combustion, the use of chlorofluorocarbons, and deforestation are one of the main factors responsible for increasing CO₂ concentration and for an increase of air temperature. In addition global changes will affect precipitation patterns, nitrogen concentration in the atmosphere and enhanced UV-B radiation. Forest trees constitute a relevant economic and ecological resource that is under severe pressure by such environmental changes.

However, the response of forest trees and in particular of the important forest tree species *Fagus sylvatica* to elevated CO₂ levels on a gene expression basis is unknown so far. The principal aim of this study is the investigation of two different genotypes of *Fagus sylvatica* upon increased CO₂ by microarray and gene expression analyses.

**Materials and methods:** Shoots of *F. sylvatica* (Germany) and *F. sylvatica* "purpurea tree" (Germany) were grafted on *F. sylvatica* rootstocks. Plants were kept for 10 days under controlled conditions in climate chambers using the same temperature and light parameters, whereas the CO₂ concentration was approx. 380-400 ppm (ambient) in the control chamber and 1000 ppm (high) in the CO₂ chamber. Five leaves were taken from arbitrary chosen plants in control and high CO₂ chamber at 2 different time points (T2=2 days and T10=10 days) with 3 biological replicates per each genotype per each sampling time point. The leaves were immediately frozen in liquid nitrogen and stored at -80°C. Extraction of total RNA was according to Kiefer *et al* [1] and microarray analyses were carried out as described by Olbrich *et al* [2]. Real Time PCR (RT-PCR) [3,4] analyses were carried out for selected genes to evaluate changes in gene expression.

**Results:** The microarray resulted in differentially expressed gene at T2 and T10 in each beech genotype analyzed. In particular, genes involved in photosynthesis and chloroplast biogenesis were up regulated at T2. A similar trend was been for genes involved in sugar metabolism. This indicates that, at high CO₂ concentration, the activity of the photosynthesis machinery will be accelerated and, therefore, also the one of the glycolysis pathway which brings to an accumulation of carbon. After 10 days of high CO₂ level, few of these genes were down regulated but most of them are expressed at normal level. This effect has previously been described in most of the studies on pot-grown other C3 plants under elevated CO₂ which have indicated photosynthetic acclimation [5]. This response was particularly evident for the *F. sylvatica* "purpurea tree" showing a different behaviour to the second beech genotype.

RT-PCR for genes involved in photosynthesis, chloroplast biogenesis and sugar metabolism are in progress for both genotypes.

**Conclusions:** A lot of studies have reported contradictory responses of higher C3 plants to elevated levels of CO₂. This observation has also been made in the two German beech genotypes analyzed in this work confirming high expression variability between different genotypes of the same plant species. Therefore, considering the importance to preserve the forest ecosystems under global climate change, further investigations are necessary to understand the regulatory events associated with the adaptive acclimation responses of trees.

A lot of studies have reported contradictory responses of higher C3 plants to elevated levels of CO₂. This observation has also been made in the two German beech genotypes analyzed in this work confirming high expression variability between different genotypes of the same plant species. Therefore, considering the importance to preserve the forest ecosystems under global climate change, further investigations are necessary to understand the regulatory events associated with the adaptive acclimation responses of trees.

**References**

1. Kiefer E, Heller W, Ernst D: A simple and efficient protocol for isolation of functional RNA from plant tissues rich in secondary metabolites. *Plant Molecular Biology Reporter* 2000, 18:33-39.

2. Olbrich M, Gerstner E, Welzl G, Winkler JB, Ernst D: Transcript responses in leaves of ozone-treated beech saplings seasons at an outdoor free air model fumigation site over two growing seasons. *Plant and Soil* 2009, 323:61-74.

3. Pfaffl MW: A new mathematical model for relative quantification in real-time RT-PCR. *Nucleic Acids Res* 2001, 29(e):e45.

4. Pfaffl MW, Horgan GW, Dempfle L: Relative expression software tool (REST®) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. *Nucleic Acids Res* 2002, 30(e):e36.

5. Reddy AR, Rasineni GK, Raghavendra AS: The impact of global elevated CO₂ concentration on photosynthesis and plant productivity. *Current Science* 2010, 99:46-57.

P172

Deciphering cork formation in *Quercus suber*

Jorge AP Paiva¹*, Pedro Fevereiro², Pedro Marques³,
José Carlos Rodrigues⁴, Grégoire Le Provost⁵, Christophe Plomion⁵,
Jacqueline Grima-Pettenati⁶, Olivier Bouchez², Christophe Klopp⁸,
Hélène Berges⁹, José Graça¹⁰

¹Instituto de Investigação Científica Tropical (IICT), FLOR-Centro de Florestas e dos Produtos Florestais, Tapada da Ajuda, 1349-018 Lisboa, Portugal & Instituto de Biologia Experimental e Tecnológica, Apartado 12, 2781-901 Oeiras, Portugal; ²Instituto de Biologia Experimental e Tecnológica, Apartado 12, 2781-901 Oeiras, Portugal; ³Fundação João Lopes Fernandes (FJLF), Herdade do Leitões 7425-014 Montargil, Portugal; ⁴Instituto de Investigação Científica Tropical (IICT), FLOR-Centro de Florestas e dos Produtos Florestais, Tapada da Ajuda, 1349-018 Lisboa, Portugal; ⁵INRA-UMR 1202 - BIOGECO - "BIodiversité, Gènes et Communautés" (INRA-UMR BIOGECO) Site de Recherches Forêt Bois de Pierroton, 69 route d'Arcachon, 33612CESTAS Cedex, France; ⁶UMR CNRS/Université Toulouse III 5546, Pôle de Biotechnologies Végétales, 24 chemin de Borde Rouge, BP42617 Auzeville, 31326 Castanet Tolosan, France; ⁷Plateforme Génomique, Génopole Toulouse/Midi-pyrénées, INRA Auzeville, Chemin de Borderouge-BP 52627, 31326 Castanet-Tolosan, France; ⁸INRA-Toulouse, BIA, 31326 Castanet-Tolosan, France; ⁹INRA-CNRGV, Chemin de Borde Rouge, 31326 Castanet-Tolosan, France; ¹⁰Instituto Superior de Agronomía (ISA/UTL) Tapada da Ajuda 1349-017 Lisboa, Portugal

E-mail: jorge@itqb.unl.pt

BMC Proceedings 2011, 5(Suppl 7):P172

The family of *Fagaceae*, comprises about 900 species, among them the best-known group of this family is the oaks, genus *Quercus*, that are commonly used as timber or for cork production. Cork is produced by *Q. suber*, an evergreen oak with major economic and environmental importance for Mediterranean region, in particular for Portugal that is the leading producer of this material.

Besides, the economic importance of cork production and cork manufacturing, little attention has been paid to the molecular mechanisms underlying wood and cork formation as well as cork quality. To overcome this constraint, an international partnership (SuberGene) was established 2008, involving Portuguese and French research institutions and one Producer's Association organization (FJLF). The main driving force of this partnership is to join efforts and complementary skills to unravel the molecular mechanisms underlying cork formation and decipher the structural polymorphisms and regulation network that determine cork quality.

A non-normalized cDNA library of developing phellon (DP) was produced and 5,000 clones were sequence both ends using Sanger technology. More than 6500 good quality ESTs were deposit at GeneBank. DP transcriptome was also assessed by pirosequencing (454FLX Titanium, Roche) generating more than 200,000 reads. Sequencing data (238,911 ESTs) data were assembled into 69,559 contigs. Suberin biosynthesis genes such as Glycerol-3-phosphate acyltransferase and Omega-hydroxypalmitate O-feruloyl transferase are among the more expressed genes in DP tissues. More than 2,800 putative SNPs were detected in 1,121 contigs. As a complementary strategy, the proteome of DP are being assessed, by 2D-PAGE, and mass spectroscopy. In order to get more information about the gene structure of genes related with the suberisation of cork cell-wall, one *Q. suber* BAC library have been constructed, and are being characterized. Clones harboring genes of interest were identified by screening high-density filters of this BAC library.

These resources provides us with valuable tools to study the nature of the molecular machinery involved in cork formation, and most importantly with the players involved in the variability of cork characteristics. Future ongoing approaches and the impact of these finding will be discussed.

**Acknowledgments:** The authors would like to thank the valuable contribution of actual and former members of the involved groups and institutions: Susana Araújo¹, Victor Carocha¹, Cláudio Capitão², Clara Graça², Joana Amado², Céline Lalanne⁵, Nathalie Ladouce⁶, Céline Noirot⁸, Elisa Prat⁹, Sonia Vautrin⁹, Joelle Fourment⁹.

