生物多样性, 2021, 29(12): 1638-1649 doi: 10.17520/biods.2021249

研究报告:植物多样性

中国西北地区天然胡杨群体遗传多样性及核心保护单元的构建

陈向向,1,2,#, 盖中帅,1,2,#, 翟军团,1,2,3, 徐劲东4, 焦培培1,2,3, 吴智华,,4,*, 李志军,,1,2,3,*

1.塔里木盆地生物资源保护利用兵团重点实验室, 新疆阿拉尔市 843300

2.塔里木大学胡杨研究中心, 新疆阿拉尔市 843300

3.塔里木大学生命科学学院, 新疆阿拉尔市 843300

4.中南民族大学生命科学学院武陵山区特色资源植物种质保护与利用湖北重点实验室, 武汉 430074

Genetic diversity and construction of core conservation units of the natural populations of Populus euphratica in Northwest China

Xiangxiang Chen,1,2,#, Zhongshuai Gai,1,2,#, Juntuan Zhai,1,2,3, Jindong Xu4, Peipei Jiao1,2,3, Zhihua Wu,,4,*, Zhijun Li,,1,2,3,*

1 Key Laboratory of Corps of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang 843300

2 Desert Poplar Research Center of Tarim University, Alar, Xinjiang 843300

3 College of Life Sciences, Tarim University, Alar, Xinjiang 843300

4 Hubei Provincial Key Laboratory for Protection and Application of Special Plant Germplasm in Wuling Area of China, College of Life Sciences, South-Central University for Nationalities, Wuhan 430074

通讯作者: *E-mail:zhwu@scuec.edu.cn;lizhijun0202@126.com

第一联系人:

#共同第一作者

编委: 葛学军

责任编辑: 时意专

收稿日期: 2021-06-23   接受日期: 2021-09-30  

基金资助: 塔里木盆地兵团重点实验室项目(BRZD2003)
兵团重点领域创新团队建设计划(2018CB003)
兵团区域创新引导计划(2021BB010)

Corresponding authors: *E-mail:zhwu@scuec.edu.cn;lizhijun0202@126.com

First author contact:

#Co-first authors

Received: 2021-06-23   Accepted: 2021-09-30  

摘要

胡杨(Populus euphratica)是极端干旱荒漠区的珍稀乔木树种。为了确定天然胡杨群体遗传多样性保护单元并挖掘优异的种质资源, 本研究以中国西北地区新疆、青海、甘肃、宁夏、内蒙古的58个天然胡杨群体为研究对象, 利用120个位点的SNPs标记对这些胡杨群体进行群体遗传结构和遗传多样性分析, 并根据不同群体间Nei’s遗传相似度, 采用逐步聚类优先取样法对初始群体、遗传多样性保护单元和剩余群体进行t检验。群体结构和主成分分析表明, 胡杨群体可分为新疆南疆(SX)、新疆北疆(NX)、青海(QH)和混合群(甘肃、宁夏和内蒙古混合群, GNM) 4个分支, 遗传多样性分析表明新疆南疆(SX)遗传多样性高于其他群体。分子方差分析(AMOVA)表明天然胡杨群体的遗传变异主要分布在各个群体内。构建了天然胡杨群体一级核心保护单元3个群体(CU3), 二级核心保护单元33个群体(CU33)。南疆存在较多优异抗逆的天然胡杨古树资源, 南疆分布区的平均遗传多样性水平最高。综上所述, 南疆地区胡杨古树遗传多样性整体高于北疆及疆外地区, 结合新疆地区干旱严重指数等生境信息, 建议加大对南疆胡杨古树群体的保护力度, 重视北疆胡杨林的更新换代。

关键词： 自然居群; SNPs; 分子标记; 核心种质

Abstract

Aims: Populus euphratica is a rare tree species in the extremely arid desert area of northwest China. The research on the germplasm genetic resources within the natural populations and the construction of a germplasm bank are helpful to protect the gene resources of P. euphratica.
Methods: In this study, according to the Nei’s genetic similarity among populations by using SNPs from 120 DNA fragments, the gradual clustering priority sampling method was used and t-test was performed to compare the genetic diversity within populations, the conservation units and the rest populations. A total of 58 natural P. euphratica populations from northwest China, including Xinjiang, Qinghai, Gansu, Ningxia, and Inner Mongolia, were used to obtain the different natural conservation units.
Results: The P. euphratica populations were divided into four distinct clades that demonstrated strong geographical distribution patterns (NX, SX, QH and GNM, with the GNM clade containing individuals from Gansu, Ningxia and Inner Mongolia individuals). PCA analysis confirmed the differentiation of populations, similar to population structure. Southern Xinjiang holds the major distribution of P. euphratica in China, and the higher genetic diversity than other distribution areas, and the analysis of molecular variance (AMOVA) showed that most of the variation within P. euphratica was distributed within population compared to the variation among populations. The primary core conservation units (CU3) contained three populations, and the secondary core conservation units (CU33) contained 33 populations. There may be natural ancient P. euphratica resources with putative resistance to stress in southern Xinjiang, and the average genetic diversity in southern Xinjiang was higher than that in northern Xinjiang.
Conclusion: The overall genetic diversity of P. euphratica and the number of ancient trees in southern Xinjiang were higher than those in northern Xinjiang. The priority protection of the first and second core conservation units was constructed. Combining comprehensively with habitat information, such as the severity of drought index in Xinjiang, it was recommended to increase the conservation of ancient P. euphratica trees in southern Xinjiang, and to pay more attentions to the regeneration of P. euphratica forests in northern Xinjiang.

Keywords： natural population; SNPs; molecular marker; core germplasm

PDF (1461KB) 元数据 多维度评价 相关文章 导出 EndNote| Ris| Bibtex  收藏本文

本文引用格式

陈向向, 盖中帅, 翟军团, 徐劲东, 焦培培, 吴智华, 李志军 (2021) 中国西北地区天然胡杨群体遗传多样性及核心保护单元的构建. 生物多样性, 29, 1638-1649. doi:10.17520/biods.2021249.

Xiangxiang Chen, Zhongshuai Gai, Juntuan Zhai, Jindong Xu, Peipei Jiao, Zhihua Wu, Zhijun Li (2021) Genetic diversity and construction of core conservation units of the natural populations of Populus euphratica in Northwest China. Biodiversity Science, 29, 1638-1649. doi:10.17520/biods.2021249.

