Camelus dromedarius) and a work to establish the organization of the dromedary genome at chromosome level were recently published.Dromedary camels are unique in their morphological and physiological characteristics and are capable of providing milk and meat even under extreme environmental conditions. Like other species, the dromedary camel has also benefitted from the development of the molecular genetics to increase the knowledge about different aspect in camel genetics . In this paper we review the different molecular genetic technics used in this particular species and future prospects. Dromedary genetic studies started in the end of the 1980s with phenotypic evaluation and the attempts to highlight the protein and biochemical diversity. In the 2000s, with the development of molecular markers such as microsatellites, genetic diversity of different types in several countries were estimated and microsatellites were also used for parentage control. In terms of genetic characterization, microsatellites revealed a defined global structure, differentiating East African and South Arabian dromedaries from North African, North Arabian, and South Asian individuals, respectively. Also, mitochondrialDNA sequence analysis of ancient DNA proved to be crucial in resolving domestication processes in dromedaries. Ancient and modern DNA revealed dynamics of domestication and cross-continental dispersion of the dromedary. Nuclear SNPs, single nucleotide polymorphisms changes that occur approximately each 1000 bps in the mammalian genome were also applied in some studies in dromedary. These markers are a very useful alternative to microsatellites and have been employed in some studies on genetic diversity and relevant phenotypic traits in livestock. Finally, thanks to the use of Next Generation Sequencing (NGS) the whole-genome assemblies of the dromedary ( Genetic characterization and assessment of genetic diversity is the primary step in the conservation and the management of genetic resources . GeneticCamelus bactrianus and Camelus dromedarius. The split between Old and New world camelids was estimated by using molecular studies to have happened 11–16 million years ago (Camelus dromedarius) and two-humped (Camelus bactrianus) camel species was estimated between 4.4 and 8 million years ago (Camelus ferus) has been recently recognized as a separate species, based on molecular genetic data especially by mitochondrial DNA and nuclear markers and the time of separation was estimated around 0.6 and 1.8 million years ago . Old World camelids have a specific morphological and physiological characteristic and can provide milk and meat even under extreme harsh conditions. Dromedary camels first appeared was estimated in the middle Eocene (around 40 million years ago) and the first ancestors of the camelid’s family were found in North America . Afterwaears ago  or 25 miears ago . The divears ago . The wilears ago .Investigations on Dromedary genetics started in the end of the 1980s with phenotypic evaluation and the attempt to highlight the protein and biochemical diversities. In the 2000s, with the development of molecular markers such as microsatellites, genetic diversity of different types or breeds of dromedary camels was estimated in several countries  and micrCamelus dromedarius) were published (GenBank assembly accession: GCA_000803125.1) (Camelus ferus) (GenBank assembly accession: GCA_000311805.2) (Camelus Bactrianus) (GenBank assembly accession: GCA_000604445.1 (With the implementation of the Next Generation Sequencing (NGS) technique, two whole-genome assemblies for the camel (03125.1)  with the11805.2)  and two 604445.1  and GCA_604445.1 ; while, 604445.1 .Several genetic markers such as microsatellites, mtDNA and SNP can be used for genetic characterization of different species or breeds, parentage control and/or determination of traits of economic interest by genome wild associations studies (GWAS), an essential step for their use for selection assisted by markers or introgression.Microsatellites are used in studies aimed at characterizing genetic diversity studies because of their simple use and also the very low genetic variation in protein polymorphism . A largeA set of Camelidae microsatellites was generated from published data on New World camelids: Alpacas and Ilamas , and sevIn 2002, Mariasegaram and collaborators were able to determine eight camel-specific microsatellites: CVRL01, CVRL02, CVRL03, CVRL04, CVRL05, CVRL06, CVRL07 and CVRL08.The international panel on Animal Genetic Diversity  recommenFurthermore, the different studies on dromedary genetic diversity were not limited to these 16 microsatellites, but used instead a range of different microsatellite markers whose the number and name of which differ from one study to another. Markers such as YWLL02, YWLL29, YWLL36, YWLL40, LCA18, LCA33 and CMS58, show a low amount of variability; whereas YWLL08, YWLL09, YWLL38, YWLL44, YWLL59, VOLP03, VOLP08, VOLP10, VOLP32, VOLP67, LCA66, CVRL01, CVRL05, CVRL06, CVRL07 and CMS50 show much more alleles per locus and also high PIC values. These markers are useful in describing heterozygosity levels and are more informative .There is only one study, carried out by The use of mitochondrial DNA (mtDNA) reflects the maternal inheritance and is useful for the establishment of genetic variation between species. For example, 1.9% nucleotide difference in the mitochondrial control regions (CR) was determined between Mongolian domestic and wild Bactrian camels . On anotSNPs are modifications of a single base pair that occur approximately every 1,000 bps in the mammalian genome . They arC. dromedarius and C. bactrianus for the identification of gene and identifying polymorphism in camel at nucleotide level (SNPs). They identified 24 and 10 nonsynonymous SNPs in C. dromedarius in the heart and the kidney, respectively. In another study, The development of SNP markers that cover the coding part of genome are also needed to understand the relationship between genetic and phenotypic variations in camels or other species. In these sites, SNPs are divided in synonymous, without any effect in the amino acid sequence and nonsynonymous affecting the amino acid sequence of protein . In thisIn another context, In terms of genetic studies in livestock, SNPs have three main advantages over microsatellites: a more precise estimates of population-level diversity, a higher power to identify groups in clustering methods, and an ability to consider local adaptation . These aIn the biannual conference of the International Society for Animal Genetics, the Camel Comparison Test (CCT) for the laboratory developing parentage test for dromedary was discussed in a workshop named “Applied Genetics and Genomics in Other Species of Economic Interest” since 2016. For the parentage control, a minimum of eight microsatellites markers are needed  and are named Core panel in the CCT. For this test in 2016, twenty-four samples and one reference sample were submitted to all the laboratories participating in the CCT. A deadline was given and the participants were asked to send their results for the core panel which would be considered in the ranking system for an accreditation. It was possible to add nine other microsatellite markers in the back-up Panel  and 30 other microsatellites can be used also to compare results between participating laboratories. In the last CCT, the overall marker concordance among laboratories was good (>95%) for six of the eight markers in the Core Panel. Only two markers showed a lower concordance: LCA37 (86%) because of missed alleles and wrong allele binning and YWL44 (87%) because of a missed allele.n = 620), United Arab Emirates (n = 53) and Africa (n = 16) were used to build a database of unrelated adults. The 17 microsatellites were separated in three multiplex reactions and a high probability of parentage exclusion (PE = 0.9999) was found. PE is an index allowing quantification of the percentage of incorrect detected affiliations. They conclude that this multiplex system clearly demonstrates the importance of DNA testing to ensure accurate identification and allocation of parentage in reproductive centers.Different studies tried to use different panels of microsatellites to evaluate the exclusion power for their dromedary populations. In 2005, Nolte et al. used 16 microsatellites for the evaluation of genetic diversity and for parentage analysis in cattle. Five calves were compared to their known parents and an unrelated male. It was successful in all cases. Only one mismatch at the VOLP08 locus was observed in one calf. They conclude that this mismatch is possibly due to a mutation or a laboratory typing error. –6 and 1/55.10–6  were determinated for five camel populations by using seven microsatellites markers (VOLP03 YWLL44, YWLL59, CVRL01, CVRL05, CVRL06 and CVRL07. PE varied from 95 to 97% with one parent and was higher than 99.99% with two parents for the five populations. The PI of individual camels varied between 1/8.10/55.10–6 . They noIn Tunisia, With the actual development of new molecular biology techniques and with regard to several other species, it will probably be obvious that the establishment of parentage control using SNPs will soon be proposed by ISAG. Therefore, studies to choose the most informative SNPs on this subject should be carried out.Studies were conducted around the world on the genetic characterization and diversity of dromedary camels using microsatellites or SNPs . Each stA higher level of cross-breeding or a gain of genetic variation following genetic drift subsequent to migration from one area to another, and traditional herding practices and dromedary camel particular history of domestication likely occurring from a bottlenecked and geographically confined wild progenitor can explain the poor genetic variation . Hashim The main studies using microsatellites and undertaken in several countries are reported in The dromedary camel is a species of great zootechnical interest in several countries. Generally, camel genetic characterization studies have mainly been completed using microsatellite markers. However, to better characterize certain production interesting traits, other techniques using whole genome sequencing and SNPs are necessary. Currently, these techniques are under investigation to assess relation with some phenotypic trait. These studies will allow better understanding of this magnificent exotic species, better conservation of the different breeds and types of dromedary and would certainly provide better selection alternatives for the breeders.


