Cercis canadensis (Eastern Redbud) is an economically valuable understory tree species native to the United States (U.S.) that is also important for forest ecosystem and wildlife health. Here, we document and explain the population genetics and evolutionary history of this deciduous tree species across its distributed range. In this study, we used twelve microsatellite markers to investigate 691 wild-type trees sampled at 74 collection sites from 23 Eastern U.S. states. High genetic diversity and limited gene flow were revealed in wild, natural stands of C. canadensis with populations that are explained by two major genetic clusters. These findings indicate that an ancient population bottleneck occurred coinciding with the last glacial maximum (LGM) in North America. The structure in current populations likely originated from an ancient population in the eastern U.S. that survived LGM and then later diverged into two contemporary clusters. Data suggests that populations have expanded since the last glaciation event from one into several post-glacial refugia that now occupy this species’ current geographic range. Our enhanced understanding benchmarks the genetic variation preserved within this species and can direct future efforts in conservation, and resource utilization of adaptively resilient populations that present the greatest genetic and structural diversity.Understanding of the present-day genetic diversity, population structure, and evolutionary history of tree species can inform resource management and conservation activities, including response to pressures presented by a changing climate.  During the last glacial maximum (LGM), which occurred approximately 18,000–21,000 years ago5, the Laurentide Ice Sheet extended from the northernmost portions of North America to 39°N3. These events reduced the range of many temperate tree species, forcing them into glacial refugia, which included unglaciated southern regions and suitable micro-environments that were present in northern glaciated regions6. Many historically contiguous or closely occurring refugia have been identified in the eastern United States (U.S.), but location delineations and number of refugia continue to be debated7. These refugia are poorly represented within the fossil record, yet the spatial genetic structure and evolutionary histories of many species have been used as evidence of historical refugia10.The genetic structure and demographics of many North American plant species have been greatly influenced by climate fluctuations that occurred during the Pleistocene epoch12. The result of this recolonization process can be inferred from the genetic structure within extant plant populations, manifested as reduced genetic diversity along colonization routes, and distinct spatial genetic clusters across the newly expanded range of a species14. Patterns of reduced genetic diversity across a range in expansion are common among European temperate plant species15. This trend is not as evident among North American tree species, such as Carya cordiformis [Wagenh.] K. Koch (bitternut hickory) and C. ovata [Mill.] K.Koch (shagbark hickory), which present relatively uniform genetic variation in their distributions15. Genetic homogeneity in North American plant species can be explained by slow post-glacial expansion into new areas, presence of many refugia occurring in close proximity, and high gene flow across time16. Nevertheless, phylogeographic studies provide evidence that range dynamics of the post-glacial species populations have contributed more to the current patterns of genetic diversity in temperate tree species than any other ecological force . Cercis canadensis is a great system to study the role of LGM in eastern U.S. tree species, due to its wide and continuous geographic distribution without any major geographical barriers across eastern U.S.The distribution of tree species, their genetic diversity, and population structure are shaped by many factors including climate oscillations, demographic incidents, ecological and environmental variables, and by their distinct biologyCercis canadensis is a self-incompatible20, deciduous tree native to the midwestern and eastern U.S., as well as northeastern Mexico22. This species grows well in partial shade, is well adapted to a wide-range of climate conditions and elevations, and can be found in the USDA hardiness zones 4 through 924. This relatively small ornamental tree is characterized by its wide, colorful, umbrella-shaped canopy25, and is a popular landscape tree due to its heart-shaped foliage, compact form, and early spring flowers23.C. canadensis was examined with microsatellite loci26, wild trees maintained high genetic diversity, gene flow, and moderate to high genetic differentiation27. Although C. canadensis is ecologically important, there is limited knowledge of the contemporary genetic diversity, spatio-temporal genetic structure, gene flow, and past evolutionary history of this species across its native range in the U.S. To address this knowledge gap, we used microsatellite loci to accomplish the following: (1) characterize the genetic diversity of the wild populations of C. canadensis within its native range in the U.S.; (2) infer patterns in the spatial genetic structure of C. canadensis; and (3) reveal the evolutionary demographics in its native range. We hypothesized that C. canadensis wild populations will be genetically diverse and genotypes will be spatially clustered across its native range. We also hypothesized that the genetic structure would be consistent with range expansion that occurred from one of several southern glacial refugia. More specifically, we aimed to explore the following questions: (1) Do genetic diversity and population structures patterns reflect evidence for northern glacial refugium? We expected to detect high genetic diversity with distinct population structure in northern range limit, otherwise a trend of high to low genetic diversity from south to north would indicate recolonization of C. canadensis in north from one or more southern glacial refugia; (2) Is there any evidence for micro-refugia in current C. canadensis species distribution range? If there were multiple micro-refugia present in close proximity, especially in southern region, we expected to detect genetic homogeneity in the studied populations.When a fine-scale, smaller, and fragmented population of C. canadensis were collected by authors, collaborators, and citizen scientists (see acknowledgements), who sampled specimens across the native range of this species in 23 states in the midwestern and eastern U.S.  and were kept in liquid nitrogen for 5 min between each pulverization step. The Qiagen DNeasy Plant Mini Kit  was used to isolate genomic DNA (gDNA) from the pulverized samples with the following minor modifications in the manufacturer’s provided protocol. Specifically, 2% w/v polyvinylpyrrolidone (PVP) was mixed into the lysis buffer (AP1). Then 8 µl of RNase was added into each sample tube and incubated at 65 °C in a water bath for 45 min. Every two mins each sample tube was inverted gently to mix the sample well. Lastly, samples were incubated at − 20 °C for at least one hour. Ethanol was used to wash the spin columns if there was any visible remaining debris and elution buffer added. Elution buffer was heated to 65 °C before 50 µl was added to the spin columns twice. Concentrations of gDNA were quantified using ND1000 Ultraviolet-Vis Spectrophotometer  and the gDNA was stored at − 20 °C until further use.C. canadensis individuals from the University of Tennessee Gardens  and used to evaluate 68 candidate microsatellite loci26. Primers for twelve polymorphic microsatellite loci  and analyzed with a 15/600 bp internal alignment marker and a 25 to 500 bp DNA ladder. All 28, raw allele sizes were converted into allelic classes. In this program, alleles were binned into base-pair (bp) size categories by statistical similarities. This binned genetic dataset was used for all of the following statistical analyses, which were completed using R version 3.5.329. Clone-correction of the data was implemented to identify presence of clonal individuals at the collection site level using the R package POPPR version 2.8.231. For each collection site, only multi-locus genotypes (MLG) were used to obtain unbiased estimates of allelic frequency from the dataset32.Using the Excel macro FLEXBIN versionO; number of the heterozygotes present at a locus which is divided by sample size), expected heterozygosity , and linkage disequilibrium (rbard); non-random association of alleles between loci). Additionally, the Shannon-Weiner diversity index (H) was calculated for each collection site using POPPR. H considers both allele richness and evenness of the allelic distribution34. The number of unique private alleles in collection sites and different loci was estimated in POPPR package. Allelic richness (Ar), a measure of rarefied allelic counts per locus, was estimated using package HIERFSTAT version 0.04–2235. Allelic richness is used as an estimate of the long-term evolutionary potential to adapt and persist in a given population37. The genetic fixation index (FST), inbreeding coefficient (FIS), and allelic differentiation (F’ST)39 were calculated using HIERFSTAT package. Gene flow (Nm) was estimated using GenAlEx 6.5 software . In the program, Nm was estimated as the effective number of the migrants per locus based on F-statistics.R package POPPR was used to calculate the total number of alleles per locus, observed heterozygosity  approach was used with the following parameters: 500,000 burn-in period with 1,000,000 MCMC repetitions for 30 independent chains for K values from 1 to 18. The resulting output was visualized with STRUCTURE HARVESTER web version 6.9441. The optimum K value, indicator of population clusters present in the dataset, was calculated utilizing the Evanno method42. The estimation of ΔK criterion obtained from STRUCTURE HARVESTER were visualized using POPHELPER 2.2.643 that merged the 30 independent chains. R packages MAPS version 3.3.044 and PLOTRIX version 3.8–145 were used to generate pie charts of admixture proportions at K = 2.Population structure within the native range of wild C. canadensis samples. A Neighbor-Joining (NJ) dendrogram was constructed using Nei’s genetic distance in POPPR47. Discriminant Analysis of Principal Components (DAPC) was implemented using package ADEGENET version 2.1.148 to visualize the underlying genetic structure of this species in its wide geographical range. This is a two-step multivariate analysis that investigates the genetic variations within populations among the sampled collection sites49. At first, a principal component analysis (PCA) was conducted, and then the number of PCA vectors (to explain majority of variance with minimizing over-fit of the DAPC) was selected. Then, a selected number of PCAs were used to reveal differences between groups while minimizing within group variations, as well as ordination of collection sites into distinct groups using discriminant analysis50. Moreover, missing values were calculated as mean allele frequency and cross-validation analysis was performed to select appropriate PC numbers.Several model-free methods were utilized to investigate the population structure of 52 with 10,000 permutations in package VEGAN version 2.5–653 using Euclidean distance. IBD checks for a correlation between genetic distance and geographical distance among the individuals in a dataset. The Mantel test was implemented across the 74 collection sites while considering the whole dataset as one population.Isolation by distance (IBD) was estimated using the Mantel test54 was carried out using POPPR with 10,000 permutations by sorting the individuals into hierarchical groups to assess the degree of molecular variance partitioned within, between, and among the collection sites. The levels of population hierarchy included: (1) 74 collection sites as one hierarchical group; (2) two groups on the basis of the STRUCTURE analysis; and (3) four major groups on the basis of five major eco-region divisions namely hot continental division (mountain provinces), hot continental division, warm continental division, subtropical division, and prairie division