with growth and wood properties in Populus tomentosa. New Phytologist, 2013. 197 (3): 763- 776. doi: 10.1111/nph.12072
	Du Q Z , Wang B W , Wei Z Z , et al. Genetic diversity and population structure of Chinese white poplar (Populus tomentosa) revealed by SSR markers. Journal of Heredity, 2012. 103 (6): 853- 862. doi: 10.1093/jhered/ess061
	Fahrenkrog A M , Neves L G , Resende M F , et al. Population genomics of the eastern cottonwood (Populus deltoides). Ecology & Evolution, 2017. 7 (22): 9426- 9440.
	Felsenstein J. 2005. PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author. Department of Genome Sciences. Seattle: University of Washington.
	Frankel O H, Brown A H D. 1984. Plant genetic resources today: a critical appraisal//Holden J H W, Williams J T. Crop Genetic Resources: Conservation and Evaluation. London, UK: George Allen and Unwin Ltd, 249-257.
	Hoffman J I , Amos W . Microsatellite genotyping errors:detection approaches, common sources and consequences for paternal exclusion. Molecular Ecology, 2005. 14 (2): 599- 612.
	Jarkko K , Barbara V , William D , et al. Utilization and transfer of forest genetic resources:A global review. Forest Ecology and Management, 2014. 333, 22- 34. doi: 10.1016/j.foreco.2014.07.017
	Kalinowski S T , Taper M L , Marshall T C . Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology, 2007. 16, 1099- 1106. doi: 10.1111/j.1365-294X.2007.03089.x
	Peakall R , Smouse P E . GenAlEx6.5:genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 2012. 28, 2537- 2539. doi: 10.1093/bioinformatics/bts460
	Politov D V , Belokon M M , Belokon Y S , et al. Application of microsatellite loci for molecular identification of elite genotypes, analysis of clonality, and genetic diversity in Aspen Populus tremula L. (Salicaceae). International Journal of Plant Genomics, 2015. 3, 1- 11.
	Rohlf F J. 2000. NTSYS pc2.1: Numerical taxonomy and multivariate analysis system version 2.1. New York: Applied Biostatistics Inc.
	Santiago P L , Ana María R C , Vanessa F , et al. Genetic diversity and core collection of Malus×domestica in northwestern Spain, Portugal and the Canary Islands by SSRs. Scientia Horticulturae, 2018. 240, 49- 56. doi: 10.1016/j.scienta.2018.05.053
	Van Oosterhout C , Hutchinson W F , Wills D , et al. Micro-checker:software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes, 2004. 4 (3): 535- 538. doi: 10.1111/j.1471-8286.2004.00684.x
	Wang L , Wang B L , Wei Z Z , et al. Development of 35 microsatellite markers from heat stress transcription factors in Populus simonii (Salicaceae). American Journal of Botany, 2012. 99 (9): 357- 361. doi: 10.3732/ajb.1200056
	Wei Z Z , Zhang G Y , Du Q Z , et al. Association mapping for morphological and physiological traits in Populus simonii. BMC Genetics, 2014. 15 (S1): S3.
	Wuyun T N , Hitomi A , Xu J S , et al. Population structure and conservation strategies for wild Pyrus ussuriensis Maxim. in China. PLoS ONE, 2015. 10 (8): e0133686. doi: 10.1371/journal.pone.0133686
	Xu Q J , Zeng X Q , Lin B , et al. A microsatellite diversity analysis and the development of core-set germplasm in a large hulless barley (Hordeum vulgare L.) collection. BMC Genetics, 2017. 18 (1): 102. doi: 10.1186/s12863-017-0563-x

种源Provenance			采样点代码 Sample code	样本数量 Sample size
密西西比河流域Mississippi River basin	美国艾奥瓦州Iowa, USA	Iow	I	18
	美国密苏里州Missouri, USA	Mis	M1	3
			M2	7
			小计Subtotal	10
	美国路易斯安那州Louisiana, USA	Lou	L1	16
			L4	17
			L5	17
			L6	17
			L7	16
			L8	17
			L9	17
			小计Subtotal	117
	美国田纳西州Tennessee, USA	Ten	T1	20
			T2	18
			T3	18
			T4	17
			T5	19
			小计Subtotal	92
哥伦比亚河流域Columbia River basin	美国华盛顿州Washington, USA	Was	W	16
圣劳伦斯河流域Saint Lawrence River basin	加拿大魁北克省Quebec, Canada	Que	Q1	29
			Q2	3
			Q4	4
			Q5	21
			Q6	8
			Q7	16
			Q10	4
			小计Subtotal	85
	总计Total			338

