Knowledge on how adaptive evolution and human socio‐cultural and economic interests shaped livestock genomes particularly in sub‐Saharan Africa remains limited. Ethiopia is in a geographic region that has been critical in the history of African agriculture with ancient and diverse human ethnicity and bio‐climatic conditions. Using 52K genome‐wide data analysed in 646 individuals from 13 Ethiopian indigenous goat populations, we observed high levels of genetic variation. Although runs of homozygosity (ROH) were ubiquitous genome‐wide, there were clear differences in patterns of ROH length and abundance and in effective population sizes illustrating differences in genome homozygosity, evolutionary history, and management. Phylogenetic analysis incorporating patterns of genetic differentiation and gene flow with ancestry modelling highlighted past and recent intermixing and possible two deep ancient genetic ancestries that could have been brought by humans with the first introduction of goats in Africa. We observed four strong selection signatures that were specific to Arsi‐Bale and Nubian goats. These signatures overlapped genomic regions with genes associated with morphological, adaptation, reproduction and production traits due possibly to selection under environmental constraints and/or human preferences. The regions also overlapped uncharacterized genes, calling for a comprehensive annotation of the goat genome. Our results provide insights into mechanisms leading to genome variation and differentiation in sub‐Saharan Africa indigenous goats. Data on molecular changes have been critical in understanding genome architecture, maintaining biodiversity and fitness and exploring impacts of genome evolution. This has been made possible through the investigation of genetic diversity and structure, demographic dynamics , and samples with >5% missing genotypes, were filtered from the data set. This left 44,723 SNPs and 628 goats for analysis. A subset of these samples had been analysed for mtDNA D‐loop variation  and expected (HE) heterozygosity, proportion of polymorphic SNPs (PN) and average MAF were calculated with PLINK v1.9. The average pairwise genetic distances between individuals within a population were also calculated with PLINK v1.9. Higher values indicate elevated genetic distances and thus low genetic relationships. The average proportion of alleles shared between two individuals was calculated as DST using PLINK v1.9 with the “–genome” command line:1 and IBS2 represent the number of loci which share either one or two alleles that are identical by state in pairwise comparisons between individuals, respectively, and N is the number of loci tested. The genetic distance between all possible pairwise combinations of individuals was calculated as D = 1−DST.To estimate genetic diversity, observed . The ROH was classified into four length categories: 2, 4, 8 and 16 Mb.Detection of ROH was performed by invoking the “FROH; Kim et al., FHOM; Wright, FROH was derived for each individual following McQuillan et al.  between adjacent SNPs, the r2 values were used to model changes in effective population sizes (Ne) over generations for each population and across the 13 populations using the SNeP tool , Ne and c (recombination rate) using the equation:The r2 is the LD between different markers, Ne is the effective population size, c is the genetic distance between various markers measured in Morgans, n is the chromosome experimental sample size, α is a correction for the occurrence of mutations  tree using a kinship matrix. Pairwise Reynolds genetic distances . In the construction of the NJ tree, no outgroup population was defined, but the software was prompted to use all populations and the midpoint as outgroup. The kinship matrix captured the population structure, which was used to model covariance matrix of allele frequencies, whereas a multi‐point LD model was used to create haplotype clusters on each chromosome  per chromosome). This was determined using cross‐validation based estimation in fastPHASE 1.4.0 . To limit false positives, a q‐value threshold of 0.01 was applied to control for false discovery rate (FDR). Putative selection signatures were defined by the regions with a threshold of p < .001.The software hapFLK v.1.2  test  to identify phenotypes and protein–protein interaction networks associated with the candidate genes.Using the NCBI map viewer, the regions revealed by hapFLK and XP‐EHH were annotated using the ARS1 release 102 goat reference genome assembly ; Table HO (0.348 ± 0.143), HE (0.361 ± 0.130), PN (0.978) and DST (0.289 ± 0.018). The highest values were observed in Afar (HO = 0.382 ± 0.124), Nubian  and Hararghe Highland (PN = 0.997). The lowest values of inbreeding were observed in Long‐eared Somali (FHOM = −0.002 ± 0.03) and Gondar (FROH = 0.006 ± 0.014), respectively. Overall, Nubian had the highest values of FHOM (0.054 ± 0.118) and FROH (0.087 ± 0.116). FHOM showed a strong positive correlation (r = .978) with FROH.Genetic diversity indices  per animal ranged from 2.46 ± 2.99 (Gondar) to 16.85 ± 19.84 (Nubian)  generations ago, Nubian and Keffa had the highest and lowest ly Table . Thirtees Figure  reveals s Figure . A trendDST value, Nubian individuals spread out across the fourth quadrant of the PCA suggesting high intra‐population variation. TreeMix . Nubian goats have long‐haired coats and reside at low‐altitude drylands in north‐western Ethiopia, northern Sudan and western Eritrea (www.dagris.info/). High altitudes present a hypoxic cold environment. Low‐altitude drylands present an environment characterized by grazing stress. Grazing stress encompasses complex interacting biophysical stressors including heat, physical exhaustion, direct solar radiation and unavailability of feed  and water. The selection signatures observed in Arsi‐Bale and Nubian led us to hypothesize that putative selection may have resulted in adaptive and phenotypic divergence in the two populations.Seventy‐eight pairwise comparisons were performed with hapFLK v1.2 software and XP‐EHH test, assuming that each population was adapted to specific circumstances in its home range. Although the two approaches identified multiple regions under selection Figures  and S4, CDX2, NBEA and PITX  and PROCR, CTCFL, NNAT and PDYN (Nubian) are involved in multiple functions.We annotated the four candidate regions based on the ARS1 release 102 goat reference genome assembly. We found a total of 123  unannotated genes, that is prefixed with “LOC/ENSCHIG” in the candidate regions. Although potentially under selection, these unannotated genes were not included in the functional enrichment and ontology analysis. In total, 20 (CHI6) and 45 (CHI12) genes were present in the Arsi‐Bale regions, while 62 (CHI8) and 244 (CHI13) were observed in the Nubian regions (Table 44.1OH and EH above 0.348) and within population genetic variation (DST > 0.289). Although these values are high, they are close to those reported in other indigenous goats  between FROH and FHOM observed in our study corroborates previous findings in pigs  has been reported  (620 generations). It was followed by a rapid increase starting around 1,140 ya (380 generations) and then by a sharp decline from around 480 ya (160 generations) that persists until now   that are reported to be associated with female reproduction in bovines , oxidative stress , adaptation to different ecological environments , and mitochondrial homeostasis (TDRD7) including classical innate immunity and fever induction  . Surprisingly, we observed genes that have been associated with dairy , beef , and reproduction  traits  Table . Coat an5The genetic history of African indigenous goats is complex. It has obviously been closely intertwined with the history of local human communities. The need to adapt to diverse African environments may also have shaped present‐day African goat genomes. Here, we have provided insights that improve our understanding of the genomic landscape and demographic history of sub‐Sahara African indigenous goats in Ethiopia. Our results provide a foundation to formulate and test biological hypotheses relating to population demographic profiles and genome dynamics in African livestock. Further studies are needed to refine and confirm our interpretations and the proposed hypotheses. These include among others, the association between the uniform genetic background in Keffa and reduced susceptibility to trypanosomosis, the origin and route of entry and dispersal of the two deep ancestries into the region, and the suggestion that the historical demographic dynamics of the indigenous goats may be more complex than is reflected by the composite trend.The authors declare no conflict of interest regarding this manuscript.Fig S1‐S2Click here for additional data file.Fig S3Click here for additional data file.Fig S4Click here for additional data file.Tables S1‐S2Click here for additional data file.


