Holstein Friesian is the dominant breed of modern dairy cattle in Iran, therefore the development of a genetic evaluation system for economically important traits for this population is needed. Genetic parameters for SCS and its genetic correlations with production traits were estimated in Iranian Holstein cows. The moderate heritability for SCS and its low negative genetic correlations with yield traits indicate that genetic selection for decreasing SCS would have a relatively medium genetic progress with no necessarily antagonistic effects on lactation performance. The estimates found in this study can be considered as the first step to include SCS in the national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model.The aim of this study was to estimate the genetic parameters of somatic cell count (SCC) and its relationship with production traits in the first three parities in Iranian Holstein dairy cows. Data were 1,891,559 test-day records of SCC, milk yield, and milk compositions on 276,217 lactations on 147,278 cows distributed in 134 herds. The number of test-day records in the first, second and third parities were 995,788 , 593,848 , and 301,923 , respectively. Test-day SCCs were transformed to somatic cell scores (SCS). A random regression test-day animal model through four-trait three-lactation was used to estimate variance components for test-day records of SCS and lactation traits were included. Gibbs sampling was used to obtain marginal posterior distributions for the various parameters using a single chain of 200,000 iterates in which the first 50,000 iterates of each chain were regarded as a burn-in period. The mean heritability estimates for SCS (0.15 to 0.18) were lower than those for milk yield (0.36 to 0.38), fat yield (0.30 to 0.31), protein yield (0.31 to 0.32), fat percentage (0.21 to 0.25), and protein percentage (0.21 to 0.22). Low negative genetic correlations ranging from −0.05 to −0.30 were found between SCS and yield traits . The genetic correlation found between SCS and fat percentage was close to zero, however, a low positive genetic correlation ranging from 0.12 to 0.17 was found between SCS and protein percentage. Based on the results, it can be concluded that genetic selection for decreasing SCS would also increase lactation yield. The estimates found in this study can be used to perform breeding value estimations for national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model. There are about seven million cattle in Iran, of which some 700,000 are Holstein distributed in more than 2000 herds. The herd sizes vary from 20 to 3000 dairy cows with a mean 305-day milk production of 7200 kg ,2. AlthoData used in this study were test-day records from Holstein cows collected between January 2009 to December 2018 by the Animal Breeding Center of Iran . All evaluated herds were purebred Holsteins, managed under conditions similar to those used in most developed countries, and were under official performance and pedigree recording. The diet, fed as a total mixed ration (TMR), mainly consisted of corn silage, alfalfa hay, barley grain, fat powder, beet pulp, and feed additives. Monthly milk recording was performed by trained technicians of the Iranian Animal Breeding Center, according to the guidelines of the International Committee for Animal Recording [th class of HTDp, and jth class of AS, th class of herd-test-day parity, The following random regression (RR) test-day animal model through four-trait three-lactation was used to estimate variance components for test-day records of MY, FY, PY, FP, PP, and SCS: program . Gibbs sDescriptive statistics of the dataset used for parameter estimation for all traits included are shown in The phenotypic, permanent environmental, genetic, and residual variances by DIM for SCS in each parity are presented in 2 of SCS in the first parity compared to those for higher parities was lower in early lactation, but higher in mid and late lactation. The heritability pattern found in the second parity was the same as that found in the third parity. The mean (range) heritability estimates across lactation for SCS were 0.18 (0.11 to 0.20), 0.15 (0.11 to 0.17), and 0.15 (0.12 to 0.17), respectively, in the first, second, and third parities.The patterns of estimated heritabilities on a daily basis for SCS in the first three parities are represented in The average phenotypic, genetic, and permanent environmental correlations between SCS and production traits are presented in Lower SCS was found at peak milk yield, then increased for the remainder of the lactation which is in close agreement with previous studies ,11. The Genetic parameters were estimated for SCS in Iranian Holstein dairy cows using a random regression test-day model. SCS had a low negative correlation with the production traits, but its magnitude increased in later parities. The moderate heritability for SCS and its low negative genetic correlations with yield traits indicates that genetic selection for decreasing SCS would have a relatively medium genetic progress with no necessarily antagonistic effects on lactation performance. The estimates found in this study can be considered as the first step to include SCS in the national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model.


Rhipicephalus sanguineus sensu lato. Different studies worldwide have reported the occurrence of different well-defined lineages, in addition to Rhipicephalus sanguineus sensu stricto. To date, there are very few studies examining the diverse aspects of this tick in Colombia. We assessed the population structure and genetic diversity of R. sanguineus s.l. in eight departmental regions across Colombia.There has been a long-standing debate over the taxonomic status of R. sanguineus s.l. and subjected to genetic analysis. DNA sequences were obtained for the 12S rDNA, cytochrome oxidase I (COI) and internal transcribed spacer 2 (ITS2) markers. A concatenated set of all mitochondrial markers was also constructed. Next, maximum likelihood phylogenetic trees were constructed using the sequences generated herein and sequences available in GenBank. Finally, we assessed different summary statistics and analysed population structure and divergence with Fst and Dxy and demographic changes with Tajima's D and Fu and Li’s statistical tests.A total of 170 ticks were collected from dogs in different departments of Colombia. All specimens were morphologically compatible with COI revealed that all R. sanguineus s.l. specimens collected across different regions of Colombia clustered within the tropical lineage. Micro-geographical analyses showed that the tick population from Amazonas formed a distinct cluster separated from the other sequences, with moderate Fst and Dxy values. However, no signs of a robust population structure were found within the country. The results of Fu’s FS tests, together with the haplotype networks and diversity values, signal a possible population expansion of this tick species in Colombia.Analysis of the 12S rDNA and Evidence provided herein supports the tropical lineage as the main circulating lineage in Colombia, exhibiting a general lack of genetic structure except for the Amazonas region.The online version contains supplementary material available at 10.1186/s13071-021-04898-w. Rhipicephalus belong to the Metastriata group, which includes species distributed across most continents, displaying the most abundant diversity of species, mostly in Africa [Rhipicephalus sanguineus sensu lato, also known as the brown dog tick, is probably the tick with the largest global distribution [Rhipicephalus spp. ticks are known to cause high morbimortality in livestock leading to huge losses in meat and dairy production [Rhipicephalus spp. ticks have also been identified as vectors for the causative pathogens of spotted fever group rickettsioses, babesiosis, ehrlichiosis and hepatozoonosis among others [Ixodid ticks are one of the most important pathogen vectors for humans and domestic animals worldwide . Ticks on Africa , 3. Rhipribution , primariribution –7, and cribution . In addioduction . Indeed,g others , 10.R. sanguineus s.l. is considered to be a complex of species [R. sanguineus sensu stricto described by Latreille in 1806. The taxonomic classification of R. sanguineus s.s. has long been a matter of debate [R. sanguineus s.s., frequently identified using traditional taxonomic keys [R. sanguineus s.l., unless it is assigned to reference sequences of R. sanguineus s.s. .COI) and 12S rDNA have demonstrated the existence of two major distinct lineages, whose distribution is tightly linked to geographical and climate patterns. The first is located between latitudes 25°N and 22°S and the second is found closer to the poles, above 25°N and below 22°S [R. sanguineus s.s.) have been coined to define the presence of these two major lineages [R. sanguineus s.l.) present in Paraguay and tropical regions of Argentina, and R. sanguineus s.s. found at more temperate localities in Chile, Uruguay and Argentina. In relation to vector competence, it is known that pathogen transmission varies in relation to lineages, with the tropical lineage exhibiting higher vector competence and increased transmissibility in contrast to R. sanguineus s.s. [Genetic studies interrogating mitochondrial genes such as 18S rDNA, cytochrome oxidase  that could represent previously described or newly discovered species [A more in-depth study by Dantas-Torres et al.  further  species . From a  species . Interes species , confirm species . Still,  species  suggesteR. sanguineus s.l. and its potential biogeography showed a link between lineages and different bioclimatic variables, particularly temperature. Zemtsova and co-workers were the first to delineate the geographical distribution of R. sanguineus s.l. [R. sanguineus s.s. was found at temperatures ranging between 10 and 20 °C [R. sanguineus s.l. has allowed both lineages to co-occur in the same regions [Parallel population studies aimed at establishing the systematic relationships within eus s.l. . In thei regions  and ArgeR. sanguineus s.l. at a global scale. However, studies on the genetic variability of this tick in Colombia and across its diverse ecosystems are still scarce [R. sanguineus s.l. have yet not been conducted. In this study, we aimed to assess the current genetic diversity of R. sanguineus s.l. ticks across departments and various biogeographical regions including Amazonas, Andes, Caribbean, Orinoco and the Pacific.A number of studies have provided information about the biology and genetic diversity of l scarce . Also, pR. sanguineus s.l. ticks were collected from owned dogs, across eight different departments encompassing five out of the six main ecoregions in Colombia. Samples from the Amazon region included 59 ticks from the Amazonas Department  and two from Putumayo . Samples from the Andean region included eight ticks from Cundinamarca . From the Caribbean region, four ticks