South America is home to one of the most culturally diverse present-day native populations. However, the dispersion pattern, genetic substructure, and demographic complexity within South America are still poorly understood. Based on genome-wide data of 58 native populations, we provide a comprehensive scenario of South American indigenous groups considering the genomic, environmental, and linguistic data. Clear patterns of genetic structure were inferred among the South American natives, presenting at least four primary genetic clusters in the Amazonian and savanna regions and three clusters in the Andes and Pacific coast. We detected a cline of genetic variation along a west-east axis, contradicting a hard Andes-Amazon divide. This longitudinal genetic variation seemed to have been shaped by both serial population bottlenecks and isolation by distance. Results indicated that present-day South American substructures recapitulate ancient macroregional ancestries and western Amazonia groups show genetic evidence of cultural exchanges that led to language replacement in precontact times. Finally, demographic inferences pointed to a higher resilience of the western South American groups regarding population collapses caused by the European invasion and indicated precontact population reductions and demic expansions in South America. Human history in South America began as early as 15,000–14,000 years before the present (BP) . From thPresent-day Amazonians likely have the highest ethnolinguistic diversity of South America , and theCerrado), the Atlantic coast, the Andes, the Pacific coast, and Mexico , and the proportions per individual varied from 0% to 22% (mean 1%) and 0% to 44% (mean 6%) for the African and European ancestry components , respectThese results suggest no hard genetic divide between the Andes and Amazonia or between their putative areas of influence, classified here in western and eastern South America, respectively. Our data set encompassed groups from Bolivia, Colombia, Ecuador, and Peru, representing western South America, whereas eastern South America was represented by groups from Brazil , although some groups are outliers . This result suggests that the genetic variation is more structured in the longitudinal direction, which is a rather unexpected result, as environmental and climatic conditions tend to vary less in this axis, thus facilitating population movement. However, the South American continent might be an exception, considering the amount of environmental and climatic variation in a longitudinal axis from the Pacific to the Atlantic coast, mainly owing to the influence of the Andes on the distribution of climatic conditions. Our results on computed matrices of genetic (estimated as 1 − outgroup F3) and geographic distances (great circle distances) between all pairs of individuals indicated (P ≤ 2.2e–16) that populations more closely located tend to be more genetically similar and are therefore compatible with an isolation-by-distance model. Additional evidence came from the multidimensional scaling (MDS) of individual-based  , also inal-based B and popal-based C genetical-based C. Howeveal-based  to examial-based . We deteFurthermore, the historical relationships among populations inferred with Treemix  broadly We also inferred putative gene flow events using Treemix by fitting an increasing number of gene flow events until a model likelihood plateau was reached with six events  to the northwest boundary between the Amazon forest and the Andes (Kokama) and to the region close to the borders between Brazil, Argentina, and Paraguay (Guaraní), with more than 5,000 km in the maximum expansion range. During the Tupí expansion , the TupF3), in which both Kokama groups were clustered with western Amazonians  presented genetic ancestry profiles much more similar to populations from western Amazonia, especially those from the Loreto region located close to the eastern Andean slopes , rather than to other Tupí-speaking groups, as shown by ADMIXTURE, PCA, and Treemix , and 3. azonians B and C, a groups , as wella groups . This gea groups . MeanwhiThis striking result aligns with a previous hypothesis about the origins of present-day Kokama. According to this interpretation, the Kokama were a non-Tupí-speaking people who went through a process of language replacement due to contact with speakers of Tupí-Guaraní , likely At the other end of the Tupí expansion, on the border among Argentina, Brazil, and Paraguay, are the Guaraní people, currently representing most Tupí speakers, who were divided into three ethnic groups, Kaiowá, Mbyá, and Ñandeva. Previous studies have shown that the Pre-Columbian admixture with Gran Chaco, Mesoamerican, or other related sources probably contributed to the formation of this southern Tupí branch . AccordiWe were likely unable to fit the Guaraní Mbyá into a model, as well as to distinguish a clear best-fitted model for Guaraní Ñandeva, owing to significant contributions from Gran Chaco lineages or other closely related groups not represented in our data set. This admixed origin of Guaraní was first inferred by F4  for every combination of X, Y, and Z Native American test groups  segments present in genomic regions of Native American local ancestry. We adapted the approach used by The results showed a widespread network of IBD sharing formed in the Pre-Columbian period, with a much higher number and intensity of connections among groups within a few main areas , where X is any ancient sample and Y and Z are any present-day Native American group. The complete set of statistics was then summarized as the number of highly significant tests (Z > 4) grouped by pairs of X ancient individuals and Z present-day groups summed over all Y present-day groups  between all pairs of individuals and applied an MDS to the matrix of pairwise genetic distances. The analysis identified the most distinctive groups  and 0.5274 (P = 1.041e−15), whereas the models “lm(Dimension 1 ∼ Latitude)” and “lm(Dimension 2 ∼ Latitude)” exhibited estimated R2 values of 0.2830 (P = 6.855e−08) and 0.2904 (P = 4.348e−08), respectively. Once again suggesting the relationship between genetic variation and geography, especially with the longitudinal distribution.We also analyzed the global pattern of genetic affinities among present-day Native Americans and ancient individuals from across the whole American continent and Siberia. For this, we estimated the genetic distances , enslavement, warfare, disruption of subsistence strategies, and forced displacement from territories, among other processes . To evalMost groups produced FI estimates concentrated at approximately 5–10% and FA estimates less than 500 BP or approximately 18 generations before present  than that of western South Americans, which showed the highest Ne  in the last 100 gBP, whereas Mesoamerica and northern Mexico had values similar to those of western South America ; however, some of them showed a steep decline in Ne, even going below ∼102  (Looking at the inferred effective population size histories of the major ethnolinguistic/geographic groups  represennd Tupí) . Notablynd Tupí) . Howevernd Tupí)  inferredNe of 104 to almost 106. In South America, especially Tupí speakers and the Andean populations presented with an increase of at least two orders of magnitude , thereby partially overlapping with the hypothesized period of the Tupí Expansion, which would have started between 3000 and 2000 BP  thus producing an LD-pruned data set. Next, a supervised clustering analysis was performed with ADMIXTURE  present a missingness rate above 5%, though not exceeding 7%, which were removed. The data set contains a proportion of 10.96% of rare alleles . Following this initial evaluation, the complete data set was pruned to remove markers with a pairwise correlation above 20% , “scatterpie” to plot the pie charts on the map, and “ggrepel” to create labels for each group.Initially, PCA was applied with SNPRelate R/Bioconductor  to the LAs a first step, we analyzed how identity by descent (IBD) blocks are shared between the entire set of pairs of Native American groups and how these connections were distributed along the geographical space, following the same approach used by We only analyzed IBD segments of Native American ancestry, identified in the maximum unrelated subset of individuals, and to secure reliable results we selected blocks with more than 2 cM and with an estimated LOD score above 3 , furtherF3 , as well as the formal test F4 . Both statistics (F3 and F4) were calculated for every pair of Y and Z indigenous groups, and “Test” was iterated over every single indigenous group or individual in the F4 statistics computation. Additionally, a matrix of Outgroup F3  calculated for all Y and Z pairs of groups and pairs of individuals, was converted to genetic distances (Genetic distance = 1 − Outgroup F3 estimate). A MDS analysis was then applied to the matrix of pairwise genetic distances with the “stats” R package.Next, to assess the patterns of allele sharing between indigenous groups and to test prior hypotheses regarding the formation of some specific groups, we first estimated the Outgroup F4 , where X is any ancient sample, and Y and Z are any pair of present-day Native American groups. First, we filtered the highly significant tests (Z > 4) and then the selected set was summarized as the number of significant tests, grouping by pairs of X ancient individuals and Z present-day groups, and summing over all the Y present-day groups. We also estimated the pairwise genetic distance (1 − Outgroup F3 estimate) matrix between all present-day (Native Americans) and ancient (from the American continent and Siberia) individuals and applied an MDS to this matrix using the “stats” R package.To shed light on the local patterns of genetic continuity in the South American continent, first, we wanted to investigate the relative patterns of excess affinity between ancient individuals and each pair of present-day Native American groups, by computing F3 as the measure of genetic distance and the geographical distances were calculated based on the coordinates of every pair of groups as great circle distances with the R package “geosphere.” We then applied a linear regression model (R “stats” package) to the matrices of genetic and geographical distance of all 87 indigenous individuals from the unadmixed-unrelated data set. Finally, we looked at the relationship between continental ancestry components  and Latitude/Longitude, and also between the estimated principal components and the latter, by fitting linear regression models.Furthermore, we wanted to investigate if and how much the genetic diversity of indigenous populations was influenced by their geographic distances. We used the 1 − Outgroup First, we aimed to produce an outline of the population history of the Native American groups here represented, therefore providing subsidies, along with other lines of evidence from archeology and linguistics, for a framework to model how these groups relate to each other and for how their population history unfolded. This was initially explored with Treemix program , which uZ|) as candidates to represent the population history.Second, we used the qpGraph (v.6450) from Admixtools  to modelNext, we modeled the test groups in all possible placements along the scaffold branches, both as one-way models assuming a single origin of the tested group or as two-way models assuming a mixed origin. When both models (single and admixed origin) presented a good fit, we gave preference to the single-origin model (one-way), as it is the more parsimonious scenario. However, if among the multiple models there was no one-way with a good fit, we used the criteria of the lowest maximum Z score among all two-way models and the number of outliers as a proxy to decide which is the best candidate model to explain the genetic patterns observed. In search of the best fit, we tested one group at a time , placing the test group in all terminal positions.N ≥ 5) and to avoid the confounding effect of consanguinity. ASCEND infers the age and intensity of founder events (or bottlenecks in this case) as parameters of a model based on the empirical curve of exponential decay of allele sharing correlation between pairs of individuals inside the same population as a function of the genetic distance. The cross-population correlation with an outgroup is subtracted from this intra-population correlation to exclude the effect of ancestral allele sharing. A random sample of 15 individuals from the complete data set was used as the outgroup population as in We then used the ASCEND software  to inferWe also analyzed the IBD segments identified as described previously in the section “Patterns of Shared Ancestry”, first by selecting segments shared between individuals from the same population  and present in genomic regions of Native American ancestry as inferred with RFMix , and secNe history also based on the inferred IBD segments (section “Patterns of Shared Ancestry”), but first, we selected those located inside the blocks of Native American ancestry identified through a Local Ancestry Inference conducted with RFMix , and 4) SNPs with more than 10% of missing values. The resulting set of markers is composed of 251,940 autosomal SNPs.Finally, we combined the unadmixed set of Native Americans, with a data set containing information from 952 individuals from worldwide populations from the Human Genome Diversity Project (HGDP)  and SimoFROH averages were estimated from the individual values. Last, the FROH estimates were compared with the geographic position of these groups, by assessing the correlation between the FROH estimates for each group with their Longitude and Latitude.Next, the ROH identification was performed with PLINK v1.9 , using aMolecular Biology and Evolution online.msab339_Supplementary_DataClick here for additional data file.


