Genetic testing for cancer susceptibility has been widely studied and utilized clinically. Access to genetic services in research and practice is largely limited to well‐insured, Caucasian individuals. In 2009, the Cancer Resource Foundation (CRF) implemented the Genetic Information for Treatment Surveillance and Support (GIFTSS) program to cover the out‐of‐pocket expenses associated with cancer genetic testing, targeting high‐risk individuals with limited financial means and limited health insurance coverage. Here, we (i) describe the characteristics of participants in the Massachusetts (MA) GIFTSS program and (ii) evaluate mutations found in this diverse sample. A secondary retrospective data analysis was performed using de‐identified demographic data obtained from laboratory requisition forms and cancer genetic testing result information from the laboratory source. Eligible participants were those who utilized the MA GIFFTS program from 2009 through December of 2014. Data were summarized using descriptive measures of central tendency. Participants were residents of Massachusetts who had health insurance and had a reported income within 250–400% of the federal poverty level. Genetic testing results were categorized following clinical guidelines. Overall, 123 (13%) of participants tested positive for a mutation in a cancer susceptibility gene. For those with a cancer diagnosis, 65 (12%) were found to have a positive result and 20 (7%) had a variant of uncertain significance (VUS). For those unaffected patients, 58 (15%) had a positive result and 10 (3%) were found to have a VUS. The results from this study are useful in describing genetic testing outcomes in this high‐risk underserved community. Repeatedly, the literature reports that individuals from diverse or limited resource settings are less likely to access genetic testing. Continued research efforts should be devoted to promoting the access of genetic testing in the high‐risk, underserved community. Results from cancer predisposition genetic testing are an important component of holistic cancer care and can inform treatment, diagnostic, surveillance, and preventative health recommendations BRCA1/2 gene testing. Out‐of‐pocket costs associated with genetic testing even in the insured have also been identified as a barrier, regardless of race or ethnicity Costs of the genetic test and limitations to health insurance coverage are barriers to genetic testing. Cragun et al. 2015) identified that having public health insurance, with an implied limitation to coverage was a barrier to utilizing genetic testing in young black women  identifiIn 2009, the Cancer Resource Foundation (CRF), a 501(c)(3) program led by oncology and public health nurse leaders, initiated the Genetic Information for Treatment Screening and Surveillance (GIFTSS) voucher program in Massachusetts (MA) to support the underinsured who could not afford the out–of‐pocket expenses associated with genetic testing. Underinsured individuals were defined as those individuals who have health insurance that covers some health costs, but whose health insurance neglects to cover the entire costs of specific medical tests. This leaves these underinsured with either no access to the specific test or with a high out‐of‐pocket cost. At the time of inception of the program, the MA Healthcare Reform Act (HCRA), which was enacted in 2006, provided comprehensive health insurance to adults earning up to 150% of the federal poverty level. The MA HCRA did not include genetic testing as a covered service. Because individuals covered under the HCRA did have health insurance, participants in this program were not eligible for local or national financial relief programs. Thus, those individuals covered under HCRA had neither access to genetic testing as a covered benefit through their insurance nor the ability to seek outside relief programs.The eligibility of individuals for the GIFTSS program met medical high risk as defined by the National Comprehensive Cancer Network (NCCN) N = 128) included participants from the same cohort and indicated that approximately half of the participants had a high school education or less, over half utilized state health insurance, and were from over 31 different ancestral backgrounds The CRF relied on referring clinical experts  to identify at‐risk individuals who needed referral to the GIFTTS resource. The patient and provider completed the application for voucher assistance. Once completed, the provider ordered genetic testing and CRF evaluated eligibility based on financial need. Once an application is submitted, a voucher to cover the out‐of‐pocket costs associated with obtaining genetic testing was provided. No direct clinical care, genetic counseling, or direct (cash) reimbursement to the patient was provided as part of GIFTSS, although advanced practice nurses with expertise in cancer and genetics were available to facilitate answering questions or identifying resources as needed. Previous research conducted with a subset of participants who took part in GIFTSS had indicated that the program included a diverse group of individuals The objectives of this analysis were to: (i) describe the characteristics of participants from the MA GIFTSS program and (ii) evaluate the types of mutations found in this sample.A secondary analysis of data collected from 2009 to 2014 was completed using de‐identified demographic and genetic testing results obtained from the laboratory source. Partners Healthcare Institutional Review Board reviewed the protocol and determined it exempt. All data were summarized using descriptive statistics (frequency and proportion). Age at the time of genetic testing and cancer diagnosis were reported using median and range. Individuals were categorized based on gender, ancestry (as classified by the referring provider), presence or absence of a cancer diagnosis, timing of genetic testing in relation to a cancer diagnosis , genetic testing results, and presence or absence of a reported family history of cancer. Genetic testing results were defined by three categories APC gene due to risk for Familial Adenomatous Polyposis, which is clinically indicated as standard of care Genetic testing results were available for 927 of 928 participants who took part in the voucher program. Participant characteristics are detailed in Table There were 123 (13%) individuals with gene mutations identified that were considered positive.The family history information of the participants can be found in Table BRCA1, BRCA2, MLH1, MSH2, MSH6, PMS2, EPCAM, APC, MYH, CDKN2A, CDK4, TP53, PTEN, STK11, CDH1, BMPR1A, SMAD4, PALB2, CHEK2, ATM, NBN, BARD1, BRIP1, RAD51C, and RAD51D. Table Participants underwent a variety of cancer genetic tests, including single‐site gene testing for known family mutations, multisite gene testing, multi‐gene panel, and large rearrangement testing. The genes analyzed for the cohort included: The breakdown of mutations by cancer diagnosis is described in Table Here, we report individual‐level genetic findings in an at‐risk cohort of program participants with low‐socioeconomic status in MA. Our findings demonstrate that genetic testing can provide valuable information within this community and to reach equitable genetics care, reducing barriers to accessing genetic testing should be addressed. The findings from this study should be interpreted within the socialecological context of the multiple systems that impact genetic testing uptake, including health system, policy, and community‐level factors BRCA1 and BRCA2, a focus of most research in diverse groups In our sample of individuals at high risk for having a genetic predisposition to cancer who had financial need for assistance to obtain genetic testing, 42% of participants were unaffected with cancer, and of those who were unaffected, 98% had a first‐degree relative (FDR) with cancer. Of those with a cancer diagnosis, the median age of onset was young, age 44. Therefore, our findings indicate that referral to GIFTSS was likely highly selective and that those individuals were likely appropriately referred, though this could not be confirmed. Our cohort's testing included genes other than Single‐site testing for a familial mutation was performed in 15% of our sample. In this subset of patients, 44% tested positive, and were given recommendations for medical management based on their results. For those individuals in the subset who did not have a familial mutation, the emotional and financial benefit of learning of these negative results and not needing additional medical intervention may be beneficial at both the individual and at the larger economic level.In 2006, MA was the first state to enact the HCRA, followed by the National Affordable Care Act (ACA) signed into law 3/23/2010 with most provisions taking place on January 1, 2014. Although universal healthcare is mandatory in the state of MA, it seems clear that the state still has a significant population of underinsured individuals when it comes to genetic testing services. This study included over 900 participants who received services from 2009 to 2014. Updated data from 2016 indicates that over 1600 Massachusetts residents have now received services from the GIFTSS program, clearly demonstrating a need in our community. The ACA has a provision to offer “essential health benefits” for preventive and wellness services, guided by the US preventative Services Task Force. Genetic testing covered under this act includes testing for “BRCA‐related Cancer”. These benefits do not extend to those with a diagnosis of cancer or more rare cancer syndromes.Additionally, laws surrounding health insurance, specifically for those with federal insurance, vary from state to state and often impact the underserved Some private insurers place additional restrictions. For instance, genetic counseling by an approved genetic counselor is required prior to testing. This may limit access in rural or underserved communities where genetic counselors might not be available. Alternative models of providing cancer genetic counseling might be of benefit to at‐risk individuals, such as through telegenetic counseling or video counseling. In a randomized trial, telegenetic counseling has been shown to be noninferior to in‐person counseling, although it did lead to lower rates of genetic testing uptake Furthermore, the results of genetic testing may lead to additional treatment, diagnostic, or prevention recommendations. Co‐payments and deductibles for those services may prove to be prohibitive in pursuing treatment recommendations based on the results of the testing Our study has some limitations that should be noted. First, the accuracy of information entered on laboratory test requisition forms could not be verified. Although the test requisition forms ask for patient characteristics including family history information, it is unclear as to how deliberate these are completed by referring health care providers. Second, we were unable to capture additional socioeconomic information because this was a secondary data analysis. Further, sociodemographic data were limited to what was included on the laboratory case report forms. Therefore, data such as work status, marital status, and other sociodemographic characteristics were not included. Finally, we were unable to identify the number of unique families included in our sample because data were de‐identified and specific mutation information was not available. It is possible that multiple individuals from the same family may have been included which may inflate the mutation rate.The results from this study are useful in describing genetic testing outcomes in this high‐risk underserved community. Future work is needed to evaluate mutation rates in diverse samples to present a more inclusive description of the landscape of hereditary cancer risk in the general population. Continued research efforts should be devoted to promoting access to genetic testing in the high‐risk underserved community.None declared.