天然胡杨(Populus euphratica)是中国西北干旱荒漠区重要的珍稀乔木树种, 被列为世界珍稀濒危保护林木资源(王世绩等, 1995)。全世界61%的胡杨分布在中国, 而中国91%的胡杨林分布在新疆(王世绩等, 1995), 胡杨林对新疆沙漠地区的生态环境起到防风固沙的作用, 而且其耐盐碱、抗干旱等优异抗逆的特性(顾亚亚等, 2013)对未来培育其他适应于盐碱地环境的植物提供了理论上的可行性。近年来, 由于生境破坏和人类活动的增加, 胡杨林面积严重减少或退化, 加强对现有极端荒漠地区胡杨群体和优异种质资源的保护显得格外重要。一般而言, 原地保存和异地保存是植物群体保护的两种主要方式(Dzialuk et al, 2014; Nagamitsu et al, 2014)。原地保存通常针对群体间无明显的遗传分化, 且遗传多样性高的群体(Dzialuk et al, 2014; Tijerino & Korpelainen, 2014), 异地保存通常针对群体间存在分化且遗传多样性低的群体(李斌和顾万春, 2005)。胡杨种质资源分布范围广泛, 对整个分布区的资源进行保护难度较大。因此, 在有限条件下保护有价值或有代表性的种质资源, 不失为一种经济有效的保护策略。在此过程中, 还需要全面衡量不同胡杨群体分布区面积大小、遗传多样性水平高低、分布区生态环境、实施保护的难易程度和经济成本等因素(Sáenz-romero et al, 2003)。

前期胡杨群体遗传学研究局限于狭窄地理区域, 采用的分子标记、个体或群体数量相对有限(Wu et al, 2008; Eusemann et al, 2013; Xu et al, 2013; Wang et al, 2014), 或使用较为传统的非共显性标记(如AFLP、RAPD和SRAP) (Saito et al, 2002; Wang et al, 2011; Kansu & Kaya, 2020)。此外, 利用核标记和叶绿体DNA标记对中国西北地区胡杨群体结构和谱系地理学的初步研究表明, 新疆南疆和北疆胡杨群体存在明显的分化, 且南疆群体遗传多样性低于北疆(Zeng et al, 2018)。然而, 利用全基因组重测序对胡杨的27个天然群体252个个体的遗传多样性研究表明, 南疆和北疆群体间遗传分化程度较高,南疆群体的遗传多样性高于北疆(Jia et al, 2020)。近期谱系生物地理学研究表明, 胡杨群体的遗传多样性可能与地理距离和环境因子有关, 其中遗传多样性与经度和纬度呈显著负相关, 且纬度对遗传多样性的影响更大, 而与最暖季和最干月降水量、年平均气温等环境因子呈显著正相关(Gai et al, 2021)。先前的研究表明胡杨和灰杨(Populus pruinosa)存在着基因流和分化时间的差异, 进而促进了胡杨物种形成的复杂性(Ma et al, 2018)。因此, 研究胡杨的遗传多样性和群体结构, 对于探索其适应性进化以及群体间的遗传关系具有重要意义。

单核苷酸多态性(single nucleotide polymorphisms, SNPs)指单个核苷酸变异, 包括碱基转换、颠换等。SNPs具有二态性、高频率和稳定遗传等特性, 被认为是继限制性片段多态性标记、微卫星标记之后的第三代DNA遗传标记。随着高通量测序技术的发展, SNPs标记的开发也变得相对容易, 因此被广泛应用于人类、动植物的分子遗传学研究中, 如基因的关联定位、遗传图谱的构建及群体遗传多样性的分析等(Kaiser et al, 2017)。

先前已有研究对植物核心种质构建的方法进行了探讨, 如系统抽样法(李自超等, 2000)、分组法(赵冰和张启翔, 2007)和最小距离逐步抽样法(Liu et al, 2020)。张玲等(2012)利用分子标记对天然灰杨群体遗传变异进行了研究, 结果表明灰杨群体内的遗传变异大于群体间。然而依据天然胡杨群体遗传多样性水平的高低来构建其保护单元的研究却未见报道。本研究通过采样逐步聚类优先取样法和均值t检验来筛选出具有最小群体数目且遗传多样性保留率较高的保护单元群体, 为构建、评价和利用胡杨优质的核心保护群体提供依据, 同时也为其他林木种质资源的保护单元构建提供参考。

1 材料与方法

1.1 研究对象

2020年通过对中国西北地区天然胡杨林的实地考察, 获得了58个群体的采样点信息(表1)。其中每个群体选取30株左右的成年样株, 从每样株上取当年生条上基部开始第3节位的叶片, 在野外用硅胶干燥保存用于总DNA提取。为了减少无性系分株的影响, 每个群体所有取样个体至少间隔100 m, 同时对SNP基因型完全一致的个体进行去冗余。

表1   本研究中58个胡杨群体采样信息

Table 1  Sampling information of 58 Populus euphratica populations in this study

地区 Region样点 Site群体 Population经纬度 Location海拔 Altitude (m)
南疆阿克苏 Aksu, SX柯坪县 Kalpin CountyAKS-KPX79.52° E, 40.22° N1,042-1,095
阿瓦提县 Awat CountyAKS-AWT80.94° E, 40.36° N1,000-1,036
温宿县 Wensu CountyAKS-WSX80.79° E, 41.21° N1,104-1,140
沙雅县 Shaya CountyAKS-SYX83.42° E, 41.59° N929-989
库车县 Kuqa CountyAKS-KCS83.86° E, 41.28° N917-934
拜城县 Baicheng CountyAKS-BCX81.81° E, 41.66° N1,231-1,256
阿拉尔市 Alaer CityAKS-ALE81.03° E, 40.51° N1,012-1,038
南疆喀什 Kashgar, SX巴楚县 Marabishi CountyKS-BCX78.31° E, 39.77° N1,121-1,137
麦盖提县 Makit CountyKS-MGTX78.24° E, 39.36° N1,132-1,156
岳普湖县 Yopurga CountyKS-YPHX77.24° E, 39.18° N1,166-1,246
伽师县 Payzawat CountyKS-JSX77.38° E, 39.65° N1,161-1,174
疏勒县 Shule CountyKS-SLX76.18° E, 30.17° N1,259-1,279
莎车县 Yarkant CountyKS-SCX77.36° E, 38.40° N1,187-1,220
叶城县 Yecheng CountyKS-YCX77.58° E, 38.18° N1,230-1,299
南疆和田 Hotan, SX皮山县 Pishan CountyHT-PSX79.01° E, 37.62° N1,290-1,328
墨玉县 Karakax CountyHT-MYX90.19° E, 37.77° N1,239-1,290
洛浦县 Lop CountyHT-LPX80.12° E, 37.43° N1,101-1,284
策勒县 Qira CountyHT-CLX81.03° E, 36.94° N1,394-1,457
于田县 Yutian CountyHT-YTX81.41° E, 37.60° N1,263-1,452
民丰县 Minfeng CountyHT-MFX82.79° E, 37.73° N1,278-1,387
南疆巴音郭楞蒙古自治州
Bayingol Mongolian
Autonomous Prefecture, SX		且末县 Qiemo CountyBZ-QMX84.09° E, 37.73° N1,088-1,315
若羌县 Ruoqiang CountyBaZ-RQX87.12° E, 38.78° N801-984
尉犁县 Yuli CountyBaZ-YLX85.77° E, 41.14° N841-931
库尔勒市 Korla CityBaZ-KEL85.78° E, 41.53° N884-895
和硕县 Heshuo CityBaZ-HSX86.85° E, 42.17° N1,047-1,084
轮台县 Bugur CountyBaZ-LTX84.25° E, 41.26° N905-969
甘肃 Gansu民勤县 Minqin CountyGS-MQX103.1° E, 38.65° N1,283-1,323
金塔县 Jinta CountyGS-JTX98.87° E, 39.93° N1,191-1,284
瓜州县 Guazhou CountyGS-GZX96.05° E, 40.54° N1,027-1,218
敦煌县 Dunhuang CountyGS-DHX94.83° E, 40.17° N1,033-1,140
阿克塞哈萨克族自治县
Kazak Autonomous County of Aksay		GS-AKS93.43° E, 39.78° N1,447-1,493
宁夏 Ningxia中卫市 Zhongwei CityNIX-ZW105.12° E, 37.59° N1,207-1,220
内蒙古 Inner Mongolia额济纳旗 EjinaNMG-EJN101.08° E, 41.97° N813-926
四子王旗 Siziwang BannerNMG-SZWQ111.27° E, 42.83° N901-963
青海 Qinghai格尔木市 Geermu CityQH-GEM94.33° E, 36.44° N2,709-2,936
北疆吐鲁番 Turpan, NX托克逊县 Tuokexun CountyTLF-TKX88.17° E, 43.21° N1,128-1,152
北疆哈密 Hami, NX伊州区 Yizhou DistrictHM-YZQ93.08° E, 42.59° N390-405
伊吾县 Yiwu CountyHM-YWX95.25° E, 43.66° N456-489
巴里坤县 Barkol CountyHM-BLKX93.97° E, 43.97° N1,049-1,120
北疆昌吉 Changji, NX木垒哈萨克自治县
Mulei Kazak Autonomous County		CJ-MLX91.29° E, 44.82° N730-756
吉木萨尔县 Jimusaer CountyCJ-JMSE89.01° E, 44.07° N670-676
呼图壁县 Hutubi CountyCJ-HTBX86.90° E, 44.52° N359-401
玛纳斯县 Manasi CountyCJ-MNSX86.87° E, 44.66° N353-362
北疆阿勒泰 Altay, NX哈巴河县 Habahe CountyALT-HBH86.26° E, 47.92° N431-456
福海县 Fuhai CountyALT-FHX87.78° E, 47.21° N489-494
布尔津县 Burqin CountyALT-BEJ86.94° E, 47.66° N466-494
富蕴县 Fuyun CountyALT-FYX88.75° E, 46.91° N677-724
北疆博州 Bortala Mongol Autonomous Prefecture, NX阿拉山口市 Alashankou CityBoZ-ALSK82.97° E, 45.01° N194-206
精河县 Jinghe CountyBoZ-JHX83.43° E, 44.91° N203-217
北疆塔城 Tarbagatay, NX沙湾县 Shawan CountyTC-SWX85.77° E, 44.88° N312-328
乌苏市 Wusu CityTC-WUSU83.83° E, 44.80° N260-268
和丰县 Hefeng CountyTC-HFX85.27° E, 46.26° N469-477
托里县 Toli CountyTC-TLX85.32° E, 46.15° N426-431
北疆伊犁哈萨克自治州
Ili Kazak Autonomous Prefecture, NX		霍城县 Huocheng CountyYL-HCX80.55° E, 44.09° N631-638
察布查尔锡伯自治县 Qapqal Xibe Autonomous CountyYL-CX80.69° E, 43.84° N528-542
北疆克拉玛依 Karamay, NX克拉玛依区 Karamay DistrictKLMYS85.14° E, 45.33° N271-278
乌尔禾区 Urho DistrictKLMY-WEH85.67° E, 46.13° N296-302
北疆乌鲁木齐 Urumqi, NX乌鲁木齐市 Urumqi CityWLMQ88.35° E, 43.28° N936-969