C. canadensis, we used DIYABC program version 2.156 that utilized Approximate Bayesian Computation (ABC) statistical methods. For this analysis, collected individuals were pooled into two major groups, based on the STRUCTURE results. To elucidate the evolutionary history of C. canadensis, we analyzed competing scenarios in two ABC steps. In the first step, we tested five demographic scenarios using 200,000 simulated pseudo-observed datasets (PODs) wherein: (1) the first two scenarios suggested stepwise divergence of the current two major groups from an ancient population, (2) a third scenario suggested a single, two-way split of contemporary groups from an ancient unsampled population, and (3) the last two scenarios were based on the hypothesis of divergence of current groups from two separate ancient un-sampled populations. Once the analysis of these scenarios was completed, the two scenarios from the first step that yielded higher logistic regression support were selected as the basis for assessing the second step of ABC. In the second step, seven scenarios were constructed that addressed the possibility of a bottleneck occurrence within the evolutionary history of the species. Over 1,000,000 pseudo-observed datasets (PODs) were simulated under the assumed prior parameter ranges for each scenario. Posterior probabilities of the compared scenarios were estimated to select the best supported scenario55.To investigate and interpret the evolutionary history of C. canadensis trees sampled in this study. Due to presence of missing data (missing ≥ 40% SSRs), five of 79 collection sites were excluded and 49 individuals from the remaining 74 sites were discarded, resulting in 691 individuals from 74 collections. Additionally, after deleting two clonal individuals, 689 unique multilocus genotypes from 74 collection sites remained for further data analyses (Table E) value in the studied 74 collection sites was 0.67, ranging from 0.32  to 0.68   but significant linkage disequilibrium value detected in the dataset. Nineteen private alleles were detected within the 74 collection sites  across all loci was 0.32, ranging from 0.01 (locus 995a and 680a) to 0.99 (locus 127spa). The overall expected heterozygosity (HE) across all 12 microsatellite loci was high (HE = 0.69), ranging from 0.52 (locus 995a) to 0.86 (locus 780b).Twelve microsatellite loci were amplified from 790 es Table . Nei’s gFST = 0.19; ranging from 0.05 to 0.53; Table F’ST = 0.19; ranging from 0.05 to 0.54) were identified among C. canadensis populations. We estimated an inbreeding coefficient (FIS) of 0.43 across all loci, indicating excess homozygotes  for the 12 loci was 1.42 and ranged from 0.84 (locus 995a) to 2.19  and mid-south to mid-north (from Texas to Nebraska) were part of the first cluster (designated as north genetic cluster)  Fig. . The resers Fig. –3. TheseP < 0.001) (Table P < 0.001). When the dataset was divided into two genetic clusters based on STRUCTURE results, 69.2% (P < 0.001) of the genetic variability was attributed to the location of collection sites (Table P < 0.001) and between collection sites within the clusters   of the variability could be attributed among eco-region groups, versus 18.6% (P < 0.001) variability that was attributed among the collection sites within groups  with genetic distance  analysis, the first data arrangement showed that most of the genetic variation was present within 74 collection sites  Table . A signies Table . There w1) Table . When thps Table . The majps Table . NeverthC. canadensis wild populations. From the first step of the analysis, two probable scenarios were chosen according to their posterior relative support  = 0.39 and Scenario 3, posterior probability (P) = 0.37; Fig. C. canadensis population originated in the southeastern U.S. region from an ancient population and then later, a north population group (first genetic cluster) diverged from the south population group (second genetic cluster). Alternatively, Scenario 3 suggested that both current C. canadensis groups (north and south) have split from an ancient, as yet unsampled group  , which is approximately 25,000 years ago, given the average time for a C. canadensis that were sampled across its native range in the U.S. revealed high levels of genetic diversity and population differentiation, the presence of population structure, limited gene flow, and an ancient bottleneck that temporally coincides with the last glacial period in North America. We detected the presence of geographical clusters, longitudinally in the southern region , and northern region. Evolutionary history analyses revealed an ancient bottleneck event occurring in the C. canadensis population in the south followed by divergence of the northern population from the southern population of C. canadensis.Wild populations of C. canadensis. Low genetic variation in C. canadensis across ecoregions is not surprising, given that this tree species is well-adapted to a wide range of soil types, environmental conditions and habitats, has not been constrained by any major geographical barriers, and is widespread among the eastern U.S. However, we found evidence of relatively higher genetic diversity among the northernmost collection sites  that are located at the periphery of the contemporary northern range of this species. A plausible explanation for this discrepancy between northernmost samples when compared to the southern collection sites is the probability of one major refugium or admixture between small, but genetically rich, populations in refugial contact zones60. This effect is most evident in species that experience reproduction via long distance gene flow and local adaptation among sensitive individuals in the distributed population margins. However, unlike European temperate species, eastern north American species maintained high genetic diversity in northern populations62. This high level of genetic diversity in the C. canadensis northern population could be maintained by long-distance seed dispersal events during range expansion from post-glacial northern refugia63.When populations were compared across the ecoregion divisions from which they were collected, ecoregion designations were not associated with population structure and genetic diversity of wild populations of C. canadensis to maintain high genetic diversity can be influenced by several factors, including wide and continuous geographic distribution, an outcrossing reproductive system, and large effective population size66. Many other temperate tree species sustain high genetic diversity and allelic richness across a wide geographical range even in the presence of environmental stressors58, pressure from insect and plant pathogens68, and human disturbances70. A study using microsatellite loci revealed high genetic variation among five Asian Cercis spp., averaging 5.7 alleles per locus71. A recent study focused on smaller and fragmented C. canadensis populations also determined that trees in this species maintain high genetic diversity and allelic richness across the native range27, congruent with Asian Cercis species and several other hardwood tree species76.The ability of C. canadensis populations also display a wide range of morphological variation across diverse environmental conditions79. For example, Cercis leaf shape, size, surface pubescence, and other structural features were found to be strongly related to environmental factors, such as temperature and moisture content81. In Cercis spp., these characteristics likely originated through local adaptation to varying climatic pressure83. Morphological variation in C. canadensis has led efforts to differentiate the species into the following three varieties: C. canadensis var. canadensis L., distributed across mesophytic habitats of the eastern U.S., C. canadensis var. mexicana (Rose) M. Hopkins (Mexican redbud) and C. canadensis var. texensis (S. Watson) M. Hopkins (Texas redbud), which are both commonly found in semi-arid regions of central Mexico and southwestern Texas86. However, the validity of such sub-specific classification has been questioned because of the highly continuous pattern of morphological variation in C. canadensis populations across its range. Moreover, current phylogenetic studies were unable to provide sufficient support to validate these divisions87. Because C. canadensis var. mexicana and C. canadensis var. texensis were not represented in our study, our data will not assist in resolving this question.In addition to high genetic variability, 88. Populations of Viburnum rufidulum Raf.89 and Cornus florida L.68 are temperate tree species that are widely distributed in the southeastern U.S. and have low genetic differentiation with weak population structures. Across populations of V. rufidulum and C. florida, high levels of gene flow via pollen and seed dispersal may have reduced genetic variability89. Contrary to these studies, high genetic differentiation observed among widely distributed populations of C. canadensis may be attributed to a limited gene flow, as well as the demographic history of the species.Widely distributed tree species that grow in large populations usually have low genetic differentiation and have limited population structure across their geographic range20, gene flow in C. canadensis is dependent upon various pollen and seed dispersal mechanisms. Flight distance of insect pollinators varies from one to several miles91, which would limit long distance gene flow by pollen dispersal among trees. Seedpods and seeds of C. canadensis are relatively heavy and typically fall in close proximity to the parental tree. Progeny that survive grow as non-reproductive seedlings during the next several years92 and yield half-sib “neighborhoods” within a localized spatial scale96. Several seed-feeding mammals, such as eastern woodrats (Neotoma floridana Ord)97, and birds including quail98 contribute to the dispersal of C. canadensis seed to some extent. Small rodents and deer may repeatedly eat from the same tree, thus carrying the closely related, half-sibling propagules (if eaten when seeds have matured) for distances restricted to the retention time of fecal scats101. To fully understand gene flow patterns and predict changes to C. canadensis distribution patterns, it may be helpful to unravel the seed and pollen dispersal methods and efficacy of seed transport by animals that have been associated with this tree species. However, seed transport efficacy will likely be limited to the relatively short distances traveled by these animals during foraging. Fruit consumption rate by animals is also restricted by reliance upon C. canadensis fruits as emergency food in late fall or winter, and this behavior would lower efficiency of functional seed dispersal101. These events likely limit the gene flow to short distances, create spatial genetic structures, and increase the likelihood of inbreeding at a local level, as revealed in fine scale level assessments of C. canadensis102. We also collected C. canadensis samples from New York (U.S.) that represent individuals occurring farther north than the reported geographic range of the species. These individuals also could result from open-pollinated escapes subsequent to introduction of C. canadensis into managed landscapes.Similar to many other self-incompatible forest tree speciesC. canadensis dataset revealed the presence of two geographically distinct clusters, designated as northern and southern clusters, that are divided longitudinally northwest by southeast along a Kentucky-Tennessee-Mississippi transition zone. From this evidence, the southern Appalachian Mountains have not posed a barrier, as populations belonging to the northern STRUCTURE clusters were found on both sides of the Appalachian Mountains. The presence of only two genetic clusters is congruent with the simple postglacial lineage theory presented for eastern North American tree species103. The most recent glacial event ended approximately 21,000 years ago. By its conclusion, boreal and temperate tree species had shifted closer to mid-latitudes within the eastern U.S., where many species survived within bottlenecked refugial populations104. According to our DIYABC supported scenario, a southeastern refugium was also likely to