Flavobacterium columnare, is one of the most prevalent fish diseases worldwide. An exceptionally high level of genetic diversity among isolates of F. columnare has long been recognized, whereby six established genomovars have been described to date. However, little has been done to quantify or characterize this diversity further in a systematic fashion. The objective of this research was to perform phylogenetic analyses of 16S rRNA and housekeeping gene sequences to decipher the genetic diversity of F. columnare. Fifty isolates and/or genomes of F. columnare, originating from diverse years, geographic locations, fish hosts, and representative of the six genomovars were analyzed in this study. A multilocus phylogenetic analysis (MLPA) of the 16S rRNA and six housekeeping genes supported four distinct F. columnare genetic groups. There were associations between genomovar and genetic group, but these relationships were imperfect indicating that genomovar assignment does not accurately reflect F. columnare genetic diversity. To expand the dataset, an additional 90 16S rRNA gene sequences were retrieved from GenBank and a phylogenetic analysis of this larger dataset also supported the establishment of four genetic groups. Examination of isolate historical data indicated biological relevance to the identified genetic diversity, with some genetic groups isolated preferentially from specific fish species or families. It is proposed that F. columnare isolates be assigned to the four genetic groups defined in this study rather than genomovar in order to facilitate a standard nomenclature across the scientific community. An increased understanding of which genetic groups are most prevalent in different regions and/or aquaculture industries may allow for the development of improved targeted control and treatment measures for columnaris disease.Columnaris disease, caused by the Gram-negative bacterium  Flavobacterium columnare, is a prevalent disease of fish due to an ability to infect most freshwater species in a range of environmental temperatures. The disease was first described in the early 1900s and clinical signs include lethargy, loss of appetite, necrotic gills, depigmented and necrotic lesions of the skin, and necrotic or frayed fins. Upon the discovery of this disease, it was suggested to be a significant pathogen due to an ability to infect numerous fish species . The first whole genome sequence of F. columnare was published in 2012 (F. columnare (described further below). Their research suggested that the core genomes were mostly conserved, but the isolates were genetically distinct as defined by in silico DNA–DNA hybridization methods. F. columnare isolates and that phylogenetic resolution is affected by the methods used to compare isolates.Following these original reports of genetic diversity, numerous studies have analyzed isolates from various locations using different molecular approaches such as random amplified polymorphic DNA (RAPD), pulsed-field gel electrophoresis (PFGE), amplified fragment length polymorphism (AFLP), single-strand conformation polymorphism (SSCP), repetitive extragenic palindromic PCR (REP-PCR), multilocus sequence analysis (MLSA), and sequencing of the 16S rRNA gene and 16S–23S intergenic spacer region. The results from these studies are strikingly similar in that most indicate at least two different groups among  in 2012  and subs in 2012  allowingF. columnare genetic diversity. To begin to understand the genetic diversity of F. columnare, we first standardized the 16S-RFLP technique  with previously assigned genomovars.It is well known that development of control methods and vaccines can be complicated by genetic diversity of bacterial pathogens. In regards to vaccines, genetic diversity can result in antigenic variation that may render vaccines ineffective against heterologous isolates . The difechnique  developeisolates . More reisolates . With thF. columnare, originating from diverse years, geographic locations, and fish hosts, were analyzed in this study (Tables 3). Of these, 26 (Table 2) were cultured from archive laboratory stocks, and extracted DNA was used to sequence genes of interest as described below. Eleven publicly available genomes and thirteen additional genomes  were used to obtain DNA sequences from annotated genomes. The identity of isolates was confirmed by PCR using species specific primers as described by Fifty isolates and/or genomes of Bacterial genomic DNA (gDNA) was extracted from isolates using the DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer’s protocol for Gram-negative bacteria and quantified using a NanoDrop ND-1000 spectrophotometer (NanoDrop). Each isolate was assigned to genomovar as described by F. columnare, in which the primers were designed from the DNA sequence of a genomovar I isolate (ATCC 49512). In the present study, the same six housekeeping genes were used for a MLPA, including trpB, gyrB, dnaK, tuf, atpA, and rpoD. To ensure primer specificity for isolates assigned to different genomovars, these gene sequences were extracted from 13 draft genomes  and analyzed. For each gene, a multiple sequence alignment was performed using CLC Genomics Workbench (version 9.5.2) and the primer binding sites designed by Table 4).F. columnare isolate (Table 2) by PCR using the primers designed in this study or previously published (Table 4). PCR was performed with AccuPrime Pfx DNA polymerase (Invitrogen), and the final concentrations of each component in the 50 μL reaction mixture were as follows: 5 μL 10X AccuPrime Pfx reaction mix, 0.4 μM forward and reverse primer, 1 unit AccuPrime Pfx DNA polymerase and 25 ng total gDNA. PCR amplification was performed with a MyCycler thermal cycler (Bio-Rad) using a cycling protocol as follows: 1 cycle of 5 min at 95°C; 30–40 cycles of 30 s at 95°C, 20 s at 45–62°C and 45 s at 68°C; and a final cycle of 10 min at 68°C. Different numbers of PCR cycles and annealing temperatures were used for each primer pair (Table 4). Following amplification, PCR products were detected by subjecting 5 μL of the PCR reaction to 1.5% (w/v) agarose gel electrophoresis in Tris-acetate-EDTA (TAE buffer). Gels were precast with 1X SYBR Safe DNA gel stain (Invitrogen), and the products were visualized using ultraviolet transillumination. PCR products were purified using the QIAquick PCR Purification Kit (Qiagen) and were sequenced commercially (Eurofins Genomics) using the same primers used for PCR. Sequence reads were assembled into contigs using BioNumerics , and sequences were verified by manually examining chromatograms. The sequences for the gyrB, tuf, dnaK, rpoD, atpA, and trpB genes were deposited into GenBank under accession numbers MG516221–MG516454 and the 16S rRNA gene sequences were deposited under accession numbers MG516944–MG516975.The 16S rRNA and each of the six housekeeping genes were amplified from each F. columnare (Table 2), sequences extracted from F. columnare genomes (Table 3), and sequences from F. psychrophilum and F. johnsoniae were aligned and trimmed using the Molecular Evolutionary Genetics Analysis (MEGA6) software , sequences extracted from annotated F. columnare genomes (Table 3), and sequences from F. psychrophilum and F. johnsoniae were aligned and trimmed using MEGA6. The six gene sequences from each individual isolate were then concatenated and used to infer the evolutionary relatedness by using the maximum likelihood method based upon the general time reversible model . From these, multiple sequences were removed because Basic Local Alignment Search Tool  analysis indicated they were not related to F. columnare. Sequences less than 1,000 nucleotides were omitted as were duplicate sequences of the same isolate. A total of 90 sequences were obtained that met these criteria and were added to the 50 sequences described above for phylogenetic analysis  as described above. There were a total of 1,061 positions in the final dataset, the final tree was constructed from 1,000 bootstrap replicates, and rooted with F. psychrophilum and F. johnsoniae.An additional 16S rRNA gene phylogeny was performed. All available  BLASTn;  at the NF. columnare genetic diversity using phylogenetic analyses. In order to be inclusive, a diverse panel of isolates was collected from broad geographical regions, different fish species, and across a range of years. Additionally, it was important to include isolates assigned to the six established genomovars of F. columnare in order to use assigned genomovars as the basis to compare phylogenies derived from DNA sequences. Therefore, 12 genomovar I, 3 genomovar I/II, 22 genomovar II, 1 genomovar II-A, 2 genomovar II-B, and 10 genomovar III isolates were included and encompassed a large degree of diversity as indicated above (Tables 3).The objective of the present study was to decipher Figure 1). There was an association between genomovar and genetic group, but this association was imperfect. Genetic group 1 was comprised of all genomovar I isolates and the genomovar I/II isolate, F4-HK. Genetic group 2 was comprised of a portion of the genomovar II isolates, the only genomovar II-A isolate (CC1351), and the two genomovar II-B isolates. Genetic group 3 was comprised of all genomovar III isolates and two genomovar I/II isolates. Within genetic group 3, the two genomovar I/II isolates, TI2063 and 1215, formed a separate supported group with strong bootstrap support (98). Genetic group 4 was comprised of all the remaining genomovar II isolates. Within genetic group 4, two isolates, BZ-1-02 and BZ-5-02, formed a separate group with strong bootstrap support (100). Although there were four distinct genetic groups, the presence of the two supported sub-groups within genetic groups 3 and 4, may indicate the existence of additional genetic groups. Three of the genetic groups described above contained members from more than one genomovar as assigned by 16S-RFLP. These results indicate the 16S-RFLP method may not accurately reflect the genetic diversity in the 16S rRNA gene sequences of F. columnare. This may be explained by the nature of this technique which only interrogates sequence variation at restriction sites. Similar results were suggested by The 16S rRNA gene sequences from these isolates were obtained by sequencing or were downloaded from publicly available and unpublished genomes. Phylogenetic analysis of these sequences resulted in the establishment of four distinct genetic groups as evidenced by bootstrap values >70  and there was 100% agreement in the placement of isolates into each genetic group between the analysis of the 16S rRNA genes and the MLPA. Moreover, each genetic group was robustly supported as distinct from all other genetic groups as evidenced by bootstrap values >70. Additionally, there was a greater level of sequence heterogeneity in the MLPA analysis compared to the 16S rRNA phylogeny, as expected. However, the supported subgroups within genetic groups 3 and 4 that were present in the 16S rRNA gene phylogeny were not present in the MLPA phylogeny, which suggests these subgroups are not unique genetic groups.The MLPA analysis of the concatenated housekeeping gene sequences also resulted in the establishment of four distinct genetic groups , and all basal nodes within the dendrogram were also highly supported . Thus the dnaK gene may represent an optimal locus to assign F. columnare isolates to a genetic group. Analysis of the rpoD gene sequences resulted in robust support for each genetic group; however, three genetic group 1 isolates  could not be ascribed to this genetic group via this locus  formed a separate clade  were included with the 50 sequences of the present study for phylogenetic analysis. Similar to the previous phylogenetic analyses, analysis of these sequences resulted in the establishment of four distinct genetic groups as evidenced by bootstrap values >70. . F. columnare. These authors also generated a whole genome phylogenetic tree based on concatenated single nucleotide polymorphisms (SNPs) of the core genomes and the resultant tree topology was different from both the 16S rRNA and multilocus sequence phylogenies. Additionally, there were variable topologies upon phylogenetic analyses of the individual housekeeping genes in the present study . The use of low variation and higher variation genes likely contribute to the topology inconsistencies observed between markers. Due to the observation of variable topologies following phylogenetic analyses of different markers in the present and previous studies, future research should critically analyze whole genome sequences and construct genome based phylogenies to gain a better understanding of how these genetic groups were established as was recently published with F. psychrophilum . For example the phylogenetic analysis of the 16S rRNA gene sequences placed genetic group 