Conservation and genetic improvement of cattle breeds require information about genetic diversity and population structure of the cattle. In this study, we investigated the genetic diversity and population structure of the three cattle breeds in the Korean peninsula.O and HE), inbreeding coefficient (FIS) and past effective population size. Molecular variance and population structure between the nine breeds were analyzed using a model-based clustering method. Genetic distances between breeds were evaluated with Nei’s genetic distance and Weir and Cockerham’s FST.Jeju Black, Hanwoo, Holstein cattle in Korea, together with six foreign breeds were examined. Genetic diversity within the cattle breeds was analyzed with minor allele frequency (MAF), observed and expected heterozygosity (HE = 0.21) among the studied taurine breeds, and an average MAF of 0.16. The level of inbreeding was −0.076 for Jeju Black, while −0.018 to −0.118 for the other breeds. Principle component analysis and neighbor-joining tree showed a clear separation of Jeju Black cattle from other local (Hanwoo and Japanese cattle) and taurine/indicine cattle breeds in evolutionary process, and a distinct pattern of admixture of Jeju Black cattle having no clustering with other studied populations. The FST value between Jeju Black cattle and Hanwoo was 0.106, which was lowest across the pair of breeds ranging from 0.161 to 0.274, indicating some degree of genetic closeness of Jeju Black cattle with Hanwoo. The past effective population size of Jeju Black cattle was very small, i.e. 38 in 13 generation ago, whereas 209 for Hanwoo.Our results revealed that Jeju Black cattle had lowest level of heterozygosity (HThis study indicates genetic uniqueness of Jeju Black cattle. However, a small effective population size of Jeju Black cattle indicates the requirement for an implementation of a sustainable breeding policy to increase the population for genetic improvement and future conservation. Cattle are an integral part of animal agriculture since 8000 BC, when it is thought that they become domesticated in different parts of the world such as India, Middle East and North Africa . DiffereJJBC are adapted to the subtropical environment of the Jeju Island. Also, beef of JJBC is rich in oleic acid, linoleic acid, and unsaturated fatty acids, which make it a premium quality for Korean consumers. However, in the past decades, this indigenous breed was paid little attention by beef cattle producers due to their slow growth and thus were was not competitive compared to ‘Hanwoo’, a breed in mainland of Korea that has been extensively bred for superior meat quality.e), inbreeding coefficient, levels of heterozygosity, etc. can be estimated with high density SNP chips [Genomic studies using high throughput whole genome sequencing data have become popular in recent years. Single nucleotide polymorphisms (SNP) are one of the common genetic variants for any organism, and genotyping with a high density SNP microarray chip provides genome information in an efficient and cost effective manner. Many useful genetic parameters such as linkage disequilibrium (LD), effective population size , level of inbreeding (FIS), effective population size (Ne), and genetic distances between the breeds.Development of sustainable breed improvement strategies depends on the precise characterization of animal genetic diversity . AlthougAnimal ethics approval statement was not applicable as the Hanwoo DNA was extracted either from commercial bull semen straws or from tail hair samples obtained from different farmers with the permission of the owners. A total of 373 animals from nine cattle breeds were chosen to study, including two indicine breeds , seven taurine breeds . Hanwoo DNAs were extracted either from AI bull semen straws or tail hair samples obtained from different farmers with the permission of the owners, and JJBC DNAs were prepared either from AI bull semen straws or tail hair in Jeju Island, Korea. Holstein DNAs were collected from semen straws provided by Nonghyup Dairy cattle improvement center. All other cattle DNAs were provided by Texas A & M University, USA, except the two Japanese Wagyu breeds. No ethics statement was required for the collection of DNA samples from the Brahman, Nelore, Angus, and Hereford cattle, because DNA samples were provided by the two authors in USA under their rules and regulations. The data of two Japanese Wagyu breeds were provided by the authors in Japan, which was previously used and published. Genomic DNA purification and genotyping was accomplished by DNA Link Inc. , a commercial genome analysis service provider in Korea.The samples of all breeds in this study except the two Wagyu breeds were genotyped using a customized Affymetrix 150K SNP Axiom array by DNA Link Inc. , which included the 50K SNPs from the Bovine 50K v.3 Bead Chip . The samples of the two Wagyu breeds were genotyped with the Illumina 50K SNP chip. All the genotyped data were then merged and the common SNP markers on autosomal chromosomes were selected, resulting in 45,526 SNP markers in the final dataset across the breeds.indep-pairwise 50 5 2 , because pruning of SNP markers in high LD can counter the effect of ascertainments bias and generate meaningful comparison between breeds [SNP quality control and filtering were performed across the nine cattle breeds to remove SNP markers with less than 95% call rate and animals with less than 95% call rate with PLINK software program . This prn breeds . After pE), observed heterozygosity (HO), and inbreeding coefficient (FIS), for which the parameters were calculated using R software package divRsity v1.9.9 [ST estimates according to the approach of Weir and Cockerham’s [Genetic diversity within cattle breeds can be estimated by expected heterozygosity  determines breed relationships that are based directly on allele frequencies by using a multivariate method, in which the information from a large number of alleles and loci is condensed into a few synthetic variables known as principal components (PC) . PCA wasA), which can be defined asPhylogenic analysis on the basis of SNP data has become an important tool for studying evolutionary history of any organism. In this study, phylogenic tree was constructed by calculating Nei’s genetic distances (DA)  with Popxij and yij are the frequencies of the i-th allele at the j-th locus in populations X and Y, respectively, mj is the number of alleles at the j-th locus, and r is the number of loci used.where r2 [r2 is preferred for association studies due to its robustness, simplicity and not sensitivity to changing gene frequency and effective population size [r2 estimator represents a squared correlation coefficient (r) between two variables  at two separate SNP marker loci [r2 parameter:To measure the extent of LD, Lewontin’s D′  and Hillr2  are wideion size . The r2 ker loci . PLINK sker loci  was usedPab represents the frequency of haplotypes consisting of allele a at the first locus and allele b at the second locus [r2 threshold, in order to encapsulate all possible linkage interaction between SNPs per chromosome. To display the decay of LD, distances of pair-wise SNPs were binned into twenty types of intervals . For each chromosome, r2 values were then sorted by inter-SNP distance, and were averaged across the afore-mentioned intervals to observe possible r2 patterns with increasing inter-SNP distances.where, nd locus . Ther2 ve was estimated using SNeP v1.1 by Barbato et al [Nto et al , which wto et al ,NT(t) represents the past effective population size with t generations ago, Ct represents the recombination rate, t generations ago in the past for specific physical distance between markers calculated by the SNeP tool, r2adj represents LD value adjusted for sample size, and α =  is the correction factor (constant) for the occurrence of mutation. The recombination rate was calculated using the following equation suggested by Sved [where  by Sved ,e estimates were subsequently obtained from the r2 values for the average distance of each distance bin.The data sets for each sub-population, as well as the merged dataset, were grouped into 20 distance bins of 10 to 100 kb each. NE = 0.15), while Hanwoo, Angus, and Holstein had the highest level of genetic diversity (HE = 0.28). JJBC had a middle range value of HE (0.21) in the studied breeds.IS measures the heterozygosity of individuals (I) relative to the subpopulation (S) represented by non-random mating (inbreeding), so that negative FIS value means less inbreeding. The FIS ranged from −0.018 in Black Wagyu to −0.118 in Brown Wagyu cattle. JJBC had the FIS value of −0.076, while −0.025 in Hanwoo . AMOVA indicated that almost 17% of the variation was estimated for variation among the populations, while 85% of the variation was accounted due to within individual variation (ST are displayed in ST ranged from 0.085 (Hanwoo and Brown Wagyu) to 0.376 (Nelore and Brown Wagyu). The genetic distance (DA) between Hereford and Nelore (0.107) was relatively greater than between JJBC and Hanwoo (0.028). JJBC had great distances with Nelore (0.084) and Brahman (0.078), while small distances with Hanwoo (0.028) and Black Wagyu (0.042) cattle breeds.The average Wright’s F-statistics that were estimated with 20,000 bootstraps over loci were of values, F = 0.148 . FIT meaariation . GeneticA) matrix of the nine cattle breeds were also used to construct phylogenetic trees with NJ method [Bos Taurus and Bos Indicus, the NJ trees showed two sub-branches within the taurine branch, i.e. one for JJBC and the other for Hanwoo, two Japanese breeds and three European taurine breeds  than Hanwoo and Holstein in Korea (HE = 0.218). Sharma et al [E = 0.39 and 0.25), while Struken et al [E = 0.29. Heterozygosity level in our study is close to Sharma et al [JJBC showed lower level of genetic variability  in JJBC was estimated to be −0.076, which was lower than Hanwoo (−0.025) and Holstein (−0.026) in Korea. Genetic variability was lowest in Nelore (HE = 0.15) and low in Brahman (HE = 0.17). Indicine breeds might have less genetic variability than taurine breeds as reported by Lin et al [ST), within population inbreeding (FIS) and total inbreeding (FIT), showed that 85% of total genetic variation was due to within populations across nine cattle breeds. This value was lower than the within populations genetic variation observed in South African cattle populations (92%) [IT) and estimate of population differentiation (FST) was0.148 and 0.173 respectively, with statistical significance (p<0.001) (ST = 0.106) compared toother breed pairs. Sharma et al [ST values for Korean cattle breeds, ranging 0.02 to 0.06, andreported that JJBC was differentiated from another Korean cattle breed, Brindle Hanwoo (Chikso). Struken et al [ST value of 0.024 for JJBC-Hanwoo, 0.038 for JJBC-Chikso and 0.023 for Hanwoo-Chikso. Bothstudies confirmed that JJBC was least differentiated with Hanwoo, which was in good agreement with our study.Inbreeding level  , but higns (92%)  and Ethins (92%) . Total ip<0.001) . JJBC anma et al  calculat% , but hST value and phylogenetic tree, we are in agreement with the concept that Hanwoo and Japanese Wagyu cattle breeds were genetically much closer to each other than other indicine and European taurine breeds (Japanese breed Black Wagyu breeds showed less differentiation with Hanwoo (0.085) than JJBC (0.164), indicating a closer relation with Hanwoo. Based on Fe breeds . PCA anae breeds .Unsupervised hierarchical clustering of our data implemented with ADMIXTURE analysis revealed that 95% of Hanwoo individuals were assigned to cluster ten, whereas 39%, 38%, 23%, and 1% of JJBC individuals were assigned to four different clusters, i.e. five, one, six, and ten, respectively. This means that JJBC shared its genome only with Hanwoo cattle. Japanese Brown Wagyu (100%) stands alone in cluster three, while Black Wagyu (96%) individuals were assigned in cluster eleven and the rest of the 4%were assigned to cluster three, nine and ten . This lePhylogenic tree analysis also showed a distinct branch for JJBC, while Hanwoo and Wagyu breeds shared the same branch more recently than JJBC , suggeste estimate of 67. Sudrajad et al [e in JJBC was estimated to be 60 until 11 generation ago, and Struken et al [e estimate of 11 at nearest generation. These Ne estimates were much smaller than the Ne of Hanwoo, i.e. 209. Differences of Ne estimates in the various reports might be caused by many factors such as sample size, SNP quality control measures and models used to study LD and Ne [JJBC have an effective population size of 38 in the nearest 13 generation ago, whereas Sharma et al  reportedad et al  reporteden et al  reportedD and Ne .e value of JJBC seems to be sufficient for maintaining genetic diversity for short term species management as suggested by Frankham et al [The small Nam et al , but notThis study supports genetic uniqueness of JJBC breed that has been evolved differently from Hanwoo and Wagyu breeds, as well as from indicine and western taurine breeds, although a small amount of genetic components in terms of allele sharing exists between JJBC and Hanwoo. However, further in-depth study with whole genome sequencing and scanning using high density markers with larger samples would help us to accurately measure genetic parameters for establishment of JJBC as a unique breed.