Vitis sylvestris into the cultivated compartment during domestication events. So far, the present study is the first most representative and comprehensive analysis of Armenian grape germplasm.The knowledge of genetic diversity and relatedness among grapevine varieties is important for recognizing gene pools. One of the major goals of the present large-scale study was to evaluate the level and relationships of existing genetic diversity across Armenia, aiming to identify genotypes that could provide genetic insights into the Armenian grapevine germplasm structure. A combination of nuclear microsatellite markers and ampelography proved useful to determine the identity of collected samples recovered from old vineyards and home gardens. Synonyms, homonyms, alternative spellings, and misnomers were clarified. First-degree genetic relationships between autochthonous varieties were partly uncovered. Missing parents might still exist in old vineyards but were not sampled yet or might have disappeared over time. The continuation of prospections to fill that gap is planned. The high number of new bred varieties included in the study reflects the enormous breeding activity in Armenia. The high number of alleles, high level of observed and effective heterozygosity, and presence of female APT3-allele 366, which is absent in western European cultivars, illustrate the huge diversity of the Armenian germplasm. Presumably, these findings are related to recurrent introgression of Vitis vinifera subsp. vinifera and wild Vitis vinifera subsp. sylvestris and has played a key role in the long history of grape cultivation in the Southern Caucasus. The existence of immense grapevine biodiversity in a small territory is strongly linked with unique relief and diverse climate conditions assembled with millennium-lasting cultural and historical context. In the present in-depth study using 25 nSSR markers, 492 samples collected in old vineyards, home gardens, and private collections were genotyped. For verification of cultivar identity, the symbiotic approach combining genotypic and phenotypic characterization for each genotype was carried out. The study provided 221 unique varieties, including 5 mutants, from which 66 were widely grown, neglected or minor autochthonous grapevine varieties, 49 turned out to be new bred cultivars created within the national breeding programs mainly during Soviet Era and 34 were non-Armenian varieties with different countries of origin. No references and corresponding genetic profiles existed for 67 genotypes. Parentage analysis was performed inferring 62 trios with 53 out of them having not been previously reported and 185 half-kinships. Instability of grapevine cultivars was detected, showing allelic variants, with three and in rare cases four alleles at one loci. Obtained results have great importance and revealed that Armenia conserved an extensive grape genetic diversity despite geographical isolation and low material exchange. This gene pool richness represents a huge reservoir of under-explored genetic diversity.Armenia is an important country of origin of cultivated  Vitis genus, which consists of nearly 60 inter-fertile species, Vitis vinifera is the only species indigenous to Eurasia and is suggested to have first appeared ~65 million years ago [Vitis vinifera, two subspecies exist: V. vinifera subsp. sylvestris including the wild populations and V. vinifera subsp. vinifera, resulting from domestication of the wild progenitor and including about ten thousand cultivated varieties [Vitis vinifera spp. vinifera. According to the International Organization of Vine and Wine (OIV) the global grape area is estimated at 7.4 million hectares, with a production of 77.8 million tons of fresh grapes and 260 million hectoliters of wine .In the ears ago . Within arieties ,3. GrapeV. vinifera subsp. sylvestris and feral types, cultivated, and ancient indigenous varieties are common in this region [V. vinifera subsp. vinifera, an increased number of berries per cluster, a higher sugar content, the enlargement of bunch and berry size, seedlessness in table grapes  and the change in seed morphology, which is the most stable character to differentiate remains of wild or cultivated grape [Archaeological, historical, and genetic studies reveal that South Caucasus, Northern Iran and Southeast Anatolia are most likely the places of earliest grape domestication ,5. Theres region . The pros region . The maied grape ,8,9.Domestication of grapevines occurred nearly eight thousand years ago, during the Neolithic Age. After that, the migration of cultivars took place along with the spreading of wine culture from their primary domestication center in the Near East to Mesopotamia, Levant, Africa, and Europe ,11,12,13The World Wide Fund for Nature defined the Caucasus region as a Global 200 Ecoregion, based on criteria such as species richness, high levels of endemism, taxonomic uniqueness, and global rarity of major habitat types . The RepViticulture and wine industry in particular always played a vital role as the most important sectors of the Armenian economy, and the production of brandy is one of the main branches of its export. Wine production became industrialized already in the 1870s when Nerses Tairyan/Tairov started industrial production of vodka. Later, from 1887 on brandy production progressed on the territory of the former Yerevan fortress. During the pre- and Soviet Era, grape-growing and winemaking were leading branches of agriculture in Armenia and strongly connected to the development of capitalism and market demands in Russia. In the 1975’s the vineyard surface planned to be enlarged and reach peak levels up to 80–90 thousand ha. At that time, Armenia accounted for 72 percent of all brandy production in the South Caucasus despite its small territory . The indIn 2016, with the support of Food and Agriculture Organization (FAO), a nationwide program to collect, conserve and characterize Armenian grapevine germplasm was conducted. In the newly established Armenian National Grapevine Collection in Etchmiadzin 293 grapevine accessions were planted. On the map of the Republic of Armenia, viticultural regions and their most iconic grapevine varieties native for each area are presented in The precise number of Armenian varieties is not clearly known and there is often uncertainty about their real number since synonyms and homonyms occur. The rescue and conservation of grapevine genetic diversity in Armenia are particularly urgent since a large number of local native varieties are no longer cultivated or existing as single vines and are therefore at serious risk of loss.During the last years in parallel with wine industry development, only a limited number of varieties were used for wine production with a serious shift to single variety vineyards. The intensive cultivation of a small number of commercial cultivars has resulted in an alarming reduction in genetic diversity since only about 30 from 400 native grape varieties are used in wine and brandy production. Minor autochthonous cultivars having only a local significance in the different wine-growing regions are under-exploited. Their ignorance might be related to the lack of comprehensive characterization of native neglected varieties, especially to missing data on oenological and agronomical traits and partially, due to demands of the wine/brandy market. All of these arguments prove the necessity and importance of collection, conservation, characterization, and efficient use of grape germplasm resources, as well as knowledge of genetic diversity and genetic relationships between genotypes .Vitis species. They are widely used primarily for the differentiation and identification of cultivars, parentage analysis, and genetic mapping [Until recently, the only method traditionally used in Armenia for the characterization and identification of grapevine varieties was ampelography  a method based on morphological description mainly of shoot-tips, leaves, bunches, and berries . Ampelog mapping ,28,29,30Vitis International Variety Catalogue (VIVC)  and Réseau Français des Conservatoires de Vigne .Very little is known about the magnitude of grape germplasm in Caucasian countries, although this region is considered a center of grape diversity . To fillV. vinifera in Armenia [The presented research was part of the extensive research started in 2017 in the scope of the Armenian-German bilateral project intending preservation, promotion, and prominence of native grape germplasm towards recovering the untapped genetic diversity of  Armenia .Prospections were carried out in five traditional viticultural regions of Armenia: Ararat Valley (Ararat and Armavir districts), Aragatsotn, Vayots Dzor, Tavush, and Syuniq during the vegetation and harvest period. Sampling regions are reported in http://www.montpellier.inra.fr/grapegen06, 15 August 2021) project: VVMD5, VVMD7, VVMD25, VVMD27, VVMD28, VVMD32, VVS2, VrZAG62, and VrZAG79 were used for comparison of genetic profiles with the SSR-marker database of the Julius Kühn-Institut (JKI), maintaining about eight genetic profiles from distinct sources. Fingerprints from the European Vitis Database  produced during European project GrapeGen06 and resulting from COST Action FA1003 were used to find corresponding profiles [Total genomic DNA was extracted from 100 mg of young leaf tissue after grinding with MM 300 Mixer Mill system  and stored at −80 °C until use. DNA extraction was performed employing the DNeasy 96 plant mini kit  following to the manufacturer’s protocol. DNA concentration and quality were checked by spectrophotometric analysis and electrophoresis in 1% agarose gel. Microsatellite fingerprinting of genotypes were performed on 24 microsatellite loci (nSSRs) well distributed across the nineteen grape chromosomes as previously described ,33 , all forward primers were 5′-labelled with a fluorescent dye . The combination of markers with different labels and diverse fragment lengths allows one to perform the polymerase chain reaction (PCR) and grouped markers in seven multiplex pools, comprising two to five SSR markers characterized by similar annealing temperatures . The 2x The determination of flower sex was carried out for all genotypes collected throughout Armenia and was analyzed by a specifically designed APT3 marker from adenine phosphoribosyl transferase gene capable to distinguish flower sex: female (F), male (M) or hermaphrodites (H) .The genetic diversity among grapevine genotypes was estimated. The standardized nSSR genotyping data were used to determine the number of different alleles (Na), the number of effective alleles (Ne), Shannon’s Information Index (I), observed heterozygosity (Ho), expected heterozygosity  referred to as the inbreeding coefficient. The allele frequency for each nSSR loci was calculated as well. The GenAlEx software version 6.5 was used to compute genetic diversity statistics for each nSSR locus ,39. ClusParentage analysis was carried out by Cervus 3.0.7 using non-redundant grapevine genotypes to determine possible first-order kinship relationships: trios (mother-father-offspring) and duos (parent-offspring pairs) using the likelihood-based method implemented by software . Based oColony software (version 2.0.6.6) was applied to reconstruct genotypes used by Armenian breeders, but not available in the data set. Colony parameters were set up in order to perform one medium-length run with the full likelihood (FL) method, allelic dropout rate 0, and other genotyping error rates 0.0050 . InferreVitis Database and genetic profiles generated during COST Action FA1003 and bibliography. Three volumes of Armenian ampelographies , three volumes of Russian ampelographies , Caucasus and Northern Black Sea Region Ampelography (published in 2012) and Ampelography by Melyan et al. (published in 2019), represented the most important sources [The solid determination of trueness to type of grapevine genotypes required a combination of molecular fingerprinting, morphological description, and exhaustive bibliographic studies. The identity of each genotype was defined based on the analysis of 25 SSR markers and comparison of genetic profiles with almost eight thousand fingerprints documented in the JKI-SSR-marker database, the European  sources ,49,50. AVIVC variety number, prime name, Armenian variety name, accession numbers of varieties preserved in Armenian national grapevine collection, origin/pedigree given by breeder, color of berry skin, flower sex phenotype, flower sex genotype (ATP3 marker), utilization, viticulturual region, the status of identity, confirmation of variety based on leaf and bunch morphology, number of collected samples, bibliographic references for genetic profile identification and ampelographic references used for confirmation of trueness to type. The numbers of bibliographic references correspond to source codes in VIVC . Owing to the fact that no living references were available, morphological features of the analyzed varieties were compared with descriptions and photographs available in bibliographical references.An overview of the huge information gathered is displayed in A total of 492 genotypes were