This work was partially supported by FCT (Portugal) (PTDC/AGR-GPL/101785/2008). Authors also acknowledged FJLF that provided the plant material necessary for this work.
P173

Interspecific discovery and expression profiling of *Eucalyptus* micro RNAs by deep sequencing

Marilia Pappas¹*, Alessandra Reis², Laurent Farinell³, Giancarlo Pasqual⁴,
Georgios Pappas Jr⁵, Dario Grattapaglia¹

¹Embrapa Genetic Resources and Biotechnology, Brazil; ²Catholic University of Brasília, Brazil; ³Fsateris SA, Brazil; ⁴Federal University of Rio Grande do Sul, Brazil

E-mail: mariliac@cenargen.embrapa.br

BMC Proceedings 2011, 5(Suppl 7):P173

**Background:** Micro RNAs (miRNAs) are a class of small (~21 nucleotide) non-coding RNAs that recently gained much attention due to their perceived role as master regulators of gene expression in Eukaryotes, responsible for fine tuning gene expression regulation and, in plants, has been shown to be involved in a diverse range of biological processes such as plant development and architecture, flowering, cell differentiation and response to biotic and abiotic stresses [1]. The repertoire of expressed miRNAs differs among cell types, tissues, development, environmental condition, etc [2]. Notwithstanding, the exact function of thousands miRNAs sequences present in miRBase [http://www.mirbase.org/] is not elucidated. At this point, discovery and profiling of new and conserved miRNAs are critical in the attempt to understand their function and mechanism. Deep sequencing through next generation sequencing is the methodology of choice for this purpose as its ultra high throughput permits a comprehensive interrogation of the small RNA transcriptome, permitting *de novo* identification and relative quantification of different small RNA species [3].

Due to its economic importance the *Eucalyptus grandis* genome has been sequenced by JGI and the annotation of miRNAs is pivotal. In order to provide the first large scale experimental characterization of *Eucalyptus* miRNAs we performed an Illumina deep sequencing run that allowed us to discover and quantify the miRNA levels in two different tissues – xylem and leaves. Additionally, to get insights of the observed phenotypic differences in wood quality among *Eucalyptus* species, we characterized the xylem small RNA transcriptome of two different *E. globulus* individuals and integrated the results to catalog conserved and *Eucalyptus* specific miRNA gene families.

**Materials and methods:** Four biological samples were used: xylem from two *E. globulus* genotypes, xylem and leaf from BRASUZ1 *E. grandis*, the one currently being sequenced by JGI. Total RNA extraction was performed with CTAB protocol to a total amount of 10 mg per sample [4]. Fraction of small RNAs were barcoded to be sequenced in a single flow cell in Illumina GA II Sequencing System by Fasteris [http://www. fasteris.com]. A computational pipeline was specifically developed to process the deep sequencing data. The pre-processing step cleans the sequences by quality screening, adapter sequence removal, contaminant checking. Cleaned reads were sorted according to size, quantified (tag counting) and used to create an additional set of non-redundant sequences (using uclust). Bowtie was used to map sequences against the 8X *E. grandis* - BRASUZ1 genotype - genome sequence draft. Mapped positions in the genome were extended by 150 bases to be used as input to predict secondary structure (miRDeep) to test for stem loop structure of miRNA precursors. Northern blot hybridization is being used for experimental validation of some conserved and potentially new *Eucalyptus* miRNAs sequences.

**Results and conclusions:** Total number of reads was 6,104,498 ranging from 1,115,404 to 1,766,355 per sample – 36 nt average size. After pre-processing, total number of sequences was reduced to 1,980,958. As expected, read size distribution has two main peaks at 21 and 24 nt. Comparative analysis of size distribution interestingly shows higher abundance of the 24 nt fraction for all samples, being up to 3,75 times higher than 21 nt. The 24 nt small RNAs are predominantly small interfering RNAs (siRNAs) which are involved in RNA-directed DNA methylation resulting in gene and transposon silencing. Putting it all together, reads from four samples resulted in 169,642 unique sequences mapped against the genome. From that, 70,55% had at least one alignment to the genome reported, 23,54% failed to align and 5,91% mapped to multiple loci, indicative of repeat regions.

**Mapping 20-22 nt reads against the reference genome** revealed that BRASUZ1 had more reads mapping to its own genome than the other

samples, totaling 95% for leaves sample and 91% for the xylem. *E. globulus* samples showed a reduced percentage of mapped reads, around 85%, corroborating the existence of interspecific variability. Besides that, the relative abundance among the three xylem samples reinforces the variability also in the expressed repertoire of small RNAs. Annotation of plant miRNAs was done meeting a set of strict criteria, particularly a proper secondary structure of the precursor [5]. The positions in the genome with a mapped reads were extended to 300 bases and fed to the program miRDeep [6] to test for the compatibility of precursor hairpin. At least 38 sequences mapped were positive under these premises.

Conserved *Eucalyptus* miRNAs were identified by similarity searches against the miRBase. A total of 206 distinct *Eucalyptus* sequences showed significant similarity (at most one mismatch) to an orthologous sequence, confirming the presence of 36 different miRNA genes, including many of its isoforms.

**Quantitative differences** in miRNA abundance were probed by pairwise comparison of tag counts contrasting intraspecific, interspecific and tissue-specific analysis. Results revealed that the most similar small RNA repertoire are between intraspecific samples and, the least, between tissue specific. Tissue specific differential expression analysis shows that around 36% of the conserved miRNAs sequences observed in each tissue was mutually exclusive and the ones present in both samples vary up to two-fold (p-value=0.05).

**Experimental validation** is being carried out by northern blot hybridization and preliminary results validated new and conserved miRNAs, such as mir 156 and mir 172.

**Acknowledgments:** This work was supported by the Brazilian Ministry of Science and Technology through CNPq grant 577047/2008-6 and FAP-DF Grant NEXTREE 193.000.570/2009 and EMBRAPA Macroprogram 2 project grant 02.07.01.004.

**References**

1. Axtell M, Snyder J, Bartel D: Common functions for diverse small RNAs of land plants. *Plant Cell* 2007, 19:1750-1769.

2. Creighton C, Reid J, Gunaratne P: Expression profiling of microRNAs by deep sequencing. *Brief Bioinform* 2009, 10(5):490-497.

3. Meyer S, Pfaffl M, Ulbrich S: Normalization strategies for microRNA profiling experiments: a 'normal' way to a hidden layer of complexity? *Biotechnol Lett* 2010, 32:1777-1788.

4. Chang S, Puryear J, Cairney J: A simple and efficient method for isolating RNA from pine trees. *Plant Molecular Biology Reporter* 1993, 11(2):113-116.

5. Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao X, Carrington JC, Chen X, Green PJ, et al: Criteria for Annotation of Plant MicroRNAs. *Plant Cell* 2008, 20:3186-3190.

6. Friedländer M, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N: Discovering microRNAs from deep sequencing data using miRDeep. *Nature Biotechnology* 2008, 26:407-415.

P174

Next-generation gene catalogues and genomics tools focused on
forestry research

Philippe Rigault

Gydle Inc.,1363 av. Maguire, Québec, QC G1T 1Z2, Canada

E-mail: prigault@gydle.com

BMC Proceedings 2011, 5(Suppl 7):P174

Gydle is developing reference gene catalogues and genomics resources targeted at forestry research, leveraging its unique bioinformatics expertise in next-generation sequencing.

Next-generation sequencing technologies have revolutionized the field of genomics and have reached the capacity to generate enough quality data to sequence and assemble thousands of genomes and gene catalogues per year. These extraordinary opportunities are currently limited by challenges in data analysis which hinder the translation from raw sequencing data to applications in research and in the field. There is an enormous gap between an instrument capacity to produce millions of reads per day and the ability to analyze and translate quickly this data into usable information and value-added sets for genomics research. One particular limitation stems from the current state of assemblers which produce crude contigs and scaffolds that need considerable editing in order to obtain contiguous, gene-oriented, full-length, artifact-free
annotated sequences desirable for the production of quality tools for genomics research. Researchers also lack tools to rapidly integrate and visualize their own data and collaborate in a user-friendly way. Finally, the ability to produce gene catalogues for thousands of samples calls for a new generation of tools to conduct large-scale comparative genomics studies between and within species.

Gydle has developed a complete suite of proprietary bioinformatics tools to address many of the challenges associated with next-gen sequence analysis. A survey of these tools will be presented, which include innovative raw data filtering, rapid and accurate DNA alignment and gene-oriented assembly software, automated and interactive visualization tools for sequence correction and annotation. These tools enable users to process from start to finish a typical next-gen sequencing run in a user-friendly way in a matter of minutes to hours instead of weeks. Users can then visualize their results, edit sequence assemblies and annotations and identify features such as sample-specific expression patterns, SNPs, unspliced introns and alternative splicing events, handling information from hundreds of millions of reads on their workstation or laptop computer. We intend to make these bioinformatics tools available commercially in the near future.

Applying these bioinformatics tools, we combined sequencing data generated by Gydle with publicly available data to produce curated reference gene catalogues for species of interest to the forestry industry, which currently 35 tree species including 7 pinus, 3 picea, 3 eucalyptus, 2 poplar and 5 oak species. Gydle gene catalogues also include over 50 other plant species of agricultural and medicinal interest as well as gene catalogues for species ecologically related to trees such as insects, endophytes, fungi, and microbiota. We intend to make these catalogues available commercially in addition to offering the possibility for researchers to integrate their own data with these catalogues privately.

