De novo transcriptome characterization and gene expression profiling of the desiccation tolerant moss Bryum argenteum following rehydration

BMC Genomics

Andrew J. Wood²  Yuanming Zhang¹  Honglan Yang¹  Xiaoshuang Li¹  Daoyuan Zhang¹  Bei Gao³ 

[1] Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;Department of Plant Biology, Southern Illinois University-Carbondale, Carbondale 62901-6509, IL, USA;University of Chinese Academy of Sciences, Beijing 100049, China

关键词: Biological soil crust;    Physcomitrella;    Bryum;    Desiccation;    Gene expression;    Transcriptome;   

Others  :  1208963
DOI  :  10.1186/s12864-015-1633-y

 received in 2015-01-21, accepted in 2015-05-18,  发布年份 2015

【 摘 要 】

Background

The desiccation-tolerant moss Bryum argenteum is an important component of the Biological Soil Crusts (BSCs) found in the Gurbantunggut desert. Desiccation tolerance is defined as the ability to revive from the air dried state. To elucidate the molecular mechanisms related to desiccation tolerance, we employed RNA-Seq and digital gene expression (DGE) technologies to study the genome-wide expression profiles of the dehydration and rehydration processes in this important desert plant.

Results

We applied a two-step approach to investigate the gene expression profile upon rehydration in the moss Bryum argenteum using Illumina HiSeq2000 sequencing platform. First, a total of 57,247 transcript assembly contigs (TACs) were obtained from 54.79 million reads by de novo assembly, with an average length of 863 bp and N50 of 1,372 bp. Among the reconstructed TACs, 36,916 (64.5 %) revealed similarity with existing protein sequences in the public databases. 23,509 and 21,607 TACs were assigned GO and KEGG annotation information, respectively. Second, samples were taken from 3 hydration stages: desiccated (Dry), rehydrated 2 h (R2) and rehydrated 24 h (R24), and DEG libraries were constructed for Differentially Expressed Genes (DEGs) discovery. 4,081 and 6,709 DEGs were identified in R2 and R24, compared with Dry, respectively. Compared to the desiccated sample, up-regulated genes after two hours of hydration are primarily related to stress responses. GO function enrichment network, EKGG metabolic pathway and MapMan analysis supports the idea of the rapid recovery of photosynthesis after 24 h of rehydration. We identified 770 transcription factors (TFs) which were classified into 50 TF families. 142 TF transcripts were up-regulated upon rehydration including 23 members of the ERF family.

Conclusions

In this study, we constructed a pioneering, high-quality reference transcriptome in B. argenteum and generated three DGE libraries to elucidate the changes of gene expression upon rehydration. Expression profiles consistent with the rapid recovery of photosynthesis (at R2) and the re-establishment of a positive carbon balance following rehydration (at R24) were observed. Our study will extend our knowledge of bryophyte transcriptomes and provide further insight into the molecular mechanisms related to rehydration and desiccation-tolerance.

