药学学报

Ecotype	Sample ID	Sampling site	Longitude/°	Latitude/°
Outside Shanhaiguan	DB1	New House Town North Port Participation, Changbai Mountain, Jilin	41.5836207800	127.3892081200
	DB2	New House Town North Port Participation, Changbai Mountain, Jilin	41.5861100000	127.3952900000
	DB3	New House Town North Port Participation, Changbai Mountain, Jilin	41.5918778844	127.4018935661
Inside Shanhaiguan	SD1	Zhang Jiachan Town, Shandong	37.0999326500	122.0990977200
	SD2	Zhang Jiachan Town, Shandong	37.1007800000	122.1041300000
	SD3	Zhang Jiachan Town, Shandong	37.1064385767	122.1107613345

Ecotype	Sample ID	Sampling site	Longitude/°	Latitude/°
Outside Shanhaiguan	DB1	New House Town North Port Participation, Changbai Mountain, Jilin	41.5836207800	127.3892081200
	DB2	New House Town North Port Participation, Changbai Mountain, Jilin	41.5861100000	127.3952900000
	DB3	New House Town North Port Participation, Changbai Mountain, Jilin	41.5918778844	127.4018935661
Inside Shanhaiguan	SD1	Zhang Jiachan Town, Shandong	37.0999326500	122.0990977200
	SD2	Zhang Jiachan Town, Shandong	37.1007800000	122.1041300000
	SD3	Zhang Jiachan Town, Shandong	37.1064385767	122.1107613345

Sample	Raw reads	Clean reads	Clean bases	Error/%	Q20/%	Q30/%	GC/%
SD1_1	34893434	33390538	3.34G	0.03	98.60	94.94	45.11
SD1_2	34893434	33390538	3.34G	0.03	97.92	93.75	45.16
SD2_1	31758271	30599780	3.06G	0.03	98.62	94.95	45.46
SD2_2	31758271	30599780	3.06G	0.03	97.85	93.57	45.52
SD3_1	32188565	30832289	3.08G	0.03	98.65	95.08	45.10
SD3_2	32188565	30832289	3.08G	0.03	97.91	93.75	45.15
DB1_1	32292768	31196124	3.12G	0.02	98.73	95.29	44.35
DB1_2	32292768	31196124	3.12G	0.03	98.06	94.11	44.39
DB2_1	33767990	32488000	3.25G	0.03	98.66	95.08	44.92
DB2_2	33767990	32488000	3.25G	0.03	97.97	93.87	44.98
DB3_1	32465989	31029001	3.1G	0.03	98.65	95.08	44.85
DB3_2	32465989	31029001	3.1G	0.03	97.92	93.78	44.90

Sample	Raw reads	Clean reads	Clean bases	Error/%	Q20/%	Q30/%	GC/%
SD1_1	34893434	33390538	3.34G	0.03	98.60	94.94	45.11
SD1_2	34893434	33390538	3.34G	0.03	97.92	93.75	45.16
SD2_1	31758271	30599780	3.06G	0.03	98.62	94.95	45.46
SD2_2	31758271	30599780	3.06G	0.03	97.85	93.57	45.52
SD3_1	32188565	30832289	3.08G	0.03	98.65	95.08	45.10
SD3_2	32188565	30832289	3.08G	0.03	97.91	93.75	45.15
DB1_1	32292768	31196124	3.12G	0.02	98.73	95.29	44.35
DB1_2	32292768	31196124	3.12G	0.03	98.06	94.11	44.39
DB2_1	33767990	32488000	3.25G	0.03	98.66	95.08	44.92
DB2_2	33767990	32488000	3.25G	0.03	97.97	93.87	44.98
DB3_1	32465989	31029001	3.1G	0.03	98.65	95.08	44.85
DB3_2	32465989	31029001	3.1G	0.03	97.92	93.78	44.90

Database	The number of the Unigenes	Percent/%
Annotated in NR	28 580	40.37
Annotated in NT	15 264	21.56
Annotated in KO	9 804	13.84
Annotated in SwissProt	21 205	29.95
Annotated in Pfam	22 901	32.34
Annotated in GO	28 873	40.78
Annotated in COG/KOG	11 529	16.28
Annotated in all Databases	4 380	6.18
Annotated in at least one Database	34 050	48.09
Total Unigenes	70 793	100

Database	The number of the Unigenes	Percent/%
Annotated in NR	28 580	40.37
Annotated in NT	15 264	21.56
Annotated in KO	9 804	13.84
Annotated in SwissProt	21 205	29.95
Annotated in Pfam	22 901	32.34
Annotated in GO	28 873	40.78
Annotated in COG/KOG	11 529	16.28
Annotated in all Databases	4 380	6.18
Annotated in at least one Database	34 050	48.09
Total Unigenes	70 793	100

Ko Number	KEGG pathway	Key unigene	The number of the unigenes
ko00909	Sesquiterpenoid and triterpenoid biosynthesis	comp75083_c0, comp65271_c0, comp76120_c0, comp59474_c0, comp69688_c0, comp70679_c0	10
ko00900	Terpenoid backbone biosynthesis	comp58220_c0, comp58220_c1, comp77697_c0, comp76561_c0, comp69124_c0, comp65081_c0, comp76232_c1, comp67432_c0, comp65471_c0, comp72369_c0	72
ko04146	Peroxisome	comp69588_c0	108
ko00280	Valine, leucine and isoleucine degradation	comp67540_c0	77
ko00100	Steroid biosynthesis	comp70267_c0, comp61865_c0	24
ko02020	Two-component system	comp53463_c0, comp53463_c1, comp63076_c0	122

Ko Number	KEGG pathway	Key unigene	The number of the unigenes
ko00909	Sesquiterpenoid and triterpenoid biosynthesis	comp75083_c0, comp65271_c0, comp76120_c0, comp59474_c0, comp69688_c0, comp70679_c0	10
ko00900	Terpenoid backbone biosynthesis	comp58220_c0, comp58220_c1, comp77697_c0, comp76561_c0, comp69124_c0, comp65081_c0, comp76232_c1, comp67432_c0, comp65471_c0, comp72369_c0	72
ko04146	Peroxisome	comp69588_c0	108
ko00280	Valine, leucine and isoleucine degradation	comp67540_c0	77
ko00100	Steroid biosynthesis	comp70267_c0, comp61865_c0	24
ko02020	Two-component system	comp53463_c0, comp53463_c1, comp63076_c0	122

Gene name	EC	Gene ID
Farnesyl-diphosphate farnesyltransferase (SS)	2.5.1.21	comp75083_c0
Squalene monooxygenase (SE)	1.14.13.17	comp65271_c0
		comp76322_c0
		comp76120_c0
Phosphomevalonate kinase (PMK)	2.7.4.2	comp58220_c0
		comp58220_c1
		comp77697_c0
Diphosphomevalonate decarboxylase (MVD)	4.1.1.33	comp76561_c0
Mevalonate kinase (MK)	2.7.1.36	comp69588_c0
Isopentenyl-diphosphate delta-isomerase (IDI)	5.3.3.2	comp69124_c0
Hydroxymethylglutaryl-CoA synthase (HMGS)	2.3.3.10	comp67540_c0
Hydroxymethylglutaryl-CoA reductase (HMGR)	1.1.1.34	comp65081_c0
		comp76232_c1
		comp67432_c0
Farnesyl diphosphate synthase (FPS)	2.5.1.10	comp65471_c0
		comp72369_c0
Cycloartenol synthase (CAS)	5.4.99.8	comp70267_c0
		comp61865_c0
Beta-amyrin synthase (AS)	5.4.99.39	comp59474_c0
		comp69688_c0
		comp70679_c0
Acetyl-CoA C-acetyltransferase (AACT)	2.3.1.9	comp53463_c0
		comp53463_c1
		comp63076_c0
Dolichyl-diphosphooligosaccharide-protein glycosyltransferase (GT)	-	comp70364_c0
		comp60837_c0
		comp75027_c0
		comp64229_c0

