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De novo transcriptome analysis of Hevea brasiliensis tissues by RNA-seq and screening for molecular markers.

ABSTRACT: BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

SUBMITTER: Salgado LR

PROVIDER: S-EPMC4051172 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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De novo transcriptome analysis of Hevea brasiliensis tissues by RNA-seq and screening for molecular markers.

Salgado Leonardo Rippel LR Koop Daniela Martins DM Pinheiro Daniel Guariz DG Rivallan Ronan R Le Guen Vincent V Nicolás Marisa Fabiana MF de Almeida Luiz Gonzaga Paula LG Rocha Viviani Ribeiro VR Magalhães Milena M Gerber Alexandra Lehmkuhl AL Figueira Antonio A Cascardo Júlio Cézar de Mattos JC de Vasconcelos AnaTereza Ribeiro AR Silva Wilson Araújo WA Coutinho Luiz Lehmann LL Garcia Dominique D

BMC genomics 20140326

<h4>Background</h4>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 physiol ...[more]

PMID: 24670056

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Project description:BACKGROUND: In rubber tree, bark is one of important agricultural and biological organs. However, the molecular mechanism involved in the bark formation and development in rubber tree remains largely unknown, which is at least partially due to lack of bark transcriptomic and genomic information. Therefore, it is necessary to carried out high-throughput transcriptome sequencing of rubber tree bark to generate enormous transcript sequences for the functional characterization and molecular marker development. RESULTS: In this study, more than 30 million sequencing reads were generated using Illumina paired-end sequencing technology. In total, 22,756 unigenes with an average length of 485?bp were obtained with de novo assembly. The similarity search indicated that 16,520 and 12,558 unigenes showed significant similarities to known proteins from NCBI non-redundant and Swissprot protein databases, respectively. Among these annotated unigenes, 6,867 and 5,559 unigenes were separately assigned to Gene Ontology (GO) and Clusters of Orthologous Group (COG). When 22,756 unigenes searched against the Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) database, 12,097 unigenes were assigned to 5 main categories including 123 KEGG pathways. Among the main KEGG categories, metabolism was the biggest category (9,043, 74.75%), suggesting the active metabolic processes in rubber tree bark. In addition, a total of 39,257 EST-SSRs were identified from 22,756 unigenes, and the characterizations of EST-SSRs were further analyzed in rubber tree. 110 potential marker sites were randomly selected to validate the assembly quality and develop EST-SSR markers. Among 13 Hevea germplasms, PCR success rate and polymorphism rate of 110 markers were separately 96.36% and 55.45% in this study. CONCLUSION: By assembling and analyzing de novo transcriptome sequencing data, we reported the comprehensive functional characterization of rubber tree bark. This research generated a substantial fraction of rubber tree transcriptome sequences, which were very useful resources for gene annotation and discovery, molecular markers development, genome assembly and annotation, and microarrays development in rubber tree. The EST-SSR markers identified and developed in this study will facilitate marker-assisted selection breeding in rubber tree. Moreover, this study also supported that transcriptome analysis based on Illumina paired-end sequencing is a powerful tool for transcriptome characterization and molecular marker development in non-model species, especially those with large and complex genomes.

Project description:BackgroundOne of the concerns of assembling de novo transcriptomes is determining the amount of read sequences required to ensure a comprehensive coverage of genes expressed in a particular sample. In this report, we describe the use of Illumina paired-end RNA-Seq (PE RNA-Seq) reads from Hevea brasiliensis (rubber tree) bark to devise a transcript mapping approach for the estimation of the read amount needed for deep transcriptome coverage.FindingsWe optimized the assembly of a Hevea bark transcriptome based on 16 Gb Illumina PE RNA-Seq reads using the Oases assembler across a range of k-mer sizes. We then assessed assembly quality based on transcript N50 length and transcript mapping statistics in relation to (a) known Hevea cDNAs with complete open reading frames, (b) a set of core eukaryotic genes and (c) Hevea genome scaffolds. This was followed by a systematic transcript mapping process where sub-assemblies from a series of incremental amounts of bark transcripts were aligned to transcripts from the entire bark transcriptome assembly. The exercise served to relate read amounts to the degree of transcript mapping level, the latter being an indicator of the coverage of gene transcripts expressed in the sample. As read amounts or datasize increased toward 16 Gb, the number of transcripts mapped to the entire bark assembly approached saturation. A colour matrix was subsequently generated to illustrate sequencing depth requirement in relation to the degree of coverage of total sample transcripts.ConclusionsWe devised a procedure, the "transcript mapping saturation test", to estimate the amount of RNA-Seq reads needed for deep coverage of transcriptomes. For Hevea de novo assembly, we propose generating between 5-8 Gb reads, whereby around 90% transcript coverage could be achieved with optimized k-mers and transcript N50 length. The principle behind this methodology may also be applied to other non-model plants, or with reads from other second generation sequencing platforms.

Project description:Anopheles funestus is one of the primary vectors of human malaria, which causes a million deaths each year in sub-Saharan Africa. Few scientific resources are available to facilitate studies of this mosquito species and relatively little is known about its basic biology and evolution, making development and implementation of novel disease control efforts more difficult. The An. funestus genome has not been sequenced, so in order to facilitate genome-scale experimental biology, we have sequenced the adult female transcriptome of An. funestus from a newly founded colony in Burkina Faso, West Africa, using the Illumina GAIIx next generation sequencing platform.We assembled short Illumina reads de novo using a novel approach involving iterative de novo assemblies and "target-based" contig clustering. We then selected a conservative set of 15,527 contigs through comparisons to four Dipteran transcriptomes as well as multiple functional and conserved protein domain databases. Comparison to the Anopheles gambiae immune system identified 339 contigs as putative immune genes, thus identifying a large portion of the immune system that can form the basis for subsequent studies of this important malaria vector. We identified 5,434 1:1 orthologues between An. funestus and An. gambiae and found that among these 1:1 orthologues, the protein sequence of those with putative immune function were significantly more diverged than the transcriptome as a whole. Short read alignments to the contig set revealed almost 367,000 genetic polymorphisms segregating in the An. funestus colony and demonstrated the utility of the assembled transcriptome for use in RNA-seq based measurements of gene expression.We developed a pipeline that makes de novo transcriptome sequencing possible in virtually any organism at a very reasonable cost ($6,300 in sequencing costs in our case). We anticipate that our approach could be used to develop genomic resources in a diversity of systems for which full genome sequence is currently unavailable. Our An. funestus contig set and analytical results provide a valuable resource for future studies in this non-model, but epidemiologically critical, vector insect.

Dataset Information

De novo transcriptome analysis of Hevea brasiliensis tissues by RNA-seq and screening for molecular markers.

Publications

De novo transcriptome analysis of Hevea brasiliensis tissues by RNA-seq and screening for molecular markers.

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