To the editors,We are writing in relation to the article ‘An autosomal recessive mutation in SCL24A4 causing enamel hypoplasia in Samoyed and its relationship to breed-wide genetic diversity’ published in Canine Genetics and Epidemiology on 22nd November 2017. Our chief concerns relate to the methodology, namely that: 1) using a small number (33) of microsatellite markers that cover only 66% (25/38) of autosomes is suboptimal for determining genetic variation occurring across the genome; and more seriously 2) the sample of dogs from which “breed-wide genetic diversity” was estimated contained a substantial but undisclosed number of close relatives (and so was not a random sample nor representative of the wider breed), meaning that findings pertaining to genetic variation cannot safely be extrapolated without qualification.Canis familiaris has 38 autosomes, there was no means in this study to determine genetic variation across 1/3 of the genome. It is highly likely that there is genetic variation present within the Samoyed breed on these 13 autosomes, but this study is simply unable to detect its extent. Furthermore, genetic variation at genomic regions on the 25 included autosomes not in linkage disequilibrium with the STRs also cannot be detected. Thus, while this number of STRs may be sufficient for their stated purpose (parentage verification and forensic testing) and an acceptable ‘broad brush’ means of estimating diversity in a population where there is no alternative (such as wild populations), they are unable adequately to describe the extent of genetic variation across the canine genome, including regions of depleted variation due to selection. Also, it is not immediately evident how the cited website (endnote 14) justifies the claim that “this population [of 182 animals] would identify over 95% of existing genetic diversity and heterogeneity in Samoyed based on experience with other breeds”.The study used microsatellite markers to estimate the genetic diversity of the Samoyed breed. While microsatellites have previously been used to this end, they have largely been superseded by dense SNP chips, where the quantity of bi-allelic marker data provides more precise information on the extent of genetic variation via homozygosity. The study used 33 short tandem repeats (STRs) on 25 autosomes, which is an average of 1.32 STRs per autosome included. However, since There is also an important issue regarding sampling of the 182 animals in relation to the inference of genetic variation at the 33 STRs in the wider, global breed. Little detail is given regarding the sampling and the likely bias therein. The authors state that “Samples were solicited through web communications and owners/breeders wishing to submit DNA for testing” and report that the sample comprised 144 dogs from North America, 32 from Europe and 6 from Australia . The preponderance of North American dogs in the sample could imply the sample largely consisted of a  subsection of the wider breed. Furthermore, given the method of sampling it is conceivable, or likely even, that repeat customers may have resulted in several individual breeders submitting samples from multiple, closely related dogs in their kennels or lines. Indeed, the authors state in the results section that “twenty of 168 (12%) healthy dogs were found to be heterologous [sic] for the mutation and most were parents or known close relatives of affected dogs”, thereby revealing that a significant section of the sample did indeed consist of close relatives, which would have an impact on detected genetic variation. However, other than reporting in the abstract that “This population was biased towards close relatives” as a caveat when estimating the population-wide incidence of enamel hypoplasia, the authors provide no further information, such as the degree of relationship among dogs within the unaffected or affected cohorts, which were nevertheless used to determine breed-wide genetic diversity. The authors report that they sought pedigree data and information on relationship to affected dogs, yet provide no evidence of the degree of relationship, as determined by pedigree, of this sample. This is critical to interpretation of the results; the interpretation would be very different if all 182 dogs were part of a large extended family compared to if they were unrelated [as determined from pedigree records] at 5 generations. The authors may point to their internal relatedness (IR) results, with one quarter of Samoyed IR scores between 0.132 and 0.502 putatively indicating a significant degree of parental relatedness, but there is no way of knowing the extent to which this level of relatedness is due to the sampling, as distinct from a reflection of the whole breed. In the conclusion, the authors state that “Samoyed have a lower level of genetic diversity than estimated from prior pedigree or SNP-based studies”, but this finding is to be expected given the inability to detect genome-wide variation in the methods employed and a sample that, by the authors’ own admission, contains a number of closely-related dogs.The authors advise in the paper that “the mutation [for SCL24A4] could be safely eliminated without affecting existing genetic diversity”. Leaving aside the question of whether this paper provides a realistic estimate of genetic diversity, we would caution against the wholesale exclusion of carriers for breeding for two reasons. Firstly, with the availability of a DNA test for the mutation, breeders have the means to ensure that no affected puppy will ever be produced. So long as the mutation is not under indirect positive selection, the mutation frequency in this scenario is expected to remain static . Therefore, it is a sensible course of action to make use of the available DNA tests to retain heterozygotes (carriers) in the breeding pool, at least for the first few generations after the DNA test becomes available, thereby decreasing the possibility of an artificially created genetic bottleneck which may lead to a rapid loss of genetic diversity. Selection against the mutation, by using carriers in a decreasing proportion of matings over the course of a number of generations, may still be applied and would result in a gradual reduction in the mutation frequency. Secondly, there are a number of independent selection objectives  in the Samoyed and most other breeds. There are several DNA tests commercially available to Samoyed breeders, including for degenerative myelopathy, hereditary nephritis, X-linked progressive retinal atrophy and oculo-skeletal dysplasia, as well as recommendations to participate in hip dysplasia screening. Because these objectives are most likely independent in genetic aetiology, identifying suitable breeding animals by excluding all those known to be carriers of any of the identified mutations influencing these disorders and that fall below a particular threshold for hip dysplasia would result in a cumulative effect, leaving a considerably smaller pool of breeding candidates and thus potentially creating a genetic bottleneck. Indeed, with identification of an ever-increasing number of mutations that are either the direct cause of, or are influential on the development of, disease, breeders are being faced with an increasing number of objective traits relating to diseases. Therefore, the focus of future breeding strategies will have to be on compensatory pairings of candidates, since very few individuals will have a clean bill of health for all objectives. Professors Nicholas and Mellersh and Dr. Lewis were concerned about the methodology that led us to conclude that Samoyed lack genetic diversity. They then used these concerns to frame a personal opinion meant to be reassuring to breeders. In doing so, they ignored the major theme of our study, which was to describe a heretofore unrecognized autosomal recessive disorder in Samoyed and the historic and genetic context in which it arose. As veterinarians, we were deeply concerned about identifying health problems of a genetic nature and providing tests to deal with them. We also wanted to make the study a teaching as well as research experience for all breeders.https://www.vgl.ucdavis.edu/services/dog.php. We are confident, therefore, that the genetic diversity we were measuring in Samoyed was accurate as described and that employing large panels of SNPs would not significantly alter the conclusions.Their first criticism involved the use of 33 microsatellite markers across only 25/38 autosomes. This was linked to another question pertaining to why microsatellites were even being used at all, given modern SNP technology. The microsatellites chosen for this study were vigorously selected for their ability to discern genetic differences by the International Society for Animal Genetics, with addition of several new markers from our Veterinary Genetics Laboratory. The microsatellites are known to be highly polymorphic and have been used successfully for many studies concerning parentage and genetic diversity. Some of the added markers were for the DLA class I and II regions, which contains genes concerned with immune responses. This region is in strong linkage disequilibrium, with one copy inherited by descent from each parent. It is extremely difficult to define the DLA region using SNPs due to the numerous polymorphisms, but it is very efficient and accurate to track this region using microsatellites. DLA haplotypes are powerful identifiers of breed founders. We were also concerned about the fact that our markers did not cover every chromosome and added 25 more microsatellites to cover missing chromosomes. We found that the additional microsatellites, although carefully selected, did not add anything to the power of the current 33 markers to study breed-wide genetic diversity and relatedness. We also compared genetic diversity in Standard Poodles by both microsatellites and 170K SNPs and found no major differences. This same microsatellite panel has been used to successfully study genetic diversity in a number of dog breeds and this information can be found on the Veterinary Genetics Laboratory website - The numbers, relatedness, and geographic distribution of Samoyed was questioned, with the implication that we underestimated the genetic diversity in Samoyed compared to earlier pedigree and SNP studies. Although we failed to mention it, more than one hundred of the DNA samples were from Samoyed from around the world submitted to the VGL for other genetic testing and not for the ARAI mutation. One hundred eighty-four Samoyed from around the world is also not a small sampling, at least compared to virtually all other breed studies one might find in the literature. The fact that the 184 Samoyed were genetically similar across the world adds also indicates that most of the existing genetic diversity in the breed was represented in this population.The reviewers cited other studies involving pedigrees and SNPs as evidence that we may have under-estimated genetic diversity in Samoyed. They failed to mention that the conclusions of these studies were the same. The pedigree study of Bell concluded that the breed had a narrow base of founders and that deep pedigrees showed extensive sharing of the same individuals. A pedigree study conducted by the UK Kennel Club estimated that the effective population size for UK Samoyed was 64.7 dogs. Both studies agreed with our conclusion that genetic diversity in the breed was not great, although adequate. The SNP study quoted by Sorsa used the MyDogDNA array containing around 6788 SNPs, but the study only involved 50 Samoyed and the author admitted that the number was too small to make any conclusion other than that diversity appeared adequate. We also concluded that genetic diversity in Samoyed was derived from a small founder population, but that it was adequate. We have limited faith in pedigrees as sole determinants of genetic diversity.The second half of the comments pertained to what should be done when a new genetic disorder is identified in a breed and a test for that mutation provided. We did offer three alternative solutions to breeders regarding autosomal recessive enamel hypoplasia: 1) ignore it, 2) eliminate it, or 3) breed around it. We believe that the professors and Dr. Lewis were saying the same things, although they offer a fourth option, i.e., to quickly reduce the incidence of the mutation by testing to an “acceptable” level and live with it. We described the reasons why each of our three approaches might be selected. If the defect is at very low incidence, the genetic diversity sufficient, and breeders are good about random mate selection, ignoring the mutation is a viable option. The chances of getting affected dogs would be extremely small. However, if there is adequate genetic diversity and the incidence of the defect is low, it might be a good idea to eliminate the trait on the perchance that it might be amplified later by some sort of artificial genetic selection . We provided our best possible scientific evidence that eliminating the mutation in Samoyed could be accomplished without loss of genetic diversity. We do agree with the reviewers that eliminating genetic traits can lead to serious inbreeding in situations where the incidence of the mutation is high and breed-wide genetic diversity low. Such a situation arose for pug dog encephalitis. We identified a region in the DLA that identified carriers of the trait, but when we looked at the incidence of the causative region, over one-third of individuals in the breed were carriers and genetic diversity for the breed was low. Eliminating carriers would seriously reduce existing genetic diversity. Therefore, a recommendation was given to select around the trait by careful mate selection. Fortunately, the trait was recessive, so breeders could select for Normal/Normal or Normal/Carrier puppies. We stand by our conclusion that the ARAI mutation can be safely eliminated from the breed.We agree that the reviewer’s description of the problems that breeders face when having to select against multiple simple and complex genetic traits when given a small number of available dogs, low genetic diversity and geographic limitations. However, the professor’s and Dr. Lewis’ major conclusion that “the focus of future breeding strategies will have to be on compensatory pairings of candidates, since very few individuals will have a clean bill of health for all objectives” is a bit defeatist. It is also dismissive of the research that went into our study and an admission that all breeds are in trouble and the best that can be done is to choose the least objectionable pairings. Since this is precisely what good breeders are already doing, their suggestion is another reassurance from certain geneticists to breeders that “all is right, and nothing needs to change.” We have hopefully shown Samoyed breeders that they have not yet reached a point of great concern but forewarned them that Samoyed around the world come from a limited genetic foundation that needs to be carefully managed. The emergence of ARAI in the breed points to the problems facing many other breeds with small numbers and limited genetic diversity. The fact that Samoyed breeders have retained reasonable health through their breed’s existence is a plus.