We used these reference genes catalogues to produce species-specific and cross-species value-added genomics resources such as:

- reference gene sequences covering biochemical pathways involved in growth, wood formation, climate adaptation, biofuel production, and secondary metabolites of interest to pest resistance and human health

- curated amino-acid databases to improve proteomic and metabolomic identifications

- SNP sets and designs of high-throughput genotyping assays such as Illumina GoldeGate/Infinium for marker discovery and genomic selection.

- reference sets and tools for gene expression studies by RNA-seq and microarrays.

Examples of gene catalogues, cross-species analysis and value-added sets will be presented.

P175

Comparative transcriptome analysis of tree *Eucalyptus* species using RNAseq technology: analysis of genes interfering in wood quality aspects

MM Salazar¹*, LC Nascimento¹, ELO Camargo¹, RO Vidal², J Lepikson-Neto¹, DC Goncalves¹, WL Marques¹, PJSL Teixeira¹, GAG Pereira¹

¹Laboratório de Genômica e Expressão - LGE- UNICAMP, Brazil; ²Laboratório

Nacional de Biociências – CNPEM/ABTLuS, Brazil

E-mail: marcelamsalazar@gmail.com

BMC Proceedings 2011, 5(Suppl 7):P175

**Background:** The *Eucalyptus* wood is one of the most important raw materials for pulp and paper industry. Brazil is currently the first producer of short-fiber pulp and sixth in total production of cellulose. To maintain the industrial competitiveness, investment in genomic research started in 2002 with the *GENOLYPTUS* project (Brazilian Network of Eucalyptus Genome Research). Recently, a new transcriptome library was generated using Next Generation RNA Sequencing by Illumina's sequencing by synthesis technology.

Different species of *Eucalyptus* are recognized for their superior characteristics in terms of growth, wood quality and resistance to different types of stress (1). Such features are probably driven by the coordinated expression of numerous genes involved in processes of structural and regulatory genes in xylogenesis. Therefore, the main purpose of this study is to identify genes and key metabolic compounds directly involved in wood quality, as well as transcription factors involved. An extensive data mining in the RNAseq database was conducted to identify sequences over expressed in xylem and those that were differentially expressed between species.

**Methods:** Genolypthus Sanger sequenced ESTs (167,271) and NCBI *Eucalyptus* ESTs (36,981) were assembled using the program CAP3 (2). All unigenes were automatically annotated using BLAST (3) (e-value cutoff of 1e-5) against protein databases, including: non-redundant (NR) database, uniref (4), pfam (5) and keg (6). Moreover, a functional annotation using the BLAST2GO software was performed (7). The RNA-Seq reads produced from three different xylem libraries (*Eucalyptus globulus*, *E. grandis* and *E. urophylla*) were aligned against the assembled unigenes using the SOAP2 aligner (8) configured to allow up two mismatches, discard sequences with "N"s and return all optimal alignments. In order to perform the differential expression analysis between libraries, a normalization and statistical pipeline were applied using DEG-seq (9) software considering a 99% confidence rate (cut-off of 0.01). From this analysis we obtained

<figure><img src="image_84.png" /><figcaption>**Figure 1 (abstract P175)** Functional annotation using the BLAST2GO software.</figcaption></figure>
<figure><img src="image_85.png" /></figure>

xylem genes and transcription factors differentially expressed between the three species.

**Results and discussion:** The assembly produced 53,412 unigenes (18,098 contigs and 35,314 singlets). The xylem libraries produced a large number of RNAseq reads (35bp). About 28 million reads were produced for the *E. globulus* library, 25 million for *E. grandis* and 25 million for *E. urophylla*. About 2% of reads were discarded after filtering. Most part of RNAseq reads mapped into the new EST assembly: 69.27% for *E. globulus*, 71.97% for *E. grandis* and 67.90% for *E. urophylla*. As a result, 33,599 unigenes were aligned to the RNAseq libraries. The functional annotations (Figure 1) show percent of genes related to the most relevant GO categories represented in each of the species pairs syduced for Biological Process, level 3.

In the *E. globulus* X *E. grandis* comparison, most genes are in the macromolecule metabolic process category that includes genes for pectin, cellulose and hemicellulose metabolism and also transcription factors involved in such pathways. Over 10% of these genes are over-expressed in *E. globulus*. Over 30% of the genes are over-expressed in *E. globulus* in the category metabolic cellular process. In the *E. urophylla* X *E. grandis* comparison, the metabolic cellular process category is representative of the total number of contigs, however, the number of genes over-expressed in *E. urophylla* is much lower. This may be an indicative that genes that participate in such pathways can contribute to the differential wood qualities found in *E. globulus*.

The new assembly, RNAseq libraries and Gbrowse are available at www.lge.ibi.unicamp.br/eucalyptus. *E. globulus* and *E. urophylla* libraries were compared against *E. grandis* library in order to access differentially expressed genes (considering 99% of confidence rate - cut-off of 0.01). As a result, 19,828 genes were differentially expressed in the *E.gl* X *E. gr* comparison (51.43%) and 18,142 (49.27%) in *E.ur* X *E. gr*. Also in these groups there were genes not expressed in one of the species, as can be seen in Venn diagram below (Figure 2).

These results may contribute to the understanding of wood formation processes and possibly help guide its improvement. The increase in wood quality and productivity has significant economic impacts especially in the pulp and paper industry.

## References

1. Grattapaglia D, Kirst M: Eucalyptus applied genomics: from gene sequences to breeding tools. *New Phytologist* 2008, 179:911-929.

2. Huang X, Madan A: CAP3: A DNA Sequence Assembly Program. *Genome Research* 1999, 9:868-877.

3. Alschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic Local Alignment Search Tool. *Journal of Molecular Biology* 1990, 215:403-410.

4. Suzek BE, Huang H, McGarvey P, Mazumber R, Wu CH: Uniref: comprehensive and non-redundant UniProt reference clusters. *Bioinformatics* 2007, 23(10):1282-1288.

5. Bateman A, Birney E, Cerruti L, Durbin R, Ettwiller L, Griffith-Jones S, Howe KL, Marshall M, Sonnhammer ELL: The Pfam Protein Families Database. *Nucleic Acids Research* 2002, 30(1):276-280.

6. Kanehisa M, Goto S: Kegg: Kyoto Encyclopedia of Genes and Genomes. *Nucleic Acids Research* 2000, 28(1):27-30.

7. Conesa A, Gotz 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.

8. Li R, Yu C, Li Y, Lam T-W, Yiu S-M, Kristiansen K, Wang J: SOAP2: an improved ultrafast tool for short read alignment. *Bioinformatics* 2009, 25(15):1966-1967.

9. Wang L, Guo K, Li Y, Tu Y, Hu H, Wang B, Cui X, Peng L: Expression profiling and integrative analysis of the CESA/CSL superfamily in rice. *BMC Plant Genomic* 2010, 10(282):1-16.

## P176

### Proteomic analysis of *Clostridium acetobutylicum* in butanol production from lignocellulosic biomass

Kumaran Sivagnanam¹, Vijaya G S Raghavan¹, Manesh Shah²,

Nathan C Verberkmoes², Robert L Hettich², Mark G Lefsrud¹

¹McGill University, USA; ²Oak Ridge National Laboratory, USA

E-mail: kumaran.sivagnanam@mail.mcgill.ca

BMC Proceedings 2011, 5(Suppl 7):P176

**Background:** Plant biomass is an abundant and renewable source of energy rich carbohydrates that can be efficiently converted by microbes into biofuels [1]. Butanol is considered as a second generation biofuel when it is produced from lignocellulosic biomass comprising of agricultural and garden wastes that does not compete with the food supplies [2]. *Clostridium acetobutylicum* is a gram positive, spore forming, obligately anaerobic bacteria capable of converting different sugars from lignocellulosic biomass to butanol through acetone – butanol – ethanol (ABE) fermentation process [3]. However, the production of butanol from ABE fermentation process is not economically viable and studies have been performed to understand the utilization of lignocellulosic biomass and regulation of butanol production to improve butanol productivity [4]. Successful industrial butanol production process through ABE fermentation requires complete understanding of the *C.acetobutylicum*. Shotgun proteomics provides a direct approach to study the whole proteome of an organism at molecular level in depth. Therefore, this paper focuses on shotgun proteomic profiling of *C. acetobutylicum* ATCC 824 from butanol fermentation process, elucidating the molecular functional mechanisms of *C.acetobutylicum* in butanol production.