3 isolates as a sister group to all other genetic groups, while the analysis of the concatenated housekeeping genes placed genetic group 4 as the sister group  and subsequent phylogenetic analysis that includes both the isolate(s) of interest and sequences belonging to each of the four genetic groups. This can be laborious and time consuming, so our laboratory is currently developing a specific multiplex PCR that can assign an unknown F. columnare isolate to genetic group in a single PCR. This assay will facilitate standard nomenclature for the genetically disparate groups within F. columnare across the scientific community, a matter of importance given the worldwide distribution of this important fish pathogen and the need for universally comparable genetic typing schemes. Recent analyses of F. columnare genomes further illustrate the importance of this. For example, F. columnare genomes and suggested that species designation of F. columnare may need to be amended. Their phylogenetic analyses are consistent with those of the present study and identified four distinct clusters. Additionally, they determined the digital DNA–DNA hybridization (dDDH) values between the genomes of isolates they sequenced as well as publicly available F. columnare genomes. In the context of this study, comparison of the genomes between isolates corresponding to the different genetic groups 1, 2, 3, and 4, resulted in dDDH values of less than 43% (F. columnare (genetic group 1) and three additional species . Additional research is needed to determine whether these are unique species of bacteria or different genetic types of the same species of bacteria.Study findings highlight the existence of four phylogenetically distinct genetic groups within the species than 43% . These dthan 43% . TherefoF. columnare 16S rRNA gene sequences, some interesting associations were found between genetic groups, the family of fish from which the isolate was recovered, and country of origin. For genetic group 1, the majority of isolates were recovered from the families Salmonidae (44.4%), Cyprinidae (16.7%), and Ictaluridae  in North and South America, Asia, and Europe. The association between genomovar I isolates  and salmonids was previously noted (Oncorhynchus mykiss) and the results clearly demonstrated genetic group 1 isolates were more virulent than isolates in genetic groups 2 and 3. Salmonids are cold water fish species, and early research demonstrated that genomovar I isolates  were the only isolates capable of growth at 15°C  for each of the 140 isolates included in the 16S rRNA phylogeny were retrieved from GenBank and/or publications  from North America and Asia. For genetic group 3, which contained the lowest number of isolates (n = 16), the majority of isolates were recovered from the families Ictaluridae (37.5%) and Cichlidae  from North America, Asia, and Africa. Ictalurus punctatus). The research demonstrated that genetic group 2 isolates were extremely virulent, with mortality greater than 60% for all isolates tested and the genetic group 1 isolates were less virulent. However, Figure 4 and Supplementary Figure For genetic group 2, the majority of isolates were recovered from the families Ictaluridae (21.9%), Cyprinidae (18.8%), Pangasiidae (15.6%), and Percichthyidae  in the family Cichlidae . These isolates were recovered from infected fish in South America, Central America, and Asia. Figure 4 and Supplementary Figure F. columnare isolates, mostly of United States origin, and thus far none have been assigned to genetic group 4.For genetic group 4, all isolates, with the exception of one were recovered from tilapia (F. columnare and demonstrate that 16S-RFLP and genomovar assignment does not accurately reflect this genetic diversity. Therefore, we propose that isolates be assigned to the genetic groups defined in this study rather than genomovar to facilitate a standard nomenclature across the scientific community. Analysis of the historical data of the isolates utilized indicates there is biological relevance to the genetic diversity identified. Thus, increased knowledge on the genetic groups of F. columnare that are most prevalent in different regions and/or aquaculture industries may allow for the development of better targeted control and treatment measures for columnaris disease.The results from this research establish the existence of four phylogenetically distinct genetic groups within the species BL conceived the research, analyzed the DNA sequence data, performed the phylogenetic analyses, interpreted the data, and prepared the manuscript. JG managed the bacterial isolates, performed DNA extraction, PCR, and RFLP. GW and JE assisted with sequencing and data analysis. TL and ML assisted with the interpretation of the phylogenetic data. FW and SC assisted with bacterial isolate management. All authors contributed to manuscript revision, and read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Creating healthy cities promotes socio-economic development, thus, the creation of such cities has been receiving more attention from the Chinese government and the Chinese people. In the current study, the intention was to conduct a comprehensive evaluation of the creation of healthy cities in Henan province in central China.We randomly selected 18 cities  in middle regions of China in 2013 and established evaluation indices to evaluate the beneficial effects by horizontal and vertical comparison analyses.Creating the healthy cities promoted health service, economic development, spiritual and ecological success. This was achieved by constructing cities and changing work style among the officials and establishment of patriotic health organizations.This is the first comprehensive, in-depth, appraisal of the healthy cities in China. We suggest that creating the healthy cities should be promoted a larger extend world-wide since it is beneficial at many levels. The concept of the healthy city was first promulgated by the World Trade Organization in 1988 .Statistical analysis revealed that the average life expectancy of the residents in healthy cities was 77.81±2.13 yr compared with 73.78± 3.23 yr in non-healthy cities, difference was statistically significant (P<0.05). In 2012, the morbidity in healthy cities was 369.12/100000 persons, compared to 527.74/100000 persons in non-healthy cities. National healthy cities made greater efforts to prevent and treat chronic diseases, usually with a comprehensive prevention and control strategies in demonstration areas. The rate of residents in healthy cities who engage in active exercise have a low-salt diet, quit smoking and alcohol intake control were 47.6%, 27.6%, and 13.2%, respectively, while in non-healthy cities it were 32.2%, 18.4% and 32.2%, respectively. There was a statistically significant difference (P<0.05). The proportion of residents with knowledge of chronic disease prevention and control as outstanding, good, ordinary, and poor levels were are 19.7%, 21.6%, 33.2% and 25.5%, respectively, while that in non-healthy cities were 8.2%, 11.4%, 37.6% and 42.8% respectively; there was a statistical significance in the level of outstanding, good and poor (P<0.05). Finally, national healthy cities have better institutions and organizations for disease prevention and control, better staffs, and more resources than non-healthy cities.The incidence of infectious diseases in healthy cities was lower than that in non-healthy cities  of national healthy cities in Henan province was 85.2 billion and 213.1 billion, respectively in 2006 and 2012. In non-healthy cities, it was 59.2 billion and 136.2 billion, less than in the national healthy cities. Vertical comparison in a city indicated that the economic growth rate was 16.2% before it was established as a healthy city, and it rose to 18.6% after being designated as a healthy city. One reason for the rapid economic growth in national healthy cities was the improvement of investment in environment, which was favorable for attracting business investment.P<0.05).The establishment of a healthy city is the basis for the construction of the civilized city. Health is a most important factor in evaluating whether a city is civilized. There are 2 national healthy cities in Henan province, 4 nominated national healthy cities and 5 provincial civilized cities, all of which built into healthy cities before their nomination. The course of construction to healthy cities is the process of raising the level of modern management, improving civilization and hygienic quality in the city .Environmental pollution control was improved in healthy cities. The rate of household garbage and centralized urban sewage processing to hazard-free were 96.27% and 96.96%, respectively. While the rate in non-healthy cities was 78.83% and 80.48%, that was significantly less than that in healthy cities. The effect of water quality protection was also greatly improved in national healthy cities. The water quality in centralized drinking water source was 100% of the national standards based on the environmental quality of surface water and groundwater quality standards. The greening level was also significantly improved. In national healthy cities, the percentage of greening coverage was 42.3%, greening rate was 38.4%, and green areas per capita in public parks were 10.12 mThe deficiencies of the city during the construction of healthy cities were significantly improved. Usually, the urban village, the rural-urban continuum, the back street and the farmer’s market were the most disorganized and dirty spaces in the cities making these cities more vulnerable to urban decay . The livThe construction of healthy cities promoted the active learning among the officials because it brought together many aspects including law, policies, and regulations ,8. This In 7 national healthy cities, there were total 198 employees who were working for patriotic health institutions, 28 persons in each city on average, while only total 71 staffs and 7 on average in 11 national non-healthy cities. Meanwhile, the funds, tasks, and responsibilities were further intensified and defined in the patriotic health offices of national healthy cities.The construction of the healthy city in China began in 1980s, and at the same time, WHO advocated and launched the campaign of constructing the healthy cities. This was regarded as a global strategic goal. There are two main differences between the healthy city of China and WHO, one of which is the scope of the index system. The aim of healthy city in China is to govern the environment of dirty and disorderly cities and to raise the citizens’ awareness of civilization and health. There are 61 specific indicators to evaluate a healthy city in China, all of which are of clear quantitative requirements. In contrast, the concept of the healthy city of WHO is broader with greater importance given to the factors affecting sanitation and the health of the residents, and there are no strict regulations or requirements; the indicators are only instructive. In addition, healthy cities in China are subject to the review of application materials, unannounced visits, and field technology evaluation by the government organizations before being finally nominated as the healthy city by the country. It pays attention both to the process and the outcome. By contrast, WHO advocates and encourages each city to struggle for a healthy city, without evaluation or nomination. The primary manner of assessment is self-assessment and it only focuses on the process.This is the first comprehensive evaluation since its inception of the healthy city construction 25 yr ago in China. The benefits are obvious at multiple levels , particularly in terms of strengthening the effects on health, local political administrative system and public policies.Currently, a program by Chinese Government to control the environmental pollution and improve public health has been instituted. The importance and urgency of organizing the patriotic health campaign are redefined and more requirements that are stringent were put in place. Patriotic health legislation work, theoretical research and propaganda work, the rural areas’ creating work, self-construction and long-term management are all expected to be strengthened in the future.Community participation and empowerment in the healthy cities program will be improved . InterseOur investigation and evaluation of the healthy city construction in China shed light on the beneficial effects in terms of promoting health level, economic development spiritual and ecological civilization, city construction, cadre style, as well as patriotic health organizations. However, creating healthy cities remains a word-wide project that requires more participation and regulation to optimize its function.Ethical issues  have been completely observed by the authors.