analyzed using 25 SSR-markers, revealing 216 unique profiles, with 271 genotypes being duplicate individuals such as synonyms, homonyms, or clones. Five mutants were identified, from which four are autochthonous Armenian grape varieties: Mormor, a berry color chimaera of Sev Areni, Marmari/Kishmish mrarmornyi, a chlorophyllic mutant, Vardaguyn Yerevani/Kishmish rozovyii a berry color mutant of Sultanina and Kishmish chernyi teinturier, a berry flesh color mutant of Sev Qishmish/Kishmish chernyi variety. In addition, a black berry color mutant of Muscat à petits grains blancs, sampled in an old vineyard was determined. Among the 216 unique profiles 66 were old autochthonous, 49 were new bred Armenian cultivars, and 34 were non-Armenian varieties with different countries of origin . No refeAmong analyzed genotypes the most frequently found grape varieties were Sev Areni (27 samples), Tozot (18 samples), Karmir kakhani (15 samples), Rizamat (10 samples), Apoyi khaghogh (9 samples) and Spitak Arevik (9 samples). Sev Areni and Tozot are the most emblematic ancient wine grape varieties and displayed a wide range of intravarietal clonal diversity. Apoyi khaghogh is one of the neglected grape varieties and is preserved only in few private vineyards in Vayots Dzor region. Karmir kakhani and Spitak Arevik are old autochthonous table grape varieties. All samples collected as Karmir Shabi, described in ampelography as an old table grape variety, matched the genetic profile of Rizamat.From the set of 271 redundant samples, a few cases illustrating variety identification, synonyms and homonyms, and both new named and unknown genotypes are presented in Flower phenotype was analyzed by APT3 marker capable to distinguish females from hermaphrodites or male plants. According to the obtained data among 221 distinct varieties, eight different allelic patterns were determined at APT3 loci: 27 genotypes have shown 268/268 (F), 14 genotypes 268/397 (F), 6 genotypes 268/336 (F), 1 genotype 336/336 (F), 54 genotypes 268/397/466 (H), 97 genotypes 268/466 (H), 21 genotypes 336/466 (H), and 1 genotype 268/336/466 (H) alleles. Thus, among analyzed genotypes 173 were hermaphrodite and 48 turned out to be female.Field phenotypic observations were carried out during the flowering period and matched flower phenotypes predicted by DNA analysis .V. vinifera subsp. vinifera were used in the present study. The range of allele size (Ra), number of different alleles (Na), effective number of alleles (Ne), Shannon’s information index (I), observation heterozygosity (Ho), expected heterozygosity (He), and fixation index (F) were calculated to assess the genetic diversity of Armenian grape germplasm. Statistics about the discriminatory efficiency of the 24 SSR markers are presented in Genetic data from 24 nuclear microsatellites across 221 unique grapevine varieties of The number of alleles per SSR locus ranged from 5 (VVIn16) to 25 (VVMD 28) and the mean allele number per loci was 14.485. The effective number of alleles, respecting alleles that occur at a relevant frequency within the sample, ranged from 2.035 for locus VVIn73 to 10.241 for locus VMC4f3.1, with a mean of 5.531. The following loci displayed high Ne values as well: VVIv37, VVIp31, VVS2 and VrZAG67. The highest Shannon’s information index (I) was observed in VMC4f3.1 locus (2.548) and lowest in VVIn73 (0.999), while the average among SSR loci was 1.9. Shannon’s information index is an important parameter mirroring the level of polymorphism. For microsatellite markers efficiency observed and expected heterozygosity  are considered to evaluate the genetic variability among analyzed varieties. The observed heterozygosity (Ho) ranged from 0.548 (VVIn73) to 0.914 (VVIp31), with an overall mean of 0.787. The expected heterozygosity (He) values ranged between 0.509 (VVIn73) to 0.902 (VMC4f3.1), with an average of 0.789. The overall mean of observed and expected heterozygosity was almost the same. Fixation index (F), a parameter reflecting a reduction in heterozygosity level and thus an indicator of inbreeding ranged between −0.099 (VVIp31) to 0.149 (VVIh54) with a mean value of 0. The observed negative F values indicated an abundance of heterozygote genotypes presuming random mating.Allele size (AS) and frequencies (AF) for each of the microsatellites are presented in The neighbor-joining (NJ) distance tree was constructed to study genetic relationships among the 221 grape varieties based on allele frequencies of 24 SSR loci. Two major clusters with subclusters were distinguished grouping native-known varieties together with new bred varieties and unknown, respectively non-identified vines and evidenced genetic relationships among analyzed grapevine genotypes . ClusterParentage analysis was carried out with 24 nSSR markers of 265 non-redundant grapevine genotypes. To increase the discovery of first-order kinship relationships, profiles of forty-four varieties of Armenian and non-Armenian origin were included from Lacombe et al., 2013 and the JKI-microsatellite database. Their choice was based on country of origin is Armenia and previously stated relatedness to Armenian germplasm . Colony In In addition, 185 half kinships  were found and duos are presented in Based on parentage analysis the varieties, which were frequently involved in Armenian germplasm by first-order relationship, were defined: Angur Kalan, Madeleine Angevine, Muscat Hamburg, Katta Kurgan, Karmrahyut, Seyanets S1262, Seyanets S484, and Hadisi.Vitis vinifera subsp. vinifera and wild Vitis vinifera subsp. sylvestris and played an essential role in the long history of grape cultivation in the Southern Caucasus [Armenia is an important center of origin both for cultivated Caucasus . The exiVitis genetic resources, such as identification of accessions and parentage analysis, solving problems and uncertainties related to homonymy, synonymy, misnaming, and inferring the genetic structure of grape populations [During the last twenty years, nuclear microsatellite markers, as efficient molecular tools and powerful complement of ampelographic characteristics, were prevalently applied for management of the ulations . The preulations . The desulations . The oldThe first Armenian Ampelography, which includes precise morphological, agro-biological, and technological characteristics of local and foreign grapevine varieties was published in 1947 . In the The present comprehensive research on grapevine genetic resources, prospected throughout traditional viticultural regions across Armenia, allowed to examine and sometimes revise available descriptions found in ampelographies, providing a more rigorous and newer prospect on the origins and relatedness of grapevine varieties in Armenia. Obtained results have great importance and revealed that Armenia preserved a wide range of grape genetic diversity despite geographical isolation of the country and low material exchange, which was also suggested by COST Action FA1003 . This geThe knowledge of genetic diversity and relatedness among grapevine varieties is important to recognize gene pools. One of the major goals of the present large-scale study was to evaluate the level and relatedness of existing genetic diversity across Armenia, aiming to identify genotypes that could provide genetic insights into the Armenian grapevine germplasm structure. It turned out that Armenian germplasm is a blend of different genotypes, exhibiting a high level of differentiation, resulting in higher-than-expected levels of heterozygosity. This is often observed in woody perennial crops where varieties are selected for their vigor and crop performance, indirectly endorsing high levels of heterozygosity ,54. EastIn the present study, the majority of the clones within a variety revealed no difference and were grouped as one variety cluster when all 492 individuals were subjected to neighbor-joining cluster analysis (cluster not provided). However, some of them such as Sev Areni, Nazeli, Garan Dmak, and Mskhali underwent somatic mutations and showed varying genotypes and, to some extent, varying phenotypes analogous ,57. ObseDuring the process of Armenian grapevine germplasm analysis, we have found cases, when genetically related varieties have shown very similar morphology and variety identification based only on visual observation was hard and cases, when clones of varieties noticeably differed in morphology without a change in the genetic fingerprints.The application of microsatellites as highly polymorphic molecular markers is a proven efficient tool describing the level of heterozygosity across and within grapevine varieties. In the present study, the neighbor-joining cluster analysis based on 24 SSRs was applied without considering the geographic origin of the genotypes. However, the analyzed set clearly demonstrated an obviously structured arrangement of samples according to geographic origin, particular characteristics such as muscat flavor or seedlessness and ancestry. Genetic relationships between autochthonous and new bred varieties were elucidated, as well as cases related to unknown respectively not described genotypes.A majority of the identified varieties were grouped in Cluster I including Armenian native and new bred cultivars, non-Armenian varieties and unknown genotypes. In Cluster I the ancient indigenous grape varieties Lalvari, Dzrali, Sev Lkeni, Sev Koghb/Arayatly gara uzum, originated from Tavush, a region next to the Georgian border, as well as Kakhet, Eraz and unknown genotypes 71, 34, 81, 87 were combined with Gorula, Maghlari Mskhviltvala, Saperavi Atenis, Mtsvane kakhuri and Rkatsiteli, native to Georgia. According to parentage analysis Sev Lkeni displayed PO relationship with Sev Koghb/Arayatly gara uzum and unknown genotype 87. For unknown genotype 81 Sev Koghb/Arayatly gara uzum and Rkatsiteli were proposed as parents. New bred cultivars in Cluster I are Eraz, an interspecific cross having in pedigree Rkatsiteli, Kutuzovski , whose pedigree given by the breeder was confirmed and the introduced American varieties Goethe and Salem. Carter x Schiava grossa as indicated progenitors of Goethe and Salem were confirmed. Carter is most likely extinct. However, Colony inferred the missing genotype based on nine presumed Carter offspring (data not published).Cluster analysis revealed genetic similarity among the old autochthonous grapevine cultivars Shiri khaghogh spitak, Levoni mug vardaguyn (named variety), Chragi Erkser, Eghegnadzori sev (named variety), Spitak Novrast/Kalili Belyi, Noyemberyani teghakan/Telki Kuruk, Voskehat, Garan Dmak, Varandeni, Chghleni, Hastakot and unknown genotypes 32, 28, 29, 5, 76, 50, 45, 3, 41, 9, 26, and 2 (consecutive order in the cluster). Surprisingly, Afus Ali (Lebanon) and Black Alicante (Spain) were involved in the group. Those non-Armenian varieties were sampled from private old vineyards. PO relationships were found among Hastakot and unknown genotype 2 and genotype 26. Hastakot is an old autochthonous Armenian variety and was never used in crosses by Armenian breeders. Thus, genotypes 2 and 26 are considered being ancient Armenian varieties, which identity could not be determined yet. The further bibliographical investigation is needed. The most iconic Voskehat and Garan Dmak, autochthonous grapes, have shown PO relatedness with Hadisi. PO relationship of Voskeat and Hadisi confirmed the finding of Lacombe et al. . Chragi Vitis Database [https://www6.montpellier.inrae.fr/vassal_eng/, 15 August 2021) [Vitis Database can be considered as a case of a misnaming. According to the Russian Ampelography Khalili Belyi is known under different designations in post-Soviet Union countries: in Turkmenistan Ak Khalili, in Dagestan Ay izyum, in Astrakhan region of RF Tsarskiy and in Armenia Novrast beliy/Spitak Novrast. According to the authors, Khalili belyi originated from Iran. The homonym Khalili is fairly abundant, varieties differ in morphology and biological characteristics, but are similar with respect to their early ripening time [One of the cases that required clarification is related to Kalili Belyi  variety. According to the first book of Armenian Ampelography by Tumanyan one of the recorded synonyms of Spitak Sateni is Spitak Khalili (spitak means white) . Spitak Database . In 2019st 2021) . It turning time . Thus, bClustering allowed grouping of indigenous wine grapes Karmir Koteni, Khndoghni, Sveni, Spitak Areni, Tozot with autochthonous table grapes Spitak Aldara, Spitak Arevik and Mskhali. In this group also unknown genotypes 80, 84, 62, 88, 36, 51 were arranged together with two new bred cultivars Masis and Vaghahas Areni and Mushketnyi from Russia. This group perfectly mirrored the geographic distribution of indigenous wine and table grapes Karmir Koteni, Khndogni and Sveni and Spitak Aldara and Spitak Arevik, respectively, with all the unknown genotypes. All these samples were collected from Syuniq region and Artsakh. For Karmir Koteni and Khndoghni first-order relationships were not found. Parentage analysis revealed PO relationships between unknown genotypes 62 and 88. In Ampelography by Poghosyan  and AivaUnexpectedly, the collected samples Karmir khach, Gyogyam, Itsitstseni, Karch