**Materials and methods:** The microorganism *C.acetobutylicum* bacterial strain ATCC-824 was cultured [5]and ABE fermentations were carried out in batch mode using glucose substrate which is the most abundant compound present in lignocellulosic biomass. Samples of 10ml were harvested at late exponential phase from the start of the inoculation and proteins were extracted followed by digestion to peptides. The complex peptide solution was desalted through C18solid-phase extraction, concentrated, filtered and for each LC-MS/MS analysis, ~1/4 of the total sample was used based on the protocol used by [6]. Samples were analyzed in technical duplicates through a 2D nano-LC MS/MS system with a split-phase column (RP-SCX-RP) with 12hr runs [7-9]. All MS/MS spectra were searched with the SEQUEST algorithm [10] against
C. acetobutylicum Uniprot proteome databases [11] and filtered with DTASelect/Contrast [9] at the peptide level. Only proteins identified with two fully tryptic peptides from a 12hr run were considered for further biological study.

**Results:** A total of 479 proteins were identified in the proteome analysis of C. acetobutylicum from a single data point during the ABE fermentation process and 372 proteins were found to be present in both the first and second MS runs and identified as common proteins. This analysis confirms that 12 proteins were involved in the butanoate metabolism and about 32 uncharacterized proteins were found to be present during the ABE fermentation using glucose substrate. Overall, this is the first study which represents an extensive survey of whole proteome analysis of C. acetobutylicum from a single data point by multidimensional protein identification technology (MudPIT) and provides a valuable dataset of C. acetobutylicum proteins for a better understanding of the butanol production.

## References

1. Antoni D, Zverlov VV, Schwarz WH: Biofuels from microbes. *Applied Microbiology and Biotechnology* 2007, 77(1):23-35.

2. Festel GW: Biofuels - Economic aspects. *Chemical Engineering & Technology* 2008, 31(5):715-720.

3. Husemann MHW, Papoutsakis ET: Enzymes Limiting Butanol and Acetone Formation in Continuous and Batch Cultures of Clostridium-Acetobutylicum. *Applied Microbiology and Biotechnology* 1989, 31(5-6):435-444.

4. Ezeji TC, Qureshi N, Blaschek HP: Bioproduction of butanol from biomass: from genes to bioreactors. *Current Opinion in Biotechnology* 2007, 18(3):220-227.

5. Harris LM, Welker NE, Papoutsakis ET: Northern, morphological, and fermentation analysis of spo0A inactivation and overexpression in Clostridium acetobutylicum ATCC 824. *Journal of Bacteriology* 2002, 184(13):3586-3597.

6. Verberkmoes NC, Russell AL, Shah M, Godzik A, Rosenquist M, Halfvarson J, Lefsrud MG, Apajalahi J, Tysk C, Hettich RL, et al: Shotgun metaproteomics of the human distal gut microbiota. *Isme Journal* 2009, 3(2):179-189.

7. Lo I, Denef VJ, VerBerkmoes NC, Shah MB, Goltsman D, DiBartolo G, Tyson GW, Allen EE, Ram RJ, Detter JC, et al: Strain-resolved community proteomics reveals recombining genomes of acidophilic bacteria. *Nature* 2007, 446(7135):537-541.

8. Ram RJ, VerBerkmoes NC, Thelen MP, Tyson GW, Baker BJ, Blake RC, Shah M, Hettich RL, Banfield JF: Community proteomics of a natural microbial biofilm. *Science* 2005, 308(5730):1915-1920.

9. Tabb DL, McDonald WH, Yates JR: DTASelect and contrast: Tools for assembling and comparing protein identifications from shotgun proteomics. *Journal of Proteome Research* 2002, 1(1):21-26.

10. Eng JK, Mccormack AL, Yates JR: An Approach to Correlate Tandem Mass-Spectral Data of Peptides with Amino-Acid-Sequences in a Protein Database. *Journal of the American Society for Mass Spectrometry* 1994, 5(11):976-989.

11. Apweiler R, Bairoch A, Wu CH, Barker WC, Boeckmann B, Ferro S, Gasteiger E, Huang HZ, Lopez R, Magrane M, et al: UniProt: the Universal Protein knowledgebase. *Nucleic Acids Research* 2004, 32:D115.

Using methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq), we analyzed DNA methylation patterns in the *P. trichocarpa* genome in relation to four biological processes: bud dormancy and release, mature organ maintenance, in vitro organogenesis, and methylation suppression. Here, we report results from Illumina sequencing of nine sampled tissues, each representing 1 to 2 biological replicates. We sequenced 26M – 97M reads per tissue type, and validated our MeDIP-seq results using bisulfite sequencing of selected targets. Unique MeDIP-seq reads covered ~30-60% of genome space at an average depth of 4 to 12 reads/nucleotide. Transposons and other repeat elements were enriched within the methylated fraction of the genome. The pattern of gene model methylation showed higher methylation at promoters, in the middle of coding regions, and 3' to ends of genes, similar to that observed in other plant and animal species. Numbers of methylated genes identified varied widely by tissue type.

We produced summary data for genome methylation in *P. trichocarpa*, including the distribution of methylation across chromosomes (Fig. 1) and in and around genes. The intensity of methylation was highly heterogeneous within and between chromosomes. One-third of the genome, analyzed as 1 kb tiled windows, was differentially methylated among tissues. An example of a chromosomal region with differential methylation is shown in Fig. 2. Promoter methylation was more frequent than gene body methylation. Male catkins differed from the other tissues in that gene body methylation was more prevalent than promoter methylation, and two transposable element categories that were methylated in all other tissues were unmethylated in male catkins. We also analyzed the association of methylation intensity to gene expression data from an existing microarray study of the same tissues. At a whole genome scale, both promoter-

## P177
### Developmental variation in DNA methylation in poplar (Populus trichocarpa)

Kelly Vining¹, Kyle R Pomraning², Larry Wilhelm³, Henry D Priest³, Cathleen Ma¹, Ruoqing Zhu¹, Elizabeth Etherington¹, Matteo Pellegrini⁴, Todd Mockler², Michael Freitag⁵, Steven H Strauss⁶*

¹Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA; ²Molecular and Cellular Biology Program, Dept. of Biochemistry and Biophysics, Center for Genome Research and Biocomputing, Oregon State University, Corvallis, OR 97331, USA; ³Department of Botany and Plant Pathology, Center for Genome Research and Biocomputing, Oregon State University, Corvallis, OR 97331, USA; ⁴Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, 90024, USA; ⁵Dept. of Biochemistry and Biophysics, Center for Genome Research and Biocomputing, Oregon State University, Corvallis, OR 97331, USA; ⁶Department of Forest Ecosystems and Society, Center for Genome Research and Biocomputing, Oregon State University, Corvallis, OR 97331, USA

E-mail: Steve.Strauss@oregonstate.edu

BMC Proceedings 2011, 5(Suppl 7):P177

<figure><img src="image_86.png" /><figcaption>**Figure 1 (abstract P177) Two examples of section of poplar chromosomes showing tissue-specific methylation.** Each line represents one tissue type, including roots, buds, xylem, phloem, leaves, male catkins, and female catkins. Arrows point to regions showing strong tissue-specific differentiation. X-asix is 1 Kb tiled windows. Y-axis is RPKM.</figcaption></figure>
methylated and body-methylated genes had lower expression than unmethylated genes. We will report on our continued studies of tissue methylation/expression relationships.

We have developed a customized genome browser (Gbrowse version 1.6.9), compatible with the most recent (v2.2) *P. trichocarpa* genome assembly, at which our data can be explored: http://poplar.cgrb.oregonstate.edu.

P178

A drought stress transcriptome profiling as the first genomic resource for white teak - Gamhar - (*Gmelina arborea* Roxb) and related species

Carolina Rosero¹, Xavier Argout², Manuel Ruiz², Wilson Teran¹*

¹Unidad de Biotecnología Vegetal, Universidad Javeriana, Bogotá, Colombia;

²UMR DAP, CIRAD - Montpellier, France

E-mail: wteran@javeriana.edu.co

BMC Proceedings 2011, 5(Suppl 7):P178

**Background:** Gmelina (*Gmelina arborea* Roxb), also known as white teak is a tropical deciduous tree native from moist tropical forests of Asia. It has been successfully introduced in equatorial Africa, as well as central and south America. Gmelina is known for its very fast growing rate, its intrinsic disease, fire and drought tolerance, as well as the quality of its wood which is suitable for different types of uses such as paper pulping, plywood or particle board industry, furniture and light constructions. In addition, gmelina is considered a pioneer plant species capable of rapidly colonizing eroded or low nutritional quality lands, which makes it interesting for reforestation or landscape restoration programs. Despite its ecological and increasing economic importance, very little is known about the biology of this species and its remarkable field behavior such as drought tolerance, at the genetic, molecular and biochemical levels.

Genomic tools have recently increased the numbers and volume of genomic resources for several crop plants and trees and have contributed to enlarge our knowledge on basic aspects of plant biology, population dynamics or phylogeny; furthermore, they represent valuable sources of candidate genes and new molecular markers to assist breeding programs. Biological sequences reported to date in public databases and belonging to Gmelina do not exceed 20 entries: this very narrow availability of genetic information is the main bottleneck to initiate molecular breeding programs in *Gmelina arborea*.