Gene name	EC	Gene ID
Farnesyl-diphosphate farnesyltransferase (SS)	2.5.1.21	comp75083_c0
Squalene monooxygenase (SE)	1.14.13.17	comp65271_c0
		comp76322_c0
		comp76120_c0
Phosphomevalonate kinase (PMK)	2.7.4.2	comp58220_c0
		comp58220_c1
		comp77697_c0
Diphosphomevalonate decarboxylase (MVD)	4.1.1.33	comp76561_c0
Mevalonate kinase (MK)	2.7.1.36	comp69588_c0
Isopentenyl-diphosphate delta-isomerase (IDI)	5.3.3.2	comp69124_c0
Hydroxymethylglutaryl-CoA synthase (HMGS)	2.3.3.10	comp67540_c0
Hydroxymethylglutaryl-CoA reductase (HMGR)	1.1.1.34	comp65081_c0
		comp76232_c1
		comp67432_c0
Farnesyl diphosphate synthase (FPS)	2.5.1.10	comp65471_c0
		comp72369_c0
Cycloartenol synthase (CAS)	5.4.99.8	comp70267_c0
		comp61865_c0
Beta-amyrin synthase (AS)	5.4.99.39	comp59474_c0
		comp69688_c0
		comp70679_c0
Acetyl-CoA C-acetyltransferase (AACT)	2.3.1.9	comp53463_c0
		comp53463_c1
		comp63076_c0
Dolichyl-diphosphooligosaccharide-protein glycosyltransferase (GT)	-	comp70364_c0
		comp60837_c0
		comp75027_c0
		comp64229_c0

Item	Ecological factor
Extreme wind speed/m·s^-1	219.454 5	230.937 5	331.612 2	235.916 7	268.714 3	178.888 9
Extreme wind Direction	8.727 3	10.225 8	9.574 5	11.416 7	13.833 3	10.555 6
Extreme minimum station pressure/hPa	9 916.119 0	9 890.071 4	9 859.771 4	9 615.767 4	9 673.750 0	9 524.275 0
Extreme minimum temperature/℃	-155.269 8	-148.555 6	-96.016 4	-289.682 5	-268.852 5	-304.721 3
Extreme maximum station pressure/hPa	10 899.761 9	10 381.285 7	10 338.571 4	10 113.767 4	10 149.150 0	9 987.150 0
Minimum relative humidity/%	7.454 5	7.425 5	11.904 8	7.208 3	5.913 0	9.431 8
Evaporation capacity (small)/mm	18 323.627 5	19 336.120 0	14 437.016 9	16 610.941 2	13 218.959 2	10 701.571 4
Extreme maximum temperature/℃	377.015 9	378.714 3	297.450 0	335.825 4	345.868 9	336.163 9
Maximum daily precipitation/mm	833.730 2	1 234.841 3	1 066.596 8	684.193 5	493.465 5	647.508 2
Precipitation/mm	5 760.206 3	6 172.142 9	7 154.983 9	5 877.682 5	5 199.541 0	8 323.901 6
Mean station pressure/hPa	10 156.222 2	10 120.111 1	10 114.322 0	9 868.111 1	9 928.366 7	9 764.508 5
Maximum wind speed/m·s^-1	163.062 5	153.500 0	252.022 7	209.254 5	172.195 1	107.791 7
Maximum wind direction	7.022 7	9.975 0	10.952 4	11.019 6	13.029 4	9.933 3
Average wind velocity/℃	29.428 6	32.952 4	63.161 3	38.666 7	25.475 4	12.409 8
Average temperature/℃	125.444 4	124.888 9	113.573 8	54.793 7	53.262 3	51.508 2
Average temperature anomaly/℃	-0.603 2	-0.142 9	-0.459 0	-2.269 8	-0.786 9	-1.541 0
Mean vapor pressure	119.206 3	118.904 8	120.774 2	83.158 7	82.573 8	87.147 5
Average relative humidity/%	65.730 2	66.555 6	74.129 0	63.666 7	65.065 6	70.082 0
Mean minimum temperature/℃	74.000 0	74.349 2	91.311 5	4.460 3	-3.836 1	-3.163 9
Mean maximum temperature/℃	186.984 1	186.984 1	140.983 3	111.285 7	121.377 0	121.366 7
Daily number of days precipitation ≥ 0.1 mm	70.063 5	78.047 6	89.225 8	100.825 4	102.508 2	138.803 3
Percentage of sunshine/%	58.096 8	58.152 5	55.660 7	58.698 4	52.233 3	49.883 3
Sunshine duration/h	25 751.000 0	25 764.288 1	24 714.232 1	26 071.142 9	23 200.933 3	22 166.233 3

Item	Ecological factor
Extreme wind speed/m·s^-1	219.454 5	230.937 5	331.612 2	235.916 7	268.714 3	178.888 9
Extreme wind Direction	8.727 3	10.225 8	9.574 5	11.416 7	13.833 3	10.555 6
Extreme minimum station pressure/hPa	9 916.119 0	9 890.071 4	9 859.771 4	9 615.767 4	9 673.750 0	9 524.275 0
Extreme minimum temperature/℃	-155.269 8	-148.555 6	-96.016 4	-289.682 5	-268.852 5	-304.721 3
Extreme maximum station pressure/hPa	10 899.761 9	10 381.285 7	10 338.571 4	10 113.767 4	10 149.150 0	9 987.150 0
Minimum relative humidity/%	7.454 5	7.425 5	11.904 8	7.208 3	5.913 0	9.431 8
Evaporation capacity (small)/mm	18 323.627 5	19 336.120 0	14 437.016 9	16 610.941 2	13 218.959 2	10 701.571 4
Extreme maximum temperature/℃	377.015 9	378.714 3	297.450 0	335.825 4	345.868 9	336.163 9
Maximum daily precipitation/mm	833.730 2	1 234.841 3	1 066.596 8	684.193 5	493.465 5	647.508 2
Precipitation/mm	5 760.206 3	6 172.142 9	7 154.983 9	5 877.682 5	5 199.541 0	8 323.901 6
Mean station pressure/hPa	10 156.222 2	10 120.111 1	10 114.322 0	9 868.111 1	9 928.366 7	9 764.508 5
Maximum wind speed/m·s^-1	163.062 5	153.500 0	252.022 7	209.254 5	172.195 1	107.791 7
Maximum wind direction	7.022 7	9.975 0	10.952 4	11.019 6	13.029 4	9.933 3
Average wind velocity/℃	29.428 6	32.952 4	63.161 3	38.666 7	25.475 4	12.409 8
Average temperature/℃	125.444 4	124.888 9	113.573 8	54.793 7	53.262 3	51.508 2
Average temperature anomaly/℃	-0.603 2	-0.142 9	-0.459 0	-2.269 8	-0.786 9	-1.541 0
Mean vapor pressure	119.206 3	118.904 8	120.774 2	83.158 7	82.573 8	87.147 5
Average relative humidity/%	65.730 2	66.555 6	74.129 0	63.666 7	65.065 6	70.082 0
Mean minimum temperature/℃	74.000 0	74.349 2	91.311 5	4.460 3	-3.836 1	-3.163 9
Mean maximum temperature/℃	186.984 1	186.984 1	140.983 3	111.285 7	121.377 0	121.366 7
Daily number of days precipitation ≥ 0.1 mm	70.063 5	78.047 6	89.225 8	100.825 4	102.508 2	138.803 3
Percentage of sunshine/%	58.096 8	58.152 5	55.660 7	58.698 4	52.233 3	49.883 3
Sunshine duration/h	25 751.000 0	25 764.288 1	24 714.232 1	26 071.142 9	23 200.933 3	22 166.233 3

基于遗传-化学-生态特征的西洋参品质生态型研究

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孙晓 ¹^,² , 钱秋玉 ³ , 郑司浩 ¹^,² , 陈海梅 ¹ , 黄林芳 ¹^,²^,^*

药学学报 | 研究论文 2019,54(9): 1695-1705

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药学学报 | 研究论文 2019, 54(9): 1695-1705

基于遗传-化学-生态特征的西洋参品质生态型研究

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孙晓¹^,², 钱秋玉³, 郑司浩¹^,², 陈海梅¹, 黄林芳¹^,²^,^*

作者信息

1.中国医学科学院、北京协和医学院药用植物研究所, 国家中医药管理局中药资源保护重点研究室, 北京 100193

2.中药资源教育部工程研究中心, 北京 100193

3.解放军总医院第七医学中心263临床部, 北京 101149

通讯作者:

*黄林芳, Tel:86-10-57833197, Fax:86-10-57833197, E-mail:lfhuang@implad.ac.cn

Quality ecotype of Panax quinquefolium L. based on heredity-chemistry-ecology characteristics

Xiao SUN¹^,², Qiu-yu QIAN³, Si-hao ZHENG¹^,², Hai-mei CHEN¹, Lin-fang HUANG¹^,²^,^*

Affiliations

1. Key Lab of Chinese Medicine Resources Conservation, State Administration of Traditional Chinese Medicine of China, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China