Diaphorina citri Kuwayama is a key pest of citrus as the vector of the bacterium causing the “huanglongbing” disease (HLB). To assess the global mtDNA population genetic structure, and possible dispersal history of the pest, we investigated genetic variation at the COI gene collating newly collected samples with all previously published data. Our dataset consists of 356 colonies from 106 geographic sites worldwide. High haplotype diversity (H‐mean = 0.702 ± 0.017), low nucleotide diversity (π‐mean = 0.003), and significant positive selection (Ka/Ks = 32.92) were observed. Forty‐four haplotypes (Hap) were identified, clustered into two matrilines: Both occur in southeastern and southern Asia, North and South America, and Africa; lineages A and B also occur in eastern and western Asia, respectively. The most abundant haplotypes were Hap4 in lineage A (35.67%), and Hap9 in lineage B (41.29%). The haplotype network identified them as the ancestral haplotypes within their respective lineages. Analysis of molecular variance showed significant genetic structure  between the lineages, and population genetic analysis suggests geographic structuring. We hypothesize a southern and/or southeastern Asia origin, three dispersal routes, and parallel expansions of two lineages. The hypothesized first route involved the expansion of lineage B from southern Asia into North America via West Asia. The second, the expansion of some lineage A individuals from Southeast Asia into East Asia, and the third involved both lineages from Southeast Asia spreading westward into Africa and subsequently into South America. To test these hypotheses and gain a deeper understanding of the global history of D. citri, more data‐rich approaches will be necessary from the ample toolkit of next‐generation sequencing (NGS). However, this study may serve to guide such sampling and in the development of biological control programs against the global pest D. citri.The Asian citrus psyllid  Recentl Hollis, .D. citri  and may thus rapidly evolve in response to new environments after an invasion. If semi‐isolated subpopulations acquire different ecological traits, such as in host preference, development time, pathogenicity, vector capacity, susceptibility to pesticides, and tolerance to heat, and other abiotic stressors  was run with the following temperature cycling profile: 5 min denaturation at 92°C followed by 35 cycles of 1 min at 92°C denaturation, 1 min at 53°C annealing, 1.5 min at 72°C extension and a final extension at 70°C for 10 min. The PCR reactions were composed of 0.1 mmol/L dNTPs, 2 pmol of each primer, 1.5 U Taq polymerase , 1× PCR buffer, 2.5 mmol/L MgCl2, and 20 ng of DNA. Amplification products were purified and sequenced with primers from the original PCR reactions on an ABI 3730 automatic sequencer , using BigDye technology. The chromatographs were interpreted with Phred and Phrap  using the FFT‐NS‐i strategy to increase accuracy  were calculated using the software MEGA v.5.05  and was partitioned by defined seven populations from the regions: North America (NM); South America (SA); West Asia (WA); East Asia (EA); South Asia (SA); Southeast Asia (SEA); and Africa (AF).A haplotype network was constructed to compare genetic relationships between geographic populations based on the genetic data. The unrooted minimum spanning tree (MST) was implemented in PopART  using the admixture model. Ten independent runs were evaluated for each K. The total length of the Markov Chain was set to be 100 000, and the length of burn‐in period was 20 000. We adopted the parsimony criterion, in which the lowest K capturing the most differentiation among populations was selected as the most likely K value  is taken as evidence for rejecting the sudden population expansion model , with relative frequencies of 93.75% and 6.25%, respectively. The COI gene comprised 468 bp when including data from GenBank. Forty‐four haplotypes were identified with 31 polymorphic sites and 15 parsimony informative sites. The average p‐distance among COI gene sequences was 0.003 (range from 0.000 to 0.017). High haplotype diversity (H‐mean = 0.702 ± 0.017) and low nucleotide diversity (π‐mean = 0.003) were identified within the whole sample. The average number of nucleotide differences (k) is 1.483.We succeeded in amplifying a 760‐bp Among the 44 unique haplotypes, most (95.45%) occurred only in a single locality, and the remaining 4.55% occurred in more than one locality Table . Hap9 waFST value , indicating the genetic structure among sites. The hierarchical AMOVA (Table FST = 0.62 (p < .0001), which demonstrates that global D. citri populations are genetically structured. The Ka/Ks ratio is 32.92 (much greater than 1) suggesting natural selection is acting to promote the fixation of advantageous mutations (positive selection).The overall nonhierarchical AMOVA test Table  resultedVA Table  analysis3.2D. citri populations  and Tajima's D . These statistical values are indicative of historical population expansions, genetic drift, and/or selection  levels for D. citri were seen in the seven analyzed regions. The psyllids from both East and West Asia, and North America showed low genetic diversity, results that could imply recent introductions events that may have consisted of as little as a single haplotype. We cannot rule out other processes such as reduction in mtDNA variation due to Wolbachia infections, male‐biased dispersal, or other potential limitations of mtDNA data  dispersal capacity  here is interesting as invasion success may occur after severe population bottleneck events or even with singly mated female invasion depending on its heterozygosity level  within each lineage of D. citri, two star‐like cluster patterns in the haplotype network, and the unimodal mismatch distributions for the whole sample and both lineages all rejected the null hypothesis of neutral evolution of the partial COI gene. That low genetic diversity characterized most sampling regions, and native and invasive populations share common haplotypes (Hap4 and Hap9), is consistent with recent introductions events and could suggest a single introduction of haplotypes in most region.Significantly negative neutrality tests (Tajima's 4.3D. citri has to date exclusively been studied with mtDNA represented by the COI locus. These studies have allowed understanding of the matrilineage structure of this species and generated hypotheses regarding dispersal and colonization of this important pest. However, while mtDNA data have proven highly useful in phylogeographic studies, there are several shortcomings of this approach (e.g., Avise, COI data and add new data re‐analyses of global patterns, and discuss prior and novel hypotheses on dispersal and colonization history of D. citri. Robustly testing these hypotheses, and gaining a deeper understanding of population structure of this species, will require data drawn at random from the whole genome, utilizing methods such as RADseq or targeted sequence capture. Such data will tease apart male and female dispersal, testing the “female‐based” dispersal hypotheses proposed here. They will also allow testing of “independent lineages” hypothesis through precise measures of genetic isolation and gene flow unavailable to single‐marker studies. Finally, such data will be immune to potential issues such as Wolbachia induced biases. However, for such work to be realized, resampling specimens across the globe will be necessary, and we hope our study can aid in strategical sampling reflecting known haplotype diversity.The continent‐global scale phylogeographic history of the psyllid None declared.Yufa Luo designed this study, collected and processed samples from all field sites, conducted data analyses, and wrote the manuscript. Ingi Agnarsson helped extensively with manuscript writing. All authors critically revised and approved the final version of the manuscript submitted. Click here for additional data file.


