De novo transcriptome analysis of Hevea brasiliensistissues by RNA-seq and screening for molecular markers
- Leonardo Rippel Salgado1Email author,
- Daniela Martins Koop2,
- Daniel Guariz Pinheiro1,
- Ronan Rivallan3,
- Vincent Le Guen3,
- Marisa Fabiana Nicolás4,
- Luiz Gonzaga Paula de Almeida4,
- Viviani Ribeiro Rocha4,
- Milena Magalhães4,
- Alexandra Lehmkuhl Gerber4,
- Antonio Figueira5,
- Júlio Cézar de Mattos Cascardo^2,
- AnaTereza Ribeiro de Vasconcelos4,
- Wilson Araújo SilvaJr1,
- Luiz Lehmann Coutinho6 and
- Dominique Garcia3Email author
© Salgado et al.; licensee BioMed Central Ltd. 2014
Received: 12 March 2013
Accepted: 24 March 2014
Published: 26 March 2014
The rubber tree, Hevea brasiliensis, is a species native to the Brazilian Amazon region and it supplies almost all the world’s natural rubber, a strategic raw material for a variety of products. One of the major challenges for developing rubber tree plantations is adapting the plant to biotic and abiotic stress. Transcriptome analysis is one of the main approaches for identifying the complete set of active genes in a cell or tissue for a specific developmental stage or physiological condition.
Here, we report on the sequencing, assembling, annotation and screening for molecular markers from a pool of H. brasiliensis tissues. A total of 17,166 contigs were successfully annotated. Then, 2,191 Single Nucleotide Variation (SNV) and 1.397 Simple Sequence Repeat (SSR) loci were discriminated from the sequences. From 306 putative, mainly non-synonymous SNVs located in CDS sequences, 191 were checked for their ability to characterize 23 Hevea genotypes by an allele-specific amplification technology. For 172 (90%), the nucleotide variation at the predicted genomic location was confirmed, thus validating the different steps from sequencing to the in silico detection of the SNVs.
This is the first study of the H. brasiliensis transcriptome, covering a wide range of tissues and organs, leading to the production of the first developed SNP markers. This process could be amplified to a larger set of in silico detected SNVs in expressed genes in order to increase the marker density in available and future genetic maps. The results obtained in this study will contribute to the H. brasiliensis genetic breeding program focused on improving of disease resistance and latex yield.
KeywordsNext generation sequencing Molecular markers KASP genotyping chemistry Rubber tree
Hevea brasiliensis (Wild.) Muell.-Arg. is a tree native to the Brazilian Amazon region and it is botanically classified in the Angiospermae division, class Dicotyledoneae, and family Euphorbiaceae. Many species from the Euphorbiaceae produce latex in specialized cells (laticifers). In the case of H. brasiliensis, the latex is a stable emulsion of isoprenoid polymers widely employed to produce natural rubber. In the Amazon, the population of H. brasiliensis is estimated to be one of the twenty most abundant tree species . Hevea brasiliensis is also the most abundant specie of the genus, with the largest production capacity, accounting for about 99% of all natural rubber produced in the world, and with the greatest genetic variability . Natural rubber is a strategic natural raw material used in more than 40,000 industrial products, including 400 medical devices . Due to its structure and high molecular weight (> 1 million Dalton), natural rubber presents special features such as resilience, elasticity, resistance to abrasion and impact, which cannot be achieved by synthetic polymers . Increased demand for natural rubber on the international market and, consequently, the strengthening of the price, has promoted the rubber cultivation, placing rubber production within the range of highly attractive options available .
One of the major challenges for rubber tree cultivation is its adaptation to biotic and abiotic stress. In areas with a notable dry season and low mean temperatures, rubber cultivation is characterized by a long period of immaturity. In tropical regions of Latin America where the high level of relative humidity might be more suitable for rubber development, the climatic conditions are also conducive to the infection of rubber tree leaves by the fungus Microcyclus ulei, the causal agent of the South American Leaf Blight. Repeated attacks of this disease cause massive losses of leaves, leading to plant death. The main strategies proposed for avoiding the M. ulei damage in plantations involve cultivating genotypes tolerant for dryness and cold in sub-optimal areas and promoting new SALB-resistant and productive cultivars in tropical areas . One of the measures for avoiding M. ulei infection takes advantage of the strict high temperature and air humidity conditions for the fungus to reproduce. Based on this requirement, two infection avoidance strategies can be proposed: climatic escape, where leaf exchanges occur during the dry season, when weather conditions are not favorable to fungal sporulation or growing rubber trees in sub-optimal areas (with lower average temperatures and air humidity). Both approaches inhibit M. ulei infection, but also may reduce rubber tree yield. The important factor for rubber cultivation is the vegetative fitness of the tree, which is directly reflected in the genetic potential of the cultivated clone . The RRIM600 Oriental clone is classified as susceptible to SALB, and highly productive over a range of temperatures and relative humidity.