from Bolívar , 38 from La Guajira  and 33 from Magdalena  were included. Orinoco and Pacific region samples included 23 ticks from Meta  and three from Valle del Cauca , respectively. Additional information has been included in Additional file A total of 170 adult Ticks were manually removed and stored in RNAlater  after coDNA extraction was performed using a commercial kit  following the manufacturer's recommendations, with the exception that bead-based disruption was replaced by manual disruption. DNA purity was assessed by measuring the absorbance at a 260/280 ratio using the NanoDrop system (Thermo Fisher Scientific), followed by sample storage at −20 °C until use.COI (709 bp) and internal transcribed spacer 2  molecular markers were amplified by PCR in a Labnet thermal cycler  using previously reported primers sets , Amplicons were separated based on size in a 2% agarose gel stained with SYBR Safe and visualized in the MiniBIS Pro (DNR Bio Imaging Systems). Those that showed a single product were subsequently purified with ExoSAP  according to the manufacturer’s instructions and bidirectionally sequenced (with specific primers for each marker) using the Sanger method at Macrogen Inc. . Geneious software  was usedCOI), as previously reported for the identification of lineages traditionally accepted for R. sanguineus s.l. [COI, 464 bp in 161 sequences; and for ITS2, 920 bp in 154 sequences. Concatenation of mitochondrial markers was carried out in alphabetical order, obtaining 146 sequences 790 bp in length.The sequences obtained were aligned using the MUSCLE method  in UGENEeus s.l. . AnalysiR. sanguineus”, which included information regarding its geographical origin. A total of 42 sequences for the 12S rDNA marker, 66 for COI and 54 for ITS2 were included.In order to better represent the diversity for each marker, haplotypes were depicted by geographical regions, using DnaSP v6 software . HaplotyIQ-TREE version 1.6.12  was usedFinally, in order to observe the relationships between the sequences obtained for Colombia, haplotype networks were constructed by means of the TSC method in PopART  software . PhylogeD [FS test of selective neutrality was performed, based on the infinite sites model [Genetic diversity was assessed for each genetic marker and the concatenated set using DnaSP software . The totD  evolutioes model , in ordeCOI and 12S rDNA) showed similar topologies for both trees and phylogenetic networks , tropical lineage of R. sanguineus s.l., Rhipicephalus sp. I , Rhipics sp. IV . All theR. sanguineus s.l. lineages. Lastly, the ITS2 marker analysis presented great differences in tree topology, lacking significant grouping and/or differentiation trends among lineages  and finally ITS2 , where the concatenated mitochondrial markers showed a good intermediate representation between 12S rDNA and COI (Table Low levels of genetic diversity (pi and theta) were observed across all samples from Colombia, contrasting with the high number sequences available from around the world Table . In termD* and/or Fu and Li's F* values for one marker. COI with −2.661119 and −2.36679, respectively, proved significant for both statistical values, in addition to the concatenated sequences (P < 0.05), with a Fu and Li’s D* value of − 2.37026. In contrast, 12S rDNA and ITS2 failed to reveal significance for either statistical value. Tajima'D values were also very low (between −0.50354 and −0.96082), except in the ITS2 marker (0.9155), showing no statistical significance for any marker or the concatenated sequences.High levels of haplotype diversity were observed for most markers, with values ranging between 0.318 and 0.850, suggesting a recent population expansion. This hypothesis was supported by obtaining significant Fu and Li's D values were determined in these sequences but failed to show significance , but there was no clear clustering for these departments in the corresponding tree. The rest of the departments showed Fst values ranging from 0 to 0.10, and Dxy between 0 and 0.003, with some negative values of Fst in COI for Cundinamarca and Guajira.Finally, analysis of genetic diversity indexes by regions showed moderate values of Fst and Dxy in sequences from Amazonas , a trend that was consistent for all markers evaluated. The Fu/Li and Tajima's R. sanguineus s.l. [R. sanguineus s.l. from across different regions of Colombia in order to elucidate the phylogeographical landscape of this tick species through diverse regions and its potential influence on the observed genetic variation. Results obtained from previous studies have revealed the tropical lineage as the only clade currently circulating in Colombia [R. sanguineus s.l. populations, as a consequence of their recognized limitations to adapt to different environmental conditions [R. sanguineus s.s. from Colombia [R. sanguineus s.s. is actually established in any geographical region of Colombia. In addition, other factors influencing the biology of this species need to be looked at, including (i) the range of host species, particularly wild synanthropic animals known to serve as hosts for these ectoparasites [R. sanguineus s.s. and tropical lineage have been reported [R. sanguineus s.l. populations.Despite the wide distribution of eus s.l.  and its eus s.l. –7, littlColombia . In genenditions . IntriguColombia  suggestsarasites ; (ii) a reported . AssessiR. sanguineus s.l. lineages [Our phylogenetic network analysis using all available sequences Fig.  revealedlineages , and thelineages . Given tlineages  and thatlineages . Still, R. sanguineus s.l. lineages/species, grouping all the collected ticks into a single cluster. In fact, low resolution for species-level identification has been previously documented for R. turanicus [When assessing levels of genetic variation in our study, we found that the ITS2 failed to finely resolve uranicus , highliguranicus . In thisR. sanguineus s.l.Deciding on the most appropriate marker for tick-specific genetic population studies is a difficult task. However, mitochondrial genes have become the preferred standard given that their mutation rate enables resolution to a species level, proving highly informative for the purpose of phylogenetic and taxonomic studies. In our study, the use of concatenated mitochondrial markers allowed us to reconstruct phylogenetic relationships with higher confidence. We believe that following a combined approach that includes both the integration of new and further concatenation of mitochondrial markers will help achieve a higher resolution than using single gene-based molecular markers. Moreover, the inclusion of the analysis of mitochondrial genomes would provide better scrutiny of deep-level relationships, allowing us to reconcile phylogenetic controversies in tick taxonomy, particularly in the phylogenetic diversification of R. sanguineus s.l. in Colombia. We found a high diversity of haplotypes along with low nucleotide diversity for all markers, a pattern known to define the genetic signature of populations that had undergone geographical expansion followed by bottlenecks [FS  for most of the markers assessed  reveals a different scenario, depicting moderate levels of structuring which could be explained based on its geographical remoteness and isolation and limited human and host mobility. A similar pattern of structuring has been documented for the tick in hosts , 44. Int species . Future R. sanguineus s.l. evidenced in this study could have important repercussions for pathogen transmission, considering that vertical transmission of pathogens such as Phlebovirus and Coxiella has been reported in ticks [R. sanguineus population across different regions in Colombia could possibly lead to an increase in diversity of tick-borne pathogens. Understanding the genetic structure of these ticks serves as a proxy indicator to infer the potential spread of these pathogens. Because genetic differences among different tick lineages may influence the ability to transmit different pathogens, further studies would be very informative to determine the wide variety of pathogens that this species transmits both country-wide and in the Amazon region. Correlating patterns of tick genetic variation with pathogen profiling will provide the most valuable insights into the epidemiology of tick-borne diseases caused by pathogens transmitted by R. sanguineus s.l. in Colombia.Information provided from population genetic structure studies is key to deciphering the many intricate aspects of host-vector-pathogen systems. In fact, different population structures are known to modulate diverse aspects of disease dynamics . The lowin ticks , 47. PotR. sanguineus s.l. in Colombia. Although a wide range of departments and varied ecosystems were surveyed, our results revealed the exclusive circulation of the tropical lineage all across the country. However, circulation of other lineages cannot be ruled out, particularly in light of the evidence for genetic admixture observed in this study. Our study also found signs of a recent demographic expansion as supported by normality tests. No strong signs of genetic structuring were found, except for the Amazon region, highlighting the importance of future studies in order to elucidate genetic connectivity across different tick populations. The domestic dog appears to play the most important role in dispersal and thus in determining gene flow amongst R. sanguineus s.l. nationwide, except for the most isolated regions like the Amazon, where most of the bioecological features of this tick have yet to be deciphered. This study represents the first detailed approach for characterizing the population structure and geographical distribution of this vector in Colombia and its possible implications in disease transmission. Tick-associated pathogen profiling, potential circulation of other lineages and vector competency are intriguing questions to be addressed in future studies of R. sanguineus s.l. in Colombia.This study is the first to characterize the genetic structure of Additional file 1:Table S1. Information on the ticks collected in this study.Additional file 2:Table S2. Primers used for amplification by PCR in 12S rDNA, COI, and ITS2. Table S3. Amplification conditions for each marker used.Additional file 3:Figure S1. Phylogenetic tree with sequences available for the ITS2 marker. Rhipicephalus bursa (GenBank: KM986320) was used as outgroup. Bootstraps >60% are shown. Sequences generated in this study are in bold.Additional file 4:Figure S2. Haplotype networks, phylogenetic trees, and haplotype distribution of the sequences generated in this study. a 12S rDNA. b COI. Rhipicephalus leporis  was used as outgroup. Bootstraps >60% are shown.Additional file 5:Table S4. FU’s tests in the Amazonas Department and the phylogenetically separated population by the mitochondrial markers and their concatenated set (Concatenated M).Additional file 6:Figure S3. Genetic structure values Fst and Dxy. a 12S rDNA. b COI.


