Puccinia graminis, and the prevalence of alternate  host, Berberis species, have regained attention as the sexual host may serve as source of novel pathogen variability that may pose a threat to cereal supply. The main objective of the present study was to investigate the functional role of Berberis species in the current epidemiological situation of cereal stem rust in Europe. Surveys in 11 European countries were carried out from 2018 to 2020, where aecial infections from five barberry species were collected. Phylogenetic analysis of 121 single aecial clusters of diverse origin using the elongation factor 1-α gene indicated the presence of different special forms  of P. graminis adapted to different cereal and grass species. Inoculation studies using aecial clusters from Spain, United Kingdom, and Switzerland resulted in 533 stem rust isolates sampled from wheat, barley, rye, and oat, which confirmed the presence of multiple special forms of P. graminis. Microsatellite marker analysis of a subset of 192 sexually-derived isolates recovered on wheat, barley and rye from the three populations confirmed the generation of novel genetic diversity revealed by the detection of 135 multilocus genotypes. Discriminant analysis of principal components resulted in four genetic clusters, which grouped at both local and country level. Here, we demonstrated that a variety of Berberis species may serve as functional alternate hosts for cereal stem rust fungi and highlights the increased risks that the sexual cycle may pose to cereal production in Europe, which calls for new initiatives within rust surveillance, epidemiological research and resistance breeding.The increased emergence of cereal stem rust in southern and western Europe, caused by the pathogen  Puccinia graminis, is a major threat to cereal production globally  that is the most widely distributed barberry species in Europe. The incidence of common barberry in Europe has significantly increased due to the repeal of eradication campaigns and legislation banning the planting of barberry plants near cereal crops and its re-introduction promoted by natural conservationists  adapted to certain cereal hosts, such as P. graminis f.sp. tritici infecting wheat (Pgt), P. graminis f.sp. secalis infecting rye (Pgs) and P. graminis f.sp. avenae infecting oat (Pga)  . Berberienatheri . Howeverderstood . Since toduction . Additiooduction . DNA seqass host . Howevern Europe .Berberis species in the epidemiology of cereal rust fungi by identifying the rust genera and/or species that infect the alternate host across Europe. Additionally, we evaluated which rust species may infect major cereal crops after sexual reproduction on Berberis spp., and investigated the genetic diversity generated on the cereal host. This fundamental knowledge on the role of the alternate host in cereal rust epidemiology will be crucial as sexual reproduction potentially increase genetic variability in cereal rust populations, and thereby increase the risks of break-down of rust resistance in crop varieties.The increased emergence of stem rust coupled with renewed prevalence of the alternate host in cereal growing areas in Europe have recently drawn the attention due to the detrimental role that the alternate host may pose to cereal supply. The main objective of the present study was to investigate the potential role of B. vulgaris, B. aetnensis, B. vulgaris subsp. seroi, B. vulgaris subsp. australis, and B. x ottawensis (an interspecific hybrid of B. vulgaris and B. thunbergii) were collected in 11 European countries . Samples were pulverized in a 2010 Geno/Grinder (SPEX samplePrep), at 1,500 strokes per minute for 3 s × 20 s. Samples were extracted with the sbeadx plant kit (LGC genomics) using a KingFisher Magnetic Particle Processor for 24 samples (Thermo Scientific). DNA was extracted according to manufacturer’s instructions using 300 µl lysis buffer and 50 µl of the lysate for extraction. DNA was eluted in 50 µl elution buffer.P. graminis  and 1 µl of undiluted DNA. PCR conditions were 95°C for 3 min and 10 cycles at 95°C for 30 s, annealing at 60°C for 30 s, and 72°C for 2 min with 0.5°C decrease in annealing temperature per cycle followed by 30 cycles of 95°C for 30 s, annealing at 55°C for 30 s, and 72°C for 2 min and a final extension at 72°C for 2 min. PCR products were analyzed in an agarose gel electrophoresis assay and those which were successfully amplified were purified and bidirectionally sequenced with the same primers as for the PCR analysis using Sanger sequencing at Macrogen Europe BV, Amsterdam, Holland.The PCR amplifications and sequencing of the elongation factor gene (EF1-α) region were conducted using the primers EFbasidR  and EF1-graminis . The PCRhttps://digitalinsights.qiagen.com) and apparent misalignments manually examined. After trimming, all sequences were aligned and a consensus sequence generated for each aecial sample. The Basic Local Alignment Search Tool (BLASTN) were used to find similarities between sequences in GenBank, NCBI , rye , barley (Hordeum vulgaris var. Hiproly), and oat (Avena sativa var. Marvellous). for samples collected in Spain and United Kingdom, and var. Line E, Cartago, and Palazzo for samples collected in Switzerland, respectively. All varieties are considered as “universal” susceptible varieties of P. graminis ff.spp. including Pgt , Pgs , and Pga (var. Marvelous)  . Additio tritici .®, MH 180, Crompton Registrations Ltd., Birmingham, England) was added to slow plant growth and enhance spore production. Two pots of each cereal variety were randomized and placed below barberry leaves bearing aecia, which were fixed to a plastic stand, misted with water and incubated at 15°C for 24 h in darkness, 100% relative humidity (RH). Subsequently, seedlings were transferred to spore-proof greenhouse cabins and kept at 18°C day/14°C night with a photoperiod of 16 h of natural light and supplementary artificial light (200 μmol·s−1 m−2), RH 80%. Uredinia resembling the stem rust fungus were observed from 10 days after aeciospore exposure on all cereal varieties. When clearly separated pustules developed, leaf segments of approximately 1–3 cm were detached and rinsed with water to remove possible spores from additional lesions. Leaf segments bearing uredinia were then dried for 2 days in a desiccator at room temperature and stored until further use.Twenty seeds of each variety were grown in square plastic pots and when the seedlings were approximately 2–4 cm, 3 ml of maleic hydrazine solution  was used for genetic analyses of sexually-derived uredinial isolates from three populations, i.e., Spain, United Kingdom and Switzerland, and cereal hosts, i.e., wheat, barley, and rye (5) (exp) (st), measuring pairwise divergence between populations, the number of effective migrants {Nm = [(1/Fst)-1]/4} and Nei’s genetic distance were assessed using GenAlEx 6.503 with 9,999 permutations and bootstraps (ρ) were calculated to measure the linear correlation between Fst, Nm, and Nei’s genetic distance values.The “ and rye . Populat and rye , evennes rye (5) , and Nei5) (exp) . Analyse5) (exp) . The fixotstraps . Pearsonadegenet” package version 2.1.5 implemented in the R environment . This is normally associated with the lowest Bayesian Information Criterion (BIC) K value, which is frequently indicated by an elbow in the BIC curve  with 1,000 replicates was implemented to find the optimal number of PCs to be retained, which was associated with the lowest root mean square error. Subsequently, a scatterplot with the first and second linear discriminants and the resultant clusters was generated. Finally, membership probabilities of isolates associated to a specific MLG and to a resultant cluster were calculated.The population structure of related sexually-derived uredinial isolates was analysed by Discriminant Analysis of Principal Components (DAPCs) using the “ironment . The DAPironment . The finIC curve . As the P. graminis reference samples from NCBI collected from three different hosts, i.e., T. aestivum, Dactylis glomerata, and Lolium rigidum  to  rigidum . For bett clades . Clade Ioutgroup .Pgt, Pgs, and Pga  . The higTo infer in the genetic structure of the three populations, a DAPC analysis was conducted using the 135 MLGs detected in this study. The DAPC analysis revealed four genetic clusters based on 20 PCs retained and three discriminant eigenvalues . The optst values, Nei’s genetic distances and number of effective migrants (Nm) are shown in st and Nei’s genetic distance and higher values of Nm were observed for United Kingdom vs. Switzerland, suggesting a low genetic differentiation between these two populations. The correlation coefficient between the Fst and the Nei’s genetic distance values for the genetic clusters detected by DAPC analyses and the original populations from Spain, United Kingdom, and Switzerland ranged from 0.70 to 0.99, respectively, implying a high correlation between these two genetic differentiation parameters. Additionally, the number of effective migrants was inversely correlated to Fst (ρ = −0.94 and ρ = −0.97) and Nei’s genetic distance values .Pairwise comparisons for genetic differentiation between the genetic clusters (CL) detected by the DAPC analysis in addition to the original populations from Spain, United Kingdom, and Switzerland based on FBerberis spp. in the epidemiology of stem rust infecting major cereal crops  and orchard grass (D. glomerata). Clade II comprised P. graminis ff.spp. tritici and secalis infecting wheat and rye, respectively, in addition to E. caninus (aka bearded wheatgrass or bearded wild rye)  . This isild rye) . Certainild rye) . Althoug related . For exa ff.spp. .in vivo experiments using aecial samples resulted in successful stem rust infections in susceptible varieties of wheat, barley, rye, and oat, indicating the presence of multiple ff.spp. of P. graminis infecting Berberis spp. in Europe. Stem rust lesions on wheat and rye indicated the presence of ff.spp. tritici and secalis, respectively. The same may be applied to the stem rust lesions obtained from barley, which could be a result of infections by either Pgt or Pgs or alternatively from