Mezenskaya horse (Mezenka) is Russia’s aboriginal breed. It is a domestic selection in the northern territories of Arkhangelsk region. The breed is perfectly adapted to the conditions of the Far North, and has a numberof valuable economic and biological qualities. At present, it has a limited gene pool and is bred only in the Mezensky district, where one gene pool-breeding farm is operating and so is a number of basic farms, where selectionand breeding activities take place with the breed. Due to a small population of Mezen horses, the challenge ofpreserving its intra-breed diversity is very urgent. To determine the degree of genetic variability in the Mezenpopulation, the alleles-fond was monitored. A comparative analysis of the genetic structure of the breed wasdone on DNA microsatellites at time-intervals of 10 years . Crista samples of 198 horses werestudied in specialized laboratories. It was established that the breed has wide genetic diversity in 17 loci of nuclearDNA. The population’s alleles-fond includes from 128, 139, and 133 alleles respectively . The most common alleles are AHT4O, AHT5N, ASB2K, ASB23S, CA425N, HMS1J,HMS1M, HMS2H, HMS3M, HMS7L, HTG4M, HTG6O, HTG7K, HTG7O and LEX3M. Mezen horses revealed 6 rare, lowfrequency (0.004–0.056) alleles not found in the horse populations of domestic selection. The average value of thepolymorphic level (Ae) in the breed over the years is 4.16, 4.21 and 4.06, respectively. The highest polymorphismis found in locus ASB17 (6.49–6.90–6.76); the lowest, in locus HTG6 (1.71–1.66–1.67) and HMS7 (1.77–1.95–1.77).A slight deficit of heterozygous genotypes (Fis = 0.003) was observed in Mezen horses in 2010. In 2000 and 2020,the observed heterozygosity (Ho) exceeds the expected value (He), which indicates the absence of intra-population inbreeding . The results obtained testify to the effectiveness of breeding activities carried out to preserve, improve and maintain genetic diversity in the population. Presently, considerable attention is paid to the preservation of biological diversity, as the “creative effort” of humans has brought many animal species onto the brink ofextinction. Populations of local breeds that bear in theirgenome valuable qualities adapting them to the conditions of the area where they had been developed havereduced significantly. The main cause for the decline ofpopulations and extinction of aboriginal breeds is theirinability to compete with modern farm breeds and globalbreeds in terms of productivity . The depletionof genetic resources leads to dramatic changes in the genepool and, above all, to reduction of genetic variability.Investigation of genetic characteristics of several localhorse breeds in Russia demonstrates that at the presentstage of their development these breeds have high levelsof genetic diversity and allele pools characteristic of thebreeds. For instance, 145 alleles for 17 microsatelliteDNA loci were identified in the genotypes of horsesof the Yakut breed, that is, 8.53 alleles per locus on theaverage . The population of Kyrgyz horses has a vast set of alleles, 135 . In Bashkir horses, 130 alleles, or 9.29 alleles perlocus, were identified in 14 short tandem repeat (STR)loci . The population of TransBaikal horses has high genetic diversity indices. With116 alleles in 14 satellite DNA loci, the level of polymorphism (Ae) of the breed amounts to 5.29, and theobserved heterozygosity (Ho) amounts to 0.786 . Acharacteristic feature of aboriginalhorse breeds is that their genotypes bear rare and uniquealleles not found in farm breeds. Unique alleles wereidentified in the Buryat, Khakassian , Trans-Baikal , Altai,Bashkir, Yakut , and Tuvan  horse breeds.The Mezen horse (Mezenka) is one of the local Russian breeds. The area of its origin and present distribution is the Mezensky district, situated in the northeast ofArkhangelsk Oblast. The breed was developed by localinhabitants, and it was perfectly adapted to the harshconditions of the Far North during its historical formation. The Mezen horse is easy to keep, feed, and manage.It shows good disease resistance, retains its nutritionalstatus in winter, has universal working abilities, and canwalk through deep snow and sticky clayey soil. In the17–19 centuries, Mezen horses were widespread in theArkhangelsk region. The mechanization of agricultureand termination of the state support of horse breeding inthe second half of the 20th century led to a decline in thepopulations of native horse breeds in Russia, includingthe Mezen horse breed. By the early 1990s, the breedwas preserved only in the Mezensky district. At present, the population of Mezen horses has alimited gene pool; it is an intrabreeding population ofsmall size (187 mares as of 01.01.2020). According tothe classification of breeds by the degree of risk presented in the Food and Agriculture Organization of theUnited Nations (FAO) report of 2015, it is included inthe “critical status” category  .Activities on the restoration and preservation of thegenetic diversity of the Mezen horse breed have beenconducted since 1993. A specialized breeding farm hasbeen operating in the region since 1994, and its mainaim is to preserve the intrabreed diversity of the population. The stallions and the mares at the farm includerepresentatives of the breed from various communities ofthe Mezensky district, characterized by a certain geneticpattern. Important stages of breeding are the exchangeof breeding material among the farms raising Mezenhorses and the identification of new genetic resources ofthe breed. The assessment of the genetic situation in thepopulation conducted earlier on the base of polymorphicproteins and blood types revealed the presence of considerable intrabreed diversity . However, over the past twentyyears, the number of farms and horses in the Mezenskydistrict decreased significantly, and therefore breedingactivities engage a small number of stallions and mares. With the increasing likelihood of inbreeding, it may leadto the loss of individual genes and decrease in geneticvariability in the breed.The aim of this study was to monitor the genetic structure of the Mezen horse breed by microsatellite DNAloci and to assess the genetic diversity of the population.The material for the study comprised genetic certificates with test results for 17 microsatellite DNA locifrom Mezen breed horses. Only data for the animalsincluded in the breed at the beginning of 2000 (n = 62),2010 (n = 163), and 2020 (n = 143) were processed.DNA samples obtained from the biological material ofhorses were genotyped at the Laboratory of Genetics ofthe All-Russia Research Institute of Horse Breeding andat the Molecular Certification Laboratory of the Gordizcompany in 2007–2019. DNA was isolated from hair follicles with Diatom™ DNA Prep, ExtraGene™ DNA Prep, and COrDISSPRINT kits .The samples were analyzed by PCR with multiplexkits for genotyping horses from the Stock Marks andCOrDIS Reindeer companies for 17 microsatellite loci:VHL20, HTG4, AHT4, HMS7, HTG6, AHT5, HMS6,ASB23, ASB2, HTG10, HTG7, HMS3, HMS2, ASB17,LEX3, HMS1, and CA425 .PCR was carried out in a 2720 Thermal Cycler. The amplificates were resolved by capillary electrophoresis in anABI 3130 automatic genetic analyzer (Applied Biosystems). The results were identified using a standard DNAprofile and data from international comparison tests(Horse Comparison Tests) .The genetic analysis of the population was performed as in . The followingindicators were calculated: frequencies of alleles andgenotypes, polymorphism level (Ae), expected (He)and observed (Ho) heterozygosity levels, and fixationindex (Fis). Statistical analysis was conducted on aPENTIUM-MMX-166 PC with Excel 7.0 software.The time variation of the Mezen horse genetic structuretraced by 17 microsatellite DNA loci demonstrates itsbroad allelic diversity. In 2000, 128 alleles were identified in the Mezen horses. The horses included in thisresearch were born in six communities of the Mezendistrict, and they had a certain set of alleles in theirgenotypes. A more than twofold increase in the numberof examined horses and expansion of their range of originto 11 communities permitted us to identify 139 alleles in2010. The new alleles were identified with frequenciesof occurrence from 0.003 to 0.031. In 2020, 133 alleleswere identified in the examined horses. The number ofalleles decreased over the past decade due to the disappearance of rare (p < 0.05) variants from the population:AHT4L and AHT4N, ASB23Q and ASB23R, CA425O,HMS2Y, HMS3N, and HTG6P. At the same time, in2020, two new alleles (HTG6G and HTG10T ) werediscovered; they were absent from the horses examinedin the first two rounds of the study. The alleles identifiedin the Mezen breed are shown in Table 1As for the loci, the minimum number of alleles wasdetected at HTG6 and HTG7 , the maximum number was at theASB17 locus . The numbers of identified allelesper locus averaged over each year were 7.53, 8.18, and7.82, respectively.The commonest alleles in the breed are AHT4O,AHT5N, ASB2K, ASB23S, CA425N, HMS1J, HMS1M,HMS2H, HMS3M, HMS3R, HTG4M, HTG7K, HTG7O,LEX3M, and VHL20N. The frequencies of their occurrence range from 0.258 to 0.569. More than 70 % inthe structure of their loci is made up by the HMS7L andHTG6O alleles. The frequencies of rare alleles in the population vary from 0.003 to 0.048. Low frequencies(0.003–0.041) are characteristic of six unique allelesfound in the Mezen genotype that had not been detectedin other domestic horse breeds .In all the analyzed years, the allele pool of Mezen horsescontained unique alleles ASB17X and LEX3S. In 2000and 2010, the HMS2Y allele was detected, and in 2010and 2020, alleles ASB2U, ASB23N, and LEX3RComparative analysis of the genetic structure ofMezen horses over the time span of the study revealedsignificant ( p < 0.001) differences in the frequency ofoccurrence of individual allelic variants. New allelesappeared at several loci; as a result, allele frequenciesincreased or decreased. In particular, alleles AHT5J,ASB17K, CA425I, CA425M, HMS1L, HMS6K, andHTG10O, identified in 2000 at frequencies 0.121–0.213,were 1.2 times less