SX: 南疆; NX: 北疆; QH: 青海; GS: 甘肃; NIX: 宁夏; NM: 内蒙古。

SX, Southern Xinjiang; NX, Northern Xinjiang; QH, Qinghai; GS, Gansu; NIX, Ningxia; NM, Inner Mongolia.

新窗口打开| 下载CSV


1.2 天然胡杨群体遗传多样性分析

采用靶向测序技术(target sequencing)对样品进行基因型分析。首先基于公开发表的胡杨重测序数据(Jia et al, 2020)和本实验室的参考基因组数据, 进行高质量SNP检测, 从中选择胡杨19条染色体上均匀分布的120个区间作为靶向测序的目标区间。筛选标准如下: (1) SNP间隔大于50 kb; (2) SNP对应的最小等位基因频率(minor allele frequency)不小于0.4; (3)杂合率不超过55%; (4)基因型缺失率不超过25%, 同时也检测了获得的SNPs标记符合随机抽取的变异位点。利用改良的CTAB法(Allen et al, 2006)提取叶片的DNA, 用Qubit 3.0 (Agiannitopoulos et al, 2020)检测DNA纯度(Thermo Qubit 3.0), 再通过多重PCR捕获目标区间, 最后利用Illumina 2500平台进行高通量测序。得到测序数据之后, 首先通过BWA软件将其比对到胡杨参考基因组(http://bio-bwa.sourceforge.net/), 随后利用GATK v3.7软件(DePristo et al., 2011)进行SNP分析。最后用GenAlEx 6.5软件(Peakall & Smouse, 2012)进行分子方差分析(AMOVA)和遗传多样性指标计算, 包括各群体的期望杂合度(He)、观测杂合度(Ho)、Shannon’s信息指数(I)和多态信息含量(PIC)等。用STRUCTURE v2.3.4软件分析群体结构(Earl & VonHoldt, 2012), 采用GCTA进行主成分分析(PCA) (Yang et al, 2011)。利用Powermarker V3.25计算Nei’s遗传距离(D) (Nei, 1983), 运用NTSYSpc 2.10e软件进行非加权组平均法(UPGMA)聚类分析(Rohlf, 1998)。

1.3 胡杨遗传多样性保护单元的构建及评价

通过计算不同胡杨天然群体的Nei’s相似性系数(Nei, 1972), 采用逐步聚类优先取样法(曾宪君等, 2014; Wang et al, 2021)。按照遗传相似性从大到小的顺序将群体进行排序, 其中在遗传相似性最大的2个群体中, 剔除遗传多样性低的群体, 保留的57个群体记为CU57, 剔除的群体标记为R1; 如果2个群体的遗传多样性水平比较接近, 则考虑这2个群体的分布地环境及其保护成本高低, 从而做出可行性的删减; 依此类推, 直到天然群体的数目到2为止。然后对逐步聚类获得的不同天然群体的保护单元与初始群体间进行显著性分析。从CU57到CU2进行分析, 直到差异显著时为止; 此时上一组合所构成的胡杨保护单元, 则满足以最小的群体量尽可能多地代表整个群体遗传多样性的要求(李慧峰等, 2013)。

评价不同群体核心种质的指标包括期望杂合度(He) (Nei, 1973)、多态信息含量(PIC) (Botstein et al, 1980)和Shannon’s信息指数(I) (Shannon & Weaver, 1959)等。通过计算天然胡杨保护群体、初始群体和剩余群体间遗传多样性指标并估算其变异程度的显著性水平, 并考虑胡杨保护群体数目大小和主要遗传多样性指标保留率的高低来实现对胡杨保护单元的代表性水平进行评价。所有群体的显著性分析均在SPSS 23软件中完成(IBM Corp., Armonk, NY, USA)。

1.4 胡杨古树遗传多样性保护单元的评价

胡杨古树是指估测树龄在100年以上的个体。利用卷尺测量每棵树的胸径, 然后通过Logistic方程表达式A = 13.679/(1+3.3476×exp (-0.2099 D))来估测树龄, 其中A是树龄, D是胸径(顾亚亚等, 2013)。本研究中对各群体胡杨古树单独统计, 计算其遗传多样性。

2 结果

2.1 胡杨群体结构及遗传多样性

群体结构和主成分分析表明中国胡杨主要分为南疆(SX)、北疆(NX)、青海(QH)、混合群(甘肃、宁夏和内蒙古混合群, GNM) 4个分支(图1, 图2), 表现出明显的地理分布格局。遗传多样性分析表明南疆(SX)遗传多样性整体高于其他亚群(附录1)。进一步对58个天然胡杨群体的遗传多样性进行分析(表2), 结果表明新疆南疆喀什地区麦盖提县(KS-MGTX)群体的遗传多样性最高(I = 0.443), 新疆北疆塔城地区托里县(TC-TLX)群体的遗传多样性最低(I = 0.153)。胡杨群体13.74%和68.38%的变异分别来源于个体内和个体间, 17.88%的变异来源于群体间(表3)。

图1

新窗口打开| 下载原图ZIP| 生成PPT

图1   中国西北地区胡杨群体的群体结构。SX: 南疆; NX: 北疆; QH: 青海; GNM: 甘肃、宁夏和内蒙古。群体代号见表1。

Fig. 1   The structural analysis of Populus euphratica populations in China. SX, Southern Xinjiang; NX, Northern Xinjiang; QH, Qinghai; GNM, Gansu, Ningxia, and Inner Mongolia. Population codes see Table 1.