Aphrastura spinicauda), a South American bird that breeds along a wide latitudinal gradient. We combine capture‐mark‐recapture data from eight breeding seasons and molecular genetics to compare two peripheral populations with contrasting environments in Chile: Navarino Island, a continuous and low density habitat, and Fray Jorge National Park, a fragmented, densely populated and more stressful environment. Natal dispersal showed no sex bias in Navarino but was female‐biased in the more dense population in Fray Jorge. In the latter, male movements were restricted, and some birds seemed to skip breeding in their first year, suggesting habitat saturation. Breeding dispersal was limited in both populations, with males being more philopatric than females. Spatial genetic autocorrelation analyzes using 13 polymorphic microsatellite loci confirmed the observed dispersal patterns: a fine‐scale genetic structure was only detectable for males in Fray Jorge for distances up to 450 m. Furthermore, two‐dimensional autocorrelation analyzes and estimates of genetic relatedness indicated that related males tended to be spatially clustered in this population. Our study shows evidence for context‐dependent variation in natal dispersal and corresponding local genetic structure in peripheral populations of this bird. It seems likely that the costs of dispersal are higher in the fragmented and higher density environment in Fray Jorge, particularly for males. The observed differences in microgeographic genetic structure for rayaditos might reflect the genetic consequences of population‐specific responses to contrasting environmental pressures near the range limits of its distribution.The distribution of suitable habitat influences natal and breeding dispersal at small spatial scales, resulting in strong microgeographic genetic structure. Although environmental variation can promote interpopulation differences in dispersal behavior and local spatial patterns, the effects of distinct ecological conditions on within‐species variation in dispersal strategies and in fine‐scale genetic structure remain poorly understood. We studied local dispersal and fine‐scale genetic structure in the thorn‐tailed rayadito ( This is typically a consequence of the interaction between environmental heterogeneity and species‐specific life history traits such as dispersal patterns, mating systems, and demography , and detected genetic differences among populations of species that showed high habitat specificity  data and molecular genetics to examine local natal and breeding dispersal and fine‐scale genetic structure in two peripheral populations of a South American forest bird, the thorn‐tailed rayadito The thorn‐tailed rayadito is a secondary cavity nesting bird distributed along an extensive latitudinal gradient  and in forest relicts in Fray Jorge (21 ± 2.6 m between nearest nest boxes). The position of all nest boxes was georeferenced with a 2 m measurement error. The spatial arrangement of the nest boxes was defined after considering previous density estimates of breeding birds  in both localities. Adults were captured inside the nest boxes when feeding 12‐ to 14‐day‐old nestlings using a manually triggered trap  and the distance moved (m) by recaptured individuals , using α = .05 for hypothesis testing. To compare natal and breeding dispersal distances between the sexes in each population we employed Kolmogorov–Smirnov tests  to compare natal/breeding dispersal distances (m). Given that density of breeding pairs, and therefore, territory size, can vary between populations and years, we did not use the distances moved by dispersing birds in these analyzes as they might not be directly comparable. Instead, we transformed distances into territory units Arcese, , using tLog‐linear analyzes were used to test whether the frequency of dispersers and nondispersers was independent from bird sex and population of origin. Because virtually all individuals showed natal dispersal see , this anr = 0; see Table Finally, to test the critical assumption that dispersal patterns were not affected by sex differences in mortality rates or probability of recapture . Given the absence of evident sexual dimorphism in rayaditos  and primer mixes containing four to five primer pairs . Primer concentrations in these mixes were adapted due to differences in amplification efficiency and dye strength  or 28 cycles (mix 3) of 30 s denaturation at 94°C, 90 s annealing at the temperature given in Table ® Size Standard, heat denatured and resolved in POP4 polymer on an ABI™ 3130 Genetic Analyzer . Raw data were analyzed and alleles assigned using the genemapper 4.0 software (Applied Biosystems).Microsatellite amplifications were performed in multiplex PCRs using the Type‐it2.5p > .1), and frequency of null alleles never exceeded 0.05. Details on genetic diversity measures are addressed elsewhere  spatial autocorrelation analyzes and heterogeneity tests were applied to investigate if local spatial genetic structure in each population corresponded to dispersal patterns observed with CMR data; (2) two‐dimensional autocorrelation analyzes (2D LSA) were implemented to explore how spatial genetic autocorrelation was distributed in a two‐dimensional landscape; and (3) Mantel tests Mantel,  of matrin = 63; FJ: 2013, n = 50). Spatial autocorrelation analyzes were conducted in genalex 6.5 , genalex uses pairwise squared genetic and pairwise geographic distance matrices, and then plots r‐values as a function of distance across different distance class intervals . We rejected the null hypothesis of no autocorrelation when both estimates indicated significant nonrandom genetic structure . Although this is a conservative approach, it is highly recommended when sample sizes are relatively small   based on all genotyped individuals for 2010–2015  based on pairwise comparisons between every individual and its n nearest neighbors. Calculation of lr and standard permutation tests  for significance was conducted in genalex as described by Double et al. , but only presented results for 14 nearest neighbors, as such subsets comprised an equivalent linear distance to the distance class size used for spatial autocorrelation analyzes  to assess the significance of correlations between matrices of genetic similarity and geographic distances  or 3 years (n = 2). Based on the distance moved from their natal nest box, all 17 recaptured birds were defined as dispersers. The median distance moved by females  and males  was similar, and there was no sex‐difference in the distribution of traveled distances  and random‐walk models .From a total of 565 fledglings marked in Navarino up to 2014, 17 3%) were recaptured at least once as breeding adults, of which eight were females and nine were males. Twelve individuals were recaptured the year after hatching, the remainder after two (% were ren = 1), two (n = 19), three (n = 8), or four (n = 1) years after hatching. Three males were recaptured in their natal box (nondispersed); all other cases were defined as dispersal events. Females traveled longer median distances  than males , and the distribution of movement distances differed significantly between the sexes ; on the other hand, the random‐walk model showed that females moved significantly longer distances than expected, but male movements were not different from values generated under the null hypothesis .From 491 marked fledglings in Fray Jorge up to 2014, 29 (6%) were recaptured as breeding adults, including 14 females and 15 males. Individuals were recaptured one  than those in Fray Jorge. The upper limit of the 95% CI of the mean territory diameter in Navarino ranged from 63 to 110 m across breeding seasons, while in Fray Jorge it ranged from 29 to 39 m. We also compared natal dispersal distances as territory units (tU). In Navarino, movements of females  and males  were similar, while there was a marked difference between the sexes in Fray Jorge , and therefore, we report descriptive and statistical analyzes incorporating all distances, including those from adults that were recaptured more than once , albeit not different from values taken from a random‐walk distribution .From a total of 210 captured adults in Navarino, we obtained 127 recapture events of 69 individuals between consecutive breeding seasons . The distribution of traveled distances did not differ significantly between the sexes, even though females tended to move farther , but not differing from values generated under the random‐walk model .From the 197 captured adults in Fray Jorge, 162 recaptures of 92 individuals were obtained between consecutive breeding seasons . No difference in the distribution of traveled distances was observed between the sexes  and males  from both populations tended to move little between consecutive breeding seasons, usually not crossing an entire territory but breeding in the same or in the nearest vacant nest box. According to the best supported GLMM, there was no effect of sex or population on breeding dispersal distances, and nearly 50% of the total random variance was attributed to intrinsic differences between individuals  only retained the dispersal status × sex interaction , suggesting that the frequency of breeding dispersal differed between the sexes but not between the two populations  was observed in 61% of all female recaptures and in 72% of male recaptures. The best supported model from the hierarchical log‐linear analysis  and recapture rate . According to this model, there were no sex differences in survival probabilities or recapture rates in each population  than in Navarino . Recapture rates of fledglings were almost equal between the sexes . Despite r‐values above the 95% CI around rp up to 600 m, the 95% CI around r was significantly different from 0 only up to 450 m , while in Fray Jorge males showed a significant structure  up to 150 m .Genetic autocorrelation for increasing distance class sizes for the 2010–2015 dataset  showed that neither of the sexes in Navarino departed from a random distribution of genotypes at any of the assessed distance intervals , and also no sex differences when comparing the whole correlogram . Similarly to Multi Dclass analyzes, correlograms for Fray Jorge suggested no genetic structure for females , but the autocorrelation patterns did not reveal significant sex differences . Analyzes for “snapshot” years confirmed the same patterns as obtained with the whole 2010–2015 dataset (details not shown).Traditional correlograms indicated, again, no detectable genetic structure in Navarino, with correlations for both sexes oscillating between positive and negative values Figure a,b. The lr‐values for only 5% of the 89 females  and for only 1% of the 72 males (p = .047) sampled. The subsets of positively correlated individuals were not geographically clustered, and there were no significant negative lr‐values , 17% of all lr‐values were significant and positive for the 66 males (p = .002–.048), and three small clusters of correlated subsets of males were distinguishable  and males  in Navarino, and for females in Fray Jorge ; however, there was a weak, but significantly positive correlation for males in Fray Jorge .Although Mantel tests are less powerful than autocorrelation analyzes, the observed relationships between pairwise geographic and pairwise genetic distance matrices were consistent with the autocorrelation results. Random permutation tests indicated