2. Engineering Research Center of Chinese Medicine Resource, Ministry of Education, Beijing 100193, China

3. The 263 nd Clinical Department, General Hospital of Beijing Military Area Command of PLA, Beijing 101149, China

出版时间: 2019-09-12 doi: 10.16438/j.0513-4870.2019-0394

文章导航

摘要

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我国不同生态型的同种药材品质差异显著，本课题组前期发现国产西洋参根据人参皂苷的特征存在关外型与关内型两大生态型，然而引起西洋参品质变异的遗传生态机制尚不清楚。本文基于遗传-化学-生态策略，运用转录组学技术、HPLC技术，并进行西洋参转录组数据、人参皂苷含量及环境气候生态因子的相关性分析。转录组结果显示人参皂苷生物合成关键基因如羟甲基戊二酰辅酶A还原酶（hydroxymethylglutaryl-CoA reductase，HMGR）、β-氨基酸合成酶（beta-amyrin synthase，AS）和法呢基焦磷酸合成酶（farnesyl diphosphate synthase，FPS）等在关内型均显著下调。HPLC结果表明关外型西洋参中人参皂苷含量高于关内型西洋参。相关性分析结果显示西洋参人参皂苷的含量与甲羟戊酸二磷酸脱羧酶（mevalonate kinase，MK）、羟甲基戊二酰辅酶A合酶（hydroxymethylglutaryl-CoA synthase，HMGS）、HMGR和AS等人参皂苷生物合成关键基因的表达成正相关，而与糖基转移酶GT的表达成负相关，西洋参的人参皂苷含量与两大生态型所处环境的温度、日照等气候因子成负相关，与水分成正相关。本文为阐释西洋参两大生态型品质变异的形成机制提供了新思路，也为道地药材品质生态学理论研究提供科学依据。

关键词

西洋参 / 中药品质生态学 / 转录组 / 人参皂苷 / 道地药材

Abstract

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Medicinal materials in China differ in quality by different ecological types. Our research group found that there were two ecotypes of domestic Panax quinquefolium L. according to the characteristics of ginsenosides, inside versus outside Shanhaiguan. The genetic and ecological mechanisms of quality variation of Panax quinquefolium L. is unknown. Based on the genetic-chemical-ecological strategy, transcriptome and HPLC technology were used for comprehensive correlation analyses of transcriptomic data, ginsenoside content and environmental climate ecological factors. The transcriptomic results showed that key genes of ginsenoside biosynthesis, such as HMGR, AS and FPS, were significantly down-regulated in the inside Shanhaiguan ecotype. HPLC results showed that the quality of outside Shanhaiguan ecotype Panax quinquefolium L. was higher than that of the inside ecotype, with the content of ginsenosides in outside Panax quinquefolium L. was higher than that of inside ecotype except Rb₂. Correlation analyses revealed that content of Panax quinquefolium L. ginsenoside is positively related to the expression levels of ginsenoside biosynthesis key genes (MK, HMGS, HMGR, and AS), and negatively related to the expression of glycosyl transferase (GT). The content of ginsenosides is negative related with climate factors, such as temperature, sunshine, and is positively related with moisture in both ecological environments. This study has provided a new mechanistic insight into the quality variations of two ecotypes for Panax quinquefolium L. and established a scientific basis for studying the ecological factors for the quality of traditional Chinese medicine.

Key words

Panax quinquefolium L. / quality ecology on chinese medicines / transcriptome / ginsenoside / daodi herbs

引用本文

孙晓, 钱秋玉, 郑司浩, 陈海梅, 黄林芳. 基于遗传-化学-生态特征的西洋参品质生态型研究. 药学学报, 2019 , 54 (9) : 1695 -1705 . DOI: 10.16438/j.0513-4870.2019-0394

Xiao SUN, Qiu-yu QIAN, Si-hao ZHENG, Hai-mei CHEN, Lin-fang HUANG. Quality ecotype of Panax quinquefolium L. based on heredity-chemistry-ecology characteristics[J]. Acta Pharmaceutica Sinica, 2019 , 54 (9) : 1695 -1705 . DOI: 10.16438/j.0513-4870.2019-0394

正文

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西洋参为五加科人参属植物西洋参(Panax quinquefolium L.)的干燥根, 具有补气养阴、清热生津之功效。西洋参原产于北美, 因其化学成分丰富, 生物活性广泛, 作为保健食品补充剂得到全球认可^[1]。西洋参主要活性成分是人参皂苷类, 因此被广泛地用于抗肿瘤、抗应激、抗衰老、抗疲劳、心脏保护和保肝属性^{[2, 3]}。人参皂苷根据其结构分为原人参二醇(如Rb₁、Rb₂、Re、Rd、F₂、Rg₃、Rh₂等)、原人参三醇(如Re、Rg₁、Rg₂、Rf、Rh₁等)和齐墩果酸(如Ro)^[4], 生物体内的合成途径为甲羟戊酸代谢途径(mevalonic acid pathway, MVA), 主要的关键酶基因有糖基转移酶(glycosyltransferase, GT)、角鲨烯环氧酶(squalene monooxygenase, SE)等^[5]。本课题组^[6]前期基于人参皂苷成分和气候特征, 应用生物统计、数量分类等分析方法对中国产西洋参进行了生态型划分, 将其分为Rb₁-Re山海关外型和Rg₂-Rd山海关内型两大化学生态型, 然而缺乏从遗传分子角度的基础性研究。

中药品质生态是研究中药品质及与生态环境关系及机制的关键^[7]。我国幅员辽阔, 拥有复杂的地理地貌条件和多样的气候环境, 这些均极大地影响中药材的品质, 形成了中药材特有的多产地、多道地现象。陈士林^[8]提出: “生态型是道地药材形成的生物学实质”, 从生物与生态学角度阐释道地药材形成的科学内涵。认为生态气候因子通过影响药材生长的环境, 进而影响药材的化学成分含量及遗传物质基础, 并对重楼^[9]、银杏^[10]、川贝母^[11]等大宗道地药材进行了生态适宜性的区划研究。然而相对于水稻等农业经济作物, 中药材的生态型研究相对薄弱, 不同生态型品质差异亟待研究。课题组在多年研究道地性理论及前人工作的基础上, 创新性地提出中药道地性理论研究新体系, 即遗传-化学-生态相关性的综合分析体系。运用UPLC-QTOF/MS与转录组和DNA条形码等技术, 结合生态气候因子及土壤因子数据综合分析评价道地药材的形成机制, 为深入研究中药道地性理论提供新思路。该体系已成功应用于肉苁蓉^[12]和黄花蒿^[13]等大宗道地药材。如课题组前期对黄花蒿进行品质变异分析, 发现秦岭-淮河分界线以南地区黄花蒿的青蒿素含量较高, DNA条形码分子标记分析显示黄花蒿种质资源存在显著的遗传差异和丰富的多样性, 且遗传多样性与地域相关, GMPGIS技术预测了湖南武陵山区、广西等优质黄花蒿的生态适宜区^[13]。应用超高效液相色谱法测定山西、内蒙古及甘肃三大主产地的黄芪中的毛蕊异黄酮苷等6种化学成分, 运用DNA条形码分子标记技术对黄芪进行分析^[14], 同时采用电感耦合等离子体原子发射光谱法(ICP-AES)测定黄芪及其根系土壤中19中无机元素含量^[15], 通过遗传-化学-生态相关性的综合分析体系探讨了黄芪品质变异的原因及其形成机制。

本研究通过对西洋参山海关内型与山海关外型两大生态型进行转录组测序, 分析比较其转录组差异, 以及人参皂苷合成途径关键酶基因的表达差异, 并结合化学成分含量及气候数据, 通过对遗传、化学及生态的相关性分析探讨影响不同生态型西洋参化学品质变异的潜在分子机制。

材料与方法

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材料本实验材料四年生西洋参样品于2012年采自吉林长白山新房子镇北港参场(关外型: DB)与山东威海文登张家产镇(关内型: SD), 采挖后用水洗净, 切断后迅速用锡箔纸包好放入液氮中, 并尽快转移至-80 ℃冰箱保存。西洋参样品由中国医学科学院药用植物研究所林余霖教授鉴定, 凭证标本保存于中国医学科学院药用植物研究所标本馆。

RNA提取及检测 应用百泰克植物通用总RNA提取试剂盒提取总RNA。按说明书对西洋参山东及东北样品进行总RNA提取。提取后的RNA进行琼脂糖凝胶电泳分析RNA降解程度, 并运用Nanodrop (2000, 赛默飞)检测RNA的纯度, 运用Aglient 2100生物分析仪(安捷伦)精确检测RNA的完整性。