frequent in the population in 2010 and1.5 to 2.2 times less frequent in 2020. Inversely, allelesAHT5K, ASB2M, ASB17R, ASB23I, CA425L, CA425N,HMS1J, HMS3M, and HTG10I at the second and thethird steps of the study occurred at frequencies higherthan at the first step by factors 1.1–1.2 and 1.3–1.5,respectively. Over twenty years, the frequencies of thetypical HTG7O (38.0 to 49.0 %) and HMS3M (27.5 to38.7 %) alleles increased significantly, while the frequencies of HTG7K and LEX3M decreased by 9.6 and13.6 %, respectively.A significant difference (p < 0.05) between the examined groups was also noted in the number of genotypes. In 2000, 278 variants were tested at17 microsatellite DNA loci in the Mezen horses, thenumbers of which in the loci varied from 6 (HTG6 )to 30 (ASB17 ). By 2010, the number of genotypes increased to 387. The number of genotypes identified in2020 was 345. At the same time, the analyzed population lacked 44 variants present in the horses examinedin 2000, but 111 new ones were discovered. The mostsignificant increase over the past 20 years was noted inloci HTG10 (from 20 to 29), ASB17 (from 30 to 46), andLEX3 (from 8 to 27).The conducted genetic analysis of the populationdemonstrated that due to the wide genetic diversity inthe population of the Mezen horses the level of polymorphism, characterizing the number of effective alleles,remained high throughout the study (Table 2).The maximum number of effective alleles (Ae) overyears was observed in the highly polymorphic locusASB17 , in which homozygousgenotypes constituted 11.3 to 16.7 %. In loci HTG6 andHMS7, alleles O (0.742–0.754) and L (0.697–0.738),respectively, were predominant, thus accounting for theirlow polymorphism (1.66–1.95). Since the homozygousgenotypes HTG6OO and HMS7LL dominate in these lociwith frequencies above 50 %, their levels of observedheterozygosity (Ho) were low, 37.4 to 47.5 %, respectively. In other loci, the levels of polymorphism in 2000varied from 2.53 (LEX3) to 5.43 (HMS6 ); in 2010, from2.96 (HTG7) to 5.29 (HMS6 ); and in 2020, from 2.74(HTG7 ) to 5.49 (HMS2); the observed heterozygosityvarying from 57.1 to 88.7 %.Generally, heterozygous genotypes prevailed in thepopulation in 2000. This was proven by the value ofobserved heterozygosity (0.734), which was higher thanthe predicted level (0.724), and the negative value of thefixation index (Fis = –0.014). This indicator demonstrated the presence of genetic balance in the breed and theabsence of intrapopulation inbreeding. Aslightly reducedvalue of heterozygotes (Fis = 0.003) was observed inthe Mezen horses in 2010. In this study, the actual heterozygosity at loci ASB23 and HTG7 corresponded tothe predicted value, and at several loci , the predictedheterozygosity was higher than the observed one. By2020, the genetic balance in the population was restored.This was confirmed by the negative values of fixationindex at most loci and on the average over the breed(Fis = –0.011). The predominance of heterozygous genotypes proved the effectiveness of the breeding activities aimed at the preservation and maintenance of geneticdiversity in the breed. Molecular tracing of the time variation of the Mezenhorse allele pool at DNA microsatellite loci shows thatthe breed, like other local horse breeds, has a high levelof allelic diversity in most of the loci tested and a widegenetic variability. The population has its specific geneticprofile, which differs from some other local breeds  . Thus,the genetic structure of the Mezen horse breed doesnot include the AHT4L, AHT4P, ASB17Q, HMS7K, orHTG6G alleles, which are found in the genotypes ofthe Trans-Baikal , Kalmyk, Yakut , and Bashkir  horse breeds.The AHT5M, HTG7M, and HTG10L alleles ( p < 0.05),rare in the Mezen horse breed, are characteristic of thementioned populations. Conversely, the CA425L allele,widespread in the Mezen breed (frequency 0.214),was designated as rare in the Yakut horse breed andwas not detected in Bashkir horses. The ASB23Q andHTG10T alleles, which are present at low frequenciesin the Mezen population, are observed only in thegenetic structure of Bashkir horses, and the ASB17Yallele occurs in the Yakut horse breed. The AHT5H,ASB17X, HMS2Y, HMS6J, LEX3R, and LEX3S alleleswere detected only in the Mezen horse breed.At present, agricultural enterprises of the Mezenskydistrict have stallions and mares with rare allelic variantsof microsatellite DNA. Some of them have two to fiverare alleles in their genotypes. The replication of thesealleles through their carriers and identification of newgenetic resources in the region will allow not only thepreservation but also the expansion of genetic diversityin the small population of the Mezen horse breed.Monitoring of the genetic structure of the Mezen horsebreed revealed certain changes in the numbers of allelesand their combinations in the allele pool, as well as inthe frequencies of their occurrence. The breed has a highlevel of allele variability and a certain genetic profile forDNA microsatellites, which is an important factor inmaintaining the gene pool in a small population.The authors declare no conflict of interest.Altukhov Y.P. (Ed.). Dynamics of Gene Pools in Populations Exposed to Anthropogenic Effects. Moscow: Nauka Publ., 2004.(in Russian)Avon Laurent. La conservation des ressources genetigues bovinesen France: les causes d’amoindrissement. 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(in Bulgarian)Moiseeva I.G., Ukhanov S.V., Stolpovsky Yu.A., Sulimova G.E.,Kashtanov S.N. Gene Pools of Farm Animals. Moscow: NaukaPubl., 2006. (in Russian)Simon D.l., Schulte-Coerne H. Verlust genetischer Alternativer inder Tierzucht – notwendige Konseguenzen. Zuchtungskunde.1979;51(5):332-342.Stolpovskiy Yu., Zakharov-Gezekhus I. The problem of conservation of gene pools of domesticated animals. Vavilovskii ZhurnalGenetiki i Selektsii=Vavilov Journal of Genetics and Breeding.2017;21(4):477-486. DOI 10.18699/VJ17.266. (in Russian)van de Goor L.H.P., Panneman H., van Haeringen W.A. A proposal for standardization in forensic equine DNA typing: allele nomenclature for 17 equine-specific STR loci. Anim. Genetics. 2010;41(2):122-127. DOI 10.1111/j.1365-2052.2009.01975.x.Yuryeva I.B., Svishcheva G.R., Vdovina N.V., Khrabrova L.A.,Stolpovsky Yu.A. Genetic diversity of the Mezenskaya horsebreed  revealed by microsatellite DNA.Genetika = Genetics. 2018;54(13):64-69. DOI 10.1134/S0016675818130210. (in Russian)Yuryeva I., Vdovina N., Domozhirov V. Immunogenetic control inthe Mezen horse population. Zootekhniya = Zootechnics. 2005;8:8-10. (in Russian)


We previously showed that zinc (Zn) deficiency affects the STAT3 signaling pathway in part through redox-regulated mechanisms. Given that STAT3 is central to the process of astrogliogenesis, this study investigated the consequences of maternal marginal Zn deficiency on the developmental timing and key mechanisms of STAT3 activation, and its consequences on astrogliogenesis in the offspring. This work characterized the temporal profile of cortical STAT3 activation from the mid embryonic stage up to young adulthood in the offspring from dams fed a marginal Zn deficient diet (MZD) throughout gestation and until postnatal day (P) 2. All rats were fed a Zn sufficient diet (control) from P2 until P56. Maternal zinc deficiency disrupted cortical STAT3 activation at E19 and P2. This was accompanied by altered activation of JAK2 kinase due to changes in PTP1B phosphatase activity. The underlying mechanisms mediating the adverse impact of a decreased Zn availability on STAT3 activation in the offspring brain include: (i) impaired PTP1B degradation via the ubiquitin/proteasome pathway; (ii) tubulin oxidation, associated decreased interactions with STAT3 and consequent impaired nuclear translocation; and (iii) decreased nuclear STAT3 acetylation. Zn deficiency-associated decreased STAT3 activation adversely impacted astrogliogenesis, leading to a lower astrocyte number in the early postnatal and adult brain cortex. Thus, a decreased availability of Zn during early development can have a major and irreversible adverse effect on astrogliogenesis, in part via multistep alterations in the STAT3 pathway.  •Maternal zinc deficiency disrupts offspring's brain cortical STAT3 activation.•Impaired PTP1B proteasomal degradation inhibits JAK/STAT3 activation.•Tubulin oxidation and decreased interactions with STAT3 can affect STAT3's nuclear localization.•Zinc deficiency impairs STAT3 acetylation.•Altered STAT3 activation leads to astrogliogenesis disruption which extends into adulthood. BMPbone morphogenetic proteinCcontrol (zinc sufficient diet)CTcortical tissueCT-1cardiotrophin-1Eembryonic daybFGFbasic fibroblast growth factorGAPDHglyceraldehyde 3-phosphate dehydrogenaseGFAPglial fibrillary acidic proteinhnRNPheterogeneous nuclear ribonucleoprotein A1JAK2Janus kinase 2LIFleukemia inhibitory factorMZDmarginal zinc dietNSCneural stem cellsPpostnatal dayPTP1Bprotein-tyrosine phosphatase 1BSHP2SH2 containing protein tyrosine phosphatase-2STATsignal transducer and activator of transcriptionSVZsubventricular zoneS100βS100 calcium-binding protein βVZventricular zoneZnzinc1Zinc (Zn) is essential for all living organisms and is one of the most abundant metals in the body. Zn plays a key role in the physiology of the nervous system. In this regard, Zn is a structural or functional component for a large number of proteins including enzymes, receptors, and transcription factors ,2, regulin vivo and in vitro [Given the critical role of Zn in the regulation of cell proliferation, differentiation, and survival, a decreased zinc availability during early development can have a major impact on brain structure and function . In thisin vitro . Dietaryin vitro  and affein vitro . The latin vitro and mouse models indicate that bone morphogenetic protein (BMP)-Smads [Almost half the cells in the adult human brain are glial cells , astrocyP)-Smads ,14, NotcP)-Smads ,15, and P)-Smads ,17.trans-activating activity [Our recent study showed that Zn deficiency impairs the activation of STAT1 and STAT3 in the developing rat brain and in neuroblastoma cells in culture, in