In total, we successfully genotyped 269 R. mangle trees, using a panel of 677 SNPs developed with 2b-RAD methodology. Within the 400 m2 parcel, we found two distinct clusters with high levels of genetic differentiation (FST = 0.355), corresponding to trees primarily located on the seaward fringe and trees growing deeper into the forest. In contrast, there was limited genetic differentiation (FST = 0.027–0.105) across the sites at a larger scale, which had been predominantly sampled along the seaward fringe. Within the 400 m2 parcel, the cluster closest to the seaward fringe exhibited low genetic differentiation (FST = 0.014–0.043) with the other Honduran sites, but the cluster further into the forest was highly differentiated from them (FST = 0.326–0.414). These findings contradict the perception that genetic structure within mangroves forests occurs mainly along a coastline and highlights that there is greater genetic structure at fine spatial scales.Mangroves form coastal tropical forests in the intertidal zone and are an important component of shoreline protection. In comparison to other tropical forests, mangrove stands are thought to have relatively low genetic diversity with population genetic structure gradually increasing with distance along a coastline. We conducted genetic analyses of mangrove forests across a range of spatial scales; within a 400 m Mangroves provide critical ecosystem services such as fisheries2, protection from hurricanes and storms4, flood events5, and climate change mitigation, through carbon sequestration6. Despite their importance, mangrove cover has significantly declined since the 1960’s7 and these systems have become more fragmented8. There was a real concern that if deforestation rates continued at the historical rates of the 1980’s and 1990’s we faced a world without mangroves9. However, over the past decades, mangrove deforestation rates have significantly slowed, and there is cause for cautious optimism11.Mangroves are a group of highly specialized plants that have adapted to live in the harsh conditions of the intertidal zone along tropical and subtropical coastlines12. Mangroves are considered to have limited genetic structure at fine-spatial scales (≤ 200 m) due to life history traits, which can facilitate high self-pollination rates14, and high rates of self-recruitment, which are common in established mangrove stands, particularly in species that produce large propagules, such as Rhizophora spp.16. Additionally, habitat discontinuities can form strong barriers to gene flow17.There are calls for greater protection of mangroves, with aims of no net loss and to increase mangrove cover through restoration over the coming years, and such efforts will start to be expanded as we enter the United Nations Decade of Ecosystem Restoration. Maintaining genetic diversity of extant and restored mangrove forests provides the opportunity for natural selection to occur in response to changing environmental conditions18, seascape19, regional20 and biogeographic scales21, with low to moderate genetic diversity observed. There has been less focus at small spatial scales (< 200 m), due to the presumed limited genetic diversity at the forest scale, but see Iuit et al.22, Ngeve et al.23 and Triest et al.24. However, fine-scale genetic analyses of other habitat forming foundational species, the scleractinian coral Acropora cervicornis25 and three species of bulrush, Bolboschoenus maritimus, Schoenoplectus acutus and S. americanus26 revealed higher levels of genetic diversity than previously expected, which has major implications for spatial management and restoration practices of these species. Understanding mangrove genetic structure, at various spatial scales, is therefore critical in informing management and restoration strategies, and population genetics should be a key component of management and restoration frameworks .Population genetics studies have been used to assess genetic connectivity of mangrove populations at estuaryRhizophora mangle (red mangrove), an iconic mangrove species found along the Atlantic shores of Latin American, the Caribbean and African countries, at fine (≤ 20 m) and larger spatial scales (6–115 km). An isolated R. mangle forest was selected to test the hypothesis of limited genetic differentiation at fine, within forests, spatial scales. We also sampled from the seaward forest fringe of three other mangrove stands located along the Honduran north shore to place the fine scale samples in a broader context. We observed limited genetic structure across the seascape for populations of mangroves sampled along the seaward fringe of a forest. However, significant genetic structure was observed at fine spatial scales, with higher levels of genetic differentiation within the forest than expected. Our findings have important implications for the management and restoration of mangrove forests.Here we conduct population genetic analyses of ST analyses of the two clusters revealed significant genetic differentiation (FST = 0.355) within the 400m2 parcel , followed by significant negative autocorrelation at the next five distance classes (10–18 m) Fig. . No signST analyses of the four sampling sites separated by distances of 6–115 km identified limited genetic structure among the four sites, with FST values ranging from 0.027 to 0.105    mangrove forests lack genetic structure13, with significant genetic differences occurring at 8–10 m scales. We observed significant positive spatial autocorrelation at 2 m spatial scales, at 2–8 m distance classes, and significant negative genetic spatial autocorrelation at 10–18 m distance classes. These results indicate that individual clusters have a spatial dominance of 2–8 m, and trees outside of this boundary are significantly different and potentially from different sources, either from distinct parental families within the same forest or from spatially distant sources.Our analysis of a small parcel of mangrove forest revealed significant genetic structure at fine spatial scales, with two genetically distinct clusters of trees identified in STRUCTURE and assigned through K-means clustering. Our findings provide evidence that refute the hypothesis that 30, the most severe was hurricane Mitch in 1998, which caused various levels of damage to mangrove stands throughout the Bay Islands, Honduras31. Such events could have had a role in shaping the genetic structure observed in the parcel of mangrove on Fort Cay. Damage to the fringe from tropical storms or hurricanes could have opened space for the recruitment of propagules from other populations that were dispersed by the storm event to the parcel. However, dispersal alone does not equate to recruitment success, as recruitment is influenced by numerous biotic and abiotic factors, including propagule predation rates32, sediment conditions33, and the presence of canopy gaps34. The sources and the mechanism of these different recruitment events is unknown, but with trees of various sizes associated with each of the identified clusters present, we suggest recruitment has persisted over various temporal and spatial scales. Whilst defining the drivers and spatial and temporal scales of dispersal and recruitment events are beyond the scope of this study, our results identify the influence of potential recruitment events, from either proximal or distal sources, on genetic diversity and structure at fine scales.We suggest that the genetic structure observed, both in genetic spatial autocorrelation and pairwise R. mangle forests between the four sampling sites within the Honduran Caribbean, at spatial scales of 6–115 km. These results suggest high levels of connectivity among mangroves within the Honduran Caribbean, and mirror findings from previous studies on both R. mangle and Avicennia germinans (black mangrove) in the Mesoamerican Reef region and Gulf of Mexico, at scales of 100’s km35. A more recent study observed greater genetic structure between R. mangle stands located between these two ecoregions, but, limited genetic structure within an ecoregion, at spatial scales of 10’s to 100’s km19. By placing the two clusters identified in Fort Cay in a wider context of R. mangle forests from across the Honduran Caribbean, we suggest that the connectivity observed at large-scales in many studies is potentially an artifact of sampling design. Mangroves assigned to cluster FC-K1 were predominantly associated with the seaward fringe of the parcel, and were most genetically similar to the three other sampling sites, where samples had also been collected from the seaward fringe. In contrast, individuals assigned to cluster FC-K2 were associated with the greatest levels of genetic differentiation to R. mangle trees sampled from the seaward fringe, including FC-K1. The limited genetic structure at the larger scale may be explained by propagules being dispersed by prevailing currents and recruiting along the seaward fringe, as propagules are capable of dispersing 1000’s km36. Similarly, larval models have demonstrated high levels of connectivity for other marine species in the region37. Alternatively, individuals assigned to FC-K1 may represent local recruitment and individuals of FC-K2 represent recruitment from another unknown population. Due to the higher frequency of individuals assigned to cluster FC-K1, local recruitment may be dominant, but interspersed with recruitment events from other more distant populations, and that layers of these events build up as the forest matures. We can only hypothesize about the drivers of the genetic structure observed, however, we can state unequivocally that sampling only the seaward fringe of a mangrove stand does not provide a complete overview of genetic structure of mangroves at larger spatial scales, and may greatly influence our interpretation of genetic connectivity within these ecosystems.Limited genetic structure was observed in 39. Maintaining genetic diversity within mangroves (and other ecosystems) is of increasing importance during an era of unprecedented climate change, and therefore population genetics should be an essential component of management and restoration frameworks41. To improve management and conservation efforts it is essential to have a greater understanding of the genetic structure of mangroves at the forest and seascape scale, and to ensure that management occurs at the appropriate spatial scales. Previous population genetic studies have increased our understanding of dispersal mechanisms and connectivity of mangrove populations , and sampling scales of 5–30 m44, and up to 100 m45 have prevented sampling the same individual multiple times. However, most of these studies also only sampled along the seaward fringe of the mangrove. Our findings suggest that such sampling ranges are adequate, but based on the genetic structure observed here  we recommend sampling at similar spatial scales, 10–30 m, into the interior of mangrove forests. Sampling inland, not just along, a coastline will provide greater