We report here the first genomic resource for this tropical tree based on an RNAseq transcriptome profiling approach.

**Methods:** Two subtracted cDNA libraries were constructed from both leaf and root tissue of gmelina seedlings submitted to a water deficit stress. Subtracted cDNA sequencing was completed using 454 GS FLX Titanium sequencing. After sequence trimming, de novo assembly and clustering were completed using TGICL assembler and contigs were functionally annotated using BlastX against high quality curated protein reference databases. Both Gene Ontology (GO) terms and KEGG metabolic pathways

assignments were used to further characterize transcripts. SSR motives were identified using MISA. Except for the KEGG pathway assignments, all the sequence analysis was compiled in the previously developed bioinformatic pipeline ESTTIK [http://esttik.cirad.fr/].

**Results:** A preliminary collection of 10.528 contigs and 10.661 singletons, enriched in drought related transcripts, was obtained from both root and leaf subtracted libraries. Contig sequence sizes ranged from 97 to 2.187 bp with an average of 456 bp and a mean coverage depth of 38-fold. Functional annotation was completed only for contigs: up to 65% of these assembled sequences had significant Blast hits and about half of all assembled contigs could be assigned to one or more GO terms (Table 1).

Top hit species for homology based annotations of gmelina unigenes were: *Arabidopsis thaliana* (20-27%), *Vitis vinifera* (10-14%), *Populus trichocarpa* (4-7%) and *Ricinus communis* (4-7%). Among the different biological processes, cellular and metabolic processes, biological regulation, localization and response to stimulus were the most highly represented GO term categories, involving several genes related to drought or general stress, transport, transcription regulation and signal transduction, as expected. Analysis of KEGG metabolic pathway assignments revealed that our gene catalog covers all major plant metabolic pathways, with a certain dominance of enzymes of the carbohydrate, amino acid and energy metabolism in leaves, indicative that those pathways, seemingly impaired in response to water deficit stress, tend to recover by means of an active transcriptional rate (Table 2). The metabolic response in roots was slightly different with dominance of enzymes related to lipid, amino acid and carbohydrate metabolism, supporting important membrane and osmotic adjustment mechanisms in these tissues. Importantly, our gene catalog comprises many genes encoding proteins involved in signal perception and transduction, effector proteins as well as proteins with regulatory functions, allowing to cover the whole molecular response to drought stress. On the other hand the presence of several unigenes with no blast hit or with homology to unknown hypothetical proteins opens the possibility to uncover either previously unknown or less characterized protein functions related to drought stress.

Finally, we also identified microsatellite motifs within 428 unigenes, from which, 255 primer pairs have been designed for further experimental validation as functional SSR markers.

**Conclusions:** In this survey, we present the first unigene resource of this economically important tropical timber for which almost no prior genetic information existed. We identified drought stress related genes in different functional categories ranging from membrane bound sensor proteins, signal transduction proteins, transcription factors to metabolic or effector proteins. The SSR motifs found are good candidates for drought-related functional marker development in this species. Altogether, the results represent a first contribution to a better knowledge of the biology of white teak as well as the molecular mechanisms underlying its drought tolerance, which is essential to further encourage breeding program developments.

<table><caption>Table 1(abstract P178) Summary of Gmelina arborea transcript sequencing and functional annotation</caption><thead><tr><th></th><th>LIBRARY</th><th>Leaves</th><th>Roots</th><th>TOTAL</th></tr></thead><tbody><tr><td rowspan="5">ASSEMBLY</td><td>Input sequences</td><td>401.181</td><td>87.078</td><td>488.259</td></tr><tr><td>Clean sequences</td><td>340.654 (85%)</td><td>74.480 (86%)</td><td>415.134 (85%)</td></tr><tr><td>Singleton</td><td>6.045</td><td>4.616</td><td>10.661</td></tr><tr><td><strong>Contigs</strong></td><td><strong>5.696</strong></td><td><strong>4.832</strong></td><td><strong>10.528</strong></td></tr><tr><td>Size range (average) (bp)</td><td>100-1731 (413)</td><td>97-2197 (499)</td><td>97-2197 (456)</td></tr><tr><td></td><td>Depth coverage (fold)</td><td>59</td><td>14</td><td>38</td></tr><tr><td rowspan="5">Annotation</td><td><strong>Blast Hit</strong></td><td><strong>4.185 (73%)</strong></td><td><strong>2.623 (54%)</strong></td><td><strong>6.808 (65%)</strong></td></tr><tr><td>No Blast hi</td><td>1.511</td><td>2.209</td><td>3.720</td></tr><tr><td><strong>GO annotated contigs</strong></td><td><strong>3.274 (57%)</strong></td><td><strong>1.743 (36%)</strong></td><td><strong>5.017 (48%)</strong></td></tr><tr><td>GO terms</td><td>20.965</td><td>10.474</td><td>31.439</td></tr><tr><td>Contigs with Enzime Codes</td><td>1.252</td><td>509</td><td>1.761</td></tr><tr><td></td><td><strong>KEGG pathway assigned contigs</strong></td><td><strong>738 (13%)</strong></td><td><strong>292 (6%)</strong></td><td><strong>1.030 (10%)</strong></td></tr></tbody></table>

<footnote>a Percentages are related to total number of contigs</footnote>
<table><caption>**Table 2(abstract P178) Principal KEGG metabolic pathway assignments**</caption><thead><tr><th>Metabolic pathway</th><th>Leaves</th><th>%</th><th>Roots</th><th>%</th><th>Total</th><th>%</th></tr></thead><tbody><tr><td>Carbohydrate</td><td>348</td><td>20.5</td><td>99</td><td>15.0</td><td>447</td><td>18.9</td></tr><tr><td>Energy</td><td>362</td><td>21.3</td><td>87</td><td>13.2</td><td>449</td><td>19.0</td></tr><tr><td>Lipid</td><td>119</td><td>7.0</td><td>106</td><td>16.1</td><td>225</td><td>9.5</td></tr><tr><td>Nucleotide</td><td>60</td><td>3.5</td><td>45</td><td>6.8</td><td>105</td><td>4.4</td></tr><tr><td>Amino Acid</td><td>299</td><td>17.6</td><td>118</td><td>17.9</td><td>417</td><td>17.7</td></tr><tr><td>Other Amino Acids</td><td>67</td><td>3.9</td><td>28</td><td>4.2</td><td>95</td><td>4.0</td></tr><tr><td>Glycan Biosynthesis</td><td>13</td><td>0.8</td><td>19</td><td>2.9</td><td>32</td><td>1.4</td></tr><tr><td>Cofactors and Vitamins</td><td>124</td><td>7.3</td><td>33</td><td>5.0</td><td>157</td><td>6.7</td></tr><tr><td>Terpenoids and Polyketides</td><td>66</td><td>3.9</td><td>19</td><td>2.9</td><td>85</td><td>3.6</td></tr><tr><td>Other Secondary Metabolites</td><td>128</td><td>7.5</td><td>46</td><td>7.0</td><td>174</td><td>7.4</td></tr><tr><td>Other</td><td>114</td><td>6.7</td><td>60</td><td>9.1</td><td>174</td><td>7.4</td></tr><tr><td>Total Assignments</td><td>1700</td><td></td><td>660</td><td></td><td>2360</td><td></td></tr></tbody></table>

# S9. BIOSAFETY, CERTIFICATION AND ECONOMICS OF TREE BIOTECHNOLOGY

## P179

### *Eucalyptus* transgenic plants: from genetic transformation protocols to biosafety analysis

Rochele Kirch¹*, Leandro V Astarita², Eliane R Santarém², Giancarlo Pasquali¹
¹Biotechnology Center, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil; ²Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, RS, Brazil
E-mail: rochelekirch@terra.com.br

*BMC Proceedings* 2011, **5**(Suppl 7):P179

*Eucalyptus* is an exotic plant in Brazil, being originally from Australia. There are about 700 *Eucalyptus* species described and over 3,000 hybrids. It is one of the most planted tree genus in the world. The great economic interest on *Eucalyptus* trees is due to their fast growth, high productivity, great adaptability to different types of soils and climates, and also to the high versatility of their wood. *Eucalyptus* timber has applications for many different purposes such as cellulose pulp and paper production, electric poles, energy, charcoal, lumber and furniture. Given the economic importance of *Eucalyptus* in Brazil, it is of great interest to generate trees with superior characteristics that may result in considerable gains for the sector, particularly with regard to productivity and wood quality. One main goal of the present work is the definition of an efficient protocol for the genetic transformation and regeneration of transgenic *Eucalyptus* trees. We have so far obtained callus derived from leaves of *E.globulus* showing high capacity of *in vitro* regeneration. These calli were transformed with *Agrobacterium tumefaciens* LBA4404 harboring the binary plasmid pGfpKan, containing the green fluorescent protein (gfp) gene as reporter. Regenerated plants were transferred to culture pots with MS medium. Leaves derived from each regenerated plant were collected and analyzed using confocal microscopy to investigate the presence of fluorescence, indicating successful transformation. Molecular assays are also being performed to confirm the independence of transformation events via the pattern of transgene integration into plant genomes. The commercial release of GMOs and its derivatives in Brazil is regulated by the National Technical Biosafety Commission (CTNBio) in terms of the Regulatory Resolution No. 5, March 12, 2008. A series of experiments must be performed in order to prove the equivalence between GM and non-GM plants concerning the effects on human and animal health as well as on the environment. We are conducting the evaluation of global gene expression among different lines of transgenic and non-GM *Eucalyptus* adult plants, already available in test-fields belonging to FuturaGene in Brazil. Leaf and stem samples of GM and controls were collected and stored at -80 °C. Total RNA and proteins from leaves and stems were extracted and quantified. Messenger RNAs are under sequencing in Illumina platforms, according to the mRNA-Seq protocol (Fasteris S.A.) Our

idea is to compare transcript profiles among GM and non-GM tree samples, checking for possible pleiotropic effects of the transgenes. Protein profiles of the same individuals will also be analyzed to verify if the presence of the transgene influences the expression of other proteins in *Eucalyptus*. In order to do so, total proteins were extracted from samples and fractionated by 1D SDS-PAGE, cut off from gels and processed for posterior Mass Spectrometry sequencing.

