Full Text:   <1507>

Summary:  <1254>

Suppl. Mater.: 

CLC number: Q37

On-line Access: 2017-11-06

Received: 2017-03-11

Revision Accepted: 2017-07-28

Crosschecked: 2017-10-20

Cited: 0

Clicked: 2756

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jin-huan Chen

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

-   Go to

Article info.
Open peer comments

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.

@article{title="Physiological characterization, transcriptomic profiling, and microsatellite marker mining of Lycium ruthenicum",
author="Jin-huan Chen, Dong-zhi Zhang, Chong Zhang, Mei-long Xu, Wei-lun Yin",
journal="Journal of Zhejiang University Science B",
volume="18",
number="11",
pages="1002-1021",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1700135"
}

%0 Journal Article
%T Physiological characterization, transcriptomic profiling, and microsatellite marker mining of Lycium ruthenicum
%A Jin-huan Chen
%A Dong-zhi Zhang
%A Chong Zhang
%A Mei-long Xu
%A Wei-lun Yin
%J Journal of Zhejiang University SCIENCE B
%V 18
%N 11
%P 1002-1021
%@ 1673-1581
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1700135

TY - JOUR
T1 - Physiological characterization, transcriptomic profiling, and microsatellite marker mining of Lycium ruthenicum
A1 - Jin-huan Chen
A1 - Dong-zhi Zhang
A1 - Chong Zhang
A1 - Mei-long Xu
A1 - Wei-lun Yin
J0 - Journal of Zhejiang University Science B
VL - 18
IS - 11
SP - 1002
EP - 1021
%@ 1673-1581
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1700135


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

Reference

[1]Alam, S.M., Naqvi, S.S.M., Ansari, R., 1999. Impact of soil pH on nutrient uptake by crop plants. In: Pessarakli, M. (Ed.), Handbook of Plant and Crop Stress. Marcel Dekker, Inc., New York, p.51-60.

[2]Altintas, A., Kosar, M., Kirimer, N., et al., 2006. Composition of the essential oils of Lyceum barbarum and L. ruthenicum fruits. Chem. Nat. Compd., 42(1):24-25.

[3]Babuin, M.F., Campestre, M.P., Rocco, R., et al., 2014. Response to long-term NaHCO3-derived alkalinity in model Lotus japonicus ecotypes Gifu B-129 and Miyakojima MG-20: transcriptomic profiling and physiological characterization. PLoS ONE, 9(5):e97106.

[4]Benjamini, Y., Hochberg, Y., 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B, 57(1):289-300.

[5]Bi, Y.H., Wu, Y.Y., Zhou, Z.G., 2014. Genetic diversity of wild population of Pyropia haitanensis based on SSR analysis. Biochem. Syst. Ecol., 54:307-312.

[6]Chagné, D., Chaumeil, P., Ramboer, A., et al., 2004. Cross-species transferability and mapping of genomic and cDNA SSRs in pines. Theor. Appl. Genet., 109(6):1204-1214.

[7]Chang, S., Puryear, J., Cairney, J., 1993. A simple and efficient method for isolating RNA from pine trees. Plant Mol. Biol. Rep., 11(2):113-116.

[8]Chen, J.H., Xia, X.L., Yin, W.L., 2009. Expression profiling and functional characterization of a DREB2-type gene from Populuse uphratica. Biochem. Biophys. Res. Commun., 378(3):483-487.

[9]Chen, J.H., Tian, Q.Q., Pang, T., et al., 2014. Deep-sequencing transcriptome analysis of low temperature perception in a desert tree, Populuse uphratica. BMC Genomics, 15:326.

[10]Conesa, A., Gotz, S., Garcia-Gomez, J.M., et al., 2005. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics, 21(18):3674-3676.

[11]Diao, Q.N., Song, Y.J., Shi, D.M., et al., 2016. Nitric oxide induced by polyamines involves antioxidant systems against chilling stress in tomato (Lycopersicon esculentum Mill.) seedling. J. Zhejiang Univ.-Sci. B (Biomed. & Biotechnol.), 17(12):916-930.