be the major postglacial refugium for C. canadensis. This scenario is further supported by several phylogenetic studies that have indicated that southeastern U.S. populations served as one prominent large-scale, post-glacial refugium for many temperate species104. Modern day temperate species including Fagus grandifolia Ehrh. (American beech), Acer rubrum L. (Red maple), and C. florida (Flowering dogwood), for example, likely originated from this southeastern refugium105. Cercis canadensis also shares the same geographic distribution as these temperate tree species, and modern-day wild populations of C. canadensis are ubiquitous throughout this region.STRUCTURE analysis of the C. canadensis populations from this geographical range may have spread northward to establish the current species distribution. Post-glacial populations of other tree species from this range are adapted to semi-arid to xeric environments103 and present adaptive characteristics that are similarly evident in mid-western C. canadensis populations. Moreover, the presence of a number of refugia or fragmented refugia is also can be supported by the high genetic diversity and allelic richness of the modern-day C. canadensis populations60.Our analyses also revealed support for several possible micro-refugia across the eastern U.S., evident in genetic differences among populations and presence of substructures that lack distinct centers. Several studies on different tree species indicated presence of refugia in the eastern U.S. such as southern Appalachian Mountains, southeastern coastal plains, and lower Mississippi River Valley . Post-glacial 108. Due to insufficient fossil data from the Late Pleistocene in the northern region, it is difficult to conclude the definite presence of northern refugia of the C. canadensis populations6. The best supported DIYABC evolutionary scenario suggests that at the time of the last glacial period C. canadensis populations persisted within a southern population group. Therefore, we also find little evidence for the possibility of a northern cryptic refugium for this species. Instead, pre-glacial C. canadensis was distributed in midwestern and southeastern U.S. populations, which later survived in one or more post-glacial midwestern and southeastern U.S. refugia. As a consequence of long-term population isolation within the refugial areas, a post-glacial refugial population in the midwestern U.S. may have diverged from the southeastern large refugium population, giving rise to a genetically differentiated northern spatial cluster95. Also, this post-glacial northern population may have later migrated from the midwestern U.S. to establish the current range distribution.Phylogeographical studies of other tree species and animals indicate that they survived as northern cryptic micro-refugiaCercis species are thought to have originated under mesic conditions and may have dispersed into North America across the North Atlantic Land Bridge109. According to several studies, ancestral Cercis population adapted to the drier environment and then spread into the Northern hemisphere during the mid-Miocene period87. It is possible, then, that this ancestral, un-sampled, mid-Miocene Cercis population gave rise to the southern C. canadensis population as suggested by DIYABC Scenario 2a.Ancestors of North American 57. Fruits and seeds of C. canadensis are consumed by several bird species and small mammals101, and many pollinators depend on this tree for an early season food source110. More than three dozen cultivars are available commercially and nursery stock sales of the species contribute to more than $27 M annually in the U.S.111. When paired with recent introductions of novel horticultural cultivars with highly desirable characteristics, the value of adaptive traits that are likely to exist across different geographic localities supports the importance in conserving local level diversity of C. canadensis. These populations are genetic reservoirs of potential variability that can provide breeding programs with the resources needed to improve selected traits  and provide additional opportunities for developing high-value cultivars for commercial trade. Future work should also focus on identifying important adaptive traits in wild populations that can be used to help ensure that C. canadensis populations will persist and will continue to adapt to a changing climate that is occurring across portions of the current species distribution.This economically and ecologically significant deciduous shade tree species has a number of desirable morphological variations and ornamental characteristics including foliar color and texture, flower color variation, drought tolerance, pathogen resistance, as well as a wide variety of architectural formsAfter the manuscript is accepted, data will be publicly available and deposited to Dryad Depository.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.


The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighboring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses, we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighboring populations display their unique geographic position while increased intra- versus inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes. Situated at the crossroads of Africa, Europe, and Asia, and together with strong tribal social structure, the populations of the Arabian Peninsula provide an important ingredient to understanding human evolution and population admixture events. Studies unraveling the population history and genetic structure of Middle Eastern—and particularly Arabian Peninsula—populations have been relatively limited and Arabia is still underrepresented in such investigations, which may exacerbate health inequalities for diseases such as metabolic syndromes traits , which aOver the last 10,000 years, there is evidence of sequential climatic effects on Arabian populations. Aridification and long droughts led to regional abandonments and geographic relocation of groups , inducinIn recent history, the discovery of oil in 1959 transformed the population of UAE, growing from 87,000 to 9.9 million (November 2020), largely due to the influx of expatriates primarily from the Indian subcontinent. Emiratis account for an estimated 11% of the current population. Against this complex flux that would be expected to promote genetic admixture, social and, cultural factors are proposed to have restricted gene flow and diversity . There iHere we report the fine-scale genetic structure and ancestry of the Emirati population based on an analysis of 1,198 individuals from the UAE, a federation of seven Emirates  . Dubai aP = 3.97 × 10−5 and 1.4 × 10−29, respectively) (Mann–Whitney U test), E and R by Ras Al Khaimah , I and N by Umm Al Quwain , M by Dubai (P = 2.85 × 10−8), and P by Abu Dhabi (P = 1.85 × 10−32). These results are additionally supported by a population relationship tree inferred using Treemix   showed tWhen we examined the pattern of distribution of individual Emirates within the 1000G and GME joint PCA analyses, we observed inter-Emirati genetic structure e and f. Population tree inferred using Treemix  showed tWe next tested admixture using f3-statistics  placing Next, the five largest Emirate groups were analyzed separately, which allowed observation of distinct ancestral differences between them. The Sharjah Emirate appears in this test to have more significant African/Eurasian admixture compared with the other Emirates c. When tWe next inferred Y chromosome  and mitoWe observed clear patrilineal and matrilineal differences between the Emirates . More spWe observe considerable contrast in the distribution of Y and mitochondrial haplogroup frequencies within families originating from the same Emirate . Some ofWe have investigated the genome-wide diversity of the Emirati population and found that both ancient and more recent demographic events have contributed to the genetic formation and structure of the population. Our admixture tests suggest that the population retains an autochthonous Middle Eastern ancestry supplemented with African and South Asian ancestries. The Emirati population captures admixture events that have occurred thousands of years ago, possibly related to movement of people in the Middle East after major cultural transitions such as the invention of agriculture or more recent movements related to climate change and desertification of the region in the past 6,000 years ago . HoweverOur study represents the first fine-scale genetic analysis of the Emirati population building on broader population structures revealed by other studies of the Arabian Peninsula. We uncover a unique and distinct genomic architecture and provide new insights into the ancestry of these populations and the social dynamics influencing their diversity. Complex disease risk alleles, rare and undetectable in other populations, may be amplified by cultural factors to discoverable levels, providing novel insights into disease mechanisms applicable to all populations. For Emirati populations, this will have important implications for future efforts to understand genetic risk and facilitating development of population-specific therapeutic interventions  includinSamples from Emirati individuals were collected through the Imperial College London Diabetes Centre (ICLDC), Abu Dhabi, UAE. The cohort reflects volunteers attending ICLDC for periodic health check-ups regardless of any disease status. Emirate of origin of each volunteer was assigned as per their Emirati Family Book  or was reported by the individual. Tribes were defined by family name. All volunteers gave written informed consent for inclusion in the study. Ethical approval was given by the ICLDC Research Ethics Committee (IREC 011).Abu Dhabi, Sharjah, Umm Al Quwain, Fujairah, and Ras al Khaimah assigned volunteers had the largest sample sizes and it is for these Emirati populations that we discuss the most significant results in the main text of the manuscript. The two remaining Emirati populations (Dubai and Ajman) for whom we had fewer volunteers  were omiSamples were genotyped using Illumina’s Multi-Ethnic Global-8 v1 chip (Illumina). Genotyping data were processed and quality controlled using PLINK  standardWhen measuring homozygosity, we used the plink –homoz together with the –homozyg-window-het flag to allow 0, 1, 2, or 3 heterozygous calls to be present in homozygous windows which was shown to be useful when comparing runs of homozygosity size and sum between data sets using different technologies   .Tests of admixture were performed (tistics)  placing tistics)  fig. 4)f3-statististics)   was used to infer a maximum-likelihood tree with migration events for the five largest Emirate samples and GME populations. The same analysis was performed for the Emirati tribes.Treemix  .Patrilineal inheritance was determined from the Y-chromosome genotypes of 568 Emirati males using YHaplo  .Matrilineal inheritance was determined from the mitochondrial genotypes of 630 Emirati females using HaploGrep 2  1000G, http://www.sciencedirect.com/science/article/pii/S0002929715001561 Ethiopian and Egyptian genomes, https://www.simonsfoundation.org/ Whole genome diversity panels, http://evolbio.ut.ee/ Estonian Biocentre, https://www.wikipedia.org/ Wikipedia, https://www.python.org/ Python, https://www.r-project.org/ R, https://www.rstudio.com/ Rstudio, http://www.cog-genomics.org/plink2/ PLINK, https://people.maths.bris.ac.uk/~madjl/finestructure/index.html fineSTRUCTURE and ChromoPainter, https://bitbucket.org/nygcresearch/treemix/wiki/Home treemix: https://github.com/23andMe/yhaplo Yhaplo, http://haplogrep.uibk.ac.at/ HaploGrep2, http://tree.bio.ed.ac.uk/software/figtree ;FigTree Maps in kelliott@well.ox.ac.uk), Hinda Daggag, Alia Al Tikriti, Houman Ashrafian, and Maha Barakat (chair). Access will be subject to the rules and regulations of the Emirate of Abu Dhabi, at the time of request. Access-required membership and/or appropriate use agreement with Imperial College London Diabetes Centre (ICLDC) will also apply.Access can be granted by contacting the data access committee: Katherine Elliott (corresponding author; Molecular Biology and Evolution online.msac039_Supplementary_DataClick here for additional data file.


