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Received: 2023-10-17

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 ORCID:

Jin-huan Chen

http://orcid.org/0000-0001-7223-3215

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Journal of Zhejiang University SCIENCE B 2017 Vol.18 No.11 P.1002-1021

http://doi.org/10.1631/jzus.B1700135


Physiological characterization, transcriptomic profiling, and microsatellite marker mining of Lycium ruthenicum


Author(s):  Jin-huan Chen, Dong-zhi Zhang, Chong Zhang, Mei-long Xu, Wei-lun Yin

Affiliation(s):  College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; more

Corresponding email(s):   chenjh@bjfu.edu.cn

Key Words:  De novo, Genetic diversity, Lycium ruthenicum, Molecular marker, Saline-alkaline mixed stress


Jin-huan Chen, Dong-zhi Zhang, Chong Zhang, Mei-long Xu, Wei-lun Yin. Physiological characterization, transcriptomic profiling, and microsatellite marker mining of Lycium ruthenicum[J]. Journal of Zhejiang University Science B, 2017, 18(11): 1002-1021.

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doi="10.1631/jzus.B1700135"
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Abstract: 
Lycium ruthenicum is a perennial shrub species that has attracted considerable interest in recent years owing to its nutritional value and ability to thrive in a harsh environment. However, only extremely limited transcriptomic and genomic data related to this species can be found in public databases, thereby limiting breeding research and molecular function analysis. In this study, we characterized the physiological and biochemical responses to saline-alkaline mixed stress by measuring photochemical efficiency, chlorophyll content, and protective enzyme activity. We performed global transcriptomic profiling analysis using the Illumina platform. After optimizing the assembly, a total of 68 063 unique transcript sequences with an average length of 877 bp were obtained. Among these sequences, 4096 unigenes were upregulated and 4381 unigenes were down-regulated after saline-alkaline mixed treatment. The most abundant transcripts and over-represented items were assigned to gene ontology (GO) terms or Kyoto Encyclopedia of Genes and the Genomes (KEGG) categories for overall unigenes, and differentially expressed unigenes were analyzed in detail. Based on this set of RNA-sequencing data, a total of 9216 perfect potential simple sequence repeats (SSRs) were identified within 7940 unigenes with a frequency of 1/6.48 kb. A total of 77 primer pairs were synthesized and examined in wet-laboratory experiments, of which 68 loci (88.3%) were successfully amplified with specific products. Eleven pairs of polymorphic primers were verified in 225 individuals from nine populations. The inbreeding coefficient and the polymorphism information content value ranged from 0.011 to 0.179 and from 0.1112 to 0.6750, respectively. The observed and expected heterozygosities ranged from 0.064 to 0.840 and from 0.115 to 0.726, respectively. Nine populations were clustered into three groups based on a genetic diversity study using these novel markers. Our data will be useful for functional genomic investigations of L. ruthenicum and could be used as a basis for further research on the genetic diversity, genetic differentiation, and gene flow of L. ruthenicum and other closely related species.

黑果枸杞生理指标测定、转录组分析以及分子标记开发研究

目的:以高耐盐碱多年生沙漠经济灌木黑果枸杞为研究材料,对其在盐碱胁迫处理下的生理指标进行测定,确定转录组测试的时间。通过转录组分析挖掘潜在抗逆基因,并挖掘全转录组水平的分子标记。旨在为黑果枸杞的优良基因资源利用、野生品种保护和新品种培育提供理论依据和实践指导。
创新点:首次对黑果枸杞进行盐碱胁迫下的生理指标变化和全转录组水平的基因表达变化进行分析,并基于转录组进行大规模简单重复序列标记开发和验证,并将所获取的分子标记应用到9个野生群体进行遗传多样性分析。
方法:采用双通道PAM-100荧光仪研究盐碱胁迫对黑果枸杞P700(PS I)和叶绿素荧光(PS II)的影响;通过盐碱胁迫下丙二醛(MDA)含量、超氧化物歧化酶(SOD)和过氧化物酶(POD)活性变化选定转录组测序(RNA-seq)取样时间;采用Illumina高通量测序平台进行转录组从头测序;选取20个基因采用荧光定量聚合酶链式反应(PCR)法进行基因表达分析;基于转录组序列组装结果进行简单重复序列扫描;采用聚丙烯酰胺凝聚和毛细管电泳法鉴定引物多态性,选取其中11对多态性引物应用于遗传多样性分析。
结论:通过对对照以及混合盐碱处理的黑果枸杞无菌苗进行生理和生化测试,结果选定处理6小时为取样点。RNA-seq结果共获得68 063个unigene,平均长度为877 bp,其中4096个基因在混合盐碱处理下表现为上调,4381个表现为下调。随机选取24个基因进行荧光定量表达分析,结果显示,荧光定量表达结果与RNA-seq结果呈显著正相关。基于转录组测试数据,在7940个基因中挖掘出9216个简单重复序列标记,对其中77个进行检测,显示有68个位点清晰存在,选取其中11个多态性位点对来自西北四个省份或自治区的9个野生种质资源进行遗传多样性分析,结果显示分析可靠。

关键词:从头测序;遗传多样性;黑果枸杞;分子标记;盐碱混合胁迫

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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[51]List of electronic supplementary materials

[52]Table S1 Primer sequences used in qPCR analysis

[53]Table S2 Top 100 most abundant transcripts in control sample

[54]Table S3 Top 100 most abundant transcripts in salt-alkaline mixed treated sample

[55]Table S4 Upregulated transcripts between the control and the saline-alkaline-treated sample

[56]Table S5 Downregulated unigenes between the control and treated sample

[57]Table S6 Top 300 most upregulated transcripts after treatment with annotation

[58]Fig. S1 Function classifications of GO terms of all L. ruthenicum transcripts

[59]Fig. S2 COG functional classification of the L. ruthenicum transcriptome

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