In each DCE, participants evaluated four or five sets of four inserts, selecting the most and least motivating (DCEs 1 & 3) or helpful (DCE 2) for quitting. Linear mixed models regressed choices on insert and smoker characteristics. For DCE 1, the most motivating messages involved novel disease topics and imagery of younger women. For DCE 2, topics of social support, stress reduction and nicotine replacement therapy were selected as most helpful, with no differences by imagery type. For DCE 3, imagery influenced choices more than topic, with imagery of a family or a mom and baby selected as most motivating. Statistically significant interactions for all three experiments indicated that the influence of imagery type on choices depended on the message topic. Messages to promote smoking cessation through cigarette pack inserts should consider specific combinations of message topic and imagery.This study assessed smokers’ responses to different smoking cessation topics and imagery for cigarette package inserts. Adult smokers from Canada ( In 2000 Canada was the first country to mandate pictorial health warnings on cigarette packs; since then, over 100 countries have implemented them . Howeverwww.tobaccolabels.ca/countries/canada). Observational studies of Canadian smokers indicate that those who read inserts are more likely to have stronger downstream self-efficacy to quit and are more likely to subsequently make a quit attempt, including attempts that last for at least a month [A lesser known characteristic of the Canadian warning label policy is its requirement for “inserts”, which are small, printed leaflets inside of cigarette packs that contain messages about the benefits of quitting  and behavioral recommendations to increase successful smoking cessation   to assess Canadian smokers’ preferences for different message content and imagery  that could be used on newly adopted inserts. Three separate DCEs were conducted in order to assess: (1) cessation benefit messages that targeted a general audience of adult smokers (DCE 1); (2) quitting tips messages that targeted a general audience of adult smokers, but particularly those interested in quitting (DCE 2); and (3) messages about pregnancy-related cessation benefits that targeted smokers of reproductive age (DCE 3). We also assessed the test-retest reliability of DCE 1 and DCE 2 in a subsample of participants who were followed up four weeks later.Adult smokers from Canada were recruited through GMI-Lightspeed’s online consumer panel. Invitation emails with a link to the online survey were sent to panel members, who were given a brief study description before providing consent. Eligible participants were 18 to 64 years old, had smoked at least 100 cigarettes in their lifetime, and had smoked cigarettes at least once in the prior 30 days. The first wave of the experiment was conducted between 22 and 31 August 2017. Sample quotas were established to recruit a minimum of 1000 participants, 50% of whom intended to quit smoking within the next 6 months. Four weeks after first participation in the experiments (20–30 September 2017), we recontacted participants to re-administer the experiments. GMI-Lightspeed has several quality control measures in place to ensure participants are engaged and provide thoughtful responses, including removal of panelists who complete the questionnaire too quickly  and regular screening of panelists with short batteries of questions and associated algorithms to identify and eliminate from the panel those who do not provide truthful, engaged responses. Participants were provided compensation that is standard for GMI-Lightspeed . The study protocol received ethics approval from the IRB at the University of South Carolina (Pro00054788).most and least, thereby increasing the precision of estimates and statistical power for assessing the reliability of DCE data [We used discrete choice experiments (DCEs), which have been used extensively in transportation studies, environmental economics, and marketing ,34,35. DDCE data .Participants evaluated three blocks of material that corresponded to three DCEs. In each DCE, participants evaluated four or five sets of four inserts , selecting the most and least motivating (DCEs 1 & 3) or helpful (DCE 2) for quitting. DCE 1 on cessation benefit messages unrelated to reproductive health involved a 5 × 5 within-subjects design (with a between-subjects element due to random assignment to different blocks of choice sets): five distinct topics  and five types of accompanying imagery  were tested See . DCE 2 oInsert message topics were selected and adapted from those developed by Health Canada as part of the process of selecting message content for inserts that will be implemented in 2020. Health Canada and the research team worked with a graphic designer to identify a range of possible images that fit each message and the typologies used .For all participants, DCE 1 was followed by DCE 2 and DCE 3. For both DCE 1 and DCE 2, all 25 message combinations were used. Fifty different “choice sets” were used, each with four contrasting inserts, such that the alternatives were pairwise independent of each other across choice sets (see n = 582) were assigned to the same blocks of material that they evaluated at baseline in DCEs 1 and 2. Responses to DCE 3 stimuli were not assessed due to concerns about survey length and because of expectations regarding the substantially smaller analytic sample both due to attrition and exclusion after considering participants who found no messages in DCE to be motivating .Participants who were successfully re-contacted , respectively.Which insert would MOST motivate you and LEAST motivate you to quit smoking?”, with participants choosing one insert as “most motivating” and one as “least motivating”, with mutually exclusive options allowed for each choice set  None would be motivating if you decided to quit, or (b) At least one would be motivating if you decided to quit?” For DCE 2, participants were asked “Which insert would be MOST helpful and which would be LEAST helpful for you if you decided to quit smoking?” with mutually exclusive choices allowed for each insert. Then, participants were asked “Thinking about these inserts, do you actually think that: (a) None would be helpful if you decided to quit, or (b) At least one would be helpful if you decided to quit?” Participants could view each choice set for as long as they wished. For each choice set, the insert selected as most helpful/motivating to quit smoking was assigned a value of 1, and the least helpful/motivating to quit was assigned a value of −1. The remaining inserts in that set were assigned a value of 0. If the participant indicated that none would be helpful/motivating, all inserts in that choice set were assigned a value of 0.For each choice set, participants were presented with four inserts, and for DCEs 1 and 3 they were asked “ set see . AfterwaInsert characteristics  were effects coded such that coefficients reflected deviations of the group from the grand mean. Participant sociodemographics included age group in years , sex , education , and income . Smoking-related variables included: smoking frequency ; nicotine dependence as determined by the heaviness of smoking index  with those who found at least one insert message to be motivating/useful . Omnibus chi-square tests were used to assess whether participant characteristics differed across the blocks of stimuli to which they were randomized.We used mixed linear regression to control for repeated measures when analyzing each DCE’s analytic sample . DependeWe conducted these analyses for the entire baseline sample, as well as for the subsample that was followed up and repeated DCEs 1 and 2. For the sample that was followed up, the consistency of choices in DCEs 1 and 2 were based on Cohen’s kappa. All data analyses were conducted using Stata v. 13.1 .n = 1000; see In the baseline sample (n = 804). Those who opted out of all choice sets they evaluated were less likely to intend to quit  or to have tried to quit recently  compared to those who selected at least one insert.The proportion of participants who indicated that at least one of the DCE 1 messages motivated them to quit was 80% (p < 0.001), whereas the overall effects of imagery were not  and new diseases (b = 0.015) were significantly more likely to be selected as motivating than the average of all messages, whereas topics on wellbeing (b = −0.013) and financial benefits from cessation (b = −0.016) were identified as less motivating. No statistically significant influences for imagery type were found, although imagery of younger women was only marginally non-significant .The relative importance of message topic on choice  was much higher than for imagery . Males selected messages with imagery of older women to be less motivating (b = −0.015) and symbolic imagery to be more motivating (b = 0.016). No imagery was selected as superior for females.Interactions between participants’ sex and imagery was marginally non-significant (p = 0.056). However, when examining specific coefficients, older participants selected messages with imagery of younger women to be more motivating (b = 0.013) and imagery of older men to be less motivating (b = −0.014). The overall interaction between topic and imagery was statistically significant (p < 0.001), indicating that the effectiveness of any particular image type depended on the topic  of the sample found at least one message helpful. Compared to those who chose at least one insert as helpful, those who found no messages helpful were more likely to have lower education , be more nicotine dependent , be less likely to intend to quit  or to have tried to quit recently .More than three-quarters  and on average the topic that listed cessation strategies was selected as less helpful (b = −0.046) than other messages. Imagery type did not have a significant effect on choice, whether assessed overall or individually.The relative impact of message topic on choice was substantially higher than for image type , although on average older participants selected messages with imagery of the young man to be less helpful (b = −0.014). The overall interaction between message topic and imagery was statistically significant (p < 0.001), indicating that the effectiveness of imagery was contingent on message topic (see Interactions between imagery type and participant sex and age were not significant (opic see .n = 577) found at least one message motivating to quit. Compared to those who found at least one message motivating, those who did not were more likely to be older , have lower education , have lower income , smoke more often , have greater nicotine dependence , have tried to quit recently , and be less likely to intend to quit .In DCE 3, about half of the baseline sample  and of mom, dad and baby (b = 0.031) were selected as significantly more motivating than the average, whereas the topic of fertility (b = −0.118) was significantly less motivating (see b = 0.107), or a mom, dad and baby (b = 0.122) were selected as significantly more motivating than the average, whereas the symbolic figure of a pregnant woman (b = −0.252) were selected as significantly less motivating . However, the pattern of responses was similar for males and females , and females selected messages with imagery of a pregnant woman (b = 0.045) while males did not.The overall interaction between participant sex and message imagery was statistically significant . However, the primary difference between younger and older groups concerned the somewhat stronger effects of imagery on message selection amongst older compared to younger participants. No differences in direction of effect or statistical significance were found  and re-evaluated the same blocks of inserts they evaluated in DCEs 1 and 2 at baseline. Compared to the baseline sample, those who were followed up were more likely to be older than 40  and less likely to intend to quit . Results were similar with regard to differences between the analytic and excluded samples due to opting out (results not shown). For both DCEs 1 and 2, the percent agreement in choice was 94%, with a Kappa statistic of 0.38 for DCE 1 and 0.37 for DCE 2, which indicates a moderate level of reliability.Four weeks after the baseline experiments, 58% of participants were successfully re-contacted  or a quitting tip message to be helpful 78%). As expected, these smokers were more likely to intend to quit or have recently tried to quit when compared to those who found no message motivating or helpful. It is noteworthy, however, most smokers who did not intend to quit also found these messages to be effective . While theories of health behavior, such as the theory of planned behavior ,50, high8%. As exFinding cessation benefit or quitting tips messages to be helpful was inversely associated with SES indicators . This may reflect SES-related barriers  that can cause communication campaigns to exacerbate health inequalities . To bettSmokers’ evaluations of messages about reproductive health benefits of cessation exhibited a similar pattern: smokers with cessation intentions, recent quit attempts and higher SES were more likely to select at least one message as motivating. The percentage of smokers in this group was lower than for the aforementioned messages that targeted a broader audience, yet more than half of smokers still found at least one of these reproductive health messages to be effective (58%). As expected, younger smokers were more likely to be in this group than to be unaffected, likely because of message relevance for people of reproductive age; however, females and males were equally likely to be affected, inconsistent with results for loss-frame messages on reproductive health that showed stronger responses among females . This maWhen assessing cessation benefit and quitting tips messages with topics that targeted the general audience of smokers , message topics explained more variation in choices than imagery types, whereas the opposite was found for reproductive health messages (DCE 3). The contrasting results between the first two DCEs and the third is likely due, in part, to the broader range of topics used for the more general cessation messages relative to the narrower range of reproductive health topics. Furthermore, different images were used within any particular image type category  across general efficacy topics for the first two DCEs to make the imagery “fit” general efficacy message topics—this contrasts with the fixed images within each imagery type category across the reproductive health topics see . Hence, We found mixed support for the importance of image congruence with smokers’ sex and age. For general cessation messages (DCEs 1 & 2), females were relatively uninfluenced by any particular imagery type whereas males had weaker responses to messages that portrayed an older woman. For reproductive health benefit messages (DCE 3), image congruence mattered more, with females having stronger responses to pregnancy imagery than males and males having stronger responses than females to family imagery that included a father. Smoker age mattered when considering responses to general cessation benefit messages , but not for quitting tips messages (DCE 2). For the reproductive health benefit messages, no striking differences were found by age, except that imagery appeared to have a somewhat stronger effect amongst older than younger participants. Participants across all age groups agreed that the symbolic figure of the pregnant woman was less motivating than the imagery of real people. Contrary to expectations, however, symbolic imagery was quite effective for some general efficacy topics see , which cK = 0.36–37), such scores are not uncommon given the paradoxical nature of the Kappa statistic [n = 2) appeared due to reduced statistical power in the follow-up study due to attrition. Remaining discrepancies (n = 9) also may be due to statistical power issues , as well as random fluctuation in responses perhaps due to the hypothetical nature of the task performed. Another explanation, however, concerns repeated exposure. Learning of insert content may make inserts less effective over time—for example, the topic of new diseases became statistically non-significant at follow-up after being motivating to quit at baseline. Future research should more squarely explore the impact of learning, since naturalistic insert exposure involves repetition. Indeed, some prior research has found that attention to inserts with cessation messages increases over time, even while attention to warnings wears out, suggesting that some insert message characteristics may become more salient over time [Our study generally supported the reliability of DCE results over time. The factors associated with indicating at least one insert was motivating/helpful and the variance explained by each message attribute were consistent across the baseline and follow-up DCEs . Althougtatistic ; indeed,This study has a number of limitations, including its reliance on self-reported choice to evaluate message effectiveness. While DCEs may do a better job of obscuring study intent and reducing demand effects than other study designs, our use of a relatively limited set of message attributes (topic and imagery) may have lessened this advantage. Social desirability bias may have led to overestimation of the percentage of smokers who would be influenced by these messages. Furthermore, the images we used to represent each category were not the same for each topic and therefore did not involve tight experimental control—however, doing this would have resulted in highly variable “fit” of imagery across topics. Even so, our results indicated that perceived message effectiveness depended on the specific combination of imagery and topic. Our stimuli were presented via a relatively unrealistic online modality, although some evidence indicates that online experiment results are similar to those found when presenting warnings in person and on mock cigarette packs ,9,10,11,In sum, our study found support for the contention that efficacy messages, whether focused on cessation benefits or quitting tips, on cigarette package inserts may help promote smoking cessation, even amongst Canadian smokers who have been exposed to similar messages through inserts for over a decade. Some message topics appeared generally more motivating and helpful than others, although future research in other countries should help determine whether other topics may be more powerful in setting where efficacy messages have not been a critical component of communication campaigns and labeling policies. Furthermore, implementing multiple inserts may allow for targeting of messages to specific groups, particularly vulnerable groups that suffer tobacco-related disparities. In the end, the specific combinations of message topic and imagery worked best across each message domain we assessed, indicating the need for pretesting specific combinations in order to select message characteristics that are most likely to result in maximum effectiveness for smoking cessation.