图2

新窗口打开| 下载原图ZIP| 生成PPT

图2   中国西北地区胡杨群体的主成分分析。SX: 南疆; NX: 北疆; QH: 青海; GNM: 甘肃、宁夏和内蒙古。

Fig. 2   The PCA analysis of Populus euphratica populations in China. SX, Southern Xinjiang; NX, Northern Xinjiang; QH, Qinghai; GNM, Gansu, Ningxia, and Inner Mongolia.


表2   58个天然胡杨群体的遗传多样性。群体代号同表1。

Table 2  Genetic diversity analysis of 58 natural populations of Populus euphratica. He, Expected heterozygosity; Ho, Observed heterozygosity; I, Shannon’s information index; PIC, Polymorphism information content. Population codes see Table 1.

群体
Population		期望杂合度
He		观测杂合度
Ho		Shannon’s
信息指数 I		多态信息
含量 PIC		群体
Population		期望杂合度
He		观测杂合度
Ho		Shannon’s
信息指数 I		多态信息
含量 PIC
KS-MGTX0.2940.2620.4430.235BoZ-JHX0.2170.2170.3270.174
AKS-ALE0.2780.2700.4200.223TLF-TKX0.2130.2300.3210.171
KS-YPHX0.2660.2610.4060.215AKS-WSX0.2110.2380.3190.169
HT-LPX0.2610.2640.3900.208GS-DHX0.2100.2420.3100.165
HT-PSX0.2480.2550.3780.200KLMYS0.2100.2110.3150.167
HT-YTX0.2460.2440.3730.198TC-WUSU0.2080.2390.3140.167
KS-JSX0.2460.2430.3780.199ALT-BEJ0.2050.2190.3080.164
NMG-EJN0.2440.2380.3680.196TC-SWX0.2040.2290.3060.164
KS-BCX0.2440.2450.3740.197HT-CLX0.2030.2580.3040.161
HT-MFX0.2410.2590.3680.195GS-AKS0.2000.2490.3030.161
KS-SLX0.2400.2480.3650.193CJ-HTB0.1980.2550.2970.159
NX-ZW0.2360.2610.3510.188YL-HCX0.1840.2390.2740.147
AKS-SYX0.2340.2330.3580.189CJ-JMSE0.1770.1990.2660.142
BaZ-KEL0.2340.2530.3550.188YL-CX0.1770.2220.2710.145
GS-GZX0.2310.2450.3470.185HM-BLKX0.1760.2250.2550.137
HT-MYX0.2300.2410.3500.185TC-HFX0.1740.2210.2610.139
BaZ-HSX0.2300.2500.3440.183ALT-FHX0.1740.2140.2660.142
KS-SCX0.2280.2460.3470.184ALT-HBH0.1740.2100.2670.142
BaZ-RQX0.2280.2440.3470.183KLMY-WEH0.1720.2450.2590.137
AKS-AWT0.2280.2370.3510.185BoZ-ALSK0.1670.2080.2620.138
GS-JTX0.2280.2430.3420.182HM-YZQ0.1640.2390.2470.131
BaZ-LTX0.2260.2320.3400.180AKT-FYX0.1540.2390.2250.120
AKS-KCX0.2250.2280.3400.181GS-MQX0.1450.2740.2050.110
AKS-BCX0.2240.2370.3450.181CJ-MLX0.1420.2530.2040.109
CJ-MNS0.2240.2540.3330.178WLMQ0.1400.2180.2140.112
BaZ-YLX0.2220.2450.3390.179NMG-SZWQ0.1280.2370.1820.098
KS-YCX0.2220.2470.3350.178QH-GEM0.1260.2330.1810.097
AKS-KPX0.2210.2430.3330.177TC-TLX0.1090.2040.1530.082
BaZ-QMX0.2180.2410.3290.175平均 Mean0.2080.2390.3140.167
HM-YWX0.2170.2380.3280.174标准差 SD0.0390.0160.0610.032

新窗口打开| 下载CSV


表3   胡杨群体内和群体间遗传变异的分子方差分析

Table 3  Analysis of molecular variance of genetic variation within and among populations of Populus euphratica

来源
Source		自由度
Degree of freedom (df)		平方和
Sum of square (SS)		均方
Mean square (MS)		方差分量
Variance component		方差分量占比
Proportion (%)
群体间 Among populations5793,766.131,645.0236.4017.88
个体间 Among individuals1,103215,156.92195.0727.9613.74
个体内 Within individual1,161161,558139.15139.1568.38
总计 Total2,321470,481.05-203.51100

新窗口打开| 下载CSV


2.2 胡杨保护单元群体与初始群体间的差异性

根据不同群体的Nei’s相似性系数, 采用逐步聚类优先取样法将58个天然群体逐步分为56个保护单元(CU2-CU57), 分别与初始58个群体进行遗传多样性比较(附录2), 发现在不同抽样比例下各保护单元的标准差数值波动范围小, 且各个遗传多样性保护单元均与初始群体无显著差异。

通过胡杨保护单元群体(CU2-CU57)分别与58初始58个群体遗传多样性指标的显著性分析, 可以发现在期望杂合度(He)的t检验中, 保护单元(CU2-CU7、CU33-CU57)均与初始群体无显著差异(P > 0.05), 在观测杂合度(Ho)的t检验中, 保护单元(CU3-CU57)与初始群体均无显著差异, 在Shannon’s信息指数(I)和多态信息含量(PIC)的t检验中, 保护单元(CU2-CU4、CU7、CU33-CU57)与初始群体均无显著差异(附录3)。综合以上4个遗传多样性指标, 符合与初始群体相比无显著差异的胡杨保护单元群体分别为CU3、CU4、CU7、CU33-CU57, 其中保护单元最小群体为CU3, CU3的保留率分别为90.471% (He)、107.118% (Ho)、88.090% (I)、88.551% (PIC), 保护单元CU3的3个群体分别为甘肃省民勤群体(GS-MQX)、喀什地区麦盖提群体(KS-MGTX)和青海省格尔木群体(QH- GEM)。为了最大限度保护有代表性的胡杨群体, 构建的二级核心保护单元也应该能较好地代表初始群体的遗传多样性, 且与初始群体无显著差异。结果表明最适宜的二级保护单元群体为CU33, 保留率分别为92.376% (He)、99.668% (Ho)、91.872% (I)、92.046% (PIC)、He (92.376%)、Ho (99.668%)、I (91.872%)、PIC (92.046%)。