representation of the genetic structure within a population. This in turn can inform the spatial scale required for effective management of mangroves across seascapes, and can be used to monitor the effectiveness of restoration projects in maintaining genetic diversity, which are fundamental to the success of forest management41, and restoration frameworks . Maintaining genetic diversity and gene flow of restored forests is a critical step in building resistance, resilience and adaptation of restored mangroves to future environmental conditions46. Understanding the genetic structure of mangroves at the forest scale can also help inform propagule source selection and planting practices, where required. This study provides further evidence of how genetic and genomic tools can improve the monitoring and evaluation of the management and restoration of mangroves48.Genetic structure has implications for ecosystem function and the composition of associated biodiversity2 area of mature mangrove forest comprising of only R. mangle was identified on Fort Cay, which is separated from the island of Roatan, Honduras, by a minimum of 1 km. The parcel was delineated using a 20 × 20 m sampling grid, and individual 1 × 1 m sampling cells were constructed in the forest using measuring tapes and ropes  and Elijah canal (EC), and collections at these occurred on the 22nd and 23rd November 2016, respectively. The third site was on the Honduran mainland at Cuero y Salado (CS), where collection occurred on the 25th July 2017 Fig. . Samplin49, as secondary metabolites can cause shearing of DNA during extraction50. Upon collection, petioles were removed and leaves were broken in half to facilitate desiccation, and stored in individually labeled bags containing a 0.06–0.80 mm granular mix silica gel with cobalt indicator, prior to DNA extraction.At all sites, young leaves were preferentially sampled, due to lower concentrations of polyphenolics and other secondary metabolites compared to older leaves2 of leaf tissue sample was placed in individually labeled 2.0 ml microcentrifuge tubes, and bathed in 500 µl of 100% ethanol for 3–4 days and then dried under fume hood for an additional two days. This process aided in the removal of secondary metabolites within leaves, and provided an additional dehydration step. Once dry, a single 5 mm stainless steel ball-bearing  was added to each tube and samples were lysed using a Retsch  MM440 mixer mill . Samples were placed in one of two Tissuelyser adapter sets and lysed at 30 Hz for 1 min. Samples were flipped and swapped between Tissuelyser arms and lysed at 30 Hz for a further 1 min to facilitate consistent lysing across samples. DNA extraction from lysed tissue was conducted using the DNeasy 96 Plant Kit (Qiagen) following the manufacturers’ protocol.Prior to extraction approximately 1 cm51 restriction site associated DNA (RAD) protocol. This methodology utilizes type IIB restriction enzymes that cut both upstream and downstream of the enzyme’s target site, resulting in the production of RAD tags of uniform length. Briefly, approximately 50–100 ng of high-quality genomic DNA  from each sample was digested with the enzyme BcgI , producing uniform 36 bp length fragments with random overhangs. Genomic digests were then ligated to a pair of partially double-stranded adaptors targeting a reduced subset of BcgI sites through a different reduction scheme depending on organism genome size. RAD tags were then amplified with sample-specific 5.6 bp or 6.6 bp dual-barcodes and Illumina adaptors. PCR products were visualized on a 2.0% agarose gel to verify the presence of the expected 160–170 bp target band . Gel purification of the target band was carried out following protocols outlined in Guo et al.52. Amplification products were pooled at equimolar concentrations and sequenced on an Illumina HiSeq 3000 , at the Center for Genome Research and Biocomputing at Oregon State University, with single end sequence read lengths of 50 bp.2b-RAD-seq libraries were prepared using a modified version of the Wang et al.53 on the Smithsonian Institution High Performance Computing Cluster (https://doi.org/10.25572/SIHPC). The genome of R. apiculata54, a close relative of R. mangle, was used as the reference genome. In ipyrad v0.9.1253, all parameters were set to default, except for the following: data type = 2brad; restriction overhang = ‘TGCAG’; cluster threshold = 0.85; maximum barcodes mismatch = 0; filter adapters = 2; filter minimum trim length = 20; maximum alleles consent = 2; minimum samples per locus = 4; and, trim read = 0; and trim loci = 0. An initial panel of 113,626 loci was generated. We removed markers with 50% or more missing data and those with minor alleles frequencies of < 0.0155. Screening for null alleles, deviation from Hardy–Weinberg equilibrium and linkage disequilibrium were conducted in R Studio56 using the packages adegenet57, poppr58, and genepop59. Whilst the removal of markers due to Hardy–Weinberg disequilibrium may reduce the resolving power of the SNP data set, due to the Wahlund effect60, less than 30 SNPs were identified as deviating from Hardy–Weinberg equilibrium and were removed from the SNP panel. After post filtering and quality control, a panel of 677 informative SNPs was identified. The screening process was highly conservative, this was to reduce the effect of rare alleles being the underlying driver of structure within Fort Cay, the fine-scale analysis site.Raw reads were downloaded from the Oregon State University online portal. Libraries for three trees failed to amplify. Successfully amplified libraries from the remaining 269 trees were processed using ipyrad v0.9.12R. mangle stands was analyzed using the software STRUCTURE v2.3.462, with a burn-in length of 100,000, and Markov chain Monte Carlo replications set at 100,000. The model was run with K values of 1 through 10, with 10 permutations per K value. Optimal K values were selected from the highest delta K value generated by STRUCTURE HARVESTER63. This was conducted firstly for Fort Cay only, and subsequently for the four sites , and then for five sites, where individuals from Fort Cay were included as one of two sites, FC-K1 or FC-K2, based on their assigned cluster in the Fort Cay only analysis. Further analysis of individuals from Fort Cay to identify nested patterns of genetic structure, or hierarchical structure analysis, were conducted as recommended by Pritchard and Wen64 and Vähä et al.65. K-Means clustering analyses were conducted in GenoDive using the settings: cluster = individuals; method = Amova; run from 1 to 20 clusters. Convergence type was simulated annealing using 50,000 steps with 20 algorithm repeats, and best clustering according to Calinski & Harabasz’ pseudo-F66. Iterations of these analyses were conducted using “Bayesian Information Criterion (BIC)”, “Aikaike’s Information Criterion (AIC)” and “within-groups sum of squares” statistics. Pairwise FST analyses, using 50,000 permutations, were conducted in GenoDive67, on clusters K1 and K2 from Fort Cay, all four sampling sites, and five sites where mangroves from Fort Cay were included as one of two sites, FC-K1 and FC-K2.Population structure of 68, we calculated pairwise inter-individual genetic distances as outlined in Smouse and Peakall69 and geographic distances measured between the grid locations of individual trees. Consistent with our systematic sampling design, we performed the spatial autocorrelation analysis with even distance classes  which maintained large numbers of sample pairs (565–2204) at each distance class. An autocorrelation coefficient (r) was calculated for each distance class and plotted as a spatial genetic correlogram. Null 95% confidence intervals at each distance class were generated via 999 random permutations of all samples and 95% confidence intervals around each r value were generated via 103 bootstrap replicates of the samples at the respective distance class. As described in Peakall et al.70, we accepted statistical significance of spatial autocorrelation at a distance class when (1) the r value exceeded the null confidence interval and (2) the confidence interval around the r value did not overlap with zero.Spatial autocorrelation analysis between pairs of individuals at specified distance classes were performed to assess fine-scale genetic structure of mangroves at Fort Cay. In GenAlEx 6.5


The scaling of mortality in cities of the Americas varies widely by cause and region. We explored how mortality scales with city population size using vital registration and population data from 742 cities in 10 Latin American countries and the United States. We found that more populated cities had lower mortality , driven by a sublinear pattern in U.S. cities, while Latin American cities had similar mortality across city sizes. Sexually transmitted infections and homicides showed higher rates in larger cities . Tuberculosis mortality behaved sublinearly in U.S. and Mexican cities and superlinearly in other Latin American cities. Other communicable, maternal, neonatal, and nutritional deaths, and deaths due to noncommunicable diseases were generally sublinear in the United States and linear or superlinear in Latin America. Our findings reveal distinct patterns across the Americas, suggesting no universal relation between city size and mortality, pointing to the importance of understanding the processes that explain heterogeneity in scaling behavior or mortality to further advance urban health policies. More than 50% of the global population lives in cities, and by 2050, this figure is expected to reach 70% , 0.92 to 0.96]  and linear (for Latin America) scaling of all-cause mortality applied to the six large groupings of causes of death . The thrR2 above 80% and most above 90%, with the exception of homicides in Mexico , indicating a higher variability in homicide rates across cities in Mexico after accounting for city size, suggesting stronger place-based (city-specific) effects in Mexico. Later in this section, we will describe a more comprehensive exploration of the relationship between this variability in outcomes and scaling behaviors. Of note, model fit for most outcomes by region was very good, with all Given the heterogeneity in causes of death within these large six groupings, we also conducted a more fine-grained analysis focused on specific death causes  and HIV/AIDS, tuberculosis, respiratory infections, and all other infectious diseases], we found different patterns by region and cause. STDs and HIV/AIDS had a superlinear behavior for U.S. cities, Latin American cities as a whole, Brazilian cities, and all other Latin American cities , but they were sublinear in Mexico (β = 0.90). STDs and HIV/AIDS were actually the most superlinear cause of death in U.S. cities and in Latin American cities excluding Brazil and Mexico, but they were the second most sublinear cause in Mexico.On the other hand, tuberculosis had a very different pattern in U.S. and Latin American cities : It was We observed