mat, Karmir milagh, Salli, and Tozot showed matching genetic profiles. Gyogyam, Itsitstseni, Karch mat, Salli, and Tozot were described as distinct varieties in ampelographies. They all shared close morphologic characteristics such as circular, five-lobed leaves, conical, dense or very dense bunches and black, slightly elliptic/ovate berries covered by dense/middle dense layer of fax. The comprehensive comparison of bibliography and ampelographic features led to the final conclusion that these varieties are clones of Tozot. Karmir khach is a locally known name in Aghavnadzor village, Vayots Dzor region. The accession collected as Karmir milagh was a case of misnaming, since Karmir milagh is a documented synonym of Karmir kakhani.In Cluster I the most ancient and emblematic Armenian grape varieties Sev Areni, Mormor, Hadisi, Khatun Khardji, Sev Khardji, Vanqi, and Hakobi vordi collected from Vayots Dzor region and Spitak Berri and Chilar collected from Ararat Valley were grouped together with unknown genotypes 67, 6, and 16. The oldest and well-preserved industrial wine complex was discovered in 2007 in Areni village, Vayots Dzor region dating back to the end of the 5th and the first quarter of the 4th millennium B.C . The ancVIVC database Noyemberyani teghakan collected by us perfectly matched with ‘Lisyi Khvost’ (translated from Russian means foxtail) or ‘Tilki Kuyrugu’, ‘Telki kuruk’. However, the genetic profiles of Chilar and Noyemberyani teghakan were distinct and genetic relatedness was stated neither. Thus, Tulki Ghuyrughi can be considered as a case of homonymy. Probably the reason of confusion is related to the close morphology of bunch and berry shape. Both Chilar and Noyemberyani teghakan have oblong-cylindrical or cylindrical-conical, dense or loose, foxtail such as the shape of bunches and ovate berries. Genotype 16, whose identity could not be determined yet, is derived from a single plant. In the meanwhile, two further samples matching genotype 16 were recovered, proving its dissemination in former times.Parentage analysis, unexpectedly, underlined the key role of Hadisi participating in revealed trios and duos. Poghosyan  did a deThe half-kinship relationships of Hadisi as a genitor were found with Sev Areni, Garan Dmak, Voskehat, Khatun khardji, Karmrahyut and Genotype 67. Respective Khatun khardji, an endangered autochthonous wine grape variety, full parentage resulted from a liaison of Hadisi and Vanqi, the latter being also an old Armenian variety. A PO relationship between Sev Areni and Sev khardji was determined. For the great part of autochthonous varieties, only single plants were recovered, indicating the threat of ancient cultivars and emphasizing the relevance of these surveys to safeguard the genetic diversity of indigenous varieties and to prevent them from extinction.This group is encompassing also two representatives of the “Areni family”, namely Sev Areni and Mormor. During our surveys, 27 different clones were collected with matching genetic profiles and expressing unexpectedly high phenotype variability.The material was collected from different villages in the Vayots Dzor region, from vineyards older than 200 years. Sev Areni is the most iconic wine grape variety planted in Armenia for many centuries. Tumanyan described the variety in detail . Until 1Movuz and Lyustra are not documented synonyms of Sev Areni in any of the Armenian ampelographies. While in the Caucasus and Northern black sea region ampelography for the Meleyi N. variety the authors noted Movuz, Urza sev and Areni Cherniyi as synonyms, which is a true case of homonymy. The major differences among these genotypes are associated with bunch shape and compactness, in the case of Mormor variety also with grey berry color. Mormor was described by Poghosyan as a neglected variety, cultivated in old vineyards in Vayots Dzor region . The regAs shown in Movuz and Sev Areni have medium-sized and conical-shaped, sometimes winged bunches and ovate/elliptic berries with a rounded top, covered by greyish-blue bloom. Movuz was identified as a clone of Sev Areni and thus the opinion that Movuz is a distinct variety was contradicted . With reInterestingly, the group of unknown genotypes 16, 86, 95, 85, 93, 96, 31, 68, 70, and 55 clustered with endangered local wine grape Eraskheni and non-Armenian varieties Dunavski Lazur (Bulgaria) and Opsimos Edessis (Greece). Strikingly, seven unknown Genotypes  showed female flower sex confirmed by APT3 marker analysis. The material was collected from very old, out of cultivation vineyards in Artsakh. Based on the morphology of berries  and bunch compactness (middle dense/loose) they were considered feral types. Further analysis is required to clarify the status of these samples. It is important to underline, that in the scope of the present study an unpredicted high number of female varieties, especially among autochthonous genotypes, were found. Being cross-pollinated, most likely they have played an important role in the formation of genetic diversity of Armenian grape germplasm. For Eraskheni involved in this group, first-order genetic relationships were not found. Eraskheni is a very old neglected wine and table grape variety described by Tumanyan and Melyan ,50. SomeThe majority of Qishmish varieties were clustered involving ancient varieties Nazeli, Apoi khaghogh, Sev Qishmish, Marmari, Kishmish chernyi teinturier, Degin Yerevani, Vardaguyn Yerevani, Sermnali and Karmir Qishmish together with new bred cultivars Parvana, Arevar, Hrushaki, Ushahas Nazeli, Anush, and Zvartnots. Based on molecular fingerprinting the genetic profiles of old seedless varieties Marmari, Deghin Yerevani, and Vardaguyn Yerevani matched with Sultanina. Marmari/Kishmish mrarmornyi is a chlorophyllic mutant and Vardaguyn Yerevani/Kishmish rozovyii is a berry color mutant of Sultanina. Kishmish chernyi teinturier, considered as a berry flesh color mutant of Sev Qishmish/Kishmish chernyi variety. According to the parentage analysis, first-order relationships were found among Sultanina and Apoi khaghogh, Sermnali and Sev Qishmish varieties. According to the parentage analysis Sultanina as genitor of Nazeli was confirmed. Some authors referred Nazeli as new bred cultivar , which iTwo main groups were formed with new bred cultivars sharing common parents and unknown genotypes for which no genetic relationships were unraveled. Karmrahyut clustered with its offspring Arpa, Charentsi, Anushayut, Nerkarat, Merdzavan, Charentsi 2, and Artashati Karmir. The inferred Seyanets S 1212 was confirmed as the second parent. The usefulness of Colony software for reconstruction of genotypes, respectively, missing parents in pedigrees was demonstrated in previous studies as well ,71. OwinThe neighbor-joining analysis grouped Muscat varieties, some new bred varieties, and unknown genotypes in Cluster II. Armenian new bred Muscat cultivars Muscat desertnyi, Muscat deghin, Muscat haykakan and named cultivar Muscat spitak Merdzavani were grouped with non-Armenian Muscat varieties Muscat Ottonel, Muscat à petits grains blancs and Muscat à petits grains noirs. The cluster involved also the variety Moschato Mavro from Greece, a progeny of Muscat à petits grains blancs and the true progenitor of Muscat haykakan. Armenian new cultivar Arazi has Chasselas musqué in its pedigree. The unknown Genotypes 57, 15, 24, 22, and 66 could not be identified and no relationships were found. Further clarifications related to the status of these samples are required.Vitis sylvestris into the cultivated compartment during domestication events. Instability of grapevine cultivars was detected, showing three and in rare cases also four alleles at one locus. A deeper study of this quite frequent phenomenon will be carried out. So far, the present study is the first most representative and comprehensive analysis of Armenian grape germplasm. The majority of varieties is preserved non-grafted in the national grape germplasm collection at Etchmiadzin. Due to the recent arrival of Phylloxera in the Ararat valley, grafting on rootstocks is urgent and absolutely needed.Prospections in traditional viticulture regions across Armenia provided insights in the huge grapevine genetic diversity existing in the country. A combination of nuclear microsatellite markers and ampelography proved useful to determine the identity of collected samples recovered from old vineyards and home gardens. Synonyms, homonyms, alternative spellings, and misnomers were clarified. Well-identified and referenced grape genetic resources are a prerequisite for its utilization and the management of germplasm repositories. However, the assignment of variety names was not always successful. Sixty-seven genotypes could not be identified, due to missing genetic profiles in SSR databases or lack of names. Further bibliographical studies and cooperation with national germplasm repositories, preserving Armenian varieties is envisaged. First-degree genetic relationships between autochthonous varieties were uncovered. Missing parents might still exist in old vineyards but were not sampled yet or might have disappeared over time. Continuation of prospections to fill that gap is planned. The high number of new bred varieties included in the study reflect the enormous breeding activity in Armenia. Eleven non-determined genotypes were identified as new crosses due to the inferred parents involved in the cross. The high number of alleles, high observed and effective heterozygosity values, and presence of female APT3-allele 366, which is absent in western European cultivars, illustrate the huge diversity of Armenian germplasm. Presumably, these findings are related to recurrent introgression of www.vitis.am, 15 August 2021) and in Vitis International Variety Catalogue .On the basis of realized in-depth investigation, a true-to-type inventory of Armenian grape germplasm was carried out and is documented in Armenian Vitis Database (


P = 96.26%), number of effective allele (Ne = 2.653), observed heterozygosity (Ho = 0.584), expected heterozygosity (He = 0.550), total heterozygosity (HT = 0.666), and rare alleles (54) were observed which indicates that MPOB-Senegal germplasm has a broad genetic variation. Among the SSR markers, sMo00053 and sMg00133 were the most informative markers for discrimination among the MPOB-Senegal oil palm germplasm for having the highest private alleles and the rare alleles. For selection and conservation, oil palm populations with high rare alleles and Nei's gene diversity index should be considered as these populations may possess unique genes for further exploitation.Molecular characterization of oil palm germplasm is crucial in utilizing and conserving germplasm with promising traits. This study was conducted to evaluate the genetic diversity structures and relationships among 26 families of MPOB-Senegal oil palm germplasm using thirty-five microsatellite markers. High level of polymorphism ( The African oil palm (Elaeis guineensis) is the most productive among oil-bearing palms. It is endemic largely in West and Central Africa's tropical lowlands, occurring extensively from 16°N in Senegal to 15°S in Angola . The MalOver time, the oil palm germplasm collections were screened using various molecular markers to evaluate and investigate the genetic variability between and within the population. Hayati et al.  studied Molecular characterization of MPOB-Senegal oil palm germplasm is yet to be evaluated among and within the populations. Also, MPOB-Senegal germplasm populations are adapted to dry weather conditions from their original collection site, which implies that they may possess drought-tolerant characteristics. Therefore, for further exploitation and understanding of valuable genes, genetic diversity and population structures of Senegal germplasm collections should be evaluated using the simple sequence repeat (SSR) marker. Hence, this study was conducted to evaluate the genetic diversity and population structures of MPOB-Senegal oil palm germplasm using microsatellite markers.Germplasm collection was carried out between July and August 1993 with assistance from the Ministry of Agriculture, Senegal. A total of 104 bunch samples belonging to eight different populations distributed across the southern and northern parts of Senegal were collected  and planλ = 260.0 nm, 280.0 nm, and 350.0 nm using a spectrophotometer . All the samples were later diluted to 50 ng/μl and stored at 20°C for subsequent PCR amplification use.The molecular characterization was carried out on a total of twenty-six families from eight populations. Spear leaf (unopened leaves) samples were collected from each palm during the trial; the number of collected samples varied from 5 to 10 palms per family based on the availability of palms with a total sum of 222 palms obtained . The speμl, comprising 50 ng of genomic DNA, 6.625 μl of MilliQ water, 1× PCR standard buffer , 0.2 μl of 10 mM deoxynucleotide triphosphates (dNTPs) , 0.025 μl of each of the M13-tailed forward primers and untailed reverse primers for every primer pair, 0.025 μl dye, and 0.1 μl of Taq DNA polymerase (5 U/μl) . PCR was performed in a Perkin Elmer 