Mining of Stress-related Genes in Pigmented and Non-pigmented Rice using Gene Co-expression Network and Clustering Approaches

Pigmented rice has been associated with stress-resistant traits, such as resistance to abiotic and biotic stresses, but the genes network that is responsible for such traits remains limited. Hence, this study aims to identify stress-related genes in the pigmented rice using computational approaches. The gene co-expression network was constructed using Pearson Correlation Coefficient (PCC) ≥ 0.9 among differentially expressed genes (DEGs) of trancriptomes between pigmented and non-pigmented rice. The gene co-expression network was clustered using Markov Cluster algorithm (MCL) to identify the functional modules and the hub genes for each module were determined. The functional analyses were performed to each module to determine the related gene ontology (GO) and pathway. Protein-protein interaction (PPI) from STRING database was used to validate the functional analyses. A total of 721 DEGs were used to construct the gene co-expression network of pigmented and non-pigmented rice varieties. Of these, 614 DEGs with 15,259 edges were identified by PCC. Using MCL, 10 clusters were identified in the gene co-expression network of pigmented and non-pigmented rice varieties. Three clusters were enriched with seven GO terms (i.e., response to stress, response to stimulus, transcription factor activity) that are related to stress-resistant traits, indicating the highly correlated genes were the stress-related genes. Interestingly, nine hub genes were found to be related to drought tolerance, disease resistance and hormone biosynthesis. Validation of hub genes using STRING database revealed that 48 hub genes were also connected in the PPI network, suggesting their potential as candidate proteins in stress-related traits. This study demonstrated that the molecular interaction network and the network clustering approach are efficient in identifying the stress-related genes, which could provide new insights in understanding plant responses to abiotic and biotic stresses.

Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach

The proteome data of whole rice grain is considerably limited particularly for rice with pigmentations such as black and red rice. Hence, we performed proteome analysis of two black rice varieties (BALI and Pulut Hitam 9), two red rice varieties (MRM16 and MRQ100) and two white rice varieties (MR297 and MRQ76) using label-free liquid chromatography Triple TOF 6600 tandem mass spectrometry (LC-MS/MS). Our aim was to profile and identify proteins related to nutritional (i.e. antioxidant, folate and low glycaemic index) and quality (i.e. aromatic) traits based on peptide-centric scoring from the Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) approach. Both information dependent acquisition (IDA) and SWATH-MS run were performed in this analysis. Raw data was then processed using ProteinPilot software to identify and compare proteins from the six different varieties. In future, this proteomics data will be integrated with previously obtained genomics [1] and transcriptomics [2] data focusing on the above nutritional and quality traits, with an ultimate aim to develop a panel of functional biomarkers related to those traits for future rice breeding programme. The raw MS data of the pigmented and non-pigmented rice varieties have been deposited to ProteomeXchange database with accession number PXD018338.

1H NMR-Based Metabolomics Approach in Investigating the Chemical Profile, Antioxidant and Anti-Inflammatory Activities of Gynura procumbens and Cleome gynandra

Gynura procumbens and Cleome gynandra are two herbs commonly used in Malaysia to treat various ailments and are also consumed as salads (ulam) and vegetables. The present study aims to evaluate the relationship between the chemical compositions of both herbs and their antioxidant and anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach, which is being reported for the first time. Different ethanolic extracts of both herbs were tested for DPPH scavenging and inhibition of nitric oxide (NO) via RAW 264.7 macrophage cell induction. Principal component analysis (PCA) revealed a good separation between the extracts and the corresponding metabolites identified via ¹H NMR spectroscopy. The 100% ethanolic extract from both herbs and 20% ethanolic extract of C. gynandra were found to have the best antioxidant and anti-inflammatory activities. Kaempferol, quercetin, caffeoylquinic, dicaffeoylquinic acids, gallic acid, mallic acid, citric acid, phenylalanine, and choline are among the metabolites that contributed to bioactivities. The partial least square (PLS) model for both herbs have an overall acceptable goodness of fit and predictive power, which further strengthens the validity of this study. The present study provides a preliminary reference for the selection of optimum extract and will shed some light on the potential use of G. procumbens and C. gynandra as a phytomedicinal preparation.