crosses between these two ff.spp.  in Spain and from wheat and barley in Sweden in areas where the alternate host is locally present (The application of neutral co-dominant molecular markers have proven very useful to infer in the genetic variability and structure among cereal rust populations e.g., . Here, td barley . Moleculoduction . Indeed, and oat . More re present .st values, Nei’s genetic distance and Nm revealed a moderate to low genetic differentiation and high gene flow between these two populations (P. graminis samples derived from three locally separated locations in Spain. These three subpopulations were characterized by high Fst and Nei’s values, and relatively low number of migrants. This suggested that each of the Spanish subpopulations were formed as a result of fungal infections generated on barberry plants infected with local P. graminis populations with low genetic exchange. A fourth cluster was comprised of isolates derived from United Kingdom and Switzerland. This is consistent with the low genetic differentiation observed between these two populations based on results from AMOVA, Fst, Nei’s genetic distance and Nm values. Indeed, gene flow due to aerial dispersal of fungal spores over long distances is a common phenomenon previously reported for rust fungi (Analysis of molecular variance of the sexual populations from Spain, United Kingdom and Switzerland revealed that the highest molecular variance was observed within and among samples, which is in line with the high genetic diversity observed based on the number of MLGs and diversity parameters. Genetic variation among populations explained 14% of the total variance, which significantly decreased to 2% in a pairwise comparison between sexual populations from United Kingdom and Switzerland. Pairwise comparisons for genetic differentiation between populations from United Kingdom and Switzerland based on Fulations . In contulations , providest fungi . An addiP. graminis will allow to evaluate the current level of stem rust susceptibility and assess which resistance genes are more likely to evolve towards new virulences and hence put at risk the durability of specific resistance genes. This will help to select resistance genes and combinations thereof, which are expected to be more durable, and develop more sustainable disease management and resistance deployment strategies.This study demonstrated that a range of barberry species across multiple sites in Europe were functionally active as sexual host for stem rust infecting cereals. This underlines the need to reinitiate rust resistance breeding strategies to enhance cereal crop defenses in case the sexual host becomes a significant part of the epidemiology of stem rust in Europe. Future screen of cereal germplasm commonly grown in Europe using sexual-derived populations of


Canis rufus) is a critically endangered wolf endemic to the eastern United States, where all extant red wolves are descended from 14 founders which has led to elevated levels of inbreeding over time. Red wolves were considered extirpated from the wild by 1980, but before they disappeared, they interbred with encroaching coyotes creating a genetically admixed population of canids along coastal Texas and Louisiana. In 2018, a genetic study identified individuals on Galveston Island, Texas with significant amounts of red wolf ancestry. We collected 203 fecal samples from Galveston for a more in-depth analysis of this population to identify the amount of red wolf ancestry present and potential mechanisms that support retention of red wolf ancestry on the landscape.Hybridization can be a conservation concern if genomic introgression leads to the loss of an endangered species’ unique genome, or when hybrid offspring are sterile or less fit than their parental species. Yet hybridization can also be an adaptive management tool if rare populations are inbred and have reduced genetic variation, and there is the opportunity to enhance genetic variation through hybridization. The red wolf (We identified 24 individual coyotes from Galveston Island and 8 from mainland Texas with greater than 10% red wolf ancestry. Two of those individuals from mainland Texas had greater than 50% red wolf ancestry estimates. Additionally, this population had 5 private alleles that were absent in the North American reference canid populations used in this study, which included 107 southeastern coyotes, 19 captive red wolves, and 38 gray wolves, possibly representing lost red wolf genetic variation. We also identified several individuals on Galveston Island and the mainland of Texas that retained a unique red wolf mitochondrial haplotype present in the red wolf founding population. On Galveston Island, we identified a minimum of four family groups and found coyotes on the island to be highly related, but not genetically depauperate. We did not find clear associations between red wolf ancestry estimates and landscape features, such as open green space or developed areas.Our results confirm the presence of substantial red wolf ancestry persisting on Galveston Island and adjacent mainland Texas. This population has the potential to benefit future red wolf conservation efforts through novel reproductive techniques and possibly through de-introgression strategies, with the goals of recovering extinct red wolf genetic variation and reducing inbreeding within the species.The online version contains supplementary material available at 10.1186/s12862-022-02084-9. Anas platyrhynchos) has led to population declines of the New Zealand gray duck (Anas superciliosa) [Anas wyvilliana) [Hybridization and the resulting admixture, the movement of alleles from one species into another, occurs naturally in many organisms and is thought to be an important evolutionary process –6. This ciliosa)  and the illiana) , 14.Puma concolor) to Florida assisted in the recovery of the Florida panther (Puma concolor coryi) that was experiencing reduced fitness due to fixed deleterious traits from decades of low population size [Chelonoidis elephantopus) were detected within admixed individuals of the Wolf Volcano Giant-Tortoise (Chelonoidis becki) [Alternatively, hybridization can be a source of genetic rescue to restore fitness in critically endangered populations or species when crossed with populations or subspecies with a more diverse gene pool , 16. Forion size –20. Todaion size . Genome ion size , 22, 23.s becki) , and theWhether hybridization is a conservation concern, or an adaptive management tool depends on a variety of factors, such as the size of an endangered population, the current genetic variation present, and importantly the strengths and weaknesses of reproductive barriers operating in a system . For effCanis latrans) on Galveston Island, Texas, an island where coyotes with red wolf (Canis rufus) ancestry were recently discovered, despite red wolves being declared extinct from the region since 1980 [We investigate ancestry and population structure of admixed coyotes  estimate red wolf ancestry within the population of Galveston Island coyotes, (2) evaluate baseline genetic variation of Galveston Island coyotes and compare it to adjacent mainland Texas coyotes to measure restricted gene flow and inbreeding, (3) estimate relatedness and genetic structure of coyotes on Galveston Island, and (4) describe the distribution of red wolf ancestry within different habitat features. We conducted a systematic noninvasive fecal survey across Galveston Island paired with tissue collection from roadkill, as well as opportunistic sampling from National Wildlife Refuges on mainland Texas from August 2019 to February 2021. This study provides a crucial step in understanding how endangered red wolf ancestry is distributed on the landscape and the mechanisms that reinforce the persistence of red wolf alleles.We collected a total of 229 fecal samples and 32 tissue samples from southeastern Texas. A total of 168 fecal samples were collected systematically along 25 transects across Galveston Island, Texas, an additional 61 fecal samples were collected opportunistically during a pilot study on Galveston Island in August 2019 and on mainland Texas throughout the duration of the study. Twenty-one of the tissue samples were collected from Galveston Island and 11 tissues were collected from mainland Texas throughout the study  from the cytochrome B control region to confirm the matrilineal species assignment of each sample. We successfully obtained mtDNA haplotypes at the cytochrome B control region for 94 fecal samples, for a 42% success rate of mtDNA amplification, and for all 32 tissue samples. Based on species identification from mtDNA haplotypes, we removed 9 samples that were not wild canids: 8 domestic dogs and 1 otter. We identified four mitochondrial haplotypes on Galveston Island that matched haplotypes previously published on NCBI GenBank  , one sa80913; , SIBS for five loci was 0.0081, thus any combination of five loci would ensure our ability to distinguish between individuals and still be below the PIDSIBS threshold of 0.01 (1 out of 100 siblings are predicted to have matching genotypes). We performed a matching analysis in GenAlEx and identified a total of 51 individuals from Galveston Island and 17 individuals from mainland Texas. One sample from Galveston Island was later revealed to be a domestic dog and was removed from further analyses, leaving 50 individuals from Galveston Island . Coyotes from mainland Texas had on average 21% (standard deviation 0.197) red wolf ancestry (range = 2.0–55.8%)  Fig. .Fig. 4PiWe used a principal components analysis (PCA) and found that clusters were consistent with taxonomic classifications and previous analyses , 41. GalCanis samples. We found the lowest level of genetic differentiation between southeastern reference coyotes and Galveston Island coyotes (FST = 0.075), followed by Texas mainland samples and reference coyotes (FST = 0.093)  Table .Table 1EO = 0.729) and mainland Texas (HO = 0.722) samples also had similar heterozygosity estimates to our reference coyote groups (0.725). We found that Galveston Island and mainland samples had five private alleles compared to reference