Phylogenetic trees and network analysis consistently revealed three major haplotype groups  in S. fusiforme, with A and B distributed in the Japan‐Pacific coast. Group C consisted of three subgroups  which were distributed in the Sea of Japan, the Yellow–Bohai Sea, and East China Sea, respectively. Isolation‐with‐migration (IMa) analysis revealed that the three groups diverged approximately during the mid‐Pleistocene . Extended Bayesian skyline plots (EBSP) showed that groups A and B underwent relatively long‐term stable population size despite a subsequent rapid demographic expansion, while subgroups C2 and C3 underwent a sudden expansion at c. 260 ka. FST and AMOVA detected low population‐level genetic variation and high degrees of divergence between groups. The cryptic diversity and phylogeographic patterns found in S. fusiforme not only are essential to understand how environmental shifts and evolutionary processes shaped diversity and distribution of coastal seaweeds but also provide additional insights for conserving and managing seaweed resources and facilitate predictions of their responses to future climate change and habitat loss.Understanding the evolutionary processes that have created diversity and the genetic potential of species to adapt to environmental change is an important premise for biodiversity conservation. Herein, we used mitochondrial  Profit‐S. fusiforme on the coast of southern Japan and China. It is estimated that the SST rose by 1–2°C along Kagoshima, Japan, in the past four decades  Kuntze codominated beds in zonal community in 1959 to become dominated solely by S. thunbergii in 2006  to quantify the phylogeographic structure and large‐scale assessment of genetic variation within and between populations by integrating mitochondrial and plastid loci, (ii) to detect the historical demography and geographic distribution of lineage/group diversity in the natural range, and (iii) to place current patterns of genetic diversity and phylogeographic structure into both historical and conservation context with the aim of sustaining natural seaweed resources in the ANP.22.1Sargassum fusiforme individuals were collected from 26 sites in the ANP ranging from Ishinomaki, Miyagi, Japan (38.35°N), to Naozhou, Guangdong, China (20.85°N)  and cytochrome oxidase III subunit (cox3), and the plastid spacer intervening the large and the small subunit of ribulose bisphosphate carboxylase oxygenase (RuBisCo rbcL‐S), were targeted due to their effectiveness in revealing phylogeographic structure of the congeneric Sargassum species : YC3F (5’‐GAAGGGGTGACTGAGGGGTTG‐3’) and YC3R (5’‐AAACTTTATACTTTATTTAGGGGTC‐3’) for cox3 with a product length of 724 bp; YTRNF (5’‐ACCCCTGTAGTTATGAAATGAGAAAGTC‐3’) and YTRNR (5’‐ACCCCTACCTCATAGAAGACTGGAA‐3’) for trnW‐L with a product length of 649 bp. Plastid rbcL‐S was amplified using 3F  Figure , Table 1) Figure . The mit2.2Nh), haplotype diversity (h), and nucleotide diversity (π), which were all calculated in arlequin 3.5 . The trnW‐L+cox3 and rbcL‐S sequences were applied for phylogenetic analysis, performed using the neighbor‐joining (NJ), maximum‐likelihood (ML), and Bayesian inference (BI) in MEGA 5.0, phyML 3.0 , S. thunbergii (no. KP280065), and S. muticum (Yendo) Fensholt (no. KJ938301) were chosen as out‐groups.Sequences were aligned with MEGA 5.0  conducted in GENALEX  was also conducted in arlequin to assess the spatial partitioning of genetic variance among the groups defined above.Plastid 2.3ma2 , population sizes (Θ), and divergence time (t) based on the concatenated trnW‐L and cox3 data sets , was applied to convert the output into units of years.The isolation‐with‐migration model implemented in IdA = 2μT, where μ is the average substitution rate per site of gene and dA is the net average genetic distance between groups /2 with 1000 replicates in MEGA 5.1  and historical (θW) genetic diversities were assessed using DNASP 5.0  or recent population growth (if θπ > θW)  were produced in BEAST 1.7.4 , and cox3 yielded 26 haplotypes (GenBank accession numbers: KX085149‐KX085174). The concatenated trnW‐L+cox3 alignment consisted of 50 polymorphic sites of which 37 were parsimony informative, yielding 47 haplotypes from 560 individuals. Of these haplotypes, 38 (80.9%) were found in a single population and 24 were singletons (haplotypes represented by a single sequence) (Table S1). Diversity estimates varied among populations, with the top three highest genetic diversity detected in Ama, Japan , Yingzuishi, China , and Ishinomaki, Japan   than that in other regions . Of these haplotypes, eight were found in a single population and five were represented by only one sequence. The most abundant haplotype, R1, was shared by 515 specimens, accounting for 86.6% of all samples (Table S1). Diversity indices showed that the populations from Daquan and Nanji Island, China, and Awaji Island, Japan, harbored the highest genetic diversity , whereas all populations in Korea (POP 7–10) exhibited no genetic diversity . Three major haplotype groups were discovered, supported by robust bootstrap values (>80%). BI and ML analysis revealed a similar phylogenetic topology as the NJ method .The neighbor‐joining tree based on the concatenated me Fig. S. Three mme Fig. S. Three mme Fig. S. Three mme Fig. S. Three mme Fig. S. Three mFST values based on mitochondrial data indicated that populations along the Japan‐Pacific coasts were significantly divergent from all other populations (FST range = 0.865–1.000)  and East China Sea (group C3) (FST range = 0.299–0.978), but the genetic variance within each marginal sea was low  (Table S2). In contrast, plastid rbcL‐S revealed low‐to‐moderate FST values between all populations except for the population in the Awaji Island, Japan (POP 4), with all FST values > 0.60  occurred among the groups and/or subgroups (Table S3). The remaining 12.18% variation was found among and within populations, with all F‐values statistically significant  (Table S3).Pairwise a group C and East3.3S. fusiforme was also supported by mtDNA‐based principal component analysis (PCoA)  Figure a. Firstl Figures a, 3a. Be Figures a and 3a.ma results indicated that group A may have diverged from group B during the mid‐Pleistocene . The relative divergence time between groups A and C  resembled that between groups B and C (858–937 ka) .The I3.4Fs and Tajima's D were negative for groups C2 and C3, indicating a scenario of historical population expansion (Table S5). For groups A, B, and C1, most of the values were statistically nonsignificant. However, the mismatch distribution for each group showed a unimodal except for group B , indicating a signal of population expansion. Extended Bayesian skyline plots (EBSPs) analyses detected a slight population expansion in group A and a subsequent population expansion at c. 13 ka  and contemporary (θπ) genetic diversity showed that θw was substantially higher than θπ, especially for groups C2 and C3 (Table S5), indicating a recent bottleneck.Neutrality tests showed that both Fu's n Table S. For gron Table S. For gro44.1S. fusiforme were based on the concatenated mitochondrial DNA rather than the plastid rbcL‐S. This is principally due to their contrasting phylogeographic resolution  in the brown algae, the mitochondria and plastid of Sargassum are inherited maternally  at a fine spatial–temporal scale.In this study, the majority of phylogeographic patterns in S. fusiforme is characterized by deep genetic splits in the ANP  has a mixture of two subgroups (C1 and C2)  from the southwestern diversity hotspot  into the Sea of Japan . Several useful conservation insights can thus be presented for S. fusiforme. First, the average FST values among S. fusiforme populations in the Japanese Archipelago largely exceed average values between all China–Korea populations, including the population (CNZ) from southern China separated by over 2000 km  cornutus, Kojima, Segawa, & Hayashi, Batillaria cumingi, Kojima, Hayashi, Kim, Iijima, & Furota, Cellana nigrolineata, Nakano, Sasaki, & Kase, Leucopsarion petersii, Kokita & Nohara, S. fusiforme in this study are also applicable to other marine species inhabiting similar coastal environments around the Japanese Archipelago. Integrating ecological niches, biological features, and life histories of different species as a manageable system may minimize the impact of anthropogenic activities and habitat loss on these diversity hotspots, and ultimately to preserve and maintain coastal ecosystem functioning.The ANP, particularly the Japanese Archipelago, is one of the most prominent marine biodiversity hotspots on the earth  gS. fusiforme correspond to species or subspecies boundaries in terms of conservation genetics and taxonomic uncertainties (Karl & Bowen, S. fusiforme need to be further examined to check whether there are significant allele frequency shifts in nrDNA, along with the identification of possible elusive phylogeographic processes such as population‐level genetic introgression and incomplete sorting of ancestral genetic polymorphisms (Gaudeul, Gardner, Thomas, Ennos, & Hollingsworth, Nevertheless, there are limitations in applying uniparentally inherited mitochondrial genes for conservation biogeography. First of all, the ESUs identified in 5S. fusiforme reflect both older phylogeographic history and long‐term isolation. These historical phylogeography and cryptic genetic diversity can not only help to understand species’ underlying adaptive potentials following drastic environmental shifts, but also present important insights for conservation purpose and predict how species will respond to future climate change. Nevertheless, ancestral genetic relics have been demonstrated to link to population trends in a biogeographic context (Schmitt & Hewitt, S. fusiforme on a scale from less to more susceptible to damage and to recognize protection priorities.The structured genetic lineages and sublineages with nearly disjunct geographic boundaries found in https://doi.org/10.5061/dryad.2q6bm.GenBank accessions of DNA sequences: KX085135–KX085196. Data for this study are available at  Click here for additional data file.