that mortality from most cancers showed a sublinear (13 of the 21 subcategories) or linear (7 of 21) pattern in U.S. cities. In contrast, cancer deaths showed a linear (10 of 21) or superlinear (10 of 21) pattern in Latin American cities. Specifically, and as seen in Cardiovascular and other NCDs were clustered into three groups . The firIn the case of injury deaths, patterns were mostly consistent between U.S. and Latin American cities  and 4D. We also explored the association between the levels and variance of each outcome and their respective scaling coefficient . We founOur analysis of 366 Latin American and 376 U.S. cities (encompassing over 560 million residents) revealed a heterogeneous scaling landscape of mortality across the continent. While in the United States all-cause mortality was relatively lower in larger cities and did not differ by size in Latin American cities, the relation between city size and mortality differed by cause of death and region. Nonviolent injury deaths were sublinear in both regions, whereas homicides and deaths due to STDs/AIDS were superlinear in both regions. NCDs and cancer were generally sublinear (or linear for some cancers) in the United States and mostly linear or superlinear in Latin America. Deaths from CMNN (other than AIDS/STDs) were sublinear in the United States and linear in Latin America.et al.  and United States (mostly sublinear) may be related to differential associations of chronic disease risks factors with city size in both regions, particularly considering that most of Latin America has swiftly transitioned toward a predominance of urban areas and the accompanying epidemiological and nutritional transitions that are still in progress , a topic that has been extensively studied from a productivity perspective  that overlapped with the urban extent of the city, in 10 countries  study, which has compiled and harmonized vital registration and other health data  using a pro rata redistribution, based on cause of death, sex or age, country, and year. Second, we redistributed deaths assigned to ill-defined causes (4.1% for Latin American cities and 1.5% for U.S. cities) using a pro rata redistribution by age, sex, country, and year. Ill-defined causes are causes of death that do not provide useful information on the cause of death for public health purposes, and we define these as ICD-10 codes R00-R94 and R96-R99. Third and last, we corrected for the underregistration of deaths at the city level by using an ensemble of death distribution methods. We assumed that U.S. cities had complete coverage of death counts and conducted this correction only for Latin American cities. More details on these three steps are available elsewhere , ijN is the population of the city, and ε is a residual , Prop(40_64), and Prop(65p) represent the percentage of the population in each city aged 15 to 39, 40 to 64, and 65+. We ran the model in n = 152 cities), Mexico (n = 92), and all other Latin American cities (n = 122). Models for a single country  do not include any adjustment for country, while models for multiple countries  include the adjustment covariates for country.Here, the vector of variables Countryet al.  commuting zones (


Cannabis sativa (2n = 2x = 20) is a popular species belonging to the Cannabaceae family. Despite its use for medical, recreational, and industrial purposes as well as its long history, the genetic research on this species is in its infancy due to the legal implications and the prohibition campaigns. The recent legalization of Cannabis in many countries along with the use of genomics boosted the approaches aimed at marker-assisted selection, germplasm management, genetic discrimination, and authentication of cultivars. Nonetheless, the exploitation of molecular markers for the development of commercial varieties through marker-assisted breeding schemes is still rare. The present study aimed to develop an informative panel of simple sequence repeat markers to be used for the genotyping of high breeding value C. sativa lines. Starting from 41 nuclear SSR designated by in silico analyses, we selected 20 highly polymorphic and discriminant loci that were tested in 104 individuals belonging to 11 distinct hemp varieties. The selected markers were successful in accessing homozygosity, genetic uniformity, and genetic variation within and among varieties. Population structure analysis identified eight genetic groups, clustering individuals based on sexual behaviors (dioecious and monoecious) and geographical origins. Overall, this study provides important tools for the genetic characterization, authentication, conservation of biodiversity, genetic improvement and traceability of this increasingly important plant species. Cannabis sativa L. is a multiuse plant species cultivated for its fiber and seeds  or for its high content in cannabinoids (var. sativa and var. indica) [Cannabis is tetrahydrocannabinol (THC) with varieties containing up to 30% THC by dry weight [Cannabis belongs to the family Cannabaceae , and its nomenclature has been disputed since the Linnaeus classification in 1753. At that time, it was not clear whether the genus was mono- or polytypic [C. sativa, namely, subsp. sativa and indica, the validity of which is still universally accepted. Recently, some authors have proposed a classification of C. sativa varieties based on their cannabinoid and terpenoid profiles [Cannabis strains, including those originating from the black market [ indica) . Among ty weight . The genolytypic ,5. Subseolytypic  proposedprofiles ,7,8. In k market .Cannabis is prevalent as a dioicous plant although monoecism and even hermaphroditism are possible with plants showing male and female reproductive organs within the same plant and flower, respectively [Cannabis and Humulus genera [From a reproductive point of view, ectively ,10,11. Aectively . Accordis genera .C. sativa genome is composed of nine pairs of autosomes and a pair of sex chromosomes (X and Y). Heterogametic (XY) individuals are males, while females and monoicous individuals are homogametic (XX) [The tic (XX) . The mectic (XX) .C. sativa varieties were bred through mass selection, optimizing basic quality traits, such as the content of fiber, oil, and cannabinoids [Cannabis cultivars were also constituted by crossing individuals selected from different landraces and cultivars to increase hybrid vigor and, therefore, productive performances. The “Skunk No. 1” hybrid, produced in the early 1970s, represents a successful variety obtained by this conventional breeding approach.Traditionally, both hemp and drug abinoids . New CanCannabis have been mostly employed to investigate genetic diversity, geographical origin, relationships between cultivated germplasm, varietal characterization and sex determination as well as to generate genetic linkage maps [Recently, the advent of genomics applied to crop plant species has revolutionized conventional breeding methods. The use of marker-assisted selection (MAS) allows specific traits of agronomic interest to be controlled, and marker-assisted breeding (MAB) exploits the presence of molecular markers dispersed among the genome for the genetic characterization of samples and the breeding of new varieties ,16,17. Mage maps . Among mage maps ,21,22.Cannabis cultivars and genotypes to evaluate genetic diversity. While early studies have identified and characterized a small number of polymorphic SSR sites specific for Cannabis sativa, [Microsatellites have been frequently used in  sativa, ,24,25, t sativa, ,29,30,31Regarding geographical origin, a several studies have reported that the highest genetic diversity is found within hemp varieties compared to drug varieties, and it is possible to differentiate distinct gene pools in Europe and Central Asia ,32,33.Cannabis spp. [Cannabis sativa varieties of high breeding value based on their geographical origin and, possibly, on their sexual attitudes (dioecious and monoecious).A previous study has developed a panel of SSR markers, organized in multiplex assays, to predict in silico from polymorphic and widely distributed microsatellite regions of bis spp. . HoweverCannabis plants. Separating male and female plants at early developmental stages is useful due to the influence of gender on agriculturally significant traits [Several experiments have focused on developing a reliable molecular marker for sex determination in t traits . Sequenct traits . Howevert traits ,36 makest traits .Linkage disequilibrium  is a sensitive indicator of the population genetic forces that structure a genome . In the C. sativa (cs10) genome (BioProject ID: PRJNA560384), a total of 126,593 perfect and 12,017 compound SSR regions were identified with a density equal to 148 SSRs/Mbp and 0.34% of the total length of the genome [Based on a previous study on the i), the observed heterozygosity (Ho), expected heterozygosity (He), average heterozygosity (Ha) and the polymorphism information content (PIC) of the 20 selected loci.a) and, therefore, the resulting PIC values reflect the extension of the geographical area of varietal origin. A similar average PIC value (0.71) was obtained by [i) was low when the observed number of marker alleles was high and vice versa. For instance, SSR_6-4 and SSR_X-1, had Na values equal to 3 and 28, showed pi values of 0.67 and 0.13, respectively.In total, 301 alleles were detected among 11 varieties with several observed alleles per locus ranging between 3 (SSR_6-4) and 28 (SSR_X-1). According to , 16 of 2ained by  by analyained by  obtains o), was always lower than the expected heterozygosity (He), highlighting an excess of homozygosity equally distributed across the genome. One possible explanation for this discrepancy is the excess of false homozygotes caused by null alleles. Nuclear SSRs are in fact characterized by high frequencies of null alleles, i.e., alleles that are not amplified due to the failure of primer annealing in the flanking regions of a target SSR locus [n < 13) and the lack of both parents and offspring genotyping data, the main limitation is the lack of HW equilibrium due to the strong selection pressure imposed by breeders. Moreover, the accessions analyzed for each variety are unrelated and were chosen as representative of the variety itself. A second plausible explanation is that the excess of homozygosity is the result of a strong selection pressure and inbreeding, which has characterized hemp cultivation over the years. Industrial hemp is in fact grown on a wide scale leading to a stabilization of agronomically important traits in seed stocks and, likely, to a reduced heterozygosity. On the contrary, drug-type varieties, being the results of hybridization events and being mainly propagated via cloning, are usually characterized by higher levels of heterozygosity [Although extremely variable (loci ranging from 0.07-SSR_2-1 to 0.84-SSR_8-2), the observed heterozygosity (HSR locus . ConsequSR locus . In our zygosity .is) result was always positive and, on average, equal