Breeding between inbreeds with different characteristics targeting tolerance of biotic and abiotic stress has been identified as an alternative for improving rubber tree growth and production. Overcoming such challenges can be assisted through the development of new strategies and tools in the biotechnology field. Of those tools, we can highlight sequencing of the expressed genome of H. brasiliensis (transcriptome), representing the complete set and quantity of transcripts in a cell or tissue for a specific developmental stage and/or physiological condition . In the rubber tree, the identification and characterization of expressed genes may improve our understanding of plant tolerance of biotic and abiotic stress, and the regulation of latex biosynthesis. Thus, the objectives of our study were to capture the transcriptional profile of a large variety of Hevea brasiliensis organs and tissues with a view to completing the available reference transcriptomes, then to identify in silico SNP and SSR markers and, lastly, develop the first SNPs markers in the rubber tree.
Results and discussion
Transcriptome sequencing and assembling
Organs and tissues used in the RRIM600 and RRIM600 OPS RNA extracts
Cotyledon in the seed (germination stage I)
Leaflets stage A
Seedlings (germination stage II)
Leaflets stage B2
Stalk (germination stage III)
Leaflets stage C
Roots (germination stage III)
Leaflets stage D
Seed (germination stage III)
Petiole (Leaf stage B2)
Leaves (germination stage IV)
Petiole (Leaf stage C)
Stalk (germination stage IV)
Petiole (Leaflets stage D)
Roots (germination stage IV)
Seed (germination stage IV)
Bark (trunk grafted with MDF180 crown)
Immature seeds with transparent endosperm
Bark (trunk and crown of RRIM600)
Immature seeds with white endosperm
Fertilized female flowers
Male flowers, mature and immature
Columns and wall of fruit lobes
Seed stage A endosperm
Summary of Hevea brasiliensis transcriptome sequencing
Number of reads
Number of contigs
Average contig size
RRIM600 and RRIM600 OPS
Triwitayakorn et al.  sequenced the expressed genome of the H. brasiliensis from the vegetative shoot apex of the rubber tree using the 454 platform, obtaining a larger number of reads (2,311,497 reads vs. 525,371 reads obtained here) with a lower average read length (294 vs. 379 bp) but with a similar number and size of the assembled sequences in 19,152 isogroups (theoretically, each one represents a single gene and its variations) ranging between 500 and 1000 bp, while our assembly produced 19,708 contigs with 676 bp on average. Apart from the higher number of reads and the sampling of a few exclusive rubber tree tissues by Triwitayakorn et al. , the overall assembly process was very similar.
Summary of Hevea brasiliensis sequential annotation
Plant RefSeq protein
H. brasiliensis PUT
NR NCBI protein
Transcriptome sequencing identified the genes (134) of the main active pathways confirmed by KEGG, covering the majority of enzymes in key processes such as ‘plant hormone signal transduction’ (39/41); ‘plant-pathogen interaction’ (27/50); and ‘photosynthesis’ (46/63) indicating that the effort to capture a global transcriptome landscape was achieved, demonstrated by the diversity of KEGG and GO annotation. Xia et al. (2011)  obtained 125 KEGG pathways, mainly distributed on ’metabolic pathways’, ‘spliceosome’, and ‘plant-pathogen interaction’, while our most enriched pathways where ‘Ribosome’, ‘Spliceosome’, and ‘RNA transport’.
Comparisons with HeveaEST resources
To gain an understanding of our transcript sets, comparing our contig set (19,708 sequences) with the read set originated from Triwitayakorn et al. , we identified 2,833 sequences with no correspondence, indicating new gene contributions from our libraries. Of those, 367 were exclusive sequences from the RRIM600 library and 564 originated from young tissues (RRIM600 OPS library). The 2,833 novel sequences were annotated on 56 GO terms in three ontologies, being ‘cell part’ as the most representative on the ‘Cellular Component’ term, ‘Metabolic Process’ for the ‘Biological Process’ term, and ’binding’, for ‘Molecular function’. Of the 2,833 new sequences identified in this study, 31 sequences were identified as genes related to plant cell dehydration processes. The most frequent was annotated as a Heat-shock proteins (Hsps)/chaperones with 21 occurrences.