Lycaena tityrus) from the European Alps, using genome‐wide SNPs identified through RADseq. We found strong genetic differentiation within the Alps with four genetic clusters, indicating western, central, and eastern refuges, and a strong reduction of genetic diversity from west to east. This reduction in diversity may suggest that the southwestern refuge was the largest one in comparison to other refuges. Also, the high genetic diversity in the west may result from (a) admixture of different western refuges, (b) more recent demographic changes, or (c) introgression of lowland L. tityrus populations. At small spatial scales, populations were structured by several landscape features and especially by high mountain ridges and large river valleys. We detected 36 outlier loci likely under altitudinal selection, including several loci related to membranes and cellular processes. We suggest that efforts to preserve alpine L. tityrus should focus on the genetically diverse populations in the western Alps, and that the dolomite populations should be treated as genetically distinct management units, since they appear to be currently more threatened than others. This study demonstrates the usefulness of SNP‐based approaches for understanding patterns of genetic diversity, gene flow, and selection in a region that is expected to be particularly vulnerable to climate change.Understanding factors influencing patterns of genetic diversity and the population genetic structure of species is of particular importance in the current era of global climate change and habitat loss. These factors include the evolutionary history of a species as well as heterogeneity in the environment it occupies, which in turn can change across time. Most studies investigating spatio‐temporal genetic patterns have focused on patterns across wide geographic areas rather than local variation, but the latter can nevertheless be important particularly in topographically complex areas. Here, we consider these issues in the Sooty Copper butterfly ( Lycaena tityrus in the European Alps at different spatial scales. SNP analyses showed a strong genetic differentiation between populations in the European Alps, a decrease in genetic diversity from west to east, and a clear separation of the dolomite populations. At a smaller scale, high mountain ridges and large river valleys hampered gene flow and structured populations.We aim at unraveling the spatial and historical factors having shaped the contemporary genetic structure of the butterfly  Lycaena tityrus is a widespread butterfly of the temperate zone with a range from Western Europe to central Asia . We followed the manufacturers' instructions but included an additional step of RNase A treatment. Afterward, we applied double‐digest restriction site‐associated DNA sequencing (ddRADseq) following Trense et al. , 0.1 µl (100 units) Phusion® HF DNA Polymerase (New England BioLabs Inc.), nuclease‐free water, and 2 µl (10 µM) each of Illumina P1 and P2 primers  in coancestry version 1.0.1.9  in the package “raster”  iterations, each with a burn‐in of 100,000 and a thinning interval of 9,999.To test for isolation by distance, we calculated pairwise genetic distances between individuals according to Bray Curtis , while the data for grass cover, tree cover, and water bodies were taken from Copernicus (land.copernicus.eu), and for roads from the Global Roads Inventory Project (GRIP) dataset of the global biodiversity model for policy support (globio.info). We used the digital surface model from Copernicus to generate the slopes using the function Slope in the Raster‐analysis in QGIS version 3.14 (www.qgis.org). The packages “raster” and “rgdal” in R were used for identical landscape features in resolution, extent, and projection. For Maxent distribution modeling, we selected default settings but changed the random test percentage to 25. We used the reverse suitability values of Maxent estimates for the landscape features . We then ran circuitscape version 4.0 , we first modeled the distribution of the 30 2.6arlequin version 3.5  in the package “LEA”  with 100 repetitions for each K. The minimal cross‐entropy value was selected to visualize the genetic clustering. Based on the results of the eems analysis which indicated that major river valleys and high mountain ridges may comprise genetic barriers for this species  were defined  method as implanted in d Figure . For thed Figure . We set 2.8FST outlier analyses were performed to minimize the risk of false positives, namely, baypass version 2.1  in the package “LEA” in R to find outlier SNPs linked to altitude and different temperature variables . We controlled for a false discovery rate in baypass, bayescan, and lfmm. SNPs were considered as potential outliers if the p‐values were below 0.05, FST were above 0.1, and at least two out of the three outlier analyses identified them as SNPs under selection. We searched for the sequences of the respective SNPs and corresponding protein sequences in the genome annotation of Calycopis cecropis (Lepidoptera: Lycaenidae) v. 1.1 using samtools version 1.2  for functional analysis of the identified proteins.To identify potential outlier loci linked to altitude, we used the altitude of each sampling location; that is, the individuals of one location were assigned the same altitude. Three different Gautier, , FDIST2  1.2 Li, . For cha33.1ml‐relate confirmed all putative pairs of full‐ and half‐siblings. All pairs of full‐siblings were found within the same sampling location. In four out of the 114 putative pairs of half‐siblings, the half‐siblings were found in different populations , separated by a geographic distance of 24 km and an altitudinal distance of 160 m a.s.l. All others occurred at the same location.Comparisons of relatedness across all 268 individuals revealed seven probable pairs of full‐siblings (0.607 < TrioML < 0.291) and 114 probable pairs of half‐siblings (0.246 < TrioML < 0.126). The program 3.2r = 0.574, p < .0001; Figure r = 0.033, p = .170). The eems analysis showed several dispersal barriers  ranged from 0.086 to 0.137, and the geographic (Euclidean) distance between sampled populations ranged from 6.2 to 254.4 km. Mantel tests for isolation by distance showed a significant correlation between genetic and Euclidean distances , eastern (8), southeastern (2), and a central cluster . Nine outlier SNPs were found to be linked to both altitude and different temperature variables.In total, we identified 514 SNPs as potential outliers according to altitude with at least two analyses. 4L. t. subalpinus populations in the European Alps, indicated by (a) relatively high FST values between populations, (b) evidence for isolation by distance and resistance, (c) genetic barriers separating populations and population clusters , and (d) a high number of half‐siblings within populations. These findings are expected if L. t. subalpinus is a relatively sedentary butterfly forming closed populations  seemed to have a large impact on the genetic structure of ts Table  and 6. HErebia butterflies , and eastern Alps, with the southeastern population cluster originating from the eastern refuge. Interestingly, the different genetic clusters in our study are characterized by striking differences in genetic diversity, being high in the western, intermediate in the central, and low in the eastern and especially in the southeastern cluster. These data suggest that the largest glacial refuge of L. t. subalpinus was located in southwestern Europe or at the southwestern edge of the Alps. This refuge may have included the lowlands between the western Alps and the Pyrenees, as the alpine subspecies occurs in both mountain areas, which may thus indicate relict populations  the eastern cluster is currently unclear. Thus, while the large‐scale population structure of L. t. subalpinus is likely shaped by the last glacial period, local and regional factors may also be important.In addition to effects of the last glaciation, the patterns found could be also influenced by more recent developments. In the dolomites, for instance, L. t. subalpinus represents an evolutionary significant unit for conservation, based on substantial morphological, ecological, and genetic differences compared to the lowland form L. t. tityrus ; Data curation (lead); Formal analysis (lead); Investigation (lead); Methodology (lead); Visualization (lead); Writing‐original draft ; Writing‐review & editing . Ary A. Hoffmann: Conceptualization ; Data curation ; Formal analysis ; Software ; Visualization ; Writing‐review & editing . Klaus Fischer: Conceptualization ; Data curation ; Formal analysis ; Funding acquisition (lead); Investigation ; Methodology ; Project administration (lead); Software ; Visualization ; Writing‐original draft ; Writing‐review & editing .Appendix S1Click here for additional data file.


