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Building an mRNA transcriptome from the shoots of Betula platyphylla by using Solexa technology

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Abstract

All plant shoot tips contain apical meristems, an area that differentiates into multiple cell and tissue types and is critical to the development of the above ground plant body. To study the development of birch (Betula platyphylla Suk.), we constructed a transcriptome from the young shoot tips of birch by using the Solexa method. In total, 40,780 tentative unique genes (TUGs) were generated. Among these, 29,939 genes showed significant (>1E5) sequence similarity with proteins in the NR-database. Gene ontology (GO) classification suggested that 6,945 TUGs were categorized as involved in biological processes, 10,639 TUGs were grouped into encoding cellular components, and 6,159 TUGs were assigned to roles involving molecular function group. Our results showed that the GO subgroup of genes involved in binding and those involved in metabolic processes are most abundant in terms of molecular functions and biological processes, respectively. Furthermore, the most abundant genes in the transcriptome are β-N-acetylhexosaminidase, ribosomal protein L44, thioredoxin H, light-harvesting complex I protein, S-adenosylmethionine decarboxylase, NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, and tonoplast proton pump. The expression profiles of some abundant genes were studied during a 1-year growth period using real-time RT-PCR. The results showed that their expression altered significantly during the growth stages, suggesting that they play active roles in shoot development.

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Abbreviations

AS:

Asparagine synthetase

β-NAHA:

β-N-acetylhexosaminidase

CAB:

Chlorophyll a/b-binding proteins

GAPDH:

Glyceraldehyde-3-phosphate dehydrogenase

GO:

Gene ontology

PRPs:

Proline-rich proteins

RPKM:

Reads per kb per million reads

SAMDC:

S-adenosylmethionine decarboxylase

SuSy:

Sucrose synthase

TUGs:

Tentative unique genes

References

  • Baroja-Fernández E, Muñoz FJ, Montero M, Etxeberria E, Sesma MT, Ovecka M et al (2009) Enhancing sucrose synthase activity in transgenic potato (Solanum tuberosum L.) tubers results in increased levels of starch, ADPglucose and UDPglucose and total yield. Plant Cell Physiol 50:1651–1662

    Article  PubMed  Google Scholar 

  • Cazalis R, Pulido P, Aussenac T, Pérez-Ruiz JM, Cejudo FJ (2006) Cloning and characterization of three thioredoxin h isoforms from wheat showing differential expression in seeds. J Exp Bot 57:2165–2172

    Article  PubMed  CAS  Google Scholar 

  • Chen L, Zhao LP, Gao QK (2005) Generation and analysis of expressed sequence tags from the tender shoots cDNA library of tea plant (Camellia sinensis). Plant Sci 168:359–363

    Article  CAS  Google Scholar 

  • Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676

    Article  PubMed  CAS  Google Scholar 

  • Cuddapah S, Barski A, Cui K, Schones DE, Wang Z, Wei G et al (2009) Native chromatin preparation and Illumina/Solexa library construction. Cold Spring Harb Protoc. doi:10.1101/pdb.prot5237

  • Heather DC, Yan J, Mansfield SD (2009) Sucrose synthase affects carbon partitioning to increase cellulose production and altered cell wall ultrastructure. Proc Natl Acad Sci USA 106:13118–13123

    Article  Google Scholar 

  • Hegedus Z, Zakrzewska A, Agoston VC, Ordas A, Rácz P, Mink M et al (2009) Deep sequencing of the zebrafish transcriptome response to mycobacterium infection. Mol Immunol 46:2918–2930

    Article  PubMed  CAS  Google Scholar 

  • Ihalainen JA, Croce R, Morosinotto T, van Stokkum IH, Bassi R, Dekker JP et al (2005) Excitation decay pathways of Lhca proteins: a time-resolved fluorescence study. J Phys Chem B 109:21150–21158

    Article  PubMed  CAS  Google Scholar 

  • Irizarry RA, Warren D, Spencer F, Kim IF, Biswal S, Frank BC et al (2005) Multiple laboratory comparison of microarray platforms. Nat Methods 2:345–350

    Article  PubMed  CAS  Google Scholar 

  • Karsi A, Cao D, Li P, Patterson A, Kocabas A, Feng J et al (2002) Transcriptome analysis of channel catfish (Ictalurus punctatus): initial analysis of gene expression and microsatellite-containing cDNAs in the skin. Gene 285:157–168

    Article  PubMed  CAS  Google Scholar 

  • Koning AJ, Rose R, Comai L (1992) Developmental expression of tomato heat-shock cognate protein 80. Plant Physiol 100:801–811

    Article  PubMed  CAS  Google Scholar 

  • Li R, Li Y, Zheng H, Luo R, Zhu H, Li Q et al (2009) Building the sequence map of the human pan-genome. Nat Biotech 28:57–63

    Article  Google Scholar 

  • Libault M, Farmer A, Joshi T, Takahashi K, Langley RJ, Franklin LD et al (2010) An integrated transcriptome atlas of the crop model Glycine max, and its use in comparative analyses in plants. Plant J 63:86–99

    PubMed  CAS  Google Scholar 

  • Marx C, Wong JH, Buchanan BB (2003) Thioredoxin and germinating barley: targets and protein redox changes. Planta 216:454–460

    PubMed  CAS  Google Scholar 

  • Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628

    Article  PubMed  CAS  Google Scholar 

  • Pedotti P, ‘t Hoen PA, Vreugdenhil E, Schenk GJ, Vossen RH, Ariyurek Y et al (2008) Can subtle changes in gene expression be consistently detected with different microarray platforms? BMC Genomics 9:124

