Natural and Unanticipated Modifiers of RNAi Activity in Caenorhabditis elegans

Organisms used as model genomics systems are maintained as isogenic strains, yet evidence of sequence differences between independently maintained wild-type stocks has been substantiated by whole-genome resequencing data and strain-specific phenotypes. Sequence differences may arise from replication errors, transposon mobilization, meiotic gene conversion, or environmental or chemical assault on the genome. Low frequency alleles or mutations with modest effects on phenotypes can contribute to natural variation, and it has proven possible for such sequences to become fixed by adapted evolutionary enrichment and identified by resequencing. Our objective was to identify and analyze single locus genetic defects leading to RNAi resistance in isogenic strains of Caenorhabditis elegans. In so doing, we uncovered a mutation that arose de novo in an existing strain, which initially frustrated our phenotypic analysis. We also report experimental, environmental, and genetic conditions that can complicate phenotypic analysis of RNAi pathway defects. These observations highlight the potential for unanticipated mutations, coupled with genetic and environmental phenomena, to enhance or suppress the effects of known mutations and cause variation between wild-type strains.     

A Two-Level Computation Model Based on Deep Learning Algorithm for Identification of piRNA and Their Functions via Chou’s 5-Steps Rule

International Journal of Peptide Research and Therapeutics - Piwi interacting RNA (piRNA) molecules belong to a largest class of small non coding RNA molecules which are originally discovered in...     

Screening of Synthetic Isoxazolone Derivative Role in Alzheimer’s Disease: Computational and Pharmacological Approach

Neurochemical Research - Alzheimer's disease (AD) is age-dependent neurological disorder with progressive loss of cognition and memory. This multifactorial disease is characterized by...     

Growth and Physiology of Maize (Zea mays L.) in a Nickel-Contaminated Soil and Phytoremediation Efficiency Using EDTA

Journal of Plant Growth Regulation - Nickel (Ni) element is strongly phytotoxic at high concentrations for several plants, but due to its dual behavior and complicated chemistry, it has received...     

In-vitro and In-vivo management of Meloidogyne incognita (Kofoid and White) Chitwood and Rhizoctonia bataticola (Taub.) Butler in cotton using organic’s

Root-knot nematodes Meloidogyne incognita (Kofoid and White) Chitwood and Rhizoctonia bataticola (Taub.) Butler, fungus, are very dangerous root damaging pathogens. Present study was planned to establish a chemical control of these root deteriorating pathogens under lab conditions as well as in field. Maximum death rate of nematode juveniles and minimum numbers of nematode eggs hatched were recorded in plates treated with Cadusafos (Rugby® 100G) @12 g/100 ml and Cartap® (4% G) @9g/100 ml. Chemical treatment of Rhizoctonia bataticola with Trifloxystrobin + Tebuconazole (Nativo®) @0.2 g/100 ml and Mancozeb + Matalaxyl (Axiom) @0.25 g/100 ml significantly controlled the mycelial growth in plates. The best treatments tested in laboratory were applied in field as protective and curative treatments. Results proved that chemical control of root-knot nematode and root rot fungi by tested chemicals at recommended time and dose is a significant management technique under field conditions.     

DENS: data center energy-efficient network-aware scheduling

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The existing work in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, named DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network).     

A survey on Green communications using Adaptive Link Rate

The Information and Communication Technology sector is considered to be a major consumer of energy and has become an active participant in Green House Gas emissions. Lots of efforts have been devoted to make network infrastructure and network protocols power-aware and green. Among these efforts, Adaptive Link Rate (ALR) is one of the most widely discussed approaches. This survey highlights the most recent ALR approaches with a brief taxonomy and the state of the art.     

A two-phase heuristic for the energy-efficient scheduling of independent tasks on computational grids

The sensitivity analysis of a Cellular Genetic Algorithm (CGA) with local search is used to design a new and faster heuristic for the problem of mapping independent tasks to a distributed system (such as a computer cluster or grid) in order to minimize makespan (the time when the last task finishes). The proposed heuristic improves the previously known Min-Min heuristic. Moreover, the heuristic finds mappings of similar quality to the original CGA but in a significantly reduced runtime (1,000 faster). The proposed heuristic is evaluated across twelve different classes of scheduling instances. In addition, a proof of the energy-efficiency of the algorithm is provided. This convergence study suggests how additional energy reduction can be achieved by inserting low power computing nodes to the distributed computer system. Simulation results show that this approach reduces both energy consumption and makespan.     

Comparative Efficacy of Weed Control Practices for Parthenium Weed and Sunflower Crop under Varying Tillage Systems

Parthenium poses serious threat to modern crop production system and necessitate evaluating control practices for its effective management. Efficacy of different weed control practices for controlling parthenium was explored in conventional and deep tillage systems in the field conditions. Hand hoeing (20 and 35 days after emergence), S-Metolachlor (pre-emergence herbicide), sorghum straw mulch @ 5 tons ha^-1 and combination of hand hoeing and sorghum straw mulch (hand hoeing at 20 and straw mulch at 35 days after emergence) were used as weed control practice. Weedy check where no weed control measure was applied was also included in this experiment for comparison. Results concluded that the all weed management treatments significantly reduced parthenium density, its fresh and dry biomass during both the years of study as compared to weedy check. Maximum sunflower achene yield was recorded in hand hoeing (20 and 35 days after emergence) in combination with deep tillage. So, mold bold plough used for the purpose of deep tillage should be encouraged for better control of parthenium and higher achene yield of sunflower crop (3293.3 kg ha^-1 in 2017 and 3221.3 kg ha^-1 in 2018). Moreover, is also inferred that total dose of herbicide might be reduced by using hoeing and mulching in an integrated way.     

LC-MS/MS-based metabolic profiling of Escherichia coli under heterologous gene expression stress

Escherichia coli is frequently exploited for genetic manipulations and heterologous gene expression studies. We have evaluated the metabolic profile of E. coli strain BL21 (DE3) RIL CodonPlus after genetic modifications and subjecting to the production of recombinant protein. Three genetically variable E. coli cell types were studied, normal cells (susceptible to antibiotics) cultured in simple LB medium, cells harboring ampicillin-resistant plasmid pET21a (+), grown under antibiotic stress, and cells having recombinant plasmid pET21a (+) ligated with bacterial lactate dehydrogenase gene grown under ampicillin and standard isopropyl thiogalactoside (IPTG)-induced gene expression conditions. A total of 592 metabolites were identified through liquid chromatography-mass spectrometry/mass spectrometry analysis, feature and peak detection using XCMS and CAMERA followed by precursor identification by METLIN-based procedures. Overall, 107 metabolites were found differentially regulated among genetically modified cells. Quantitative analysis has shown a significant modulation in DHNA-CoA, p-aminobenzoic acid, and citrulline levels, indicating an alteration in vitamin K, folic acid biosynthesis, and urea cycle of E. coli cells during heterologous gene expression. Modulations in energy metabolites including NADH, AMP, ADP, ATP, carbohydrate, terpenoids, fatty acid metabolites, diadenosine tetraphosphate (Ap4A), and l -carnitine advocate major metabolic rearrangements. Our study provides a broader insight into the metabolic adaptations of bacterial cells during gene manipulation experiments that can be prolonged to improve the yield of heterologous gene products and concomitant production of valuable biomolecules.