part through oxidative stress-mediated mechanisms . We obseactivity . Thus, aBased on the above, this study investigated the effects of a marginal Zn nutrition imposed to rats from gestation day 0 until postnatal day (P) 2, on STAT3 activation, astrogliogenesis, and its consequences on corticocerebral astrocyte population in the young adult brain. The mechanisms of STAT3 activation were characterized at different developmental stages (embryonic day (E) 14, E19, P2, P56). A marginal decrease in fetal Zn availability caused alterations in STAT3 activation and astrogliogenesis leading to a lower number of cortical astrocytes in the young adult brain. These findings stress the relevance of a proper zinc availability during critical developmental periods for normal brain development and function.22.1Y705-STAT3), acetyl-lysine 685 STAT3 (ac-STAT3), total STAT3, phospho-tyrosine 1007/1008 Janus kinase 2 (JAK2) (pY1007/1008-JAK2), total JAK2 (JAK2), and ubiquitin were purchased from Cell Signaling Technologies . Primary antibodies for cardiotrophin-1 (CT-1) and glial fibrillary acidic protein (GFAP) were obtained from Abcam . The primary antibody for protein-tyrosine phosphatase 1B (PTP1B) was from Millipore . Polyvinylidene difluoride (PVDF) membranes were obtained from Bio-Rad . The ECL Plus Western blotting detection reagent was from Amersham Pharmacia Biotech Inc. . All other reagents were of the highest quality available and purchased from Sigma .Primary antibodies for glyceraldehyde 3-phosphate dehydrogenase (GAPDH), leukemia inhibitory factor (LIF), SH2 containing protein tyrosine phosphatase-2 (SHP2), and S100 calcium-binding protein β (S100β), heterogeneous nuclear ribonucleoprotein A1 (hnRNP), β-actin, and Protein A/G PLUS-Agarose were obtained from Santa Cruz Biotechnology . Primary antibodies for phospho-tyrosine 705 STAT3 . At E14 and E19, dams were submitted to laparotomies, the gravid uterus was removed, and fetuses were collected, weighed and examined for gross structural malformations. Fetal rat brains were removed, weighed and either immediately processed for immunofluorescence or kept on ice to dissect cortical tissue (CT)-enriched regions which were subsequently frozen in liquid nitrogen and stored at −80 °C. In E14 embryos, CT comprised the cortical neuroepithelium with the subventricular zone (SVZ) and ventricular zone (VZ); in E19 embryos, CT comprised the cortical plate with the SVZ and VZ. P2 and P56 offspring brain/brain cortices were dissected after rat euthanasia, and processed as described above.2.34 containing inhibitors of proteases and phosphatases and 1% (v/v) Igepal). Samples were incubated at 4 °C for 20 min and then centrifuged at 10,000×g for 20 min. Supernatants were stored at −80 °C. Protein concentration was determined immediately before starting the assay [For preparation of total tissue extracts, CTs were manually homogenized . An equal amount of buffer A containing 0.2% (v/v) of Igepal was added and samples were incubated on ice for 10 min. After 15 min of centrifugation at 850×g, the supernatant (cytosolic fraction) was separated and stored at −80 °C. The pellet was rinsed with buffer A and centrifuged twice at 850×g for 2 min. The nuclear pellet was gently resuspended in 100 μl of buffer B (20 mM Tris (pH 8.0), 25% (v/v) glycerol, 1.5 mM MgCl2, 0.4 M NaCl, 0.2 mM EDTA, 0.5 mM dithiothreitol, 0.4 mM NaVaO4, 0.5 mM PMSF and inhibitors of proteases and phosphatases) and incubated for 15 min on ice. After centrifuging for 30 min at 10,000×g, the supernatant (nuclear fraction) was transferred into new tubes and stored at −80 °C.Nuclear and cytosolic fractions were isolated as previously described . Briefly2.4Cell extracts containing 20–35 μg protein were added with 4× Laemmli sample buffer and heated for 5 min at 95 °C. Proteins were separated by 8–12% (w/v) polyacrylamide gel electrophoresis and electroblotted onto PVDF membranes. Colored molecular weight  and biotinylated  standards were run simultaneously. Membranes were blocked for 1 h in 5% (w/v) nonfat milk and incubated at 4 °C overnight with the corresponding primary antibodies (1:1000–1:5000) in 5% (w/v) bovine albumin serum (BSA) in TBS-Tween. After incubation with the secondary antibodies , the conjugates were visualized using an ECL system in a Phosphoimager 840 .2.5Fetal rat brains were dissected out and fixed in a 4% (w/v) solution of paraformaldehyde in PBS overnight. Tissues were washed with PBS twice before cryoprotection by incubations in 15% (w/v) sucrose in PBS for 24 h, and subsequently in 30% (w/v) sucrose for 3 d. Brains were then submerged in Cryoplast , frozen, cut into 18-μm sections on a Leica CM 1850 cryotome  and mounted on positively charged microscope slides. Sections were blocked in 1% (v/v) donkey serum in 0.1% (v/v) Triton X-100 in PBS for 45 min and then incubated overnight at 4 °C with GFAP (1:700) and S100β (1:100) primary antibodies. Sections were washed once in 0.1% (v/v) Triton X-100 in PBS and once in 0.1 M phosphate buffer, pH 7.4, and later incubated for 2 h at room temperature with the corresponding Cy2 or Cy3-conjugated secondary antibodies (1:1000) . Cell nuclei were stained with Hoechst 33342.Sections were imaged using an Olympus FV 1000 laser scanning confocal microscope  or an Olympus BX50 epifluorescence microscope equiped with a Cool-Snap digital camera. Image Pro software  was used to merge and analyze the resulting micrographs. GFAP-positive cells were counted using ImageJ  and results were expressed as the number of positive cells per area. At least 300 cells were counted and analyzed in three independent experiments performed in triplicate on four animals per group. Colocalization of GFAP/S100β was analyzed by laser confocal microscopy, and optical sections (Z = 1 μm) of confocal epifluorescence images were obtained sequentially by means of a 60×  oil objective.2.6g for 10 min. Protein concentration was determined immediately before starting the assay. Protein lysates (400 μg100 μl)were immuno precipitated using STAT3 or PTP1B antibodies(4 μg)and immune complexes were collected on protein A/G agarose beads. The pellets were washed twice with lysis buffer Proteins were added with 4 x Laemmli sample buffer and heated for 5 min at 95 °C before Western blots. After SDS-PAGE and protein transfers, membranes for the STAT3 immunoprecipitates were probed with primary antibodies for PTP1B, SHP2, STAT3, pY705-STAT3, JAK2, β-actin and α-tubulin, while membranes for PTP1B immunoprecipitates were probed with primary antibodies for ubiquitin, JAK2 and PTP1B. After an overnight incubation at 4 °C, membranes were incubated with the corresponding HRP-conjugated secondary antibodies and visualized using chemiluminescence detection in a Phosphoimager 840 .Fetal brain cortices were lysed in 1% (v/v) Nonidet P-40 buffer (10 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1 mM EDTA, 1% (v/v) Nonidet P-40, 5% (v/v) glycerol, and proteases and phosphatase inhibitor cocktails). Lysates were cleared by centrifugation at 13,000×2.7PTP1B activity was measured as previously described with minor modifications ,23. Brie2.832P)-ATP using T4 polynucleotide kinase and purified using Chroma Spin-10 columns. Samples were incubated with labeled oligonucleotide  for 20 min at room temperature in 1× binding buffer [5× binding buffer: 50 mM Tris-HCl buffer, pH 7.5, containing 20% (v/v) glycerol, 5 mM MgCl2, 2.5 mM EDTA, 2.5 mM DTT, 250 mM NaCl and 0.25 mg/ml poly(dI-dC). Products were separated by electrophoresis in a 6% (w/v) non-denaturing polyacrylamide gel using 0.5 × TBE  as the running buffer. Gels were dried and the radioactivity quantified in a Phosphoimager 840 .Oligonucleotides containing the consensus sequence for STAT3 (5′-GAT CCT TCT GGG AAT TCC TAG ATC-3′) were end-labeled with . A p-value < 0.05 was considered statistically significant. Values are given as means ± S.E.M. The litter was considered the statistical unit.Student unpaired 33.1Maternal MZD did not affect maternal and offspring outcomes at E14, E19, and P2. However, maternal MZD led to a higher  body weight of the female offspring at P56, and a trend  for higher body weight of the male offspring compared to controls . The rat3.2Y705-STAT3 by Western blot in the offspring CT at E14, E19, P2 and P56. Maternal MZD differentially affected STAT3 tyrosine phosphorylation depending on the developmental stage. Maternal MZD did not affect CT pY705-STAT3 levels at E14 and P56, while they were significantly lower  at E19 when compared to controls  in MZD than control CT at P2  did not vary between MZD and control groups at E14 and P56, while at E19 and P2 JAK2 phosphorylation levels were 92% lower and approximately 10-fold higher, respectively, compared to controls , kinases (JAK2) and phosphatases (PTP1B and SHP2). In agreement with the pattern of STAT3 activation, JAK2 phosphorylation levels at Tyr 1007/1008 , while at all other developmental stages they were similar, in MZD compared to controls H and I. During astrogliogenesis, STAT3 is activated by extracellular signals such as CT-1 and LIF ,17,24,253.3Data showed that the critical timing of initiation of cortical STAT3 activation is E19, which coincides with the beginning of active astrogliogenesis. At this time point, STAT3 was particularly susceptible to the deleterious effects of gestational MZD. Thus, this time was selected to further study potential molecules/mechanisms involved in maternal MZD-mediated impairment of fetal brain STAT3 activation.To examine whether zinc deficiency could affect the interactions of STAT3 with JAK2 and the phosphatases PTP1B and SHP2, we immunoprecipitated STAT3 from E19 CT and did immunoblotting for the interacting proteins. Compared to controls, maternal MZD caused a decrease  in the amount of JAK2 that co-immunoprecipitated with STAT3  A,C. In In terms of cytoskeletal proteins, the amount α-tubulin and β-actin that co-immunoprecipitated with STAT3 was 19% (p < 0.01) and 26% (p < 0.05) lower, respectively, in the E19 CT from the MZD group compared to controls D and E. 3.4We subsequently focused on PTP1B given that STAT3 and JAK2 are substrates