Daphnia population shows that standing genetic variation in over 500 genes follows an evolutionary trajectory that parallels the pronounced and rapid adaptive evolution of multiple traits in response to predator-driven natural selection and its subsequent relaxation. Genetic variation carried by only five founding individuals from the regional genotype pool is shown to suffice at enabling the observed evolution. Our results provide insight on how natural populations can acquire the genomic variation, through colonization by a few regional genotypes, that fuels rapid evolution in response to strong selection pressures. While these evolutionary responses in our study population involved hundreds of genes, we observed no evidence of genetic erosion.We lack a thorough understanding of the origin and maintenance of standing genetic variation that enables rapid evolutionary responses of natural populations. Whole genome sequencing of a resurrected  Standing genetic variation allows natural populations to evolve rapidly. Genome sequences of a resurrected Daphnia population show that genetic variation carried by only five founding individuals from the regional genotype pool is enough to fuel rapid evolution in response to strong selection pressures with no evidence of genetic erosion. Such rapid trait change provides resilience to the elevated pace and magnitude of human-driven environmental change3. But there is much uncertainty on how this genetic variation is acquired, structured, and maintained, and how precisely natural selection induces genome-wide changes when multiple loci or genes are involved.Natural populations can adapt to environmental change within a few generations when there is sufficient genetic variation to support trait evolution in response to selection6. Such selective sweeps are responsible for detecting “footprints” of natural selection in genomes. Yet, they also conceal the identity of the actual loci targeted by selection, which can be revealed by witnessing changes over time.Complex adaptive traits are assumed to be shaped and to evolve through changes in many loci. We know from theory that if change in the frequency of a beneficial allele under positive selection is more rapid than the regional recombination rate, the variation within genomic regions around the selected locus will be distorted by hitchhiking on linked DNADaphnia over time. The crustacean Daphnia is a keystone species in the food chains of lakes and ponds and an important model organism in ecology and evolution7. Its life cycle includes a stage of diapause during early development, producing a dormant stage that can be retrieved from dated lake sediments and resurrected to capture population-level genetic diversity through time8.Here, we directly quantified changes in genome-wide sequence variation in response to strong predator-driven selection and subsequent relaxation of that selection in a natural population of the waterflea Daphnia population that shows an elaborate evolutionary response to changes in fish predation pressure9, we demonstrate (i) that the rapid evolutionary response observed in this population is largely based on standing genetic variation and (ii) that this standing genetic variation is maintained through time, irrespective of the responses to selection. By also sequencing genotypes from other spatially distributed populations that differ in terms of fish predation pressure, we also demonstrate (iii) that standing local genetic variation in the temporal population reflects regional standing genetic variation and (iv) that a few founding individuals from the regional genotype pool suffice to establish the extensive standing genetic variation fueling rapid evolution in natural populations of Daphnia.In this work, by resequencing the genomes of resurrected genotypes over time of a natural Daphnia magna that persisted through a well-documented and pronounced change in fish predation pressure  . The allele-frequency changes over time were not significant for 94.45% of all SNPs )11. This result suggests that there is little-to-no contribution of genetic drift in structuring the genome-wide polymorphisms within this population, which is corroborated by the very large estimates of effective population size (Ne ~ 1.66 million)  across the sequenced genomes of 36 individuals. The level of genetic differentiation between temporal subpopulations measured across all SNPs was low . This result indicates that only a small fraction of the genome responded to predation selection, and that transition from pre-fish to high-fish (six years) induced twice as many changes compared with the transition from high-fish to reduced-fish (10 years) .During the pre-fish to high-fish transition, 4.23% of the overall SNPs showed a significant change in allele frequency, while during the later transition from high-fish to relaxed-fish, 1.55% of SNPs showed significant allele-frequency changes . In contrast, only 18 (0.05%) of the SNPs showed a significant frequency change in the same direction across both transition periods over which we quantified evolution   Fig. .Fig. 2Al4. These arise when strong selection results in a rapid increase in the frequency of beneficial alleles and ancestral variation from nearby region hitchhikes along with these changes in the frequency of targeted alleles4.The rapidly shifting allele frequencies across thousands of SNPs that mirror the response trajectory of evolved phenotypic traits Fig.  and aligP value = 9.78E-20) and on average contain a greater number of genes  than the islands of divergence identified for the second transition  based on a hidden Markov model  were located in overlapping regions of these genomic islands (representing 0.83% of the D. magna genome), and are thus potentially under directional selection due to changes in predation pressure. This signal is quite reliable, given that the majority of overlapping highly differentiated genomic islands between the pre-fish to high-fish and the high-fish to reduced-fish transitions  only contain one gene. The remaining of overlapping regions of highly differentiated genomic islands also harbor only two (16.7%) or three genes (9.1%). The nonoverlapping regions contain 131 genes (1.06% of genes in Daphnia), which likely hitchhiked with target genes of selection during the first transition. In other words, 72.30% of 473 detectable genes through the analysis of genomic islands of divergence harbor reversible variation that is potentially targeted by natural selection , which is linked to phototactic behavior9, the Wnt signaling pathway , and the mTOR signaling pathway . Phototactic behavior shapes diel vertical migration, a well-known fish-avoidance strategy that is known to have evolved in this population.Tracking the dynamics of genomic islands and the action of recombination during the sequel of natural selection and its subsequent relaxation allows us to identify those potential regions of the genome that are differentiated because of positive selection vs linked responses during the first transition. We identified 390 genomic islands representing 1.93% of the genome in the pre-fish to high-fish transition that overlaps with 406 smaller genomic islands representing only 1.21% of the genome during the high-fish to reduced-fish transition Fig. . A totalDaphnia faced increasing fish predation. Rarefaction analysis revealed that five randomly selected individuals from the prefish temporal subpopulation captured most of the polymorphisms, as they were on average polymorphic for 65% of the SNPs in the genomic islands  of the founding  temporal subpopulation. This result suggests that the original founders were carrying all of the genetic variation that enabled the adaptive evolution of multiple traits in response to an increase and subsequent relaxation of fish predation pressure. The pre-fish temporal subpopulation is indeed highly polymorphic for these SNPs, with single individuals being polymorphic for 15–46% of all SNPs residing in the genomic islands that were potentially under directional selection when nds Fig. . These pnds Fig. . These rOne plausible way in which standing genetic variation builds up in a local population is through immigration of genotypes from the surrounding landscape, either during colonization or through subsequent immigration. To assess regional genetic variation, we resequenced whole genomes of genotypes from twelve populations inhabiting ponds in the region , of which six harbor fish and six are devoid of fish  are hitchhiking with the targets of selection. The majority of alleles that showed significant frequency changes during a period of intense selection also showed a reversal after relaxation.Our study of a resurrected population, benchmarked against a spatial survey at the landscape level, reveals how natural populations can harbor substantial standing genetic variation that can be built up through colonization or immigration of just a few regional genotypes, and how standing genetic variation is structured through changing selection pressures over time. Polygenic predator-driven selection shaped approximately 1% of the 13 and about 3% of the genes14. In another example, host races of the pea aphid living on alfalfa, clover, or pea differ in 9.12% of the genome and up to 8.10% of the genes15. While these examples represent major changes in habitat , the pattern of evolution documented in the present study represents a response to an in situ environmental change occurring during a time period of a few years, documented through data on whole genomes sampled through time. Size-selective predation by fish not only differs among habitats but can also rapidly change through time within the same habitat.Patterns of adaptation to strong environmental gradients that are driven by a relatively small proportion of the genome but involving several hundreds of genes have been shown before in both vertebrates and invertebrates. For instance, freshwater adaptation in three-spined stickleback elicits responses involving <0.5–15% of the genomeDaphnia populations. More likely the absence of genetic fixation might reflect the polygenic nature of the traits under selection, resulting in a relatively weak selection pressure on individual loci. Furthermore, our data suggest that the maintenance of high-standing genetic variation is also due to very large effective population sizes (>1.106), which are locally sustained by an extensive dormant egg bank, despite seasonal declines of Daphnia populations16. The combination of dormant egg banks and fluctuating environments further enhances the maintenance of standing genetic variation17, which enables rapid evolution and provides a high evolutionary rescue potential18 permitting effective adaptive responses to environmental change, as observed in other studies on natural Daphnia populations20.Our results show that the substantial genetic variation enabling the observed rapid genome-wide response to predation in our study population can be obtained from even a very limited number  of founding individuals from the regional gene pool. Despite strong response to selection, we did not observe complete fixation of allelic variants, resulting in the maintenance of genetic variation. This