The unique ornamental features and extreme sexual traits of Peacock have always intrigued scientists and naturalists for centuries. However, the genomic basis of these phenotypes are yet unknown. Here, we report the first genome sequence and comparative analysis of peacock with the high quality genomes of chicken, turkey, duck, flycatcher and zebra finch. Genes involved in early developmental pathways including TGF-β, BMP, and Wnt signaling, which have been shown to be involved in feather patterning, bone morphogenesis, and skeletal muscle development, revealed signs of adaptive evolution and provided useful clues on the phenotypes of peacock. Innate and adaptive immune genes involved in complement system and T-cell response also showed signs of adaptive evolution in peacock suggesting their possible role in building a robust immune system which is consistent with the predictions of the Hamilton–Zuk hypothesis. This study provides novel genomic and evolutionary insights into the molecular understanding toward the phenotypic evolution of Indian peacock.

The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84–0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better (R2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better (R2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility, and permeability of small molecules.

The unique ornamental features and extreme sexual traits of Peacock have always intrigued the scientists. However, the genomic evidence to explain its phenotype are yet unknown. Thus, we report the first genome sequence and comparative analysis of peacock with the available high-quality genomes of chicken, turkey, duck, flycatcher and zebra finch. The candidate genes involved in early developmental pathways including TGF-β, BMP, and Wnt signaling pathway, which are also involved in feather patterning, bone morphogenesis, and skeletal muscle development, showed signs of adaptive evolution and provided useful clues on the phenotype of peacock. The innate and adaptive immune components such as complement system and T-cell response also showed signs of adaptive evolution in peacock suggesting their possible role in building a robust immune system which is consistent with the between species predictions of Hamilton-Zuk hypothesis. This study provides novel genomic and evolutionary insights into the molecular understanding towards the phenotypic evolution of Indian peacock.

No abstract

A rhodamine-based compound, 2-(2-((3-(tert-butyl)-2-hydroxybenzylidene)amino)ethyl)-3′-6′-bis(ethylamino)-2′,7′-dimethylspiro[indoline-1,9′-xanthen]-3-one, (HL-t-Bu), is reported here as a dual chemosensor for Zn 2+ and Al 3+ ions. This compound has been synthesized under mild conditions with high yield and characterized by elemental analysis and different standard spectroscopic methods. Its structure has been confirmed by single-crystal X-ray diffraction analysis. It acts as a fluorescent dual sensor for Zn 2+ and Al 3+ in 10 mM HEPES buffer in the methanol/water mixture (9:1, pH = 7.4) with wellseparated excitation and emission wavelengths. The fluorescence intensity at 457 nm of HL-t-Bu increases by ∼7 folds in the presence of 1 equiv of Zn 2+ when it is excited at 370 nm. With the excitation at 500 nm, the emission intensity of the probe at 550 nm increases massively (∼650 times) in the presence of 1 equiv of Al 3+ . No other metal has any significant effect on the enhancement of the emission intensity of the probe in the detection process for either of the metal ions. The quantum yield of HL-t-Bu enhances significantly in the presence of Zn 2+ and Al 3+ . Rhodamine derivatives are generally colorless and nonfluorescent when the spirolactam ring is closed, and they are pink in color and highly fluorescent when it exists in the ring-open form. In the presence of Al 3+ , the probe is pink and highly fluorescent, indicating that this metal ion is able to the open spirolactam ring of the probe. However, Zn 2+ is not able to open the spirolactam ring, but it is coordinated through phenolic oxygen and imine nitrogen (salicylaldehyde unit) of the Schiff base restricting PET (photoinduced electron transfer) and imposing CHEF (chelation-enhanced fluorescence) to enhance the emission intensity of the probe. 1 H NMR, FT-IR, elemental analysis, and pH-dependent studies support these mechanisms. Limit of detection values are in the nanomolar range for both the metal ions, confirming very high sensitivity of the probe. The probe has been used in cell imaging studies for both of the metal ions.