of this enzyme, and that the amount of PTP1B co-immunoprecipitated with STAT3 was affected by developmental MZD. During astrocyte precursor differentiation, PTP1B down-regulation occurs via ubiquitin/proteasome-mediated degradation . Thus, w3.5Based on the reciprocal activation of STAT3 and JAK2 observed in E19 and P2 CT, we investigated if PTP1B varied accordingly. While PTP1B protein levels in CT at P2 was not significantly different, the enzymatic activity of PTP1B in MZD brain cortices was higher  at E19  A and lo3.6STAT3 transactivating activity requires STAT3 tyrosine phosphorylation, and its subsequent dimerization and transport into the nucleus. We next examined the effects of developmental MZD on STAT3-DNA binding activity in nuclear fractions. At E19 and P2, the ratio of nuclear/cytosolic STAT3-DNA binding was significantly lower  in MZD CT compared to controls A and B.FY705-STAT3/total STAT3 in MZD CT was lower at E19   C and D b < 0.05) E and F.STAT3 acetylation in the nucleus is another relevant mechanism leading to STAT3 activation. Acetylated (lysine-685) STAT3 levels in nuclear fractions were not detectable in both control and MZD CT at E19 C and D. 3.7We next investigated whether the developmental impairment of the STAT3 signaling pathway caused by zinc deficiency could affect the number of astrocytes in the offspring brain cortex. The astrocyte marker S100β was assessed by Western blot in the offspring CT at different developmental stages. S100β, a marker for mature astrocytes, was only detectable in the P56 brain cortex, and its levels were significantly lower  in the brain cortex of the MZD offspring than in controls A and B. 4This study shows that a decreased Zn availability during gestation and early postnatal stages affects cortical astrogliogenesis, in part as a consequence of a dysregulation of STAT3. The adverse effects of early developmental Zn deficiency on astrogliogenesis caused irreversible alterations in the astroglial population in the young adult rat brain. Maternal Zn deficiency adversely affects several steps in the JAK/STAT pathway, i.e. JAK2 and STA3 activation (phosphorylation), PTP1B degradation, STAT3-cytoskeleton interactions, and STAT3 acetylation.Mild maternal Zn restriction in rats does not affect general maternal and fetal outcomes . HoweverDuring brain development, STAT3 expression is region-specific . In the per se [Maternal marginal Zn deficiency increased the protein levels and activity of the STAT3 phosphatase PTP1B in the E19 CT. Given that PTP1B dephosphorylates both JAK2 and STAT3 , this phper se . Thus, Zper se ,50. The per se . Overallin vitro and in vivo [Zn deficiency causes oxidative stress and oxidative damage to lipids, proteins and DNA , being t in vivo . One con in vivo ,33,52,53 in vivo  and STAT in vivo . We did  in vivo . Thus, z in vivo ,56, the  in vivo ,58. TakeIn association with STAT3 dysregulation, a marginal zinc nutrition during gestation and until P2 impaired astrogliogenesis in the offspring brain, which extended into young adulthood. In mammals, astrogliogenesis is considered to be completed soon after birth and could be reactivated only in pathological situations. The astroglial population increases 6-8-fold in normal rats and mice during the first 3 postnatal weeks ,60, beinIn summary, our results show that marginal dietary Zn deficiency during pregnancy and until P2 causes a disruption in astrogliogenesis which extends into adulthood even after reinstatement of a diet with adequate Zn concentration shortly after birth. Given the mechanisms underlying astrocyte generation in the rodent CNS , it may The authors have no conflict of interest to declare.


IS) varied from 0.78 to 0.89 with a mean value of 0.83, suggesting that most of the accessions are inbred. Cluster analysis and population structure identified four groups with each comprising accessions from the six different sources. Weak to moderate differentiation was observed among the populations with a genetic differentiation index varying from 0.014 to 0.117. Variation was highest (78%) among accessions within populations and lowest between populations (7%). These results revealed a moderate level of diversity among the Togo cowpea germplasm. The findings of this study constitute a foundation for genetic improvement of cowpea in Togo.Crop genetic diversity is a sine qua non for continuous progress in the development of improved varieties, hence the need for germplasm collection, conservation and characterization. Over the years, cowpea has contributed immensely to the nutrition and economic life of the people in Togo. However, the bulk of varieties grown by farmers are landraces due to the absence of any serious genetic improvement activity on cowpea in the country. In this study, the genetic diversity and population structure of 255 cowpea accessions collected from five administrative regions and the agricultural research institute of Togo were assessed using 4600 informative diversity array technology (DArT) markers. Among the regions, the polymorphic information content (PIC) ranged from 0.19 to 0.27 with a mean value of 0.25. The expected heterozygosity (He) varied from 0.22 to 0.34 with a mean value of 0.31, while the observed heterozygosity (Ho) varied from 0.03 to 0.07 with an average of 0.05. The average inbreeding coefficient (F Vigna unguiculata, (L.) Walp.], an annual herbaceous legume plant, is widely distributed in tropical and subtropical regions of sub-Saharan Africa (SSA), where it plays important roles in both human nutrition and food security, income generation for farmers and food vendors, and feed for livestock. Cowpea grains are rich in protein (23.0% to 32.0% depending on variety), carbohydrates and folic acid, and contain considerable amounts of some minerals [Cowpea [minerals . The youunguiculata, is divided into five cultivar groups, namely Unguiculata, Sesquipedalis, Textilis, Biflora, and Melanophthalmus [Cultivated cowpea, which belongs to the subspecies hthalmus ,4. The chthalmus ,6. The chthalmus .From 2014 to 2018, the world annual average cowpea production was 6.57 million tons on a harvested area of 12.4 million ha with an average yield of 0.53 t/ha. Africa, and specifically West Africa, produced 96% of the world production on 82.8% of the land area . This loGenetic diversity of crops plays an important role in sustainable development and food security, as it serves as a source of genes needed in the development of better performing and well adapted varieties . Food prVigna unguiculata ssp. unguiculata and 30 wild/weedy accessions, which included those from West, East and Southern Africa, were evaluated. The wild accessions from East Africa were most diverse [Vigna species. Diouf and Hilu [2:3 populations, and new lines that might combine the attributes of the two parents could be identified [Several approaches have been utilized to enhance our knowledge of the nature and extent of variability among cowpea accessions stored in different genetic resource centers. To evaluate the genetic diversity of a given crop, morphological (phenotype) and molecular (genotype) markers have been used. However, morphological attributes are subject to environmental influences, may vary at different developmental stages, and are limited in number . Molecul diverse . Ajibade diverse  used intand Hilu  assessedand Hilu  further and Hilu  characteand Hilu  assessedand Hilu  on a minand Hilu . Potentiand Hilu . The DArand Hilu ,25, garland Hilu , apple [and Hilu , barley and Hilu  and sorgand Hilu . In cowpentified  assessedentified  reportedentified . In thisThe cowpea accessions were collected from the Republic of Togo between October and November 2018 through the country’s agricultural extension service ICAT (Institut de Conseil et d’Appui Technique) and the agricultural research institute ITRA (Institut Togolais de Recherche Agronomique). The cowpea lines were obtained directly from farmers across 63 locations in the country’s five administrative regions : “RegionSeeds were harvested from a single plant of each accession. Five (5) seeds of each representative accession were sown in pots containing about 5 kg of topsoil on 25 January 2020 in the screenhouse at IITA and thinned to two plants two weeks after planting and later to one plant per pot. A newly expanded young trifoliate leaf was collected from each plant five weeks after sowing and placed in small plastic bag containing two small packs of previously oven dried silica gel. All samples were kept inside an air-conditioned room for two weeks to allow the leaves to dry.The dried leaves were later squeezed and a quantity of 10 to 15 mg for each accession was placed in a sampling tube arranged inside six 96 well collection plates. These were shipped to Diversity Arrays Technology Pty. Ltd., .https://www.diversityarrays.com/orderinstructions/plant-dna-extraction-protocol-for-dart/ (accessed on 26 March 2021)). The DNA quality of each sample was qualitatively and quantitatively assessed on 0.8% agarose gel and Nanodrop 2000c spectrophotometer , respectively.Total genomic DNA extraction was performed at the Diversity Arrays Technology (DArT) facility, Australia, following their in-house DNA extraction protocol (https://www.diversityarrays.com/technology-and-resources/dartseq/ (accessed on 26 March 2021)). Genomic DNA Library construction was done using genomic complexity reduction technology [Vigna unguiculata v1.1, publicly accessible on Phytozome ).Genotyping was done using DArTseq methodology , more than 95% and less than 5% minor allele frequency (MnAF) in TASSEL 5 , a totalPairwise identity by state (IBS) was calculated among accessions, and those with values > 0.98 were considered duplicates. A single accession was retained for each group of duplicated accessions, leading to a dataset of 255 accessions used for further analyses.IS) for each locus were calculated for DArT markers using PowerMarker 3.25 [The minor allele frequency (MnAF), major allele frequency (MAF), gene diversity (GD) or expected heterozygosity (He), observed heterozygosity (Ho), polymorphic information content (PIC) and