Plasmodium falciparum to adapt to environmental changes depends considerably on its ability to maintain within-population genetic variation. Strong selection, consequent to widespread antimalarial drug usage, occasionally elicits a rapid expansion of drug-resistant isolates, which can act as founders. To investigate whether this phenomenon induces a loss of within-population genetic variation, we performed a population genetic analysis on 302 P. falciparum cases detected during two cross-sectional surveys in 2002/2003, just after the official introduction of sulphadoxine/pyrimethamine as a first-line treatment, and again in 2010/2011, in highly endemic areas in Papua New Guinea. We found that a single-origin sulphadoxine-resistant parasite isolate rapidly increased from 0% in 2002/2003 to 54% in 2010 and 84% in 2011. However, a considerable number of pairs exhibited random associations among 10 neutral microsatellite markers located in various chromosomes, suggesting that outcrossing effectively reduced non-random associations, albeit at a low average multiplicity of infection (1.35–1.52). Within-population genetic diversity was maintained throughout the study period. This indicates that the parasites maintained within-population variation, even after a clonal expansion of drug-resistant parasites. Outcrossing played a role in the preservation of within-population genetic diversity despite low levels of multiplicity of infection.The ability of the human malarial parasite  Malaria is caused by the protozoan parasite Plasmodium, and 216 million cases were reported worldwide in 2015, responsible for an estimated 445,000 deaths2. In high transmission areas, populations of P. falciparum, the species of Plasmodium responsible for the most lethal form of malaria, generally exhibit high levels of genetic diversity, which has enabled this parasite species to develop survival mechanisms such as antimalarial drug resistance and immune evasion6. Genetic diversity can be lost in response to several population genetic and environmental factors. In particular, reductions in population-size can potentially reduce genetic variation, an extreme case of which is known as the bottleneck effect7. In malarial parasites, reductions in population size are often induced by significant environmental changes, such as effective malaria control programs which reduce the vector mosquito population as well as the number of malaria-infected individuals. One factor that potentially creates population bottlenecks is widespread antimalarial drug use8. This is because, while susceptible parasites succumb to the selective pressure imposed by antimalarial drug usage, a small number of parasites resistant to the drugs survive and expand in the parasite population. However, since random recombination theoretically occurs in malaria parasites, the effect of selection is expected to be limited to genetic regions flanking drug resistance genes10, and selection is therefore not expected to have a global effect on genetic diversity and the genome in general. However, in the Greater Mekong Subregion, where P. falciparum parasites resistant to artemisinin combination therapies have emerged13, rapid expansion of artemisinin-resistant parasite numbers resulted in distinct but apparently sympatric parasite subpopulations with extremely high levels of genetic differentiation between them15. This further emphasizes the importance of investigating if the expansion of single origin drug-resistant parasite isolates contributes to the reduction of within-population genetic diversity in different transmission settings.Genetic diversity, or the extent of genetic variation within a population, is one of the factors necessary for organisms to adapt to environmental changes2. Overall, malaria transmission intensity is high, with limited seasonal fluctuations in the costal and lowland zones17. Malaria epidemiology is, however, substantially heterogeneous because of diverse ecological factors related to the malarial parasites themselves, mosquito vectors, human hosts, and the natural environment18. All four Plasmodium species that cause malaria in humans  are observed in this region18. An intense malaria control program was launched with the first country-wide free distribution of long-lasting insecticidal nets (LLIN) in 200419, which led to substantial reduction in mosquito biting rates and entomological inoculation rates20 as well as in malaria incidence rates and malaria prevalence21. A combination of sulphadoxine/pyrimethamine along with one of the 4-aminoquinolines (chloroquine or amodiaquine) was used as a first-line treatment for uncomplicated malaria between 2000 to 2010. We previously conducted a study on the molecular epidemiology of drug resistance in the Wewak district of East Sepik in Papua New Guinea. Our study found that single-origin sulphadoxine-resistant P. falciparum parasites appeared in 2003, soon after the penetration of this treatment to the studied area22. However, it is not clear whether this rapid expansion of the sulphadoxine-resistant parasite isolate has affected local parasite populations and, in particular, whether it has contributed to the emergence of a subpopulation and caused reductions in within-population genetic variation. To assess this, we performed a population genetic analysis using P. falciparum isolates obtained from four cross-sectional surveys in the Boikin-Dagua Rural Local-Level Government area, East Sepik, which is 56 km away from the Wewak district (where the previous study was conducted in 2002 and 200322) before and just after the rapid increase in sulphadoxine-resistant parasites.Papua New Guinea has the highest burden of malaria outside of AfricaP. falciparum 10.8%, P. vivax 8.8%, and P. malariae 2.8%) in 2002 and 20.1%  in 2003  and 2003 (42.3%) were significantly higher than those in 2010 (28.0%) and 2011 (30.3%) .The studies were conducted in a small catchment area spanning 15 km along the coast and containing 14 villages in the Boikin-Dagua Rural Local-Level Government area, East Sepik . Mean MOI was 1.52 in 2002, 1.64 in 2003, 1.41 in 2010, 1.35 in 2011 and a significant downward trend in mean MOIs  was observed. We consider that distribution of LLIN as a part of National Malaria Control Programme launched in 2004, between our sampling times, had a significant impact on the observed reduction in prevalence of P. falciparum and MOI in 2010/2011.MOIs were determined from ten neutral microsatellite markers by counting the greatest numbers of alleles at the most polymorphic locus Table . This mepfcrt, dhfr, and dhps based on the prevalence of these alleles and MOIs using MalHaploFreq23  was fixed or nearly fixed throughout the study period, probably owing to long-term chloroquine usage before our study. The sulphadoxine/pyrimethamine plus 4-aminoquinoline (chloroquine or amodiaquine) regimen was officially introduced as a first-line treatment for uncomplicated malaria in 2000, but the penetration of this change into the study area occurred sometime in 2002, concurrent with our sampling period. Before this change, sulphadoxine/pyrimethamine had been used infrequently as a second-line treatment with quinine. Notably, the increase in sulphadoxine/pyrimethamine selection pressure did not affect the frequencies of pyrimethamine- and sulphadoxine-resistant alleles equally. The frequency of the pyrimethamine-resistant dhfr allele  was already high at the beginning of the study (70% in 2002 and 86% in 2003), and subsequently achieved fixation in 2010. In contrast, conspicuous changes in allele frequencies were observed with respect to sulphadoxine resistance. The sulphadoxine-resistant allele  was not observed in 2002 and 2003. The frequency of this allele, however, reached 54% in 2010 and rapidly increased to 84% in 2011.We estimated allele frequencies of dhps were genotyped. A microsatellite haplotype  accounts for 87% of parasites harbouring the SGEAA mutation : 2002/2003 (0%), 2010 (54%), and 2011 (84%). In 2002/2003, high levels of expected heterozygosity (0.60–0.81) were observed at all but three loci   Fig. . These h90) Fig. . This ob90) Fig. . These rGEAA allele with the Common microsatellite haplotype. These results exclude the possibility that the parasite populations in 2010 and 2011 were derived from a population distinct from that observed in 2002/2003.There is a possibility that the observed preservation of high genetic variation in 2010 and 2011 is because of the mixture of distinct population(s) possessing high genetic variation. To assess this, we performed a widely used Bayesian clustering method, STRUCTURE analysis, which can detect a weak population structure. The result exhibited that the highest delta K was obtained at K = 3 in both the analysis with all isolates Fig.  and thatGEAA) isolates and, notably, these values tend to be higher in dhps in the mutant isolates than in the wild-type isolates. This result was supported by PCA, which exhibited a more scattered distribution of mutant isolates than wild-type isolates  but significant multilocus non-random association in 2010  and 2011   Table . We next4) Table . Even wh4) Table . Becausedhps-SGEAA mutant and those harbouring the wild-type dhps allele. Despite the higher proportion of pairs which displayed random associations in the group with the wild-type dhps allele, as many as 29 pairs (64%) showed random associations in the parasite group with SGEAA  in East Sepik Province in 2005 and in Madang Province in 20065 and in a county-wide analysis (1–1.6) in 2008-20096. These MOIs were much lower than those in African endemic regions such as Uganda where mean MOI was 4.4629. At this stage, there is no evidence that the observed degree of MOIs in Papua New Guinea is sufficient to quickly break the non-random association patterns. Even so, it is very likely that outcrossing played a considerable role in the persistence of high within-population genetic diversity observed in this study area.In spite of this, the levels of within-population genetic variation were not reduced. We consider that multiple instances of outcrossing between drug-resistant and drug-susceptible parasite isolates might have occurred just after the emergence of the single-origin sulphadoxine-resistant isolates in the parasite population. This could have caused the breakage in clonality of the single-origin sulphadoxine-resistant isolates and produced resistant isolates with multiple genetic backgrounds. Thereafter, the batches of resistant isolates possessing considerable genetic variations might have rapidly expanded in the parasite population for a short time. In other words, outcrossing that was sufficiently high to disrupt the clonality of the original sulphadoxine-resistant isolates might have continued since the emergence of resistant isolates. This is considered to be the main reason for the observed