DOI: 10.5061/dryad.p5hqbzkm7
title: Parasite turnover zone at secondary contact: a new pattern in host-parasite population genetics

description: We introduce a new pattern of population genetic structure in a
 host-parasite system that can arise after secondary contact of previously
 isolated populations. Due to different generation time and therefore
 different tempo of molecular evolution the host and
 parasite populations reach different degrees of genetic
 differentiation during their separation (e.g. in refugia). Consequently,
 during the secondary contact the host populations are able to re-establish
 a single panmictic population across the area of contact, while the
 parasite populations stop their dispersal at the secondary
 contact zone and create a narrow hybrid zone. From the host’s perspective,
 the parasite’s hybrid zone functions on a microevolutionary scale as a
 “parasite turnover zone”: while the hosts are passing from area A to area
 B, their parasites turn genetically from the area A genotypes to the area
 B genotypes. We demonstrate this novel pattern on a model
 composed of Apodemus mice and Polyplax lice by comparing maternally
 inherited markers (complete mitochondrial genomes, and complete genomes of
 vertically transmitted symbiont Legionella polyplacis) with SNPs derived
 from the louse genomic data. We discuss circumstances that may lead to
 this pattern and possible reasons why it has been overlooked in the
 studies on host parasite population genetics.
description: <em>Apodemus flavicollis</em> mice were captured
 across the HZ of <em>Polyplax serrata</em>-specific lineages
 in 2018 and 2019 in the north-west of Czech Republic, using wooden snap
 traps. Mice were searched for lice by visual checking and combing. Lice
 were removed and stored in 100% ethanol in the -20°C. Genomic DNA from
 whole louse specimens was individually extracted using the Qiagen QIAamp
 DNA Micro Kit (Qiagen, Valencia, CA, USA). Twenty six lice ((15 SE and 11
 SW)), 1 to maximum 3 from each parasitized host, were selected for genomic
 re-sequencing. Whole genome re-sequencing was performed
 to generate metagenomic data used to map the SNPs, and to assemble genomes
 of the <i>L. polyplacis</i> symbionts and mitochondrial
 minichromosomes. gDNA libraries for twenty six louse specimen were
 constructed for paired-end Illumina sequencing with NovaSeq6000
 instrument. All samples were sequenced on one Illumina Novaseq lane
 producing on average 62.5 million 150 bp paired-end reads (PE) per
 sample. The contigs corresponding to Legionella
 polyplacis were visually identified using ORF prediction done in the
 Geneious package (the prokaryotic gene arrangement could be readily
 recognized by the density of predicted ORFs). In most samples, the genome
 of <em>L. polyplacis </em>was assembled into a single complete
 contig. In three assemblies (DPH41,19JA1_SW, 46MAN_SW) the symbiont genome
 was highly fragmented or could not be found, despite the good assembly
 quality of the louse genome (these samples were removed from the L.
 polyplacis analysis). Complete <em>L. polyplacis </em>genomes
 were annotated in RAST (Aziz et al., 2008) and aligned using Mafft
 algorithm implemented in Geneious. In three samples (Ne125b_Kot_SW,
 99b_Pro_SE, 98c_Pro_SE) the rRNA region did not assemble correctly and was
 only represented by short fragments. To extend these fragments into a full
 length, we used the program aTRAM 2.0 (Allen, LaFrance, Folk, Johnson,
 & Guralnick, 2018). Phylogenetic analysis of the resulting 530,063
 bp long matrix was performed in Phyml (Guindon et al., 2010).
 Due to the conserved noncoding region shared by all
 minichromosomes, the Spades based assembly was not able to separate the
 different minichromosomes reliably. We, therefore, took an alternative
 approach. Using a single gene from each minichromosome as a reference
 (preliminary assignment of the genes to individual minichromosomes was
 based on the GenBank data available for <em>P. spinulosa</em>;
 acc. nos. KF647762-KF647771) we mapped the reads and extended the
 sequences in the program aTRAM 2.0 (Allen at al., 2018). To obtain
 annotations of the resulting sequences, we combined two methods. The first
 method utilized the web based server Mitos (Bernt et al., 2013). Since
 this method missannotated or entirely missed some of the genes, we
 corrected the results by a  blast based approach, taking advantage of the
 available annotated mitochondrial genome from <em>P.
 spinulosa</em>. We combined assembled minichromosome sequences into
 a custom database of<em> P. serrata </em>and used the 37 genes
 of <em>P. spinulosa </em>as blast queries (we run discontinous
 megablast and tblastx, both with E-value set to 10). We then aligned the
 <em>P. serrata </em>minichromosome sequences together with
 <em>P. asiatica </em>and <em>P. spinulosa
 </em>using Mauve (Darling, Mau, Blattner, & Perna, 2004).
 These alignments were used as a background for combining and correcting
 the annotations.