that correlation coefficients were not different from 0 for females . The combined results from CMR data and population genetic analyzes showed that local natal dispersal and sex‐specific fine‐scale genetic structure differed markedly between the two populations and exhibited congruent patterns. Local breeding dispersal was much less frequent and involved more restricted movements than natal dispersal and did not vary between the two localities.The observed patterns of dispersal corresponded with the analyzes of the genetic structure, although the patterns of natal dispersal should be interpreted cautiously given that recaptures of fledglings were in general low. The limited sample size of recruits, particularly in Navarino, might suggest that the spatial scale of the study and the reported dispersal distances are not entirely representative of the actual natal dispersal distances in this population. This is plausible, as the extensive and continuous forest habitat in Navarino could promote higher rates of long‐distance movements compared to Fray Jorge , nearly all recaptures in Fray Jorge were 2‐ to 3‐year‐old birds (93%), suggesting that both females and males delayed their first breeding attempt in the fragmented and densely populated environment . The median breeding dispersal distances of females and males were shorter than expected by chance (random model), but not significantly different from a random‐walk process, suggesting that adult birds tended to move to the nearest vacant nest box within their territory, or in some instances, to a contiguous territory. Interestingly, individual identity explained almost half of the observed variation in the number of territories traversed by adult rayaditos. This suggests that breeding dispersal is an individually determined trait, which might partly be genetically determined or may be related to phenotypic quality  showed that the population genetic structure corresponded to patterns of natal dispersal in both localities. In contrast, breeding dispersal had no influence on microgeographic genetic patterns, as expected, given the limited and less frequent movements of adults compared to fledglings. In Navarino, the absence of a small‐scale population structure is consistent with our observations suggesting nonrestricted, nearly random natal dispersal in both sexes. Similarly, females in Fray Jorge, who dispersed over larger distances that did not differ from a random pattern, also showed no fine‐scale genetic structure. In contrast, males in Fray Jorge, who showed restricted dispersal within forest patches, indeed showed a clear pattern of isolation by distance (Mantel tests), and a positive genetic structure extending to distances up to 450 m Figure . This diThe 2D LSA confirmed that the positive genetic structure for males in Fray Jorge was the result of a patchy signal , doi:10.5061/dryad.7tp60.The datasets analyzed during the current study are archived in the Dryad Digital Repository ( Click here for additional data file.


Aedes aegypti in Yunnan Province, China, until 2002, but this species is now continuously found in nine cities (or counties). Until now, little was known about the genetic diversity and population structure of this invasive species. Thus, a detailed understanding of the invasion strategies, colonisation and dispersal of this mosquito from a population genetics perspective is urgently needed for controlling and eliminating this disease vector.There was no record of Ae. aegypti communities were analysed by screening nine microsatellite loci from 833 Ae. aegypti mosquitoes sampled from 28 locations in Yunnan Province.The genetic diversity and population structure of P-values less than 0.05, and a bottleneck effect was detected among locations from Ruili and the border areas with the degree of 60% and 50%, respectively. Combined with the F-statistics , the analysis of molecular variance (AMOVA) revealed that there was substantial molecular variation among individuals, accounting for 77.76% of the sample, with a significant P-value (<0.0001). The results suggest that genetic differences in Ae. aegypti originated primarily among individuals rather than among populations. Furthermore, the STRUCTURE and UPGMA cluster analyses showed that Ae. aegypti from the border areas were genetically isolated compared to those from the cities Ruili and Jinghong, consistent with the results of the Mantel test .In total, 114 alleles were obtained, and the average polymorphic information content (PIC) value was 0.672. The value of the alleles per locus ranged from 2.90 to 5.18, with an average of 4.04. The value of He ranged from 0.353 to 0.681, and the value of Ho within populations ranged from 0.401 to 0.689. Of the 28 locations, two showed significant departures from the Hardy-Weinberg equilibrium (HWE) with Ae. aegypti populations’ genetic diversity and different invasion accidents result in the genetic difference among Ae. aegypti populations of Yunnan Province.Continuous invasion contributes to the maintenance of The online version of this article (doi:10.1186/s13071-017-2213-6) contains supplementary material, which is available to authorized users. Aedes mosquitoes. There are approximately 390 million dengue infections per year, and approximately 40% of the world population is at risk of infection from dengue  and the analysis of molecular variance (AMOVA) were performed with Arlequin (version 3.5.2.2). The software STRUCTURE (version 2.3.4) was used to assess the genetic structure differences among populations based on a Bayesian clustering approach with a Markov chain Monte Carlo algorithm . The K value was set from 1 to 31 (the true number of populations plus 3) with 20 runs for each K value [ΔK methods were executed to determine the most likely K value [ST/(1- FST)] and geographic distance [ln (km)], a Mantel test with 10,000 permutations was performed using the ZT software package, and a graphical display of the results was produced with Excel 2016   between all locations of Ae. aegypti. (DOCX 22 kb)


Lutra lutra, from across the United Kingdom possess sex and biogeography-specific odours. Subpopulations with the most distinctive odour profiles are also the most genetically diverse but not the most genetically differentiated. Furthermore, geographic distance between individuals does not explain regional odour differences, refuting other potential explanations such as group odour sharing behaviour. Differences in the language of odours between subpopulations have the potential to affect individual interactions, which could impact reproduction and gene-flow.Across multiple taxa, population structure and dynamics depend on effective signalling between individuals. Among mammals, chemical communication is arguably the most important sense, underpinning mate choice, parental care, territoriality and even disease transmission. There is a growing body of evidence that odours signal genetic information that may confer considerable benefits including inbreeding avoidance and nepotism. To date, however, there has been no clear evidence that odours encode population-level information in wild mammals. Here we demonstrate for the first time the existence of ‘odour dialects’ in genetically distinct mammalian subpopulations across a large geographical scale. We found that otters,  Intraspecific chemical communication therefore affects a plethora of behavioural interactions, and in the context of reproduction is essential for maintenance of animal population structure. As well as signalling key identifiers such as sex and age6, there is evidence that differences in odour may allow genetic differences to be detected at a variety of scales. On a taxonomic scale, there are differences in odours between species (e.g. canids7) and to some extent subspecies (e.g. beavers8), whereas at a much finer scale, there is emerging evidence that within small groups there are odour signals of relatedness and genetic quality, for example, within captive primate groups11, within beaver families12 or between laboratory mice13 and more recently in wild fur seals14. The communication of genetic similarity through odours on this individual scale has been suggested to function in phenotype matching12, mate choice for genetic diversity and MHC genotype11, kin recognition and inbreeding avoidance or nepotism10.Chemical communication, arguably the most important mode of mammalian communication15. Consequently, geographical separation of wild animal populations  results in reduced gene-flow and thus genetic structuring of populations. It remains unclear, however, whether associations between individual genetic relatedness and odour that are found in laboratory and captive populations are also present at the sub-population level, or in wild vertebrates living across large geographical areas. The relationship between population genetic structure and intraspecific odour communication has thus far received little attention, but recent evidence suggests that geographical separation may drive a divergence in chemical signals16. Laboratory based choice experiments provide some evidence that olfactory discrimination could act a mechanism for reproductive isolation and speciation17; differences in chemical signals could therefore impede reproduction between sub-populations. In the case of species of conservation concern, such differences could therefore impede species recovery even where, for example, conservation measures reduce habitat fragmentation. At a higher taxonomic level, chemical signals may provide effective barriers to hybridization18. Olfactory discrimination is therefore potentially fundamental to adaptation and evolution via the maintenance of species boundaries18.Gene-flow among wild populations is affected by geographic features and for many species individuals that are geographically closer are more likely to be related than those further apartLutra lutra) over a large geographic area across England and Wales . Otters possess two anal sacs positioned on either side of the rectum with ducts opening just close to the anus. Secretion from these glands is deposited with faeces (known as spraint) in prominent locations in a way that is typical of scent marking19. It has been assumed that spraint is used to signal territorial boundaries, usage of food resources, to aid navigation or attract mates25. More recently it has been shown that the odour of otter anal gland secretions is significantly associated with individual’s age, sex, reproductive status6 and individual identity26. Genetic sub-structuring in UK otters is known to relate to geographical location, probably as a result of re-colonisation from small and spatially separated remnant populations surviving severe declines in otter numbers across the UK during the 1960s27. Based on genetic data, four major subpopulations in the UK have been described that were significantly differentiated from each other: Wales and Borders (W&B), South-west England (SW), North England (NE) and Central England (CE)  odour profiles would differ between genetically distinct subpopulations, (2) groups with the most distinct odours would also exhibit the highest genetic differentiation, and (3) geographical distance between individuals would not on its own explain odour differences between groups.Here, we measured volatile organic compounds (VOCs) from otter anal glands, tested whether these varied spatially and related these results to population