Screening for EST-SSR markers
For many plant species, large numbers of expressed sequence tags (ESTs) have been generated although low numbers of validated EST-SSR and SNP markers are available for plants, especially for non-model plants. For the rubber tree, most of the available marker resources are isozyme, RFLP, AFLP and SSR markers . SSR markers are today mainly obtained by a traditional method of SSR marker development, such as genomic-SSR hybrid screening and selective (or not) amplified microsatellite enrichment [17–21]. Recently, new EST-SSR markers were identified and proposed by several authors from transcriptomic data [13, 22–24]. SSRs are typically co-dominant markers, proved to be useful in assessing population structure, determining relationships between closely related species and QTL mapping. Although SSR markers derived from expressed sequences are considered less informative due to DNA sequence conservation in the transcribed region , such markers are cost-effective and considered as functional sequences .
Distribution of identified SSRs according to SSR motif types and repeat numbers
Type of Repeat
Number of repeat units
≥ Pentanucleotide repeat
Screening for SNV markers
Characterization of the 2,191 identified SNVs associated with 889 contigs
Number of SNVs
Number of associated contigs
Non coding sequence
Exclusive to the RRIM600 library
Exclusive to the RRIM600 OPS library
Common for both libraries
Out of the 2,191 predicted SNVs there were 1,877 substitutions on CDS regions (predicted protein coding sequence) for 889 contigs, which resulted in 1,594 non-synonymous substitutions on 597 contigs. A total of 283 SNVs was observed on non-coding regions. Of all the detected variations, 1,594 were potential non-synonymous substitutions, accounting for 78% of all variations, indicating a high level of genetic variability.
Using a similar strategy, Barbazuk et al.  screened maize ESTs from shoot apical meristem by 454 searching for SNPs from two inbred lines and the data were anchored onto the sequence of the maize genome. An initial number of 36,000 putative SNPs was detected after the alignment of nearly 260,000 and 280,000 transcripts of both inbred lines. This figure fell to 7,000 putative SNPs after post-processing. Our strategy was different, using identification parameters with high stringency, allowing the prediction of only 2,191 SNVs, but with an average quality of Q20 and a coverage ≥4x. This strategy proved effective as demonstrated by the validation of 172 out of 191 putative SNPs (90%) using an allele-specific amplification strategy. Similarly, Barbazuk et al.  identified variants exclusive to each inbred maize line and polymorphic sites with a different depth by inbred line. The validation of a subset of SNPs by PCR amplification and Sanger sequencing revealed a validation rate over 85%. These data suggest that the computationally identified SNVs represented ‘true’ polymorphisms even for low ESTs-coverage regions, suggesting that 454-based transcriptome sequencing is an excellent method for the high-throughput acquisition of gene-associated SNPs. In the same way, Novaes et al.  studying multiple tissues and genotypes of Eucalyptus grandis, a non-model plant, on a 454 platform, sequenced and assembled 148 Mbp ESTs from 1,024,251 reads identifying 23,742 SNPs, of which 83% were validated by Sanger sequencing in a sample of 337 SNPs.
From our data, non-synonymous SNVs accounted for 64% (1,211) of overall variations occurring in CDS regions. For non-synonymous changes it is not possible to directly determine how much the amino acid change will affect the protein structure, stability or localization. In Eukaryotes, changes in the protein isoelectric point (iP) may directly influence the localization and reactions of proteins, and it is reasonable to assume that alterations to the global protein iP may interfere in interactions between proteins and complexes. Alendé et al. , studying the evolution of iP over mammalian proteins, showed that insertions/deletions were the main reason for the shift in iP and suggested that shifts in iP might be related to the gain in additional activities, such as new interacting partners or preferences for orthologous or isoforms.
From the calculated iP and molecular weight (Mw) for the mutated and non-mutated contigs that displayed non-synonymous mutation, the variation in iP ranged from -1.95 to 1.09, and the Mw from -97.11 kDa to 66.08 kDa. A major alteration in iP was observed on a conserved hypothetical protein from Ricinus communis (alteration of -1.95 over original iP) annotated as a Ricinus communis conserved hypothetical protein, and 1.09 iP variation over the non-consensus sequence annotated as glycotransferase activity (GO: 0004579), KEEG (K12670) Glycan Biosynthesis. The characterization of mW and iP for the protein sequences translated from contigs with non-synonymous mutation showed that the mW from the mutated sequences was altered, but 250 sequences did not demonstrate any changes in iP values. Flegr  suggested that, since cell cytoplasm pH is stratified ranging from 6.4 to 7.2 in Eukaryotes, changes in the protein isoelectric point may directly influence the localization and reactions of proteins, and it is reasonable to assume that alterations to the global protein iP may interfere in interactions between proteins and complexes.