[12]Doyle, J., Doyle, J.L., 1987. Genomic plant DNA preparation from fresh tissue-CTAB method. Phytochem. Bull., 19(11):11-15.

[13]Ge, Y., Li, Y., Zhu, Y.M., et al., 2010. Global transcriptome profiling of wild soybean (Glycine soja) roots under NaHCO3 treatment. BMC Plant Biol., 10:153.

[14]Grabherr, M.G., Haas, B.J., Yassour, M., et al., 2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol., 29(7):644-652.

[15]Grace, S.C., Logan, B.A., 2000. Energy dissipation and radical scavenging by the plant phenylpropanoid pathway. Philos. Trans. R. Soc. B., 355(1402):1499-1510.

[16]Guo, Y.Y., Yu, H.Y., Kong, D.S., et al., 2016. Effects of drought stress on growth and chlorophyll fluorescence of Lycium ruthenicum Murr. seedlings. Photosynthetica, 54(4):524-531.

[17]Hong, Z., Lakkineni, K., Zhang, Z., et al., 2000. Removal of feedback inhibition of Δ1-pyrroline-5-carboxylate synthetase results in increased proline accumulation and protection of plants from osmotic stress. Plant Physiol., 122(4):1129-1136.

[18]Iseli, C., Jongeneel, C.V., Bucher, P., 1999. ESTScan a program for detecting, evaluating, and reconstructing potential coding regions in EST sequences. ISMB, 99:138-148.

[19]Jin, H., Plaha, P., Park, J.Y., et al., 2006. Comparative EST profiles of leaf and root of leymuschinensis, a xerophilous grass adapted to high pH sodic soil. Plant Sci., 170(6):1081-1086.

[20]Knapp, S., Bohs, L., Nee, M., et al., 2004. Solanaceae a model for linking genomics with biodiversity. Comp. Funct. Genom., 5(3):285-291.

[21]Liu, T., Zhu, S., Tang, Q., et al., 2013. De novo assembly and characterization of transcriptome using Illumina paired-end sequencing and identification of CesA gene in ramie (Boehmeria nivea L. Gaud). BMC Genomics, 14:125.

[22]Liu, Y.D., Zhang, G.W., Liu, D.L., 2014. Simultaneous measurement of chlorophyll and water content in navel orange leaves based on hyperspectral imaging. Spectroscopy, 29(4):40-44.

[23]Liu, Y.L., Zeng, S.H., Sun, W., et al., 2014. Comparative analysis of carotenoid accumulation in two goji (Lycium barbarum L. and L. ruthenicum Murr.) fruits. BMC Plant Biol., 14:269.

[24]Liu, Z.G., Shu, Q.Y., Wang, L., et al., 2012. Genetic diversity of the endangered and medically important Lycium ruthenicum Murr. revealed by sequence-related amplified polymorphism (SRAP) markers. Biochem. Syst. Ecol., 45:86-97.

[25]Luo, J., Huang, C., Peng, F., et al., 2017. Effect of salt stress on photosynthesis and related physiological characteristics of Lycium ruthenicum Murr. Acta Agric. Scand. B, 67(8):1-13.

[26]Mortazavi, A., Williams, B.A., McCue, K., et al., 2008. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods, 5(7):621-628.

[27]Nei, M., 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89(3):583-590.

[28]Peng, Q., Liu, H., Lei, H., et al., 2016. Relationship between structure and immunological activity of an arabinogalactan from Lyceum ruthenicum. Food Chem., 194:595-600.

[29]Pertea, G., Huang, X.Q., Liang, F., et al., 2003. TIGR gene indices clustering tools (TGICL):a software system for fast clustering of large EST datasets. Bioinformatics, 19(5):651-652.

[30]Petrussa, E., Braidot, E., Zancani, M., et al., 2013. Plant flavonoids—biosynthesis, transport and involvement in stress responses. Int. J. Mol. Sci., 14(7):14950-14973.

[31]Polle, A., Otter, T., Seifert, F., 1994. Apoplastic peroxidases and lignification in needles of norway spruce (Piceaabies L.). Plant Physiol., 106(1):53-60.