    Article  PubMed  Google Scholar 

  • Pegg AE (2009) S-Adenosylmethionine decarboxylase. Essays Biochem 46:25–45

    Article  PubMed  CAS  Google Scholar 

  • Pertea G, Huang X, Liang F, Antonescu V, Sultana R, Karamycheva S, Lee Y, White J, Cheung F, Parvizi B, Tsai J, Quackenbush J (2003) TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics 19:651–652

    Article  PubMed  CAS  Google Scholar 

  • Qin L, Smant G, Stokkermans J, Bakker J, Schots A, Helder J (1998) Cloning of a trans-spliced glyceraldehyde-3-phosphate-dehydrogenase gene from the potato cyst nematode Globodera rostochiensis and expression of its putative promoter region in Caenorhabditis elegans. Mol Biochem Parasitol 96:59–67

    Article  PubMed  CAS  Google Scholar 

  • Schürmann P, Jacquot JP (2000) Plant thioredoxin systems revisited. Annu Rev Plant Physiol Plant Mol Biol 51:371–400

    Article  PubMed  Google Scholar 

  • Serrato AJ, Cejudo FJ (2003) Type-h thioredoxins accumulate in the nucleus of developing wheat seed tissues suffering oxidative stress. Planta 217:392–399

    Article  PubMed  CAS  Google Scholar 

  • Shan X, Wang J, Chua L, Jiang D, Peng W, Xie D (2011) The role of Arabidopsis Rubisco activase in jasmonate-induced leaf senescence. Plant Physiol 155:751–764

    Article  PubMed  CAS  Google Scholar 

  • Sirover MA (1997) Role of the glycolytic protein, glyceraldehyde-3-phosphate dehydrogenase, in normal cell function and in cell pathology. J Cell Biol 66:133–140

    CAS  Google Scholar 

  • Sulieman S, Fischinger SA, Gresshoff PM, Schulze J (2010) Asparagine as a major factor in the N-feedback regulation of N fixation in Medicago truncatula. Physiol Plant 140:21–31

    Article  PubMed  CAS  Google Scholar 

  • Wada M, Shirahata A (2010) Identification of the primary structure and post-translational modification of rat S-adenosylmethionine decarboxylase. Biol Pharm Bull 33:891–894

    Article  PubMed  CAS  Google Scholar 

  • Wall PK, Leebens-Mack J, Chanderbali AS, Barakat A, Wolcott E, Liang H et al (2009) Comparison of next generation sequencing technologies for transcriptome characterization. BMC Genomics 1(10)

  • Wang W, Vinocur B, Shoseyov O, Altman A (2004) Role of plant-heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci 9:244–252

    Article  PubMed  CAS  Google Scholar 

  • Wilhelm BT, Landry JR (2009) RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing. Methods 48:249–257

    Article  PubMed  CAS  Google Scholar 

  • Wong CE, Prem LB, Harald O, Mohan BS (2008) Transcriptional profiling of the pea shoot apical meristem reveals processes underlying its function and maintenance. BMC Plant Bio 8:73

    Article  Google Scholar 

  • Wu T, Qin Z, Zhou X, Feng Z, Du Y (2010) Transcriptome profile analysis of floral sex determination in cucumber. J Plant Physiol 167:905–913

    Article  PubMed  CAS  Google Scholar 

  • Wyatt RE, Nagao RT, Key JL (1992) Patterns of soybean proline-rich protein gene expression. Plant Cell 4:99–110

    PubMed  CAS  Google Scholar 

  • Yano H, Wong JH, Cho MJ, Buchanan BB (2001) A strategy for the identification of proteins targeted by thioredoxin. Proc Natl Acad Sci USA 98:4794–4799

    Article  PubMed  CAS  Google Scholar 

  • Ye J, Fang L, Zheng H, Zhang Y, Chen J, Zhang Z, Wang J, Li S, Li R, Bolund L, Wang J. (2006) WEGO: a web tool for plotting GO annotations. Nucleic Acids Res 34 Web Server: W293-297

  • Zhou X, Su Z, Sammons RD, Peng Y, Tranel PJ, Stewart CN Jr et al (2009) Novel software package for cross-platform transcriptome analysis (CPTRA). BMC Bioinforma 10(Suppl 11):S16

    Article  Google Scholar 

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Acknowledgments

This work was supported by grants from Special Research Funds for Public Welfare Forestry (No. 200904039), Fundamental Research Funds for the Central Universities (DL09DA01), Specialized Research Fund for the Doctoral Program of Higher Education (20100062120001), and the National Natural Science Foundation of China (30972385).

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Authors and Affiliations

  1. State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, 26 Hexing Road, 150040, Harbin, China

    Yucheng Wang, Caiqiu Gao, Lei Zheng, Guifeng Liu, Jing Jiang & Chuanping Yang

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  1. Yucheng Wang
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  2. Caiqiu Gao
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  3. Lei Zheng
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  4. Guifeng Liu
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  5. Jing Jiang
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  6. Chuanping Yang
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Corresponding author

Correspondence to Chuanping Yang.

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Communicated by J. Wegrzyn

Yucheng Wang and Caiqiu Gao have the same contribution to this paper.

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Wang, Y., Gao, C., Zheng, L. et al. Building an mRNA transcriptome from the shoots of Betula platyphylla by using Solexa technology. Tree Genetics & Genomes 8, 1031–1040 (2012). https://doi.org/10.1007/s11295-012-0483-x

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  • DOI: https://doi.org/10.1007/s11295-012-0483-x

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