genetic differentiation. Otter anal gland secretions were collected from across four distinct subpopulations in the UKet al.27  between 2004 and 2009, and stored at −20 °C until defrosted for post mortem examination. Only those showing minimal autolysis were selected for the present study, n = 122 . After every 4–6 samples, 0.2 µl of an external hydrocarbon standard (MA EPH Aliphatic Hydrocarbon Standard [Restek] diluted 1:50 with n-hexane) was injected using an automatic liquid injector to check the performance of the GC-MS and for calculation of retention indices. This allowed standardisation of retention times. Compounds were provisionally identified (minimum match factor between the deconvoluted component and the library spectra of 80%) and quantified using Automated Mass Spectral Deconvolution and Identification System (AMDIS) version 2.65 and the NIST Mass Spectral Library Version 2.0 (2005). Both mass spectral data and retention indices were used by AMDIS in identification. Peaks with a retention time below 2 min were not included in the analysis because peaks with retention times close to the hold-up time of the system are not measurable with sufficient accuracy. Since an internal standard was not used, absolute values could not be measured; instead the relative contribution of each peak to the overall scent profile was calculated, that is, the data were normalised. Data were also standardised across compounds to ensure compounds were given equal weight in the analysis, irrespective of their size. Zero values were replaced with half the value of the lowest intensity compound measured in the entire data set.Volatile organic compounds (VOCs) emitted from the secretion of the anal glands were analysed using solid-phase microextraction (SPME) and gas chromatography mass spectrometry (GCMS) (see Kean 28 in R (version 3.3.3)29. Post-hoc tests do not exist for the ‘adonis’ function, so individual models were performed on male and female data. Female reproductive status was controlled for in the female only models. Canonical analysis of principal coordinates using ‘ordiplot’ in the vegan28 and BiodiversityR packages30, was used to create an ordination plot to visualise the VOC profile differences between the sub-populations.Differences in odour profiles between the four subpopulations were tested using Permutational Multivariate Analysis of Variance (PerMANOVA), with a Euclidean distance matrix and 999 permutations. PerMANOVA was used to investigate whether subpopulation explained any variation in the odour data (432 VOCs) while controlling for sex and age . PerMANOVAs were performed using the function ‘adonis’ in the vegan packageST values among subpopulations were previously published27. In addition, we calculated pairwise FST values within each subpopulation between males and females in ARLEQUIN 3.531. Statistical significance was tested with 10,000 permutations as implemented in ARLEQUIN.Pairwise F28 in R (version 3.3.3)29. This tested for correlation between two dissimilarity matrices: geographical location where the otter was found (x and y coordinates) and all odour data (432 VOCs). The Mantel test was based on Pearson product moment correlation with 999 permutations.To test whether subpopulation odour differences were based purely on geographical distances between samples, a Mantel test was performed using the vegan packageThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.6 and comprise a complex mixture of organic acids, their esters, alkanes, alkanols, aldehydes and ketones, aromatic compounds, furanes, and nitrogen and sulphur containing compounds. Marked differences in anal gland VOCs of otters were found between the four genetically distinct subpopulations .The VOCs measured from otter anal gland secretions have already been describedpost hoc comparisons were statistically significant , but this was not the case. All pairwise FST values were significant , or where sexes were examined separately . Our results show that associations between odour and location are not based simply on geographical distance between individuals, but reflect subpopulation genetic differentiation.We found no correlation between odour similarity and spatial distance, either for the dataset as a whole . Higher diversity in NE may also reflect immigration from Scotland, which is reported to have greater genetic diversity than southern UK populations33.The distinctiveness of odours detected among males from CE and females from NE may reflect aspects of their genetic history other than differentiation. The CE and NE otter population clusters had a higher number of unique alleles, and higher allelic diversity compared with SW and W&B subpopulations34). Studies in which a link between genetic and odour differences are inferred from spatial correlation alone, without explicit testing of genetic differences, may therefore be confounded. The anal gland odour of otters, presented here, showed an association with its location of origin, but only in terms of the genetically distinct subpopulation it belongs to. Geographic distances between individual animals are not always relevant to genetic relatedness, for example where barriers to migration (e.g. large roads) or habitat less favourable to movement restrict breeding between spatially adjacent individuals. By testing for both spatial and genetic differences in odour, we support the growing body of evidence35, of associations between odour and genetic diversity and differentiation.Variables other than genetic sub-structuring could account for spatial variation in odours, for example similar diet and habitat could explain an association between odour similarity and spatial proximity. Many group-living species engage in behaviours that promote shared odours to aid group cohesion (e.g. badgers, which simultaneously press together their sub-caudal regions, where glands are located36. Here we provide evidence that genetically distinct subpopulations differ in their odour profile, suggesting that communication between individuals might also be affected by fragmentation. This raises the intriguing possibility that population fragmentation may result in the accumulation of distinct odour profiles in populations, thus adding odour traits to the range of phenotypic characteristics that may diverge under environmental change37. To identify the significance of results presented here, investigation into recognition of odour differences and behavioural responses is needed35. Should avoidance of, or attraction to, unfamiliar odour profiles occur, then there are broad implications for reproduction and gene flow, and thus the recovery of wild animal populations.Previous research has shown that fragmentation of wild animal populations leads to reduced gene flow and in some cases reduced population viabilitySupplementary Table S1.


Research on these components can be framed to target and connect both the theoretical understanding of the evolutionary processes, the practical aspects of conservation, and food and forestry production. The target, main challenges, problems to be faced and key research questions are presented for each component, followed by a roadmap for the consolidation of this proposal as a national initiative.Domestication has been influenced by formal plant breeding since the onset of intensive agriculture and the Green Revolution. Despite providing food security for some regions, intensive agriculture has had substantial detrimental consequences for the environment and does not fulfill smallholder’s needs under most developing countries conditions. Therefore, it is necessary to look for alternative plant production techniques, effective for each environmental, socio-cultural, and economic conditions. This is particularly relevant for countries that are megadiverse and major centers of plant domestication and diversification. In this white paper, a Mexico-centered initiative is proposed, with two main objectives: (1) to study, understand, conserve, and sustainably use the genetic diversity of domesticated plants and their wild relatives, as well as the ongoing evolutionary processes that generate and maintain it; and (2) to strengthen food and forestry production in a socially fair and environmentally friendly way. To fulfill these objectives, the initiative focuses on the source of variability available for domestication ( Species’ domestication is an evolutionary process in which humans, by means of artificial selection, take advantage of the genetic diversity of a wild species and modify it to our needs . The domDomestication was particularly modified by formal plant breeding after World War II, with the onset of intensive agriculture . This tyThese unintended consequences cannot be ignored, especially in developing countries that still hold important remnants of natural ecosystems and native agrobiodiversity. Also, given the diversity of environments and social conditions where agriculture occurs in such ecologically diverse countries, it is highly unlikely that any single agricultural system will solve their problems of food and fiber production . TherefoIn this white paper we describe a Mexico-centered initiative with two objectives: (1) to study, understand and conserve the genetic diversity of native crops and their wild relatives, and preserve the ongoing domestication processes that generate and maintain this diversity; and (2) to use this diversity to strengthen food and forestry production in a socially fair and environmentally friendly way. These objectives relate to biodiversity conservation because the fate of the remaining ecosystems of Earth depends on how we undertake agricultural and forestry production over the following decades ; moreoveThis initiative proposes going back to two core elements of domestication: (1) the genetic diversity of domesticated species, their wild relatives and associated microbiome, and (2) the evolutionary potential that implies having millions of smallholders cultivating extensive areas of diverse crops in different environments. These are core elements for the following reasons.First, genetic diversity provides options to grow diverse and nutritious food with fewer resources, adapted to harsher environments, and making cultivars less susceptible to pests and diseases. Proof of this is that cultivars can already be grown in a wide variety of environments, including marginal conditions where commercial lines do not perform well . Similarcampesinos that keep their own seed and devote part of their production for self-sufficiency. Although they are commonly seen as ‘unproductive,’ they are the backbone of food security  not only as a productive force, but also as an un-substitutable engine for crop evolution under diverse and challenging environments. Crop genetic diversity is not useful by itself: it needs to be related to production practices that can make the most out of the traits given by genetic diversity. The people who use this genetic diversity and possess its associated traditional knowledge are the heirs of the domestication processes that indigenous groups started 1000s of years ago . They tesecurity . Similarsecurity .genetic diversity and functional genomics), the context in which domestication acts (breeding and production) and one of the main challenges it faces . The genetic diversity within crops’ wild relatives, cultivated species, and their associated microbiome is the basis of domestication. Functional