lack of fixation might reflect that the periods of directional selection were relatively short in this population. Strikingly, however, we observed the same level of genetic polymorphism for SNPs under potential selection also in our spatial survey, both in populations with and without fish . This suggests that if the maintenance of genetic polymorphism is a reflection of short phases of directional selection, this is a common phenomenon across 21), our study also yields empirical evidence for the evolutionary rescue potential that even a few colonists derived from multiple populations in the landscape can provide. A modeling study similarly predicted that a few migrants might facilitate rapid freshwater adaptation in sticklebacks22, and a study on carabid beetles living in habitats that differ in predictability revealed that as few as ten individuals in most cases were enough to provide the standing genetic variation to allow evolution from long-winged to short-winged morphs23. Standing genetic variation seeded during colonization or subsequent immigration by a limited number of genotypes whose genome bears the legacy of divergent selection in the past might be a common facilitator of rapid evolution, and might explain the growing number of studies reporting rapid adaptive evolution in nature1. Rapid evolution fueled by standing genetic variation has been shown in both vertebrate25 and invertebrate taxa27. The insights offered by our study on the origin and maintenance of standing genetic variation are highly relevant in the context of how evolution can modulate ecological responses to global change31.In addition to delivering rare insights into the temporal dynamics of standing genetic variation . This may be crucial for the long-term maintenance of regional diversity, as it ensures that a few colonists or immigrants seed diversity in local populations, irrespective of their origin. The resulting local standing genetic variation allows divergent responses to environmental gradients, which in turn again contributes to the maintenance of regional genetic diversity. Thanks to the large effective population sizes, local populations can be ecologically responsive while maintaining evolutionary potential to respond to future changes.The emerging pattern from our study is one of high regional genetic polymorphism that is likely maintained at the landscape level through differential selection regimes across ecologically divergent habitats33, and most traits are polygenic. Our results also testify to the importance of standing genetic variation. Maintenance of genetic diversity is an important biodiversity goal34, and likely requires multiple sufficiently large populations because of the interdependence of local and regional genetic diversity. Protection and restoration of the evolutionary potential of larger-bodied and less common species that are characterized by low effective population sizes and suffer from loss of evolutionary potential36 should be a high priority, and requires a landscape perspective.We suggest that the patterns we observe are likely general, given that many species, especially invertebrates, are often characterized by large effective population sizesa D. magna population (OHZ) from a small, shallow man-made pond in Oud-Heverlee, Belgium (50°50´ N– 4°39′ E). This pond was constructed for pisciculture in 1970 and has a detailed record of fish-stocking densities for 16 years  the pre-fish period (1970–1972), during which no fish were stocked in the pond; (2) the high-fish period (1976–1979), a period with high fish-predation pressure due to intensive fish stocking; (3) the reduced-fish period (1988–1990), with relaxed fish predation pressure due to a reduction in fish stocking  were sampled from fishless ponds, while six populations  were sampled from ponds that harbored fish  for quality checks. Subsequently, low-quality base trimming and adapter cleaning was performed using the Trimmomatic software38. Here, parameter values to remove adapter sequences were chosen for seedMismatches (2), palindromeClipThreshold (30), and simpleClipThreshold (10). The minimum phred quality required to keep a base was set to 28, and the minimum read length to 50 bp. Furthermore, the cleaned reads were mapped to the D. magna genome version 2.439 using Bowtie240 software with very-sensitive parameter settings  and insert size between 200 and 700 bp. The mapped reads were then marked for duplicates using the MarkDuplicates feature of Picard tools (http://broadinstitute.github.io/picard/) to avoid PCR duplicates. The resulting sorted BAM files were then used for variant calling using FreeBayes41. FreeBayes41 is a haplotype-based variant caller that calls SNPs, indel, and complex variants. Minimum base quality was set to 30 with minimum coverage of four reads. We obtained more than 3 × 106 raw variants (3 441 615) for the OHZ temporal subpopulations and 6 × 106 raw variants for the spatial populations.The paired end reads (100 × 2) of each individual were first analyzed using FASTQC  were removed retaining a total of 724,321 SNPs  for the temporal analysis of the OHZ population and 748,511 SNPs for the spatial populations. These SNPs were used for downstream analyses.Only biallelic SNPs supported by at least four reads and sequenced in at least 90% of individuals were retained after filtering. The draft genome of ST; Weir & Cockerham 198442) using the diffCalc function of the diveRsity43 package in R44. These calculations were performed for each pair of temporal subpopulations  in the temporal setting (OHZ) and for six random pairs of nonfish and fish populations in the spatial survey.We calculated both genome-wide and locus-specific levels of genetic differentiation (Fhttps://github.com/vcflib/vcflib) to set genotypes that are most likely to be true based on maximum genotype likelihood. We then identified the significant differences in allele frequencies between temporal subpopulations over time  using a modified chi-square test developed by RS Waples (Waples 1989)11 and implemented in the TAFT software45 (hereafter referred to as Waples test) that accounts for effective population size (Ne), yielding 30,669 significant SNPs  by comparing the prefish and high-fish temporal subpopulation and yielding 11,257 SNPs  for the high-fish and reduced-fish temporal subpopulation comparison; 1771 SNPs showed significant allele-frequency changes in both transitions, most of them also showing a significant reversal in the second transition. To determine whether the observed number of SNPs that showed a significant reversal in allele frequencies is higher than expected by chance, we estimated the null distribution by randomly permuting the temporal subpopulation labels  and alleles per locus , and recalculating the number of reversals based on Buffalo and Coop 202012.To calculate allele frequencies in the temporal analysis, we used vcfglxgt function of vcflib (Ne) were calculated from θ = 4Neµ, across the whole genome and with a mutation rate per generation of 4 × 10−946 and a generation time of one year , where Ɵ is Watterson’s diversity index and µ is mutation rate. Watterson Ɵ was calculated using the folded SFS option in ANGSD software47 and found to be stable, i.e., near 0.03 across the three subpopulations . The calculated Ne was found to be ~1.66 million in the prefish temporal subpopulation and ~1.72 million for the high-fish and reduced-fish temporal subpopulations. Similarly, for spatial populations, the value ranges from ~1.06 to 1.45 million , a Gaussian distribution of log10(FST + 1) was assumed with the mean and variance initialized as those of the log10(FST + 1) values within each respective level. We then used the Baum–Welch algorithm49 to refine the Gaussian model for each state and the transition matrix among the states. Direct transition from the low to the high state was not allowed. Hidden states were then estimated from the data and we estimated the parameters by the Viterbi algorithm using the R package HiddenMarkov50. A high differentiating island between genomes is defined to contain at least three consecutive SNPs categorized as high-state SNPs by HMM, yielding 6111 and 2879 islands of genomic differentiation between the prefish vs high-fish (mean length: 2428 bp) and the high-fish vs reduced-fish comparison (mean length: 1713 bp), respectively. Similarly, for six independent spatial fish vs no-fish comparisons, the number of islands of differentiation ranged between 4136 and 7493 (with range of mean length 1879–3290 bp), depending upon the comparison  was used to distinguish genomic regions of high, moderate, or low differentiation among (sub)populations. We used a similar approach as used earlier by Soria-Carrasco et al. (2014)P values smaller than 0.01) in the comparison among temporal subpopulations (prefish vs high fish and high fish vs reduced fish) and in HMM-based high-differentiation islands in spatial comparisons. Transcriptome-based functional annotation was performed using the Daphnia magna genome version 2.439. The pathway enrichment analysis was performed using the orthologous genes of D. magna in the D. pulex genome51 based on OrthoDB gene families52 and the KEGG pathway database53. Out of ~29,000 annotated genes of D. magna, 17,400 genes have 17,832 orthologs in D. pulex. However, due to the fragmented status of the D. magna genome assembly, manual curation for high-quality gene models resulted in a total of 12,264 D. magna genes used in our study, of which 2402 genes are annotated to KEGG pathways. Ortholog mapping is not unique. A given gene from the source species, here D. magna, can map to a single, multiple, or no ortholog in the target species, here D. pulex. This can bias statistical tests when referencing to D. pulex genomics resources. We used the number of nonunique mappings for each D. magna gene on the KEGG pathways of D. pulex to weight-adjust the confusion matrix for Fisher’s exact test to obtain the correct P values. Significant pathways are defined as those with FDR corrected (Benjamini–Hochberg method) P values smaller than 0.05. The data analysis was performed using Python packages .We investigated the function of the outlier SNPs  as well as the youngest temporal subpopulation  represent. In the first set of analyses, we used the 1109 SNPs belonging to the divergent SNPs that showed significant changes in allele frequencies in the prefish to high-fish transition and also a significant reversal during the high-fish to reduced-fish and were potentially under positive selection (i.e. excluding hitchhiked SNPs) in the OHZ population. This group of SNPs represent polymorphisms that are presumably adaptive or at least contribute to adaptive allelic variants and hence contribute to the adaptive potential of the temporal subpopulations. The analyses were performed by rarefying the genotype matrix of all 12 individuals from either the prefish or the reduced-fish population to all possible  subsets of samples of 1–12 genotypes. For each of these subsets we then calculated the average proportion of polymorphic SNPs. These values were plotted against sample size to generate rarefaction curves. Similarly, rarefaction analyses were performed for the 1003 SNPs belonging to the outlier SNPs that were potentially under positive selection  in the OHZ population and that were also present as SNPs in the full spatial dataset . In this case, rarefaction curves were plotted by randomly resampling (1000 times) 1–30 individuals from the total of the 111 individuals of the Leuven regional populations in the spatial data set  to the focal OHZ population).Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Toxoplasma gondii is a major zoonotic agent which may cause harmful effects mainly in pregnant and immunocompromised hosts. Despite many efforts on its genetic characterization, an entirely clear picture of the population structure in Europe has not been achieved yet. The present study aimed to summarize the available genotyping information and to map the distribution of circulating strains. There is consensus on type II T. gondii genotypes prevailing in Europe, but the absence of harmonization in the use of typing methods limits detailed knowledge. Standardized, high-end typing tools and integrative strategies are needed to fill the gaps and complete an accurate image of the T. gondii genetic population in Europe. Toxoplasma gondii, the etiologic agent of toxoplasmosis, is an apicomplexan obligate intracellular protist of major medical and veterinary relevance. The complex life cycle of T. gondii is defined as facultative heteroxenous, with virtually all warm-blooded animals as intermediate hosts , and members of the Felidae family acting as definitive hosts , which can accumulate T. gondii oocysts by water filtration     and dises (MCDA) . Congeni system) .T. gondii circulating in Europe, type II strains and, to a lesser extent, type III strains, are the dominating populations, both in domestic and wild environments .Because of the importance of a genetic characterization of T. gondii populations circulating worldwide  markers led to solid observations on the predominance of three clonal/archetypal types or lineages in Europe and North America, but new concepts of “recombinant” and “atypical/non-canonical” strains appeared on the scene , provided an excellent and continuing foundation for further population genetic analyses.During the 1990s, restriction fragment length polymorphism (RFLP) among other methods allowed researchers to establish the existence of three clonal lineages distinguished according to their virulence for mice. Type I isolates were 100% lethal to mice, irrespectively of the dose, while types II and III were moderately or non-virulent in a dose-dependent manner . Since the scene . Later, e , the esT. gondii contains 13 chromosomes, with a total genome size of about 65 million base pairs (Mbp) and more than 8300 protein coding genes identified  1, 2 and 3) were joined by a fourth clonal lineage (HG12) largely confined to North America, where it is more common in wild animals. In contrast, much greater genetic diversity is observed in South America, where the population seems to consist of a few major clonal complexes and abundant less related isolates .T. gondii populations could be a mixture between both above situations, with abundance of isolates belonging to type I, II, and III clonal lineages, coexisting with a considerable number of other recombinant or atypical genotypes, but exhibiting a less divergent character than in South America; however, both continents remain poorly explored, especially in tropical regions  or environmental matrices  considered. Both T. gondii strain genotyping studies involving isolated viable parasites or DNA positive specimens/clinical samples from Europe were included. Nevertheless, data from overseas territories in other continents and zoo-kept animals were not covered, in order to better limit the origin of infections to continental Europe. Finally, 101 and 43 studies including PCR-RFLP/PCR-Sequencing or MS typing, respectively, were selected  probably because it was among the first PCR-RFLP markers described, setting a milestone on T. gondii genetic studies   . RegardiFurthermore, it is observed that regardless of the typing technique used, the collected information (from 21 different countries) is highly unbalanced between countries, and there is a lack of data for large areas of the European continent .Aiming to find the right balance between reliability and robustness, and taking into account the number of studies implementing a different number of PCR-RFLP/PCR-Seq or MS genotyping markers . Based on the One Health concept, we sorted genotypic information according to samples or isolates origin into four “compartments”, namely humans, domestic animals, wildlife, and environment  is a sensitive issue. In most cases this requires the availability of viable parasites in a sample that could be separated into different co-existing clonal populations,  cloning . The unaConcerning strain types detected in humans, only three countries are represented  in five studies with a total of 33 samples typed . Among tMost European (geno)typed samples have been collected from infected domestic (pets and livestock) and wild animals. Regarding domestic animals, the range of countries represented is wider but not enough, with molecular studies from Austria, Czech Republic, Denmark, France, Germany, Ireland, Italy, Poland, Portugal, Serbia, Spain, Switzerland, and The Netherlands  (Dermacentor reticulatus) collected in field areas of Poland  of the total samples collected in 51 different studies included . ReportsToxoplasma molecular markers deposited in NCBI database (https://www.ncbi.nlm.nih.gov/nucleotide?cmd=search) to implement possible phylogenetic analyses. After a detailed screening and manual curation of nucleotide sequences available from T. gondii specific genetic markers (n=7776), only entries from Europe  were extracted (GRA6 (n=86) and SAG3 (n=49). In addition, B1 gene (n=76) was included as it is the marker that better represents the environmental compartment .Under the view of the available literature  (n=54) (Sus scrofa ferus) (n=44)  from a pigeon from Portugal and a wild boar from Italy, respectively  and Portugal (20.6%), together with Austria (27.3%), stood out in the number of genotyped samples. Data from Finland, Germany, Italy, Romania, Serbia, and The Netherlands are also available. In respect of the different hosts studied, most of the samples were collected from chicken (93) and sheep (91) . In pets) (n=54)  and wild) (n=44) . Among sectively .Mytilus galloprovincialis) collected in southern Italy  of the total samples analyzed in 42 studies that meet the criteria of at least 5 genotyping markers characterized , either by human migration or trade. Overall, France, Portugal, Austria, and Belgium are the countries with the highest number of MS genotyping results; in contrast, there are large areas of the continent from which there is no information, especially northern European countries  using PHYLOViZ 2.0a (http://www.phyloviz.net/) was performed. At Locus Variant Level 4 the minimum spanning tree-like structure clearly separated type I, type II, type III and MRA genotyping results , as shown in T. gondii strains involved in human toxoplasmosis where in rural regions T. gondii associated with cases of congenital toxoplasmosis were genetically different between the eastern and western part of the country based on MS typing results eBURST Full MST (goeBURST distance) analysis  of all T results .T. gondii means that researchers face not only the detection of routes or sources of transmission, as in other emerging zoonotic diseases, but also the enormous variety of susceptible hosts that makes it an underestimated and silent concern, only visible in specifically vulnerable groups of populations (immunosuppressed or pregnant hosts). This review examines the distribution of various T. gondii genotypes throughout the European continent taking into account the different One Health compartments. As a whole, the predominance of clonal type II strains is evident, but exhaustive published data collection and analysis suggests the existence of an interesting proportion of divergent strains (MRA), slightly more concentrated in the wildlife compartment. Hence, the dichotomy “domestic versus wild” so manifest in the American continent is possibly present in Europe as well  in Poland, respectively. Clonal type I isolates fully typed by 15 MS markers have been also described infecting humans  was one of the approaches that comes closest to this objective, storing around 1500 strains from different hosts  and from different countries around the world, all genotyped by the widely applied 15 MS markers  data analysis has emerged as the most suitable approach for a thorough analysis of the genetic diversity in T. gondii, its evolutionary history, and population structure. Although WGS is difficult to apply as a routine technique for strain typing, the number of studies using this technology is growing rapidly, mainly due to its enormous potential and the continued costs reduction. WGS data are publicly available only for a few isolates from Europe  of which only two  belong to the dominant clonal type II. The others, although isolated in Europe  are at least partially reminiscent of strains likely originating from other continents, like FOU and BOF (Africa) or MAS (South America)  evidenced in literature between European isolates  . The EurAmerica) . The genisolates .Under the light of the data exposed, authors identified some key questions that should be addressed:T. gondii population structure in Europe?To what extent are the different anthropogenic factors involved in shaping T. gondii biodiversity in the wild in Europe?Is there an unexplored Are traditional typing methods  going to be replaced by Next-Generation or Third-Generation Sequencing techniques?T. gondii help to understand differences in virulence?Will Whole Genome Sequencing of European T. gondii genotyping in Europe, the situation is still blurred and in need of extra and closer look. Still many questions remain unsolved and will constitute medium term challenges for researchers. Some important facts, like the lack of consensus over the methodologies and markers applied, the huge differences in samples’ quality and concentration, the sampling disparities among regions and the fact that vast areas remain unexplored, as well as the scarcity of data from human cases and environment, are the main limitations to having a complete picture. In this respect, epidemiological surveillance systems must be strengthened at many levels, in humans and in livestock industry . Therefore, close collaboration between the medical and veterinary sectors is crucial.Despite many important efforts on T. gondii prevailing in Europe, followed by type III, but the presence of a noticeable proportion of recombinant and atypical genotypes whose phylogenetic positioning remains obscure, deserves further investigation. Standardized, high-end typing tools and integrative strategies within the One Health approach are needed to fill the existing gaps and provide a clear picture of the T. gondii population in Europe.There is consensus on type II All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.MF-E was funded by UCM-Santander/2017 pre-doctoral Grants. MF-E, GS, PM, MJ, LO-M, and RC-B are part of the TOXOSOURCES consortium supported by the funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement No 773830: One Health European Joint Programme.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.The handling Editor OD declared a past collaboration with the author GS.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