2.3 天然胡杨保护群体与剩余群体间的差异性

首先比较了保护单元与初始群体遗传多样性指标的差异显著性, 发现与初始群体相比均无显著差异的胡杨保护单元群体为CU3、CU4、CU7、CU33-CU57; 其次比较了胡杨保护单元群体与剩余群体遗传多样性指标的差异显著性, 发现在期望杂合度(He)、Shannon’s信息指数(I)和多态信息含量(PIC)的t检验中, 保护单元CU3、CU4、CU56均与初始群体无显著差异(P > 0.05); 在观测杂合度(Ho)的t检验中, 保护单元群体CU3、CU4、CU7、CU33-CU56与初始群体均无显著差异(附录4)。综合以上4个遗传多样性指标, 符合与剩余群体相比无显著差异的胡杨保护单元群体为CU3、CU4、CU56, 其中构建的保护单元最小群体为CU3, CU3的保留率分别为90.024% (He)、107.530% (Ho)、87.521% (I)、78.002% (PIC)。

2.4 遗传多样性保护单元的聚类分析

58个天然胡杨保护单元群体遗传距离的聚类结果(图3)表明, 当遗传距离等于0.3时, 58个群体分为两类, 且构建的33个保护单元群体也分为两类: 以南疆群体为代表聚为一类, 以北疆群体为代表聚为另一类, 进一步表明南疆和北疆的胡杨核心保护单元群体的遗传分化程度有显著差异。

图3

新窗口打开| 下载原图ZIP| 生成PPT

图3   58个胡杨群体遗传距离的聚类分析。群体采样信息见表1, 加粗字体为33个保护单元(CU33)。

Fig. 3   The cluster analysis based on genetic distance of 58 Populus euphratica populations. See Table 1 for sampling information of the populations, and bold font indicate the 33 conservation units (CU33).


2.5 胡杨古树遗传多样性评价

23个胡杨古树群体的遗传多样性分析表明(表4), 古树群体的期望杂合度在0.144-0.274之间, 其中喀什地区麦盖提县古树群体(KS-MGTX)的期望杂合度最高, 昌吉地区木垒县古树群体(CJ-MLX)最低。Shannon’s信息指数(I)也表现出相同的趋势。结合胡杨地理分布区域综合分析表明, 胡杨古树主要分布在南疆, 且南疆地区群体的遗传多样性整体上高于北疆。

表4   23个胡杨古树群体的遗传多样性。群体代号同表1。

Table 4  Genetic diversity analysis of 23 ancient Populus euphratica populations. He, Expected heterozygosity; Ho, Observed heterozygosity; I, Shannon’s information index; PIC, Polymorphism information content. Population codes see Table 1.

群体
Population		期望杂合度
He		观测杂合度
Ho		Shannon’s
信息指数 I		多态信息
含量 PIC		群体
Population		期望杂合度
He		观测杂合度
Ho		Shannon’s
信息指数 I		多态信息
含量 PIC
KS-MGTX0.2740.2680.4390.236AKS-WSX0.2210.2560.3310.176
KS-BCX0.2570.2650.3900.207BaZ-YLX0.2180.2470.3260.174
KS-YPHX0.2520.2770.3770.201BaZ-QMX0.2170.2540.3250.173
AKS-SYX0.2460.2490.3760.199BoZ-JHX0.2120.2310.3080.164
AKS-BCX0.2440.2500.3730.197HT-MFX0.2000.2660.3030.161
HM-YWX0.2360.2580.3540.189TC-WUSU0.1980.2400.2860.152
BaZ-RQX0.2330.2480.3540.187BaZ-HSX0.1810.2590.2610.140
HT-PSX0.2310.2630.3510.186TC-HFX0.1750.2290.2620.139
BaZ-KEL0.2300.2550.3440.183KLMY-WEH0.1670.2580.2530.134
AKS-KCX0.2250.2430.3390.180BoZ-ALSK0.1640.2210.2510.133
AKS-KPX0.2240.2670.3290.176CJ-MLX0.1440.2600.2110.113
BaZ-LTX0.2230.2430.3300.176

新窗口打开| 下载CSV


3 讨论

3.1 天然胡杨群体遗传多样性的分布格局

了解不同分布区天然胡杨群体遗传多样性水平有助于从分子水平上保护其遗传种质资源和构建核心种质库。本研究对采集的58个胡杨天然群体统计表明, 南疆群体最多(26个), 北疆次之(23个), 甘肃、青海、宁夏和内蒙古分布的群体最少。其中南疆群体的遗传多样性水平高于北疆及疆外群体(甘肃、青海、宁夏和内蒙古)。不同物种遗传多样性水平的高低与其分布区生态环境、物种繁殖能力及传播媒介等相关, 例如具有分布广泛、种子离体寿命长、风媒传播等生物学特性的物种相对较易克服群体间的地理隔离, 有利于不同群体间个体的杂交, 从而使群体维持较高水平的遗传多样性(Hamrick et al, 1979)。胡杨具有寿命长、根蘖繁殖、风媒传粉、种子借风传播等生物学特性, 有利于产生丰富的遗传变异, 从而适应不同的环境条件, 这可能是导致其群体遗传多样性丰富的主要原因(Wang et al, 2011)。同时, 南疆地区胡杨种子成熟常常发生于洪水期(Eusemann et al, 2013), 独特的环境条件有利于胡杨群体繁殖并建成大规模的有效群体, 使得南疆成为全球胡杨分布最密集的地区(王世绩等, 1995)。此外, 南疆地区有大量的灰杨分布, 胡杨和灰杨为雌雄异株的异交树种, 两物种开花阶段一致、花期重叠(王世绩等, 1995), 风媒传粉为种间基因交流提供了可能(Wang et al, 2011; 张玲等, 2012; Ma et al, 2018)。先前的研究也表明胡杨和灰杨之间有明显的基因渐渗现象(Wang et al, 2014; Jia et al, 2020)。这些可能是南疆地区胡杨群体具有较高遗传多样性和较低群体分化的主要原因。

3.2 胡杨遗传多样性保护单元的构建

保护一个物种全部种质资源的遗传多样性既困难又昂贵, 因此应该构建具有最小重复性和最大遗传多样性的核心子集, 以代表一个物种的整个基因库(Anoumaa et al, 2017)。在本研究中, 利用4个遗传多样性指标, 将胡杨保护单元群体分别与初始群体和剩余群体进行显著性分析, 得到与初始群体和剩余群体均无显著性差异的胡杨核心保护单元CU3、CU34和CU56。其中CU3样本量最小, 保留率最优, 因此定义CU3为一级胡杨核心保护单元群体(CU3群体为GS-MQX、KS-MGTX、QH-GEM)。其抽样比例为5.17%, 符合一般以5%-30%的抽样群体比例来覆盖整个初始群体的遗传变异(Wang et al, 2021)。考虑到胡杨的生态价值, 例如作为极端干旱区仅存乔木树种, 能够起到防风固沙、减缓土壤沙漠化的作用, 为了让核心保护群体不仅从遗传多样性水平同时能够从表型性状多样性方面代表整个群体的多样性水平, 选择原始58个群体大约一半的样本量作为胡杨的二级保护群体, 且保护群体需满足与原始群体无显著差异, 即此时二级保护单元群体也能较好地代表初始群体的遗传多样性。本文结果表明, 样本量最适宜的胡杨保护单元群体为CU33。定义CU33作为胡杨二级核心保护单元群体, 同时对CU33进行了聚类分析(图3), 结果表明当遗传距离等于0.3时, 新疆南疆和北疆的天然群体间出现了明显的遗传分化。