genomics represents a second layer of information that allows mapping genetic diversity to useful traits, both in human and environmental terms. Genetic drift, linkage disequilibrium, and epigenetics also play an important role in shaping diversity among populations and within genomes. These types of data can help to understand and monitor domestication and environmental adaptation . Similarly, maize landraces’ distribution and domestication history has been widely analyzed . However, since the 1980s, the programs directed at smallholder agriculture were drastically reduced, or redirected to provide farmers with Green Revolution packages . RemarkaImportantly, smallholder farmers tend to be able to obtain some degree of usable yield in underperforming environments without aid . This has two main implications. First, the productivity gap of many of these farmers could be closed with minor agronomic improvements and breeding, with important consequences. Second, millions of farmers, spread across a wide variety of environments and cultural preferences, represent the ideal scenario for evolution under domestication to continue to occur at the scale and range needed to effectively maintain and generate new genetic diversity.This component aims attending agricultural and forestry production so that they can be increased in a sustainable and sovereign way, while also fulfilling the Mexican needs regarding desired cultivars, quantity, quality, and local cultural preferences. For this, it is crucial to protect smallholders’ production and target it with adequate programs that consider management, markets, and education.Formal plant breeding was introduced into Mexico in replication of the model of the United States. However, in Mexico most production does not use seeds generated by ‘formal’ breeding . This coCommercial lines have not been widely adopted for several motives, one is that the formal breeding lines tend not to be useful to the smallholders’ production systems and environments. This is a consequence of the way breeding is performed and targeted. The environmental conditions characteristic of the areas where the vast majority of smallholders are located are poorly represented by the Mexican public research stations where improved lines have been developed . Also, tGiven the range of conditions under which smallholders conduct agriculture and the limited success of formal breeding over the last 70 years in Mexico, it is unlikely that commercial-type breeding would become a successful strategy. Instead, Mexico should recognize, and incorporate into breeding, the diversity of traditional and local knowledge on shaping and adapting cultivars. For this, public policies should be shifted to better support informal breeding, and to focus formal breeding on the smallholders’ needs and adaptation to local conditions. For this, landraces should be incorporated as the base material of breeding programs, instead of only as donors for elite materials .The aim for this component is to have breeding programs for a range of native species, using alternative tools to accelerate and improve the breeding process, where the objective would be breeding for the smallholders’ needs under present and future, social and environmental conditions. To accomplish this, alternative tools need to be explored, including documenting and sharing campesino-to-campesino experiences, participatory breeding, genomic selection and evolutionary breeding.Mexico’s agriculture and forestry production are facing environmental change in the form of soil degradation, pollution, invasive species and climate change. It is difficult to generalize how environmental change would affect a particular crop or wild species; for instance, the effect of climate change on maize depends on the plant’s genotype, local environment, and management . NonetheResearch on the previous components could target and connect both the theoretical understanding of the evolutionary processes, and the practical aspects of applying this knowledge to conservation and production. However, for this to happen in a National scale, it is necessary to systematize and make data available to both the academy and wider public, and to influence public policy. CONABIO is a Mexican inter-ministerial commission in charge of that type of activities regarding biodiversity. We therefore envision that CONABIO would help to develop the initiative’s in the following early stages:(1)Pilot research projects on genetic diversity of Mexican cultivars and wild relatives, developed by CONABIO and external research groups.(2)An information system developed by CONABIO that allows data on agrobiodiversity and genetic diversity to be analyzed, archived, and made public.(3)Better and more collaboration between research groups, civil organizations and education institutions to accelerate participatory research and the formation of human resources.(4)Implementation of public policy recommendations and participatory research congruent with the Mexican reality and smallholders needs.1. For the cultivated forms, maize is the species with more data available on the distribution of native races and their genetic characterization. What is next needed is to integrate its management practices, uses and environmental and microbiome data, to then make this information available and accessible to farmers, breeders and wider audience. The target of this should be to strengthen seed exchange networks, resources for participatory breeding and campesino-to-campesino experience sharing. Molecular tools would help to accelerate breeding, especially at the stage of crosses design and genetic diversity monitoring. We estimate that with minimal breeding support and agronomic improvements, it would be possible to increase the average yield of 4 million ha from 1.3 to 2.3 ton/ha. This would be enough to cover the maize needs of c.a. 88.5 million people (Examples of the first steps are already ongoing. For instance, in the case of wild relatives, a systematic conservation planning analysis is being performed incorporating both the distribution of genetic diversity and social variablesn people  without AM-Y, MCR, and CB performed literature reviews and contributed to the discussion. AM-Y, DP, FAG, and JS wrote the manuscript. All authors conceived and designed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling Editor declared a shared affiliation, though no other collaboration, with the authors.


Data obtained by genotyping single nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C) levels were utilized in Genetic Risk Score [unweighted (GRS) and weighted (wGRS)] computation on Hungarian general and Roma populations. The selection process of the SNPs as well as the results obtained are published in our research article   Specifications TableValue of the data•Several studies describe the health status of the Roma, which constitutes the largest ethnic minority in Europe however studies focusing on their genetic predisposition to common chronic diseases are scarce.•Genetic background of atherosclerosis among Roma as well as the general Hungarian population can be studied separately or in international cohort.•Genetic risk score assessment can be further utilized to compare susceptibility to reduced HDL-C level among different population groups.1Distribution of SNPs related to HDL-C level were analysed in the Hungarian Roma and general populations and weighted Genetic Risk Scores were defined and used to categorize the population into quintiles.22.1Study involved subjects of samples investigated during recent cross sectional surveys 2.2DNA was isolated using a MagNA Pure LC system  with a MagNA Pure LC DNA Isolation Kit–Large Volume according to the manufacturer's instructions. Extracted DNA was eluted in 200 µl MagNA Pure LC DNA Isolation Kit-Large Volume elution buffer.2.3A systematic literature review on the PubMed, HuGE Navigator and Ensembl databases was conducted to identify SNPs most strongly associated with HDL-C metabolism . The sel2.4Genotyping was performed on a MassARRAY platform  with iPLEX Gold chemistry. Validation, concordance analysis and quality control were conducted by the facility according to their protocols.2.5Two-sided t tests were used to compare the distribution of genetic risk scores in populations. To reveal the association between genetic risk, serum HDL-C level and ethnicity several statistical models were used , Table 6All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.This study was approved by the Ethical Committee of the University of Debrecen, Medical Health Sciences Centre (Reference no. 2462-2006) and by the Ethical Committee of the Hungarian Scientific Council on Health (Reference nos. NKFP/1/0003/2005 and 8907-O/2011-EKU).This article does not contain any studies with animals performed by any of the authors.


Dimerization in signal transduction is a dynamically regulated process and a key regulatory mechanism. Signal transducer and activator of transcription 3 (STAT3) dimerizes after tyrosine phosphorylation upon cytokine stimulation. Because only the STAT3 dimer possesses the trans-activation activity, dimerization is an indispensable process for cytokine signaling. Here we report the detection of dynamic STAT3 dimerization in living cells using the homoFluoppi system. This method allowed us to validate the presence of an intact Src homology 2 domain and STAT3 Tyr705 phosphorylation, which facilitate puncta formation and homodimerization. Puncta formation was reversible, as determined by a decreased punctate signal after washout of oncostatin M. We analyzed STAT3 mutants, which have been reported in patients with hyper IgE syndrome and inflammatory hepatocellular adenoma (IHCA). Analysis of the IHCA mutants using homoFluoppi revealed constitutive activity independent of cytokine stimulation and novel insight into kinetics of dimer dissociation process. Next, we used homoFluoppi to screen for inhibitors of STAT3 dimerization, and identified 3,4-methylenedioxy-β-nitrostyrene as a novel inhibitor. The results of this study show that homoFluoppi is a useful research tool for the analysis of proteins like STAT3 that dynamically dimerize, and is applicable for the screening of dimerization modulators. Therefore, protein dimerization seems to be an essential mechanism underlying the diverse functions of a limited number of proteins. More importantly, dimerization is a decision point in signal transduction, so dimerization events must be tightly regulated1. Excessive and prolonged dimer formation causes problems in cell signaling, which can lead to disease. Thus, analyzing the relationship between mutations in the dimerization motifs of signal transduction molecules and pathogenesis may result in novel therapeutic strategies. Because there are some known causal relationships between aberrant protein dimerization and pathogenesis2, investigations of inhibitors or modulators of protein dimerization have garnered attention as potential therapeutic agents4.The dimerization of many proteins such as transcription factors or G protein-coupled receptors is an important regulatory mechanism governing cell function. For example, heterodimerization is a mechanism that gives rise to functional diversity. Homodimerization gives rise to unique functions that monomers do not have7. The STAT family comprises seven members , all of which induce the transcriptional activation of many target genes. STAT