Comparative Estimation of Genetic Diversity in Population Studies using Molecular Sampling and Traditional Sampling Methods

Entomopathogenic nematodes (EPN) are efficient biological pest control agents. Population genetics studies on EPN are seldom known. Therefore, it is of interest to evaluate the significance of molecular sampling method (MSM) for accuracy, time needed, and cost effectiveness over traditional sampling method (TSM). The study was conducted at the Mohican Hills golf course at the state of Ohio where the EPN H. bacteriophora has been monitored for 18 years. The nematode population occupies an area of approximately 3700 m² with density range from 0.25-2 per gram soil. Genetic diversity of EPN was studied by molecular sampling method (MSM) and traditional sampling method (TSM) using the mitochondrial gene pcox1. The MSM picked 88% in compared to TSM with only 30% of sequenced cox 1 gene. All studied genetic polymorphism measures (sequence and haplotype) showed high levels of genetic diversity of MSM over TSM. MSM minimizes the chance of mitochondrial genes amplification from non target organisms (insect or other contaminating microorganisms). Moreover, it allows the sampling of more individuals with a reliable and credible representative sample size. Thus, we show that MSM supersedes TSM in labour intensity, time consumption and requirement of no special experience and efficiency.     

Development of a cost-effective high-throughput process of microsatellite analysis involving miniaturized multiplexed PCR amplification and automated allele identification

Background

Microsatellites are nucleotide sequences of tandem repeats occurring throughout the genome, which have been widely used in genetic linkage analysis, studies of loss of heterozygosity, determination of lineage and clonality, and the measurement of genome instability or the emergence of drug resistance reflective of mismatch repair deficiency. Such analyses may involve the parallel evaluation of many microsatellite loci, which are often limited by sample DNA, are labor intensive, and require large data processing.

Results

To overcome these challenges, we developed a cost-effective high-throughput approach of microsatellite analysis, in which the amplifications of microsatellites are performed in miniaturized, multiplexed polymerase chain reaction (PCR) adaptable to 96 or 384 well plates, and accurate automated allele identification has been optimized with a collective reference dataset of 5,508 alleles using the GeneMapper software.

Conclusions

In this investigation, we have documented our experience with the optimization of multiplex PCR conditions and automated allele identification, and have generated a unique body of data that provide a starting point for a cost-effective, high-throughput process of microsatellite analysis using the studied markers.

     

Multiple, non-allelic, intein-coding sequences in eukaryotic RNA polymerase genes

Background  

Inteins are self-splicing protein elements. They are translated as inserts within host proteins that excise themselves and ligate the flanking portions of the host protein (exteins) with a peptide bond. They are encoded as in-frame insertions within the genes for the host proteins. Inteins are found in all three domains of life and in viruses, but have a very sporadic distribution. Only a small number of intein coding sequences have been identified in eukaryotic nuclear genes, and all of these are from ascomycete or basidiomycete fungi.     

Phosphorylation and biosynthesis of high molecular weight proteins of tumor nuclear matrix

INTRODUCTIONAsearlyasin1948wehavefr8CtionatedisolatednucleifromnormalandtumorcellsbyextractionwithiMNaCIanddilutealkali[1].Thenuclearresiduewasthenstudiedmorethoroughly[2,3].Lateron,sillillarproteinousnuclearresidueswereisolatedbyotherworkers[46]andasstud…     

A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization

Background  

G protein-coupled receptors (GPCRs) represent a family of well-characterized drug targets with significant therapeutic value. Phylogenetic classifications may help to understand the characteristics of individual GPCRs and their subtypes. Previous phylogenetic classifications were all based on the sequences of receptors, adding only minor information about the ligand binding properties of the receptors. In this work, we compare a sequence-based classification of receptors to a ligand-based classification of the same group of receptors, and evaluate the potential to use sequence relatedness as a predictor for ligand interactions thus aiding the quest for ligands of orphan receptors.