to 0.41 (it (heterozygosity between subpopulations) and Fst (fixation index) indices were highly variable with values ranging from 0.10 to 0.89 and from 0.06 to 0.37, respectively. Nm (gene flow measure) ranged from 0.23 to 2.78 with an average value of 1.02 ± 0.13, showing the presence of gene flow (Nm > 1) for 9 loci out of 20. C. sativa sampled.In support of this, the inbreeding coefficient , except for the FRA3 variety. Nevertheless, it should be emphasized that this result may be affected by the reduced number of individuals considered in this variety compared to the others (only 3 in contrast to the 8–13 of the other varieties). A similar result was observed for the Shannon index (I) of phenotypic diversity and simple matching-based genetic similarity, which showed high values in all varieties , except for the FRA3 variety.is and Fit were higher than 0 in all varieties, suggesting repeated crosses of genetically related individuals and thus strong selective pressure operated by breeders. Estimates of the fixation index (Fst) changed considerably (from 0.54 to 0.73) among the 11 varieties, indicating an unbalancing contribution of the investigated populations to the total genetic variation. Accordingly, our estimates of inbreeding coefficients suggested that these varieties are characterized by a relatively high degree of genetic differentiation with approximately 64% (average Fst = 0.64) of the genetic variation found among varieties and 36% of the total genetic variation expressed within varieties. As expected, the gene flow (Nm) estimate derived from Fst was low (ranging from 0.09 to 0.21), demonstrating the absence of gene flow among the varieties.On the other end, the mean genetic similarity (MGS) among all varieties was more uniform with values ranging between 86% and 91%. The mean number of observed and effective alleles per locus ranged from 2.10 to 6.15 and from 1.89 to 4.43, respectively. Despite the different geographical origins and the different sexual behaviors, the observed heterozygosity was comparable among all varieties, and on average, it was equal to 0.58 ± 0.09, consistent with the allogamous reproductive system. When compared to the expected heterozygosity, all varieties showed an excess of homozygosity as confirmed by Wright’s statistics. Both FCannabis. In fact, it is conceivable that the longer a species is present in each geographical area, the higher the number of allelic variants  that have accumulated.Private alleles, beyond estimating genetic diversity, are also useful for varietal registration and traceability. The 301 alleles were screened for private markers by considering the core collections from different perspectives. The first classification was made between dioecious and monoecious samples, and the second classification considered the 11 varieties as distinct groups. In addition, the third classification was based on the geographical origin . In the first case, 22 alleles were found to be private for dioecious samples and 13 for monoecious samples. By considering the 11 groups separately, the highest number of private alleles was found in the ITA3 variety (23 out of 123). Finally, the third division of the samples based on their geographical origin found the highest number of private alleles in the Italian, Finnish and Hungarian samples with 13 out of 175, 12 out of 124, and 10 out of 153, respectively. However, it should be noted that the frequency of each private allele was low with few highly frequent alleles. For example, in the case of the ITA3 variety, the private allele frequency ranged from 5% (loci 8–4) to 41.7% (loci 5–2) with 16 out of 23 private alleles having a frequency ≤10%. Although this finding would discourage the use of single SSR loci for traceability or registration purposes, the combination of multiple private alleles at different loci may still represent an excellent tool for varietal identification . The facThe genetic structure of the germplasm collection was investigated to infer population relationships among individuals .Following the procedure of , a maximCannabis in Europe is vague. If the center of origin is in Central or East Asia [Cannabis/Humulus-type pollen in the southeastern part of Europe and, in particular, in Hungary, Romania, and Bulgaria approximately 10200–8500 years BP [Cannabis in Northern Europe and the Mediterranean basin occurred independently at different times. The clear division between the two European clusters was also clearly visible with PCoA analysis , sample clustering by geographical area becomes even more detailed. Plant materials from ITA1 and ITA2 were clearly assigned to a single, distinct cluster by STRUCTURE software , panel bCannabis accessions has demonstrated the tight relationship existing among three French and two Polish genotypes, suggest a recent common ancestor [In particular, the HUN1 and HUN2 dioecious samples were assigned to two different clusters by STRUCTURE software. Members of the HUN1 variety showed, on average, higher membership percentages to the cluster (91.9%) compared to the HUN2 ones (85.3%), which was clearly visible in the PCoA with the HUN1 samples tightly clustered in the bottom-right quadrant and the HUN2 samples dispersed around the previous ones. Similarly, samples from Finland (FIN), Poland (POL), and Netherlands (NED) were assigned to three different clusters with an average membership equal to 92.6%, 93.2%, and 91.2%, respectively. The results observed for the three French varieties  were unexpected. FRA1 and FRA2 formed a cluster apart with an important share of admixed samples and a consistent representation of the Polish ancestor. The only exception was represented by FRA1-8 that resulted admixed also with the Hungarian cluster HUN2 and towards which it showed a mean GS of 88% . Similarancestor . On the Overall, this is the first study in which a robust and novel panel of SSRs has been successfully used to investigate the geographical origin of samples derived from different European countries. Previous studies have mainly concerned Asian accessions , while tCannabis. Thus, the entire germplasm was screened using UBC354151 RAPD-deriving SCAR119, originally developed by Törjék [Cannabis (MADC4). In the last few years, several sex predictive markers have been developed and tested [P, 0.01) linkage disequilibria were found between the SCAR119 sex determination locus and the 2.1 and 5.5 SSR loci  on the Cannabis reference genome , we located MADC4 on chromosome 2 , justifying the association with SSR_2-1, which is located on the same chromosome as much as 15,695,145 bp upstream. Although neither the SCAR119 marker locus nor the 2.1 and 5.5 SSR marker loci are located on the sex chromosome , it is likely that specific regions of autosomal chromosomes also contribute to sex determination. In this regard, a recent study has reported that, of 555 sex-linked genes, 363 mapped to sex chromosomes, while the remaining 192  mapped to all the other autosomes [In the scientific literature, there is no information regarding the localization of the SCAR119 marker as its identification precedes the sequencing of the utosomes .Cannabis sativa industrial hemp varieties of high breeding value kindly provided by Gruppo Padana  were collected in December 2020 and stored at −20 °C. Varieties were selected based on their geographical origin  and their sex behavior (dioecious and monoecious). Detailed information is presented in Fresh samples from 104 individuals representing 11 different ® 96 Plant Kit”  following the manufacturer’s instructions. The quality of the genomic DNA samples was assessed by electrophoresis on a 1% (w/v) agarose gel stained with 1X SYBR® Safe™ DNA Gel Stain  in Tris–acetate-EDTA (TAE) running buffer. The yield and purity were evaluated using a NanoDrop 2000c UV–vis Spectrophotometer . Following DNA quantification, all the DNA samples were diluted to a final concentration of 20 ng/μL to be used as templates for PCR amplification.Genomic DNA (gDNA) was extracted from 70–100 mg of each sample using the “DNeasy® 96 Well Thermal Cycler  as follows: 95 °C for 5 min; 35 cycles at 95 °C for 30 s, 55 °C (or 57 °C) for 45 s and 72 °C for 45 s; and a final extension of 30 min at 60 °C. The quality of the PCR products was assessed by electrophoresis on a 2% (w/v) agarose gel stained with 1X SYBR® Safe™ DNA Gel Stain  using Tris–acetate-EDTA (TAE) running buffer. DNA fragment capillary electrophoresis was then performed with an ABI PRISM 3130xl Genetic Analyzer  using LIZ500  as the molecular weight standard. Fragment analysis was conducted using Peak-Scanner V1.0 . A subset of 20 primer pairs was selected based on their amplification capability, polymorphism and repeatability. These primer pairs were organized into four multiplexes (The amplification reactions were performed using the three-primer strategy reported by Schuelke  with somtiplexes  and thene), Levene’s observed heterozygosity  and the average heterozygosity  were computed for each SSR locus and over all SSR markers. PopGene software was also used to estimate F-statistics [is) and between (Fit) subpopulations as well as the fixation index (Fst), according to Wright [m) estimates among subpopulations were derived from the fixation index as described by McDermott and McDonald [Statistical analyses for all SSR marker loci were performed using the PopGene software package v. 1.32 . The obsity , Nei’s atistics , includio Wright . The pheo Wright . Gene flMcDonald .The genetic similarity (GS) in all the pairwise comparisons and the principal component analysis (PCoA) for the two main dimensions were conducted under default settings using NTSYS software package v. 2.21c . MoreoveC. sativa collection was investigated using the model-based (Bayesian) clustering algorithm implemented in STRUCTURE software v.2.2 [5 and a final run of 106 Markov chain Monte Carlo (MCMC) steps were set. GENALEX v 6.503 [The population structure of the re v.2.2 , which gre v.2.2  was used v 6.503  was usedTo predict the sex of dioecious individuals (61 out of 104) at the seedling stage,  develope®-one apparatus (Advance®) with Tris-acetate-EDTA buffer (TAE) and SYBR Safe for staining. The presence and size of PCR products were visualized using an UV transilluminator (Uvitec Cambridge®).Electrophoresis was performed using a 1.5% agarose gel on a MupidAny possible linkage disequilibrium existing between SCAR119 and the SSR loci previously analyzed was estimated and tested by Fisher’s exact test. A probability lower than 0.01 was selected to indicate a statistically significant amount of disequilibrium. All calculations and analyses were conducted using Genetic Data Analysis (GDA) version 1.0 software .Cannabis sativa is a high-demand crop with a long human history of medicinal, agricultural, industrial, and recreational uses. However, there is a lack of knowledge of this valuable plant in many fields of science, including the use of genomics for breeding new varieties and tracing their commercial derivatives.C. sativa