【 授权许可】

   
2015 Gao et al.; licensee BioMed Central.

【 图 表 】

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【 参考文献 】

• [1]Bewley JD. Physiological Aspects of Desiccation Tolerance. Annu Rev Plant Physiol. 1979; 30(1):195-238.
• [2]Wood AJ, Jenks MA: Plant desiccation tolerance: diversity, distribution, and real-world application. In: Plant Desiccation Tolerance. Blackwell Publishing Ltd; 2007:3–10.
• [3]Gaff DF, Oliver M. The evolution of desiccation tolerance in angiosperm plants: a rare yet common phenomenon. Funct Plant Biol. 2013; 40(4):315-328.
• [4]Oliver M, Tuba Z, Mishler B. The evolution of vegetative desiccation tolerance in land plants. Plant Ecol. 2000; 151(1):85-100.
• [5]Wood AJ. The nature and distribution of vegetative desiccation-tolerance in hornworts, liverworts and mosses. Bryologist. 2007; 110(2):163-177.
• [6]Belnap J. The world at your feet: desert biological soil crusts. Front Ecol Environ. 2003; 1(4):181-189.
• [7]Zhang YM, Chen J, Wang L, Wang XQ, Gu ZH. The spatial distribution patterns of biological soil crusts in the Gurbantunggut Desert, Northern Xinjiang, China. J Arid Environ. 2007; 68(4):599-610.
• [8]Li XR, Xiao HL, Zhang JG, Wang XP. Long-Term Ecosystem Effects of Sand-Binding Vegetation in the Tengger Desert. Northern China Restoration Ecology. 2004; 12(3):376-390.
• [9]Li XR, He M-Z, Zerbe S, Li X-J, Liu L-C. Micro-geomorphology determines community structure of biological soil crusts at small scales. Earth Surf Process Landf. 2010; 35(8):932-940.
• [10]Zheng Y, Xu M, Zhao J, Zhang B, Bei S, Hao L. Morphological Adaptations to Drought and Reproductive Strategy of the Moss Syntrichia caninervis in the Gurbantunggut Desert, China. Arid Land Research and Management. 2011; 25(2):116-127.
• [11]Li J, Li X, Chen C. Degradation and reorganization of thylakoid protein complexes of Bryum argenteum in response to dehydration and rehydration. Bryologist. 2014; 117(2):110-118.
• [12]Proctor MCF, Smirnoff N. Rapid recovery of photosystems on rewetting desiccation-tolerant mosses: chlorophyll fluorescence and inhibitor experiments. J Exp Bot. 2000; 51(351):1695-1704.
• [13]Nabe H, Funabiki R, Kashino Y, Koike H, Satoh K. Responses to Desiccation Stress in Bryophytes and an Important Role of Dithiothreitol-Insensitive Non-Photochemical Quenching Against Photoinhibition in Dehydrated States. Plant Cell Physiol. 2007; 48(11):1548-1557.
• [14]Rensing SA, Lang D, Zimmer AD, Terry A, Salamov A, Shapiro H et al.. The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants. Science. 2008; 319(5859):64-69.
• [15]Zimmer A, Lang D, Buchta K, Rombauts S, Nishiyama T, Hasebe M et al.. Reannotation and extended community resources for the genome of the non-seed plant Physcomitrella patens provide insights into the evolution of plant gene structures and functions. BMC Genomics. 2013; 14(1):498. BioMed Central Full Text
• [16]O'Neil S, Dzurisin J, Carmichael R, Lobo N, Emrich S, Hellmann J. Population-level transcriptome sequencing of nonmodel organisms Erynnis propertius and Papilio zelicaon. BMC Genomics. 2010; 11(1):310. BioMed Central Full Text
• [17]Szovenyi P, Perroud PF, Symeonidi A, Stevenson S, Quatrano RS, Rensing SA et al.. De novo assembly and comparative analysis of the Ceratodon purpureus transcriptome. Mol Ecol Resour. 2015; 15(1):203-215.
• [18]Gao B, Zhang D, Li X, Yang H, Wood A. De novo assembly and characterization of the transcriptome in the desiccation-tolerant moss Syntrichia caninervis. BMC Research Notes. 2014; 7(1):490. BioMed Central Full Text
• [19]Wang L, Park HJ, Dasari S, Wang S, Kocher JP, Li W. CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model. Nucleic Acids Research 2013;41(6):e74.
• [20]Ferreira P, Patalano S, Chauhan R, Ffrench-Constant R, Gabaldon T, Guigo R et al.. Transcriptome analyses of primitively eusocial wasps reveal novel insights into the evolution of sociality and the origin of alternative phenotypes. Genome Biol. 2013; 14(2):R20. BioMed Central Full Text
• [21]Derrien T, Johnson R, Bussotti G, Tanzer A, Djebali S, Tilgner H et al.. The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome Res. 2012; 22(9):1775-1789.
• [22]Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012; 40(Database issue):D109-114.
• [23]Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR et al.. Pfam: the protein families database. Nucleic Acids Res. 2014; 42(Database issue):D222-230.
• [24]Jin J, Zhang H, Kong L, Gao G, Luo J. PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors. Nucleic Acids Res. 2014; 42(D1):D1182-D1187.
• [25]Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Meth. 2008; 5(7):621-628.
• [26]Audic S, Claverie J-M. The Significance of Digital Gene Expression Profiles. Genome Res. 1997; 7(10):986-995.
• [27]Konishi M, Yanagisawa S. Arabidopsis NIN-like transcription factors have a central role in nitrate signalling. Nat Commun. 2013; 4:1617.
• [28]Nakano T, Suzuki K, Fujimura T, Shinshi H. Genome-wide analysis of the ERF gene family in Arabidopsis and rice. Plant Physiol. 2006; 140(2):411-432.
