Comparative transcriptome profiling of Polianthes tuberosa during a compatible interaction with root-knot nematode Meloidogyne incognita.

BACKGROUND: The root-knot nematode (RKN; Meloidogyne spp.) is the most destructive plant parasitic nematode known to date. RKN infections, especially those caused by Meloidogyne incognita, are one of the most serious diseases of tuberose. METHODS AND RESULTS: To investigate the molecular mechanism in the host-pathogen interactions, the Illumina sequencing platform was employed to generate comparative transcriptome profiles of uninfected and Meloidogyne incognita-infected tuberose plants, during early, mid, and late infection stage. A total of 7.5 GB (49 million reads) and 9.3 GB (61 million reads) of high-quality data was generated for the control and infected samples, respectively. These reads were combined and assembled using the Trinity assembly program which clustered them into 1,25,060 unigenes. A total of 85,360 validated CDS were obtained from the combined transcriptome whereas 6,795 CDS and 7,778 CDS were found in the data for the control and infected samples, respectively. Gene ontology terms were assigned to 958 and 1,310 CDSs from the control and infected data, respectively. The KAAS pathway analysis revealed that 1,248 CDS in the control sample and 1,482 CDS in the infected sample were enriched with KEGG pathways. The major proportions of CDS were annotated for carbohydrate metabolism, signal transduction and translation related pathways in control and infected samples. Of the 8,289 CDS commonly expressed between the control and infected plants, 256 were significantly upregulated and 129 were significantly downregulated in the infected plants. CONCLUSIONS: Collectively, our results provide a comprehensive gene expression changes in tuberose during its association with RKNs and point to candidate genes that are involved in nematode stress signaling for further investigation. This is the first report addressing genes associated with M. incognita-tuberose interaction and the results have important implications for further characterization of RKN resistance genes in tuberose.

Identification of putative flowering genes and transcription factors from flower de novo transcriptome dataset of tuberose (Polianthes tuberosa L.).

Polianthes tuberosa is commercially popular because of their economic importance in floriculture for cut and loose flowers and in perfume industry because of the unique fragrance. Despite its commercial importance, no ready-to-use transcript sequence information is available in the public database. We have sequenced the RNA obtained from tuberose flowers using the Illumina HiSeq. 2000 platform and have carried out a de novo analysis of the transcriptome data. The de novo assembly generated 11,100 transcripts. These transcripts represent a total of 7876 unigenes that were considered for downstream analysis. These 7876 unigenes, which was further annotated using blast2go and KEGG pathways, were also assigned. Tuberose transcripts were also assigned to metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes database to determine their biochemical functions. 4591 of the tuberose transcripts matched to genes in KEGG pathways and 66 transcripts were mapped to the Flavonoid biosynthesis pathway. 21 flowering genes have been identified in this tuberose transcriptome. Transcription factor analysis helped in the identification of a large number of transcripts similar to key genes in the flowering regulation network of Arabidopsis thaliana. Among the transcription factors identified "NAC" which is associated with plant stress response represented the most abundant category followed by APETALA2 (AP2)/ethylene-responsive element binding proteins (EREBPs) which plays various role in floral organ identity and respond to different biotic and abiotic stress.