文库构建及测序 样品检测合格后, 用带有Oligo (dT)的磁珠富集真核生物mRNA。随后加入破碎缓冲液将mRNA打断成短片段, 以mRNA为模板, 用六碱基随机引物(random hexamers)合成cDNA第一链, 然后加入缓冲液、dNTPs和DNA polymerase Ⅰ合成cDNA第二链, 随后利用AMPure XP beads (Beckman)纯化双链cDNA。纯化的双链cDNA再进行末端修复、加A尾并连接测序接头, 然后用AMPure XP beads进行片段大小选择, 最后进行PCR富集得到最终的cDNA文库。文库构建完成后, 先使用Qubit2.0荧光定量仪(赛默飞)进行初步定量, 稀释文库至1 ng·μL^-1, 随后使用Agilent 2100对文库的insert size进行检测, insert size符合预期后, 使用Q-PCR方法对文库的有效浓度进行准确定量(文库有效浓度 > 2 nmol·L^-1), 以保证文库质量。库检合格后, 把不同文库按照有效浓度及目标下机数据量的需求合并后进行Illumina HiSeq测序。

转录组分析 西洋参无参考基因组, 分析转录组数据时, 先将转录组测得序列拼接成转录本, 以此为参考序列进行后续数据分析。首先对测得数据进行检测, 并去掉质量较差的reads。应用Trinity软件进行转录组拼接, 对拼接后的基因进行功能注释[参考数据库包括Nr、Nt、Pfam、KOG/COG、Swiss-Prot、KEGG (Kyoto encyclopedia of genes and genomes)、GO (gene ontology)等]。对基因进行GO注释后, 可将注释成功的基因GO三个大类(BP: Biological process, CC: Cellular component, MF: Molecular function)的下一层级进行分类, 将KOG注释成功的基因按KOG的group进行分类, 对基因做KO注释后, 可根据它们参与的KEGG代谢通路进行分类。按NR、SwissProt、KEGG GENES的优先级顺序将unigene与以上数据库做blastx比对, 根据最佳比对结果确定unigene基因的ORF读码框, 然后根据标准遗传密码子表确定其CDS及编码的氨基酸序列; 将与以上数据库都比对不上的unigene用estscan (3.0.3)软件预测其CDS序列。

以Trinity拼接得到的转录组作为参考序列(ref), 采用RSEM软件(bowtie参数mismatch 2)将每个样品的clean reads对ref做mapping。RSEM对bowtie的比对结果进行统计, 进一步得到每个样品比对到每个基因上的read count数目, 并将之进行RPKM转换。RPKM密度分布能整体检查样品的基因表达模式, 对不同实验条件下的基因RPKM密度分布进行比较能整体上检查不同实验条件之间的RPKM分布的情况。两大生态型西洋参基因表达量差异表达的输入数据为基因表达水平分析中得到的read count数据。对于有生物学重复的样品, 采用DESeq进行分析, 筛选阈值为padj < 0.05, 该分析方法基于的模型是负二项分布, 第i个基因在第j个样本中的read count值为Kij, 则有: Kij~NB (μij, σij2)。

火山图可以直观展现p-value与log₂(fold change)的关系。差异基因聚类分析用于判断不同实验条件下差异基因表达量的聚类模式。每个比较组合都会得到一个差异基因集, 将所有比较组合的差异基因集的并集在每个实验组/样品中的RPKM值用于层次聚类分析。差异基因GO富集分析与KEGG富集分析可更好地对差异基因的功能进行研究。

人参皂苷含量测定 运用HPLC技术对关内型与关外型两大生态型的西洋参进行7种人参皂苷(Rg₁、Re、Rb₁、Ro、Rb₂、Rd、F₂)含量测定。色谱条件为Waters C₁₈色谱柱(150 mm×3.9 mm, 4.6 μm), 流动相为乙腈与0.1%甲酸水, 色谱条件为: 0~15 min, 19% A; 15~20 min, 19%~21% A; 20~22 min, 21%~26% A; 22~40 min, 26%~31% A; 40~45 min, 31% A; 45~57 min, 31%~43% A; 57~60 min, 43%~45% A。流速为1 mL·min^-1, 紫外检测波长为203 nm, 进样量为10 μL。方法学考察参考课题组前期实验工作^[16]。

相关性分析 本研究从中国气象数据网(http://data.cma.cn/)收集整理西洋参两大生态型附近的6个气象站(山东惠民54 725、潍坊54 843、成山头54 776, 吉林长春54 161、延吉54 292、临江站54 374) 1951~2013年间24个气候因子数据, 作为气候因子数据用于后续相关性分析。本研究结合西洋参不同生态型样品差异表达基因及人参皂苷生物合成途径中的关键酶基因表达差异, 找出与人参皂苷合成相关的关键酶基因群。运用各基因表达的RPKM值, 结合7种人参皂苷化学成分含量以及两产地24个生态气候因子数据, 应用SPSS 19.0统计分析软件进行Pearson相关性分析。

结果与分析

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1 西洋参两大生态型7种人参皂苷类成分含量测定

对西洋参中7种主要皂苷类成分进行HPLC含量测定。含量测定结果显示(图 1a), 关外型与关内型西洋参样品7种主要皂苷类成分含量存在差异, 关外生态型西洋参的人参皂苷含量较关内生态型西洋参高。PCA分析结果(图 1b)也表明两大生态型的西洋参样品差异显著, 明显地被聚成了两类。

2 西洋参两大生态型的转录组测序结果分析

对西洋参转录组数据进行测序错误率分布检查、GC含量分布检查, 并去除低质量的reads, 对原始reads进行过滤, 以得到clean reads (表 2)。采用Illumina HiSeq™ 2000高通量测序技术对东北(DB)和山东(SD) 2种不同生态型的西洋参测序, 分别获得9.47G和9.48G的原始数据。2组样品分别产生98 526 747和98 840 270条raw reads, 经过质量评估和数据过滤, 去除低质量和带有接头的序列, 分别得到94 713 125和94 822 607条clean reads。Q20 (Phred质量值大于20的碱基数占总碱基数clean data的比例)分别为98.26%和98.33%。这些序列经过组装, 总共获得70 793条Unigenes。从Unigene的长度分布情况(图 2)可知, Unigene主要集中在200~500 bp区间, 其Unigene数量为43 043, 占总数的60.80%;其次集中在500~1 000 bp, Unigene数量为12 701个, 占总数的17.94%;位于1 000~2 000 bp的Unigene数量为9 364个, 占总数的13.23%;大于2 000 bp的Unigene数量为5 685个, 占总数的8.03%。

3 西洋参两大生态型的基因功能注释

BLASTx同源性比对结果显示(表 3), 转录组所产生的70 793条Unigenes中, 共有34 050 (48.09%)条Unigenes至少在一个数据库中得到注释。其中, 注释到Nr数据库的有28 580条, 注释到Nt数据库的有15 264条, 注释到KEGG数据库的有9 804条, 注释到GO、KOG数据库的分别为28 873、11 529条, 其中有4 380条被这7个数据库同时注释。

将所有Unigenes与GO数据库比对(图 3a), 有28 873条Unigenes被分成三大类, 即“生物学过程(biological process)”、“细胞组分(cellular component)”和“分子功能(molecular function)”。“生物学过程”有最多的四级功能分类, 共有1 331条Unigenes。在“生物学过程”分类中, 注释最多的是“细胞组分的组织和生物合成(cellular process)”, 其次为“代谢途径(metabolic process)”, 推测这些途径与代谢产物的合成有关。共有387条Unigenes注释到“细胞组分”分类中, 其中占比例最多的是“细胞(cell)”与“细胞区域(cell part)”, “细胞器(organelle)”其次。仅有172条Unigenes注释到“分子功能”分类, 其中“连接(Binding)”占比例最大, 其次为“催化反应(catalytic activity)”。

根据Unigene的KEGG注释, 共有9 804个Unigene被注释, 被注释到的通路共有31条。Unigene参与的KEGG代谢通路可分为5个分支(图 3b):有机系统(organismal systems)、代谢(metabolism)、遗传信息处理(genetic information processing)、环境信息处理(environmental information processing)、细胞过程(cellular processes)。对西洋参的转录组数据进行代谢途径分析, 比对到了254个KEGG通路。“碳水化合物代谢(carbohydrate metabolism)”分类拥有最多的Unigenes。“代谢”中, 大多数代谢通路为能量、氨基酸、脂质等代谢产物。有6个与人参皂苷生物合成相关的通路(表 4), 包括倍半萜和三萜生物合成(sesquiterpenoid and triterpenoid biosynthesis)、萜类骨架生物合成(terpenoid backbone biosynthesis)、类固醇生物合成(steroid biosynthesis)等。其中, 有1条涉及到角鲨烯合成酶(SS)、3条涉及角鲨烯环氧酶(SE)、3条涉及磷酸甲羟戊酸激酶(PMK)等。