BRCA mutations including ovarian, pancreatic, prostate and breast. Access distributions were quantified, and associations with region, cancer type, and socioeconomic variables were investigated using correlational tests. Nationally, in 2020, there were 4,813 genetic counselors, or 1.49 genetic counselors per 100,000 people, varying between 0.17 to 5.7 per 100,000 at the state level. Seventy-one percent of U.S. residents live within a 30-minute drive-time to a genetic counselor. Drive-times, however, are not equally distributed across the country – while 82% of people in metropolitan areas are 30 minutes from a genetic counselor, only 6% of people in nonmetro areas live within 30 minutes’ drive time. There are statistically significant differences in access across geographical regions, socioeconomics and cancer types. Access to genetic counselors for cancer patients differs across groups, including regional, socioeconomic, and cancer type. These findings highlight areas of the country that may benefit from increased genetic counseling provider supply, by increasing the number of genetic counselors in a region or by expanding the use of telegenetics a term used to describe virtual genetic counseling consults that occur via videoconference. Policy intervention to allow genetic counselors to bill for their services may be an effective route for increasing availability of genetic counselors’ services However, genetic counselors in direct patient care settings also face other challenges such as salary, job satisfaction, job recognition, overwork/burnout, and appropriate administrative/clinical support, and addressing these issues should also be considered along with policy support. These results could support targeted policy reform and alternative service models to increase access to identified pockets of unmet need, such as telemedicine. Data and analysis are available to the public through an interactive dashboardIn the US, the growing demand for precision medicine, particularly in oncology, continues to put pressure on the availability of genetic counselors to meet that demand. This is especially true in certain geographic locations due to the uneven distribution of genetic counselors throughout the US. To assess these disparities, access to genetic counselors of all specialties is explored by geography, cancer type, and social determinants of health. Geospatial technology was used to combine and analyze genetic counselor locations and cancer incidence at the county level across the US, with a particular focus on tumors associated with  Advances in genomic research, new testing technologies, increased use of electronic medical records, and general public interest have led to the expansion of precision medicine, which is an approach to patient care that allows doctors to select treatments that are most likely to help patients based on a genetic understanding of their disease . PrecisiBRCA testing for individuals with a personal and/or family history of ovarian or pancreatic cancer, and a personal and/or family history of breast or prostate cancer as long as other criteria are met   . These ry, etc.) . Furthery, etc.) . As suchBRCA mutational status such as breast, ovarian, prostate and pancreatic  offer a method to understand spatial distributions of cancer patients, including subsets of those with cancers associated with ncreatic , and proncreatic –12. The BRCA mutations: breast, ovarian, prostate, and pancreatic cancers) and socioeconomic variables.Geospatial methods were used to understand the relationship between genetic counselor locations, patient population locations, and SDoH in the US. Data were collected along three categories: location of genetic counselors working in direct patient care, incidences of cancers  National Plan and Provider Enumeration System (NPPES) National Provider Identifier (NPI) registry, and the public-facing member directories of both the American Board of Genetic Counseling (ABGC) and the National Society of Genetic Counselors (NSGC) (see The office addresses of the genetic counselors (as self-reported in the public-facing membership directories or present in the business practice location address field of NPPES) were converted into latitude and longitude using Google Maps Geocoding. Individual datasets were cleaned and reconciled into a registry of 4,813 unique genetic counselors across the 50 states and the District of Columbia  United States Cancer Statistics (USCS) program and filtered to county-level statistics on total , breast, ovarian, pancreatic and prostate cancer. Note that USCS does not contain data on Kansas or Minnesota incidence rates, as those states prohibit release of county-level data .County-level demographic data were downloaded from the American Community Survey (ACS) 2018 5-year estimates, including total population, median household income, median age , and estimates of population stratified by sex, race, Hispanic origin, highest educational attainment for those aged at least 25 years, employment status for those aged at least 16 years (either civilian or armed forces), and health insurance coverage . Counties were classified into metropolitan and nonmetropolitan categories using Rural-Urban Continuum Codes downloaded from the Economic Research Service at the United States Department of AgricultureBRCA-associated tumor sites. County shapefiles for GIS were downloaded from the US Census Bureau and used to categorize counties into two groups, depending on whether any genetic counselor latitude/longitude point fell within a county polygon. The distance between each county and the closest genetic counselor was determined by calculating the Haversine distance (surface distance between two points on a sphere) between population-weighted county centroids (from the US Census Bureau) and all providers. Population weighted-county centroids reflect population distributions within a county, in contrast to geographic centroids. The Mapbox Matrix API was used to calculate drive-times to the nearest 20 genetic counselors for each county to render the calculation computationally feasible on standard machines.Patient access to care, in this study meaning patient’s physical proximity to genetic counselors, was calculated at the state level by taking the weighted median of county-level drive-time to the closest provider, weighted by cancer incidence rate, for all cancer types or by each of four p-values were Bonferroni-corrected to account for multiple comparisons. Statistical analyses were performed using the R Statistical Software , with the largest difference between the West and Northeast regions (p = 0.006). There are also significant differences in access between different types of incident cancer patients (p < 0.001), with the largest between prostate and ovarian cancer  — counties with a genetic counselor had a median income of $60,000/year while counties without a genetic counselor had median income under $50,000/year.Further analysis investigated correlations between SDoH and genetic counselor access, revealing significant differences between counties with and without genetic counselor access in all demographic variables – age, sex, race, Hispanic origin, employment status, health insurance coverage and educational attainment , with genetic counselors assumed to provide services only to residents of their states as reported in the NSGC registry. Note that this calculation does not consider the effects of multi-state licensure, i.e., cases in which a genetic counselor could technically provide services in additional states beyond those self-reported due to lack of licensure. Genetic counselors may provide both in-person and telegenetics from the same location.The purpose of this study was to evaluate equity of access to genetic counselors at a national level across the United States. The number of genetic counselors per 100,000 people was 1.49, on average, but this belies considerable state-level variability, ranging from 0.17 to 5.7. These findings show systematic differences in access to care between regions, and provide insight for potential policy action, e.g., in the southern United States where overall cancer incidence is relatively high and genetic counselors are relatively few. Furthermore, there are associations between socioeconomic characteristics and access, with counties with genetic counselors being younger, more diverse, with a higher level of education, and with higher incomes, consistent with previous studies and typical for urban locales , but their per-capita access is 0.5 and 38.8 respectively. Underserved patient populations are revealed for further research, e.g., for policy reform to improve access to either in-person or virtual genetic counseling . For example, Gloucester County, New Jersey had among the poorest mismatches between genetic counselor supply and demand, with one genetic counselor for a population of nearly 300,000 people despite having an annual cancer incidence rate of 542.2 per 100,000, the fifth highest rate across all U.S. counties. To communicate these results more directly to the public an interactive dashboard is available that includes maps of genetic counselor locations and visuals of accessibility distributionsMeasurements of driving time required to see a genetic counselor are particularly telling, showing that most metropolitan residents live within one hour of a genetic counselor, but most nonmetropolitan residents do not. Previous research has shown that patients that are more than an hour from care are less likely to access the health system and are associated with poorer health outcomes , 15. LonThe Supplemental Information includes analogous analysis of available telegenetic access data, but these are complicated by nuances such as differences in state licensure requirements and provider eligibility in payer reimbursement rules, which are beyond the scope of this study as no robust single data source exists to capture these complications. Virtual genetic counseling care has potential to increase patient access to genetic counselors, both in-state with a far driving distance as outlined above or supporting access across state lines as drive time and distance is no longer a barrier. Currently, only 26 states require licensure  to practLimitations of this study include reconciling non-standardized genetic counselor data from NSGC, ABGC, and NPPES which included manual review and may have introduced error. A sensitivity analysis, however, showed no changes in statistical results when the genetic counselor data were subset by source , a drug used to treat certain cancers of interest to this study.The authors declare that this study received funding from Merck & Co., Inc., Kenilworth, N.J., U.S.A and AstraZeneca Pharmaceuticals. The funder had the following involvement with the study: conceptualization, methodology, writing—original draft, writing—review and editing, supervision and project administration.