3.3 胡杨优先保护群体遗传多样性评价

同一物种不同群体的遗传多样性水平越高, 所构建的核心种质数目越大(曾宪君等, 2014)。然而在天然胡杨群体二级核心保护单元群体CU33中, 南疆大部分群体遗传多样性大于北疆群体(表2), 但南疆的保护单元群体数目(7个)小于北疆(19个) (图3)。可能的原因是南疆不同群体的Nei’s遗传相似性系数高, 意味着南疆群体内遗传多样性水平高、群体间遗传分化程度低; 其次由于生态环境的差异造成胡杨片断化的分布, 且北疆地区胡杨群体长期地理隔离, 导致群体间基因流动较少, 从而形成了群体内低的遗传多样性和群体间高的遗传分化(Zeng et al, 2018; Jia et al, 2020)。因此, 58个初始群体应选择更多的北疆群体作为保护单元群体, 在构建的二级核心保护单元群体CU33中, 北疆胡杨群体(19个)占比超过50%。保护单元CU33与初始58个群体在4个遗传多样性指标上的t检验均无显著差异, 更说明CU33能很好地代表初始58个群体。

天然胡杨群体拥有大量优异抗逆基因资源, 尤其对于古树资源的保护, 无论是对遗传多样性保护还是优异抗逆基因资源挖掘均具有重要的意义。在本研究中23个胡杨古树群体主要分布在南疆, 且南疆地区胡杨古树群体的遗传多样性整体上高于北疆。新疆位于干旱和半干旱区, 不同分布区水资源供需矛盾大, 干旱性气候频繁, 尤其在极端和严重干旱等级中, 南疆的年均干旱分布区大于北疆(张喜成等, 2020)。同时天山山脉阻隔了南北疆之间直接的基因流动, 造成了南北疆不同群体的遗传差异(Zeng et al, 2018; Jia et al, 2020)。南、北疆巨大的地理和环境差异是造成遗传天然胡杨群体遗传多样性分布不均一的重要原因。基于保护群体遗传相似性, 北疆的胡杨群体被优先作为保护单元; 同时北疆的胡杨遗传多样性低暗示着北疆的群体可能是经历天然选择的结果, 对现存的生态环境具有更好的适应性。然而, 南疆地区胡杨群体具有比北疆更丰富的遗传多样性和胡杨古树资源, 且南疆干旱程度较北疆严重。因此, 胡杨多样性的保护既要考虑遗传多样性丰富的群体, 确保为群体的扩大提供丰富的基因库; 也需要考虑经历自然选择而保留下的低遗传多样性群体, 有助于挖掘适应特定自然生态环境的优良基因型。综合考虑, 为了更好地保护胡杨种质资源, 核心保护单元群体的构建对于南北疆的胡杨资源的保护十分必要。

此外, 胡杨存在多个谱系且与灰杨构成并系群, 胡杨与灰杨群体之间也存在较强的基因流(Ma et al, 2018)。前期的研究表明了新疆南疆灰杨群体的遗传多样性整体高于北疆(Gai et al, 2021)。这些结果暗示了灰杨的基因渗入可能促进了南疆胡杨较高的遗传多样性。未来在保护单元的基础上, 可根据胡杨谱系分布扩大对现存群体的保护范围。同时继续加大对新疆南疆胡杨古树群体的保护力度, 重视北疆胡杨林的更新换代。

附录 Supplementary Material

附录1 胡杨4个亚群间遗传多样性比较

Appendix 1 Comparison of genetic diversity among four subpopulations

https://www.biodiversity-science.net/fileup/PDF/2021249-1.pdf

附录2 不同胡杨保护单元遗传多样性指标的多重比较

Appendix 2 Multiple comparison of genetic diversity indexes of different Populus euphratica conservation units

https://www.biodiversity-science.net/fileup/PDF/2021249-2.pdf

附录3 胡杨保护单元与初始群体期望杂合度(He)、观测杂合度(Ho)、Shannon’s信息指数(I)、多态信息含量(PIC)的t检验

Appendix 3 The t-test of the expected heterozygosity (He), observed heterozygosity (Ho), Shannon’s information index (I), polymorphism information content (PIC) between conservation units and all populations of Populus euphratica

https://www.biodiversity-science.net/fileup/PDF/2021249-3.pdf

附录4 胡杨核心保护单元与剩余群体期望杂合度(He)、观测杂合度(Ho)、Shannon’s信息指数(I)、多态信息含量(PIC)的t检验

Appendix 4 The t-test of the expected heterozygosity (He), observed heterozygosity (Ho), Shannon’s information index (I), polymorphism information content (PIC) between the conservation units and the rest populations of Populus euphratica

https://www.biodiversity-science.net/fileup/PDF/2021249-4.pdf

致谢

感谢张山河、孙健皓、韩晓莉、李秀、王佳宁、董晓山和王子健等同学在采样过程中的协助。

参考文献

Agiannitopoulos K, Samara P, Papadopoulou E, Tsamis K, Mertzanos G, Babalis D, Lamnissou K (2020)

Study on the admission levels of circulating cell-free DNA in patients with acute myocardial infarction using different quantification methods

Scandinavian Journal of Clinical and Laboratory Investigation, 80, 1-3.

DOI:10.1080/00365513.2019.1672086      URL     [本文引用: 1]

Allen GC, Flores-Vergara MA, Krasynanski S, Kumar S, Thompson WF (2006)

A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide

Nature Protocols, 1, 2320-2325.

PMID:17406474      [本文引用: 1]

We describe a modification of the DNA extraction method, in which cetyltrimethylammonium bromide (CTAB) is used to extract nucleic acids from plant tissues. In contrast to the original method, the modified CTAB procedure is faster, omits the selective precipitation and CsCl gradient steps, uses less expensive and toxic reagents, requires only inexpensive laboratory equipment and is more readily adapted to high-throughput DNA extraction. This protocol yields approximately 5-30 microg of total DNA from 200 mg of tissue fresh weight, depending on plant species and tissue source. It can be completed in as little as 5-6 h.

Anoumaa M, Yao NK, Kouam EB, Kanmegne G, Machuka E, Osama SK, Nzuki I, Kamga YB, Fonkou T, Omokolo DN (2017)

Genetic diversity and core collection for potato (Solanum tuberosum L.) cultivars from Cameroon as revealed by SSR markers

American Journal of Potato Research, 94, 449-463.

DOI:10.1007/s12230-017-9584-2      URL     [本文引用: 1]

Botstein D, White RL, Skolnick M, Davis RW (1980)

Construction of a genetic linkage map in man using restriction fragment length polymorphisms

American Journal of Human Genetics, 32, 314-331.

PMID:6247908      [本文引用: 1]

We describe a new basis for the construction of a genetic linkage map of the human genome. The basic principle of the mapping scheme is to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms, when hybridized to restriction digests of an individual's DNA. Each of these probes will define a locus. Loci can be expanded or contracted to include more or less polymorphism by further application of recombinant DNA technology. Suitably polymorphic loci can be tested for linkage relationships in human pedigrees by established methods; and loci can be arranged into linkage groups to form a true genetic map of "DNA marker loci." Pedigrees in which inherited traits are known to be segregating can then be analyzed, making possible the mapping of the gene(s) responsible for the trait with respect to the DNA marker loci, without requiring direct access to a specified gene's DNA. For inherited diseases mapped in this way, linked DNA marker loci can be used predictively for genetic counseling.

DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJA (2011)

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Nature Genetics, 43, 491-498.

DOI:10.1038/ng.806      PMID:21478889      [本文引用: 1]

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (∼4×) 1000 Genomes Project datasets.

Dzialuk A, Chybicki I, Gout R, Mączka T, Fleischer P, Konrad H, Curtu AL, Sofletea N, Valadon A (2014)

No reduction in genetic diversity of Swiss stone pine (Pinus cembra L.) in Tatra Mountains despite high fragmentation and small population size

Conservation Genetics, 15, 1433-1445.

DOI:10.1007/s10592-014-0628-6      URL     [本文引用: 2]

Earl DA, VonHoldt BM (2012)

STRUCTURE HARVESTER: A website and program for visualizing structure output and implementing the Evanno method

Conservation Genetics Resources, 4, 359-361.

DOI:10.1007/s12686-011-9548-7      URL     [本文引用: 1]

Eusemann P, Petzold A, Thevs N, Schnittler M (2013)

Growth patterns and genetic structure of Populus euphratica Oliv. (Salicaceae) forests in NW China-Implications for conservation and management

Forest Ecology and Management, 297, 27-36.

DOI:10.1016/j.foreco.2013.02.009      URL     [本文引用: 2]

Gai ZS, Zhai JT, Chen XX, Jiao PP, Zhang SH, Sun JH, Qin R, Liu H, Wu ZH, Li ZJ (2021)

Phylogeography reveals geographic and environmental factors driving genetic differentiation of Populus sect. Turanga in northwest China

Frontiers in Plant Science, 12, 705083.

DOI:10.3389/fpls.2021.705083      URL     [本文引用: 2]

Gu YY, Zhang SQ, Li XY, Li ZJ (2013)

Relationship between diameter at breast height and age of endangered species Populus euphratica Oliv

Journal of Tarim University, 25(2), 66-69. (in Chinese with English abstract)

[本文引用: 2]

[ 顾亚亚, 张世卿, 李先勇, 李志军 (2013)

濒危物种胡杨胸径与树龄关系研究

塔里木大学学报, 25(2), 66-69.]

[本文引用: 2]

Hamrick JL, Linhart YB, Mitton JB (1979)

Relationships between life history characteristics and electrophoretically detectable genetic variation in plants

Annual Review of Ecology and Systematics, 10, 173-200.

DOI:10.1146/ecolsys.1979.10.issue-1      URL     [本文引用: 1]

Jia HX, Liu GJ, Li JB, Zhang J, Sun P, Zhao ST, Zhou X, Lu MZ, Hu JJ (2020)

Genome resequencing reveals demographic history and genetic architecture of seed salinity tolerance in Populus euphratica

Journal of Experimental Botany, 71, 4308-4320.

DOI:10.1093/jxb/eraa172      URL     [本文引用: 5]

Kaiser SA, Taylor SA, Chen N, Sillett TS, Bondra ER, Webster MS (2017)

A comparative assessment of SNP and microsatellite markers for assigning parentage in a socially monogamous bird

Molecular Ecology Resources, 17, 183-193.

DOI:10.1111/1755-0998.12589      PMID:27488248      [本文引用: 1]

Single-nucleotide polymorphisms (SNPs) are preferred over microsatellite markers in many evolutionary studies, but have only recently been applied to studies of parentage. Evaluations of SNPs and microsatellites for assigning parentage have mostly focused on special cases that require a relatively large number of heterozygous loci, such as species with low genetic diversity or with complex social structures. We developed 120 SNP markers from a transcriptome assembled using RNA-sequencing of a songbird with the most common avian mating system-social monogamy. We compared the effectiveness of 97 novel SNPs and six previously described microsatellites for assigning paternity in the black-throated blue warbler, Setophaga caerulescens. We show that the full panel of 97 SNPs (mean H = 0.19) was as powerful for assigning paternity as the panel of multiallelic microsatellites (mean H = 0.86). Paternity assignments using the two marker types were in agreement for 92% of the offspring. Filtering individual samples by a 50% call rate and SNPs by a 75% call rate maximized the number of offspring assigned with 95% confidence using SNPs. We also found that the 40 most heterozygous SNPs (mean H = 0.37) had similar power to assign paternity as the full panel of 97 SNPs. These findings demonstrate that a relatively small number of variable SNPs can be effective for parentage analyses in a socially monogamous species. We suggest that the development of SNP markers is advantageous for studies that require high-throughput genotyping or that plan to address a range of ecological and evolutionary questions.© 2016 John Wiley & Sons Ltd.

Kansu C, Kaya Z (2020)

Genetic diversity of marginal populations of Populus euphratica Oliv. from highly fragmented river ecosystems

Silvae Genetica, 69, 139-151.

DOI:10.2478/sg-2020-0019      URL     [本文引用: 1]

Li B, Gu WC (2005)

Conservation genetics of Pinus bungeana-Evaluation and conservation of natural populations’ genetic diversity

Scientia Silvae Sinicae, 41(1), 57-64. (in Chinese with English abstract)

[本文引用: 1]

[ 李斌, 顾万春 (2005)

白皮松保育遗传学--天然群体遗传多样性评价与保护策略

林业科学, 41(1), 57-64.]

[本文引用: 1]

Li HF, Chen TY, Huang YM, Wu CR, Li YQ, Lu SQ, Chen XT (2013)

Sampling strategies of sweet potato core collection based on morphological traits

Journal of Plant Genetic Resources, 14, 91-96. (in Chinese with English abstract)

[本文引用: 1]

[ 李慧峰, 陈天渊, 黄咏梅, 吴翠荣, 李彦青, 卢森权, 陈雄庭 (2013)

基于形态性状的甘薯核心种质取样策略研究

植物遗传资源学报, 14, 91-96.]

[本文引用: 1]

Li ZC, Zhang HL, Zeng YW, Yang ZY, Shen SQ, Sun CQ, Wang XK (2000)

Study on sampling schemes of core collection of local varieties of rice in Yunnan, China

Scientia Agricultura Sinica, 33(5), 1-7. (in Chinese with English abstract)

[本文引用: 1]

[ 李自超, 张洪亮, 曾亚文, 杨忠义, 申时全, 孙传清, 王象坤 (2000)

云南地方稻种资源核心种质取样方案研究

中国农业科学, 33(5), 1-7.]

[本文引用: 1]

Liu M, Hu X, Wang X, Zhang JJ, Peng XB, Hu ZG, Liu YF (2020)

Constructing a core collection of the medicinal plant Angelica biserrata using genetic and metabolic data

Frontiers in Plant Science, 11, 600249.

DOI:10.3389/fpls.2020.600249      URL     [本文引用: 1]

Ma T, Wang K, Hu QJ, Xi ZX, Wan DS, Wang Q, Feng JJ, Jiang DC, Ahani H, Abbott RJ, Lascoux M, Nevo E, Liu JQ (2018)

Ancient polymorphisms and divergence hitchhiking contribute to genomic islands of divergence within a poplar species complex

Proceedings of the National Academy of Sciences, USA, 115, 236-243.

