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

• Grant number: 14/12934-0
• Support Opportunities: Regular Research Grants - Publications - Scientific article
• Duration: August 01, 2014 - January 31, 2015
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Anete Pereira de Souza
• Grantee: Anete Pereira de Souza
• Host Institution: Centro de Biologia Molecular e Engenharia Genética (CBMEG). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

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. (AU)