groups. Galveston Island coyotes showed no loss of heterozygosity or increased inbreeding coefficients (FIS = 0.0151) compared to other groups . We found that the family groups of East End Lagoon Nature Preserve and the Galveston Island State Park both overlapped with undeveloped habitat, while the groups from Scholes International Airport and the middle of the island overlapped with developed habitat. We found that undeveloped habitat types were correlated with significantly higher red wolf ancestry proportions than developed habitat . However, when we grouped all individuals into three category types , there was no difference in mean red wolf ancestry between habitat types when accounting for family groups .We evaluated the ancestry, genetic variation, and genetic structure of the coyote population on Galveston Island, Texas where red wolf ancestry was previously detected in two roadkill individuals . We deteWe further detected the presence of the species-specific red wolf mtDNA haplotype both on and off Galveston Island. This haplotype has only been detected in the wild, outside of the North Carolina red wolf population, by Murphy and colleagues 2019) in southwestern Louisiana, a location that was part of the last remaining stronghold of wild red wolves , 45. Gal019 in soThe main mechanism promoting the persistence of red wolf ancestry is not likely isolation due to water between the mainland and the island given the significant amount of red wolf ancestry found on mainland Texas and high genetic diversity of Galveston Island canids. Other mechanisms such as prey selection, territorial aggression, or body size assortative mating like seen in North Carolina , 46 may One limitation of this work is we may be underestimating red wolf ancestry in these samples. Our reference red wolf population represent 13 of the 14 genetic founders of the captive breeding population, three offspring of the fourteenth genetic founder, and three additional animals who were selected for the captive breeding population but never reproduced. Although this represents all the genetic diversity remaining in the extant red wolf population, this is a vast underrepresentation of the red wolf genetic diversity prior to the population bottleneck it underwent in the twentieth century. For instance, in the mid-1900s, red wolf/coyote hybrids were documented using morphometrics in Texas , 48, LouWe found two main mtDNA maternal lineages on Galveston Island. Interestingly, these haplotypes were divided spatially with one lineage in the west side of the island and one in the east side. From these, we identified four main family groups, while some individuals did not assign to any group. These individuals could be migrants or we may have missed family groups due to sampling biases. For instance, there was a 7 km distance on the west side of the island where we could only sample along the main road and the public beach because the rest was private land we could not access. Areas such as this created gaps in our sampling where we could be missing additional family groups. Additionally, two mtDNA haplotypes from fecal samples on the west side of Galveston Island matched the red wolf haplotype, but we were not able to generate genotypes; we could be missing an important family group with high amounts of red wolf ancestry in this area. From the groups we did identify, the ones with the largest percentage of red wolf ancestry were found in The East End Lagoon Nature Preserve and the Galveston Island State Park Fig. . These aCanis lupus lycaon) has resulted in selection for larger body size and skeletal proportions [This research is the first to evaluate Galveston Island coyotes as an entire population, where we are beginning to identify population genetic structure, family groups, and starting to evaluate how habitat may play a role in maintaining high amounts of red wolf ancestry in Texas coyotes. Yet, much more needs to be understood to determine the mechanisms maintaining red wolf ancestry in coyotes, such as whether there is a selective benefit of red wolf/coyote hybridization. Hybridization may have provided an adaptive advantage to expanding coyotes by introducing genetic material already filtered by natural selection in southeastern environments . This prportions , 55. If portions –58. We hWe evaluated a population of coyotes with red wolf ancestry along the Gulf Coast of Texas. The study of these admixed coyotes has important implications for red wolves, which are critically endangered and may soon be in need of conservation action. First, admixed populations can act as reservoirs of historic or lost genetic variation , 54, 59,2 wildlife refuge that is a mix of salt marsh, coastal prairies, and bottomland hardwood forests [2 [Our study was located south of Houston, Texas on and around Galveston Island, San Bernard Wildlife Refuge, and Anahuac National Wildlife Refuge. This region is humid and subtropical, where hurricanes are common during the summer and fall seasons . Galvest forests . The Anarests [2 .We systematically sampled Galveston Island for feces for noninvasive genetic sampling. We collected fecal samples and recorded their GPS location along 25 designated transects distributed east to west , in a laboratory dedicated to low-quality DNA at MTU. We extracted DNA from tissue samples using a DNeasy Blood and Tissue Kit  following the manufacturers protocol in a laboratory dedicated to high-quality DNA samples. We amplified a portion of the cytochrome B region of the mitochondrial genome via polymerase chain reaction (PCR) to confirm DNA isolated from fecal samples was collected from wild coyotes and to gather information on matrilineages, which is useful in differentiating red wolves and coyotes . Extant 2 and 0.5 µL Amplitaq Gold (Applied Biosystems) in a 15 µL reaction with 1.5 µL of DNA extract. We used an Eppendorf Mastercycler Gradient Thermal Cycler  using an initial denaturation step of 95 °C for 10 min, 40 cycles  and a final extension for 7 min at 72 °C. For high quality DNA extracted from tissue we targeted a ~ 420 base-pair fragment using primers Thr-L: 15,926 5ʹ-CAATTCCCCGGTC TTGTAAACC-3ʹ and DL-H 16,340: 5ʹ-CCTGAAGTAGGAA CCAGATG-3ʹ [2 and 0.5 µL Amplitaq Gold (Applied Biosystems) in a 10 µL reaction with 1 µL of DNA extract. The Eppendorf Mastercycler Gradient Thermal Cycler conditions were an initial 10-min denaturation at 95 °C, 40 cycles  and a final extension for 7 min at 72 °C. Each PCR was run with a negative control from DNA extractions to monitor for contamination. We visualized each PCR product on a 2% agarose gel run at 115 V for one hour. Samples that contained nonspecific amplification were reamplified with an annealing temperature of 58 °C. We enzymatically cleaned samples using the product ExoSapIT [For low quality DNA extracted from fecal samples, we targeted a ~ 200 base-pair fragment using primers ScatSeqF: 5ʹ-CCATGCATATAAGCATGTACAT-3ʹ and ScatSeqR 5ʹ-AGATGCCAGGTATAGTTCCA-3ʹ . The PCRAGATG-3ʹ . The PCRExoSapIT  on an EpExoSapIT .We compared our generated sequences to all previously published sequences in the NCBI BLAST database using Geneious. The samples confirmed to be from the target sequence were aligned using a pairwise MUSCLE alignment in Geneious using 8 iterations. The shorter sequences that were amplified using the Scatseq primers were matched to a longer sequence from the Thr-L 15,926 and DL-H 16,340 primers for haplotype identification. We used a Muscle alignment in Geneious to compare our mtDNA haplotypes to all extant North American canid haplotypes from NCBI GenBank.SIBS) using nine loci in Multiplex 1 with GenAlEx v6.5 [We genotyped nuclear DNA (nDNA) at 17 microsatellites at the Laboratory for Ecological, Evolutionary, and Conservation Genetics  to identify individuals from fecal samples, estimate ancestry, and estimate relatedness. This multi-locus microsatellite panel has been used extensively in the past for identifying red wolf X coyote hybrids –39, 66. lEx v6.5  and perfOur first objective was to estimate red wolf ancestry proportions in each coyote by assessing the mitochondrial lineage and determining the distribution of red wolf ancestry in nDNA across the island and adjacent mainland Texas. To accomplish this, we estimated gene trees with mtDNA haplotypes using Bayesian methods implemented in BEAST v.1.10.4 , with a Canis references. References included Mexican wolves (n = 14), domestic dogs (n = 38), gray wolves (n = 38), red wolves (n = 19) representing 13 of the 14 genetic founders plus descendants of the fourteenth founder of the captive breeding population, and southeastern coyotes  a priori to five  and ran 10 independent runs of the admixture model with correlated allele frequencies with a burn-in of 20,000 Markov chain Monte Carlo iterations followed by 50,000 iterations to estimate a posterior probability of ancestry , to test for differences in mean red wolf ancestry proportions between developed and undeveloped natural areas of Galveston Island. We used The National Oceanic and Atmospheric Administration (NOAA) geospatial classification system with a 30-m resolution . We ran Additional file 1. Microsatellite genotypes, ancestry statistics, and identification of private alleles.Additional file 2: Fig S1. Mitochondrial DNA haplotype gene tree of the cytochrome B region of the mitochondrial control region. Accession numbers are from NCBI GenBank; accession numbers that match sequences from this study are labeled with their detection location. Species code Vv represents the outgroup red fox (Vulpes vulpes), Clu is gray wolf (Canis lupus), Cll is eastern wolf (Canis lupus lycaon), Cla is coyote (Canis latrans), and Cru red is red wolf (Canis rufus). Fig S2. Systematic sample design on Galveston Island, Texas. We noninvasively collected scat samples across 25 transects during three field seasons. Fig S3. Probability of Identity for locus combinations. Fig S4. Distribution by state of the coyote reference samples used in this study. Fig S5. STRUCTURE output including every reference samples. Fig S6. PCA with all reference samples. Table S1. STRUCTURE q percentage and credible interval of all samples using 15 microsatellites.