9600 Thermocycler following an initial denaturation temperature at 95°C for 3 minutes, followed by 35 cycles at 95°C for 30 seconds, primer annealing for 30 sec, and an extension temperature of 72°C for 30 minutes, terminated by a final extension at 72°C for 2 min. The amplified PCR products were resolved using 1% agarose gel and run in a horizontal electrophoresis system to check the band sizes using a 100 bp ladder. The DNA fragment on agarose gel was documented using Gel Imager® . DNA concentration was measured by using a NanoDrop spectrophotometry machine (ND1000 Spectrophotometer USA). Four PCR products for different primers labeled with different fluorescent dyes were pooled and multiplexed with the new PCR plate. The pooled PCR products (2 μl) were combined with 7.84 μl of formamide  and 0.16 μl of the Gene Scan 500  LIZ size standard . The samples were inserted in a 96-well PCR microplate and heated for 3 minutes. The sample plate was kept at 4°C before automated capillary electrophoresis using an ABI 3730 DNA Genetic Analyzer.A total of 35 highly polymorphic and reproducible markers were selected for this study. The information of the 35 markers was presented in Supplementary Table Na), effective allele number (Ne), observed heterozygosity (Ho), expected heterozygosity (He), fixation indices (Fis), percentage of polymorphism (%P), and number of private alleles were calculated using GenAlex 6.5 software [SSR data were analyzed using Genemapper 4.1 software to identify the allele sizes of each marker. Electropherogram profiles (sample plots) were generated, and allele sizes for the markers were exported as data table for genotyping. Genetic diversity parameters such as allelic frequency, number of alleles per locus (software . POPGENENa) detected across 26 families ranged from 2.038 to 6.231, with an average of 3.869 different alleles. SMo00131 detected the highest number of different alleles, whereas marker sEg00189 recorded the least number of differences at 2.038 (Ne), estimated as the inverse of homozygosity, and the observed alleles. The number of effective alleles varied from 1.393 to 4.662, and sMo00131 was the most informative marker among the markers evaluated. Family SEN05.08 had the highest number of effective alleles (3.06) as shown in A total of 384 alleles were regenerated, the number of alleles per locus ranging from 4 to 21, with an average value of 10.971. Markers sMo00053 and sMg00133 detected the highest number of alleles (21), indicating that these markers are the most informative marker while sMg00027, sEg00189, and sEg00092 identified the least number of alleles, with each marker identifying 4, 5, and 6 alleles, respectively . The numat 2.038 . Among tat 2.038 . On the I) ranged from 0.401 (sEg00189) to 1.597 (sMo00131) with an average value of 1.024 (I) was recorded in family SEN05.05 (1.181) (Ho) of 0.584 (Ho) was recorded in locus sEg00009. The expected heterozygosity (He) among the 35 loci for 26 families varied from 0.236 in sEg00189 to 0.755 in sMo00131 while the average expected heterozygosity was 0.550.Diversity indices provide important information regarding the rarity and commonness of species in a community. Shannon's information index  . High heof 0.584 . Among tHo was observed in SEN12.03 while the highest was recorded in SEN06.08. The highest He was recorded in SEN05.05, and the lowest was observed in SEN02.04. The observed heterozygosity was high, indicating the occurrence of a wide genetic diversity among the families. The chi-square test was employed in the determination of the differences between the observed (Ho) and the expected (He) heterozygosity of 26 families of MPOB-Senegal oil palm germplasm (HT) for the 26 families was 0.666, suggesting a high value of genetic diversity among the families. The highest total genetic diversity (HT) was observed in primers sMo00131 and mEgCIR0369 with values of 0.859 and 0.855, respectively  across the families observed in SEN 02.09, SEN03.07, SEN05.04, SEN05.05, SEN05.08, SEN06.08, SEN07.03, SEN10.05, and SEN12.03. The lowest polymorphism level was recorded in SEN02.04 and SEN10.03 with 85.71% and 88.57% polymorphism. These results showed that most families from the southern part have higher genetic diversity than the northern part of Senegal .Fis) per locus varied from -0.438 (sEg00061) to 0.510 (sMg00234) with a negative mean of – 0.050. These negative Fis indicate an excess of heterozygosity as observed in 23 loci. However, positive Fis values were observed in 12 loci which indicate less heterozygosity. Furthermore, the Fit  values ranged from -0.325 (sEg00061) to 0.618 (sMg00234) with an average value of 0.127. Positive Fit values were recorded in most of the loci except for 6 loci . The genetic differentiation (Fst) varied from 0.091 (sEg00092) to 0.363 (sEg00126) with a mean value of 0.174. This result indicates that the genetic material can be shared among the families (Nm ranged from 0.438 (sEg00126) to 2.916 (sEg0006) with a mean value of 1.338, and this can be considered as high according to Bakoumé et al. [Nm value > 1 as high. Nm decreases with increasing Fst because greater differentiation between populations corresponds to lower levels of gene flow, thus, indicating that Nm is inversely related to Fst. Marker sEg00126 detected the lowest Nm, while also recording the highest Fst. On the other hand, sEg0066 detected the highest Nm while low Fst was recorded by the marker , effective allele (Ne = 1.39), number of observed alleles (Ho = 0.224), and number of expected alleles (He = 0.232). In addition, population 12 also showed high Na 1.57, Ne 1.28, Ho 0.171, and He 0.171. Moreover, Maizura et al. [Na) was 1.7 and expected heterozygosity (He) was 0.214 in the genetic diversity study of 11 African oil palm germplasms using RFLP. In the current study, these genetic variability results increased to the number of alleles per locus (Na = 3.869), expected heterozygosity (He = 0.550). These genetic diversity measures increased with an increase in the number of samples covering all Senegal oil palm populations. The molecular technique used also influences the result of a genetic diversity study. Thus, these results agree with Ting et al. [Na and Ne's results were affected by the number of markers and sample size assay.The comparisons of results of the percentage of polymorphic loci have also been recorded among studies where microsatellites were used. A higher result was reported in the current study than Singh et al. , and Tina et al.  reportedg et al. , who claNa = 3.869), effective alleles per locus (Ne = 2.653), observed heterozygosity (Ho = 0.584), and expected heterozygosity (0.550) were higher in this study compared to the previous study by Singh et al. [Ho) of 0.434 and expected heterozygosity (He) of 0.436 in Senegal germplasm. Meanwhile, the heterozygosity results of Madagascar, Gambia, Ghana, Congo, Cameroon, and Nigeria germplasm from the studies of Singh et al. [Ho), and 0.496 in expected heterozygosity (He) of Senegal germplasm. This was lower than the values recorded in MPOB-Senegal germplasm in the current study, where the mean number of alleles per locus (Na) = 3.869, the effective alleles per locus (Ne) = 2.653, the observed heterozygosity (Ho) = 0.584, and expected heterozygosity (He) = 0.550. This result was equivalent to the results obtained in Cameroon, Congo, and Ghana where the mean value of Na was 3.8 and was comparable with Madagascar (Na = 3.7), Angola (Na = 3.5), and Gambia (Na = 2.7). Likewise, the mean heterozygosity of the current study on MPOB-Senegal oil palm germplasm (Ho = 0.584 and He = 0.550) was greater than the values (Ho = 0.387 and He = 0.495) recorded in Senegal germplasm by Zulkifli et al. [Na = 4.014, Ne = 2.821). However, the observed heterozygosity (Ho = 0.542) was lower compared to the current study. In this research, the observed heterozygosity (Ho) values for all the 35 evaluated markers were higher than the expected heterozygosity (He). This result corroborates the result of Bodia et al. [Ho's value was higher than He.The observed number of alleles per locus  by Arias et al. [I) recorded in the current study was higher (1.024) than that reported by Zhou et al. [I of 0.6565 using a microsatellite marker to assess genetic diversity among the oil palm materials collected from Malaysia and China. The result was also comparable with Bharath et al. [Ne, He, and %P in understanding populations' genetic diversity. Among the 26 families, SEN05.05 showed the highest I value (1.181) as well as the highest Ne (3.036), He (0.621), and P (100%). On the other hand, SEN02.04 had the lowest I value and 12 families had Shannon's information index value lower than the trial mean. This Shannon's information index parameter could be used as an initial criterion to narrow down the number of accessions for evaluation [Ne, He, and %P information for use in establishing core germplasm.Senegal is located in the extreme part of West Africa . The hets et al.  in Cameru et al. , who obsh et al.  who recoh et al.  in five aluation  and coulFis, Fit, and Fst were estimated to measure the excess or deficit of heterozygosity in the entire families. The total genetic diversity (Fst) among the 26 families was 0.174, and this was considered high according to Wright [Fis showed an excess of heterozygosity at 23 loci with a mean value of -0.050. The average gene flow (Nm = 1.338) in this study is considered high, as Slatkin reported [The fixation indices o Wright . Negativreported . These hreported , 31.Moges et al.  reportedAccording to Zeng et al.  and UpadFst) among the 26 families was 0.174 and can be considered as high according to Wright [Fis. Based on segregating genetic diversity, a considerable genetic diversity within the families would be applied in the oil palm improvement program.The analysis of molecular variance (AMOVA) shows that genetic variations were greater within the families. The total genetic diversity  was recorded between SEN02.04 and SEN02.06; this is because the two families belong to the same population, namely, population 2. Generally, there is a strong relationship between genetic distance and geographical locations , 13. TheThe UPGMA dendrogram was constructed that showed the genetic similarity and dissimilarity among the families. Among the total 8 populations, populations 2, 3, 4, 5, 6, 7, and 10 were situated in the southern part of Senegal whereas population 12 was located in the northern part, separated by Gambia. The populations in the southern part were within an 80 km radius. Populations 2 and 3 were collected around 45 km from Ziguinchor while population 5 was collected around 17 km from Ziguinchor whereas population 4 was from Dar Salam. Among the three main clusters as revealed by the dendrogram, families from the same population were not assembled in the same cluster; however, a grouping of families from different populations was formed. The families of populations 2 and 3 were grouped in cluster I. Additionally, families SEN04.01 and SEN05.02 were contained in cluster I while the rest of the families from populations 4 and 5 were grouped with families of populations 6 and 7 in cluster II. This is due to the limited geographical distance in the collection sites of populations 2, 3, 4, 5, 6, 7, and 10 (not more than 80 km).Nm = 1.338). This result is similar to that reported by Arias et al. [Nm). These results indicated a weak genetic differentiation among the families, and this is consistent with the AMOVA result which shows lesser genetic variation among the families than among the individuals. Based on the results of the cluster, distributions of different families are a mixed type. This is in agreement with Oladosu et al. [On the other hand, two families of population 10 and family SEN07.08 were grouped with three northern outlying families from population 12 to form cluster III, which may be due to the genetic similarity among the families and the high number of migrants (s et al.  who descu et al.  and Oladu et al.  and Ariau et al.  in theiru et al. , Zulkiflu et al. , and BakThe simple sequence repeat markers are useful in detecting the genetic variability and relationship among MPOB-Senegal oil palm germplasm. It shows a high degree of sensitivity for discriminating genetic variability, thereby providing ample opportunity for further genetic improvement. This will assist oil palm breeders in identifying redundancies in the collection and development strategies for field conservation. The presence of relatively high different allele, effective alleles, and heterozygosity indicates that MPOB-Senegal germplasm possesses unique traits which could be used in the future breeding program. Among the SSR markers employed, sMo00053 and sMg00133 were the most informative markers for MPOB-Senegal oil palm germplasm due to their capability to detect both the highest private alleles and the rare alleles. SEN07.05 and SEN12.03 were unique families due to the highest occurrence of rare alleles. Also, SEN05.03 and SEN12.03 families had the highest private alleles. The information obtained from this study could be vital in core collection establishment without any loss of genetic variations.