**Financial Support:** MAPA/CNPq & FuturaGene.

## P180

### Towards male sterility in *Cryptomeria japonica* using the male strobilus-specific genes of *C. japonica*

Kurita Manabu¹*, Watanabe Atsushi², Konagaya Ken-ichi¹, Tsubomura Miyoko², Hirao Tomonori¹, Ishii Katsuaki¹, Taniguchi Toru¹

¹Forest Bio-Research Center, Forestry and Forest Products Research Institute, Japan; ²Forest Tree Breeding Center, Forestry and Forest Products Research Institute, Japan

E-mail: mkuri@affrc.go.jp

BMC Proceedings 2011, **5**(Suppl 7):P180

**Background:** *Cryptomeria japonica* D. Don (sugi) is one of the most important Japanese conifer species. Rapid improvement of the wood trait (e.g., growth speed and wood quality) using a conventional breeding approach is not possible, because breeding of coniferous tree requires a very long time. Genetic modification might be a powerful tool to shorten the time needed to breed trees compared with traditional breeding methods because it is able to induce the favorable traits by introduction of specific genes in trees without unnecessary genetic transitions. But the transfer of foreign genes from GM plants to related plant species by pollen has been cited as an environmental concern. For the purpose of creating male sterile GM *C. japonica*, we attempted to identify genes related to male flower formation.

**Methods:** To isolate the male strobilus specific genes, we constructed male strobilus specific SSH libraries based on three different stages according to male strobilus development; early stage, tetrad stage and mature stage. The microarray were designed using 19,259 genes consisting of isolated genes from SSH libraries and ForestGen(FORest EST and GENome database [http://forestgen ffpri affrc go.jp/en/index.html]). We analyzed expression profiling associated with male strobilus development. To isolate the male strobilus specific promoter of male strobilus specific genes, 1009-C47 and 1009-C96, TAIL-PCR methods were performed. To confirm the tissue specific activity of the promoter regions, the promoter::GUS fusions were introduced into *Arabidopsis* and *C. japonica*. Furthermore, we introduced 1009-C47::Barnase and 1009-C96::Barnase to *Arabidopsis* and *C. japonica*. We evaluated the ability of pollen formation of the transgenic *Arabidopsis* that introduced 1009-C47::Barnase and 1009-C96::Barnase construct.

**Results and discussion:** The microarray analysis was performed using cDNA of different developmental stages of male strobilus; early stage, microspore mother cell stage, tetrad stage, free spore stage and mature pollen stage. We showed that the strongly expressed genes in each developmental stage were markedly different. The GUS assay revealed that the 1009-C47::GUS showed anther-specific GUS activity in *Arabidopsis* and *C. japonica*. The introduction of 1009-C47::Barnase and 1009-C96::Barnase into *Arabidopsis* led to male sterility phenotype. We showed probability that the 1009-C47 promoter and 1009-C96 promoter are useful for male sterilization of *C. japonica*.

## P181

### Molecular Certification Laboratory of Arauco

Paulina Núñez¹*, Claudio Balocchi¹, Christian De Veer¹, Ximena Muñoz¹, Emilio Bustos¹, Philipp Bilabel¹, Mauricio Ramirez¹, Marcela Millar¹, Patricio Lavados², Jose Ordoñez³, Liliana Villalobos⁴

¹Bioforest S.A., Chile; ²Forestal Celco, Chile; ³Bosques Arauco S.A., Chile; ⁴Forestal Valdivia S.A., Chile

E-mail: paulina.nunez@arauco.cl

BMC Proceedings 2011, **5**(Suppl 7):P181

**Objective:** The main objective of the Laboratory is the Molecular Certification of the genetic material of Arauco, through the use of microsatellites (SSR).
**Methodology:** For the selection of the markers, a reference population of 30 unrelated parents for each species of interest (Eucalyptus globulus and Pinus radiata) was used. In these populations, we tested 25 SSR for pinus and 38 SSR for eucalyptus and the best 12 markers were selected for each species. With the selected markers, a pattern or fingerprint of each operational clone was obtained, out of samples taken from the original material (tree or embryogenic mass). Against these patterns, a total of over 20,000 samples were compared for validation of various operational processes. The sampling is planned to get 90% confidence of detecting operational errors (contamination) greater than 10%. Since the laboratory should process a large number of samples, protocols have been developed to be simple and short. DNA is extracted with 96 commercial Qiagen kit, for different tissues (embryogenic cells, embryos, leaves, bark, etc.). Sometimes, extractions are doubled by mixing leaf tissue of P. radiata and E. globulus, which is possible because SSRs amplified in one species do not interfere with the other. The amount of sample used for the extraction process varies from 50 to 200mg, which yields to concentrations of 30 to 100ng/ul of DNA. Since the amount is enough for several analyses, there is no need to store the original samples. The amplification is performed in thermal cyclers AB 9700 with a single PCR program for each species, using 10 ng of DNA for P. radiata and 2-4ng DNA for Eucalyptus sp. The reading of the fragments is performed in AB 3130xl Genetic Analyzer, while the analysis and correction of the electropherograms is done with the GeneMapper 4.0 program. The fingerprint comparison is made with self developed software, which reduces the noise of size variation observed between samples from the same clone and the appearance of false alleles or silent alleles. All these noises are more noticeable in some clone-marker combinations.

**Results:** Currently, Arauco has determined the pattern of 400 molecular clones of P. radiata and 200 clones of E. globulus. Thanks to the massive use of fingerprinting in the production and multiplication of clones, steps

where mistakes are most likely have been identified and in many cases, errors have been repaired. During 2010, out of 4600 P. radiata samples corresponding to 170 clones, the rate of mistaken identity found was 5.6% in genetic field trials, 5.3% in the embryogenesis laboratory process and 8.4% in nurseries. In E. globulus for 3,000 samples analyzed, of 135 clones, the mistaken identity rate was found to be 7.4% in genetic field tests, 8.3% in clonal orchards and 7.1% in nursery samples.

P182

Evaluating impact of possible transgenic poplar cultivation on protected areas

Anna Buonamici¹, Donatella Paffetti²*, Davide Travaglini², Stefano Biricolti³, Francesca Bottalico², Lorenzo Chelazzi², Filippo Cimò⁵, Isabella Colombini¹, Silvia Fiorentini², Valeria Tomaselli⁶, Cristina Vettori¹

¹Plant Genetics Institute, CNR, UOS FI, Via Madonna del Piano 10, 50019 Sesto Fiorentino (FI), Italy; ²Department of Agricultural and Forest Economics, Engineering, Sciences and Technologies, University of Florence, Via San Bonaventura 13, 50145 Florence, Italy; ³Department of Agronomy and Land Management, University of Florence, piazzale delle Cascine 22, Florence, Italy; ⁴Institute of Ecosystem Study – CNR, UOS FI, Via Madonna del Piano 10, 50019 Sesto Fiorentino (FI), Italy; ⁵DG Competitiveness of regional system and development of competencies, Regional Government of Tuscany, Via di Novoli 26, 50127, Firenze, Italy; ⁶Plant Genetics Institute, CNR, Via Amendola 165/A, 70126 Bari, Italy

E-mail: donatella.paffetti@unifi.it

BMC Proceedings 2011, 5(Suppl 7):P182

**Background:** Plant biodiversity studies have been performed in the Migliarino-San Rossore-Massaciuccoli Regional Park in Tuscany (Italy) within the framework of the European project LIFE08 NAT/IT/342.