In multivariable models, having higher worry about genetic risks, higher genetic knowledge, and higher perceived importance of genetic information were associated with higher interest across multiple models. Predictors of interest were generally similar by ethnicity. Our findings show substantial interest in both cancer predisposition testing and carrier screening among young women as part of routine healthcare with similar interest between Latina and non-Latina women. Efforts to broadly offer such testing could be important in improving access to genetic information. It will be critical to develop tools to help healthcare providers communicate about genetic testing and to address the needs of those who have less prior knowledge about genetics to support informed decision making.Sequencing technologies can inform individuals’ risks for multiple conditions, supporting population-level screening approaches. Prior research examining interest in genetic testing has not generally examined the context of population-based approaches offered in routine healthcare or among ethnically diverse populations. Cancer predisposition testing and carrier screening could be offered broadly to women of reproductive age. This study therefore examined interest in these tests when offered as part of routine care, and predictors of interest, among an ethnically diverse sample of women aged 20–35. We conducted an online English-language survey of 450 women; 39% identified as Latina. We examined predictors of interest for two outcomes, interest in testing in the next year and level of interest, in multivariable logistic regression models and stratified analyses by Latina ethnicity. More than half of respondents reported being interested in cancer predisposition testing (55%) and carrier screening (56%) in the next year; this did not differ by ethnicity. About 26% reported being very interested in cancer predisposition testing and 27% in carrier screening. Latina respondents (32%) were more likely to be very interested in cancer predisposition testing than non-Latina respondents (22%;  DNA-based population screening of unaffected individuals has been identified as an important future approach to inform individual disease risks and direct screening and prevention efforts . CurrentA number of recent commentaries have outlined key questions that need to be addressed prior to launching population screening efforts . AlthougIn considering potential future population screening initiatives, pre-pregnancy may offer a unique opportunity to engage women and their reproductive partners in genetic testing. Pre-pregnancy has been identified as a key window for health promotion activities . While dWhile carrier screening is ideally offered prior to pregnancy, it is often not offered until a pregnancy when results could increase anxiety to a greater extent due to the high likelihood of carrier status for one or more conditions and time for partner results . In consThis wide range of interest and uptake observed in different studies with different populations heightens the importance of examining factors affecting interest if expanded carrier screening were offered pre-pregnancy to a broad population. A few studies have examined women’s reasons for choosing to have or declining pre-pregnancy carrier screening. In one survey of the general Dutch population, the primary motivation for receiving expanded carrier screening was to spare a child from a life with a severe hereditary disorder, while lack of a hereditary disorder in the family was identified as a reason to decline screening . AnotherUse of sequencing technologies for expanded carrier screening could allow for informing risks for other health conditions among those receiving genetic testing . RoutinePrior related research conducted outside of the pre-pregnancy and carrier status context has shown that patients are often interested in receiving multiple types of genetic information from genome sequencing, including cancer risk information . Many ofOur prior work has examined possible predictors of interest in various types of findings from genome sequencing informed by a model of risk information and processing , examiniIssues of equity must be considered when assessing interest in population screening, as well as predictors of interest, so that these technologies do not further exacerbate health disparities . There hPrior related research has indicated that a broad population sample may be interested in receiving genetic testing for multiple health conditions, including cancer predisposition testing and carrier status, with at least some support for expanded cancer screening offered pre-pregnancy. However, these studies have not generally been conducted in a clinical setting and little is known about individuals’ interest in genetic testing offered as part of routine healthcare. In addition, research examining predictors of interest in different types of genetic testing among racially and ethnically diverse populations is limited. To address these identified research gaps, this study examined interest, and predictors of interest, in population-based carrier screening and cancer predisposition testing offered as part of routine gynecologic care among an ethnically diverse sample of women aged 20–35.n = 41) or age (n = 34) criteria in the pre-screener questions, did not complete the consent acceptance question at the beginning of the survey (n = 51), or were below the 6-min speed threshold pre-set for time to complete the survey (n = 52). This resulted in a final sample of 450 respondents. The survey was approved as an exempt protocol by the University of Utah Institutional Review Board.We conducted an online English-language survey in order to investigate these research questions see . A conveWe began the survey with an educational component that described different types of genetic testing and then asked participants a series of questions about their interest in the different types. Because of our prior work showing that predictors of interest may vary depending upon item wording , we asseSelection of hypothesized predictors was informed by a conceptual framework based on the model of Risk Information and Processing and Uncertainty Management Theory .α of 0.83), which was treated continuously in analysis.We assessed genetic worry with three items  . Responsα of 0.76) and modeled as a continuous variable in analysis.We assessed genetic self-efficacy  using a three-item measure on which participants indicated the extent to which they agreed with each item on a five-point Likert-type scale from strongly disagree to strongly agree  . Scores To assess general knowledge about genetics, we utilized an 18-item  genes can cause disease”) measure . Each itα of 0.69) as very important vs. other categories for analysis.We used two items to assess the perceived importance of genetic information, one focused on cancer predisposition testing  and one on carrier screening, adapted from our prior work . Both itα of 0.83) and treated continuously in analysis. Higher scores indicated a stronger health consciousness.Participants’ degree of health consciousness was assessed with five items , which were answered on a five-point Likert-type scale from “strongly disagree” to “strongly agree” . The resα of 0.86) and treated continuously in analysis. Higher scores indicated a stronger health information orientation.The importance placed on health information was assessed with eight items , which were answered on a five-point Likert-type scale from “strongly disagree” to “strongly agree” . The resOne item was used to assessed health information seeking , which respondents answered on a four-point Likert-type scale from “Not at all” to “Very often” . ResponsWe assessed relative risk perceptions for breast, ovarian, and colon cancer with three items ” which was answered on a five-point scale from “a lot less likely” to “a lot more likely” to get the disease . Risk peα of 0.72) were dichotomized as strongly agree or very motivated vs. other categories for analysis.We assessed social influences on learning more about health  and motivation to comply using two items from our prior research : “The peWe utilized the 12-item short version of the intolerance of uncertainty scale  . Respondα of 0.85), and treated the average score as continuous in analysis. Higher scale scores reflected greater perceived ability and stronger preference for numeric information.We assessed numeracy using the Subjective Numeracy Scale, a self-report measure with two four-item subscales: perceived ability to perform mathematical tasks and preference for the use of numeric versus verbal information . Each itHealth literacy was assessed with a three-item screener  . Each itWe also assessed the following characteristics as potential covariates: age, race, ethnicity, Jewish ancestry, educational attainment, marital status, having biological children, planning to become pregnant in next year, urban vs. rural residence, household income, health insurance status, personal history of cancer, family history of cancer, and having had prior genetic testing.p < 0.10 were included in multivariable logistic regression models . About 50% of respondents identified as white/Caucasian, 39% as Latina/Hispanic, and 24% as Black/African-American. The majority had not completed college; 29% had a high school degree or less and 40% had some college education. Respondents had a moderate level of self-reported numeracy ability  and health literacy . About half (50%) had a household income of <$50,000. Less than half were married or living as married (40%). About 47% had biological children, and 28% reported that they were planning to become pregnant in the next year. Few respondents (10%) reported a personal history of cancer, although 58% had a family history of cancer. Less than half (31%) reported having had prior genetic testing. As shown in In terms of possible psychosocial predictors of interest in genetic testing , approxiWe assessed how interested respondents would be in having each type of genetic testing in the next year if it were offered . More thTo further investigate women’s level of interest in genetic testing, we also examined the proportion of respondents having a high level of interest . When asked about genetic testing as part of a general check-up, 24% were very interested in receiving testing with their healthcare provider and 23% through a gynecologist. For different types of testing, we found the highest proportions were very interested in genetic testing to learn about their risk of developing a preventable or treatable cancer (26%) and learn about carrier status (27%). Similarly, about 25% were very interested in learning about their risk of preventable or treatable diseases more generally. A slightly lower proportion reported being very interested in genetic testing to learn about pharmacogenomic variants (21%) or risk of an unpreventable or untreatable disease (20%).p = 0.046). For level of interest in different types of genetic testing, we found that Latina respondents (32.0%) were more likely to be very interested in learning about their risk of a preventable or treatable cancer compared with non-Latina respondents . Latina respondents (25.7%) were also more likely to be very interested in learning about their risk of an unpreventable or untreatable disease compared with non-Latina respondents . There was a trend toward a greater proportion being very interested in carrier status information .Interest in different types of testing was generally similar between Latina respondents and non-Latina respondents, as was interest in genetic testing as part of a general check-up . Howeverp < 0.001), higher genetic self-efficacy (both p < 0.05), higher genetic knowledge (both p < 0.001), greater perceived importance of cancer genetic information (both p < 0.001) and carrier status information (both p < 0.001), greater health consciousness (both p < 0.001), stronger health orientation (both p < 0.001), greater health information seeking (both p < 0.05), stronger social influence (both p < 0.001), higher intolerance for uncertainty (both p < 0.001), and higher subjective numeracy (both p < 0.001). Higher breast cancer risk perceptions were significantly associated with interest in cancer predisposition testing (p < 0.05) but not carrier status testing, and ovarian and colorectal cancer risk perceptions were not significantly related with interest in either type of genetic testing in the next year.We next examined the bivariate relationships of hypothesized predictors and ethnicity with interest in genetic testing for cancer predisposition and carrier status. As shown in p < 0.001), higher genetic self-efficacy (both p < 0.001), higher genetic knowledge (both p < 0.001), greater perceived importance of cancer genetic information (both p < 0.001) and carrier status information (both p < 0.001), greater health consciousness (both p < 0.001), stronger health orientation (both p < 0.001), greater health information seeking (both p < 0.001), higher breast cancer risk perceptions (both p < 0.001), higher ovarian cancer risk perceptions (both p < 0.01), stronger social influence (both p < 0.001), higher intolerance for uncertainty (both p < 0.001), and higher subjective numeracy (both p < 0.001).We found similar patterns of bivariate associations for the outcome of being very interested in genetic testing, with the exception of risk perceptions. Being very interested in both types of genetic testing was associated with higher worry about genetic risks , higher perceived importance of cancer genetic information , higher perceived importance of carrier status information , and higher health literacy . Being very interested in genetic testing for carrier status was associated with higher perceived importance of cancer genetic information  and higher perceived importance of carrier status information . In this model, respondents with some college were less likely to report being very interested than those with a high school degree .In models stratified by Latina ethnicity, predictors of interest in having cancer predisposition genetic testing in the next year were similar between strata , althougIn this study, we examined interest, and predictors of interest, in carrier screening and cancer predisposition testing offered as part of routine care among an ethnically diverse sample of 450 women aged 20–35. We found substantial interest in both types of genetic testing, with about half of respondents reporting that they would have each type of testing in the next year if it were offered. The proportion interested in testing for carrier status is consistent with the proportions found to be interested in a hypothetical expanded carrier screening test in prior studies . The finOf note, however, about half of respondents were not interested in testing in the next year, or were not sure, and many did not indicate the highest level of interest in either type of genetic test. It is therefore critical to develop effective decision support tools so that women can make informed decisions about testing if population-based genetic testing efforts are initiated. Better understanding of the predictors of interest is essential to developing effective decision support tools. Consistent with our prior research conducted with women who had been diagnosed with breast cancer at a young age, we found that women’s worry about their broader genetic risks was an important predictor of interest in genetic testing. Notably, worry about genetic risks was predictive, while risk perceptions for breast, ovarian, and colorectal cancer were not predictive of interest in either type of genetic testing in multivariable models. This finding suggests the importance of focusing on information that could be provided about inherited risks, rather than disease risks more generally, in approaches to informed decision making. Also consistent with our prior work, as well as other studies , those wUnlike the findings from our prior work with women who had been diagnosed with breast cancer at a young age , in thisNeither social influences nor intolerance for uncertainty was predictive of interest in genetic testing for cancer predisposition or carrier status in this population. Our prior research conducted with primary care patients offered genetic susceptibility testing for multiple health conditions had found that social influence from family and friends impacted interest in seeking information about genes . To explOur findings also add to what is known about interest in genetic testing among young Latina women. We generally found similar interest between Latina and non-Latina women in receiving different types of genetic testing in the next year, although a higher proportion of Latina women reported being interested receiving cancer predisposition testing in the next year and being very interested in this type of testing. However, ethnicity was not a significant predictor of interest in multivariable models, suggesting that younger Latina women are just as interested in testing as non-Latina women. We also found many similarities in predictors of interest, such as the importance of worry about genetic risks and genetic knowledge in both strata. These findings suggest the importance of addressing provider- and system-level barriers that may be driving lack of access to and uptake of genetic testing among interested Latina women . We alsoThese findings from this study should be considered in light of its limitations. Because population-based genetic testing is not being offered to this population, we asked about interest in hypothetical testing and actual testing uptake is likely to be lower . HoweverOur findings show substantial interest in both cancer predisposition testing and carrier screening among young women if offered as part of routine healthcare. We found similar interest between Latina and non-Latina women in receiving genetic testing, and worry about genetic risks and genetic knowledge were predictors of interest in both of these groups. The findings showed that women who were more concerned about their genetic risks, had higher knowledge about genetics, and perceived genetic information to be more important were more likely to be interested in both types of genetic testing. These findings therefore indicate support from the survey respondents for offering genetic testing for multiple, clinically indicated genetic tests as part of routine health visits. Such efforts will be important in improving access to genetic information among a broader population of patients than has been reached by many genetic testing initiatives to date. However, it will be critical to develop strategies to standardize outreach to all patients, to develop tools to help healthcare providers offer and communicate about genetic testing, and to address the needs of those who have less prior knowledge about genetics and lower health literacy in order to support informed decision making about genetic testing.