Pylodictis olivaris). We describe a suite of microsatellite loci that can be used to characterize population structure, predict invasion history, and assess potential mitigation strategies for flathead catfish.Flathead catfish are rapidly expanding into nonnative waterways throughout the United States. Once established, flathead catfish may cause disruptions to the local ecosystem through consumption and competition with native fishes, including species of conservation concern. Flathead catfish often become a popular sport fish in their introduced range, and so management strategies must frequently balance the need to protect native and naturalized fauna while meeting the desire to maintain or enhance fisheries. However, there are currently few tools available to inform management of invasive flathead catfish (Our panel of 13 microsatellite loci were polymorphic and appear to be informative for population genetic studies of flathead catfish. We found moderate levels of diversity in four nonnative collections of flathead catfish in the Pennsylvania and Maryland sections of the Susquehanna River and the Schuylkill River, Pennsylvania. Analyses suggested patterns of genetic differentiation within- and among-rivers, highlighting the utility of this marker panel for understanding the structure and assessing the degree of connectivity among flathead catfish populations. Pylodictis olivaris) is a large piscivorous catfish native to the Mississippi, Mobile, and Rio Grande basins in the United States that has experienced rapid range expansions following permitted and non-permitted stocking [Flathead catfish , eradication of nonnative flathead catfish may not be feasible or warranted for many populations . There aHere, we describe a panel of microsatellite loci that can be used to support management of flathead catfish populations through studies of population genetics. We highlight the utility of this marker panel in a population genetic analysis of flathead catfish collected from two river basins (Delaware and Susquehanna rivers) within its introduced range in Pennsylvania and Maryland.2 sample of the caudal fin was collected from each individual, preserved in 95% ethanol, and provided to the U.S. Geological Survey (USGS) Eastern Ecological Science Center, Kearneysville, WV. All fish sampling and tissue collections were conducted in agreement with the Pennsylvania State University Institutional Animal Care and Use Committee (PROTO201901210).Flathead catfish were collected from one location in the Schuylkill River in the Delaware River Basin in eastern Pennsylvania and three locations distributed along the Susquehanna River in central Pennsylvania and Maryland Fig. a. Fish wIctalurus punctatus [Microsatellite marker panels have not been previously described for flathead catfish; however, studies have suggested that microsatellites are well-conserved among ictalurid catfishes . Therefounctatus –14). Theunctatus . Flatheaunctatus  to the 5unctatus .Of the 25 candidate loci, six loci failed to amplify under varying conditions, including subjection to the 50 °C to 64 °C gradient program on a Bio-Rad T100 thermal cycler. Another six loci proved to be monomorphic in the individuals analyzed. The remaining 13 loci that successfully amplified were ultimately chosen for our final panel based on clean amplification, free of artifacts and any co-amplification, number of alleles observed, and annealing temperature compatibility  in 96-well semi-skirted plates. Each reaction was 15 µl in total volume and contained 1.5 µl genomic DNA (~ 25 ng/µl), 4.6 µl of nuclease-free water, 7.5 µl Qiagen Multiplex 1X MasterMix, 0.2–0.5 µl of each primer , observed (HO) and unbiased expected (uHE) heterozygosity, the number of private alleles (P), and the fixation index (F) and the program HP-Rare [rAR; standardized to 40 alleles) for each collection. We also used GenAlEx to perform an analysis of molecular variance (AMOVA) to understand the spatial scale of genetic variation within and between river basins.We used R package GENEPOP  to perfo HP-Rare  to estimK = 1 to 5 genetic clusters using the admixture model with no a priori information on sample location. Each STRUCTURE run had 200,000 iterations as burn-in, followed by 100,000 replicates of data collection. Results from STRUCTURE were visualized using STRUCTURESelector [K value using the ΔK method [K that showed biologically relevant patterns in genetic structure. We also completed a principal coordinate analysis (PCoA) in GenAlEx to further visualize genetic variation within and among collections.To evaluate the extent of genetic differentiation among collections, we calculated pairwise  v 2.3.4  to identSelector . We seleK method  but alsoIpCG00189 and Ip271). All 13 loci were polymorphic across the four collections (AR per locus range = 2 to 6) and heterozygosity and allelic richness were moderate in each collection (Table n = 17) relative to those observed in the upper Susquehanna (n = 2) collection.Across all four collections of flathead catfish, we found few deviations from HWE or LD, no scoring errors, and no evidence of large allele dropout. However, there was possible evidence of null alleles at two loci (P < 0.001), with the largest values observed between the collection site on the Schuylkill and all the sites on the Susquehanna River  through downstream migration and continued upstream invasion.While additional study is warranted, this analysis adds to the discussion of the invasion history of flathead catfish in Pennsylvania , 27, andWe surveyed four collections in our analysis, each of which is thought to have been established for less than three decades. Genotyping additional collections, including collections within the species’ native range and those with longer residence times will help better characterize allelic patterns at each locus and enable more robust conclusions about the origin of nonnative populations. Further investigation will also help resolve whether the null alleles identified in this study are an artifact of small sample sizes and/or nonrandom sampling.


Haïti is at risk for wild poliovirus (WPV) importation and circulation, as well as vaccine-derived poliovirus (VDPV) emergence. Environmental surveillance (ES) for polioviruses was established in Port au Prince and Gonaïves in 2016. During 2017–2019, initial ES sites were re-evaluated, and ES was expanded into Cap Haïtien and Saint Marc. Wastewater samples and data on weather, hour of collection, and sample temperature and pH were collected every 4 weeks during March 2017–December 2019 (272 sampling events) from 21 sites in Cap Haïtien, Gonaïves, Port au Prince, and Saint Marc. Samples were processed for the detection of polio and non-polio enteroviruses using the two-phase and “Concentration and Filter Elution” methodologies. Polioviruses were serotyped and underwent intra-typic characterization. No WPV or VDPVs were isolated. Sabin-like polioviruses  of serotypes 1 and 3 were sporadically detected. Five of six (83%), one of six (17%), five of six (83%), and two of three (67%) sites evaluated in Cap Haïtien, Gonaïves, Port au Prince, and Saint Marc, respectively, had enterovirus isolation from >50% of sampling events; these results and considerations, such as watershed population size and overlap, influence of sea water, and excessive particulates in samples, were factors in site retention or termination. The evaluation of 21 ES sampling sites in four Haïtian cities led to the termination of 11 sites. Every-four-weekly sampling continues at the remaining 10 sites across the four cities as a core Global Polio Eradication Initiative activity. In 1988, the World Health Assembly passed a resolution to eradicate poliomyelitis  infection), a viral disease with an oral–fecal route of transmission ,3,4. SurThe ongoing efforts to characterize ES sampling sites, to optimize sensitivity for detecting poliovirus transmission, are critical, especially in the late stages of eradication ,8,15,17.In 2014, the Pan American Health Organization (PAHO) began to consider implementing ES in selected settings in the Americas to rapidly detect WPV circulation in the event of the importation and the emergence of VDPVs . Haïti wA review of Haïti’s estimated annual national-level Pol3 coverage was conducted with data available from 1980–2019 . Th. Th17]. A total of ten sites in the four cities were retained . The majThis report describes the dynamic process of establishing and monitoring ES sites for polioviruses. The analyses of data from many months of sample collection are often necessary to make evidence-based judgements of site performance and to inform decisions for terminating or retaining sites and exploring new ones ,17. The


Dugong dugon) populations have been shrinking globally, due in large part to habitat fragmentation, degradation and ocean pollution, and today are listed as Vulnerable by the IUCN. Thus, determining genetic diversity in the remaining populations is essential for conservation planning and protection. In this study, measures of inter-simple sequence repeat (ISSR) markers and mtDNA D-loop typing were used to evaluate the genetic diversity of 118 dugongs from skin samples of deceased dugongs collected in Thai waters over a 29-year period. Thirteen ISSR primers revealed that dugongs from the Andaman Sea and Gulf of Thailand exhibited more genetic variation in the first 12 years of the study (1990–2002) compared to the last decade (2009–2019). Dugongs from the Andaman Sea, Trang, Satun and some areas of Krabi province exhibited greater diversity compared to other coastal regions of Thailand. Eleven haplotypes were identified, and when compared to other parts of the world (235 sequences obtained from NCBI), five clades were apparent from a total 353 sequences. Moreover, dugongs from the Andaman Sea were genetically distinct, with a separate haplotype belonging to two clades found only in Thai waters that separated from other groups around 1.2 million years ago. Genetic diversity of dugongs in present times was less than that of past decades, likely due to increased population fragmentation. Because dugongs are difficult to keep and breed in captivity, improved in situ conservation actions are needed to sustain genetically healthy wild populations, and in particular, the specific genetic group found only in the Andaman Sea.Dugong ( Dugong dugon) is one of four species belonging to the order Sirenia, Family Dugongidae. It is distinct compared to other marine mammals in being entirely herbivorous, and as such plays an important role in maintaining coastal ecosystems. Dugongs are critically endangered, the IUCN has listed dugongs as vulnerable to extinction on a global scale because numbers have declined by at least 20% over the last 90 years1, and will be endangered unless circumstances threatening their survival are alleviated and reproduction is improved3. In addition, it is listed in Appendix I of the Convention on International Trade in Endangered Species4. Dugong populations have declined drastically since the 1960s throughout much of their natural range. For example, in Australia, the estimated rate of decline averaged about 8.7% per year between 1962 and 1999, resulting in a 97% reduction in initial catch rates over a 38-year period1. The largest populations today are found along the coasts of Australia 5, followed by the Arabian/Persian Gulf (6000)7, Red Sea (2000)8, New Caledonia (898)9, and Mozambique (300)8. Dugongs have completely disappeared from areas in Japan (Sakishima Shoto islands), Hong Kong, Maldives, Mauritius, Philippines, Taiwan, Cambodia, and