proteins are phosphorylated at conserved tyrosine residues by Janus kinases (JAKs) upon receptor binding of cytokines like interleukin 6 (IL-6) or growth factors such as epidermal growth factor (EGF). Each STAT protein has a Src homology 2 (SH2) domain that specifically recognizes phosphorylated tyrosine residues8, leading to homodimerization or heterodimerization followed by STAT translocation into the nucleus. Translocated STAT dimers induce the transcription of target genes. Activation and inactivation of STAT signaling must be tightly regulated, because dysregulation of STAT signaling has been implicated in some pathological conditions9. For example, dysregulated activation of STAT3 has been observed in many types of cancer cells, so STAT3 is expected to be the effective target for anticancer therapy12.The signal transducer and activator of transcription (STAT) family of transcription factors are proteins that transduce signals upon dimerization13. However, STAT3 is also phosphorylated and activated by other kinases, and even some STAT3 mutations are activating14. Therefore, approaches for inhibiting STAT3 homodimerization and modulating its activity have garnered much attention12, as these compounds are expected to have anticancer activity.To date, several approaches have been taken to modulate dysregulated STAT3 activation. For example, STAT3 is activated by JAK-mediated phosphorylation, so inhibition of upstream JAK kinases is a potential way to inhibit STAT3 activation. JAK inhibitors have been tested in clinical trials for the treatment of human tumors16. Some recombinant proteins such as STAT5 are difficult to express as a full-length soluble protein17. In addition, protein dimerization is regulated by proteins that interact transiently or sequentially. Therefore, a method that is suitable for screening in living cells is especially desired.Despite the importance of modulating dimer formation as a potential therapeutic strategy, research methods for analyzing the dynamic dimerization process in normal and disease states, and screening methods for identifying dimerization modulators, especially in living cells, are limited. The conformation of proteins is influenced by changes in the environment such as pH and ionic strength, and also by macromolecular crowding19, and bioluminescence resonance energy transfer (BRET)20 are methods that have been used to detect STAT3 dimerization in living cells. However, it is difficult to detect the dynamic dimerization process by IP assays, as they do not have sufficient throughput. In addition, it is not easy to quantify dimerization by IPs. FRET and BRET assays are difficult and time-consuming for optimizing constructs such as the length of linker sequences. Another method that could be used to detect STAT3 dimerization is the split-green fluorescent protein-based biomolecular fluorescence complementation (BiFC) assay, which is based on formation of a fluorescent complex when two proteins fused to non-fluorescent fragments of a fluorescent protein interact with each other. However, the complex that forms is irreversible, so once the dimer forms it is difficult to dissociate22. Therefore, to overcome these shortcomings, a novel method that enables the detection of homodimerization in living cells easily, quantitatively, and reversibly is strongly desired.Immunoprecipitation (IP), fluorescence resonance energy transfer (FRET)23. In this system, two tags, a Phox and Bem1p tag (PB1-tag) and a tetrameric Azami-Green fluorescent protein tag (AG-tag), are fused to the protein of interest. When the tagged proteins interact, they are immediately crosslinked to form condensed phase separated droplets. The fluorescent protein tags in this droplet are detected as fluorescent puncta in a reversible manner. Although the Fluoppi system is useful for detecting PPIs in living cells26, it was recently extended to allow visualization of protein homodimerization by development of a single fusion construct containing PB1 and mAG1 (homoFluoppi) that is fused to a protein of interest23.Fluorescent protein-protein interaction visualization (Fluoppi) is a system that allows the detection of protein-protein interactions (PPIs) reversibly and quantitatively in living cellsTherefore, in this study, we applied homoFluoppi to detect STAT3 homodimerization in living cells. We validated this novel method by analyzing the regulatory mechanisms underlying STAT3 homodimerization. Then we used homoFluoppi to analyze the effects of STAT3 mutations related to disease. Finally, we conducted high throughput screening (HTS) for inhibitors of STAT3 homodimerization in living cells, and identified 3,4-methylenedioxy-β-nitrostyrene (MNS) as a new dimerization inhibitor.23. There are four ways that STAT3 can be tagged with the two Fluoppi tags  STAT3 in the unstimulated condition  receptor. STAT3 is recruited to phosphorylated gp130 via its SH2 domain, after which it is phosphorylated at a conserved Y705 residue by JAKsion Fig. , and theion Fig. . Westernion Fig. . As expeion Fig. 18. To dener Fig. , and alsner Fig. . Togethe36. To determine whether tyrosine dephosphorylation mechanisms occurred with the STAT3 fusion proteins, we observed puncta formation upon OSM stimulation and after OSM washout. The punctate signal increased and peaked 1 h after OSM washout, and gradually decreased to basal levels by 8 h after washout  family proteins or SHP2 phosphatase negatively regulate activation of STAT3 by JAK inhibition or dephosphorylation of phosphorylated STAT3out Fig. . Westernout Fig. . These r9. Therefore, we used the homoFluoppi system to determine whether these mutations affected STAT3 dimer formation, caused changes in response to cytokine stimulation, or caused a pathological state. Hyper IgE syndrome (HIES) is an immune deficiency syndrome; one cause of this disease is a specific mutation in the STAT3 gene38. To date, a variety of familial STAT3 mutations have been reported38, which are located in a specific domain of STAT3. Mutations located in the DNA-binding and SH2 domains are often observed in patients with Hyper IgE syndrome, so these mutation sites are called hotspots37. Among the hotspot mutations, we selected STAT3 R382W, R382Q, V463del, and V637M mutants to analyze the effect of each mutation on punctate formation using homoFluoppi. All of the Hyper IgE STAT3 mutants tested in this study formed puncta in response to OSM stimulation; however, only the STAT3 V637M mutant located in the SH2 domain showed an impaired response compared with STAT3 WT  to identify compounds that inhibit STAT3 homodimerization in living cells. First, we calculated the Z’-factor of STAT3 homoFluoppi in 384-well plates to assess whether this assay system was compatible with the HTS method. The Z’-factor was above 0.4, indicating that this assay is applicable for HTS  fusion to the C-terminus of STAT3 tended to be phosphorylated, because STAT3-PB1-mAG1 and STAT3-mAG1-PB1 were slightly phosphorylated on Y705 without OSM stimulation Fig. . Cells eTo calculate punctate images, three approaches are available in ArrayScan Spot Detector BioApplication. In all of the three approaches, the PB1-mAG1-STAT3 construct afforded the increased signal intensity in an OSM concentration-dependent manner as shown in Fig. 44. The PB1-mAG1 tag fused to the N-terminus of STAT3 may inhibit interaction of the coiled-coil domain with essential molecules such as importin, which facilitates translocation to the nucleus48.Although PB1-mAG1-STAT3 was the optimal construct for detection of dynamic STAT3 dimerization in living cells, it did not increase transactivation activity, even in the presence of OSM  and loss of homodimerization in STAT3 S611N and F621Vene Fig. . In addiene Fig. . Because41. He et al.56 reported that MNS inhibits NLRP3 inflammasome activation by directly inhibiting NLRP3, and that its inhibitory activity is independent of syk kinase inhibition. STAT3 is reported as an important player in the NLRP3 inflammasome57. Thus, the inhibitory effect of MNS towards STAT3 may involve inhibition of the NLRP3 inflammasome.We developed a screening system to screen for inhibitors of STAT3 homodimerization in living cells using homoFluoppi, and subsequently identified MNS as a STAT3 inhibitor. MNS selectively inhibited STAT3 dimerization in the AlphaScreen assay compared to other SH2 domain-containing proteins (STAT1 and Grb2). Thus, MNS seemed to interact with the STAT3 SH2 domain and have selective inhibitory activity toward STAT3 in the AlphaScreen Fig. . HoweverThe homoFluoppi screening system can also be applied to mutated STAT3. For example, it may be ideal to find compounds that specifically inhibit the STAT3 protein with somatic undesired mutations. In the same way as was done with the STAT3 homodimer, many homodimers can be analyzed by homoFluoppi in living cells, as well as the mechanisms and posttranscriptional modifications underlying homodimer association and dissociation. Thus, homoFluoppi can be used as a research tool for investigating whether specific mutations found in patients affect homodimerization of that molecule. In addition, homoFluoppi can be used to screen potential candidates for drug development.Human embryonic kidney (HEK) 293 cells were grown in the Dulbecco’s modified Eagle medium (DMEM) (Thermo Fisher Scientific) supplemented with 10% FBS. The cells were incubated at 37 °C in a humidified atmosphere containing 5% CO2. Transfection was done with Lipofectamine3000 (Invitrogen). Conditions and protocols were determined according to the manufacturer’s instructions. To establish cell line stably expressing PB1-mAG1-STAT3, transfected cells were cultured for 2 weeks in selection medium containing 500 μg/mL of Geneticin (Gibco). Single cell cloning was done by limiting dilution method. Each single clone was evaluated in the STAT3 homofluoppi system whether they respond to the stimulation.Total cell lysate were prepared using RIPA buffer (Wako) supplemented with protease inhibitor cocktail (Roche Diagnostics). Then total cell lysate were mixed with sample buffer  and boiled at 95 °C for 5 min. Samples were then separated on a 4–20% Mini-PROTEAN TGX Gel (Bio-rad) at 200 V for 35 min. The separated proteins were transferred to a PVDF membrane using an iBlot system (Invitrogen). The membrane was blocked with PVDF Blocking Reagent for Can Get Signal (TOYOBO). The membrane was incubated with primary antibody. Antibody toward Phospho tyrosine 705 of STAT3 , STAT3  and GAPDH  were used. Horseradish peroxidase (HRP) conjugated anti-rabbit IgG (Thermo Fisher Scientific) and anti-mouse IgG (SouthernBiotech) were used as a secondary antibody. Detection was carried out with SuperSignal West Femto Maximum Sensitivity substrate (Thermo scientific). Visualization of images was performed by a LAS1000 imaging system .58. Briefly, these assays were carried out in the buffer containing 10 mM HEPES-NaOH (pH 7.4), 50 mM NaCl, 1 mM EDTA (pH 8.0), 0.1% (w/v) NP-40, and 10 ng/mL (w/v) BSA with 96 well microplate (Coster 3693). Phospho-Tyr (pTyr) peptide probes used in this study were 5-carboxyfluorescein (FITC)-GpYLPQTV for STAT3, FITC-GpYDKPHVL for STAT1, and FITC-PSpYVNVQN for Grb2. Each SH2-containing biotinylated protein  was incubated with a test compound for 15 min. Each protein sample was then incubated for 90 min with its corresponding FITC-pTyr peptide , and mixed with streptavidin-coated donor beads and anti-FITC acceptor beads