The genetic variation of the European population at a macro-geographic scale follows genetic gradients which reflect main migration events. However, less is known about factors affecting mating patterns at a micro-geographic scale. In this study we have analyzed 726,718 autosomal single nucleotide variants in 435 individuals from the catalan Pyrenees covering around 200 km of a vast and abrupt region in the north of the Iberian Peninsula, for which we have information about the geographic origin of all grand-parents and parents. At a macro-geographic scale, our analyses recapitulate the genetic gradient observed in Spain. However, we also identified the presence of micro-population substructure among the sampled individuals. Such micro-population substructure does not correlate with geographic barriers such as the expected by the orography of the considered region, but by the bishoprics present in the covered geographic area. These results support that, on top of main human migrations, long ongoing socio-cultural factors have also shaped the genetic diversity observed at rural populations. The current genetic variation of European human populations at a macro-geographic scale is mostly driven by isolation by distance patterns  and relaA basic question is whether there are socio-cultural factors in Europe that remained immutable over time and affected mate preferences at a microgeographic scale. This question is complex, as the recent demography of European populations has been shaped by a progressive regional concentration . This phStudying a relatively isolated European rural geographic region showing geohistorical singularities that maintain over time political and cultural borders could help understanding the role of different socio-cultural factors in mating patterns during the last centuries. Within this context, the catalan Pyrenees appear as a good candidate. First, the catalan Pyrenees constitute a vast and abrupt region in the north of the Iberian Peninsula, delimited to the east by the Mediterranean Sea, to the west by the Aigüestortes National Park and the Noguera Ribagorçana river valley, to the north by the border with France and Andorra and to the south by the central depression of Catalonia. A marked orography is distributed on a west-east axis along the Prepyrenees massifs .Most of the Pyrenean valleys run from north to south, except for the maritime ends and the Puigcerdà-La Seu d’Urgell axis. The Pyrenean valleys, of river origin, run in parallel to the watershed, with narrow gorges, which does not facilitate communications between valleys . Along iSecond, the sum of all these mountain territories accounts for approximately a quarter of the surface of Catalonia, while the current population  barely exceeds 1% of the total catalan population. Throughout history, the demography of the Pyrenean region has undergone marked variations. The times of maximum splendor go back to the Middle Ages, followed by successive demographic oscillations. In Modern times, the maximum population was reached in the 1880s, followed by a progressive population decline until today . Due to comarques of Catalonia, corresponding to Alt Urgell, Alta Ribagorça, Val d’Aran, Pallars Jussà, Pallars Sobirà and Cerdanya and the northern part of another four more, Solsonès, Berguedà, Ripollès and Garrotxa (Vegueries (12th-18th centuries) (Corregimientos (18th century) (Comarques (19th century)  , Corregicentury) , Provinccentury)  (Burgueñcentury) , 1992. Dcentury) .In a previous study using whole genome sequencing on a limited sample size of 29 individuals , we showIn the present study we have conducted a large genotyping study on 435 samples, analyzing and interpreting their genetic diversity in orographic and cultural terms.We have collected samples from five reference hospital centers belonging to three health regions expanding the catalan Pyrenees. Recruitment period was extended from July 2014 to October 2016. In total, we recruited 435 samples  of subjects born and with all their grandparents born in the Pyrenean region . Genotype clustering was analyzed using the Axiom Analysis Suite 6.0 software adjusting for BestWorkflow settings. Quality control (QC) was tuned to sample calling rate >0.95, marker calling rate >0.90, and Hardy-Weinberg equilibrium (HWE) >10–5. After removing Indel and copy number variation (CNV), and QC, 780,310 SNPs  on 435 subjects were available for subsequent analyses (thereafter GENPIR data set).We collected 1 ml of peripheral blood from each participant in EDTA-coated tubes. All participants were genotyped using Applied Biosystems Axiom™ Precision Medicine Diversity Array (PMDA) on GeneTitan™ Multi-Channel Instrument  at We estimated relatedness among samples by using SNPRelate R package . IdenticData was phased using the Michigan-imputation server-1.5.7 pipeline  with theIBD tracts between pairs of chromosomes from different individuals and homozygote by descent (HBD) fragments between chromosomes from the same individual were inferred with Beagle 4.0 (IBD_Beagle) , using tTo make comparisons with other populations, GENPIR genotype data was merged with genotype data from samples of the 1,000 Genomes Phase 3 project (1KG3)   and Huma-indep-pairwise 200 25 0.3. After QC passing, PCA analysis was done on 3,805 subjects  and 175,277 autosomal markers. PCA QC control was also performed to a data set obtained after extracting subjects belonging to GENPIR and European populations including Finland , Russia ; Great Britain and Scotland ; Orcadian (Scotland) ; Utah residents (CEPH) with Northern and Western European ancestry ; French Basques ; France ; Iberian Peninsula (Spain) ; Bergamo   and Toscana  ,  in order to perform independent PCA analyses. European populations of Adygey and Sardinia were not included in the PCA analysis as they are genetically isolated populations which can bias the results.PCA was done on the unrelated set of GENPIR and worldwide merged datasets using plink1.9 software , after pt-test.ADMIXTURE v1.30  was usedThe bishopric origin of the grandparents from a given sample was projected in two dimensions using a multiple correspondence analysis  as impleGiven the regionality of the sampled dataset, the presence of population substructure must be relatively small. Since the IBD statistic is sensitive towards subtle hidden genetic relationships between individuals, we computed an IBD matrix with Beagle . We projWe evaluated the genetic ancestry across geographic space on GENPIR population autosomal data set by tess3r software , applyinThe relationship between genetic variation and cultural or political units while controlling by the putative confounder effect of geography was tested by means of a partial Mantel test  implemenA Procrustes analysis  between Unsupervised clustering of the individuals using the first two dimensions computed by SMACOF was conducted by means of the MCLUST package  implemenWe first analyzed the genetic relationships of the sampled individuals at worldwide level using a Principal Component Analysis (PCA) .The first two PCA components (PCs), explaining 11.3% of variance, show that the considered catalan Pyrenees samples are genetically related to other samples with European ancestry . Within Given these results, we run an unsupervised ADMIXTURE analysis focusing on the European region for K ranging from one to four in order to quantify the European ancestry proportions in GENPIR samples, revealing a minimum cross validation error value for K= 2–3 .As shown in At a local level, the presence of a higher proportion of SW European ancestry in the West region of the catalan Pyrenees supports that this region has been more accessible for migrations than other populations from the Iberian Peninsula. In addition, the higher contribution of N, C and SE European components at the East region of the catalan Pyrenees reflects a major permeability of this Pyrenean region, where geographical barriers are much weaker and with a much richer communications network, that has allowed contact with the nearby regions of northern and eastern Europe. We noted that the SE component, being significant on the Mid and East Pyrenean regions, reflects potential migratory events from Southeast Mediterranean coasts.Given the observed differences in ancestry among the GENPIR samples, we conducted a PCA only using GENPIR samples .Furthermore, this micro-population substructure can be interpreted in geographic terms. In particular, a procrustes analysis between the geographic coordinates of the samples and the genetic map defined by the first two PCA dimensions showed a symmetric correlation of 0.61 (comarques) and historical (bishoprics) administrative-religious boundaries, the West cluster comprises Pallars, Ribagorça, Cerdanya and Alt Urgell comarques as well as Lleida and Urgell bishoprics; the Middle cluster comprises Solsonès and Berguedà comarques and Solsona bishopric and the East cluster includes Ripollès and Garrotxa comarques as well as Vic and Girona bishoprics , or if they were influenced by other long term ongoing cultural factors such as the limits defined by middle age-founded bishoprics. We applied a Mclust analysis using the first two dimensions from SMACOF in order to identify clusters showing a similar probability distribution function. The optimal number of clusters identified by Mclust was six (BIC = 406.33) that accurately reflect a hardest effect of geographic barriers that is shaped by administrative divisions, both comarques and bishopric  that contains the intersection of four bishoprics .comarques depend on geography, the identified geographic clusters by tess3r could reflect cultural and/or political barriers. We conducted a partial Mantel test between the Euclidean distance estimated from the first two PCs, and the assignment to the same administrative division or bishoprics, controlled by the geographic distance. Pearson’s correlation between PC based distances and bishoprics after controlling by geography in a partial Mantel test was 0.434 . This degree of association is higher than the observed between genetics and administrative divisions of comarques . When considering a classification based on bishoprics and administrative divisions at the same time, Pearson’s correlation decreased to 0.294 . Similar results supporting higher correlation between bishopric divisions and genetic diversity were obtained when using the first two dimensions from the SMACOF analysis conducted with the IBD distance matrix. The degree of correlation between genetics and bishoprics after controlling by geographic distance was 0.563 . This correlation decreases to 0.382  when considering administrative divisions and it is similar when considering both bishopric and administrative divisions . Overall, these results suggest that bishoprics play a role in shaping the genetic variation of GENPIR samples by modifying their mating patterns.Since bishoprics and We supported such a hypothesis based on genetic data by taking advantage of the sampling strategy conducted in this study, which incorporated the geographic birthplace of the four grandparents .propositus network in which each propositus is linked to their four grandparents generating a complex network centered on bishopric boundaries. We can also observe that grandparent