Arab populations are largely understudied, notably their genetic structure and history. Here we present an in-depth analysis of 6,218 whole genomes from Qatar, revealing extensive diversity as well as genetic ancestries representing the main founding Arab genealogical lineages of Qahtanite (Peninsular Arabs) and Adnanite . We find that Peninsular Arabs are the closest relatives of ancient hunter-gatherers and Neolithic farmers from the Levant, and that founder Arab populations experienced multiple splitting events 12–20 kya, consistent with the aridification of Arabia and farming in the Levant, giving rise to settler and nomadic communities. In terms of recent genetic flow, we show that these ancestries contributed significantly to European, South Asian as well as South American populations, likely as a result of Islamic expansion over the past 1400 years. Notably, we characterize a large cohort of men with the ChrY J1a2b haplogroup , identifying 29 unique sub-haplogroups. Finally, we leverage genotype novelty to build a reference panel of 12,432 haplotypes, demonstrating improved genotype imputation for both rare and common alleles in Arabs and the wider Middle East. Arab populations are relatively understudied, especially their genetic architecture and historical relationship with early founders of the ancient Near East. Here, the authors examine 6,218 Qatari whole genomes, revealing insights on migration, population history and genetic structure of populations across the Middle Eastern region. The lack of sufficient whole-genome data from this region has limited large-scale analysis of its diversity and disease risk in Arab populations. Previous studies using hundreds of subjects gave insight to the history of these populations and impact of high consanguinity and tribalism on the prevalence of genetic diseases8. Indigenous Arabs were shown to form an outgroup to non-Africans and have little Neanderthal ancestry, suggesting their migration out of Africa instead of back to Africa9. Evidence from ancient human DNA suggested that the earliest populations of the Near East (which overlaps with contemporary Middle East), were derived from a Basal Eurasian lineage with minor Neanderthal admixture, and populated Anatolia, Levant and Iran prior to spreading to Europe, East Africa and Eurasian Stepp, respectively10. Iranian farmers arrived in Western Mediterranean by the Bronze age, during which this region was populated by a mix of Iranian, Steppe and North African ancestries11. The exact relationship between modern Arabs and the early founders of the ancient Near East remains unclear.The Middle East constitutes a historic intersection of human civilization and migration14. Here, we analyze the dataset from Phase 1 of the Qatar Genome Program (QGP) which aims to sequence the genomes of the population of Qatar (https://qatargenome.org.qa). We study its genetic structure in the context of regional history of admixture and migration, and build a reference panel to enable better genotype imputation for Arab and related ethnicities. There exist multiple reference panels from large-scale studies which improved imputation accuracy of low-frequency and rare variants19  including for specific populations23. However, they perform poorly for under-represented ancestries such as those from the Middle East26.The Qatari population, with its history and geographical location Fig. , constit27 (https://www.qatarbiobank.org.qa), QGP dataset (Methods). Sequencing was performed using Illumina HiSeq X10 at Sidra Medicine (https://www.sidra.org) achieving a mean coverage of 30x. Joint processing was performed using GATK following its Best Practices Pipeline (https://gatk.broadinstitute.org/hc/en-us/articles/360035894711-About-the-GATK-Best-Practices) and high-quality calls were retained. For the 6218 samples, 74,783,226 Single Nucleotide Variants (SNVs) and 6,560,138 Indels were obtained (Supplementary Table n = 2504)28, The Human Origin project 29, the Greater Middle East study 6 as well as previously published whole genomes of Qataris (n = 105)14 (Methods).We used whole-genome sequencing data on 6218 predominantly healthy individuals recruited from the general population at Qatar Biobank30, we found PC1 distinguishes 1KG AFR from other populations, PC2 distinguishes 1KG EAS, while lower PCs distinguish 1KG EU, SAS and Americans (AMR). QGP samples form a continuous density that projects on various PCs and is largely separable from 1KG samples. In comparison to Middle Eastern populations , followed by South Asians (SAS), Europeans (EUR) and lowest with East Asians   and exomes (n = 1005) found 3 and 7 ancestral components respectively14 and a study on 1KG which found 8 components that uniquely described the underlying non-admixed continental populations16. In our analysis, consistently we see that starting from k = 8 we get distinct ancestral components describing the 1KG populations and this persists with higher k values , two are dominant in Qataris and other Middle Eastern subjects and also found in South Europeans, South Asians and Admixed South Americans (blue and red). In addition, QGP has two minor components representing predominantly Africans and South Asians, colored in orange and yellow respectively. One QGP individual is found to have EUR ancestry (purple). Dominant East Asian and Native American ancestries (green and pink respectively) are absent from QGP.Next, we ran ADMIXTUREBy assigning a major ancestry for each sample based on the dominant ancestral fraction (>0.5), most QGP samples 81%) were found to be grouped to five distinct clusters with major ancestral components Fig. . We colo1% were fBy applying higher thresholds for defining dominant ancestry, we obtained smaller non-admixed clusters that are distantly separated by PCA  further subdivided the k = 8 clusters in a hierarchical manner leading to many clusters with less than 10 subjects , both k values gave robust classifications reflecting different levels of resolution. To obtain a broad insight to population structure and maximize statistical power, we refer below to the main 5 clusters of the QGP populations based on the k = 8 analysis unless indicated otherwise.Clustering based on 29. As highlighted in Supplementary Fig. 14  revealed that PAR has the highest degree of differentiation relative to all 1KG populations, especially African (Mean FST = 0.148). GAR and WEP show relatively less differentiation versus non-Africans. The QGP African and South Asians are shown to be close to their 1KG counterparts (Mean FST = 0.036 and 0.042 respectively) . We tested all possible  combinations for the QGP subpopulations and eight representative populations from Africa , Europe , South Asia , and America  . As depicted in Fig. 39  and is much earlier than the split between LWK and YRI (16 kya). While the QGP African group may reflect admixture due to recent slave trade, its African ancestry seem to have diverged relatively early from both African and Arab populations.Split time analysis shows that PAR, GAR and WEP have a common founder population, with PAR and WEP splitting 20 kya while PAR and GAR splitting 12 kya Fig. . This wa34 using the QGP dataset against 352 published ancient human genomes previously discovered in Africa, Levant, Iran, Anatolia and Europe dating back to various archeological periods ranging from Upper Paleolithic to Iron age43 . These ROH regions are of medical interest because they can be associated with autozygosity of deleterious founder mutations47. In terms of population structure, short, medium and long ROH respectively reflect ancient haplotypes predating continental migration, background relatedness and recent parental relatedness49. The QGP cohort was not targeted for specific family relationships, therefore it is likely to represent the sampled population. Consistent with previous observations, QGP had significantly higher inbreeding coefficients (F) relative to other world populations . Next, we leveraged the dataset to perform ROH analysis at large scale using whole-genome sequencing data, which is known to be more accurate than based on exome data50. We called ROH for each individual and run a Gaussian Mixture model per population to classify it to short, median and long ROH classes48, which is more accurate than adopting class boundaries form Caucasian populations as done in Scott et al.6. ons Fig. . This isR = 0.55–0.78; p < 0.0001)  unlike for long ROH. Despite having higher cumulative long ROH, PAR, WEP and GAR have lower long ROH counts than non-admixed Americans, which highlights the background relatedness caused by historical isolation of the latter population. In comparison with previous studies on Middle Eastern populations such as Scott et al.6, we saw longer ROH fragments (exceeding 80 MB), which is likely due to the larger sample size and the use of WGS versus exome/array data50. In line with the trend of cumulative total ROH, the median count of OMIM genes overlapping with ROH is generally lowest among African populations and highest among non-admixed American populations. QGP showed the largest spread whereby individuals are found with more than 4000 ROH-overlapping disease genes  and mitochondrial DNA (mtDNA) gave useful insights into world population migration, including tracing the origin and expansion from the Middle Eastous Fig. . U is lan = 1524) , abundant in GAR (77.0%) while it is modestly present in WEP (16.7%), SAS (12.5%) and AFR (7.9%). Most subjects in this J1 clade were assigned the J1a2b haplogroup   while E1 and H1 are most dominant in AFR (58.3%) and SAS (31.3%) respectively. Homogeneity of PAR individuals supports the uniqueness of this subpopulation suggested by the earlier autosomal ancestry analysis  Fig. . J1 is k6%) Fig. . Thus, t−5 to 4 × 10−3 and searched for a cut-off that resulted in the maximum number of large clusters (sample size >10)  was obtained using a 5 × 10−4cut-off. In total, 331 informative SNPs were found to distinguish these clusters based on FST = 1  by an average of 2–3% per 100 samples. Therefore, the current cohort would still benefit from sequencing additional samples, yet it is adequately sized to capture variants common in this population for the purpose of imputation. To build this panel, we used the high-quality set of 68,107,887 autosomal SNVs for 6216 individuals obtained by filtering out variants with missingness >1% and HWE p value < 10−5. We did not include short indels at this stage as they are generally less reliable and require validation. Using these SNVs, phased haplotypes were produced and converted to Minimac 3 format59. This QGP panel has some key features. Unlike many of the large publicly available panels, all samples were collected, sequenced and processed in the same site and show consistently high coverage. Also, it has relatively high diversity. While having ~80% less samples than the Haplotype Reference Consortium (HRC) panel, it contains almost double the number of variants, and that is only marginally fewer than the worldwide 1KP panel  and HAPMAP2 (http://www.hapmap.org). From the known whole-genome genetic variation of these individuals, we created three pseudo arrays with different marker densities based on CoreExome (https://www.well.ox.ac.uk/~wrayner/strand/humancoreexome-12v1-1_a-b37-strand.zip), Affymetrix 6.0 (https://www.well.ox.ac.uk/~wrayner/strand/GenomeWide_6-b37.58-v2.zip) and Illumina 5 m (https://www.well.ox.ac.uk/~wrayner/strand/HumanOmni5-4v1-1_A-b37-strand.zip). Genotypes imputed using these pseudo arrays based on the various panels were compared to the known genotypes and level of concordance (R2) was calculated for multiple bins of alternative allele frequency (AF)  is generally higher by using the QGP panel (by 57.1% for AF < 1% versus HRC and by 30.9% for AF < 5% versus 1KG) and so are the respective Minimac imputation scores  Fig. . The QGPres Fig. . HRC andThis study provides an in-depth analysis of the genomic structure of the QGP phase 1 cohort, representing a comprehensive set of genomes from a Middle Eastern population. Despite the relatively small size of Qatar, it revealed unique and shared ancestries reflecting the wider Middle Eastern region and its centrality to recent and distant history.12, identifying five main distinct ancestries that are generalizable to Arab and other Middle Eastern populations . PAR, GAR and WEP were found to be descendants of the main Arab