There is a well-recognized need to include diverse populations in genetic studies, but several obstacles continue to be prohibitive, including (but are not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying multiple diverse populations would provide informative, population-specific insights. Using Native Hawaiians as an example of an understudied population with a unique evolutionary history, I will argue that by developing key genomic resources and integrating evolutionary thinking into genetic epidemiology, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population. Genome-wide association studies (GWASs) have revealed the polygenic nature of human complex traits and diseases , but theGenetic and phenotypic differences between populations can arise through two broad categories of evolutionary mechanisms: demographic events and natural selection. An example of demographic events is a population bottleneck. In a bottlenecked population, alleles with functional, deleterious, consequences can, by chance, overcome the impact of negative selection  to reachAs an illustrative and motivating example, I will describe the challenges and benefits to combine evolutionary insights and genetic studies with the Native Hawaiian population. Though they are one of the smallest ethnic minorities in the United States, consisting of 1.2 million individuals and 0.4% of the United States census in 2010, Native Hawaiians and other Pacific Islanders  showed the second fastest rate of growth at 40% between 2000 and 2010. Compared to European- or Asian-Americans, Native Hawaiians display alarming rates of obesity, diabetes, cardiovascular diseases, cancers, and other related chronic health conditions . Environe) for Native Hawaiians are likely small throughout history since a genetically estimated Ne as recent as 1,000 years ago was reported to be ∼1,000 for Melanesians and Samoans (There is no detailed characterization of the demographic history of Native Hawaiians using genetic data, though there are suggested models for Eastern Polynesians based on archeological findings, ancient and modern DNA studies, and oral history. Because of the shared genetic ancestry with aboriginal people in Island Southeast Asia, it has been hypothesized that Austronesian-speaking people from locations such as Taiwan or the Philippines migrated to the remote reaches of Oceania and Western Polynesia about 2,000–3,000 years ago . These A Samoans . Thus, t Samoans , a moderNative Hawaiians are also recently admixed. The largest wave of migrants occurred following Captain James Cook’s arrival in Hawai‘i in 1778. Immigrants and missionaries from Europe and Americas as well as laborers from China and East Asia arrived throughout the 19th and 20th centuries. African-ancestry individuals began arriving on the island in the 20th century, mostly as part of the military force . Today, Adaptive events likely shaped the genetic architecture of complex traits in Native Hawaiians. The successful settlement of previously uninhabited Hawaiian archipelago likely involved adopting new subsistence strategies and overcoming famines, nutritional deficiencies, and higher tropical load of infections . The encper se, but to understand the link between past adaptation and present-day health. Given the advancement in population genetic methods to detect selection across different time scales (Native Hawaiians, and Polynesian populations at large, are more susceptible to metabolic diseases such as obesity and type 2 diabetes . One cone scales , and thee scales , there iOne deterrent to including Native Hawaiians in genomic studies is the underdevelopment of genomic resources. For other continental populations, these resources have been abundant and publicly available, enabling large-scale collaborations and investigations. Development of these resources in Native Hawaiians or other Polynesian populations will similarly accelerate genetic research in these populations.1. However, Native Hawaiians, or Polynesians in general, are not yet represented in these catalogs. The publicly available sequencing data of Native Hawaiians are limited to data from a single individual in the Simons Genome Diversity Project (One sorely needed resource is a catalog of genetic variation, akin to gnomAD, which contains variation discovered from sequencing data of up to ∼141,000 individuals . This ca Project . [There  Project .] Going  Project .CREBRF is associated with a large effect on BMI and T2D in Native Hawaiians, but could not be imputed or discovered using publicly available imputation resources at the time, despite the study having sufficient statistical power to do so (To accelerate the discovery of genetic associations to diseases, we also need to improve Native Hawaiian representation in imputation reference panels. Genome-wide genotyping followed by imputation of the unobserved genetic variation is one of the most efficient approaches to conduct genetic association studies. Publicly available imputation reference panels are constantly growing in size, allowing investigators to query rarer variations that are usually absent on genotyping arrays. Because of the lack of representation in imputation reference panels, the quality of imputation in Native Hawaiians lags significantly behind that of other ethnic minorities . In a prto do so . The lacpartner with indigenous communities rather than just enrolling them as participants (Ultimately, larger cohorts will boost statistical power and undoubtedly enhance the genomic insights we can garner, but large recruitments in indigenous communities such as the Native Hawaiians have been challenging. The population sizes of any indigenous population are already small, and past mistakes by researchers, such as the Havasupai diabetes study that misused genetic information from the indigenous community in unconsented studies , have alicipants .Population genetic theories predict the existence of unique genetic variants segregating in the Native Hawaiian population that disproportionately impact their health. Identifying these variants could significantly improve healthcare practices and directly benefit this community. Though several challenges currently exist, the outlook for genetic research in Native Hawaiians and other diverse populations in general can be promising while requiring only a moderate level of funding commitments. Whole genome sequencing of only 150–200 Native Hawaiian individuals would already allow better imputation of Native Hawaiian individuals in a genetic study and accelerate the discovery of population-specific alleles of large effects . The genHowever, it is important to develop the partnership of the indigenous community in order for the research to proceed. Past exploitation of indigenous populations  and the Working within the framework of the Multiethnic Cohort  study, eThis is but the first step of active community engagement. A step toward the right direction, but the efforts need to be broadened and made consistent. The Aotearoa New Zealand genomic variome project  is an exphs000220.v2.p2.Datasets analyzed in this can be found here in dbGAP with accession number The studies involving human participants were reviewed and approved by the Institutional Review Boards of the University of Hawai‘i and the University of Southern California. The patients/participants provided their written informed consent to participate in this study.CWKC conceived and designed the study, performed the analysis, and wrote the manuscript.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The findings show weak positive associations between age and increased vividness of voluntary auditory imagery and decreased involuntary musical imagery frequency, weak associations between being female and more vivid visual imagery, and relations of greater music and video game experience with higher involuntary musical imagery frequency. Moreover, all imagery stimulus modalities were associated with each other, for both intentionality levels, except involuntary musical imagery frequency, which was only related to higher voluntary auditory imagery vividness. These results replicate previous research but also contribute new insights, showing that individual differences in age, sex, and background experience are associated with various aspects of imagery such as modality, intentionality, vividness, and frequency. The study’s findings can inform the growing domain of applications of mental imagery to clinical and pedagogical settings.Mental imagery is a highly common component of everyday cognitive functioning. While substantial progress is being made in clarifying this fundamental human function, much is still unclear or unknown. A more comprehensive account of mental imagery aspects would be gained by examining individual differences in age, sex, and background experience in an activity and their association with imagery in different modalities and intentionality levels. The current online study combined multiple imagery self-report measures in a sample (The online version contains supplementary material available at 10.3758/s13421-021-01209-7. Mental imagery supports several aspects of healthy as well as pathological cognition and has received considerable interest in cognitive psychology research. Different kinds of imagery relate to a range of processes such as memory recall and future thinking  or involuntary imagery  are part of the processes that deteriorate with age, such as working memory, or of processes that generally do not decline, such as vocabulary or world knowledge  it is primarily investigated as a binary factor, for example, comparison of athletes versus non-athletes or musicians versus non-musicians; (b) the criteria used to define comparison groups vary greatly between studies ; and (c) the studies do not take into consideration individuals who might not be professionals or students but engage with the activity informally as part of a hobby. Our study took a novel approach and explored a sample with a wide age-range and used a background experience index that reflected the frequency, duration, and recency of engagement in various activities such as sports, music, and video games. Using this approach, we aimed to investigate how certain demographics and general background experience in an activity are linked to imagery aspects.Research on imagery to date is typically confined to a single stimulus modality , mostly the visual, and a single intentionality