Substitutions outside coding regions (here 247 SNVs) are often linked to gene regulatory regions and may affect events, such as gene splicing, messenger RNA degradation or non-coding RNA sequences, and therefore usually called eSNP/V (expression single nucleotide polymorphism/variant), therefore becoming an interesting feature for biotechnological uses. Here, we were able to identify 2,191 mutations associated with 889 contigs. The results obtained by Barbazuk et al.  and Novaes et al.  gave sufficient evidence about the reliability of the 454 sequencing platform for SNV identification in transcriptomic data, constituting an important feature for 454 data analysis.
Analysis of genetic diversity
Genealogy of 23 Hevea spp. genotypes
Harbel8 x unknown
RRIC52 x PB86
IRCA109 x PFB5
IRCA109 x PFB5
PB5/51 x RRIM600
RRIM600 x PB235
Tjir1 x PB86
Tjir1 x PR107
PB5/51 x RRIM600
PB5/51 x PBS/78
PB5/51 x PB49
PB5/51 x PB6/9
H. benthamiana x H.brasiliensis
F4542 x Avros363
Harbel68 x TU42-525
It is the first time that a large number of SNPs have been developed in Hevea after the publication by Pootakham et al  of 10 SNPs. The result indicates that these 172 SNPs would be useful for rubber tree genetics and breeding studies. Being heterozygous for at least one of the parents of recently published Hevea genetic maps, most of these SNPs could easily contribute in the near future to enhancing the density of these SSR-based genetic maps: 102 SNPs could be mapped in the PB260 x Fx3899 map , 103 SNPs in the PR255 x PB217 map , 100 SNP in the PB260 x Fx2784 map  and 78 SNPs in the PB260 x MDF180 map .
This is the first Hevea brasiliensis transcriptome release covering the main tissues extracted from both clonal plant materials and derived hybrid plant materials obtained by open-pollination, and the first to investigate and analyze Hevea brasiliensis SNVs. The results of similarity identification, diversity of transcript localization, and variety of predicted functions from the 19,708 contigs obtained by our study, associated with the variety of tissues sampled demonstrate a cohesive approach to capturing the transcriptional landscape of whole rubber tree physiology.
Moreover, the public availability of the sequences, functional annotation and the global variant analysis, as well as the sequencing of raw data to be released from this study will provide a source of valuable information for biotechnology assays and genetic improvement of rubber trees, an addition to be used for a reference transcriptome for further sequencing projects.
As an allogamous plant with a recent history of selection, most of Hevea genotypes are highly heterozygous, opening the way for the development of a huge number of SNP markers.
Tissues samples of H. brasiliensis from the RRIM600 cultivar, were collected at the E. Michelin Plantation in Itiquira (Mato Grosso state, Brazil) and at the Michelin Plantation in Ituberá (Bahia state, Brazil). Samples of male and female flowers, fruits, bark and latex from adult RRIM600 trees were collected at the E. Michelin Plantation and conserved in RNAlater (Life Technologies Carlsbad, CA, USA) until RNA extraction. Samples of stalks, petioles and leaves from grafted plants of RRIM600 and tissues (radicle, hypocotyl, epicotyl, albumen, cotyledon, leaves) from germinated seedlings of open-pollinated RRIM600 seeds were collected from a greenhouse at the Michelin Plantation in Ituberá. The tissue samples were stored in liquid nitrogen.
Total RNA isolation and cDNA synthesis
Total RNA was isolated from 1 g of ground conserved tissue and extracted as described by Morcillo et al. (2006) . RNA integrity was evaluated using a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Before mRNA purification, 18 RNA samples of RRIM600 tissues and 12 extracts of RRIM600 OPS (open-pollinated seedlings) were pooled. Poly(A) RNA was isolated from these two pools with oligo beads (dT) from the PolyATtract mRNA kit (Promega, Madison, WI, USA).
Following isolation, the mRNAs were fragmented using a 0.1 M zinc chloride solution in 0.1 M Tris-HCl pH7.0. Using these shorter fragments as templates, the first-strand cDNAs were synthesized using Roche random primers and the AMV reverse transcriptase from the cDNA Synthesis system and the GS Rapid Library kits (Roche Applied Science, Mannheim, Germany). Sequencing was carried out on a Roche/454 GS-FLX (Titanium) pyrosequencing platform.
454 sequencing and assembly of cDNA libraries
The cDNA libraries were amplified with emulsion PCR Lib-L (Roche Applied Science) and sequenced using the XLR70 sequencing kit and a 70 × 75 mm PicoTiterPlate (Roche Applied Science). Each library was sequenced in one region of the PicoTiterPlate.