4 西洋参两大生态型差异表达基因的筛选及功能注释

对两种不同生态型的西洋参进行差异筛选(图 4a), 在关内型与关外型西洋参中共检测到339个差异表达基因, 其中上调基因79个, 下调基因260个。这些差异基因中, 共有267个有注释信息, 其他基因可能为西洋参所特有基因。两大生态型西洋参的差异基因表达层次聚类(图 4b), 其颜色相近聚类区内的基因表达模式相近, 表明关内与关外生态型的西洋参具有更多相似的功能或参与调控同一条代谢通路的基因。同时也显示关内与关外生态型西洋参基因的表达模式不尽相同。

通过GOseq对两种不同生态型的西洋参基因进行GO富集分析(图 4c)。1 792条Unigenes中有1 153条Unigenes被富集为“生物过程(biological process)”。关内型西洋参与关外型西洋参相比, 富集度最高的基因均涉及“对非生物刺激的反应(response to abiotic stimulus)”、“光刺激反应(response to light stimulus)”、“应对辐射(response to radiation)”等, 表明两大生态型西洋参的基因在与胁迫刺激相关中表达差异显著。

对两大生态型西洋参差异基因进行KEGG pathway富集分析(图 4d), 涉及人参皂苷生物合成的代谢通路有4条, 包括“倍半萜和三萜类生物合成途径(sesquiterpenoid and triterpenoid biosynthesis, ko00909)”、“萜类骨架生物合成(terpenoid backbone biosynthesis, ko00900)”、“次生代谢产物生物合成(biosynthesis of secondary metabolites, ko01110)”和“缬氨酸、亮氨酸和异亮氨酸降解(valine, leucine and isoleucine biosynthesis, ko00280)”。其中有2条Unigenes被注释到“倍半萜和三萜类生物合成途径”、2条Unigenes被注释到“萜类骨架生物合成”、12条Unigenes被注释到“次生代谢产物生物合成”以及1条Unigenes被注释到“缬氨酸、亮氨酸和异亮氨酸降解”。

5 人参皂苷生物合成相关基因挖掘

人参皂苷属于三萜类, 是由苷元和糖相连而成的糖苷类化合物。结合KEGG注释情况与文献^[17], 鉴定了两大生态型西洋参人参皂苷生物合成的关键基因群(表 5), 如角鲨烯合成酶(SS)、角鲨烯环氧酶(SE)和磷酸甲羟戊酸激酶(PMK)等。同时绘制了可能的生物合成通路图(图 5)。从通路图中可看到两大生态型之间关键基因表达量的差异情况, 通路中除了糖基转移酶(GT)外, 大部分关键基因表达量均是关外型高于关内型的。

进一步研究发现, 两个被注释到“倍半萜和三萜类生物合成途径”的差异基因分别为角鲨烯环氧酶squalene monooxygenase (SE, EC: 1.14.13.17, comp70679_c0)和β-氨基酸合成酶beta-amyrin synthase (AS, EC: 5.4.99.39, comp76322_c0), 且这两个基因在关内型西洋参中显著下调。被注释到“萜类骨架生物合成”的两个差异基因分别为法呢基焦磷酸合成酶farnesyl diphosphate synthase (FPS, EC: 2.5.1.10, comp72369_c0), 羟甲基戊二酰辅酶A还原酶hydroxymethylglutaryl-CoA reductase (HMGR, EC: 1.1.1.34, comp67432_c0)。同样的, 这些基因在关内型西洋参中也是显著下调的。

6 西洋参生态气候因子分析

从中国气象数据网下载东北与山东两产地西洋参样品采集地附近的气象站数据, 收集1951~2013年间24个气候因子的数据(表 6), 包括极大风速、极大风速的风向、极端最低本站气压、极端最低气温、极端最高本站气压、最小相对湿度、蒸发量(小型)、极端最高气温、最大日降水量、降水量、平均本站气压、最大风速、最大风速之风向、平均风速、平均气温、平均气温距平、平均水汽压、平均相对湿度、平均最低气温、平均最高气温、日降水量≥0.1 mm日数、日照百分率、日照时数。数据下载后, 去掉未检测数据及超出正常范围的数值, 整理以备后续相关性分析用。

7 相关性分析

基于遗传-化学-生态相关性分析的研究新体系, 对两大生态型西洋参转录组的人参皂苷合成相关24个差异基因的RPKM值、7种人参皂苷成分含量, 以及24个气候因子数据进行相关性分析, 以分析不同生态型西洋参品质差异的分子与生态机制(图 6)。西洋参人参皂苷的含量与大部分的人参皂苷体内生物合成途径上的关键酶基因的表达成正相关, 而与主要气候因子成负相关。人参皂苷Rg₁的含量与关键基因MK、HMGS、HMGR (comp67432_c0)和AS的表达量成极强正相关, 与差异关键基因SS、SE、MVD、FPS成强正相关, 而与HMGR (comp76232_c1)成强负相关。人参皂苷Re与差异关键基因AS的表达量成极强正相关, 与SE、PMK (comp58220_c1)基因的表达量成强正相关。人参皂苷Rb₂的含量与差异关键基因HMGR (comp65081_c0)成极强正相关, 与PMK (comp58220_c0)基因的表达量成强正相关。人参皂苷的含量与日降水量≥0.1 mm日数、极大风速的风向成正相关, 与其他气候因子主要成负相关。其中, 人参皂苷Rg1的含量与日降水量≥0.1 mm日数成强正相关, 而与极端最低气温、平均最低气温、平均水汽压、平均本站气压、极端最低本站气压、平均气温、日照百分率及日照时数成强负相关。人参皂苷Re的含量与极大风速的风向成强正相关。人参皂苷Ro的含量与平均气温及平均最高气温呈强负相关。人参皂苷Rd的含量与最大风速成强负相关。人参皂苷F2的含量与日照百分率、日照时数成强负相关。由此可得, 人参皂苷的含量与大部分的生物合成途径上的关键酶基因的表达成正相关, 与关键基因HMGR (comp76232_c1)成负相关。同时人参皂苷的含量与气候因子降水量成正相关, 而与温度、气压及日照等成负相关。

讨论

收起

本研究对西洋参关内型与关外型两大生态型的样品进行基于遗传-化学-生态的综合性相关性分析, 对两大生态型差异基因表达进行比较, 结合两大生态型7种皂苷类成分含量测定分析及24个气候因子数据, 分析西洋参不同生态型样品基因表达差异, 找出24个人参皂苷生物合成途径相关的差异关键酶基因, 并结合其表达量(RPKM值)、气候因子与人参皂苷含量进行相关性分析, 为阐明西洋参道地性的形成机制提供参考。

西洋参因其广泛应用及显著的药理活性而受到全球关注, 人参皂苷作为其主要活性成分更是研究的热点。现代药理学研究表明, 人参皂苷具有较好的抗肿瘤、抗炎、抗氧化和抑制细胞凋亡等药理活性^[18]。如Rg₁、Rb₁具有抗衰老活性, Rg₃、Rh₂具有抗肿瘤活性等^[19]。HMGR被公认为人参皂苷生物合成途径中的第一个限速酶, 是萜类合成过程中最先起作用的关键酶, 通过影响人参皂苷前体IPP和DMAPP的产量而影响人参皂苷的生物合成^[20]。FPS在人参皂苷的生物合成中起着重要作用^[21]。SS^[22]和SE^[23]是催化甾醇和三萜类化合物合成的关键酶基因, 对人参皂苷的含量有重要影响。由氧化鲨烯环化酶(oxidosqualene cyclase, OSC)催化的2, 3-氧化鲨烯环化也是三萜皂苷和甾醇生物合成分支形成的关键位点^[24]。GT催化人参皂苷苷元的糖基化, 是人参皂苷生物合成途径中最下游的步骤。糖基化可以增加人参皂苷的稳定性和水溶性, 从而增加了人参皂苷的多样性^[25]。由图 1a可知, 关外型西洋参的人参皂苷除Rb2外, 其余如Rg₁、Ro、Rb₁等的含量均高于关内型人参皂苷含量。转录组分析结果表明, 两大生态型西洋参的基因在表达模式上不尽相同, 且关内型与关外型相比, 人参皂苷生物合成关键基因如SE、AS、FPS和HMGR等均在关内型显著下调, 与人参皂苷含量差异是一致。图 5结果显示大多人参皂苷生物合成关键基因如AACT、HMGR、HMGS、MK、PMK、MVD、FPS、SS、SE、AS等, 在关外型中表达量较高, 而在关内型却较低。值得注意的是, 下游基因糖基转移酶(GT)在关外型西洋参中表达量较低, 却在关内型中表达量较高。