simultaneously before detection at 570 nm using EnVison Xcite (PerkinElmer).AlphaScreen STAT3, STAT1 or Grb2 binding assays were performed as described in the previous reportFull length human STAT3 (NM_139276) were cloned to homoFluoppi vector. Mutant STAT3 vectors were constructed using KOD -Plus- Mutagenesis Kit  and primers listed in Table Cells transiently or stably express homoFluoppi tag fused STAT3 were seeded in 384-well plate coated with poly D lysine (Corning) using DMEM supplemented with 0.5% (v/v) Fetal bovine serum and cultured for 24 hours to make cells quiescent state. The cells were treated with OSM (Sigma-Aldrich), IL-6 (R&D systems) or IFN alpha (Sigma-Aldrich) for indicated time. For screening of dimerization inhibitor, each compound was applied 30 min before 3 ng/ml OSM stimulation. Then the cells were fixed with 4% paraformaldehyde and stained with 1ng/ml Hoechst 33342. Imaging and Image analysis of the cells were automatically proceeded using an ArrayScan XTI HCS Reader (Thermo Fisher Scientific). Filter set for the blue fluorescent (Hoechst 33342–labeled nuclei) and green fluorescent (PB1-mAG1-STAT3) were used. Images were obtained for 9 fields per well. Spot Detector BioApplication was used for the analysis after optimising manufacture’s settings. In Spot Detector BioApplication, Hoechst-labeled nuclear images were used to identify individual cells and region of interest (ROI) to find puncta. Green fluorescent puncta were identified, then total spot fluorescent intensities, spot area and number of spot within the images were analyzed automatically. To compare the different well, the total spot fluorescent intensity, spot area and number of spot was divided by the number of fluorescent cells in the images. Spot fluorescent intensities per each cell were used as an index of dimer formation and applied for the calculation of inhibitory effect of test compounds.50 value was calculated by Graph pad prism 5.0. The Z’ factor was calculated using the equation Z’ = 1–(3xSD_OSM + 3xSD_DMSO)/.In compound screening, signals for the wells treated with OSM and DMSO were represented as 0% and 100% inhibition, respectively. The ICCignal Reporter Assay Kits (Qiagen) and Dual-Glo™ Luciferase Assay System (promega) were used to evaluate STAT3 dependent transactivation activity. STAT3 expression vectors or control vectors were transfected to HEK 293 cells with reporter plasmids. 24 hours after transfection, cells were plated on 384-well plate using DMEM supplemented with 0.5% (v/v) fetal bovine serum. 24 hours after plating, cells were treated with OSM for 4 hours. Then, the Dual-Glo® Luciferase Reagent was applied to each well and incubated for 20 min at room temperature. The luciferase signals from firefly luciferase were detected by EnVision (Perkinekmer). After 5 min, Dual-Glo® Stop & Glo® Reagent was added to each well and incubated for 20 min at room temperature. The luciferase signals from Renilla luciferase were detected by EnVision (Perkinekmer). The relative signal intensity was calculated by dividing reporter signalThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.Supplementary figures


Euterpe edulis Mart (Arecaceae), a palm tree considered a keystone resource for many vertebrate species. This study was carried out in nine forest remnants in the Atlantic Forest, northeastern Brazil, located in landscapes within a gradient of forest cover (19–83%). We collected leaves of 246 adults and 271 seedlings and performed genotyping using microsatellite markers. Our results showed that the palm populations had low spatial genetic structure, indicating that forest reduction did not influence this genetic parameter for neither seedlings nor adults. However, forest loss decreased the gene flow distance, which may negatively affect the genetic diversity of future generations by increasing the risk of local extinction of this keystone palm. For efficient strategies of genetic variability conservation and maintenance of gene flow in E. edulis, we recommend the maintenance of landscapes with intermediary to high levels of forest cover, that is, forest cover above 40%.Habitat loss represents one of the main threats to tropical forests, which have reached extremely high rates of species extinction. Forest loss negatively impacts biodiversity, affecting ecological  and genetic  processes. Therefore, understanding how deforestation influences genetic resources is strategic for conservation. Our aim was to empirically evaluate the effects of landscape‐scale forest reduction on the spatial genetic structure and gene flow of  Forest loss is the main threat to biodiversity, contributing to the unprecedented levels of the current high rates of species extinction, particularly in tropical regions . The species is widespread throughout the Brazilian Atlantic Forest  Spatial genetic structure is inversely related to the percentage of forest in the landscape for both ontogenetic stages, with a greater effect on seedling populations, reflecting the recent forest loss and fragmentation in the study area; (2) seedling populations in more forested landscapes have fewer assigned parent, reflecting the larger source of pollen and seeds; and (3) landscape‐scale forest reduction negatively influences the gene flow distance, which means that the smallest gene flow distances should be found in more deforested landscapes.The research was conducted in landscapes of the Atlantic Forest in southern Bahia Fig. , where l2, which included the municipalities of Belmonte, Una, Santa Luzia, Mascote, and Canavieiras.Based on a series of freely available landsat images (1990), we first identified large remaining forest tracts in southern Bahia with similar soil conditions, topography and floristic composition , in addition to rubber and eucalyptus  plantations. However, to estimate forest cover in this study, we considered only the amount of native forest in the landscape, excluding other vegetation classes.This final map was used to identify and visually quantify different categories of land use at the scale of 1:10,000. The forest cover includes not only native forests at different successional stages, but also shade cocoa plantations  pentaload II, composed of loci EE43, EE45, EE48, EE54, and EE9; and (3) triload composed of loci EE47, EE59, and EE63. Fragment size was estimated with the software GeneMarker version 2.2 .DNA extraction from E. edulis seedlings and adults was estimated separately through the kinship coefficient average  the probability of a landscape containing at least one seedling with a parent assigned, as well as with a parent assigned in the same landscape and in another landscape; (2) the proportion of seedlings with assigned parents and that of seedlings with assigned parents in the same landscape and in another landscape; and (3) gene flow distance. For the first analyses, we used generalized linear models (GLMs) with a binomial distribution and using the presence (1) or absence (0) of seedlings with assigned parents  as response variables. For the second analyses, we also used GLMs with a binomial distribution, using the proportion of seedlings with parents assigned in each landscape as response variable and the total number of seedlings as weights to give greater importance to the landscapes that had more seedlings. For the third analyses, we used only the seedlings with assigned parents and applied linear mixed‐effect models (LMMs) between the logarithm of gene flow distance and forest cover, using the landscape identity as a random variable. The logarithms were used to reduce the dispersion of the data.R2 value; (3) randomly assigning a forest cover (from any of the nine landscapes sampled) to each landscape; (4) performing a linear regression on the randomized data set; and (5) calculating its R2. Significance was calculated as the proportion of randomized R2 values that were equal to or greater than the observed R2. We did not use mixed models in these randomizations because the nonindependence between seedlings located in the same landscape was accounted for by the randomization scheme. In both analyses, we used a total of 4999 randomizations and included the observed deviation in the comparison because it is one of the possible combinations under the null model (Manly https://github.com/pdodonov/MonteCaRlo>).For each analysis, we calculated significance of the relationship with forest cover in two ways: parametrically, using z‐ratio tests based on the normal distribution for the generalized linear models and t‐ratio tests for the linear mixed models and using Monte Carlo randomizations. For the GLM randomizations, we (1) extracted the deviance of the observed relation between the response variable and habitat cover; (2) randomized the relation between the two variables; (3) performed a GLM on the randomized data set; and (4) extracted the deviance of this GLM. Significance was calculated as the proportion of deviance values in the randomized data set that were equal to or smaller than the observed deviance. When the proportion of seedlings was the response variable, we kept the total number of seedlings associated to each proportion in the randomizations. We assessed the significance of the relation between gene flow and forest cover by (1) performing a simple linear regression between gene flow and forest cover; (2) extracting its el Manly . We perfel Manly , with thel Manly  for the E. edulis seedlings and adults . The spatial genetic structure of E. edulis populations showed low values of average relatedness coefficient (Fij) on both ontogenetic stages and they were not related to distance class  observed (0.0138) coincides with the minimum and maximum values of the confidence interval. The seedlings' average spatial genetic structure value is low (0.001), but significantly higher (P = 0.034) than the adults' average value (−0.003).Landscape‐scale forest loss did not influence the spatial genetic structure of P = 0.34, Monte Carlo P = 0.44; Fig. P = 0.03; Fig. P = 0.12, Monte Carlo P = 0.08). The proportion of seedlings with an assigned showed decreased as forest cover increased  to 21 individuals  of s Andrén , includis Andrén . We emphs et al. , such poE. edulis seedling and adult populations is considered low for plant species with pollen and seed dispersal over long distances  in both ontogenetic stages indicate that individuals are not closely related (low kinship levels)  has short displacement distance , probably an indication of high rates of gene flow.Our data did not allow us to detect whether the observed long‐distance gene flow occurred via pollen or seed. However, considering a previous record of The long‐distance gene flow was recorded only between landscapes with intermediate and high forest coverage (≥43%). This result may reflect the greater richness of frugivorous birds in these landscapes compared with little‐forested landscapes (Morante‐Filho et al. E. edulis genetic analysis, our recommendation for conservation was similar to that reported for other populations of the same species in Southeastern Brazil (Carvalho et al. E. edulis (Keller et al. , a keystone species highly threatened by harvesting and habitat modification.In conclusion, for landscape‐level conservation strategies aimed to maintain micro‐evolutionary processes through gene flow, we recommend avoiding decrease in forest cover below 40%. Based on http://datadryad.org/The authors declare no conflict of interests.