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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Invasive Insect Biocontrol & Behavior Laboratory » Research » Research Project #436386

Research Project: Molecular Genetics Analysis of White-Footed Mouse Populations to Understand Host-Tick-Pathogen Interactions

Location: Invasive Insect Biocontrol & Behavior Laboratory

Project Number: 8042-32000-012-19-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: May 1, 2019
End Date: Sep 30, 2021

Objective:
The main objective of this project is to use molecular genetics tools to understand rodent-tick-pathogen interactions to aid development of more effective host(rodent)-targeted tick control technologies/products. Specific goals include (1) to investigate movements of white-footed mice at different ecological niches by analyzing the molecular markers of the mouse populations; (2) to investigate the effect of geographical barriers on the genetic structure of white-footed mouse populations; (3) to investigate the effect of pathogen infection kinetics in relation to the genetic diversity of white-footed mice; and (4) to investigate the effect of tick abundance in relation to genetic diversity of white-footed mice.

Approach:
Species determination: The DNA extracted from the white-footed mice (P. lecuopus) will be used as a template to amplify mitochondrial COIII sequence. These amplified DNA fragments will then be sent to SUNY Upstate’s Molecular Genomics Core facility for sequencing. The sequences will be compared against NCBI GenBank database and only those samples that correspond to P. lecuopus will be used in this study. Microsatellite genotyping and genetic diversity analysis: To understand the genetic diversity in the white footed mice and to understand its correlation with the geographic distance, tick load and pathogen infection status, we will analyze 11 well defined microsatellite markers: PMl01, PMl03, PMl04, PMl05, PMl06, PMl09, PMl11, PMl12, PLGT58, PLGT66, and PLGATA70. Nucleotide primers will be designed to amplify these markers. The amplified products will be sent to the SUNY Upstate Molecular Genomics facility for genotyping. The genotype analysis of all the alleles will be analyzed by GeneMarker. Genetic variation within the population will be analyzed by testing for linkage disequilibrium, for departure from Hardy-Weinberg equilibrium and computing expected (HE) and observed heterozygosity (HO) using GENEPOP 4.0. Allelic richness (A), the number of private alleles (p) and the mean number of alleles per locus within each population (k) will be computed using FSTAT 2.9.2. MICROCHECKER 2.2.3 will be used to detect scoring errors and genotyping artifacts in the data. GENPOP 4.0 will be used to estimate genetic diversity by testing linkage disequilibrium Population genetic structure analysis: We will use STRUCTURE, a freely available program for population analysis that analyses the differences in the distribution of genetic variants amongst populations with the assumption that the population share a similar pattern of variation. Information (sampling location, behavior and ecology: tick load and infection status) about the white footed mice population will be added to this program to further refine the analysis. Fisher’s exact tests will be performed on the 11 microsatellite loci using GENEPOP 4.0 to determine the significant differences in allele frequencies between populations. Genetic differentiation of populations will also be evaluated by calculating pairwise FST values using Arlequin 3.5; significance levels were assessed through a permutation test with 1000 iterations. To assess the effect of geographical distances on the genetic structure of mouse populations, we will carry out an isolation-by-distance analysis using IBDWS 2.3 with 10,000 permutations. Information on sampling location, tick load, and infection status of each mouse will be added to this program to further understand dispersal barriers. Tick feeding, infection prevalence and genetic diversity: Multiple genetic analysis software programs will be used to assess the effect of infection prevalence on the genetic diversity of white-footed mice. Information on the number of ticks collected from each mouse will be incorporated in this analysis to further refine our understanding on rodent-tick-pathogen interactions.