maintenance of within-population genetic variation. We observed that the number of loci with non-random associations in 2011 was smaller than that in 2010, which might support this scenario. In Papua New Guinea, outcrossing was estimated to be 52% in the early 1990s31. Similarly, genetic diversity at the border between Thailand and Myanmar remained stable throughout a 10-year study period, even though the incidence of P. falciparum infection decreased considerably from 0.24 per person per year in 2000 to 0.02 in 20108. In Papua New Guinea, the first country-wide free distribution of LLIN was launched in 2004 with the financial support of round 3 and 8 grants from the Global Fund to Fight AIDS, Tuberculosis, and Malaria19. Through this distribution drive, significant increases in the ownership and use of LLINs were confirmed at sentinel surveillance sites32. A previous, well-designed cohort study in Papua New Guinea demonstrated a clear association between insecticide treated net usage and the reduction of prevalence, clinical episode, and MOIs33. Accordingly, the average population prevalence of falciparum malaria reduced from 10.1% pre-LLIN to 2.5% post-LLIN at the country-wide sentinel sites21. Despite these changes, however, the persistence of high-levels of within-population genetic diversity was confirmed by the analysis of neutral microsatellites17 and merozoite surface protein 26. In our study area, LLINs were distributed in the early phases of the drive, just after our initial sampling in 2002 and 2003. Decreases in the prevalence of falciparum malaria and mean MOI were observed in 2010 and 2011, which indicates that malaria control measures performed between our sampling times had a considerable impact on the reduction of malaria. However, within-population genetic diversity continued to be high in our study site. Consistent with these observations, we have previously demonstrated that the physical distance of a population from a sub-Saharan African origin could be the primary reason for within-population diversity, rather than regional variations in transmission intensity and previous malaria-control interventions36.Robust maintenance of genetic variation has been generally reported in malaria parasites. In western Kenya, significant decrease in transmission intensity after the implementation of insecticide-treated bed nets did not reduce the within-population genetic diversity in 10 yearsdhps alleles when sulphadoxine/pyrimethamine was introduced as the first-line treatment in the early 2000s. In contrast, approximately 70% of parasites already harboured the pyrimethamine-resistant dhfr allele (CNRNI). Similar results were previously shown in East Sepik38 and Madang province37. Historically, pyrimethamine alone was used as a prophylactic against malaria, as well as a drug to treat malarial infections in the 1950s39, this might have led to the selection of the pyrimethamine-resistant allele. The sulphadoxine-resistant SGEAA allele emerged between 2003 and 2010 in the present study area. This finding coincides with previous observations in Madang Province, where this allele appeared between 2006 and 201042. However, frequencies of the SGEAA allele in our study (84% in 2011) were much higher than those in the previous studies (~25%)42. Importantly, despite the selection of the double mutant SGEAA allele, there is no evidence of the emergence of higher sulphadoxine-resistant alleles with three or more mutations in Papua New Guinea42, although these are highly prevalent in Southeast Asia43 and were recently observed in Africa44. Together with the observation that the highest pyrimethamine-resistance (I164L) is also absent in Papua New Guinea45, sulphadoxine/pyrimethamine efficacy is still retained against P. falciparum, as shown in a previous large-scale randomized trial on intermittent preventive treatment in infants46.In the present study, all parasites showed sulphadoxine-susceptible 15. Within-population genetic diversity reflects the potential of a population to survive in a constantly changing environment. In parasite populations with low levels of genetic diversity, short-term evolutionary changes to surmount various environmental challenges are not expected. Clonal expansions of drug-resistant parasites can potentially affect the genetic diversity of malarial parasite populations largely through their effects on local malaria ecology, such as levels of multiple-clonal infection and parasite migration. This emphasizes the importance of further studies in regions with variable local malaria ecology to investigate how rapid expansion of drug-resistant parasites can affect within-population genetic diversity.In conclusion, we report that a rapid expansion of sulphadoxine-resistant parasites did not result in the emergence of distinct parasite subpopulations, nor did it reduce the within-population genetic variation in the parasite population within our study area in Papua New Guinea; this is different from the patterns observed in the Greater Mekong Subregion where transmission intensity is much lower than that in Papua New Guinea47. P. falciparum was the predominant malarial parasite species in the study area at the time of our surveys. The main vectors of malaria transmission were Anopheles punctulatus, An. farauti, and An. koliensis47. Entomological inoculation rates with P. falciparum calculated from a previous study in Dreikikir, a region ~50 km from our study area, were 159 infective bites/person/year in 2008  and 53 infective bites/person/year in 2011 20. Sulphadoxine/pyrimethamine along with one of the 4-aminoquinolines (chloroquine or amodiaquine) was introduced as a first-line treatment for uncomplicated malaria in the early 2000s. Before its introduction as a first-line treatment, sulphadoxine/pyrimethamine was used as second-line treatment in combination with quinine.This study was conducted in a single catchment area that included 14 villages in the Boikin-Dagua Rural Local-Level Government area, East Sepik, Papua New Guinea  to confirm P. falciparum infections as previously described49. This method is based on the amplification of 18S small subunit ribosomal RNA with a semi-nested, multiplex PCR. The first PCR amplification detects the Plasmodium genus in samples and the second amplification differentiates between the Plasmodium species that affect humans.We conducted two surveys in February 2002 and July 2003, immediately after sulphadoxine/pyrimethamine introduction, as well as two surveys conducted later in January–February of 2010 and 2011. Individuals living in the studied villages were asked to voluntarily participate in the surveys. Finger-prick blood samples were taken after obtaining informed consent for study participation from individuals or their guardians. Finger-prick blood samples (100 μL) from individuals were spotted onto chromatography filter papers . Parasite DNA was purified from a quarter of each blood spot using the QIAamp DNA Blood Mini Kit  according to a modified version of the manufacturer’s instructionsEthical clearance for the study was obtained from the Medical Research Advisory Committee of the Papua New Guinea National Department of Health (No. 0.1.16 and 09.26), the Tokyo Women’s Medical University Ethical Committee (No. 1744), and the Juntendo University Ethical Committee (No. 2013009). All experiments were carried out in accordance with the approved guidelines.P. falciparum genes responsible for resistance to chloroquine (pfcrt), pyrimethamine (dhfr), and sulphadoxine (dhps) were sequenced as previously described51. Briefly, nested PCRs were performed to amplify sequences, including polymorphic sites known to confer resistance , followed by direct sequencing using the BigDye Terminator v1.1 Cycle Sequencing Kit on an ABI PRISM 377 DNA Sequencer . Allele frequencies of drug-resistance genes were estimated using MalHaploFreq23; the program utilizes allele prevalence and MOI data to estimate allele frequencies with a maximum likelihood algorithm using maximum likelihood methodology. P-value < 0.05 was considered significant unless otherwise specified.The dhps gene  were determined to investigate if mutant (sulphadoxine-resistant) alleles in the studied population had a single origin or multiple origins as previously reported57. We have previously demonstrated that very limited origins of resistance for chloroquine and pyrimethamine resistance (one in a resistant pfcrt haplotype and two in resistant dhfr haplotypes) had spread in the studied area58. Semi-nested PCR products with fluorescent end-labelled primers were separated on an GenomeLab GeXP  and size variations were determined with the GenomeLab Genetic Analysis System (Beckman Coulter). If minor peak heights were greater than one third of the major peak height, these peaks were regarded as peaks from minor clones. Although this one-third criterion potentially underestimates minor alleles with peak heights lower than 33% of the dominant clone, mis-scoring of artefacts caused by stutter peaks and other technical errors can be largely avoided, because of which, this method is widely used60.Alleles of the six microsatellite markers located near the 61. These markers are located on different chromosomes from pfcrt (chromosome 7), dhfr (chromosome 4), and dhps (chromosome 8), and are commonly used for population genetic analyses of malarial parasites. Microsatellite alleles for the 10 putatively neutral microsatellites were detected and scored with the same methodology described in the previous section.Nucleotide length variations were measured in 10 putatively neutral microsatellite markers: TA42 (chromosome 5), TA81 (chromosome 5), TA1 (chromosome 6), TA109 (chromosome 6), TA87 (chromosome 6), 2490 (chromosome 10), ARA2 (chromosome 11), Pfg377 (chromosome 12), PfPK2 (chromosome 12), and TA60 (chromosome 13)62. Since this method cannot reconstruct the multilocus genotype of each clone, MOI measures only provide the minimum number of clones per isolate.Samples harbouring one or more loci with multiple alleles were interpreted as multiple-clonal infections. The greatest number of alleles at the most polymorphic locus was used to determine the multiplicity of infection (MOI) or the number of clones per sampleG with elements gij corresponding to isolate i  and microsatellite locus j . The genotype value at a microsatellite locus was initially specified as the nucleotide length of the predominant allele. Next, the genotype entries were standardized for each microsatellite locus by replacing gij withj respectively. Since the PCA does not allow missing data, only isolates without missing genotypes at 10 putatively neutral microsatellite loci were used in the calculation of Dij. In multi-clonal infections, major alleles were used for the analysis. We also used STRUCTURE 2.3.4, a Bayesian model-based clustering program, to calculate the most