Comparative population genetic structure of two Ixodidae ticks ( Ixodes ovatus and Haemaphysalis flava ) in Niigata Prefecture, Japan CURRENT STATUS: POSTED

Background Ixodid tick species such as Ixodes ovatus and Haemaphysalis flava function as important vectors of tick-borne diseases in Japan. The study of the genetic patterns of tick populations can reveal information regarding the spread of tick-borne disease. We hypothesized that I. ovatus and H. flava have different population genetic structure because of their host mobility in different tick life stages despite sharing of hosts. Methods For I. ovatus , pairwise F ST and analysis of molecular variance (AMOVA) analyses of cox1 sequences indicated significant among-population differentiation. This was in contrast to H. flava , for which there were only two cases of significant pairwise differentiation and no overall structure. A Mantel test revealed isolation by distance and there was positive spatial autocorrelation of haplotypes in I. ovatus cox1 and 16S sequences, but non-significant results were observed in H. flava in both markers. We found three genetic groups (China 1, China 2 and Japan) in the cox1 I. ovatus tree. Newly sampled I. ovatus grouped together with a published I. ovatus sequence from northern Japan and were distinct from two other I. ovatus groups that were reported from southern China.

in accordance with the manufacturer's instructions, and sequenced by Eurofin Genomics, Inc., Tokyo, Japan.

Sequence data analysis
We assembled forward and reverse reads for each individual using CodonCode Aligner ver 1. To determine if the genetic differentiation was influenced by geographical distance or altitudinal differences among populations, we performed Mantel Test in GenAlEx ver 6.51b2 [27]. Two tests per species and marker were conducted. First we compared pairwise genetic (pairwise F ST values) and geographical distances (km) and second we compared genetic distance (F ST values) with altitudinal differences (m/a.s.l.). The geographic distances were obtained from the GPS coordinates (latitude and longitude) recorded during the sampling. All Mantel tests were assessed using 9999 permutations for the significance of the correlation.
The spatial component of genetic variation was further assessed by spatial autocorrelation [28] using GenAlEx [27]. The autocorrelation coefficient (r) was computed from the geographic distance between sampling locations and the genetic distance (pairwise F ST values). This measures the genetic similarity between individual pairs within an identified distance class. The size of the distance class influences the estimation of the spatial autocorrelation. We identified the appropriate distance class based on the observed distribution of pairwise geographic distance between the sampling locations (data not shown). The distance class sizes used were the following: 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, and 320 kilometers. Bootstrap estimates of r and random permutations were set at 9999 each for the test for significance. The upper and lower error bars in the correlogram bound the 95% confidence interval of r value as identified by bootstrap resampling.
The upper and lower confidence limits bound the 95% confidence interval of the null hypothesis of no spatial structure in the data set.
The genetic relationships among the sampling locations (i.e., populations) were calculated by unweighted pair group method with the arithmetic mean (UPGMA) cluster method using the APE package [29] and R program [30] to create dendrogram using the genetic distance matrix (pairwise F ST values) generated from GenAlEx.

Phylogenetic analysis
We constructed maximum likelihood (ML) gene trees for cox1 and 16S haplotype sequences of I.
AMOVA results revealed a high among-population divergence (41.54%) in I. ovatus cox1 sequences, whereas both cox1 and 16S markers of H. flava indicated no significant genetic variation among populations ( Table 2) Table S5).
The Mantel test of I. ovatus showed evidence of isolation by geographic distance in both markers:  Abbreviations: d f degrees of freedom; ss sum of squares; Va, Vb and Vc are associate covariance

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