inbreeding coefficient (Fker 3.25 .ST) were performed using GenAlEx 6.5 [To estimate the explained genetic variation values between areas of collection, analysis of molecular variance (AMOVA) and genetic differentiation  package  implemenThe population structure of the 255 accessions was inferred using the Bayesian clustering method implemented in the software STRUCTURE version 2.3.4 . The sofThe 4600 DArT markers used in this study were subjected to genetic analysis and six SNP types  were detThe number of accessions with 98% IBS or higher similarity with another ranged from one (the most common) to 31 individuals . Each grIS) ranged from −0.83 to 1.0 (mean = 0.83). Among the regions and ITRA, the variation of FIS ranged from 0.78 (ITRA) to 0.89 (RK)  to 0.85 (RS). The He ranged from 0.04 to 0.50 (mean = 0.31) while the Ho ranged from 0.00 to 0.91 (mean = 0.05) across the 255 accessions. Mean He observed among regions and ITRA ranged from 0.22 (RS) to 0.34 (RM and ITRA), while the Ho ranged from 0.03 (RK) to 0.07 for ITRA. The highest Ho (0.07) among places of collection was observed among the accessions received from ITRA. The PIC ranged from 0.04 to 0.38 (mean = 0.25). Among the regions and ITRA, the PIC varied from 0.19 (RS) to 0.27 . The inbreeding coefficient (F.89 (RK) .p < 0.001) variation between populations, accessions and within accessions. Variation among individuals accounted for 78% of the total variation. This was followed by variation within individuals and between populations at 15% and 7%, respectively. The average accession differentiation was 0.072, while the mean value for the inbreeding coefficient and gene flow were 0.836 and 3.21, respectively.An AMOVA was performed on the 255 accessions for the distribution of genetic variation between and within the groups. The results presented in ST values were determined to quantify population differentiation among the accessions based on where they were collected from. In the present study, FST ranged from 0.014 (between RK and RC) to 0.117 (between RS and RM). Generally, weak differentiations were observed among populations. However, some moderate differentiations (0.05 < FST < 0.15) were observed between ITRA and RK (0.055), RS and ITRA (0.067), RS and RM (0.117), RS and RP (0.055), RM and RC (0.067) and RK and RM (0.091) (The F (0.091) .A phylogenetic tree resulting from cluster analysis based on Ward’s method performed on the 255 accessions shows four clusters with 26, 138, 52 and 39 accessions in cluster I, cluster II, cluster III and cluster IV, respectively A. Each oThe scatter of the cowpea lines along the first two principal coordinates showed that accessions belonging to the same cluster tend to be closely located along the axes . The firp < 0.001) variations between clusters, accessions and within accessions. Variation among accessions accounted for 45% of the total variation. This was followed by variation between clusters and within accessions at 42% and 13%, respectively. The average genetic differentiation for the four clusters was 0.423, while the mean value for inbreeding coefficient (FIS) and overall fixation index (FIT) were 0.774 and 0.870, respectively. Gene flow between the four clusters was 0.381.An AMOVA was performed on the accessions for the distribution of genetic variation between and within the four clusters. The results presented in ST values ranged from 0.140 between clusters III and IV to 0.290 between clusters II and III  was obtained for K = 2, revealing the existence of two gene pools of cultivated cowpea from Togo . AnotherThe genetic divergence among the four gene pools shown by Nei’s net nucleotide distance indicated that G2 and G3 (0.320) are the most distantly related followed by G1 and G4 (0.289). The lowest genetic distance was observed between G1 and G2 (0.145) .In this study, 4600 informative DArT markers were used to determine the genetic diversity and population structure of a set of cowpea accessions collected from Togo. Not much has been reported about the genetic diversity of Togolese cowpea germplasm. In the literature, a study on genetic diversity among cowpea germplasm from the country was carried out on 70 accessions using SSR markers . FollowiCowpea production across West and Central Africa is mainly in the savanna agro-ecologies due to the crop’s better adaptation to drought prone areas. A similar trend is expected in Togo where there also exist the Region des Savanes and Region Kara, both in dry parts of the country. It is therefore not surprising that germplasm lines collected from the northern part of the country are in the majority while the number from the maritime region (RM) is the lowest. According to production data, RM contributes only 5% of the total cowpea production of Togo . Hence, In the cowpea germplasm lines used for this study, SNP variation was found to be high with A/G, C/T, A/T, G/T, A/C and G/C having 29.04, 28.13, 11.89, 10.89, 10.11 and 9.94 percent, respectively. The SNPs, A/G and C/T were the most common in this set of cowpea lines. This result confirms earlier studies that showed A/G followed by C/T were most preponderant when compared with the others in cowpea ,46. In tIS (0.83), indicating that most of the accessions are inbred. The range in PIC by region 0.19 (RS) to 0.27  obtained in this study was consistent with gene diversity, which indicated that the accessions from RS were the least variable and those in RM, RP and ITRA most variable. The mean PIC value of 0.25 obtained in this study showed that the markers are reasonably informative. However, when considered by region, the markers were most informative for RM, RP and ITRA (PIC ≥ 0.25) and slightly informative for RS, RK and RC. The mean PIC value in this study was similar to the one obtained by Seo et al. [The expected heterozygosity (0.31) and observed heterozygosity (0.05) for the 255 accessions were comparable to the expected heterozygosity (0.296) and observed heterozygosity (0.075) values reported by Fatokun et al.  on 298 co et al. , who repST values (0.014 to 0.117) and confirmed the cluster analysis where accessions did not cluster according to areas of collection. Similar findings have been reported by some other authors. Analyzing the genetic diversity among Senegalese accessions, Sarr et al. [ST of 0.423 observed between clusters. The gene flow between clusters was less than 1.0, suggesting a limited gene exchange between the four clusters.The analysis of molecular variance (AMOVA) showed that the highest variation (78%) was observed among accessions followed by within accessions (15%) and smallest between populations (7%). These results suggest high genetic variation among accessions within each geographic origin and the accessions from one region to another were almost the same (only 10% of variation). The results confirmed the low to moderate differentiation observed between the populations according to the Fr et al.  reportedr et al.  and Mafar et al.  reportedr et al. , exploriST value in this study was 0.072 at the regional level showing a moderate differentiation among the germplasm lines. The FST values between ITRA and each of the two regions (RS and RK) showed moderate differentiation. The moderate differentiation observed between RM and RS, and between RM and RK, could be due to the distance between the regions that might not facilitate easy exchange of seeds. In fact, RM is in the coastal region while RS and RK represent the northern part of the country. The lowest FST value (0.014) observed between RK and RC suggests that the accessions from the two regions are genetically similar. This relatively low differentiation could be explained by the fact that the two regions are contiguous and seed exchange between their farmers might be high. The majority of pairwise FST values were lower than 0.05. The genetic differentiation observed by Sarr et al. [ST = 0.075) was reported among cowpea accessions collected from Ethiopia also using SSR markers [ST of 0.032. Like cowpea, pigeon pea is a self-pollinated crop. Its self-pollinating nature has been reported as the reason for the observed low genetic variation among cowpea landraces [The mean Fr et al.  using 15 markers . Kimaro  markers  investigandraces ,57. Yao andraces  explaineandraces .Cluster analysis classified cowpea accessions into four major clusters, which can also be detected on the PCoA plot along the first two principal coordinates. In the present study, the accessions clustered together irrespective of the region from where they were collected. This could be attributed to farmer-to-farmer seed exchange, a very common practice in SSA.V. unguiculata var. sesquipedalis) is the type of cowpea commonly grown and consumed as a vegetable in Asia. It has been suggested that this vegetable type cowpea originally came from Africa, after which it acquired its present characteristics following being grown in more humid environments with lower light intensity, unlike in SSA, as well as selection by farmers for succulent pods [The structure analysis showed that the 255 accessions belong to two gene pools that could be further divided into four gene pools. This observation is in agreement with the findings from an earlier study of diversity among 422 cowpea landraces collected from about 56 countries, following genotyping with a 1536-SNP GoldenGate assay . It is went pods .This study revealed the existence of genetic diversity among cowpea germplasm collections from Togo. The four groups delineated by cluster analysis were in agreement with the four gene pools identified by population structure. The grouping did not bear close relationships with the geographical regions of collection. This detection of four groups among accessions from Togo agree with earlier findings on cowpea germplasm accessions from other countries. The results of this molecular characterization would be relevant to cowpea improvement efforts in Togo and serve as reference for selecting accessions with desirable traits for breeding purposes. The genetic diversity detected within the germplasm would be of benefit to a cowpea improvement program in the country.