and parent couples come from the same bishopric (over 80% of couples) or to a nearest bishopric (near 10% of couples) (couples) . The ovecouples)  of the Mcouples) . The cencomarques); an eastern area (Girona); and a southern territory or central Catalonia .The ecclesiastical division of the modern era responds to human spheres of multisecular relationships. For this reason, it is not surprising that the bundles of family relationships roughly coincide with the bishoprics: a central Pyrenean space ‒bishopric of Urgell‒with abundant interactions (although it is capable of being subdivided into Traditionally, the main force used for explaining biases in mating choice in Spanish rural areas compared to urban areas has been geography . Poor trHumans, as social animals, are subject to rules that emanate from power, economic, political or religious, which beyond allowing the proper functioning of social structures, also modulate interpersonal relationships. The role of the church has been prominent throughout history, acting as a central and determining factor of interpersonal relationships in past societies. In particular, the Catholic Church, with its rigid pyramidal structure, has left an imprint on societies that go beyond religious aspects. As our results show, the genetic structure of the rural populations of the catalan Pyrenees, in addition to the geographical factor, has also been modulated by administrative-social factors, which have established limits to the social relationships of individuals, being the limits established by the bishoprics one of the determining factors.In this context, the bishoprics can be considered as the most representative territorial organization frameworks, historically very stable and cohesive, and necessarily well adapted to the strong geographical conditions that mark the Pyrenean environment.A singular orography that has determined the establishment of administrative-religious limits, perpetuated unalterably for centuries, and the rigid social structure enforced by the Catholic Church over long periods of time, have shaped the genetic structure of the catalan Pyrenees population. It remains to be determined to what extent this structure may have generated interpopulation differences able to be reflected in differences on genetic susceptibility to diseases.


Trifolium pratense L. applying amplified fragment length polymorphism and methylation-sensitive amplification polymorphism analyses. We observed low levels of genetic and epigenetic differentiation among populations and between habitat types. Genetic and epigenetic variations were not interdependent. Thus, genetic variation was significantly isolated by habitat dissimilarity, whereas epigenetic variation was affected by environment. More specifically, we observed a significant correlation of epigenetic diversity with soil moisture and soil pH . Genetic variation was, therefore, affected more strongly by habitat-specific environmental conditions induced by land use-related disturbance and gene flow patterns, while epigenetic variation was driven by challenging environmental conditions.Central European grasslands, such as calcareous grasslands and oat-grass meadows, are characterized by diverse environmental conditions and management regimes. Therefore, we aimed to determine potential differences in genetic and epigenetic variation patterns between the contrasting habitats and to identify the drivers of genetic and epigenetic variation. We investigated the genetic and epigenetic variation of the ecologically variable plant species  For instance, T. pratense occurs in both calcareous grasslands (CGs) and oat-grass meadows (OMs). Semi-natural CGs developed from grazing over thousands of years and represent nutrient-poor grasslands with relative dry soil conditions [T. pratense in CGs and OMs appeared as a promising model system for studying genetic and epigenetic variation patterns within contrasting habitats.Hutchinson  defined nditions . Howevernditions . AlthougPrevious studies showed that environmental conditions may affect the genetic code of a plant species indirectly –8 indicaet al. [The potential reversible DNA methylation of cytosine represents the most studied epigenetic mechanism with important effects on ecologically relevant traits ,14. Cytoet al. , allow tet al. . These met al. , since oet al. ,9,18,19.Changes in DNA methylation were observed to increase in response to biotic and abiotic stressors –22 such During the last few decades, numerous studies on various plant species observed profound effects of environmental conditions on both genetic and epigenetic variation patterns e.g. –7,9,25).,9,25.7,9T. pratense: (i) are populations genetically and/or epigenetically differentiated among contrasting grassland habitats or are they isolated by distance? (ii) does genetic and/or epigenetic diversity differ between CG and OM populations? (iii) what is the impact of environment on genetic and/or epigenetic diversity levels? and (iv) is genetic and epigenetic variation of T. pratense populations interdependent?We asked the following questions to gain a better understanding about the impact of contrasting environmental conditions on genetic and epigenetic variation in . 2. 2.1Arrhenatherum elatius (L.) J. Presl & C. Presl) meadows  flowers between June and September [T. pratense is an essential species for profitable grassland management due to its high fodder value [The widespread species eptember . It is september . The pereptember . T. prater value  and its er value .et al. [Ellenberg indicator values (EIVs), using plants as bio-indicators, were applied to gain information about environmental conditions . Environmental conditions may often fluctuate in time and space and can, thus, not be estimated in a single measurement . The indet al. , represeet al. . EIVs shet al. . Therefoet al. . These iFor molecular analyses, we identified the species in the field and took leaf samples from 16 individuals per population and species to cover more than 90% of the total (epi)genetic diversity . Samples. 2.22O.All 160 individuals were analysed genetically and epigenetically. DNA was extracted following the CTAB protocol from Rogers & Bendich  modifiedGenetic variation within populations was determined using genome-wide genotyping with amplified fragment length polymorphisms (AFLPs) . The AFLet al. [MSeI by two isoschizomers HpaII and MspI. These restriction enzymes attach at the same tetranucleotide (5′ CCGG) sequence with differing sensitivity to cytosine methylation states and cover, thus, the most frequent methylation types in the CG and CHG  sequence context [MSAP analyses were performed in accordance to the technique of Schulz et al. . Thus, M context ,16. TherHpaII and MspI) were analysed per run, respectively. Samples without a clear banding pattern between 60 and 420 bp were repeated and only strong and clearly defined fragments were taken into account for further analyses. Fragment data were analysed manually with the software Bionumerics 7.6.2 .The fluorescence-labelled DNA fragments were separated by capillary gel electrophoresis using an automated capillary electrophoresis machine . Ninety-six samples and 48 individuals  fragments are present in both profiles (unmethylated state/u-type), (ii) fragments are present only in EcoRI/MspI profiles , (iii) fragments are present only in EcoRI/HpaII profiles , and (iv) complete absence of fragments in both profiles (uninformative state).After fragment detection, we applied the ‘mixed scoring 2’ by Schulz et al.  to score [et al.  defined The reproducibility of the AFLP and MSAP analyses was tested by calculating the genotyping error rate . Ten per. 2.3Genetic and epigenetic differentiation within and among populations as well as between habitat types were partitioned with hierarchical analyses of molecular variance (AMOVA). AMOVAs were calculated based on pairwise Euclidean distances among samples using the software GenAlEx 6.41 .ΦPT values; electronic supplementary material, table S4). Pairwise geographic distances (km) were calculated from coordinates, and for habitat types, a habitat dissimilarity matrix was constructed by coding pairs of CG/OM populations by ‘1′ and pairs of equal habitats by ‘0’ . A correlation between genetic and epigenetic distance matrices was examined applying a simple Mantel test. Geographic and habitat dissimilarity matrices were also checked for correlation patterns. Genetic and epigenetic isolation by distance (IBD) and isolation by habitat dissimilarity (IBH) were tested performing simple and partial Mantel tests with 9999 permutations applying the ‘vegan’ library in R [Epigenetic and genetic distance matrices were calculated within the AMOVA (ary in R .doi:10.5061/dryad.kt71r).Although simple and partial Mantel tests are suitable to test dissimilarity hypotheses ,52, e.g.pi · log2pi, where pi is the frequency of the (epi)genetic marker score ‘1’ within the population. The acronyms ‘SIgen’ and ‘SIepigen’ stand for the mean Shannon's information index and will be substituted by the terms ‘genetic diversity’ and ‘epigenetic diversity’ in the discussion.Genetic and epigenetic diversity within populations were determined using the R script ‘MSAP_calc’ . Applyingen, SIepigen, and environmental parameters  between CG and OM populations.Two-sided T-tests (and Wilcoxon–Mann–Whitney tests if necessary) were calculated to examine differences of SIgen and SIepigen with light, soil moisture, soil pH, and soil nitrogen were analysed with correlation tests (Pearson correlation coefficients) applying the ‘PerformanceAnalytics' [Possible correlations of SIalytics'  and ‘Hmialytics'  librariegen and SIepigen were examined with paired T-tests. Additionally, SIgen and SIepigen were tested for interdependence applying the correlation tests as mentioned above. Unless otherwise stated, the R environment [Differences between SIironment  was used. 3. 3.1ΦPT of 0.07 with a differentiation between habitat types of 3% and a differentiation among populations of 4%. The hierarchical AMOVA of the combined epigenetic dataset resulted with 0.05 in a lower ΦPT. 1% of epigenetic variance resided between habitat types and 4% among populations. Values of epigenetic differentiation for h-, m- and u-subepiloci are given in Hierarchical AMOVA of genetic data  revealedr = 0.30; p = 0.069). Geographic distance (IBD) and habitat dissimilarity (IBH) were also not correlated .A simple Mantel test revealed no correlation between genetic and epigenetic differentiation across all populations  and partial  Mantel tests   (el tests  as well = 0.010) . Epigene. 3.2epigen) of 0.46   was significantly associated with soil moisture and soil pH (epigen decreased with increasing drought and soil pH.SIitrogen) . However soil pH . Thus, Sgen revealed significantly lower values than SIepigen (p < 0.001). Moreover, SIgen and SIepigen were not significantly correlated across populations .SI. 4. 