RNA-seq data from whole rice grains of pigmented and non-pigmented Malaysian rice varieties

Pigmented rice is enriched with antioxidants, macro- and micronutrients. A comprehensive investigation of the gene expression patterns among the pigmented rice varieties would help to understand the cellular mechanism and biological processes of rice grain pigmentation. Hence, we performed RNA sequencing and analysis on the whole grain of dehusked mature seeds of selected six Malaysian rice varieties with varying grain pigmentations. These varieties were black rice (BALI and Pulut Hitam 9), red rice (MRM16 and MRQ100) and white rice (MR297 and MRQ76). Illumina HiSeq™ 4000 sequencer was used to generate total raw nucleotides of approximately 53 Gb in size. From 353,937,212 total paired-end raw reads, 340,131,496 total clean reads were obtained. The raw reads were deposited into European Nucleotide Archive (ENA) database and can be accessed via accession number PRJEB34340. This dataset allows us to identify and profile all expressed genes with functions related to nutritional traits (i.e. antioxidants, folate and amylose content) and quality trait (i.e. aroma) across both pigmented and non-pigmented rice varieties. In addition, the transcriptome data obtained will be valuable for discovery of potential gene markers and functional SNPs related to functional traits to assist in rice breeding programme.

Metabolic changes of Brassica rapa transformed with a bacterial isochorismate synthase gene

Metabolome analysis by 1-dimensional proton nuclear magnetic resonance (¹H NMR) coupled with multivariate data analysis was carried out in Brassica rapa plants transformed with a gene encoding bacterial isochorismate synthase (ICS). Partial least square-discrimination analysis (PLS-DA) on selected signals suggested that the resonances that were dominant in the transgenic plants corresponded to a glucosinolate (neoglucobrassicin), phenylpropanoids (sinapoyl malate, feruloyl malate, caffeoyl malate), organic acids (succinic acid and fumaric acid) and sugars (α- and β-glucose). In contrast, amino acids alanine threonine, valine, leucine were dominant in the untransformed controls. In addition, HPLC data showed that the transgenic plant accumulated salicylic acid (SA) at significantly higher levels than the control plants, whereas the phylloquinone levels were not affected. The results suggest that the expression of the bacterial isochorismate synthase gene in B. rapa does not affect fluxes into pathways to other groups of secondary metabolites through competition for the same precursor. On the contrary, the biosynthesis of isochorismate-derived products (SA) seems to induce the competitive pathways via phenylalanine (phenylpropanoids) and tryptophan (IAA and indole glucosinolates).

Metabolic changes in Agrobacterium tumefaciens-infected Brassica rapa

Agrobacterium has the ability to transfer its genetic material, T-DNA, into the plant genome. The unique interaction between the bacterium and its host plant has been well studied at the transcriptome, but not at the metabolic level. For a better understanding of this interaction it is necessary to investigate the metabolic changes of the host plant upon infection with Agrobacterium tumefaciens. This study investigated the metabolic response of Brassica rapa to infection with disarmed and tumor-inducing strains of A. tumefaciens using (1)H nuclear magnetic resonance spectroscopy combined with multivariate data analysis. The partial least square-discriminant analysis (PLS-DA) of two varieties of B. rapa showed that there was a clear differentiation in the metabolite profiles of B. rapa leaves infected with the disarmed strain LBA4404 and with tumor-inducing octopine and nopaline strains, particularly in the flavonoid, phenylpropanoid, sugar and free amino/organic acid contents. However, individual PLS-DA of each type of infection suggests that, in general, some flavonoids and phenylpropanoids were suppressed as a consequence of these infections. The results obtained in this study indicate that the disarmed strain LBA4404 and tumor-inducing strains have different effects on the metabolite profile of B. rapa.