• [29]Hirsch S, Kim J, Munoz A, Heckmann AB, Downie JA, Oldroyd GE. GRAS proteins form a DNA binding complex to induce gene expression during nodulation signaling in Medicago truncatula. Plant Cell. 2009; 21(2):545-557.
• [30]Hirsch S, Oldroyd GE. GRAS-domain transcription factors that regulate plant development. Plant Sigsnal Behav. 2009; 4(8):698-700.
• [31]Oliver M, Dowd S, Zaragoza J, Mauget S, Payton P. The rehydration transcriptome of the desiccation-tolerant bryophyte Tortula ruralis: transcript classification and analysis. BMC Genomics. 2004; 5(1):89. BioMed Central Full Text
• [32]Wood AJ, Duff RJ, Oliver MJ. Expressed sequence tags (ESTs) from desiccated Tortula ruralis identify a large number of novel plant genes. Plant Cell Physiol. 1999; 40(4):361-368.
• [33]Oliver MJ, Wood AJ, O'Mahony P. How some plants recover from vegetative desiccation: A repair based strategy. Acta Physiol Plant. 1997; 19(4):419-425.
• [34]Velten J, Oliver MJ. Tr288, a rehydrin with a dehydrin twist. Plant Mol Biol. 2001; 45(6):713-722.
• [35]Zeng Q, Chen X, Wood AJ. Two early light-inducible protein (ELIP) cDNAs from the resurrection plant Tortula ruralis are differentially expressed in response to desiccation, rehydration, salinity, and high light. J Exp Bot. 2002; 53(371):1197-1205.
• [36]Chen X, Zeng Q, Wood AJ. Aldh7B6 Encodes a Turgor-Responsive Aldehyde Dehydrogenase Homologue That is Constitutively Expressed in Tortula ruralis Gametophytes. Bryologist. 2002; 105(2):177-184.
• [37]Chen X. Zeng Qin, Wood AJ: The stress-responsive Tortula ruralis gene ALDH21A1 describes a novel eukaryotic aldehyde dehydrogenase protein family. J Plant Physiol. 2002; 159(7):677-684.
• [38]Peng CA, Oliver MJ, Wood AJ. Is the Rehydrin TrDr3 from Tortula ruralis associated with tolerance to cold, salinity, and reduced pH? Physiological evaluation of the TrDr3-orthologue, HdeD from Escherichia coli in response to abiotic stress. Plant Biol (Stuttg). 2005; 7(3):315-320.
• [39]Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological Networks. Bioinformatics. 2005; 21(16):3448-3449.
• [40]Consortium GO. The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res. 2004; 32(suppl 1):D258-D261.
• [41]Scott HB, Oliver MJ. Accumulation and polysomal recruitment of transcripts in response to desiccation and rehydration of the moss Tortula ruralis. J Exp Bot. 1994; 45(5):577-583.
• [42]Wood AJ, Oliver MJ. Translational control in plant stress: the formation of messenger ribonucleoprotein particles (mRNPs) in response to desiccation of Tortula ruralis gametophytes. Plant J. 1999; 18(4):359-370.
• [43]Li XP, Bjorkman O, Shih C, Grossman AR, Rosenquist M, Jansson S et al.. A pigment-binding protein essential for regulation of photosynthetic light harvesting. Nature. 2000; 403(6768):391-395.
• [44]Alboresi A, Caffarri S, Nogue F, Bassi R, Morosinotto T. In Silico and Biochemical Analysis of Physcomitrella patens Photosynthetic Antenna: Identification of Subunits which Evolved upon Land Adaptation. PLoS One. 2008; 3(4):e2033.
• [45]Zhao Z, Tan L, Dang C, Zhang H, Wu Q, An L. Deep-sequencing transcriptome analysis of chilling tolerance mechanisms of a subnival alpine plant, Chorispora bungeana. BMC Plant Biol. 2012; 12(1):222. BioMed Central Full Text
• [46]Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I et al.. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotech. 2011; 29(7):644-652.
• [47]Pertea G, Huang X, Liang F, Antonescu V, Sultana R, Karamycheva S et al.. TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics. 2003; 19(5):651-652.
• [48]Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005; 21(18):3674-3676.
• [49]Ye J, Fang L, Zheng H, Zhang Y, Chen J, Zhang Z et al.. WEGO: a web tool for plotting GO annotations. Nucleic Acids Res. 2006; 34:W293-297.
• [50]Eddy SR. A new generation of homology search tools based on probabilistic inference. Genome informatics International Conference on Genome Informatics. 2009; 23(1):205-211.
• [51]Eddy SR. Accelerated Profile HMM Searches. PLoS Comput Biol. 2011; 7(10):e1002195.
• [52]Li R, Yu C, Li Y, Lam T-W, Yiu S-M, Kristiansen K et al.. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics. 2009; 25(15):1966-1967.
• [53]Benjamini Y, Yekutieli D . The control of the false discovery rate in multiple testing under dependency. Annals of statistics 2001;29(4):1165–1188.
• [54]Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics. 2011; 27(3):431-432.
• [55]Thimm O, Bläsing O, Gibon Y, Nagel A, Meyer S, Krüger P et al.. MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J. 2004; 37(6):914-939.
• [56]Usadel B, Nagel A, Thimm O, Redestig H, Blaesing OE, Palacios-Rojas N et al.. Extension of the visualization tool MapMan to allow statistical analysis of arrays, display of corresponding genes, and comparison with known responses. Plant Physiol. 2005; 138(3):1195-1204.
• [57]Lohse M, Nagel A, Herter T, May P, Schroda M, Zrenner R et al.. Mercator: a fast and simple web server for genome scale functional annotation of plant sequence data. Plant, Cell Environ. 2014; 37(5):1250-1258.
• [58]Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods. 2001; 25(4):402-408.