中药材品质变异是物种对不同生态环境长期适应与自然选择的结果。遗传因素是中药材品质变异的生物学实质, 环境因素是中药材品质变异的生态学实质^[8]。基于遗传-化学-生态相关性分析, 结果表明西洋参人参皂苷的含量与AACT、HMGR、HMGS、MK、PMK、MVD、FPS、SS、SE、AS等人参皂苷生物合成关键基因的表达成正相关, 而与糖基转移酶GT的表达成负相关。在药用植物中气候是直接影响药用植物的生长、发育和繁殖的关键因素^[26]。温度、光照和降水等是影响气候较大的因素。相关性分析结果显示, 西洋参的人参皂苷含量与两大生态型所处环境的温度、日照等气候因子成负相关, 与水分成正相关。关外地区属于温带湿润、半湿润大陆性季风气候, 地处长白山脉, 海拔较高且植被丰富, 所以气温较低, 蒸发较弱, 降水量不多, 但湿度仍较高。而关内地区则属于暖温带季风气候且临近海洋^[6]。该结果表明关外型西洋参的人参皂苷含量高于关内型, 可能与关外型所处环境气温更低、日照更少, 湿度较高有关。综上, 关外型西洋参品质较关内型西洋参高, 其中人参皂苷生物合成关键基因在关外型的表达量较高及关外型气温低、日照少和温度高等可能是品质差异的原因。研究结果为科学合理阐释西洋参品质差异成因提供参考, 为中药材品质生态学理论研究提供科学依据, 进一步为西洋参分子育种的优质品种研究奠定基础。

基金

收起

国家自然科学基金资助项目(81274013)
国家自然科学基金资助项目(81473315)
中国医学科学院医学与健康科技创新工程项目(2016-I2M-3-015)

参考文献

收起

文献

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参考文献引证文献

排序方式：

[1]

Cheng

, Wang

, Xu

et al . Progress in quality evaluation of American ginseng medicinal materials[J]. Shandong Sci (山东科学), 2018, 4: 39-43, 49.

[2]

Lee

, Jung

, Kim

et al . The antistress effect of ginseng total saponin and ginsenoside Rg₃ and Rb₁ evaluated by brain polyamine level under immobilization stress[J]. Pharmacol Res, 2006, 54: 46-49.

https://doi.org/10.1016/j.phrs.2006.02.001

[3]

Lee

, Jung

, Lee

et al . Panax ginseng induces human Type Ⅰ collagen synthesis through activation of Smad signaling[J]. J Ethnopharmacol, 2007, 109: 29-34.

https://doi.org/10.1016/j.jep.2006.06.008

[4]

Chen

, Wu

, Gao

et al . Research progress on fungal biotransformation of ginseng saponins in American ginseng[J]. Food Res Devel (食品研究与开发), 2019, 40: 220-224.

[5]

Wang

, Li

et al . Transcriptome profiling shows gene regulation patterns in ginsenoside pathway in response to methyl jasmonate in Panax quinquefolium adventitious root[J]. Sci Rep, 2016, 6: 37263.

https://doi.org/10.1038/srep37263

[6]

Huang

, Suo

, Song

et al . Quality variation and ecotype division of Panax quinquefolium in China[J]. Acta Pharm Sin (药学学报), 2013, 48: 580-589. http://www.yxxb.com.cn:8081/aps/CN/abstract/abstract14418.shtml

[7]

Huang

, Chen

. Quality ecology of traditional Chinese medicine: an emerging interdisciplinary subject[J]. Chin J Exp Tradit Med Form (中国实验方剂学杂志), 2017, 23: 1-11.

[8]

Huang

, Fu

, Chen

. Academic discussion on ecological variation of Chinese medicinal materials[J]. Chin Tradit Herb Drugs (中草药), 2012, 43: 1249-1258.

[9]

Cheng

, Wu

, Shen

et al . Analysis of ecological suitability of global producing area of traditional Chinese medicine[J]. Chin J Exp Tradit Med Form (中国实验方剂学杂志), 2017, 23: 19-24.

[10]

, Shen

, Wang

et al . Analysis of global ecological suitable production area of Ginkgo biloba based on GMPGIS[J]. World Chin Med (世界中医药), 2017, 12: 969-973. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=sjzyy201705003

[11]

Jiang

, Sun

, Qin

et al . Study on the functional zoning of Fritillaria cirrhosa based on growth suitability and quality suitability[J]. China J Chin Mater Med (中国中药杂志), 2016, 41: 3194-3201.

[12]

Zheng

, Jiang

, Huang

et al . Chemical and genetic discrimination of Cistanches Herba based on UPLCQTOF/MS and DNA barcoding[J]. PLoS One, 2014, 9: e98061.

https://doi.org/10.1371/journal.pone.0098061

[13]

Lin

, Josef

, Bing

et al . Three-dimensional evaluation on ecotypic diversity of traditional Chinese medicine: a case study of Artemisia annua L.[J]. Front Plant Sci, 2017, 8: 1225.

https://doi.org/10.3389/fpls.2017.01225

[14]

, Zheng

, Brinckmann

et al . Chemical and genetic diversity of Astragalus mongholicus grown in different eco-climatic regions[J]. PLoS One, 2017, 12: e0184791.

https://doi.org/10.1371/journal.pone.0184791

[15]

, Zheng

, Yang

et al . Distinguishing Astragalus mongholicus and its planting soil samples from different regions by ICP-AES[J]. Molecules, 2016, 21: 482.

https://doi.org/10.3390/molecules21040482

[16]

Wang ZH. Study on the Quality and Origin Variation of American Ginseng and Screening of EGFR Kinase Inhibitors for 49 Medicinal Extracts (西洋参品质和产地变异研究及49种药材提取物EGFR激酶抑制剂筛选)[D]. Beijing: Peking Union Medical College, 2015.

[17]

Yang

, Gao

, Zhu

. Advances in the biosynthesis research of ginsenosides[J]. Acta Pharm Sin (药学学报), 2013, 48: 170-178. http://www.yxxb.com.cn:8081/aps/CN/abstract/abstract14390.shtml

[18]

, Wang

, Chen

. Research progress on pharmacological effects of ginsenoside[J]. J Liaoning Univ Tradit Chin Med (辽宁中医药大学学报), 2012, 14: 118-121. http://d.old.wanfangdata.com.cn/Periodical/zcy201620029

[19]

Christensen

. Ginsenosides chemistry, biosynthesis, analysis, and potential health effects[J]. Adv Food Nutr Res, 2009, 55: 1-99. http://www.sciencedirect.com/science/article/pii/S1043452608004014

[20]

, Sun

, Chen

. Identification and expression analysis of a 3-hydroxy-3-methylglutaryl coenzyme A reductase gene from American ginseng[J]. Plant OMICS: J Plant Mol Biol Omics, 2012, 5: 414-420. https://www.researchgate.net/publication/267423211_Identification_and_expression_analysis_of_a_3-hydroxy-3-methylglutaryl_coenzyme_A_reductase_gene_from_American_ginseng

[21]

Kim

, Bang

, Jung

et al . Molecular characterization of ginseng farnesyl diphosphate synthase gene and its up-regulation by methyl jasmonate[J]. Biol Plant, 2010, 54: 47-53.

https://doi.org/10.1007/s10535-010-0007-1

[22]

Lee

, Jeong

, Seo

et al . Enhanced triterpene and phytosterol biosynthesis in Panax ginseng overexpressing squalene synthase gene[J]. Plant Cell Physiol, 2004, 45: 976-984.

https://doi.org/10.1093/pcp/pch126

[23]

Han

, In

, Kwon

et al . Regulation of ginsenoside and phytosterol biosynthesis by RNA interferences of squalene epoxidase gene in Panax ginseng[J]. Phytochemistry, 2010, 71: 36-46.

https://doi.org/10.1016/j.phytochem.2009.09.031

[24]

Lee

, Han

, Kim

et al . Dammarenediol-Ⅱ production confers TMV Tolerance in transgenic tobacco expressing Panax ginseng dammarenediol-Ⅱ synthase[J]. Plant Cell Physiol, 2012, 53: 173-182.

https://doi.org/10.1093/pcp/pcr160

[25]

Yue

, Zhong

. Purification and characterization of UDPG: ginsenoside Rd glucosyltransferase from suspended cells of Panax notoginseng[J]. Proc Biochem, 2005, 40: 3742-3748.

https://doi.org/10.1016/j.procbio.2005.05.001

[26]

Xing

, Liu

, Yin

et al . The association between property of Chinese medicinal herbs and chemical components, ecological environment[J]. J Chin Med Mater (中药材), 2011, 34: 324-325.