genealogical branches of Qahtanite and Adnanite, which refer to indigenous Arab and Arabized populations respectively. The terms ‘Arab Bedouin’ and ‘indigenous Arab’ were used interchangeably in previous studies, however we find that in many cases this is inaccurate. Modern gene flow was identified from these ancestries to various European, South Asian and South American populations, likely reflecting post-Islamic expansion.The large dataset allowed the refinement of previously described genetic ancestries in the Qatari population We performed an estimation of time divergence of Arab populations using hundreds of genomes. This pointed to an ancestral Arab population that dominated the Levant region, and split into modern lineages around 12–20 kya. Analysis involving ancient human DNA dating back to various archeological periods indicated that Peninsular Arabs are ancestral to modern Middle Eastern ancestries, being the closest to the basal founders that populated the ancient Near East. The sequencing of ancient genomes from the Arabian Peninsula will shed more light on the contribution of native Arabs to early out-of-Africa migrations.8. Population-specific boundaries defining various ROH classes were calculated, showing an upper shift in Arab in comparison to world populations. Arabs also exhibited the least short ROH after African populations, reflecting their proximity to out-of-Africa migrations.In addition to enhancing the resolution on population structure, we performed ROH analysis using whole-genome data for a Middle Eastern population and at large scale, identifying some of the highest levels of human ROH ever reported to date. This highlights the tribal, endogamous nature of Arab society and culture, as well as the utility of next-generation sequencing to uncover recessive founder pathogenic alleles in high consanguinity settingFurthermore, we report a substantial number of sequenced individuals having the J1a2b haplogroup which we further characterize into 29 novel sub-haplogroups. These sub-haplogroups were found to partition well among the autosomal ancestries, reinforcing the tribal, patrilocal nature of the regional populations.61. The value of this resource will expand in the upcoming phases of QGP as tens of thousands of additional subjects will be sequenced over the next few years, enabling vital future genomic and medical research in the Middle East and globally.Finally, a dedicated QGP imputation panel was generated to leverage this dataset, which shall complement the currently available panels by providing more accurate imputation of Arab and Middle Eastern genomes. This will enable association studies with greater scale and statistical power to detect causal variants underlying biological traits and diseases. Notably, there is an ongoing effort to build a population genotypic array (Q-chip) that would leverage rare and novel missense/LoF variants in disease genes from this panel . The current dataset has recently helped identify novel loci associated with a range of clinically relevant traitsThe current study used data related to peripheral blood samples for 6218 adult subjects (age ≥ 18) collected as part of Qatar Genome Project (QGP) phase 1. These individuals were Qatari nationals randomly recruited from the general population at Qatar Biobank. They all signed an informed consent form prior to their participation, and the study was approved by Hamad Medical Corporation Ethics Committee and QBB institutional review board. Their samples were transferred to Sidra Medicine where their genomic DNA was extracted and used to perform whole-genome sequencing.62. BAM files were compressed from SAM then sorted and indexed respectively using view, sort and index functions in SAMtools v1.263. PCR duplicates were then marked using Picard v1.117 MarkDuplicates.jar (http://broadinstitute.github.io/picard). Genome Analysis Toolkit (GATK) v3.464 was used to do further BAM improvements, including realignment around known indels and base quality score recalibration. Single-sample genotypes were called by GATK HaplotypeCaller algorithm (-ERC GVCF). All gVCF-files were combined (-T CombineGVCFs) and jointly called (-T GenotypeGVCFs).DNA extraction was performed on Qiasymphony automatic system (QIAGEN). Standard library preparation was done for all samples using a PCR-free sample preparation. Libraries were sequenced on Illumina HiSeq X Ten  according to the manufacturer’s recommendations. 150 bp paired-end reads were used to the mean coverage of 30x with a median insert size of 400 bp ± 25%. Data generation used HiSeq X Illumina Software v3. Sequencing reads were aligned to GRCh37/hg19 human reference genome using BWA-MEM v0.7.7The original set of 6218 samples yielded sufficient input DNA (>1.2 ug) and had successful library preparation and low contamination rate (<10%).GATK Variant Quality Score Recalibration was performed on the variants and only Single Nucleotide variants (SNVs) annotated as PASS were considered in further analysis.65. All samples were found to have total missingness levels <0.05 except for one sample that had missingness of 0.81. Per chromosome missingness identified an additional sample which had missingness level of 0.52 for chromosome 18. These two samples were excluded from further analysis. rtg-tools v3.8  was used to calculate the number of variants, non-reference variants (ALT), heterozygous variants (HET), HET/(HET + HOM) ratio, transition/transversion (TITV) ratio per sample in order to identify any outlier samples (below or above 3 SD from the population mean). Also, genotype and phenotype sex concordance were checked for each sample. The final set that was retained contained 6216 samples.Regarding sample QC, per sample missingness was calculated using vcftools v1.9P value < 10−5 and variants in low-complexity regions. At the end we obtained a clean set of 69,830,209 variants for downstream analysis.With regard to variant filtering, variants with missingness rate of >1% were excluded. In addition, we filtered out variants with minor allele count ≤2, Hardy–Weinberg equilibrium test 28, Human Origin dataset29, GME6, Kuwaiti13 and Qataris from non-QGP14. HO contains 587 individuals genotyped with Affymetrix array from the Middle Easter region including Arabian Peninsula , Levant , Turkey (n = 56), Iran (n = 46), North East Africa , North West Africa , various Jewish communities (n = 67) in addition to West Eurasia (n = 104) and East Africa (n = 59). GME has 731 exomes from Arabian Peninsula , Levant , Turkey (n = 138), Iran (n = 55), Iraq (n = 5), North East Africa , North West Africa  and Jews (n = 10).Datasets used for comparison are from 1KG project66 on SNVs shared between QGP and 1KG, those shared between QGP, 1KG and other reference samples from Human Origin dataset42, Greater Middle East dataset and previously published Qatari genomes14, and those shared between the later and Kuwaiti13. In the three cases, the shared SNVs were filtered based Linkage Disequilibrium (LD) cut-off 0.2, resulting in 14,396,599, 151,981 and 4238 variants respectively. Next, these were used as input for running PLINK to calculate the PCs. Given the diversity of the study samples, we did not exclude low frequency variants since they were shown to help with stratification67.Principal Component Analysis (PCA) was performed using PLINK v2.068, we intersected SNVs common to the datasets using bcftools isec  and filtered them based on Minor Allele Frequency (MAF) 0.05 and LD 0.2 using PLINK in order to achieve efficient computation time. This resulted in 351,181 variants which we used as input to run ADMIXTURE with five-fold cross validation by assuming various k values.To run ADMIXTURE v1.3.032. Starting from the VCF file containing the intersection set between QGP and 1KG pruned at LD 0.2 , the input file for TreeMix was generated using glactools v1.069. To meet the tool’s requirement, multiallelic sites were split and missing sites were replaced with reference. TreeMix was run using block size of 500 and bootstrap option, allowing for 0–5 migrations each in a separate analysis. The resulting maximum likelihood trees were plotted using iTOL (https://itol.embl.de).TreeMix analysis was performed on the combined QGP and 1KG datasets using TreeMix v1.334. For that we run qp3pop as part of ADMIXTOOLS v7.0.1 using default parameters34. F3 statistics test takes two source populations  and one target population C. The method estimates allele frequency correlations between A and B relative to C and by calculating the product of allele frequency differences between population C to A and B. A negative F3 statistics value suggests that C is indeed admixed with population A and B. The method also outputs a Z score as the deviation of the F3 statistic from zero in units of the standard error. Absolute Z > 3 suggests significant rejection of the null hypothesis that F3 statistics is not negative. We ran the F3 statistics test using all possible three-population combinations from the QGP subpopulations  and eight representative 1KG populations .F3 statistics test was used to assess genetic contribution of QGP populations to various modern world populations and vice versa38. This was run using multiple genomes per Qatari subpopulations  and eight 1KG populations representing Africa , Europe , South Asia  and East Asia . As recommended by the software’s authors (https://github.com/popgenmethods/smcpp) we first ran vcf2smc subcommand per population to convert SNP data for chromosomes 1 to 22 to SMC++ format, masking centromeres. This was followed by estimate subcommand which calculates for each population the effect population size as a function of time. For that, we used per-generation mutation rate of 1.25e−8, piecewise spline, knots 24 and timepoints in generations as t1 = 33 and tn = 34,000. Next, we created a SMC++ pairwise population dataset using the vcf2smc subcommand masking the centromeric region as before. Using the per population SMC++ data and JSON file from estimate, in addition to the pairwise population SMC++ data, we ran the split subcommand with timepoints t1 = 33 and tn = 34,000 to generate the pairwise population JSON file. The split subcommand fits two-population clean split models using marginal estimates produced by estimate. The plot subcommand was used to generate a CSV file form the obtained output which we plotted using internal scripts.We estimated population size trajectories and divergence time between populations using SMC++ v1.15.4n = 352)43 was downloaded in Eigenstrat format from https://reich.hms.harvard.edu/sites/reich.hms.harvard.edu/files/inline-files/NearEastPublic.tar.gz, and combined with QGP data. This was used as input for qpDstat program in ADMIXTOOLS v5.134 to calculate Patterson’s D-statistic which assesses the contribution of ancient human genome ancestries to QGP PAR relative to QGP and 1KG populations representing Europe , Africa (LWK) and South Asia (PJL). The D-statistic compares counts of the derived ancient genomes alleles versus distant outgroup alleles (Chimpanzee) in QGP PAR and a comparison population from QGP and 1KG. D-statistic calculation requires four populations: a comparison population (w), a basal population (x = QGP PAR), an ancient population (Y) and a distant outgroup (Z = Chimpanzee). Excess of Y alleles in W compared to PAR results in a positive D-statistic, meaning higher ancient ancestry in W compared to PAR, and vice versa. The higher the D-statics the higher the significance. Also, Z-scores are calculated whereby D-statistics with absolute Z > 3 is generally considered significant.Ancient human genomes data from previously published studies  were calculated using BCFTools v1.9 (with RoH extension) which uses a hidden Markov model optimized for whole-genome sequencing data64 was used to call SNPs and Indels from mitochondrial DNA (mtDNA) and chromosome Y (Chr Y) for all QGP samples (n = 6216) and QGP males only (n = 2687), respectively. SNPs only were retained for downstream analysis. Multiallelic sites were split and variants with missingness levels > 1% were excluded. mtDNA haplogroup assignments were made using HaploGrep v2.1.2071 which relies on PhyloTree catalog build 1772. Chr Y assignments were made using yhaplo v1.0.18 (https://github.com/23andMe/yhaplo) which uses reference haplogroups from the International Society of Genetic Genealogy73.A version of GATK supporting haploid chromosome