level, usually the voluntary. However, imagery can be conceptualized as unimodal or multimodal, when it includes, respectively, single or multiple stimulus modalities concurrently or in succession . Multimodal imagery is often identified as most useful in practical settings such as pedagogy , and was representative of the Dutch population in terms of age and sex.Participants were recruited via social media, recruitment websites, personal networks, and posters at various public spaces  in the Netherlands. A total of 690 individuals commenced participation in the online survey and of these 296The larger study received ethical approval from the Psychology Research Ethics Committee of Leiden University, the Netherlands (application number CEP 16-0226/99). All participants provided informed consent online via checkboxes on the first page of the survey before commencement of the study.We administered the following battery of self-report imagery questionnaires in the Dutch language to 5 . The instructions ask participants to imagine the scenes with their eyes closed. In the first validation study .The Vividness of Visual Imagery Questionnaire , which measure a general factor, and uses a 5-point rating scale . In the validation study of the Dutch version , which was adopted for the current study as well.The Spontaneous Use of Imagery Scale  and Control (BAIS-C). Each subscale has 14 items,”) on a 7-point scale . The original validation study . In the current study we only included the Vividness subscale in the analysis, given the focus of the other utilized measures.The Bucknell Auditory Imagery Scale . In addition, three items independent of the scale but commonly used alongside it measure other characteristics of involuntary musical imagery such as frequency of retrieval (1 = Never to 6 = Almost continuously), duration of the section  of the piece of music retrieved (1 = Less than 5 seconds to 5 = More than 1 minute), and duration of the episode . Only involuntary musical imagery frequency was used for the purposes of our study.The Involuntary Musical Imagery Scale ; (2) first-person visual imagery perspective, as if the individual is looking out through their own eyes while performing the movement ; and (3) the feeling of carrying out the movement . VMIQ-2 has 12 items and their response ratings are on a 5-point scale . The instructions ask participants to imagine and rate the vividness of items first in VMIQ-EVI, then VMIQ-IVI, and finally VMIQ-KVI. In the original validation study .The Vividness of Movement Imagery Questionnaire ; (2) duration (in months and years) of engaging in the activity at least once a week (open-ended); (3) recency (in months and years) of engaging in the activity at least once a week (open-ended).Background experience in sports , music (playing an instrument/singing), and video games (video games of any kind) was measured with three items for each activity: (1) frequency of engaging in the activity during the last year . First, participants read the information about the study and provided their consent to participate. The presentation of the consent form and demographic questions was in a fixed order, whilst the presentation of the imagery questionnaires was randomized. At the end, participants were debriefed about the purposes of the studies. The median total completion duration of the survey was 33 min (including the measures taken for the larger study mentioned above).The overall survey was implemented online in Qualtrics , and recency . In the Online Supplementary Material Tables , 2 and 3r metric, effect sizes of .10, .30, and .50 were considered small, medium, and large, respectively . We ran Spearman correlations to investigate associations of age, sex, and background experience with imagery aspects such as vividness and frequency, as the data were not normally distributed. We corrected for multiple testing using the Holm-Sidak method  = .14, p = .017) and with decreased frequency of involuntary musical imagery (IMIS (frequency), r(279) = -.12, p = .042). Age was not associated with any of the measures related to voluntary and involuntary visual imagery  = .11, p = .058; SUIS, r(279) = .04, p = .507) or voluntary motor imagery  = .02, p = .726, VMIQ-IVI, r(279) = -.09, p = .12, VMIQ-KVI, r(279) = .02, p = .668).To explore our first research question, concerning the relation of imagery aspects with individual differences, we examined the associations between age, sex, and background experience in sports, music, and video games with all imagery measures Table . Increasr(279) = .15, p = .010; SUIS, r(279) = .20, p = .001), indicating that females reported experiencing more vivid voluntary and more frequent involuntary visual imagery. We found no relations between sex and vividness of voluntary auditory and motor imagery nor frequency of involuntary musical imagery  = -.03, p = .568; VMIQ-EVI, r(279) = -.016, p = .795; VMIQ-IVI, r(279) = -.06, p = .355; VMIQ-KVI, r(279) = .04, p = .486; IMIS (frequency), r(279) = -.03, p = .599).We observed weak correlations between sex and voluntary as well as involuntary visual imagery  = .30, p < .001 and r(104) = .25, p = .010, respectively). We did not observe any further relations.The background experience indices regarding music and video games were moderately and weakly associated with increased frequency of involuntary musical imagery (IMIS (frequency), In Tables r(130) = .15, p = .090), and age and frequency of involuntary musical imagery (IMIS (frequency), r(130) = -.13, p = .150), remained approximately unchanged, indicating that musical experience does not explain the relations between age and vividness of voluntary auditory imagery nor frequency of involuntary musical imagery. Next, we explored whether the background experience in video games could partially account for the relation of sex with vividness of visual imagery. The magnitude of the correlations remained approximately unchanged, indicating that background experience did not account for the relation of sex with vividness of voluntary  = .17, p = .089) nor frequency of involuntary visual imagery  = .22, p = .023).To follow up our first research question we explored whether background experience in an activity could explain the relations of age and sex with imagery aspects. First, we calculated partial correlations between age and vividness of voluntary auditory imagery (BAIS-V), as well as frequency of involuntary musical imagery (IMIS frequency), while controlling for musical experience (Background Experience Index). When controlling for background experience in music, the magnitude of the correlation between age and vividness of voluntary auditory imagery  = .31, p < .001) and the auditory measures correlated weakly with each other  = .14, p = .021). Concerning stimulus modalities, we observed primarily strong and some moderate correlations between all modalities, that is, visual and auditory imagery (VVIQ and BAIS-V: r(279) = .46, p < .001; SUIS and BAIS-V: r(279) = .32, p < .001), visual and motor imagery (VVIQ and VMIQ-EVI: r(279) = .43, p < .001; VVIQ and VMIQ-IVI: r(279) = .41, p < .001; VVIQ and VMIQ-KVI: r(279) = .48, p < .001; SUIS and VMIQ-EVI: r(279) = .25, p < .001; SUIS and VMIQ-IVI: r(279) = .25, p < .001; SUIS and VMIQ-KVI: r(279) = .20, p = .001) as well as auditory and motor imagery (BAIS-V and VMIQ-EVI: r(279) = .46 , p < .001); BAIS-V and VMIQ-IVI: r(279) = .50 , p < .001); BAIS-V and VMIQ-KVI: r(279) = .46 , p < .001).To explore our second research question, concerning the relations between imagery modalities and intentionality levels, we calculated correlations between all imagery measures Table . First, r(279) = .46, p < .001; VVIQ and VMIQ-EVI: r(279) = .43, p < .001; VVIQ and VMIQ-IVI: r(279) = .41, p < .001; VVIQ and VMIQ-KVI: r(279) = .48, p < .001; BAIS-V and VMIQ-EVI: r(279) = .46 , p < .001; BAIS-V and VMIQ-IVI: r(279) = .50 , p < .001; BAIS-V and VMIQ-KVI: r(279) = .46 , p < .001). The involuntary measures (SUIS and IMIS frequency: r(279) = .10, p = .11) did not correlate with each other. With regard to relations between intentionality measures, we see that involuntary visual imagery (SUIS) correlated weakly to moderately with all voluntary measures  = .31, p < .001; auditory imagery, BAIS-V: r(279) = .46, p < .001; motor imagery, VMIQ-EVI: r(279) = .25, p < .001; VMIQ-IVI: r(279) = .25, p < .001; VMIQ-KVI: r(279) = .20, p < .001), whilst, as reported above, involuntary musical imagery (IMIS frequency) correlated weakly only with voluntary auditory imagery (BAIS-V and IMIS (frequency), r(279) = .14, p = .021).In relation to intentionality, we see that all voluntary measures correlated moderately to strongly with each other  did correlate with each other, as well as with all intentionality levels (voluntary and involuntary) within modalities, except for involuntary musical imagery frequency, which only correlated with vividness of voluntary auditory imagery. These findings replicate previous results but also bring some novel key information. Below we synthesize the findings in relation to the existing literature and discuss their implications for future research.n = 279) and the Lima et al. (n = 74), with the latter being too small to detect weaker effects of individual differences. Other possible explanations could relate to differences in other demographic factors between the studies such as age range, education level, and culture, which future studies should investigate. Our findings should also be interpreted with caution, as the size of the correlation is small and of course it does not imply causality. Interestingly, age was not associated with vividness of visual imagery. As previous research has reported age-related reductions in other visual imagery aspects such as manipulation  and auditory musical (IMIS frequency) imagery assess different aspects of intentionality , while voluntary measures focus on the same aspect . Future studies should consider and develop robust methods to measure the time course as well as co-occurrence and/or switch between stimulus modalities and intentionality levels. Some imagery occurrences are purely unimodal, or associated with one intentionality level, and others might be multimodal or move on a continuum of intentionality, starting involuntarily and continuing voluntarily or vice versa , and suggest that background experience may in these cases also not give cause to expect large differences in imagery aspects.ESM 1(DOCX 96 kb)