De novo development and characterization of polymorphic microsatellite markers in a schilbid catfish, <Emphasis Type="Italic">Silonia silondia</Emphasis> (Hamilton, 1822) and their validation for population genetic studies

The stock characterization of wild populations of Silonia silondia is important for its scientific management. At present, the information on genetic parameters of S. silondia is very limited. The species-specific microsatellite markers were developed in current study. The validated markers were used to genotype individuals from four distant rivers. To develop de novo microsatellite loci, an enriched genomic library was constructed for S. silondia using affinity–capture approach. The markers were validated for utility in population genetics. A total number of 76 individuals from four natural riverine populations were used to generate data for population analysis. The screening of isolated repeat sequences yielded eleven novel polymorphic microsatellite loci. The microsatellite loci exhibited high level of polymorphism, with 6–24 alleles per locus and the PIC value ranged from 0.604 to 0.927. The observed (Ho) and expected (He) heterozygosities ranged from 0.081 to 0.84 and 0.66 to 0.938, respectively. The AMOVA analysis indicated significant genetic differentiation among riverine populations (overall F_ST = 0.075; P < 0.0001) with maximum variation (92.5 %) within populations. Cross-priming assessment revealed successful amplification (35–38 %) of heterologous loci in four related species viz. Clupisoma garua, C. taakree, Ailia coila and Eutropiichthys vacha. The results demonstrated that these de novo polymorphic microsatellite loci are promising for population genetic variation and diversity studies in S. silondia. Cross-priming results indicated that these primers can help to get polymorphic microsatellite loci in the related catfish species of family Schilbidae.     

Pareto-based multi-objective optimization for classification in data mining

This paper explores the possibility of classification based on Pareto multi-objective optimization. The efforts on solving optimization problems using the Pareto-based MOO methodology have gained increasing impetus on comparison of selected constraints. Moreover we have different types of classification problem based on optimization model like single objective optimization, MOO, Pareto optimization and convex optimization. All above techniques fail to generate distinguished class/subclass from existing class based on sensitive data. However, in this regard Pareto-based MOO approach is more powerful and effective in addressing various data mining tasks such as clustering, feature selection, classification, and knowledge extraction. The primary contribution of this paper is to solve such noble classification problem. Our work provides an overview of the existing research on MOO and contribution of Pareto based MOO focusing on classification. Particularly, the entire work deals with association of sub-features for noble classification. Moreover potentially interesting sub-features in MOO for classification are used to strengthen the concept of Pareto based MOO. Experiment has been carried out to validate the theory with different real world data sets which are more sensitive in nature. Finally, experimental results provide effectiveness of the proposed method using sensitive data.     

The native membrane fusion machinery in cells.

Recombinant SNAREs have been demonstrated as the minimal membrane fusion machinery. The participation of additional proteins in the regulation of membrane fusion has been suggested. In this study we provide nanometer-resolution images of native NSF oligomers and SNARE complexes isolated from neurons and the pancreas. Our study reveals the presence of new coiled rod-like structures in association with the SNARE complex only in neuronal tissue. Neuronal SNAREs were found coiled and super-coiled with these structures. The existence of NSF as pentamers in its native state is also demonstrated. The extent of coiling and super-coiling of SNAREs may regulate the potency and efficacy of membrane fusion in cells.     

Design and synthesis of new piperidone grafted acetylcholinesterase inhibitors

Alzheimer’s disease (AD) is a neurodegenerative disorder affecting 35 million people worldwide. A common strategy to improve the well-being of AD patients consists on the inhibition of acetylcholinesterase with the concomitant increase of the neurotransmitter acetylcholine at cholinergic synapses. Two series of unreported N-benzylpiperidines 5(a–h) and thiazolopyrimidines 9(a–q) molecules were synthesized and evaluated in vitro for their acetylcholinesterase (AChE) inhibitory activities. Among the newly synthesized compounds, 5h, 9h, 9j, and 9p displayed higher AChE enzyme inhibitory activities than the standard drug, galantamine, with IC₅₀ values of 0.83, 0.98, and 0.73 μM, respectively. Cytotoxicity studies of 5h, 9h, 9j, 9n and 9p on human neuroblastoma cells SH-SY5Y, showed no toxicity up to 40 μM concentration. Molecular docking simulations of the active compounds 5h and 9p disclosed the crucial role of π-π-stacking in their binding interaction to the active site AChE enzyme. The presented compounds have potential as AChE inhibitors and potential AD drugs.     

