@article {8889,
	title = {Transcriptional transitions in Alphonso mango (Mangifera indica L.) during fruit development and ripening explain its distinct aroma and shelf life characteristics [Next Gen Genomics Facility]},
	journal = {Sci Rep},
	volume = {7},
	year = {2017},
	month = {2017 Aug 18},
	pages = {8711},
	abstract = {<p>Alphonso is known as the "King of mangos" due to its unique flavor, attractive color, low fiber pulp and long shelf life. We analyzed the transcriptome of Alphonso mango through Illumina sequencing from seven stages of fruit development and ripening as well as flower. Total transcriptome data from these stages ranged between 65 and 143 Mb. Importantly, 20,755 unique transcripts were annotated and 4,611 were assigned enzyme commission numbers, which encoded 142 biological pathways. These included ethylene and flavor related secondary metabolite biosynthesis pathways, as well as those involved in metabolism of starch, sucrose, amino acids and fatty acids. Differential regulation (p-value <= 0.05) of thousands of transcripts was evident in various stages of fruit development and ripening. Novel transcripts for biosynthesis of mono-terpenes, sesqui-terpenes, di-terpenes, lactones and furanones involved in flavor formation were identified. Large number of transcripts encoding cell wall modifying enzymes was found to be steady in their expression, while few were differentially regulated through these stages. Novel 79 transcripts of inhibitors of cell wall modifying enzymes were simultaneously detected throughout Alphonso fruit development and ripening, suggesting controlled activity of these enzymes involved in fruit softening.</p>
},
	keywords = {Cell Wall, Enzyme Inhibitors, Flowers, Fruit, Gene Expression Profiling, Gene Expression Regulation, Developmental, Gene Expression Regulation, Plant, Gene Ontology, Genes, Plant, Glycoside Hydrolases, Mangifera, Odorants, Phylogeny, Reproducibility of Results, RNA, Messenger, Transcription, Genetic, Transcriptome},
	issn = {2045-2322},
	doi = {10.1038/s41598-017-08499-5},
	author = {Deshpande, Ashish B and Anamika, Krishanpal and Jha, Vineet and Chidley, Hemangi G and Oak, Pranjali S and Kadoo, Narendra Y and Pujari, Keshav H and Giri, Ashok P and Gupta, Vidya S}
}
@article {540,
	title = {A method for comparative metabolomics in urine using high resolution mass spectrometry.},
	journal = {J Chromatogr A},
	volume = {1443},
	year = {2016},
	month = {2016 Apr 22},
	pages = {83-92},
	abstract = {<p>Developing a workflow for metabolite profiling from biological fluids using mass spectrometry is imperative to extract accurate information. In this study, urine samples from smokers (n=10) and nonsmokers (n=10) were analyzed using an ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) system. For the analysis, two different chromatographic methods [Reversed phase chromatography (RPC) and Hydrophilic interaction liquid chromatography (HILIC)], in two ionization modes (positive and negative) were used. Spiked reserpine (positive ion mode) or taurocholate (negative ion mode) were used for data extraction and normalization. Quality controls (QCs), prepared by pooling urine samples from both smokers and non-smokers (each n=10), were used to assess the reproducibility of the method. The final data output from SIEVE 2.2 after applying a cut-off for QC coefficient of variation (CV) \&lt;20\% and p-value \&lt;0.05 showed 165, 83, 177 and 100 unique components in RP positive/negative, HILIC positive/negative modes, respectively. Statistical analysis showed clustering of the two groups and the QCs, while the variable importance in projection (VIP) scores for the top fifteen metabolites in each of the four modes indicated the metabolites most responsible for the differences. Application of the developed workflow for comparative metabolomic analysis of urine in different diseased models will be of great use in the field of clinical metabolomics.</p>
},
	keywords = {Chromatography, Liquid, Chromatography, Reverse-Phase, Hydrophobic and Hydrophilic Interactions, Mass Spectrometry, Metabolomics, Reproducibility of Results, Urinalysis},
	issn = {1873-3778},
	doi = {10.1016/j.chroma.2016.02.080},
	author = {Ramakrishnan, Padma and Nair, Sreenath and Rangiah, Kannan}
}