probable number of clusters (K) in the sample set and then assign probabilities of membership to each cluster for each individual63. For each run, a burn-in period of 50,000 steps was followed by 1 × 105 iterations under the no admixture model and the assumption of correlated allele frequencies among populations. For each K of 1–10 clusters, 10 runs were performed. ΔK was calculated as previously described64. A visual output for the run of highest Ln P(D) was generated using the program Distruct65.Standardized data on 10 putatively neutral microsatellite markers were subjected to principal component analysis (PCA). Genotype data were represented by a matrix n represents the total number of malaria isolates, and pi is the frequency of the ith microsatellite allele. The allele frequencies were obtained by counting only predominant alleles . To assess the differences in expected heterozygosity between groups, a permutation test with 1,000 random shuffles was conducted for each microsatellite locus. In this permutation test, the collection-year label was randomly shuffled to obtain a distribution of differences in expected heterozygosity between two groups under the null hypothesis. Other measurements  were determined using FSTAT version 2.9.366.Several population genetic measurements were used to estimate the extent of genetic diversity in the parasite population according to the nucleotide-length variations in 10 putatively neutral microsatellite markers. In case of multiple-clonal infections, major alleles were used. These measurements were: number of alleles, allelic richness, and expected heterozygosity; expected heterozygosity is defined as the probability that two randomly selected isolates have different microsatellite alleles in the population and is calculated for each microsatellite locus using the following formula:pfcrt, dhfr, and dhps were carried out using Genepop version 4.1 under the following Markov chain parameters: dememorization number = 1000, number of batches = 100, and number of iterations per batch = 100067. A predominant allele was considered for each microsatellite locus. Bonferroni-corrected P value threshold was used to adjust for multiple comparisons.Estimations of pairwise non-random associations between 10 putatively neutral microsatellite loci, VD) and the variance expected for linkage equilibrium (Ve) were computed using LIAN 3.7 programme68. A standardized measure of linkage, ISA was calculated asl is the number of loci tested. In the calculation, only isolates without missing genotypes at the 10 putatively neutral microsatellite loci were used. To further evaluate the null hypothesis that all these loci are in linkage equilibrium , Monte-Carlo method was implemented in LIAN 3.7 programme68. In this test, the data set was shuffled 10,000 times by resampling the loci without replacement, and the variance for each resampled data set was compared with VD. The P-value was defined as the frequency with which the variance for the resampled data set was greater or equal to VD .The variance of the pairwise differences for the observed data (Supplementary Information


Amblyomma hebraeum, Rhipicephalus evertsi evertsi, Rhipicephalus decoleratus and microplus (Boofilids), Rhipicephalus appendiculatus, Rhipicephalus simus and Hyalomma marginatum) attached on eight anatomical locations on the animals and were summed by species and anatomical location. Heritability estimates, phenotypic and genetic correlations were estimated on a monthly basis using mixed linear models, fitting univariate and bivariate sire models. Fixed effects considered were location, sex, year and age as a covariate. Tick counts were higher in the hot months, and A. hebraeum was the most dominant tick species. Heritability estimates for tick count varied by month and trait and ranged from 0 to 0.89. Genetic correlations were mostly positive, and low to high, with some negative correlations with high standard error. Phenotypic correlations were low to moderate. In general, high genetic correlations were observed between whole body count and the anatomical location counts, suggesting that it may not be necessary to conduct whole body counts. Counts from the belly and perineum appeared to be the most suitable surrogate traits for whole body count. These findings provide useful information for developing strategies for the practical implementation of genetic selection, as a supplement to the traditional tick control measures.The objective of the study was to characterise genetic parameters across months for different tick species and anatomical locations in South African Nguni cattle. Tick counts were conducted monthly, over a 2-year period, on 586 Nguni cattle under natural infestation, from four herds located in different provinces of South Africa. The counts were recorded for six species of ticks (The online version of this article (doi:10.1007/s11250-017-1336-2) contains supplementary material, which is available to authorized users. Rhipicephalus (includes the genus formerly known as Boophilus), Amblyomma and Hyalomma  in Brazil and Australia has greater tick resistance when compared to European cattle (Bos taurus) (Utech and Wharton Bos taurus × Bos indicus). Resistance of cattle to ticks is heritable and responsive to selection , ARC-Roodeplaat Research Farm located in Gauteng Province (n = 143), Mukhuthali Nguni Community Farm located in the Kwa-Zulu Natal Province (n = 224) and the University of Fort Hare Farm in Alice located in the Eastern Cape Province (n = 95). Ages of the cattle and their physiological status varied in each location, with age ranging from 2.5 to 17 years. Limited pedigree information was available, with 806 animals over three generations. Animals were exposed to natural tick infestation at all four farms. Counts and identification of tick species were conducted every month from May 2012 to April 2014. All animals were spray dipped with a flumethrin pour-on formulation “Drastic Deadline®” immediately after the tick count data collection each month.Tick count data were collected from 586 randomly selected Nguni cattle  over a 2-year period from four different herds in different agro-climatic zones (locations): Agricultural Research Council (ARC) Loskop Research Farm located in the Limpopo Province of South Africa  spp., Rhipicephalus appendiculatus, Rhipicephalus simus and Hyalomma marginatum). Total counts by species and anatomical location were also considered, resulting in 63 measured phenotypes or traits. See the detailed description of the 63 traits  and recorded by species  , Rj is the effect of the jth year , Sk is the effect of the kth sex , b is the regression coefficient of age of the animal on tick count, A is the age of the animal and eijkln is the random residual error.where Variance components and heritabilities for log-transformed tick counts were estimated by univariate analysis fitting a sire model in ASREML software , b, s, pe and e are the vectors of fixed effects , permanent environment ∼N , residual ∼N , where A is a numerator relationship matrix and I is an identity matrix of order equal to the number of animals and records, σ2s, σ2pe and σ2e are the sire, permanent environmental and residual variances, respectively. The relationship matrix was constructed using pedigree. The narrow-sense heritability (h2) was calculated as follows: sire model h2 = 4σ2s/(σ2s + σ2pe + σ2e). A series of bivariate analyses were used, fitting the same model as above, to estimate genetic and phenotypic correlations among the traits of interest, considering mostly the traits with significant heritability estimates from the univariate analysis.where A. hebraeum was the most dominant tick species. The mean monthly whole body tick counts were lowest (8.4 ± 6.1) in June (Winter) and highest (32.1 ± 23.4) in November (Summer); similar trends were observed for the other traits analysed (Table Tick counts were higher in the hot months and highest 3.1 ± 23.4p < 0.05). Age fitted as covariate was also significant in most traits.In most of the traits analysed, all fixed effects with the exception of sex were significant  were low to moderate, ranging from 0 to 0.58 Table . For whoA. hebraeum (May) and one for R. evertsi evertsi (September), with no effects of the permanent environment due to the animal  and R. evertsi evertsi (in September)  Table . Few negr) Table .Table 6GHaving monthly data available for tick count collected at different anatomical locations and for different tick species in Nguni cattle over 2 years presented an opportunity to investigate the tick variation across time, and possibly identify optimal sampling time and more suitable traits. This study demonstrated that tick distribution varies across the year and that there is genetic variation across months in tick count, which varies from low to high depending on the trait. The study also identified positive genetic and phenotypic correlations among tick count at different anatomical locations. However, partitioning of data according to tick species did not seem to allow for enough power to estimate heritabilities and genetic correlations. These results should be considered in the context of the limitations and advantages of field studies  and data collection. For example, Passafaro et al.  performeBos taurus dairy breeds , in order to observe the resistance or susceptibility of the animal Hewetson . It has The current study observed high genetic correlations between whole body count and the anatomical location counts, which suggest that the use of other anatomical locations such as belly and perineum as proxies for the whole body count is feasible. This might be due to the fact that both these body locations have softer skin with short hair. However, since the perineum is more accessible than the belly, this could be more convenient for tick counting. High genetic correlations were observed between Boofilids total count and Boofilids on the perineum, indicating that the latter can be a good approximation for Boofilids total count.In the current study, genetic parameters were characterised for tick counts across months for different tick species and anatomical locations in South African Nguni cattle. Results show sufficient genetic variation to warrant improvement in tick resistance through selection, thereby complementing other tick control methods. Such genetic variation appears to be expressed more during some months of the year than in others. Results therefore suggest that collection of tick count data for genetic selection should be carried out during those months eliciting the highest genetic variation. Tick counts from either the perineum or belly may be used as reliable indicators of whole body count. However, further studies verifying these results are required, before any recommendations are adopted at national scale.Supplementary Figure 1(DOCX 343 kb)