calling (based on v3.4)74. For that, we focused on a 10-Mb region on Chr Y known to be amenable to analysis based on short read sequencing, excluding singletons and SNPs with missingness levels >1%76. vcf2phylip v2.3 (https://github.com/edgardomortiz/vcf2phylip) was used to convert VCF to FASTA format which was used as input to run RaxML using 100 rapid bootstrap searches and 10 maximum likelihood searches.In order to further characterize the set of 1426 samples that were assigned to J1a2b haplogroup, we run RaxML v8.0 which performs Maximum-likelihood based phylogenetic inference77 by applying multiple genetic distance cut-offs ranging from 1 × 10−5 to 4 × 10−3. The lower and upper boundaries of this range produced the maximum and minimum number of non-singleton clusters, respectively. Branches supported by Bootstrap values <0.9 were collapsed. Trees were plotted using iTOL 9 (https://itol.embl.de).Clusters within the resulting phylogenetic tree were defined using ClusterPicker v1.2.3FST score using a version of vcftools that supports haploid genotypes (v.0.14)65 and selecting SNPs with FST = 1.For each genetic distance cut-off, informative SNPs fixated to individual clusters were identified by calculating FST = 1 and AF = 1 in the respective cluster.A haplogroup was defined for each non-singleton cluster as the list of SNPs with 78, which takes into account the number of SNPs for a given haplogroup, mutation rate and average number of years per human generation. Statistical significance of difference in estimated date of divergence of sub-haplogoups between pairs of QGP subpopulation groups was calculated using Wilcoxon Rank Sum/Mann Whitney Test.Lineage dating for each haplogroup was calculated using the method of Poznik et al.http://www.ncbi.nlm.nih.gov/SNP). Imputed variants were annotated using Variant Effect Predictor79 version 84 which uses Ensembl database v8480 and Genecode v19 on GRCh3781.Variants were annotated using dbSNP build 151  was phased using Eagle (v2.3.5) with reference-independent parameter82. For that, bcftools missing2ref plugin was used to annotate missing sites to the reference allele and multiallelic sites were split, as required by the tool. Phasing accuracy was defined as the number of switch errors present in the phased data set. The phased haplotypes were then converted to Minimac 3 format59.Processed QGP phase 1 dataset (Where we excluded SNVs with missingness rate of >1% and Hardy–Weinberg equilibrium test 59 with default parameters. High-confidence imputed variants were defined as having Minimac 3 r2 score >0.5.Imputation using the various reference panels were performed on a High-Performance Computing Cluster at Sidra Medicine using Minimac3https://github.com/winni2k/measureAggregateRsquared) to calculate concordance between imputed and observed genotypes in order to assess performance of imputation using various combinations of arrays and imputation panels. Comparisons were performed for five allele frequency bins defined with the thresholds . Also, comparisons were performed by further filtering on Minimac3 r2 score.We used measureAggregateRsquared developed at Welcome Trust Center for Human Genetics (Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Conservation of plant genetic resources, including the wild relatives of crops, plays an important and well recognised role in addressing some of the key challenges faced by humanity and the planet including ending hunger and biodiversity loss. However, the genetic diversity and representativeness of ex situ collections, especially that contained in seed collections, is often unknown. This limits meaningful assessments against conservation targets, impairs targeting of future collecting and limits their use.M. acuminata subsp. banksii (Papua New Guinea), M. balbisiana (Viet Nam) and M. maclayi s.l. . We sequenced 445 samples using suites of 16–20 existing and newly developed taxon-specific polymorphic microsatellite markers. Samples of each species were from five populations in a region; 15 leaf samples from different individuals and 16 seed samples from one infructescence (‘bunch’) were analysed for each population.We assessed genetic representation of seed collections compared to source populations for three wild relatives of bananas and plantains. Focal species and sampling regions were M. acuminata, M. balbisiana and M. maclayi respectively). Seed samples represented all common alleles in populations but omitted some rarer alleles. The number of collections required to achieve the 70% target of the Global Strategy for Plant Conservation was species dependent, relating to mating systems. Musa acuminata populations had low heterozygosity and diversity, indicating self-fertilization; many bunches were needed (> 15) to represent regional alleles to 70%; over 90% of the alleles from a bunch are included in only two seeds. Musa maclayi was characteristically cross-fertilizing; only three bunches were needed to represent regional alleles; within a bunch, 16 seeds represent alleles. Musa balbisiana, considered cross-fertilized, had low genetic diversity; seeds of four bunches are needed to represent regional alleles; only two seeds represent alleles in a bunch.Allelic richness of seeds compared to populations was 51, 81 and 93% (We demonstrate empirical measurement of representation of genetic material in seeds collections in ex situ conservation towards conservation targets. Species mating systems profoundly affected genetic representation in seed collections and therefore should be a primary consideration to maximize genetic representation. Results are applicable to sampling strategies for other wild species.The online version contains supplementary material available at 10.1186/s12870-021-03142-y. Conservation of crop wild relatives (CWRs), wild plant species related to crops, is increasingly recognized as a vital component of both sustainable development for food security   and biodConservation of CWRs should complementarily include both in situ and ex situ approaches . Ex situPresently, for seed collectors to maximise genetic capture in collections, sampling guidance is often broad, encompassing all species, or inferred from taxonomically or ecologically related species –15. The Musa L.) is a case in point. Bananas, together with related plantains (both are Musa), are the most important fruit and among the most important crops in the world [Musa [. They are tall herbaceous monocarpic monocotyledons native to tropical and subtropical Asia and the western Pacific. Most cultivated bananas and plantains derive from two species: M. acuminata subsp. and M. balbisiana [M. maclayi [Seed conservation of banana CWRs .Table Musa species were assessed as insufficiently conserved ex situ [Musa species are therefore not represented in genebanks at all or are represented with little or as yet unknown representativeness. An evaluation of the genetic representation of present collections will help target future conservation efforts.Conservation of banana CWRs is increasingly important because they are under threat. In a recent study , 15% of  ex situ . There a ex situ . Additio ex situ . Many MuThe objectives of the present study are to assess and compare the genetic capture in seed collections compared to their source populations, at both regional and local scales, for three focal species; to provide guidance about how to maximize genetic capture for future seed collections; and to provide direction for seed distribution on how to provide representative seed samples.M. acuminata, M. balbisiana, and M. maclayi, Table AR) of populations and seeds of M. maclayi was much higher than the other two species. In general, populations had many alleles that were private (PA); seeds had a few PA - indicating that some pollination occurred by plants not present in population samples. Only two alleles in M. acuminata seeds were private.Allelic richness of seeds as a proportion of populations was 51, 81 and 93% : t = 4.595, df = 4.310, p = 0.008; Simpson’s index (λ): t = 3.163, df = 4.018, p = 0.034). Musa balbisiana seed diversity was also significantly lower than populations . However, diversity of seeds and populations of M. maclayi was not significantly different . Observed heterozygosity (Ho) was also significantly lower in seeds compared to populations for M. acuminata , and M. balbisiana , but not for M. maclayi .Diversity of M. acuminata was on average 3.84, for M. balbisiana 6.18 and for M. maclayi 18.64  apart from M. balbisiana populations where they were approximately equal. The disparity was especially evident for M. acuminata population and seeds, and M. balbisiana seeds. Evenness (E5) was high (> 0.9) across all sampling groupings but less so for M. acuminata seeds (E5 = 0.684). M. acuminata seeds and populations had the lowest diversity in all sampling groups. Fewer multilocus genotypes were observed in M. acuminata populations and, to a greater extent, seeds, compared to the number of actual samples - suggesting clonality or self-fertilization of homozygous mother plants; this was also observed in M. balbisiana seeds but to a lesser extent. Heterozygosity was very low in M. acuminata and M. balbisiana, but high for M. maclayi. There was no evidence of null allele excess, large allele drop out and error due to stuttering in M. balbisiana or M. maclayi. Six out of the 19 loci for M. maclayi showed potential null allele excess, possibly inflating homozygosity beyond predicted values, however, homozygosity was high across all loci  where Ho was zero , notably seeds from this population were completely homozygous (Ho = 0). Sandaun was the least diverse M. acuminata population (Hexp = 0.06). Inbreeding coefficient (Fis) was high for all M. acuminata populations, Vanimo being the most inbred (Fis = 0.97), its seeds were also completely homozygous. The Ramu population was the least inbred (Fis = 0.41), and had seeds with the highest heterozygosity (Ho = 0.05). Musa balbisiana populations are also characterized by a low degree of diversity, yet inbreeding coefficients were much lower compared to M. acuminata. By contrast, populations of M. maclayi were characterized by a high level of heterozygosity and genetic diversity and low inbreeding coefficients. Populations of M. balbisiana and seeds of M. maclayi had negative Fis meaning an excess of heterozygotes.ro Table . Hexp vaM. acuminata 70%, M. balbisiana 75%, M. maclayi 82%). This means that in order to maximize genetic capture in seed collections, targeting local populations is less important than increasing the number of bunches collected. This also reflects the real experience in seed collecting because the genetic structure of subpopulations is usually not known at the time of collecting. Knowing how many local collections to make is therefore more informative.Most variance found in population samples was within local populations rather than between local populations, according to AMOVA . Genetic distance [M. acuminata genetic distance was low between all samples. Populations and seeds from Vanimo were most distant from other samples. Seeds clustered with their respective populations for Vanimo and Sandaun, but not for other populations of M. acuminata. For M. balbisiana, seeds from Na Bo and Seo Leng were most distant. Notably the outlier population of Khe Ngau was not more distant from other populations and seeds. Several populations and seed pairs of M. maclayi clustered together. There were two broad clusters with samples from the North West (Boku and Panguna) having greater distance from the other three populations. Isolation by distance was evident in M. maclayi populations and seeds , but not the other species.Genetic differentiation of local populations was detected using a permutation test on the AMOVA of population samples . M. acuminata only achieved 51% proportional allelic richness. In all cases several seed collections were required from different local populations to maximize genetic capture. The number of collections necessary to achieve the 70% target was species dependent. For M. acuminata it was > 15 local seed collections, for M. balbisiana four and M. maclayi three.Allelic richness of seeds as a proportion of populations met the conservation target of 70% from the Global Strategy for Plant Conservation  for two M. maclayi and, to a lesser extent, M. acuminata and M. balbisiana, were successful , seed bearing