[32]Qiu, Y., Li, X., Zhi, H., et al., 2009. Differential expression of salt tolerance related genes in Brassica campestris L. ssp. chinensis (L.) Makino var. communis Tsen et Lee. J. Zhejiang Univ.-Sci. B (Biomed. & Biotechnol.), 10(11):847-851.

[33]Rohlf, F.J., 2000. NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.1. Exeter Software, Setauket, New York, USA.

[34]Rozen, S., Skaletsky, H.J., 2000. Primer3 on the WWW for general users and for biologist programmers. In: Misener, S., Krawetz, S.A. (Eds.), Bioinformatics Methods and Protocols. Methods in Molecular Biology™, Vol. 132. Humana Press, Totowa, NJ, p.365-386.

[35]Rumeu, B., Sosa, P.A., Nogales, M., et al., 2013. Development and characterization of 13 SSR markers for an endangered insular juniper (Juniperus cedrus Webb & Berth.). Conserv. Genet. Resour., 5(2):457-459.

[36]Sato, S., Tabata, S., Hirakawa, H., et al., 2012. The tomato genome sequence provides insights into fleshy fruit evolution. Nature, 485(7400):635-641.

[37]Shi, D.C., Sheng, Y.M., 2005. Effect of various salt-alkaline mixed stress conditions on sunflower seedlings and analysis of their stress factors. Environ. Exp. Bot., 54(1):8-21.

[38]Spychalla, J.P., Desborough, S.L., 1990. Superoxide dismutase, catalase, and α-tocopherol content of stored potato tubers. Plant physiol., 94(3):1214-1218.

[39]Tang, J., Yan, Y., Ran, L., et al., 2017. Isolation, antioxidant property and protective effect on PC12 cell of the main anthocyanin in fruit of Lycium ruthenicum Murray. J. Funct. Foods, 30:97-107.

[40]Wang, J., Li, B., Meng, Y., et al., 2015. Transcriptomic profiling of the salt-stress response in the halophyte Halogeton glomeratus. BMC Genomics, 16:169.

[41]Wang, L., Li, J., Zhao, J., et al., 2015. Evolutionary developmental genetics of fruit morphological variation within the Solanaceae. Front. Plant Sci., 6:248.

[42]Wang, Y.C., Chu, Y.G., Liu, G.F., et al., 2007. Identification of expressed sequence tags in an alkali grass (Puccinellia tenuiflora) cDNA library. J. Plant Physiol., 164(1):78-89.

[43]Wang, Z., Fang, B., Chen, J., et al., 2010. De novo assembly and characterization of root transcriptome using Illumina paired-end sequencing and development of cSSR markers in sweet potato (Ipomoea batatas). BMC Genomics, 11: 726.

[44]Wei, L., Li, S., Liu, S., et al., 2014. Transcriptome analysis of Houttuynia cordata Thunb. by Illumina paired-end RNA sequencing and SSR marker discovery. PLoS ONE, 9(1):e84105.

[45]Wheeler, D.L., Church, D.M., Lash, A.E., et al., 2002. Database resources of the National Center for Biotechnology Information: 2002 update. Nucleic Acids Res., 30(1):13-16.

[46]Xu, X., Pan, S.K., Cheng, S.F., et al., 2011. Genome sequence and analysis of the tuber crop potato. Nature, 475(7355):189-195.

[47]Ye, J., Fang, L., Zheng, H.K., et al., 2006. WEGO a web tool for plotting GO annotations. Nucleic Acids Res., 34(Suppl. 2):W293-W297.

[48]Yeh, F.C., Yang, R.C., Boyle, T., 1999. POPGENE Version 1.31. Microsoft Window-Based Freeware for Population Genetic Analysis. University of Alberta and the Centre for International Forestry Research, CA.

[49]Zheng, J., Ding, C.X., Wang, L.S., et al., 2011. Anthocyanins composition and antioxidant activity of wild Lycium ruthenicum Murr. from Qinghai-Tibet Plateau. Food Chem., 126(3):859-865.

[50]Zhu, J.K., 2001. Cell signaling under salt, water and cold stresses. Curr. Opin. Plant Biol., 4(5):401-406.

[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

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2022 Journal of Zhejiang University-SCIENCE