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Title

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

 

Authors

Amr TM Saeb1, 2* & Satish Kumar David2

 

Affiliation

1Department of Entomology, Ohio State University, USA; 2Information Technology Department, Strategic Center for Diabetes Research, King Saud University, Saudi Arabia

 

Email

saeb.1@osu.edu; *Corresponding authors

 

Article Type

Hypothesis

 

Date

Received June 03, 2014; Revised June 09, 2014; Accepted June 10, 2014; Published June 30, 2014

 

Abstract

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.

 

Keywords

Entomopathogenic nematodes, molecular population genetics, Genetic markers, pcox1, molecular sampling, Genetic analysis, Bioinformatics analysis.

 

Citation

Saeb & David, Bioinformation 10(6): 347-352 (2014)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.