M. acuminata subsp. banksii are characterized by self-compatible hermaphroditic flowers, particularly in the upper hands on the inflorescence [M. acuminata var. chinensis [M. boman [M. jackeyi (interestingly closely related to M. maclayi) [M. ingens [M. rubinea [M. schizocarpa [M. yunnanensis [M. zainfui [Musaceae species, many mother plants must be sampled.A high degree of homozygosity and low level of diversity, apparent in populations and seed collections of a et al. , corrobolization . Unlike rescence , 37, therescence . Similarhinensis , M. bomaM. boman , M. jackmaclayi) , M. inge. ingens , M. rubi rubinea , M. schiizocarpa , M. yunnnanensis  and M. z zainfui . Seed coM. maclayi were characterized by higher levels of heterozygosity and diversity, consistent with cross-fertilization [M. maclayi are temporarily and physically isolated on the same inflorescence. Female flowers are produced first, followed by male flowers, as the peduncle grows [M. maclayi seeds therefore represent both the mother plant and pollen donors within the population. As a result, less bunches need to be collected to represent the population compared to M. acuminata. The level of diversity evident in the small number of populations of the present study was somewhat surprising, because of the narrow distribution and relatively recent diversification and dispersal of the former Australimusa group to which M. maclayi belongs [By contrast, populations and seeds of lization . Male anle grows . Genetic belongs . This deM. balbisiana, in our results, had low heterozygosity and diversity, this is in keeping with several previous studies [. Moreover, the heterozygosity of seed batches was much lower than within populations. Our results were similar to those found by Bawin et al. [M. balbisiana seeds collected from ex situ field collections or feral populations, but our seeds were less diverse than those collected from native populations in Yunnan (China). Even though M. balbisiana basal flowers are functionally female [M. acuminata [Ensete superbum with pollen from M. balbisiana [M. acuminata and M. balbisiana seeds observed.Populations of  studies , 55, 56.n et al.  for M. by female  and do ny female , flowersy female . Furthercuminata  and indulbisiana , and mayM. balbisiana, in our results, may be caused by a genetic bottleneck and/or founder effect. This hypothesis was also proposed by Ge et al. [Musa ecology: being early successional or disturbance-adapted [M. balbisiana makes them particularly vulnerable to genetic erosion from anthropogenic disturbance. Furthermore, as M. balbisiana has many uses by local communities [The low diversity in populations of e et al.  and Shepe et al.  and is i-adapted , 63. Add-adapted  may also-adapted , the ecomunities , plants Musa genus demonstrates the profound effect of mating system on genetic capture in seed collection. Taxonomic relatedness, therefore, is not a good proxy for a sampling strategy [Variation in genetic capture of different species of the strategy . In suppstrategy  found spstrategy .Musa seed collections, firstly, we recommend that species mating systems should be considered to inform sampling strategies. Our results are therefore in support of Brown and Marshall’s sampling strategy discussed above [To maximize genetic capture in ed above .Musa species, as many mother plants should be sampled from as possible. For species with wide distributions, populations should be spatially dispersed; however this is less important than increasing the number of plants collected from. Collecting seeds from many individuals of adequate quality for long term storage is highly challenging; it is not straightforward to find mature seeds in the forest suitable for storage [For self-pollinated  storage , 70. It  storage , or evenTo target collections of fully out-crossing species, fewer collections are required to represent regional alleles. We recommend collections should be focussed on increasing the number of local populations collected from rather than the number of mother plants in a population. Local populations should be spatially dispersed to maximize genetic capture. This will also allow for locally distributed alleles to be captured . The amoFor all species, but especially for out-crossing species, it is also important to target collections that are far from agriculture and human interference. Large and well established populations should be prioritised . This wiM. maclayi 16 seeds represent 70% of alleles, and 35–50 seeds represent 90% of alleles. Even so, these numbers of seeds are easily achieved, for most Musa species at least, where a bunch can contain hundreds to thousands of seeds. However, for some species we have collected (e.g. M. ingens), only a few seeds were found in a bunch, perhaps due to inadequate pollination. Additionally, these findings mean that despite low levels of survival in storage of some collections [To ensure enough seeds are conserved, self-pollinated species only require one or two seeds from a bunch to be part of a core collection. There is also very little point in using many samples of self-pollinated seeds in experiments. This contrasts with fully out-crossed seeds, where more seeds should be conserved in core collections per bunch or used as samples in experiments. For lections , 69, popM. balbisiana  have a profound effect on the level of genetic diversity in seed collections. The results of the present study may be applied in sampling strategies of other wild species, in that species mating systems should be a primary consideration to maximize genetic representation in seed collections.Musa species: M. acuminata subsp. banksii (F.Muell.) N.W. Simmonds, M. balbisiana Colla and M. maclayi s.l. F.Muell.  in June 2017 and May 2019 [M. balbisiana was collected in Viet Nam during November 2018 and April 2019. Musa maclayi was collected on the island of Bougainville (PNG) in October 2016 [Natural populations of focal species in their respective native ranges were sampled during several collecting missions that took place between 2016 and 2019 Fig. ; Table 1May 2019 , 74. M. ber 2016 , 76.FigLeaf and seed samples were collected from wild natural populations. All seeds, leaves and data were collected and transferred according to local legislation, with permission and supplied for non-commercial use and research under the Standard Material Transfer Agreement in accordance with the International Treaty on Plant Genetic Resources for Food and Agriculture. None of the species included in the present study are CITES listed. Formal field identification was carried out by Steven B. Janssens . Leaf samples were collected randomly from 5 local populations per species Fig. . From eaM. acuminata and all bunches of M. balbisiana, from pooled seeds from the whole bunch. Due to low seed numbers and viability of M. balbisiana accessions DNA was extracted directly from their embryos. An average of 16 seeds per bunch were used in this study.To overcome barriers associated with low and unpredictable in vivo germination, seeds were germinated by embryo rescue as described by Kallow et al. . Seeds wFor each population, exact coordinates were recorded with a Garmin GPS device. Detailed taxonomic field notes, and notes on geography and ecology, were recorded for each sample. Photographs of mother plants (the plant from which the bunch was taken) and of bunches were taken. Seed samples from PNG and Bougainville were accessioned into the Meise Botanic Garden seed bank . Seeds from Viet Nam were accessioned into the seed bank of Plant Resources Center .M. acuminata we developed mutiplexes from previous studies [M. acuminata samples. From this, 20 markers arranged in four multiplexes were selected. For M. balbisiana, we used the multiplex arrangement of Bawin et al. [M. maclayi, a total of 16 specific SSR markers were newly developed and optimized by Genoscreen  and arranged in four multiplexes. We used an M13 labelling protocol [. See We isolated DNA using a method adapted from Doyle and Doyle  and then studies , 78–83.  studies  and Mult studies  with 12 n et al. . These iprotocol  to arranM. acuminata data, eight for M. balbisiana and two for M. maclayi   and 90% sampling . Then thAR of seeds per bunch. For this, total AR of bunches was extrapolated [vegan package [ggplot2 [A similar approach was employed to estimate proportional cumulative apolated , and the package . Trend l[ggplot2 .http://bioinformatics.psb.ugent.be/webtools/Venn) and plotted them as Euler diagrams using the eulerr package [An initial assessment of population differentiation was made by carrying out a permutation test (999 permutations) on the AMOVA described above. Secondly, We made allele groupings for local seeds and regional populations ( package . Thirdly package , and proAdditional file 1: Supplementary Methods.Additional file 2: Table S1. Populations and samples used. Table S2. Microsatellite markers and multiplexes used. Table S3. Microsatellite summary statistics per locus. Number of alleles; 1-D, Simpson's index; Hexp, Nei's 1978 gene diversity; Evenness; species. Table S4. Null allele analysis for Musa acuminata loci.


Pseudomonasfluorescens. We exposed bacterial populations to an antibiotic treatment and then imposed a one‐individual‐size population bottleneck on those surviving the antibiotic stress. During the subsequent compensatory evolution, population size increased and leveled off very rapidly. The increase of diversity was of slower paces and persisted longer. In the very early stage of compensatory evolution, populations of large sizes had a greater chance to diversify; however, this productivity–diversification relationship was not observed in later stages. Population size and diversity from the end of the compensatory evolution was not contingent on initial population growth performance. We discussed the possibility that our results be explained by the emergence of a “holey” fitness landscape under the antibiotic stress.Biological populations may survive lethal environmental stress through evolutionary rescue. The rescued populations typically suffer a reduction in growth performance and harbor very low genetic diversity compared with their parental populations. The present study addresses how population size and within‐population diversity may recover through compensatory evolution, using the experimental adaptive radiation of bacterium  Bacterial populations lost diversity and showed reduced growth performance after an evolutionary rescue from environmental stress. During the subsequent compensatory adaptation, improvement of growth performance preceded ecological diversification, and the final population size and diversity were not contingent on initial population growth performance. The mode and pace of adaptation and diversification may be explained by a holey fitness landscape under environmental stress. Processes that may promote population survival in degraded habitats have been studied extensively, among which is evolutionary rescue  and ecological diversity (diversity relevant to niche differentiation) during compensatory adaptation, using a model microbial adaptive radiation system. Cultures of the bacterium 22.1P. fluorescens SBW25 was used in this study  was analyzed using Exact test (R package “Exact”).Data analyses were performed using R  and showed relatively high morphotype richness (4.79 ± 0.0641), comparable to earlier observations with this model adaptive radiation . Their morphotype richness was also lower than the source populations ; and the probability to diversify into two ecotypes was also smaller .Populations from the end of the compensatory evolution experiment grown in the presence of the antibiotic still had significantly lower population density compared with the source populations grown in antibiotic‐free medium ; data curation ; formal analysis ; funding acquisition (supporting); investigation (lead); methodology ; project administration (supporting); resources ; software ; supervision ; validation ; visualization ; writing‐original draft ; writing‐review & editing . Quan‐Guo Zhang: Conceptualization (lead); data curation ; formal analysis ; funding acquisition (lead); investigation (supporting); methodology ; project administration ; resources ; software ; supervision (lead); validation ; visualization ; writing‐original draft ; writing‐review & editing .Supplementary MaterialClick here for additional data file.