Development of 25 near-isogenic lines (NILs) with ten BPH resistance genes in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.): production,resistance spectrum,and molecular analysis

Key message

A first set of 25 NILs carrying ten BPH resistance genes and their pyramids was developed in the background of indica variety IR24 for insect resistance breeding in rice.

Abstract

Brown planthopper (Nilaparvata lugens Stal.) is one of the most destructive insect pests in rice. Development of near-isogenic lines (NILs) is an important strategy for genetic analysis of brown planthopper (BPH) resistance (R) genes and their deployment against diverse BPH populations. A set of 25 NILs with 9 single R genes and 16 multiple R gene combinations consisting of 11 two-gene pyramids and 5 three-gene pyramids in the genetic background of the susceptible indica rice cultivar IR24 was developed through marker-assisted selection. The linked DNA markers for each of the R genes were used for foreground selection and confirming the introgressed regions of the BPH R genes. Modified seed box screening and feeding rate of BPH were used to evaluate the spectrum of resistance. BPH reaction of each of the NILs carrying different single genes was variable at the antibiosis level with the four BPH populations of the Philippines. The NILs with two- to three-pyramided genes showed a stronger level of antibiosis (49.3–99.0%) against BPH populations compared with NILs with a single R gene NILs (42.0–83.5%) and IR24 (10.0%). Background genotyping by high-density SNPs markers revealed that most of the chromosome regions of the NILs (BC₃F₅) had IR24 genome recovery of 82.0–94.2%. Six major agronomic data of the NILs showed a phenotypically comparable agronomic performance with IR24. These newly developed NILs will be useful as new genetic resources for BPH resistance breeding and are valuable sources of genes in monitoring against the emerging BPH biotypes in different rice-growing countries.

     

Statistical validation of peptide identifications in large-scale proteomics using the target-decoy database search strategy and flexible mixture modeling

Reliable statistical validation of peptide and protein identifications is a top priority in large-scale mass spectrometry based proteomics. PeptideProphet is one of the computational tools commonly used for assessing the statistical confidence in peptide assignments to tandem mass spectra obtained using database search programs such as SEQUEST, MASCOT, or X! TANDEM. We present two flexible methods, the variable component mixture model and the semiparametric mixture model, that remove the restrictive parametric assumptions in the mixture modeling approach of PeptideProphet. Using a control protein mixture data set generated on an linear ion trap Fourier transform (LTQ-FT) mass spectrometer, we demonstrate that both methods improve parametric models in terms of the accuracy of probability estimates and the power to detect correct identifications controlling the false discovery rate to the same degree. The statistical approaches presented here require that the data set contain a sufficient number of decoy (known to be incorrect) peptide identifications, which can be obtained using the target-decoy database search strategy.     

Huntingtin interacting protein HYPK is intrinsically unstructured

To characterize HYPK, originally identified as a novel huntingtin (Htt) interacting partner by yeast two hybrid assay, we used various biophysical and biochemical techniques. The molecular weight of the protein, determined by gel electrophoresis, was found to be about 1.3-folds ( approximately 22 kDa) higher than that obtained from mass spectrometric analysis (16.9 kDa). In size exclusion chromatography experiment, HYPK was eluted in three fractions, the hydrodynamic radii for which were calculated to be approximately 1.5-folds (23.06 A) higher than that expected for globular proteins of equivalent mass (17.3 A). The protein exhibited predominantly (63%) random coil characteristics in circular dichroism spectroscopy and was highly sensitive to limited proteolysis by trypsin and papain, indicating absence of any specific domain. Experimental evidences with theoretical analyses of amino acids composition of HYPK and comparison with available published data predicts that HYPK is an intrinsically unstructured protein (IUP) with premolten globule like conformation. In presence of increasing concentration of Ca(2+), HYPK showed conformational alterations as well as concomitant reduction of hydrodynamic radius. Even though any link between the natively unfolded nature of HYPK, its conformational sensitivity towards Ca(2+) and interaction with Htt is yet to be established, its possible involvement in Huntington's disease pathogenesis is discussed.