that may be useful both for marker-assisted breeding of new varieties and for unequivocally identifying specific varieties already on the market or assessing their genetic identity. The availability of easy-to-use molecular tools for the authentication of newly released varieties is also crucial for protecting plant breeders’ rights and Cannabis derivatives’ consumers.Our research focused on the implementation and validation of an informative, reliable, and reproducible multilocus genotyping system in C. sativa varieties. This information could be exploited for planning crosses and predicting heterosis as an expression of hybridity in experimental F1 populations based on the allelic divergence and genetic distance of the selected parental lines.First, we demonstrated the effectiveness of our novel set of SSR marker loci for assessing the genetic distinctiveness, uniformity, and stability of individual varieties as well as for estimating heterozygosity/homozygosity statistics of single plants or populations and the extent of genetic variation within and genetic relationship among different C. sativa.Finally, our study on linkage disequilibrium demonstrated a correlation between two newly developed SSR marker loci and the well-known sex determination locus, SCAR119, which may assist further investigations on dioecy in Knowing the parental genotypes would enable not only protection of newly registered varieties but also assessment of the genetic purity and identity of the seed stocks of commercial F1 hybrids and certification of the origin of clonal samples (cuttings) of unknown derivation. Moreover, the newly developed panel of SSR markers not only discriminated southern European samples  from northern European samples  but also assigned each sample to a single variety of hemp or its country of origin with only a few exceptions (<5%).Cannabis market for managing intellectual property rights in the Cannabis seed industry and protecting professional producers of hemp cuttings and derivatives.We are confident that the DNA-based labeling of varieties covered by patent protection represents the only solution in the


Salvelinus fontinalis) from 22 small lacustrine populations, genotyped at ~32,400 mapped SNPs. We observed highly variable patterns of domestic ancestry between each of the 22 populations without any consistency in introgression patterns of the domestic ancestry. Our results suggest that such lake-specific ancestry patterns were mainly due to variable associative overdominance (AOD) effects among populations . Signatures of AOD effects were also emphasized by highly variable patterns of genetic diversity among and within lakes, potentially driven by predominant genetic drift in those small isolated populations. Local negative effects such as negative epistasis  potentially reflecting precursory signs of outbreeding depression were also observed at a chromosomal scale. Consequently, in order to improve conservation practices and management strategies, it became necessary to assess the consequences of supplementation at the population level by taking into account both genetic diversity and stocking intensity when available.The interplay between recombination rate, genetic drift and selection modulates variation in genome-wide ancestry. Understanding the selective processes at play is of prime importance toward predicting potential beneficial or negative effects of supplementation with domestic strains . In a system of lacustrine populations supplemented with a single domestic strain, we documented how population genetic diversity and stocking intensity produced lake-specific patterns of domestic ancestry by taking the species’ local recombination rate into consideration. We used 552 Brook Charr ( Genetic admixture resulting from introgressive hybridization is a fundamental mechanism influencing populations and species evolution ,2,3,4,5.One important factor to consider for understanding the evolutionary outcomes of admixture is the local variation in recombination rate . In the e genome . Alternae genome , positive genome ,26). Ovee genome . Therefoe genome ,23. The S. fontinalis) is a socio-economically important fish species supporting a major recreational fishing industry in eastern North America. Consequently, the species has a long history of intense supplementation . In Eastern Canada, the domestication of local strains and the development of hatcheries has increased to supplement rivers and lakes over the last century [To date, the understanding of such processes shaping genome-wide admixture landscapes remain obscure due to limited number of empirical studies that specifically addressed this issue ,23. Cons century ,29,30. H century  with an  century ,32. Our  century , and we  century . We obse century ,31,33. HWe predicted three alternative evolutionary scenarios considering the relationships between genome-wide domestic ancestry rate variation and (i) local recombination rate, (ii) local genetic diversity and (iii) lake-specific stocking history A–C. ScenThe dataset used here and produced by Létourneau et al. (2018) comprises the genotypes of 553 Brook Charr collected from 22 isolated lakes from two wildlife reserves (Mastigouche and St-Maurice) in Québec, Canada as well as 37 individuals from the Truite de la Mauricie aquaculture domestic brood stock . These lThe SNP calling and ancestry inference of the 22 populations have been performed in . BrieflyWe used the ancestry estimates provided in Leitwein et al.  to perfoWe identified regions presenting excess or deficit of domestic ancestry considering local variation in recombination rate. To do so, we built a linear mixed model, where the log-transformed domestic ancestry rate was introduced as the response variable and the standardized  recombination rate was included as the explanatory variable . The LGWe examined if and how local genetic diversity, stocking intensity  and recoR2 to quantify the proportion of variance explained by the explanatory variables only.At the genome level, we used linear mixed models where the log-transformed local domestic ancestry rate was included as the response variable. Recombination rate, genetic diversity and stocking intensity were standardized and incorporated as explanatory terms in the models. To consider the non-independency of ancestry estimates across windows, the LGs and the 2-Mb windows were treated as random effects in the models. We used a likelihood ratio test to assess the significance of the tested relationship by comparing the models with and without the explanatory term. We calculated marginal p-values to evaluate the significance of the three explanatory variables across linkage groups. To correct for multiple testing, we applied the conservative Bonferroni correction and only values with p < 0.001 were considered significant  [We then investigated how domestic ancestry was influenced by local genetic diversity, stocking intensity and recombination rate at the linkage group (LG) level. For this, linkage groups were analyzed separately by building linear mixed models which included as fixed effects the best-supported combination of variables  . All ana/42 LGs) .The genome-wide level of domestic ancestry rate was estimated for each population using the 405 late-hybrid individuals and an average of 32,442 ± 1799 mapped SNPs per population . The domThe level of genetic diversity estimated within 2MB sliding windows was highly variable both among and within populations. The mean population genetic diversity ranged from 0.157 (POR population) to 0.285 (TEM population). The MIL, BRU, GAS and VIE populations also displayed relatively low genetic diversity, with a mean of 0.158, 0.166, 0.168 and 0.176, respectively . Within R2 and the marginal R2 of the full model  recombination rate was included as the explanatory variable) were 0.084 and 0.015, respectively ; χ2Stocking= 4143.9, p < 2.2 × 10−16; coefficient slope = 4.4× 10−3; ; χ2Recombination = 1797.7, p < 2.2 × 10−16; coefficient slope = −3.41 × 10−3 ; Diversityβ = −4.950 × 10−3, p < 2.2× 10−16; Recombinationβ = −3.418× 10−3, p < 2.2 × 10−16; Stockingβ= 4.441 × 10−3, p < 2.2 × 10−16)  ectively . The lik6) i.e., B.At the linkage group level, we observed contrasted patterns of relationships between domestic ancestry, local recombination rate, local genetic diversity and stocking intensity among LGs . Ten LGsOur study suggests that genetic admixture resulting from supplementation of Brook Charr populations with a domestic strain during the last century produced a lake-specific pattern of ancestry modulated by the interplay between local recombination rate, local genetic diversity and stocking intensity. As previously shown by Létourneau et al. (2018)  based onEvidence for associative overdominance was supported by prevailing domestic ancestry in low recombining and low diversity genomic regions which could result in the masking of potentially deleterious alleles. AOD effects are particularly expected when the foreign strain used for supplementation harbors a higher level of genetic diversity than populations being supplemented ,49. In opression ,51. The sion [Ne  and tendsion [Ne . An incrsion [Ne ,54,55,56sion [Ne  and/or tsion [Ne .Drosophila melanogaster [Although AOD could be the main mechanism shaping domestic ancestry patterns at the genome level, the strength of its effect was variable among LGs. The domestic ancestry landscape was dominated by AOD in 10 LGs , where wnogaster , wherebynogaster .e) of lacustrine Brook Charr populations is generally very small , geneti32:28 in ,37 likel32:28 in .Negative epistasis also interplayed with AOD in modulating the dynamics of the genome-wide variation in domestic ancestry rate, with more domestic ancestry observed in high recombining regions of six LGs. In theory, hybridization between two species and even divergent populations of the same species may lead to “Dobzhansky–Muller” incompatibilities ,62,63,64e and a low level of genetic diversity. Yet, this potentially positive asset must be considered cautiously as the use of the same domestic strain to supplement multiple populations can lead to an homogenization of the population genetic structure [Ne [Assessing the evolutionary mechanisms at play and their consequences in the context of population supplementation can help to better understand the tradeoff between costs and benefits of human-driven hybridization that may result from supplementation practices . Stockintructure  and to ttructure ,75. Moretructure ,77. Finature [Ne .To conclude, our study emphasizes the need for conservation biologists to examine how the complex interplay between the introduction pressure of exogenic genetic makeup, genetic diversity and recombination rate along the genome modulates introgression landscapes of recipient populations. As such, this study offers new avenues for the study of the mechanisms shaping the evolution of exploited populations and regulating the dynamics of hybridization, either occurring naturally  or caused by humans.


