Complementary Transcriptome and Proteome Analyses Provide Insight into the Floral Transition in Bamboo (Dendrocalamus latiflorus Munro)

Most woody bamboos bloom only once after long vegetative growth phases and die immediately afterwards. It is difficult, however, to determine the timing of the floral transition, as little information is available on the molecular mechanism of plant maturity in bamboos. To uncover the bamboo floral transition mechanism, its morpho-physiological characteristics, transcriptomes and large-scale quantitative proteomes were investigated in leaves which were collected at different stages during floral transition in a woody bamboo, Dendrocalamus latiflorus. We identified many flowering time-associated genes and the continued increase and decrease genes were screened as flowering biomarker genes (e.g., the MADS14 and bHLH13 genes). These different genes were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG). And the photoperiod pathways depending on the circadian rhythm may play an essential role in the bamboo floral transition. In addition, a total of 721 differently expressed proteins of leaves from the vegetative-to-reproductive stages were identified. Fifty-five genes were specifically differentially expressed at both the transcriptomic and proteomic levels, including genes related to photosynthesis and nucleotide sugar, which may be involved in the floral transition. This work provides insights into bamboo flowers and the management of forest breeding.

Assessment of Drugs Toxicity and Associated Biomarker Genes Using Hierarchical Clustering

Background and objectives: Assessment of drugs toxicity and associated biomarker genes is one of the most important tasks in the pre-clinical phase of drug development pipeline as well as in toxicogenomic studies. There are few statistical methods for the assessment of doses of drugs (DDs) toxicity and their associated biomarker genes. However, these methods consume more time for computation of the model parameters using the EM (expectation-maximization) based iterative approaches. To overcome this problem, in this paper, an attempt is made to propose an alternative approach based on hierarchical clustering (HC) for the same purpose. Methods and materials: There are several types of HC approaches whose performance depends on different similarity/distance measures. Therefore, we explored suitable combinations of distance measures and HC methods based on Japanese Toxicogenomics Project (TGP) datasets for better clustering/co-clustering between DDs and genes as well as to detect toxic DDs and their associated biomarker genes. Results: We observed that Word’s HC method with each of Euclidean, Manhattan, and Minkowski distance measures produces better clustering/co-clustering results. For an example, in the case of the glutathione metabolism pathway (GMP) dataset LOC100359539/Rrm2, Gpx6, RGD1562107, Gstm4, Gstm3, G6pd, Gsta5, Gclc, Mgst2, Gsr, Gpx2, Gclm, Gstp1, LOC100912604/Srm, Gstm4, Odc1, Gsr, Gss are the biomarker genes and Acetaminophen_Middle, Acetaminophen_High, Methapyrilene_High, Nitrofurazone_High, Nitrofurazone_Middle, Isoniazid_Middle, Isoniazid_High are their regulatory (associated) DDs explored by our proposed co-clustering algorithm based on the distance and HC method combination Euclidean: Word. Similarly, for the peroxisome proliferator-activated receptor signaling pathway (PPAR-SP) dataset Cpt1a, Cyp8b1, Cyp4a3, Ehhadh, Plin5, Plin2, Fabp3, Me1, Fabp5, LOC100910385, Cpt2, Acaa1a, Cyp4a1, LOC100365047, Cpt1a, LOC100365047, Angptl4, Aqp7, Cpt1c, Cpt1b, Me1 are the biomarker genes and Aspirin_Low, Aspirin_Middle, Aspirin_High, Benzbromarone_Middle, Benzbromarone_High, Clofibrate_Middle, Clofibrate_High, WY14643_Low, WY14643_High, WY14643_Middle, Gemfibrozil_Middle, Gemfibrozil_High are their regulatory DDs. Conclusions: Overall, the methods proposed in this article, co-cluster the genes and DDs as well as detect biomarker genes and their regulatory DDs simultaneously consuming less time compared to other mentioned methods. The results produced by the proposed methods have been validated by the available literature and functional annotation.