[本文引用: 3]

Nagamitsu T, Shimada KI, Kanazashi A (2014)

A reciprocal transplant trial suggests a disadvantage of northward seed transfer in survival and growth of Japanese red pine (Pinus densiflora) trees

Tree Genetics & Genomes, 11, 1-10.

[本文引用: 1]

Nei M (1972)

Genetic distance between populations

The American Naturalist, 106, 283-292.

DOI:10.1086/282771      URL     [本文引用: 1]

Nei M (1973)

Analysis of gene diversity in subdivided populations

Proceedings of the National Academy of Sciences, USA, 70, 3321-3323.

[本文引用: 1]

Peakall R, Smouse PE (2012)

GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-An update

Bioinformatics, 28, 2537-2539.

PMID:22820204      [本文引用: 1]

GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised.GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx.rod.peakall@anu.edu.au.

Rohlf FJ (1998) NTSYSpc Version 2.0:User Guide. Applied Biostatistics Inc. Setauket, New York.

[本文引用: 1]

Sáenz-romero C, Snively AE, Lindig-Cisneros R (2003)

Conservation and restoration of pine forest genetic resources in Mexico

Silvae Genetica, 52, 233-237.

[本文引用: 1]

Saito Y, Shiraishi S, Tanimoto T, Yin L, Watanabe S, Ide Y (2002)

Genetic diversity of Populus euphratica populations in northwestern China determined by RAPD DNA analysis

New Forests, 23, 97-103.

DOI:10.1023/A:1015605928414      URL     [本文引用: 1]

Shannon CE, Weaver W (1959) The Mathematical Theory of Communication. University of Illinois Press, Urbana.

[本文引用: 1]

Tijerino A, Korpelainen H (2014)

Molecular characterization of Nicaraguan Pinus tecunumanii Schw. ex Eguiluz et Perry populations for in situ conservation

Trees, 28, 1249-1253.

DOI:10.1007/s00468-014-1005-2      URL     [本文引用: 1]

Wang J, Källman T, Liu J, Guo Q, Wu Y, Lin K, Lascoux M (2014)

Speciation of two desert poplar species triggered by Pleistocene climatic oscillations

Heredity, 112, 156-164.

DOI:10.1038/hdy.2013.87      PMID:24065180      [本文引用: 2]

Despite the evidence that the Pleistocene climatic fluctuations have seriously affected the distribution of intraspecific diversity, less is known on its impact on interspecific divergence. In this study, we aimed to test the hypothesis that the divergence of two desert poplar species Populus euphratica Oliv. and P. pruinosa Schrenk. occurred during the Pleistocene. We sequenced 11 nuclear loci in 60 individuals from the two species to estimate the divergence time between them and to test whether gene flow occurred after species separation. Divergence time between the two species was estimated to be 0.66-1.37 million years ago (Ma), a time at which glaciation was at its maximum in China and deserts developed widely in central Asia. Isolation-with-Migration model also indicated that the two species had diverged in the presence of gene flow. We also detected evidence of selection at GO in P. euphratica and to a lesser extent at PhyB2. Together, these results underscore the importance of Pleistocene climate oscillations in triggering plant speciation as a result of habitats divergence.

Wang J, Wu YX, Ren GP, Guo QH, Liu JQ, Lascoux M (2011)

Genetic differentiation and delimitation between ecologically diverged Populus euphratica and P. pruinosa

PLoS ONE, 6, e26530.

DOI:10.1371/journal.pone.0026530      URL     [本文引用: 3]

Wang SJ, Chen BH, Li HQ (1995) Populus euphratica Forest. China Environmental Science Press, Beijing. (in Chinese)

[本文引用: 4]

[ 王世绩, 陈炳浩, 李护群 (1995) 胡杨林. 中国环境科学出版社, 北京.]

[本文引用: 4]

Wang XL, Cao ZL, Gao CJ, Li K (2021)

Strategy for the construction of a core collection for Pinus yunnanensis Franch. to optimize timber based on combined phenotype and molecular marker data

Genetic Resources and Crop Evolution, 68, 3219-3240.

DOI:10.1007/s10722-021-01182-9      URL     [本文引用: 2]

Wu YX, Wang J, Liu JQ (2008)

Development and characterization of microsatellite markers in Populus euphratica (Populaceae)

Molecular Ecology Resources, 8, 1142-1144.

DOI:10.1111/men.2008.8.issue-5      URL     [本文引用: 1]

Xu F, Feng SS, Wu RL, Du FK (2013)

Two highly validated SSR multiplexes (8-plex) for Euphrates’ poplar, Populus euphratica (Salicaceae)

Molecular Ecology Resources, 13, 144-153.

DOI:10.1111/men.2012.13.issue-1      URL     [本文引用: 1]

Yang J, Lee SH, Goddard ME, Visscher PM (2011)

GCTA: A tool for genome-wide complex trait analysis

American Journal of Human Genetics, 88, 76-82.

DOI:10.1016/j.ajhg.2010.11.011      URL     [本文引用: 1]

Zeng XJ, Li D, Hu YP, Huang QJ, Su XH (2014)

A preliminary study on construction of high-quality core collection of Populus nigra

Scientia Silvae Sinicae, 50(9), 51-58. (in Chinese with English abstract)

[本文引用: 2]

[ 曾宪君, 李丹, 胡彦鹏, 黄秦军, 苏晓华 (2014)

欧洲黑杨优质核心种质库的初步构建

林业科学, 50(9), 51-58.]

[本文引用: 2]

Zeng YF, Zhang JG, Abuduhamiti B, Wang WT, Jia ZQ (2018)

Phylogeographic patterns of the desert poplar in Northwest China shaped by both geology and climatic oscillations

BMC Ecology and Evolution, 18, 75.

[本文引用: 3]

Zhang L, Jiao PP, Li ZJ (2012)

Genetic diversity of Populus pruinosa populations in Xinjiang of China based on SSR analysis

Chinese Journal of Ecology, 31, 2755-2761. (in Chinese with English abstract)

[本文引用: 2]

[ 张玲, 焦培培, 李志军 (2012)

中国新疆灰叶胡杨群体遗传多样性的SSR分析

生态学杂志, 31, 2755-2761.]

[本文引用: 2]

Zhang XC, Xu CC, Song J, Li XF (2020)

Analysis of drought characteristics in Xinjiang area based on remote sensing DSI index

Jiangsu Agricultural Sciences, 48, 239-246. (in Chinese with English abstract)

[本文引用: 1]

[ 张喜成, 徐长春, 宋佳, 李晓菲 (2020)

基于遥感DSI的新疆干旱特征分析

江苏农业科学, 48, 239-246.]

[本文引用: 1]

Zhao B, Zhang QX (2007)

Preliminary construction of the core germplasm of Chimonanthus praecox in China

Journal of Beijing Forestry University, 29(S1), 16-21. (in Chinese with English abstract)

[本文引用: 1]

[ 赵冰, 张启翔 (2007)

中国蜡梅种质资源核心种质的初步构建

北京林业大学学报, 29(S1), 16-21.]

[本文引用: 1]

/

〈 〉

备案号：京ICP备16067583号-7
Copyright © 2022 版权所有 《生物多样性》编辑部
地址: 北京香山南辛村20号, 邮编：100093
电话: 010-62836137, 62836665 E-mail: biodiversity@ibcas.ac.cn