Alternaria alternata is one of the most important fungi causing various diseases on citrus worldwide. In Morocco, Alternaria black rot (ABR) and Alternaria brown spot (ABS) are two major diseases causing serious losses in commercial cultivars of citrus. The aim of the present work was to study the genetic diversity and the population structure of isolates belonging to sect. Alternaria obtained from infected citrus fruits, collected from seven provinces at different locations in Morocco . Forty-five isolates were analyzed by sequence-related amplified polymorphism (SRAP) markers, and cluster analysis of DNA fragments was performed using UPGMA method and Jaccard coefficient. Cluster analysis revealed that isolates were classified in four distinct groups. AMOVA revealed also a large extent of variation within sect. Alternaria isolates (99%). The results demonstrate that no correlation was found among SRAP pattern, host, and geographical origin of these isolates. Population structure analyses showed that the Alternaria isolates from the same collection origin had almost a similar level of admixture. Citrus spp., Rutaceae) is one of the most important crops due to its high annual worldwide production. A total of 124 million tons (Mt) was produced in 2016 [Citrus  Keissl [Alternaria diseases affecting susceptible citrus genotypes around the world. The tangerine pathotype produces brown to black lesions on young leaves, twigs, and fruits with or without a chlorotic halo and causes corky lesions on mature fruit [Alternaria species cause three other diseases in citrus, including Alternaria leaf spot of rough lemon and rangpur lime [Citrus sinensis fruits, artificially inoculated with Alternaria alternata [Alternaria alternata. The Alternaria species causing citrus brown spot were identified as belonging to Alternaria alternata and A. arborescens species complexes [Alternaria brown spot of tangerines (ABS) caused by the fungus ) Keissl , 11 is ore fruit , 12. Altpur lime , Alternapur lime , and Manpur lime . The ABRpur lime . The samlternata . In addilternata . Accordilternata , there iomplexes .Alternaria spp. population circulating in Morocco, genetic diversity studies of the Alternaria pathogen are an important approach to understand its worldwide evolution and determine the population structure of this fungus. In this context, several profiling methods have been widely used to characterize the genetic variability of citrus-associated Alternaria species. These techniques include random amplified polymorphic DNA (RAPD) [(RFLP) [Ganoderma lucidum [Sclerotinia sclerotiorum [Auricularia auricular [Lentinula edodes [Tricholoma matsutake [Auricularia auricula-judae [Rhizoctonia solani [Pyricularia oryzae [To gain insights about A (RAPD) –20, amplA (RAPD) , 22, intA (RAPD) , and res [(RFLP) . In comp [(RFLP) . As demo [(RFLP) , it is e lucidum , Sclerotrotiorum , Auriculuricular , Lentinua edodes , Tricholatsutake , Auriculla-judae , Rhizocta solani , and Pyra oryzae .Alternaria sect. alternata associated with citrus rots. In particular, the internal transcribed spacer (ITS) has been extensively used [β-tub) [Different phylogenetic loci were used to identify the species within ely used , 35–38, ely used , 39, endely used , 40, 41, [β-tub) , 20.Alternaria in citrus crop. Due to the abundance of Alternaria species in Morocco [Alternaria spp. isolated from citrus fruit in Morocco using SRAP markers and (ii) to confirm the identity of citrus-associated isolates of Alternaria circulating in Morocco.To date, there is no study reporting the genetic diversity of Moroccan  Morocco –44 whichAlternaria spp. were collected from seven provinces in Morocco from markets, packinghouses, and orchards during the period 2017-2018  and incubated at 25°C. The morphological identification of conidia was realized after 3 or 4 days of incubation using a microscope at an objective of 40x. Alternaria sp. colonies were transferred to fresh PDA medium and stored at 4°C until use.Forty-five isolates of 017-2018   CTAB, and 0.02% (v/v) of β-mercaptoethanol) and incubated to 65°C for 1 hour. A volume of 0.6 ml of chloroform isoamyl : alcohol (24 : 1—v/v) was added, and the mixture was centrifuged at 13000 rpm for 10 min. The supernatant was recovered in a new tube, and DNA precipitated overnight by isopropanol. Finally, the DNA was washed with 200 μl of ethanol (75%) and dissolved with sterile ultrapure water. The purity and quality of extracted DNA were assessed by a spectrophotometer at 230, 260, and 280 nm. For SRAP reactions, the concentration was adjusted to 25 ng/μl.For DNA extraction, mycelia were collected in single-spore cultures of the isolates grown in PDA for 7 days at 25°C. The total DNA was extracted following the modified CTAB method . A totalμl containing 1 U of Taq DNA polymerase, 1X buffer, 0.5 μM of each primer, and 25 ng of DNA template. The amplification of DNA was programmed with an initial denaturation at 94°C for 5 min followed by 5 cycles with denaturation, annealing, and extension, respectively, at 94°C, 35°C, and 72°C for 1 min for each step. Then, 35 cycles were added with the annealing temperature set at 50°C. The PCR products were analyzed on polyacrylamide gel stained by ethidium bromide and visualized using UV transilluminator.SRAP-PCR analysis was performed by assessing for polymorphism, 30 combinations of primers (five forward/six reverse) , followiAlternaria strains  were selected from our collection for molecular identification. Internal transcribed spacer (ITS) region of rDNA was amplified. PCR products were Sanger sequenced . To perform the phylogenetic analysis, ITS sequences of reference strains were retrieved from GenBank and used , where fi is the frequency of band presence for locus I [The molecular data of variability were scored for the presence or absence of the amplification profile for each primer combination, respectively, as 1 or 0. Efficiency of SRAP markers was evaluated with the polymorphism rates of primers and polymorphism information content (PIC). The PIC was calculated as 2 locus I .The percentage of polymorphic loci, heterozygosity, and Shannon's information index were calculated for the genetic diversity analysis using GenAlEX version 6.5 . MoleculAlternaria spp. isolates from citrus fruits. Each simulation considered in 10,000 iterations after a length burning period of 1,000. The true number of clusters (K) of the admixture test was estimated, afterward, from the Structure Harvester web tool [STRUCTURE software v.2.3.4  and Bayeweb tool .A total of 30 primer combinations were initially tested for SRAP analysis. The result allowed to select six primer combinations showing the highest polymorphism . The total number of bands generated by each primer varied from 10 (ME3/EM6) to 32 (ME2/EM6) with an average of 22.3. The polymorphism rate ranged from 99.3 to 100%, with an average of 99% of number of polymorphic bands . The PICI), expected heterozygosity (He), number of different alleles (Na), and number of effective alleles (Ne) were observed in Kénitra, with 0.41, 0.26, 1.89, and 1.44, respectively, while the lowest values were observed in Larache with 0.09, 0.06, 0.62, and 1.11, respectively.According to SRAP marker analysis, the results revealed various levels of genetic diversity indices . The perThe genetic distance was calculated to determine the similarity among the isolates based on their geographical origin. The results revealed that the genetic distance was very low between Kénitra and Sidi Slimane populations (0.030), while it was very high between Salé and Khemisset, Salé and Sidi Slimane, then between Larache and Beni Mellal (0.212) . MoleculUPGMA cluster analysis of SRAP data, using Jaccard coefficient, revealed four distinct groups at 60% dissimilarity mean level, with a maximum of 86% and a minimum of 25%. The dendrogram illustrated in Alternaria isolates were genetically structured using the STRUCTURE software. The true number of clusters (K) was identified based on the Bayesian approach. Structure Harvester web tool findings indicated that the highest value of delta K equals 3. The Bayesian cluster analysis revealed, afterward, four main groups with the best identified K value  . The topRhizoctonia solani infecting pulse crops in India, using this molecular marker. Longya et al.[Pyricularia oryzae, in Thailand.Sequence-related amplified polymorphism (SRAP) is an adequate molecular marker widely used to assess the genetic diversity in plants and fungi , 54–56. ya et al. used botAlternaria spp. obtained from Moroccan citrus. The results indicates a total of 133 of polymorphic bands generated by six primer combinations with an average of 22.16 bands per primer combination. The mean polymorphism rate (99%) and Shannon's index (0.27) confirmed also high levels of genetic diversity of the isolates. The same pattern was reported by [A. alternata from citrus in southern Iran, based on RAPD markers using eight primers. The average of amplified bands was 27.12. Furthermore, the Brazilian isolates of A. alternata collected from Tangerine were characterized based on ISSR markers and 20 polymorphic bands, the isolates revealing low genetic variability in three groups and high diversity only in last group [In the present study, SRAP marker was used to evaluate the level of genetic diversity within and among 45 isolates of orted by , who obsst group .Alternaria isolates.Several research used the Polymorphism Information Content Values (PICv) to assess the genetic diversity among species. According to , the higAlternaria isolates and their distribution in Morocco. These results are in accordance with [A. alternata populations sampled from tangerines in Italy and reported that there was no correlation between geographical origin, host, and year of isolation. In another study, a slight effect of host plant and geographical location on genetic variation in A. alternata obtained from seeds of Amaranthus was observed using the RAPD technique [A. alternata spores, which can cover enormous distances. In contrast, other works reported that the genetic diversity of A. alternata collected from Citrus [A. solani originating from the same field of potatoes in Germany.The dendrogram constructed in this study using the UPGMA method distinguished four main groups, based on the molecular diversity of isolates and their geographic origins. The clustering results showed no significant correlation between the genetic variability of nce with  who asseechnique . As descechnique , the absm Citrus  and potam Citrus  was depem Citrus  detectedA. brassicicola (86%) was higher than among them (14%). In another study, [A. alternata from Pinus tabulaeformis detected by random amplified microsatellites (RAMS). The results showed that there was no correlation between the fungal genotypes and host tissue. Furthermore, [A. solani in China using SSR markers.Our findings of AMOVA test showed the highest genetic variation within populations (99%), whereas the level of interpopulation variation was only 1%. This is in accordance with  who obser study,  found hihermore,  detect hAlternaria isolates of the present study selected were assembled with five other strains of Alternaria used as references. In particular, the ITS sequences of Alternaria species isolated from citrus were identical to those of A. alternata, A. tenuissima, A. arborescens, A. gaisen, and A. longipes. This result is in accordance with the finding in [Alternaria isolates from citrus and seven other species including A. alternata, A. longipes, A. infectoria, A. tenuissima, A. gaisen, A. arborescens, and A. mali based on MtLSU phylogenies. In another study, Armitage et al. [Alternaria studied were grouped with A. alternata, A. tenuissima, and A. mali (EGS references). Their findings indicated that A. alternata subsp. arborescens, A. alternata subsp. gaisen, and A. alternata subsp. tenuissima were considered subspecies within the A. alternata species group. In addition, among twenty isolates of Alternaria spp. collected from citrus, eighteen were referable to A. alternata CBS references and two referable to A. arborescens CBS references based on the ITS and endo-PG sequencing [A. alternata species when the phylogenetic analysis is based on endo-PG, ITS, β-tub, and SCAR marker (OPA1-3 and OPA2-1) sequences.The phylogeny analysis results showed that all the 11 nding in , which re et al.  based onAlternaria isolates originating from seven provinces in Morocco. SRAP markers revealed high polymorphism rate with an average of 99%. Furthermore, AMOVA results demonstrate that the level of genetic diversity was higher within the Moroccan Alternaria populations (99%) than among them (1%). Cluster analysis constructed according to the genetic diversity of the isolates and their distribution generated four distinct groups. These findings indicate that SRAP markers could be an adequate method to be used for genetic structure and molecular differentiation studies among and within Alternaria populations. Molecular identification by sequencing of the ITS region confirmed that the selected Moroccan strains belong to the A. alternata species complex. The reported knowledge of genetic diversity and population structure in this study furthers our understanding of the Alternaria pathogens on citrus. This provides importance for selecting the resistance citrus cultivars and reduces, furthermore, the pre- and postharvest losses caused by species of Alternaria sect. alternata. The collection from other provinces in Morocco could be appropriate to evaluate the variability of Alternaria on a large scale.The present study concerned the assessment of genetic differentiation of