4.1Genetic differentiation levels were higher than epigenetic ones indicating that genetic variation may be more strongly structured than epigenetic variation . Some pret al. [T. pratense.Neither epigenetic nor genetic differentiation correlated with geographic distance among populations (IBD). Kloss et al.  showed tT. pratense populations showed higher genetic than epigenetic differentiation among habitat types. This result complies with the findings of Lele et al. [Scabiosa columbaria. Management practices like mowing and grazing differ strongly in intensity and time of application [T. pratense was shown to depend on plant weight, stem length, leaf size and further traits [per se seem to shape genetic differentiation.However, even common and outbreeding species may reveal increased differentiation among populations through reduced abundance, spatial isolation, different land use regimes, and thus lowered gene flow . T. prate et al. , who obse et al.  observedlication ,61. Earllication . These alication . Flowerir traits  shaped b. 4.2T. pratense complied with genetic diversity levels previously reported for common grassland species [Mean genetic diversity of  species . The com species ,3,9,19.Previous studies about genetic diversity patterns in common CG  and OM pT. pratense populations significantly decreased with increasing drought and soil pH. Therefore, challenging environmental conditions may affect epigenetic diversity in different ways.However, OM populations showed higher epigenetic diversity levels than CG populations. The difference of epigenetic diversity between CG and OM populations was significant only for m-subepiloci. Therefore, changes of methylation in the CG context (m-subepiloci) may play a more important role for habitat adjustment than regulation of gene function in the CHG context (h-subepiloci). As mentioned above, the pattern and amount of DNA methylation in plants is sensitive to biotic and abiotic stressors ,24,69. Oet al. [T. pratense populations in OMs, while they could not observe any impact of local habitat quality. Therefore, genetic diversity of T. pratense may be affected more by landscape structure, related management, and/or gene flow patterns than by local environmental conditions.Pearson correlation revealed no significant association between genetic diversity and environment. Pagel et al.  postulatT. pratense populations seemed to be associated with environment, while genetic diversity was not. These results accompany the assumption that DNA methylation and demethylation at a genome-wide scale are induced by environmental changes [et al. [T. pratense produced less yield under drought stress. Furthermore, Labra et al. [T. pratense populations may decrease with increasing drought. Additionally, epigenetic diversity decreased with increasing soil pH. Soil pH influences the amount of plant available nutrients. Since T. pratense is a nitrogen-fixing legume [T. pratense populations may show limited productivity and decreased epigenetic diversity as reaction to phosphorus limitation. However, the correlation with soil moisture and soil pH was not significant for h-epiloci indicating that the regulation of gene function by (de-)methylation in the CHG context may not be an issue for adaptation to different environmental conditions.However, several studies reported correlations between environmental factors and epigenetic characteristics of plant populations ,12,13. I changes  and cons changes ,69. More changes –22. Labr [et al.  emphasiz [et al. , who obsa et al.  postulata et al. . Thus, eg legume , its perg legume . In calcg legume  and thusT. pratense, epigenetic diversity was even significantly higher than genetic diversity indicating that these natural populations seem to vary more in DNA methylation than in DNA sequence [Previous studies observed higher levels of epigenetic than genetic diversity especially in natural plant populations ,13,17,18sequence .et al. [T. pratense populations as facilitated or pure rather than obligatory. This finding is in accordance with the results of previous studies on wild plants, which also observed epigenetic variation to be largely autonomous from genetic variation [Furthermore, neither correlation nor simple Mantel tests revealed a significant association of epigenetic with genetic diversity or distance. In this context, Richards  defined et al.  stated tet al. ,74 and cariation ,75.. 5Our results revealed an impact of different environmental conditions on genetic and epigenetic variation. Genetic variation was affected by habitat-specific environmental conditions induced by management-related disturbance as well as gene flow patterns. Epigenetic variation was driven by challenging environmental conditions in two ways. It increased with rising necessity for niche establishment, but decreased under drought and high pH, the latter potentially resulting in phosphorus limitation.Nevertheless, MSAP markers reveal only a limited number of anonymous loci, which are difficult to link to functional genomic elements. Therefore, future studies should apply next-generation-based bisulfite sequencing approaches to evaluate the effects of challenging environmental conditions on methylation patterns more precisely .


Gentiana hexaphylla complex (Gentianaceae). We performed genetic clustering with spatial and non-spatial models, phylogenetic reconstructions, and ancestral range estimation, with the aim of addressing the processes influencing diversification of G. hexaphylla in the HM. We find the G. hexaphylla complex is characterized by geographic genetic structure with clusters corresponding to the South, North and the central HM. Phylogenetic reconstruction and pairwise FST analyses showed deep differentiation between Southern and Northern populations in the HM. The population in Mount Taibai exhibited the highest genetic similarity to the North HM. Ancestral range estimation indicated that the G. hexaphylla complex originated in the central HM and then diverged in the Pliocene and the Early Pleistocene, before dispersing widely, resulting in the current distinct lineages. Overall, we found deep genomic differentiation in the G. hexaphylla complex corresponds to geographic barriers to dispersal in the HM and highlights a critical role of the uplift of the Daxue Mountains and subsequent climatic fluctuations underlying diversification. The colonization of G. hexaphylla in the Mount Taibai region suggests directional dispersal between the alpine flora of the Qinling Mountains and the HM.Understanding the evolutionary and ecological processes driving population differentiation and speciation can provide critical insights into the formation of biodiversity. Here, we examine the link between population genetic processes and biogeographic history underlying the generation of diversity in the Hengduan Mountains (HM), a region harboring a rich and dynamic flora. We used restriction site-associated DNA sequencing to generate 1,907 single-nucleotide polymorphisms (SNPs) and four-kb of plastid sequence in species of the  The ligation products were purified and PCR-amplified, followed by gel purification and size selection for fragments in the range of 350–550 bp. Libraries were multiplexed and sequenced using 2 × 150 bp reads generated on the Illumina Novaseq 6,000 .Total genomic DNA was extracted from dry leaves using a Dzup plant genomic DNA extraction kit . DNA concentrations were quantified with a Qubit 2.0 fluorometer (Life Technologies). For RAD library construction and sequencing , each saprocess_radtags script in Stacks 2.0 , and we tested a range of different mismatches between stacks within and between individuals . PCR duplicates were filtered using gstacks following the approach of EH) and observed heterozygosity (OH) using the populations module in Stacks.Samples were initially de-multiplexed with the acks 2.0 , 2013. Racks 2.0  with defacks 2.0 , 2013 toG. hexaphylla  was created by randomly subsampling 90% of the total number of loci and run for 1,000 MCMC iterations.For exploring the genetic clusters present within the TRUCTURE  based onRUCT 1.1 . As FastRUCT 1.1  in the RRUCT 1.1 . Given tRUCT 1.1 . This meWe constructed a phylogenetic tree based on the nuclear genomic SNPs using maximum likelihood (ML) in IQ-TREE  with 1,0Using concatenated plastid sequences, ML phylogenetic analyses were conducted with IQ-TREE  implemenG. section Cruciata .p < 0.05) were removed. MaxEnt 3.4.1  to infer population genetic structure in the G. hexaphylla complex. chooseK.py indicated that the marginal likelihood scores from FastSTRUCTURE analyses peaked at K = 3 , indicating strong IBD. The cross-validation analyses in conStruct indicated that the spatial models always had higher predictive accuracy than non-spatial models, with little increase in accuracy when K was greater than three  than the northern populations  had higher values of pairwise  regions . GeneticG. hexaphylla complex formed a monophyletic lineage. The TreeMix analysis also showed that the southern populations were a distinct clade with populations placed on a long branch  and the North (HN), respectively . The two subclades in the HN and HS diverged in the Early Pleistocene 1.71 Ma (95% HPD: 1.09–2.38 Ma) and in the Late Pliocene 3.10 Ma (95% HPD: 2.28–3.88 Ma), respectively.Our divergence time analyses based on plastid sequences  showed tG. hexaphylla complex, as it received the largest LnL value and the lowest AIC and AICc scores  around 4 Ma, implying that the ancestral lineage dispersed out of this area southward and northward independently, which gave rise to different sub-lineages  were kept for distributional reconstruction. The palaeo-distributional reconstruction showed that during the LGM the potential habitat of f the HM . AfterwaGentian species, we detected deep genetic divergence corresponding to geological barriers in the HM, with divergence likely promoted by both mountain uplift and climatic fluctuations. While we detected divergence in populations spread across the landscape, there was notably high genetic similarity between populations in Mount Taibai and the North HM, indicating a connection between the alpine flora of the Qinling Mts and the HM. Here, we discuss our results in terms of the biogeographic history of this important hotspot for alpine species, and consider the implications for future studies.As the longest continuously existing alpine flora , the HM in situ alpine speciation . Thus, our results not only point to geographical structuring, but also highlight the need for taxonomic clarification in this species complex.In addition, by sequencing typical individuals of each species in the in situ diversification of many alpine groups , which may then have acted as barrier to dispersal. This is likely to be similar to Pinus armandii .The data presented in the study are deposited in Dryad  and Chinese Scholarship Council to P-CF. AF was supported by the German Science Foundation (Deutsche Forschungsgemeinschaft) project no. FA1117/1–2.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.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 genetic lottery: why DNA matters for social equality.”  