Vietnam1.The dugong  and Andaman Sea . The estimated number of dugongs in Thailand was less than 200 in 2017, with the majority (150–170) living in the Hat Chao Mai National Marine Park and Mu Ko Libong, both non-hunting areas in Trang province where seagrass is still intact11. In Thailand, 24 strandings were reported between October 1, 2018–September 30, 2019, most of which (56%) were due to human activities, including entanglement in fishing equipment and boat strikes12. A previous study over a 33-year period (1962–2008) recorded a total of 282 dugong strandings in Thailand13. For most of those, cause of death was unknown, but others were due to gillnets, stationary traps, fishing gear, boat strikes, or shark attacks. Increased long-term population monitoring and mitigating actions to protect animals and seagrass habitats are needed to conserve global dugong populations.In Thailand, dugongs are categorized as a rare marine mammal by the Wild Animal Reservation and Protection Act, B.E.255314. In a previous study, Plon et al.3 found a 355 bp sequence in the mtDNA that matched dugongs from Australia and Indonesia, but revealed several new and divergent mtDNA lineages in the Indian Ocean. Using nuclear DNA (nDNA) microsatellite markers, a study of dugongs in Australia found that the genetic diversity was low. A significant population structure was detected and mean pairwise relatedness values within populations were low as well14. Gene diversity and population structure in dugongs in Thailand have been assessed by analyses of D-loop mitochondrial DNA region sequences, cytochrome c oxidase subunit I (COI), and autosomal microsatellites15. Low genetic distance was observed between dugong populations in the Andaman Sea and Gulf of Thailand, which suggests that gene flow between populations might be occurring11. Moreover, the three mtDNA haplogroups discovered in dugongs of Thai waters were not differentiated by region. Microsatellite analyses provided a signal of dispersal between the Andaman Sea and Gulf of Thailand indicating genetic variation has remained higher than expected given the declining numbers of dugongs in each region15.Population substructure has important implications for a species’ ecology and evolution. As such, knowledge of structuring is critical for the conservation and management of natural populations. In the past decades, researchers have studied genetic diversity of Sirenia in several habitats, for instance, Australia and the Indian Ocean using mitochondrial DNA (mtDNA) amplification of overlapping fragments of the D-loop region®. The results of this study provide important information on genetic diversity and phylogeographphic structuring of dugongs in Thailand and for understanding the distribution of populations according to world geography.A major limitation to genetic studies of dugongs has been low sample numbers. This study took advantage of 29 years’ worth of banked skin samples from stranded dugongs off both coasts of Thailand to assess genetic diversity over time and between those two regions. We also determined how diversity and phylogeographphic structuring compares between dugongs in Thai waters to those globally based on sequences available in the National Center for Biotechnology Information (NCBI) GenbankThe Phuket Marine Biological Center, Phuket, Thailand provided skin samples from 118 deceased dugongs  that were stranded between 1990–2019 Fig. . The sam16.Skin samples were extracted using DNA extraction kits according to manufacturer’s instructions  at the Faculty of Veterinary Medicine, Chiang Mai University, and the DNA measured qualitatively and quantitatively by agarose gel electrophoresis and spectrophotometry, respectively2)4SO4, 50 mM Tris–HCl, 1.75 mM MgCl2, and 0.01% TritonTM X-100), 5 µm dNTP , 0.2 µM ISSR primer, 1U Taq DNA polymerase , and 20 ng DNA template with deionized water added to a volume of 25 µm. For every PCR reaction, deionized water was use instead of the DNA template to serve as a negative control. PCR amplifications were performed in PTC-200 at DNA EngineThermal Cycler  under the following conditions: pre-denaturation at 95 °C for 5 min, followed by 37 cycles consisting of a denaturation step at 95 °C for 30 s, an annealing step at 58 °C for 45 s, and an extension step at 72 °C for 1 min with a final extension step at 72 °C for 10 min. The PCR products were stained by REDSAFE Nucleic acid staining solution  and then separated electrophoretically on 2% agarose gel  by POWERPAC 200  containing 1× Tris–acetate-ethylenediaminetetraacetate (TAE) buffer at 120 V for 30 min. The PCR products were then visualized by UV light under a GELMAX 125Imager .Thirty-four ISSR primers of the microsatellite UBC primer set obtained from the University of British Columbia, Vancouver, Canada were screened twice using a polymerase chain reaction (PCR) technique resulting in the selection of 13 primers that produced reproducible and unambiguous bands (Table 17. PCR reactions were conducted in 25 μl reaction volumes using Platinum Taq DNA polymerase (Invitrogen) and 10 × reaction buffer. Reactions generally contained 2 mM MgCl2, 0.4 mg/ml bovine serum albumin, 0.25 mM dNTPs, 0.4 μM forward and reverse primers, and 2 μl of DNA template. The PCR conditions were as follows: 95 °C for 5 min, 40 cycles of , and 72 °C for 10 min. Sanger direct sequencing was performed by Ward Medic Ltd. Bangkok, Thailand. Sequences were edited and aligned manually using the program MEGA-X version 10.1.818 .One pair of PCR primers, DugDLF (5′-CAT ATT ACA ACG GTC TTG TAA ACC-′’) and DugDLR (5′-GTC ATA AGT CCA TCG AGA TGT C-3′) that contained 615 bp long regions of mtDNA d-loop (dugong) were used for amplification20.Only clearly observed and unambiguous fragments were scored in a binary manner for band presence (1) or absence (0), and a binary matrix was generated to determine the level of polymorphism for each primer represented by the percentage of polymorphic bands22; and five location zones  and present 25. The sequences were arranged into global dugong distributions representing the Pacific, Southeast Asia, South Asia and Southwest Indian Ocean regions  obtained from samples collected from the Andaman Sea (n = 110) and Gulf of Thailand (n = 8). The global dugong alignment of 353 sequences (207 bp) included these Thai sequences and additional ones downloaded from GenBank (n = 235)(i)26 to identify the population clusters within both the global and Thai dugong alignment datasets.Genetic structure was estimated using MRBAYES program version 3.2.7a(ii)27 to assess the genetic lineage within the global dugong alignment as well as for the Thai dugong dataset. Haplotype network calculations were carried out for both analyses by assigning equal weights to all the variable sites.Median joining haplotype network was constructed using program POPART version 1.7(iii)28 implemented in program JMODELTEST29. The best-fit substitution model was found to be HKY + I. Phylogenetic analysis implemented in MRBAYES program version 3.2.7a26 was conducted using a Bayesian inference approach30. The chain length consisted of 2 million generations of Markov Chain Monte Carlo (MCMC) simulations with average standard deviation of split frequencies at 0.007437 (< 0.01), sampled every 5000 generations, with the first 50,000 runs discarded as burn-ins. Steller’s sea cow was kept as an outgroup in the phylogenetic analysis. Finally, INTERACTIVE TREE OF LIFE (ITOL) online program (https://itol.embl.de) was used to view and annotate the consensus phylogenetic tree. A posterior probability value ≥ 0.05 was considered a strong relationship31.Phylogenetic relationships were assessed for both Thai and global dugong alignments. The best fit nucleotide substitution and partition schemes for the DNA dataset were selected using Bayesian Information Criterion; BIC for Thai dugong populationThe genetic structures within Thai dugong populations and genetic clades of global dugong populations were determined using three approaches:32 implemented in program JMODELTEST29. The best-fit substitution model was found to be TrN + G. Phylogenetic analysis implemented in program MRBAYES version 3.2.7a26 was conducted using a Baysian inference approach. The chain length consisted of 21 million generations of MCMC (Markov Chain Monte Carlo) simulation with an average standard deviation of split frequencies at 0.009924 (< 0.01), sampled every 5000 generations, with the first 50,000 runs discarded as burn-ins. Steller’s sea cow was kept as an outgroup in the phylogenetic analysis.For the global dugongs, the procedure was the same. The best fit nucleotide substitution and partition schemes for the DNA D-loop dataset of global dugongs were selected using the Akaike Information Criterion: AIC33, where the changes in effective population size (Ne) over time were tested. This enabled past demographic changes of dugongs in Thailand to be inferred from the current patterns of genetic diversity within a population34. The number of samples from the Gulf of Thailand was small (n = 8), so only samples from the Andaman Sea (n = 110) were analyzed. Those sequences were used for analyses at a mutation rate of 2 × 10–8 bp−1 year−135. The input was prepared in BEAUti. The analysis was run for 108 iterations with a burn-in of 107 with sampling every 104 and a strict molecular clock. All operators were automatically optimized and the results were generated using TRACER version 1.7.136. A maximum clade credibility tree was constructed from the resulting Bayesian trees using TREEANNOTATOR version 2.4.4 and FIGTREE version 1.4.33. The same analysis parameters were used in an Extended Bayesian Skyline Plot analyses37 to estimate changes in population size over time for each of the major mtDNA clades. A 95% HPD (highest posterior density) distribution of the inferred number of population changes was used. Six mammalian species were used to compare data results, including rock hyrax (Procavia capensis), African elephant (Loxodonta africana), Asian elephant (Elephas maximus), West Indian manatee (Trichechus manatus), African manatee , and Steller’s sea cow.To reconstruct the demographic history of Thai dugongs, we ran a coalescent Bayesian skyline analysis in BEAST version 2.2.0Based on 13 ISSR primers, dugongs from the Andaman Sea and the Gulf of Thailand had similar percent polymorphic bands at 63.79% and 62.43%, respectively  indicated higher genetic variation in the present (2009–2019) compared to the past (1990–2002) periods for dugongs in both the Andaman Sea and Gulf of Thailand  was the lowest compared to all other zones, with that in Zone 5 being the highest  and the highest was between past and present periods in the Gulf of Thailand (0.940) Table . The paiThe pairwise Nei’s genetic distance analysis showed the lowest distance between Zones 4 and 5 in the Andaman Sea 0.146) and the highest between Zones 1 and 2 in the Gulf of Thailand (1.151)  were identified and shown in Supplementary Fig. 38, which indicated that 2 bp from 100 bp mutate every 1 million years. Additionally, the result revealed that the effective population size of dugongs was stable from 300,000 to about 25,000 years ago, after which it has gradually decreased.Due to the low number of samples from the Gulf of Thailand, BSP could not be calculated. Moreover, all samples from the three zones in the Andaman Sea were merged for calculating BSP from D-loop markers Fig. . The calA total of 353 sequences are shown in the phylogenetic dendrogram Fig. . Five clA total of 61 haplotypes were generated from Median joining network Figs. . Hap 9, The mtDNA control region