All of the H. brasiliensis cDNA data were first filtered by quality scores, presence of adapters, PolyA/T tails and repetitive elements using preprocess.pl Perl script from est2Assembly , and then assembled into contigs using the Newbler de novo assembler algorithm of the gsassembler (Newbler version 2.7, Roche 454). Reads and assembled contigs were analyzed using R programming version 2.13.2 . Scaffolding assembly was carried out by STM (Scaffolding using Translation Mapping) . The STM method relies on the assumption that the gene set of the reference proteome, which will serve as a template for joining contigs into scaffolds, is sufficiently similar, and, in this way, all translated contigs matching a same reference protein can be assembled into a scaffold . We used the Ricinus communis Protein sequence (amino acid translation) release 0.1 
Annotation, classification and comparison of assembled sequences
Contigs were compared to the set of proteome references by the BLAST algorithm (at an E-value threshold 10-5) against NCBI RefSeq, Plant Protein Database , H. brasiliensis assembled unique transcripts (PUT) of PlantGDB  and the complete NCBI nr database. We preferentially annotated contigs (with best BLAST hits) based first on similarity to Plant Protein RefSeq, then based on H. brasiliensis PUT nucleotides, and finally on Non-Redundant of nucleotides from the NCBI database. InterProScan version 4.8 was used for Gene Ontology and InterPro annotation  to connect Hevea transcript contigs with known gene ontology annotations. WEGO  software was used to perform GO annotation analysis and for plotting GO annotations. Also, attempting to phylogenetically classify the sequences, a BLAST using the Cluster of Orthologous Groups database was performed.
To gain an understanding of our set of transcripts mapping performed by GS Reference Mapper (Newbler version 2.7, Roche 454) against currently available H. brasiliensis sequences was carried out using the 2,311,497 reads generated by the Triwitayakorn et al. , obtained by sequencing H. brasiliensis shoot apex of the RRIM600 genotype, 30,094 Hevea brasiliensis EST sequences available in the NCBI database, including 9,860 ESTs (accession No EC600050–EC609910) from RRIM600 latex deposited in NCBI by Chow et al. .
For putative genes involved in the metabolic pathway, a KEGG annotation was performed using KAAS (KEGG Automatic Annotation Server) .
Identification of Single Nucleotide Variants (SNVs) and Simple Sequence Repeat (SSR) loci
To detect nucleotide variants over the contigs, an alignment between reads and the contigs generated by Newbler as a reference was performed using the Burrows-Wheeler Aligner for long reads (BWA-SW) . The results were used as input for the Bioconductor  Rsamtools version 1.6.0 package to obtain the possible nucleotide variants with a cut-off coverage of 4x, a threshold of 2 variants in the position and a base call quality cut-off of the PHRED score Q20 on average, where Q = -10 log10P, and the score stands for the probability of a wrong base being called.
To check wether or not SNV was responsible for a non-synonym alteration in the amino acid composition from the contig, a gene prediction analysis was carried out by the GlimmerHMM Eukaryotic Gene-Finding System  using the Arabidopsis thaliana training model in an attempt to identify the Protein Coding Sequence, for correct verification of the SNV substitution type made by the R/Bioconductor script.
Searches for SSRs from the contig data set were performed by Microsatellite Identification Tool (MISA) version 1.0 . The definition of microsatellites (unit size/ minimum number of repeats) was set as mononucleotides repeats if the same nucleotide was repeated at least 10 times (1/10), di (2/6), tri (3/5), tetra (4/5), penta (5/5), or hexanucleotides (6/5), and 100 as the maximum number of bases interrupting two SSRs in a compound microsatellite (microsatellites consisted of more than a single repeat type).
The molecular weight and the isoelectric point analyses for proteins were performed by EMBOSS version 6.4.0  and the generated output analyzed by R programming language.
Development of SNP markers
where dij represents the dissimilarity between units i and j, L represents the number of loci, and ml represents the number of matching alleles between i and j for locus l. From the dissimilarity matrix, a Neighbor-Joining tree  was computed using the DARwin software version 5.0.158 (Dissimilarity Analysis and Representation for Windows, http://darwin.cirad.fr/darwin. Branch robustness was tested using 1000 bootstraps.
This work was supported by CNPq (National Council for Scientific and Technological Development) PROSUL process 490748/2008-2 and CAPES for fellowship. The authors thank the FUNDERP (Fundação Hemocentro de Ribeirão Preto) and the BIT (Bioinformatics Laboratory) for technological support and Peter Biggins for reviewing the text of this manuscript.
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