Neotamias minimus) are a widely distributed North American species of least concern, the southernmost population, N. m. atristriatus (Peñasco least chipmunk), is imperiled and a candidate for federal listing as a subspecies. We conducted a phylogeographic analysis across the N. minimus range to assess genomic differentiation and distinctiveness of the N. m. atristriatus population. Additionally, we leveraged the historical component of sampling to conduct a temporal analysis of N. minimus genetic diversity and also considered climate change effects on range persistence probability by projecting a species distribution model into the IPCC5 RCP 2.6 and 8.5 scenarios. We identified three geographically structured groups  that were supported by both mitochondrial and nuclear data. N. m. atristriatus grouped within a unique South subclade but were not reciprocally monophyletic from N. m. operarius, and nuclear genome analyses did not separate N. m. atristriatus, N. m. caryi, and N. m. operarius. Thus, while least chipmunks in the Southwest represent an evolutionary significant unit, subspecies distinctions were not supported and listing of the Peñasco population as a Distinct Population Segment of N. m. operarius may be warranted. Our results also support consideration of populations with North and West mitogenomes as two additional evolutionary significant units. We found that N. minimus genetic diversity declined by ~87% over the last century, and our models predicted substantial future habitat contraction, including the loss of the full contemporary ranges of N. m. atristriatus, N. m. arizonensis, and N. m. chuskaensis.Although least chipmunks ( Least chipmunks are comprised of three evolutionary significant units based on both mitochondrial and nuclear genome analyses. We predicted habitat loss due to climate change, particularly in the southern and western portions of the range, which support active conservation measures for the species. In contrast, Sullivan and Petersen , their range‐wide diversity and differentiation have received less attention. Bailey, . Yet, su Bailey,  that N. Petersen  found noN. m. grisescens suggest that they should be elevated to a unique species because they fall outside of least and alpine  chipmunk diversity in both mitochondrial and nuclear genome analyses  and a clade split between N. m. operarius (in the south) and N. m. borealis (in the north). Thus, current mitochondrial data do not support reciprocal monophyly among all named subspecies, and many portions of the range remain unsampled.With the development of new tools, statistical methods, and genomic markers in recent years, the validity of many species and subspecies delimitations for multiple taxa has been scrutinized following range‐wide genetic and genomic analyses , N. quadrivittatus (n = 16), N. alpinus (n = 2), and N. umbrinus  to sample prepared specimens from atus n = 6, N. alpNeotamias  previously designed for E. coli genome using BOWTIE2  so that we could reference map our reads to an outgroup. We downloaded reads for three eastern chipmunks genotyped using the same exon capture probe set (SRA Accession SRR504642). We first identified the unique barcodes for each individual as the eight base pairs next to the Illumina adapter and then used CUTADAPT to separate reads for each individual. Reads were cleaned with TRIMMOMATIC using default settings and then assembled for each sample into contigs using TRINITY v2.8.4  using the reference‐based short read assembler YASRA  and reference aligned to the same reference genome to create a single contig. We calculated the amount of missing data in each sample using AMAS  and T. striatus (NCBI SRA: SRR504642)  and N. umbrinus , and one sample each from N. canipes (NCBI Accession KY070149), N. rufus (KY070197) and T. striatus (NCBI SRA SRR504642) . We combined two independent chains and then output the tree with the highest median log credibility score using TREE ANNOTATOR v2.5.1; we report the node age and 95% HPD from this tree.To understand patterns of differentiation, we first analyzed mitogenomes by building a NeighborNet network in SPLITSTREE v4.14.8  from the called SNPs on the least chipmunk samples in ANGSD.Following mapping to the T. striatus) to avoid transitions from postmortem damage, selecting one site per contig . We plotted results using the ggplot2 package in R . Our ADMIXTURE and STF analyses, in conjunction with location data, identified samples that may have been misclassified at either the subspecies or species level ] and Euclidian distance using the vegan package in R : applying a per SNP genotyping rate of 20%  as the unit of analysis rather than grouping samples by location or time period, to avoid introducing potential biases via our clustering scheme. For each sample, we calculated heterozygosity as the proportion of genotyped base pairs at which the individual was called heterozygous divided by the total number of genotyped base pairs in that individual. We then built a novel model, implemented in the Bayesian framework of RStan v2.21.2  is constrained to vary between 0 and 1, while the distribution we used to model it  is not, we also analyzed the data using a Poisson regression approach. Because the results were consistent across both modeling approaches, we present only the results of the simpler parameterization in the main text and include the results of the Poisson regression in Appendix Text To investigate whether least chipmunks experienced a loss of genetic variation through time, as might be expected if anthropogenic habitat loss has driven population declines or increased isolation between demes, we conducted a temporal analysis of genetic diversity, leveraging the historical component of our sampling. We used individuals ), except for α2, which was modeled as uniform between 0 and 2, which are the parameter limits over which the powered exponential function is stable. We chose to use only weakly informative priors because we did not have strong beliefs about the parameter values. To explore whether our results were biased by the uneven temporal sampling, and particularly by the small number of modern samples, we dropped all samples collected after 1,952 (n = 4) and reanalyzed the remaining samples (n = 46) using the same modeling framework described above.To facilitate chain mixing in RStan, we scaled our response and predictor variables. We scaled heterozygosity by dividing all values by the maximum value, sampling year by subtracting the minimum, then dividing all values by the shifted maximum, and geographic distance by dividing by the maximum. All parameter estimates were back‐transformed to account for these scalings and are therefore interpretable within the original scale of the variables. The priors on all parameters were standard normals  , or inaccuracies in the original boundaries. Beyond clustering changes detailed below, we maintain the subspecies names from museum descriptions.Several samples in our dataset were obtained from outside the defined subspecies ranges Figure . SpecifiCarraway , which m3.2wθ = 3.7 × 10–4 in the N. minimus samples. This is within the range estimated for N. alpinus, for which the original probe set was developed . Average sequencing depth across the remaining 78 samples was 21×. As a check on data quality, we estimated 3.3K = 7 based on cross‐validation analysis . Therefore, we separated the eight samples of N. m. operarius into two groups for the differentiation analysis and calculated an STF = 0.157 , and West‐B, which contained N. m. scrutator, N. m. consobrinus, N. m. minimus, N. m. pallidus, and N. alpinus  clustered with the N. quadrivittatus species complex , distinguished the southern , western/central (N. m. scrutator and N. m. minimus), and northern  clusters of least chipmunks  along with N. m. consobrinus and the western and northern clusters : −1.56 × 10–6 to −5.55 × 10–7; Figure –6 per year. Over the 107‐year sampling period, this corresponds to a model‐predicted 87% reduction in individual heterozygosity. The finding that individual heterozygosity has decayed over time was strongly supported . We also found a statistically significant decay of heterozygosity using a parallel modeling approach  as the cutoff for defining areas of predicted presence Figure . The modN. m. atristriatus, no habitat was predicted under either the RCM 2.6 or 8.5 models  appeared stable within both climate scenarios and extended westward and eastward in the RCM 2.6 model. The forecast models predicted westward expansion of the range near the current boundaries of N. m. oreocetus and N. m. borealis. In the eastern portion of the range, the RCM 2.6 model predicted an expansion of habitat northward of Lake Superior; however, that patch was greatly reduced under the RCM 8.5 model .We limited our interpretation of these results to the western and southern clades because the contemporary distribution model predicted low probabilities of occurrence across the northern range Figure . Specifi4N. m. atristriatus, we inferred the phylogeographic history of least chipmunks across North America. N. m. atristriatus were previously delimited as a subspecies based upon quantitatively nominal and weakly supported morphological differences as well as limited allozyme data from regional studies of southwestern least chipmunks  compared with other pairwise populations across the range  of N. m. operarius. The ESA uses three criteria to define a DPS: Discreteness, significance, and conservation status . While taxonomic identity of fossil fragments of small rodents should be thoughtfully considered,  Storer, , suggesta Grady, . Our worN. m. consobrinus was inferred , although some gene flow with  Figures . Interes Figures . Althoug Figures , this li Figures . Thus, a5N. m. atristriatus, an imperiled population of least chipmunk, was supported when compared to range‐wide patterns of divergence. Neither mitochondrial nor nuclear datasets identified reciprocally monophyletic diversity between N. m. atristriatus and the geographically proximate N. m. operarius and N. m. caryi. We suggest taxonomic reduction of these three subspecies into a single taxon representative of the southern evolutionary significant unit in least chipmunks. Investigation of other southern populations, particularly N. m. arizonensis and N. m. chuskanensis, may support their inclusion into this ESU as well. Additional subspecies revisions may be warranted across the range of least chipmunks, as our data also support delimiting northern and western ESUs. Finally, predicted geographic occurrence patterns under two climate forecasts suggest loss of habitat across the southern range. This information should be useful for managers and conservationists working to conserve least chipmunks across North America.We used genomic data to test if subspecific status of Author SMM was an employee of the grant administering agency, New Mexico Department of Game and Fish. Authors EEP and GB declare no conflicts of interest.Emily E. Puckett: Conceptualization (supporting); data curation (lead); formal analysis (lead); funding acquisition ; methodology (lead); project administration (lead); visualization (lead); writing‐original draft (lead); writing‐review & editing . Sean M. Murphy: Conceptualization (lead); data curation (supporting); funding acquisition ; writing‐original draft (supporting); writing‐review & editing . Gideon Bradburd: Formal analysis (supporting); methodology (supporting); visualization (supporting); writing‐review & editing .Appendix S1Click here for additional data file.


A. aculeata, due to its vocation to supply oil with the same productive capacity as the oil palm (Elaeis guineenses) even in areas with water deficit. Although eight species are recognized in the genus, the taxonomic classification based on morphology and geographic distribution is still controversial. Knowledge about the genetic diversity and population structure of the species is limited, which has limited the understanding of the genetic relationships and the orientation of management, conservation, and genetic improvement activities of species of the genus. In the present study, we analyzed the genomic diversity and population structure of Acrocomia genus, including 172 samples from seven species, with a focus on A. aculeata with 117 samples covering a wide geographical area of occurrence of the species, using Single Nucleotide Polymorphism (SNP) markers originated from Genotyping By Sequencing (GBS).The genetic structure of the Acrocomia species were partially congruent with the current taxonomic classification based on morphological characters, recovering the separation of the species A. aculeata, A. totai, A. crispa and A. intumescens as distinct taxonomic groups. However, the species A. media was attributed to the cluster of A. aculeata while A. hassleri and A. glauscescens were grouped together with A. totai. The species that showed the highest and lowest genetic diversity were A. totai and A. media, respectively. When analyzed separately, the species A. aculeata showed a strong genetic structure, forming two genetic groups, the first represented mainly by genotypes from Brazil and the second by accessions from Central and North American countries. Greater genetic diversity was found in Brazil when compared to the other countries. Our results on the genetic diversity of the genus are unprecedented, as is also establishes new insights on the genomic relationships between Acrocomia species. It is also the first study to provide a more global view of the genomic diversity of A. aculeata. We also highlight the applicability of genomic data as a reference for future studies on genetic diversity, taxonomy, evolution and phylogeny of the Acrocomia genus, as well as to support strategies for the conservation, exploration and breeding of Acrocomia species and in particular A. aculeata.Acrocomia (Arecaceae) is a genus widely distributed in tropical and subtropical America that has been achieving economic interest due to the great potential of oil production of some of its species. In