<figure><img src="image_87.png" /><figcaption>**Figure 1(abstract P182)** Results of Geneland analyses of area A showing: (a) Spatial organisation into three clusters; (b), (c), and (d) are maps of posterior probabilities of each cluster.</figcaption></figure>
This project aims at developing a quick monitoring index (QMI) to rapidly assess the potential risk generated by transgenic plants in characterized ecosystems or biotopes. For this reason test areas have been selected inside the protected area to evaluate plant (weeds and trees), animal, and soil microorganisms biodiversity. The proximity of the selected test area to cropped surfaces where Genetically Modified Plants (GMPs) might be cultivated has been taken into account. GMPs could spread pollen and contaminate natural populations. To avoid this risk, an efficient monitoring system is required taking into account genetic diversity and breeding study. As far as tree biodiversity concern, *Populus* species were identified in the test areas. Two populations of *Populus* present into two different ecosystems (forest and wetland areas) were examined together with two cultivated varieties. The two ecosystems were characterized for the vegetation. Nuclear microsatellites were used to evaluate genetic diversity of poplar populations and level of breeding between natural and cultivated *Populus*. In addition the insect populations present on male and female poplars during flowering period have been studied.

**Materials and methods:** The selected *Populus* test areas are: A) a mixed forest stand in the Tenuta di San Rossore; B) a scattered *Populus* population in the wetland area of "lake of Massaciuccoli". Test areas A and B are 8 Km apart.

Test area A is a naturally-originated mixed forest stand. The prevailing tree species are *Populus* alba, *P. x canescens*, *Fraxinus angustifolia* and *Alnus glutinosa*. In the test area B single trees and small groups of *Populus* spp. are scattered along the lake.

In the test area A an experimental subplot 2500 m² large has been designed and the position has been acquired by GPS. All *Populus* trees within the plot have been identified and their position have been collected by GPS. The stand structure analysis has been performed using spatial functions.

In the test area B the position of *Populus* has been acquired by GPS.

The poplar populations present in areas were examined. From literature, six nuclear microsatellites were selected, all markers carried dinucleotides repeats except two with trinucleotides repeats [1,2].

Total DNA was extracted from the samples to perform microsatellite analysis [1,2]. Sizing of the PCR products was carried out using software Gene Mapper ver. 4.0 (Applied Biosystem).

In order to better define the species density and composition of the herbaceous stratum, some sampling subplots have been designed within the experimental plot by using the standardized multi-scale approach proposed by Dengler [3]. To define possible variations of distribution and/or density of plant species, their relative abundance has been evaluated according to the Braun Blanquet approach (1964).

During poplar tree blooming period inflorescences of male and female trees were collected. Weekly sampling was carried out with the aid of an elevator truck that permitted to collect samples out of reach.

**Results:** In relation to the herbaceous stratum, the observations made so far show some variability in the distribution of species to a plot to another, probably due to the micro topological characteristics of the site. The biodiversity analysis of the insects present on poplar trees indicates an evident difference in the faunal community between male and female trees and a relatively low number of species. Dipteran larvae were most abundant followed by coleopterans such as coccinellids and curculionids, araneids and lepidopteran larvae.

The analysis of spatial and genetic structure of the two poplar populations was performed using Geneland [4].

The results of Geneland clearly showed that three distinct clusters can be identified in the area A (Figure 1a) indicating the presence gene flow barriers (Figures 1b, 1c, 1d). The cluster represented in Figure 1b comprise individuals with the same genotype as indicated by microsatellites data (not shown). In fact, it is highly probable that these individuals are root suckers. The second and third clusters show the occurrence of gene flow within and among the two clusters (Figures 1c and 1d). This indicates that a minor barrier is present because the other tree species of the stand block only in part the pollen flow. The same analysis indicates two clusters in area B (Figure 2) with a gene flow among them higher respect to the area A. In fact, this population is in an open area (lake) and therefore the pollen flow is favored.

**Conclusions:** In general the level of biodiversity within the selected test area is high, and in particular the level of gene flow inside area B. Therefore, the possible cultivation of transgenic poplar close to the protected areas could influence their biodiversity. Especially the level of gene flow can determine a contamination of the autochthon poplar populations. The development of a QMI using the experimental data is in course.

<figure><img src="image_88.png" /></figure>
The availability of the QMI to rapidly assess the potential risk generated by transgenic plants in characterized ecosystems, is a useful tool to assess the releasing or not of the permission of cultivation close to protected areas.

## References

1. Tuskan GA, Gunter LE, Yang ZK, Tongming Y, Sewell MM, Difazio SP: Characterization of microsatellites revealed by genomic sequencing of *Populus trichocarpa*. *Canadian Journal of Forest Research* 2004, 34(1):85-93.

2. Smulders MJM, Van Der Schoot J, Arens P, Vosman B: Trinucleotide repeat microsatellite markers for black poplar (*Populus nigra* L.). *Molec. Ecol.* Notes 2001, 1(3):188-190.

3. Dengler J: A flexible multi-scale approach for standardised recording of plant species richness patterns. *Ecological Indicators* 2009, 9:1169-1178.

4. Guillot G, Estoup A, Mortier F, Cosson JF: A Spatial Statistical Model for Landscape Genetics. *Genetics* 2005, 170:1261-1280.

## P183

### Evaluation of different versions of the gene encoding green fluorescent protein (GFP) in plants

Camila B Scalco*, Rochele P Kirch, Giancarlo Pasquali

Biotechnology Center, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

E-mail: camilascalco@gmail.com

BMC Proceedings 2011, 5(Suppl 7):P183

The main purpose of the "CDA *Eucalyptus*: Collaborating Center in Agriculture Defense Relative to the Biosafety of Genetically Modified (GM) Eucalypts" is to gather, assess and validate the existing information concerning GM and non-GM *Eucalyptus* and its derivatives in the Brazilian environment, both in laboratories and field test experiments. Accordingly, the purpose of the present research activity is to provide a binary plasmid collection containing different versions of the gene encoding green fluorescent protein (GFP), originally from *Aequorea victorea*, for the future generation of easily detectable GM plant phenotypes. Using commercially available plasmids encoding blue (ECFP) and yellow (EYFP) versions of GFP for expression in bacteria, the initial strategy was to transfer the coding sequences to the intermediate plasmid pSport1 (Invitrogen) and, subsequently, to pART7 plasmid, which contains the promoter and terminator sequences for gene expression in plants. Although recombinant bacteria have been obtained for both genes, DNA sequencing showed that success was achieved only with pSport1-eyfp. So far, pART7 versions were not obtained. A new cloning strategy was proposed, which involves the binary plasmid pCAMBIA1302 (Cambia). This plasmid already contains one version of the *gfp* gene for expression in plants. The intention is to replace the *gfp* gene by *ecfp*, *eyfp* and *mCherryFP* versions. As soon as plasmids are finished, plants will be transformed via *Agrobacterium tumefaciens*, and their transgenic state will be confirmed by the fluorescence of the encoded proteins. Thus, the fluorescence of the GFP different versions will be used to monitor seeds, pollen, leaves and transgenic plants as a whole in the environment.

Financial support: Brazilian Ministry of Agriculture, Farming & Supply (MAPA), and The National Council for the Development of Science & Technology (CNPq), Brazilian Ministry of Science & Technology (MCT).

## IURO WORKSHOP COST ACTION FP0905

### P184

#### Plant biotechnology research at forest fields in South Korea

Jae In Park Chungbuk

National University, Korea

E-mail: jipark@chungbuk.ac.kr

BMC Proceedings 2011, 5(Suppl 7):P184

This paper is to give an outline of the tree biotechnology research in South Korea.

Tree Breeding, we call Traditional Tree Breeding later compared to Tree Biotechnology, started in 1954 in South Korea. Tree Biotechnology Research started as Tissue culture in the late 1970 in South Korea. Micropropagation was the first field adopted. Embryo culture, Bud culture, Callus culture, Cell culture are the methods for Micropropagation. Many tree species and herbaceous plants have been subjected to

micropropagation and successfully established. Tall tree species, *Populus alba* ×P. glandulosa, *Quercus*, *Betula* et al are successful for plantation, rare woody plants such as *Forsythia saxatilis*, *Abeliophyllum disticum*, *Berchemia berhemiaefolia*, *Hovenia dulsis*, *Lagerstroemia indica* for. *alba*, *Empetrum nigrum* var. *japonicum* were also subjected to in vitro culture. For somatic embryogenesis many species were successful in *Laxix leptolepis*, *Liriodendron tulipifera*, *Aralia elata*, and *Schisandra chinensis* et al. For Practical purpose a few species such as Mountain ginseng (root induction from callus culture and subsequent root culture by liquid culture), thornless *Aralia elata* (somatic embryogenesis from petioles), *Liriodendron tulipifera* (somatic embryogenesis from immature zygotic embryo) are under way of commercialization. Mountain ginseng is wild ginseng grown in mountain area. In mountain area they live very long time, even as long as over 100 years meanwhile the plants of it can grow only up to 6 years and produce healthy secondary products for human body. After Multiplication the produced roots are utilized for liquor, cosmetics, medicines et al. Yellow poplar (*Liriodendron tulipifera*), introduced from north America, shows good growth performance and is planted widely throughout the country. Through mass propagation of superior trees by somatic embryogenesis clonal forestry is planned in the forest area.

