Deep expression analysis reveals distinct cold-response strategies in rubber tree (Hevea brasiliensis).

BACKGROUND: Natural rubber, an indispensable commodity used in approximately 40,000 products, is fundamental to the tire industry. The rubber tree species Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell-Arg., which is native the Amazon rainforest, is the major producer of latex worldwide. Rubber tree breeding is time consuming, expensive and requires large field areas. Thus, genetic studies could optimize field evaluations, thereby reducing the time and area required for these experiments. In this work, transcriptome sequencing was used to identify a full set of transcripts and to evaluate the gene expression involved in the different cold-response strategies of the RRIM600 (cold-resistant) and GT1 (cold-tolerant) genotypes. RESULTS: We built a comprehensive transcriptome using multiple database sources, which resulted in 104,738 transcripts clustered in 49,304 genes. The RNA-seq data from the leaf tissues sampled at four different times for each genotype were used to perform a gene-level expression analysis. Differentially expressed genes (DEGs) were identified through pairwise comparisons between the two genotypes for each time series of cold treatments. DEG annotation revealed that RRIM600 and GT1 exhibit different chilling tolerance strategies. To cope with cold stress, the RRIM600 clone upregulates genes promoting stomata closure, photosynthesis inhibition and a more efficient reactive oxygen species (ROS) scavenging system. The transcriptome was also searched for putative molecular markers (single nucleotide polymorphisms (SNPs) and microsatellites) in each genotype. and a total of 27,111 microsatellites and 202,949 (GT1) and 156,395 (RRIM600) SNPs were identified in GT1 and RRIM600. Furthermore, a search for alternative splicing (AS) events identified a total of 20,279 events. CONCLUSIONS: The elucidation of genes involved in different chilling tolerance strategies associated with molecular markers and information regarding AS events provides a powerful tool for further genetic and genomic analyses of rubber tree breeding.

De novo assembly and transcriptome analysis of the rubber tree (Hevea brasiliensis) and SNP markers development for rubber biosynthesis pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Genetic divergence of rubber tree estimated by multivariate techniques and microsatellite markers.

Genetic diversity of 60 Hevea genotypes, consisting of Asiatic, Amazonian, African and IAC clones, and pertaining to the genetic breeding program of the Agronomic Institute (IAC), Brazil, was estimated. Analyses were based on phenotypic multivariate parameters and microsatellites. Five agronomic descriptors were employed in multivariate procedures, such as Standard Euclidian Distance, Tocher clustering and principal component analysis. Genetic variability among the genotypes was estimated with 68 selected polymorphic SSRs, by way of Modified Rogers Genetic Distance and UPGMA clustering. Structure software in a Bayesian approach was used in discriminating among groups. Genetic diversity was estimated through Nei's statistics. The genotypes were clustered into 12 groups according to the Tocher method, while the molecular analysis identified six groups. In the phenotypic and microsatellite analyses, the Amazonian and IAC genotypes were distributed in several groups, whereas the Asiatic were in only a few. Observed heterozygosity ranged from 0.05 to 0.96. Both high total diversity (H(T') = 0.58) and high gene differentiation (G (st') = 0.61) were observed, and indicated high genetic variation among the 60 genotypes, which may be useful for breeding programs. The analyzed agronomic parameters and SSRs markers were effective in assessing genetic diversity among Hevea genotypes, besides proving to be useful for characterizing genetic variability.