particular  A. aculeata (Jacq.) Lodd. ex Mart., which is large  and widely distributed throughout Central, North, and South America. The other is A. hassleri (Barb. Rodr.) WJ Hahn, which is small size and is restricted to the Cerrado savanna in Brazil and part of Paraguay. Lorenzi et al.  primers The verification of average size of the DNA fragments using the Agilent DNA 12,000 kit and the 2100 Bioanalyzer System (Agilent) equipment. The libraries were quantified by qPCR using the CFX 384 real-time thermocycler (BioRad) with the aid of the KAPA Library Quantification kit (KAPA Biosystems). We prepared two libraries of 96 samples each, which were sequenced using Illumina’s NextSeq 500/550 Mid Output Kit v2.5 (150-cycle), on the NextSeq550 platform .v. 1.42 pipeline [process_radtags module to demultiplex the samples and we remove the low-quality reads . As there is no reference genome for Acrocomia, we used the denovo pipeline of Stacks starting with the ustacks module to identify groups of putatively homologous reads (putative loci). This step was performed for each sample separately with the following parameters: the minimum sequencing depth (-m) ≥ 3, the maximum distance between stacks (-M) = 2; and the maximum distance between primary and secondary sequences [cstacks module, allowing a maximum of 2 differences between stacks [rxstacks correction module. The SNPs were filtered using the populations module, retaining only one SNP per sequence, with a minimum depth of 3X sequencing, minor allele frequency ≥ 0.01, and minimum occurrence in 75% of individuals in each location/population. After filtering, we identified 3269 SNPs (We performed the identification of SNP markers using the Stacks pipeline . We usedequences  = 2. Subn stacks  from dif269 SNPs  considerpcadapt package [fsthet package [A. aculeata), identified by the SNMF function. The p-values were adjusted using the genomic inflation factor (λ) and the false discovery rates (FDR) were defined using the Benjamini-Hochberg algorithm, considering FDR = 0.1  In the genus Acrocomia, considering the species as groups, and 2) within  methods . ConsequA. aculeata separately, considering 3259 neutral SNPs identified for the species. Each analysis in Structure was performed with a burn-in of 100,000 interactions, followed by 500,000 repetitions of the Markov Chain Monte Carlo (MCMC) in 10 independent simulations, and without prior information to define the clusters. The number of clusters (K) was determined using the average likelihood values of the ΔK method [K through the CLUMPP method [We used all samples  to perfoK method  implemenK method . The ancP method  by the sP method .A. aculeata, we obtained the Nei genetic distance [To visualize the genetic relationships among Acrocomia species and within the distance  between distance  hierarchdistance  on R [47In addition, the Principal Component Analysis (PCoA) was also carried out through the ade4 package  to exploA. aculeata populations we used the Monmonier’s function [Finally, given the wide distribution of function  in the Rfunction  to identfunction . The confunction .A. hassleri and A. glaucescens as they contain only one individual for each species), and 2) A. aculeata. Population estimates of allelic richness, number of total alleles by locus, observed heterozygosity, expected heterozygosity, and inbreeding coefficient were calculated using the diveRsity [We conducted the population diversity analysis only with the SNP data set identified as neutral for two groups or taxonomic levels: 1) The genus Acrocomia  was estimated using NeEstimator v2.01 [vcf file into GENEPOP input file. Estimation was assessed based on LD method [Contemporary effective population size  strongly associated with the geographical origin of the samples were evident. Cluster 1  and Colombia. Cluster 2  and one in state of Tocantins, northern Brazil (PAL). The samples from Campo Grande (CGR) showed low mixture levels with clusters 1 and 5 of A. aculeata. Cluster 3 . A genetic admixture of A. aculeata samples in cluster 5 , and Braúna, São Paulo (SP) (BRA), with a greater assignment to cluster 2, also showed a significant degree of admixture with clusters 3 and 5.Based on ancestry coefficients ≤ 0.75, some samples were assigned to an admixture group. Twenty samples of luster 5  with samA. crispa was clearly separated from the rest of the Acrocomia species. In addition, there is a clear genomic differentiation between A. aculeata and A. totai. Similar to the results obtained using the Structure software, the NJ analysis also recovered the substructure within A. aculeata, separating the Brazilian samples from those from other countries  originally considered as A. aculeata in the cluster of A. totai. Samples from Braúna, SP (BRA) and Cáceres, MT (CAC), which were identified as an admixture by the Structure software, occupied an intermediate position between the clusters formed mainly by A. aculeata and A. totai in the PCoA.The NJ and PCoA analyses  performeountries . This seountries . In agreA. aculeata were treated as A. totai species for further analysis of differentiation and genomic diversity. The FST values enabled a moderate genetic differentiation between species, with an average value of 0.469. The FST values between species (A. aculeata vs. A. totai) to 0.946 (A. media vs. A. crispa). In agreement with the genomic structure analysis findings, all comparisons between A. crispa and the other species showed higher values of FST, demonstrating a greater degree of genetic differentiation of A. crispa with the other species.Based on the Structure software results  and NJ a species  ranged fA. aculeata had the highest mean and A. media had the lowest mean (E) in the species ranged from 0.106 in A. totai to 0.005 in A. media. However, A. crispa was the species with the highest allelic richness (2.29) and the highest allelic richness of private alleles (0.17), while A. media presented the lowest values of allelic richness and allelic richness of private alleles . The inbreeding coefficient (F) values were high for all species, indicating relatively high levels of inbreeding in Acrocomia species, with the exception of A. media, which presented negative values (Ne) range from 0.6 to infinite. The lowest values were observed for A. aculeata, while A. totai and A. media presented the highest Ne. Nevertheless, ranges of confidence for A. media, were extremely high (infinite), making these estimates unreliable . These samples formed a subgroup that was very distant from the other samples of m Brazil .The ‘South’ group  and the lowest diversity in Mexico (HE = 0.005). Likewise, the allelic richness values were similar for all populations in the ‘North’ samples, varying from 1.09 to 1.11. However, the greatest allelic richness for the species was registered in Brazil (Ar = 1.44) (Concerning the genomic diversity within  = 1.44) .A. aculeata, the Southern group had higher estimates of population size (Ne = 3.2) than the Northern group (Ne = 0.6) (Considering the two genetic groups identified in e = 0.6) .A. aculeata samples from Brazil, genetic diversity analyses were conducted for groups of samples according to Brazilian states. Greater diversity (HE) was found in the states of Mato Grosso [Due to the vast territory and the greater number of o Grosso , São Pauo Grosso , with vaA. aculeata. Sampling was broad in terms of the occurrence of Acrocomia species and comprehensively captured the genomic diversity and structure of the species.To our knowledge, this is the first study using GBS for identifying genome-wide SNPs and their application for inferring the genetic diversity and population structure in Acrocomia species and within A. aculeata as an independent genetic group or taxon was supported through the results obtained with the Bayesian analyses  approximately 11,200 MY, and was later dispersed by humans to Central America [A. aculeata dispersion routes from South to Central and North America [Another interesting result observed was that individuals from the population of Maranhão presented as an admixture between the Northern and Southern groups of aculeata . The ori America . Accordi America , the lowA. aculeata with a degree of genetic admixture with A. totai  belonged to cluster 2 with a high ancestry coefficient (> 0.75), according to Structure analysis (A. aculeata and A. totai (treated as ecotypes) using microsatellite markers. Although not treated as distinct species, but considering the geographical distribution of both, several studies using molecular and morphological markers also reinforced the classification of A. totai as a distinct taxon. Lanes et al. [A. aculeata between individuals from the Pantanal region, State of Mato Grosso do Sul, Brazil, and other regions of the country. Similarly, Silva et al. [A. aculeata include larger fruits (3.5 and 5.0 cm) and a pulp oil content that can reach approximately 78%  while the fruits of A. totai are smaller (2.5 and 3.5 cm) with a pulp oil content between 26% and 33% [rgentina ,23. The rgentina , leaf anrgentina , and frurgentina . Howevereristics . Our resanalysis , and coranalysis . Our ress et al.  used mica et al.  (27) ana and 33% –85  between species was 0.083, which was the lowest value (CT = 0.07) by Lima et al., [Although the genetic structure and separation of st value . These r et al., . The fin et al.,  or could et al., .E and Ar values, A. totai was the species with the highest level of genetic diversity   . Howeverribution –95.A. crispa is an insular species with a distribution restricted to Cuba. A clear separation and a strong genetic divergence compared to the other species, as evidenced in the cluster analysis  compared with other Acrocomia species, although these values are expected for endemic island species. However, interestingly, A. crispa presented the greatest allele richness (2.29) and allele richness of private alleles (0.17)  . Based oed 5 Mya . This moontinent ,102.A. crispa. However, some morphological differences have been described, such as the presence of swelling in the median region of the stipe as the most discriminating botanical characteristic [A. totai (2.5 to 3.5 cm), A. intumescens (3.0 to 4.0 cm) and A. aculeata (3.5 to 5.0 cm) [A. aculeata and monocolpous pollen in A. crispa (named Gastrococos crispa by the authors) [There is no detailed information about the morphological characteristics of teristic , the smateristic , than th 5.0 cm)  and alsoauthors) .A. crispa, previously designated to the genus Gastrococos by Moore [prk gene [A. aculeata and A. crispa as sisters in a single monophyletic group [by Moore , was recprk gene . Althougic group –110, othic group  and cladic group  shown thA. crispa within the genus Acrocomia. Therefore, we suggest a revision of the taxonomy for the species and considering the low sample size, our results about genetic diversity in the species should be taken with caution and additional studies including more populations and more samples per population are needed.The morphological characteristics of the species, the divergence time and our results of genetic differentiation, diversity, and structure may collectively support an independent taxonomic status of A. crispa, the recognition of A. media as an independent taxonomic unit was not supported by our study. As A. media is also an island species, it would be expected to have a strong genetic structure when compared to other Acrocomia species with a continental distribution. Contrary to this assumption, all samples considered as A. media were assigned to the northern group of A. aculeata, as evidenced by three cluster analyses , but were consistent with several studies of population genetics in plants, which predicted that island populations have reduced levels of genetic diversity compared to continental populations [A. media can be attributed to the founder effect associated with the establishment of populations with only a few individuals [The estimates of genetic diversity observed in ulations ,112. Theividuals  or to geividuals . NeverthA. media was first described in Puerto Rico by Cook [A. media from A. aculeata. However, A. media was considered synonymous with A. aculeata for a long time due to the absence of consistent botanical characteristics for differentiation. In 2013, The Plant List recognized A. media as a distinct species based on the floristic palm inventory of Proctor [A. media was very old and based on few individuals, suggesting an increase in the number of evaluated individuals to guarantee a more consistent morphological description of the species. The only phylogenetic study performed with A. media included an individual from Puerto Rico, and a sample of A. aculeata from Brazil revealed that both species were closely related [ by Cook . The aut Proctor . However related .A. media, low genetic diversity in the species, and low pairwise FST value between A. media and A. aculeata, we hypothesize that A. media is synonymous with A. aculeata. Thus, a recent introduction in Puerto Rico was not sufficient to characterize the reproductive isolation needed for the differentiation of A. aculeata.Based on the lack of genetic differentiation of A. hassleri and A. glauscescens. Based on morphological characters, the species are clearly differentiated from the others by their small size. However, based on the results obtained from the cluster analysis, they were assigned to cluster 2, being closely related to A. totai , with greater genomic diversity in the latter populations. The results from this study will serve as a reference for current and future studies on genetic diversity, taxonomy, evolution, ecology, and phylogeny of the genus Acrocomia, and will support genetic breeding, conservation, and management activities for A. aculeata.In the case of S1 Fig(PNG)Click here for additional data file.S2 Fig(PNG)Click here for additional data file.S3 FigThe blue lines indicate the position of the barriers.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S1 File(VCF)Click here for additional data file.S2 File(DOCX)Click here for additional data file.