sequences of dugongs in this study revealed that the population divided into two groups approximately 1.9 million years ago. The first group consisted of dugongs classified in clades D1, D2.1 and D2.2. Clade D1 separated from the group 1.5 million years ago, while clades D2.1 and D2.2 separated from the group about 1.0 million years ago. In the second group, dugongs were classified in clades A, B and C. Clade C emerged 1.5 million years ago followed about 0.3 million years later by separation into clades A and B Fig. .Figure 8It is well-known that dugongs are threatened with extinction throughout their habitat ranges, due primarily to human disturbances. Creating insurance populations of dugongs in captivity has not been successful, so it is important to understand genetic structure and diversity of wild dugong populations to evaluate the status of this species and how it varies across regions and time. Results of this study support our hypothesis that genetic diversity of dugongs in the coastal areas of Thailand has decreased over time although we recognize this is based on relatively small sample sizes, so more work is needed. Moreover, from our phylogeographic analysis, 28 of 118 dugongs were in a clade that diverged over a million years ago and found only in Thailand, and as such may need special conservation protection.40. The last survey of the Andaman Sea and the Gulf of Thailand was in 2017 and identified 221 individuals11. However, these numbers were only approximates. Analysis of genetic diversity can be a more powerful tool to evaluate the genetic structure of dugong populations that does not rely on knowing exact numbers of animals in an area. Our data found that genetic variation was higher in the past (1990–2002) compared to present (2009–2019) time periods in both seas. Reductions in population size and absence of gene flow can lead to reductions in genetic diversity, reproductive fitness, and a limited ability to adapt to environmental change, thus increasing the risk of extinction41. Likewise, from a previous review by Willoughby et al.42, reductions in heterozygosity and allelic richness based on microsatellite marker analyses have been observed in threatened species, suggesting that inbreeding and genetic drift are both effective at removing genetic diversity in endangered populations. Therefore, the decrease in genetic diversity of dugongs in Thailand over the past decades may reflect some inbreeding in the population that could ultimately impact fitness and survival.Aerial surveys are the most popular technique used to determine dugong numbers45. Much of the degradation of seagrass beds is human-caused by coastal construction, pollution and illegal fishing46, but they have also been affected by seasonal changes in monsoons in some areas47. The genetic similarity of dugongs in the Andaman Sea, which has a long coastline, may mean there is more gene flow than those in more restricted areas. There does not appear to be a high level of inbreeding based on a negative fixation (Fst) value indicating more heterozygosity in this population. While the mating system of dugongs is poorly understood, it has been suggested that decreasing numbers may be impacting mating choices, leading to possible inbreeding in the future48.Degradation of seagrass habitat is a concern for the sustainability of dugong populations. Seagrass areas in Thailand cover 255 square kilometers, distributed along the Andaman Sea and the Gulf of Thailand in 13 provinces, with 13 species of seagrasses identified as important food sources for endangered marine mammals such as dugongs11. It is estimated that there are fewer dugongs living in the Gulf of Thailand (estimated number = 30) than in the Andaman Sea (estimated number = 191) in 201749. Furthermore, records of 282 strandings from 1962 to February 2008 found 71.6% were from the Andaman Sea, 25.8% were from the Gulf; 2.6% had no information on the stranding place13. Genetic diversity reflects the total number of genetic characteristics and is related to the number of genes and their alleles within individuals and can influence adaptability and distribution of a species in diverse habitats. Nevertheless, the results of this study found good genetic variability within and between Thai waters. The results showed that the expected and observed heterozygosity (He and Ho) were high, which might suggest dugongs were moving between habitats50. The percentage of polymorphic bands indicated a high level of variability in female dugongs at 60.94% and 51.10% from the Andaman Sea and Gulf of Thailand, respectively, with lower values of 47.41% and 46.56% for males, similar to a previous genetic study using microsatellite markers15. The Shannon’s information index values (I) were higher in dugongs in the Andaman Sea  compared to those in the Gulf of Thailand . In addition, the genetic variability of dugongs from samples collected between 1990 and 2019 was higher than that of other species, such as Asian elephant (2.45 ± 0.05)51, domestic dog (2.59 ± 0.034)20, Holstein cattle (0.23 ± 0.23)52, sheep (0.31 ± 0.30)52, buffaloes (0.28 ± 0.11)53, and goat (0.39 ± 0.30)54 that ranged from 0.18 to 2.5954. The highest I index was observed in Zone 5 (2.608), which represents the highest dugong population. Dugongs in Zone 1 (1.547) in the Gulf of Thailand had the lowest I index, although dugong habitat and traveling distance are considered important factors for genetic variability as they inhabit a broad but fragmented range55. Although they are not considered migratory, they are known to travel great distances from one coastal area to another, and evidence from a previous study  showed there was some migration around the Malaysian peninsula from the Andaman Sea to the Gulf of Thailand15. Thus, there may be a chance that dugongs from both seas can intermingle across zones, which would increase the genetic diversity of Thailand’s dugong populations. Moreover, the dugong’s generation time is around 27 years and violates assumptions of non-overlapping generations due to life span; that and their random mating behavior could also aid in maintaining high genetic variability and decrease the potential for inbreeding in small populations like the dugong56.Dugongs living in the Andaman Sea had higher genetic diversity than those in the Gulf of Thailand. The population in Zone 5 (Trang and Satun area) had the highest genetic diversity, which might be because these two habitats have a larger number of dugongs in the population57. Nei’s genetic distance was lowest in the Andaman Sea from past to present, and between zones potentially because of a limited ability to find mates when populations are small and spread out. In the future, dugongs in the Gulf of Thailand might have an inbreeding problem more than other populations because of low population numbers15.Fixation index (Fst) values in this study also were negative, which might indicate little genetic subdivision between populations; that is, there is only one species present in this population. Evolutionary forces can influence genetic differentiation—the accumulation of differences in allelic frequencies between completely or partially isolated populations, and so it is important to understand selection or genetic drift in endangered species58. In addition, mineral elements in dugong teeth were significantly different between dugongs in the two habitats59. Thus our data supports the idea of regional biological distinctions, with haplotype differences between dugongs in the Andaman Sea  and Gulf of Thailand (Hap G and J).The finding of some regional genetic differences agrees with data on other biological parameters. In 2017, Nganvongpanit and colleagues found skull morphometric analyses were 100% accurate in identifying dugongs in the Andaman Sea versus the Gulf of Thailand, and that dugongs living in the Andaman Sea were larger, based on skull size, than those in the Gulf of Thailand3. By comparison, the Thai population separated from other groups around 1.2 million years ago. The reason for the separation might be because of geographical factors. The dugong is a marine mammal that lives in shallow waters, near the coast, and relies on seagrass for food48. It also has to come up to the surface to breathe every 1–2 min35. Dugong can travel as much as 100 km/day or more8, but movement is limited and restricted to areas with seagrass. For example, in adjacent waters, dugongs are found in the Bay of Bengal, but not the Gulf of Mataban, the latter of which has no seagrass distribution60. On the southern side to Malaysia is the Strait of Malacca where dugongs have not been reported. Although there is still some distribution of seagrass, it is considerably less than on the eastern side of Malaysia61. The Strait of Malacca is an important passageway between China and India and used heavily for commercial trade. It is narrow, contains thousands of islets, and is an outlet for many rivers. This region has been mentioned in ancient Chinese texts, as far back as the fourteenth century62. So, the dugong population has been restricted to the Andaman Sea of Thailand for a long time, with a limited ability to migrate. Therefore, it is a population group that has evolved with specific genetic characteristics.Of great interest was the finding that the clade A group had characteristics found only in the Andaman Sea and restricted to Thailand, with decreasing numbers found among Zones 3, 4 and 5. Dugongs diverged 1.9 million years ago, similar to a previous study that also found the separation started about 2.0 million years ago3. But in this study, we found two clades in Southeast Asia and five clades in the western Indian Ocean, which might be due to differences in the number of sequences used and the length of those sequences. The previous study3 reported more variation among dugongs in the Southeast Asia region due to the longer sequence length used in the statistical analysis (355 bp), while our study used shorter sequences (207 bp). In another study, it was shown that longer sequences of D-loop mtDNA resulted in a higher genetic pattern63. Our study reported the highest genetic variation and the highest number of haplotypes were found in dugongs living in the Indian Ocean. This might because we had a higher number of sequences used for the calculation.A previous study reported that Southeast Asia and Indian Ocean regions each consisted of three dugong lineages65.This study provides the most thorough description of genetic groups of the dugong at a global scale to date and an in-depth investigation of genetic diversity and structure of Thai dugong populations, and shows the distribution of clades based on world geography. In general, genetic diversity in this study (using ISSR markers) was higher compared to studies using other dominant markers such as Random Amplified Polymorphic DNA (RAPD) marker or Amplified Fragment Length Polymorphism (AFLP) makerThis study filled in missing information on phylogeography of dugongs in the Asian region, including Thailand, Philippine, Palau and Japan. There also were new discoveries, including that only two genetic populations of dugongs exist in Thailand. Additionally, one of them has a specific haplotype restricted to Thailand. Because captive breeding has not been successful for increasing dugong populations, additional guidelines and laws are needed to conserve these rare populations of dugongs and stem the continued declines in both the Andaman Sea and Gulf of Thailand.Supplementary Figure S1.Supplementary Figure S2.Supplementary Figure S3.Supplementary Table S1.Supplementary Table S2.