2019年第54卷第9期

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文章信息

doi: 10.16438/j.0513-4870.2019-0394

接收时间：2019-05-20
首发时间：2026-01-26
出版时间：2019-09-12

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出版历史

收稿日期：2019-05-20
修回日期：2019-06-18

基金

国家自然科学基金资助项目(81274013)

国家自然科学基金资助项目(81473315)

中国医学科学院医学与健康科技创新工程项目(2016-I2M-3-015)

作者信息

1.中国医学科学院、北京协和医学院药用植物研究所, 国家中医药管理局中药资源保护重点研究室, 北京 100193

2.中药资源教育部工程研究中心, 北京 100193

3.解放军总医院第七医学中心263临床部, 北京 101149

通讯作者:

*黄林芳, Tel:86-10-57833197, Fax:86-10-57833197, E-mail:lfhuang@implad.ac.cn

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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Ecotype	Sample ID	Sampling site	Longitude/°	Latitude/°
Outside Shanhaiguan	DB1	New House Town North Port Participation, Changbai Mountain, Jilin	41.5836207800	127.3892081200
	DB2	New House Town North Port Participation, Changbai Mountain, Jilin	41.5861100000	127.3952900000
	DB3	New House Town North Port Participation, Changbai Mountain, Jilin	41.5918778844	127.4018935661
Inside Shanhaiguan	SD1	Zhang Jiachan Town, Shandong	37.0999326500	122.0990977200
	SD2	Zhang Jiachan Town, Shandong	37.1007800000	122.1041300000
	SD3	Zhang Jiachan Town, Shandong	37.1064385767	122.1107613345

Ecotype

Sample ID

Sampling site

Longitude/°

Latitude/°

Outside Shanhaiguan

DB1

New House Town North Port Participation, Changbai Mountain, Jilin

41.5836207800

127.3892081200

DB2

New House Town North Port Participation, Changbai Mountain, Jilin

41.5861100000

127.3952900000

DB3

New House Town North Port Participation, Changbai Mountain, Jilin

41.5918778844

127.4018935661

Inside Shanhaiguan

SD1

Zhang Jiachan Town, Shandong

37.0999326500

122.0990977200

SD2

Zhang Jiachan Town, Shandong

37.1007800000

122.1041300000

SD3

Zhang Jiachan Town, Shandong

37.1064385767

122.1107613345

Sample	Raw reads	Clean reads	Clean bases	Error/%	Q20/%	Q30/%	GC/%
SD1_1	34893434	33390538	3.34G	0.03	98.60	94.94	45.11
SD1_2	34893434	33390538	3.34G	0.03	97.92	93.75	45.16
SD2_1	31758271	30599780	3.06G	0.03	98.62	94.95	45.46
SD2_2	31758271	30599780	3.06G	0.03	97.85	93.57	45.52
SD3_1	32188565	30832289	3.08G	0.03	98.65	95.08	45.10
SD3_2	32188565	30832289	3.08G	0.03	97.91	93.75	45.15
DB1_1	32292768	31196124	3.12G	0.02	98.73	95.29	44.35
DB1_2	32292768	31196124	3.12G	0.03	98.06	94.11	44.39
DB2_1	33767990	32488000	3.25G	0.03	98.66	95.08	44.92
DB2_2	33767990	32488000	3.25G	0.03	97.97	93.87	44.98
DB3_1	32465989	31029001	3.1G	0.03	98.65	95.08	44.85
DB3_2	32465989	31029001	3.1G	0.03	97.92	93.78	44.90

Sample

Raw reads

Clean reads

Clean bases

Error/%

Q20/%

Q30/%

GC/%

SD1_1

34893434

33390538

3.34G

0.03

98.60

94.94

45.11

SD1_2

34893434

33390538

3.34G

0.03

97.92

93.75

45.16

SD2_1

31758271

30599780

3.06G

0.03

98.62

94.95

45.46

SD2_2

31758271

30599780

3.06G

0.03

97.85

93.57

45.52

SD3_1

32188565

30832289

3.08G

0.03

98.65

95.08

45.10

SD3_2

32188565

30832289

3.08G

0.03

97.91

93.75

45.15

DB1_1

32292768

31196124

3.12G

0.02

98.73

95.29

44.35

DB1_2

32292768

31196124

3.12G

0.03

98.06

94.11

44.39

DB2_1

33767990

32488000

3.25G

0.03

98.66

95.08

44.92

DB2_2

33767990

32488000

3.25G

0.03

97.97

93.87

44.98

DB3_1

32465989

31029001

3.1G

0.03

98.65

95.08

44.85

DB3_2

32465989

31029001

3.1G

0.03

97.92

93.78

44.90

Database	The number of the Unigenes	Percent/%
Annotated in NR	28 580	40.37
Annotated in NT	15 264	21.56
Annotated in KO	9 804	13.84
Annotated in SwissProt	21 205	29.95
Annotated in Pfam	22 901	32.34
Annotated in GO	28 873	40.78
Annotated in COG/KOG	11 529	16.28
Annotated in all Databases	4 380	6.18
Annotated in at least one Database	34 050	48.09
Total Unigenes	70 793	100

Database

The number of the Unigenes

Percent/%

Annotated in NR

28 580

40.37

Annotated in NT

15 264

21.56

Annotated in KO

9 804

13.84

Annotated in SwissProt

21 205

29.95

Annotated in Pfam

22 901

32.34

Annotated in GO

28 873

40.78

Annotated in COG/KOG

11 529

16.28

Annotated in all Databases

4 380

6.18

Annotated in at least one Database

34 050

48.09

Total Unigenes

70 793

100

Ko Number	KEGG pathway	Key unigene	The number of the unigenes
ko00909	Sesquiterpenoid and triterpenoid biosynthesis	comp75083_c0, comp65271_c0, comp76120_c0, comp59474_c0, comp69688_c0, comp70679_c0	10
ko00900	Terpenoid backbone biosynthesis	comp58220_c0, comp58220_c1, comp77697_c0, comp76561_c0, comp69124_c0, comp65081_c0, comp76232_c1, comp67432_c0, comp65471_c0, comp72369_c0	72
ko04146	Peroxisome	comp69588_c0	108
ko00280	Valine, leucine and isoleucine degradation	comp67540_c0	77
ko00100	Steroid biosynthesis	comp70267_c0, comp61865_c0	24
ko02020	Two-component system	comp53463_c0, comp53463_c1, comp63076_c0	122

Ko Number

KEGG pathway

Key unigene

The number of the unigenes

ko00909

Sesquiterpenoid and triterpenoid biosynthesis

comp75083_c0, comp65271_c0, comp76120_c0, comp59474_c0, comp69688_c0, comp70679_c0

ko00900

Terpenoid backbone biosynthesis

comp58220_c0, comp58220_c1, comp77697_c0, comp76561_c0, comp69124_c0, comp65081_c0, comp76232_c1, comp67432_c0, comp65471_c0, comp72369_c0

ko04146

Peroxisome

comp69588_c0

108

ko00280

Valine, leucine and isoleucine degradation

comp67540_c0

ko00100

Steroid biosynthesis

comp70267_c0, comp61865_c0

ko02020

Two-component system

comp53463_c0, comp53463_c1, comp63076_c0

122

Gene name	EC	Gene ID
Farnesyl-diphosphate farnesyltransferase (SS)	2.5.1.21	comp75083_c0
Squalene monooxygenase (SE)	1.14.13.17	comp65271_c0
		comp76322_c0
		comp76120_c0
Phosphomevalonate kinase (PMK)	2.7.4.2	comp58220_c0
		comp58220_c1
		comp77697_c0
Diphosphomevalonate decarboxylase (MVD)	4.1.1.33	comp76561_c0
Mevalonate kinase (MK)	2.7.1.36	comp69588_c0
Isopentenyl-diphosphate delta-isomerase (IDI)	5.3.3.2	comp69124_c0
Hydroxymethylglutaryl-CoA synthase (HMGS)	2.3.3.10	comp67540_c0
Hydroxymethylglutaryl-CoA reductase (HMGR)	1.1.1.34	comp65081_c0
		comp76232_c1
		comp67432_c0
Farnesyl diphosphate synthase (FPS)	2.5.1.10	comp65471_c0
		comp72369_c0
Cycloartenol synthase (CAS)	5.4.99.8	comp70267_c0
		comp61865_c0
Beta-amyrin synthase (AS)	5.4.99.39	comp59474_c0
		comp69688_c0
		comp70679_c0
Acetyl-CoA C-acetyltransferase (AACT)	2.3.1.9	comp53463_c0
		comp53463_c1
		comp63076_c0
Dolichyl-diphosphooligosaccharide-protein glycosyltransferase (GT)	-	comp70364_c0
		comp60837_c0
		comp75027_c0
		comp64229_c0