by Kathryn Paige Harden.A book review of “ The Genetic Lottery: Why DNA Matters for Social Equality aims to convince the reader that recent methodological developments in human genetics should change the broader societal conversation about redistributive justice. The author, Dr. Kathryn Paige Harden, is a Professor of Psychology at the University of Texas, Austin, who specializes in behavioral genetics. Her book starts from the premise that human behaviors, and in particular educational attainment, are “heritable,” i.e., that within a study sample, some fraction of the phenotypic variance is explained by differences in genotypes. As is described, we can now identify some of the genetic loci associated with trait variation through genome‐wide association studies (GWAS) and make predictions—currently, quite noisy predictions—of individual outcomes from genotypes. In the author's view, GWAS findings underscore that people differ not only in the social circumstances into which they are born but also in the genetics that they happen to inherit. Since neither social circumstances nor genetics are earned or chosen, both result from “luck.” The book argues that both sources of luck contribute commensurately to social inequalities in educational attainment and ultimately in income, and therefore that genetics is needed in order to better understand and redress social inequalities. In particular, in Harden's view, recent GWAS findings should lead us to be mindful of principles of equity and not just equality.The Genetic Lottery includes discussion of many engaging and thought‐provoking examples. But in our view, its central argument mischaracterizes where the field of human genetics stands and what it promises. Although some of the controversy over the book has centered on its premise, the fact that educational attainment is heritable was documented before GWAS and is in some sense trivial. In humans as in any other species, almost all traits that vary within a group are heritable  genetic variance varies from 17% to over 40%, depending on the assumptions of the heritability estimator and the study sample  is regressed on each genetic variant, with a statistical control for effects of population stratification  as a covariate allows one to study the impact of an environmental intervention  on an outcome , while statistically controlling for heterogeneity in genetic effects on the outcome . By analogy, sib‐GWAS provides evidence for PGS as a cause of sibling differences in outcomes: as she explains, Moreover, the book's central focus is not on differences between family members but rather on unequal outcomes among unrelated people in the population. This is where its analogy of a genetic lottery breaks down , as well as effects of assortative mating of the parents. That is not all: because no statistical control for population structure is perfect, or even all that well defined, GWAS estimates may also include residual effects of the genetic background, and, perhaps most difficult to disentangle in humans, environmental effects that are correlated with the genetic background. Thus, PGS for traits based on standard GWAS are not estimates of direct genetic effects alone, and their predictive power derives from all these effects combined. For educational attainment, the distinction between standard GWAS and family GWAS is particularly pronounced: direct genetic effects for educational attainment are estimated to account for as little as one fourth of the variance in the PGS of a standard GWAS  might be entirely caused by environmental factors, even when differences within groups are caused by genetic differences” [p. 159], but rather that, unless the environment is carefully controlled, comparisons across individuals—even within a group—do not allow genetic causes of trait variation to be isolated (Lewontin, “a statistical point that applies anytime we are trying to jump from one level of aggregation to another” [p. 86].The limits imposed by not controlling environmental effects also apply to comparisons among individuals within the study group, not just between groups—hence the methodological problem of population and environmental confounding in GWAS (Lander & Schork, within a racial or ethnic group. In particular, individuals who identify as Black Americans vary greatly in their proportions of recent African and European ancestries, as a consequence of the historical legacy of slavery, including the one‐drop rule and Jim Crow laws. This African ancestry traces back to disparate geographical locations in Africa, shaped by the routes of the trans‐Atlantic slave trade and migration patterns since (Micheletti et al., “become more global” [p. 191] to develop a reliable PGS for educational attainment in Black students in the United States, or that the development of such a PGS will be an indispensable tool in distinguishing genetic from “specific environmental causes of important developmental outcomes” [p. 192].This lack of controlled environment confounds comparisons between sets of individuals in distinct settings or of differing ancestries—acutely so for individuals from different racial groups in the United States, who have been subjected to inequitable environments for generations. But it also poses a challenge In our view, these instances reflect a more general tension in the book, which arises from trying to have it both ways: to argue that PGS for educational attainment provide interpretable and meaningful predictions of inter‐individual differences that reflect underlying genetic causes, yet to claim that they have no validity beyond hypothetical ancestry group boundaries. As we have laid out, we believe instead that current PGS for educational attainment are neither interpretable nor particularly meaningful. GWAS undoubtedly captures some causal genetic effects, that is, more than confounding alone, and there is interesting science to learn from these initial findings. But we currently understand next to nothing about the causal paths from GWAS findings to educational attainment, notably the extent to which they include analogs of Jencks‐style “red hair effects” and the legacy of accumulated indirect effects. That may not matter when PGS for EA are to be employed as a statistical tool in the study of the impact of local social interventions, but it matters greatly when they are used to elucidate, let alone redress, social inequalities.The Genetic Lottery therefore leaves us unconvinced, and with the impression of genomics serving as a distraction from much more exigent political conversations (e.g., National Academies of Sciences, Engineering, and Medicine, Given these limitations, we do not see what the field of genetics has to add to the conversation about redistributive justice, beyond confirming what has long been recognized—that life outcomes differ for all kinds of reasons beyond people's control—and we very much doubt that overstating our understanding of the genetics of behaviors is going to increase empathy. As the author appreciates, there is a history of this kind of practice, invariably with nefarious consequences, yet every generation seems to believe that their technological twist will help them to avoid the same pitfalls. Despite its engaging narrative,


Measuring genetic diversity is an important problem because increasing genetic diversity is a key to making new genetic discoveries, while also being a major source of confounding to be aware of in genetics studies.Using the UK Biobank data, a prospective cohort study with deep genetic and phenotypic data collected on almost 500 000 individuals from across the UK, we carefully define 21 distinct ancestry groups from all four corners of the world. These ancestry groups can serve as a global reference of worldwide populations, with a handful of applications. Here, we develop a method that uses allele frequencies and principal components derived from these ancestry groups to effectively measure ancestry proportions from allele frequencies of any genetic dataset.snp_ancestry_summary of R package bigsnpr.This method is implemented in function Bioinformatics online. Several projects have focused on providing genetic data from diverse populations, such as the HapMap project, the 1000 genomes project (1KG), the Simons genome diversity project and the human genome diversity project (kα (positive and sum to 1) which minimizes the following problem: M is the number of variants, K the number of reference populations, j in population k and j in the cohort of interest. Here, we carefully use information on self-reported ancestry, country of birth and genetic similarity to define 21 distinct ancestry groups from the UKBB to be used as global reference populations, which is the first innovation of this paper. These include nine groups with genetic ancestries from Europe, four from Africa, three from South Asia, three from East Asia, one from the Middle East and one from South America  onto the PC space ; 4/solve the final  quadratic programming problem, by relying on R package quadprog , FinnGen (Finnish), a Peruvian cohort, a Qatari cohort and Sub-Saharan African cohort, the ancestry proportions obtained match expectations  summary statistics for which allele frequencies are reported and apply this new method to them. We first apply function ctations . When coctations .We then perform three secondary analyses. First, we compare the results obtained previously in Here, we have identified an unprecedentedly large and diverse set of ancestry groups within a single cohort, the UKBB. Using allele frequencies and PCs derived from these ancestry groups, we show how to effectively measure diversity from GWAS summary statistics reporting allele frequencies. Measuring genetic diversity is an important problem because increasing genetic diversity is key to making new genetic discoveries, while also being a major source of confounding to be aware of in genetics studies. Our work has limitations though. First, it is unknown whether we can effectively capture any existing ancestry as a combination of the 21 reference populations we defined. For example, it seems that Native Hawaiians in the PAGE study are partly captured by the “Philippines” ancestry group we define. Second, with the 21 ancestry groups we define, we probably capture a large proportion of the genetic diversity in Europe, but more fine-grained diversity in other continents may still be lacking. Third, when using the allele frequencies reported in the GWAS summary statistics, it is not clear whether they were computed from all individuals , and, for meta-analyses of binary traits, whether they were computed as a weighted average of total or effective sample sizes. Despite these limitations, we envision that the ancestry groups we define here will have many useful applications. The presented method that uses these groups could e.g. be used to automatically report ancestry proportions in the GWAS Catalog (https://github.com/privefl/bigsnpr) and a recent enough version can be installed from CRAN. A tutorial on ancestry proportions and ancestry grouping is available at https://privefl.github.io/bigsnpr/articles/ancestry.html. The set of reference allele frequencies for 5 816 590 genetic variants across 21 diverse ancestry groups defined here can be downloaded at https://figshare.com/ndownloader/files/31620968 and PC loadings for all variants across 16 PCs at https://figshare.com/ndownloader/files/31620953. All codes used for this paper are available at https://github.com/privefl/freq-ancestry/tree/main/code. We have extensively used R packages bigstatsr and bigsnpr (The newest version of R package bigsnpr can be installed from GitHub (see  bigsnpr  for easybtac348_Supplementary_DataClick here for additional data file.