引物 Primers	正向引物 Forward primer sequence(5′—3′)	反向引物 Reverse primer sequence(5′—3′)	重复基序 Repeat motifs	退火温度 Annealing temperature(T_m)/℃	原始编号 Original number
SSR6	GGCTGCAGTCCCTGACAAA	AGATCTCGTGCATCGTGCA	ATTTTT	58	ZDQSSR83
SSR25	GCGCTTGGGTTATCTGGGTT	GATCATTGAGGGAATTAAGTGGT	CAT	60	SSR1
SSR42	GGTGATTAGGCTTCAGCCAA	CTTATGAGCCTTGGCAACCAA	TC	58	ZDQSSR10
SSR47	GAAAGGCTGTCAGACAGGT	GACTTGCTAGCTGGTGGTT	TC	58	ZDQSSR71
SSR58	GAGATGAAGAGTTTGTGTGGTA	CCTTCCTCCTTCATCGGCAA	AGG	56	SSR31
SSR80	CATTTTCTCTCGATCTTTGG	TACCTGCACTCCTTTCATTT	CTG	58	GCPM_2362
SSR85	AGTGCCTTTGATTCTACAGC	GAGTTATCTGGGTTTGGTGA	CT	60	GCPM_2803-1
SSR104	AACCACTATGCCACCTTCTT	AACTAACTCCATTCATTGCTAAA	GA	52	WPMS_1
SSR105	GATGAGAAACAGTGAATAGTAAAGA	GATTCCCAACAAGCCAAGATAAAA	GT	56	WPMS_10
SSR117	ACACCAAGAGCTGTAGCATT	ACAACATGGCCTAACTCATC	GGT	50	GCPM_2453-1
SSR120	AACCCACTTCCTCTCTCTGT	GTGAGACTTCCGACTCGTAG	CT	56	GCPM_2570-1
SSR126	TCAATGAGGGGTGCCATAAT	CTTTCCACTTTTGGCCCTTT	TG	56	ORPM_127
SSR129	CCGTGGCCATTGACTCTTTA	GAACCCATTTGGTGCAAGAT	GCT	48	ORPM_206
SSR132	TATATTGAGATCTCATCTAACAG	ACAAAATTCAATTGTGTTGTAATC	GA	44	PMGC_2840
SSR139	CTCGTACTATTTCCGATGATGACC	AGATTATTAGGTGGGCCAAGGACT	GTC	56	WPMS_16

	原始种质库 Original collection	种质库1 Bank 1	种质库2 Bank 2	种质库3 Bank 3	种质库4 Bank 4	种质库5 Bank 5	种质库6 Bank 6	种质库7 Bank 7	种质库8 Bank 8	种质库9 Bank 9	优化核心种质库 Optimized core collection
北方型 Northern-type	101	71	50	36	25	19	12	8	6	5	12
中间型 Intermediate-type	18	14	11	8	6	5	4	3	2	1	3
南方型 Southern-type	219	146	99	66	47	34	24	17	11	10	19
合计 Total	338	231	160	110	78	58	40	28	19	16	34
比例 Proportion(%)	100.00	68.34	47.34	32.54	23.08	17.16	11.83	8.28	5.62	4.73	10.06

	N	N_a	N_e	I	H_o	H	PIC
原始种质库 Original collection	119	7.933	3.821	1.310	0.543	0.619	0.574
核心种质库 Core collection	95	6.333	3.927	1.355	0.681	0.648	0.604
(保留比例Retention ratio, %)	(79.83)	(79.83)	(102.75)	(103.39)	(125.31)	(104.72)	(105.27)
优化核心种质库 Optimized core collection	119	7.933	4.125	1.453	0.649	0.666	0.626
(保留比例Retention ratio, %)	(100.00)	(100.00)	(107.94)	(110.93)	(119.48)	(107.52)	(109.19)

参数 Parameters	种质库 Banks	均值 Mean	标准差 Standard deviation	均值差值 Mean difference	t	P
N_a	原始种质库Original collection	7.93	4.92
	核心种质库Core collection	6.33	3.87	1.60	0.990	0.331
	优化核心种质库Optimized core collection	7.93	4.92	0.00	0.000	1.000
N_e	原始种质库Original collection	3.82	3.05
	核心种质库Core collection	3.93	2.79	-0.11	-0.099	0.922
	优化核心种质库Optimized core collection	4.12	2.86	-0.30	-0.281	0.781
I	原始种质库Original collection	1.310	0.643
	核心种质库Core collection	1.355	0.586	-0.044	-0.198	0.845
	优化核心种质库Optimized core collection	1.453	0.598	-0.143	-0.631	0.533
H_o	原始种质库Original collection	0.543	0.191
	核心种质库Core collection	0.681	0.218	-0.137	-1.836	0.077
	优化核心种质库Optimized core collection	0.649	0.199	-0.106	-1.486	0.148
H	原始种质库Original collection	0.619	0.210
	核心种质库Core collection	0.648	0.187	-0.029	-0.401	0.691
	优化核心种质库Optimized core collection	0.666	0.186	-0.047	-0.642	0.526
PIC	原始种质库Original collection	0.574	0.219
	核心种质库Core collection	0.604	0.197	-0.030	-0.398	0.694
	优化核心种质库Optimized core collection	0.626	0.195	-0.053	-0.697	0.492