Gene name

Gene ID

Farnesyl-diphosphate farnesyltransferase (SS)

2.5.1.21

comp75083_c0

Squalene monooxygenase (SE)

1.14.13.17

comp65271_c0

comp76322_c0

comp76120_c0

Phosphomevalonate kinase (PMK)

2.7.4.2

comp58220_c0

comp58220_c1

comp77697_c0

Diphosphomevalonate decarboxylase (MVD)

4.1.1.33

comp76561_c0

Mevalonate kinase (MK)

2.7.1.36

comp69588_c0

Isopentenyl-diphosphate delta-isomerase (IDI)

5.3.3.2

comp69124_c0

Hydroxymethylglutaryl-CoA synthase (HMGS)

2.3.3.10

comp67540_c0

Hydroxymethylglutaryl-CoA reductase (HMGR)

1.1.1.34

comp65081_c0

comp76232_c1

comp67432_c0

Farnesyl diphosphate synthase (FPS)

2.5.1.10

comp65471_c0

comp72369_c0

Cycloartenol synthase (CAS)

5.4.99.8

comp70267_c0

comp61865_c0

Beta-amyrin synthase (AS)

5.4.99.39

comp59474_c0

comp69688_c0

comp70679_c0

Acetyl-CoA C-acetyltransferase (AACT)

2.3.1.9

comp53463_c0

comp53463_c1

comp63076_c0

Dolichyl-diphosphooligosaccharide-protein glycosyltransferase (GT)

comp70364_c0

comp60837_c0

comp75027_c0

comp64229_c0

Item	Ecological factor
Extreme wind speed/m·s^-1	219.454 5	230.937 5	331.612 2	235.916 7	268.714 3	178.888 9
Extreme wind Direction	8.727 3	10.225 8	9.574 5	11.416 7	13.833 3	10.555 6
Extreme minimum station pressure/hPa	9 916.119 0	9 890.071 4	9 859.771 4	9 615.767 4	9 673.750 0	9 524.275 0
Extreme minimum temperature/℃	-155.269 8	-148.555 6	-96.016 4	-289.682 5	-268.852 5	-304.721 3
Extreme maximum station pressure/hPa	10 899.761 9	10 381.285 7	10 338.571 4	10 113.767 4	10 149.150 0	9 987.150 0
Minimum relative humidity/%	7.454 5	7.425 5	11.904 8	7.208 3	5.913 0	9.431 8
Evaporation capacity (small)/mm	18 323.627 5	19 336.120 0	14 437.016 9	16 610.941 2	13 218.959 2	10 701.571 4
Extreme maximum temperature/℃	377.015 9	378.714 3	297.450 0	335.825 4	345.868 9	336.163 9
Maximum daily precipitation/mm	833.730 2	1 234.841 3	1 066.596 8	684.193 5	493.465 5	647.508 2
Precipitation/mm	5 760.206 3	6 172.142 9	7 154.983 9	5 877.682 5	5 199.541 0	8 323.901 6
Mean station pressure/hPa	10 156.222 2	10 120.111 1	10 114.322 0	9 868.111 1	9 928.366 7	9 764.508 5
Maximum wind speed/m·s^-1	163.062 5	153.500 0	252.022 7	209.254 5	172.195 1	107.791 7
Maximum wind direction	7.022 7	9.975 0	10.952 4	11.019 6	13.029 4	9.933 3
Average wind velocity/℃	29.428 6	32.952 4	63.161 3	38.666 7	25.475 4	12.409 8
Average temperature/℃	125.444 4	124.888 9	113.573 8	54.793 7	53.262 3	51.508 2
Average temperature anomaly/℃	-0.603 2	-0.142 9	-0.459 0	-2.269 8	-0.786 9	-1.541 0
Mean vapor pressure	119.206 3	118.904 8	120.774 2	83.158 7	82.573 8	87.147 5
Average relative humidity/%	65.730 2	66.555 6	74.129 0	63.666 7	65.065 6	70.082 0
Mean minimum temperature/℃	74.000 0	74.349 2	91.311 5	4.460 3	-3.836 1	-3.163 9
Mean maximum temperature/℃	186.984 1	186.984 1	140.983 3	111.285 7	121.377 0	121.366 7
Daily number of days precipitation ≥ 0.1 mm	70.063 5	78.047 6	89.225 8	100.825 4	102.508 2	138.803 3
Percentage of sunshine/%	58.096 8	58.152 5	55.660 7	58.698 4	52.233 3	49.883 3
Sunshine duration/h	25 751.000 0	25 764.288 1	24 714.232 1	26 071.142 9	23 200.933 3	22 166.233 3

Item

Ecological factor

54725

54843

54776

54161

54292

54374

Extreme wind speed/m·s^-1

219.454 5

230.937 5

331.612 2

235.916 7

268.714 3

178.888 9

Extreme wind Direction

8.727 3

10.225 8

9.574 5

11.416 7

13.833 3

10.555 6

Extreme minimum station pressure/hPa

9 916.119 0

9 890.071 4

9 859.771 4

9 615.767 4

9 673.750 0

9 524.275 0

Extreme minimum temperature/℃

-155.269 8

-148.555 6

-96.016 4

-289.682 5

-268.852 5

-304.721 3

Extreme maximum station pressure/hPa

10 899.761 9

10 381.285 7

10 338.571 4

10 113.767 4

10 149.150 0

9 987.150 0

Minimum relative humidity/%

7.454 5

7.425 5

11.904 8

7.208 3

5.913 0

9.431 8

Evaporation capacity (small)/mm

18 323.627 5

19 336.120 0

14 437.016 9

16 610.941 2

13 218.959 2

10 701.571 4

Extreme maximum temperature/℃

377.015 9

378.714 3

297.450 0

335.825 4

345.868 9

336.163 9

Maximum daily precipitation/mm

833.730 2

1 234.841 3

1 066.596 8

684.193 5

493.465 5

647.508 2

Precipitation/mm

5 760.206 3

6 172.142 9

7 154.983 9

5 877.682 5

5 199.541 0

8 323.901 6

Mean station pressure/hPa

10 156.222 2

10 120.111 1

10 114.322 0

9 868.111 1

9 928.366 7

9 764.508 5

Maximum wind speed/m·s^-1

163.062 5

153.500 0

252.022 7

209.254 5

172.195 1

107.791 7

Maximum wind direction

7.022 7

9.975 0

10.952 4

11.019 6

13.029 4

9.933 3

Average wind velocity/℃

29.428 6

32.952 4

63.161 3

38.666 7

25.475 4

12.409 8

Average temperature/℃

125.444 4

124.888 9

113.573 8

54.793 7

53.262 3

51.508 2

Average temperature anomaly/℃

-0.603 2

-0.142 9

-0.459 0

-2.269 8

-0.786 9

-1.541 0

Mean vapor pressure

119.206 3

118.904 8

120.774 2

83.158 7

82.573 8

87.147 5

Average relative humidity/%

65.730 2

66.555 6

74.129 0

63.666 7

65.065 6

70.082 0

Mean minimum temperature/℃

74.000 0

74.349 2

91.311 5

4.460 3

-3.836 1

-3.163 9

Mean maximum temperature/℃

186.984 1

140.983 3

111.285 7

121.377 0

121.366 7

Daily number of days precipitation ≥ 0.1 mm

70.063 5

78.047 6

89.225 8

100.825 4

102.508 2

138.803 3

Percentage of sunshine/%

58.096 8

58.152 5

55.660 7

58.698 4

52.233 3

49.883 3

Sunshine duration/h

25 751.000 0

25 764.288 1

24 714.232 1

26 071.142 9

23 200.933 3

22 166.233 3