Biosafety policy of south Korea is very strict. Cultivation of transformed plants is not allowed.

**The following list shows the outline of the species which have been reported to be successful to the category in south Korea**

**Bud culture;** *Populus alba* ×P. glandulosa, *Kalopanax septemlobus*, *Corylopsis coreana*, *Eucalyptus pellita*, *Actinidia deliciosa* × A. arguta, *Prunus yedoensis*, *Diospyros kaki*. *Phellodendron amurese*, *Robinia pseudoacacia*, *Quercus acutissima*.

**Forsythia koreana for. aureoreticulata, Salix hallasanensis, Sorbus commixta, Betula schmitti, Machilus thunbrgii, Aconitum koreanum, Juglans regia, Betula dahurica, Crataegus pinnatifida,**

**Callus culture;** *Pinus koraiensis*, *Ailanthus altissima*, *Medicago sativa*, *Lycium chinense*, *Robinia pseudoacacia* wild Panax ginseng, *Populus koreana* ×

**P. nigra var. italica,**

**Cotyledon culture;** *Pinus rigida* × P. taeda

**Cell culture;** *Salix koreensis*, *Gardenia jasminoides*, *Taxus cuspidata*, *Hibiscus syriacus*.

**Embryo culture;** *Pinus rigidax* P. taeda, *Camelia sinensis*, *Pimpinella brachycarpa*, *Populus glandulosa*.

**Leaf culture;** *Camelia sinensis*.

**Cambial tissue culture;** *Larix decidua*.

**Somatic embryogenesis;** *Populus nigrax* P. maximowiczii, *Zizyphus jujuba*, *Oplopanax elatus*, *Eleutherococcus koreanum*, *Kalopanax pictus*, *Aralia elata* "Zaoh", *Liriodendron tulipifera*, *Larix kaempferi*, *Lycium chinense*, *Camelia sinensis*, *Orostachys japonicus*, *Quercus variabilis*, *Pimpinella brachycarpa*, *Juglans regia*.

**Anther culture;** *Populus glandulosa*.

**Protoplast isolation or culture;** *Populus alba* ×P. glandulosa, *Populus euramericana* *Populus alba*, *Populus glandulosa*, *Populus nigra*×P. maximowiczii

**Bioreactor culture;** *Ganoderma applanatum*, *Eleutherococcus koreanum*, *Tricholoma matsutake* (mycelium), *Lilium 'Casa Blanca'*, *Acanthopanax semicosus*, *Acanthopanax koreanum*, *wild Panax ginseng*.

**Molecular markers such as I-SSR marker, cpSSR marker have been developed in Quercus acutissima, Pinus densiflora, Salix koreensis for forensic medicine**

**Functional genomics;** *Populus alba* ×P. glandulosa, *Magnolia kobus*.

**Quantitative Traits Loci for root growth;** *Populus davidiana*.

**Root culture;** *Albizzia kalkora*, *Eleutherococcus koreanum*, *Tripterospermum japonicum*.

**Transformation;** *Populus alba* ×P. glandulosa (Model tree), *Aralia elata*, *Populus koreana* × P. nigra, *Camellia chinensis*, *Populus nigra*, *Populus davidiana*, *Pinus densiflora*, *Quercus acutissima*.

**I-SSR analysis;** *Stewartia koreana*, *Genus Juglans*, *Vaccinium uliginosum*, *Oplopanax elatus*, *Eleutherococcus semicosus*, *Ginkgo biloba*, *Abies holophylla*.

**Torreya nucifera, Ginkgo biloba, Rhododendron schlippenbachii, Pinus densiflora, Taxus cuspidate, Thuja koraiensis**.

**Cryopreservation;** *Bursaphelenchus xylophilus* (Pine Wood Namatode),

**Populus koreana × P. nigra var. italica, Populus alba×P. glandulosa**

**Expressed Sequence Tags;** *Populus alba* × P. tremula var. glandulosa.
**Microsatellite markers; Quercus acutissima**

**Secondary Metabolites:** Eleutherococcus chiisanensis (eleutherosides), Cornus walteri

Amorpha fruticosa, Eleutherococcus senticosus, Piper nigrum, Kalopanax pictus, Grifola umbellate (Sclerotium) Populus alba ×P. glandulosa (anthocyanin), Taxus cuspidate, Phellodendron amurense, Camelia chinensis

**Organogenesis:** Orchard grass

**Phytoremediation; Populus albaxP. glandulosa, Populus nigraP. maximowiczii.** Populus euramericana

**Allelopathy; Phellodendron amurense,**

**Cryopreservation; Sapindus mukorossi, Lycium chinense, Melia azedarach**
Acer mono

**Work plan and organisation:** To reach its aim, the work plan of the Action is organised in 4 Working Groups (WGs) to implement collaboration of scientists.

WG 1 - Biological characterization of GMTs: to characterize the GMTs in respect to their genetic and phenotypic features relevant for gene flow, gene containment and gene targeting.

WG 2 - Environmental impact assessment and monitoring of GMTs in the whole production chain from plantation to final products: to study environmental risk assessment strategies and monitoring the GMTs along the whole production chain.

WG 3 - Socio-economic implications of and recommendations for the use of GMTs: to make socio-economics analyses of the use of GMTs considering the concerns and acceptance by the public, the economic potential for GMTs and R&D efforts to be invested, as well as cost/benefit analyses, and propose recommendations for the use of GMTs.

WG 4 - Management of intranet - internet websites and dissemination: through a website (www.cost-action-fp0905.eu), provide science-based information and increase public awareness in the utilization of GMTs in forest plantation and at the same time safeguarding the environment
The knowledge gained will be summarised in a book as a final output of this Action which will report the state of art of knowledge and research on GMTs with suggestion on how to effectively implement present EU directives on GMO considering the problematic of forest trees and their environmental impacts.

The Action started the 12th of April 2010 and it will end the 11th of April 2014. Actually, 23 COST countries (Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Denmark, Estonia, Finland, France, Germany, Greece, Israel, Italy, Latvia, Netherlands, Norway, Romania, Serbia, Slovak Republic, Slovenia, Spain, Sweden, and United Kingdom) have signed the Memorandum of Understanding (MoU). Seven NON-COST countries (Albania, Australia, Canada, China, New Zealand, South Africa, USA) are participating to the Action.

**Conclusion:** With integration of all the countries listed above, the EU COST Action FP0905 is expected to generate important benefits as it also foresees a strong collaboration among R&D bodies and legislative directives. This kind of collaboration will be fundamental, on the one hand, to address policy-making efforts and, on the other hand, to allow the scientific community to discuss to public concerns in a responsible way, particularly concerning socio-economic implications and biosafety issues of transgenic tree plantations.

P185

**COST Action FP0905: Biosafety of forest transgenic trees: improving the scientific basis for safe tree development and implementation of EU policy directives**

Cristina Vettori¹*, Matthias Fladung²

¹Plant Genetics Institute UOS FI - CNR, Via Madonna del Piano 10, 50019

Sesto Fiorentino FI, Italy; ²Johann Heinrich von Thuenen Institute (vTI),

Institute for Forest Genetics, Sieker Landstr. 2, D-22927 Grosshansdorf, Germany

E-mail: cristina.vettori@cnr.it

BMC Proceedings 2011, 5(Suppl 7):P185

**Background:** The potential for unintended consequences of the spread of foreign genes (either via vertical or horizontal transfer) and of pleiotropic effects following transgene expression may be enhanced in long-lived forest trees. The COST Action FP0905 will focus on four key aspects related to the biosafety of genetically modified trees (GMTs): (a) analyses of the efficiency of existing gene containment strategies to avoid or if not possible to minimize gene flow; (b) facilitate efforts to develop site-specific integration of transgenes in tree genomes to minimize variability of transgene expression and pleiotropic effects, (c) evaluate possible methods to monitor GMTs in the whole production chain, and (d) conduct socio-economic and cost/benefit analyses in relation to the use of GMTs in plantations.

This Action combines multidisciplinary knowledge generated with transgenic lines of different forest genera (such as, Populus spp., Pinus spp., Eucalyptus spp., Betula spp., Castanea spp., Picea spp., etc.) as well as extensive expertise in correlated topics. The information gained should contribute to strengthen the scientific basis for the execution of the EU policy directives related to transgenic trees intended for cultivation in Europe. The main objective of the COST Action is to evaluate and substantiate the scientific knowledge relevant for GMT biosafety protocols by putting together already existing information generated in various European and Non-EU countries as basis for future EU policy and regulation for the environmental impact assessment and the safe development and practical use of GMTs.

**Cite abstracts in this supplement using the relevant abstract number,**
**e.g.:** Vettori and Fladung: COST Action FP0905: Biosafety of forest transgenic trees: improving the scientific basis for safe tree development and implementation of EU policy directives. BMC Proceedings 2011, 5(Suppl 7):P185