The landraces originated from 5° to 62.5° N and 16° to 71° E. The whole collection was genotyped using 42 SSR markers to assess the genetic diversity and population structure. With an average allelic richness of 5.74 and 372 alleles, Lrc1485 harbours considerably more genetic diversity than the most polymorphic current GWAS panel for barley. Ten major clusters defined most of the population structure based on geographical origin, row type of the ear and caryopsis type – and were assigned to specific climate zones. The legacy core reference set Lrc648 established in this study will provide a long-lasting resource and a very valuable tool for the scientific community. Lrc648 is best suited for multi-environmental field testing to identify candidate genes underlying quantitative traits but also for allele mining approaches.Global environmental change and increasing human population emphasize the urgent need for higher yielding and better adapted crop plants. One strategy to achieve this aim is to exploit the wealth of so called landraces of crop species, representing diverse traditional domesticated populations of locally adapted genotypes. In this study, we investigated a comprehensive set of 1485 spring barley landraces (L Hordeum vulgare L. ssp. vulgare, the domesticated form of wild barley H. vulgare L. ssp. spontaneum (C. Koch) Thell., is one of the oldest cereal crops Cultivated barley, In barley, as in most crops, genetic bottlenecks occurred during domestication and crop improvement. For most loci current elite varieties harbour less genetic diversity than their wild relatives or early domesticates th-century landraces were largely replaced by modern cultivars ex situ repositories. Globally, landraces represent the largest part of barley germplasm conserved in genebanks  Since the beginning of the 20Rht1 and Rht2) derived from the Japanese wheat landrace “Shiro Daruma” Sub1) in rice mlo11 (from an Ethiopian barley landrace) Examples demonstrating the utilization of landrace genetic diversity include the introgression of i) plant height dwarfing alleles , a population based method to identify marker-trait associations based on linkage disequilibrium (LD) is being recently used extensively in crop plants rc1485”). We studied genetic diversity and population structure using microsatellite  markers, which provided the basis for targeted research activities. The legacy core reference set (CRS) Lrc648 established here is available for the scientific community to integrate data and to improve our elite barley varieties under changing environmental conditions.Several studies were performed in barley to investigate genetic diversity in different germplasm collections using molecular markers, and few of these collections (panels) were established for GWAS. However, most studies were based on either cultivar collections Hordeum accessions available in 2008 at the “Federal ex-situ Genebank for Agricultural and Horticultural Crop Plants” maintained at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) in Gatersleben, Germany. The landraces originated from 41 countries in Europe, West and Central Asia, North and East Africa and covering 5.63°–62.47° N and 16.62°–71.5° E. The selection was based on the following criteria: i) Mansfeld's taxonomical classification system considering growth habit, row type of the ear, kernel coverage, spike density, and seed colour http://gbis.ipk-gatersleben.de). Barley landraces collected during targeted expeditions before 1992 were considered whenever possible to work with trustable materials. From Syria and Jordan only a few landraces (six accessions) were included - as barley landraces from this region were comprehensively investigated by In total, 1491 spring barley landrace accessions adapted to diverse climate conditions were originally considered for this study. This representative collection was carefully selected among 22,093 http://maps.google.com/maps) and global Gazetteer version 2.2 .The IPK genebank practices the splitting of original landrace accessions and maintains them as morphologically distinct accessions to counteract the possible loss of rare alleles in the original population of genotypes Four seeds per landrace accession were randomly selected and sown under greenhouse conditions at IPK in 2008. Leaf material from one representative plant per accession was harvested three weeks after sowing. DNA was isolated from freeze-dried leaves using a BioRobot 9600 Work Station and the MagAttract 96 DNA plant core kit . Forty-five fluorescence-labelled SSR markers were selected based on their mapping position in the barley genome, covering all seven chromosomes rc1485) considered was inferred using Structure 2.2 K) without prior knowledge of their population affinities. Structure simulations were performed with the number of presumed clusters from K = 1 to K = 20 and five runs per K value. For each run, the initial burn-in period was set to 50,000 followed by 100,000 Markov Chain Monte Carlo (MCMC) iterations. The most probable number of clusters was determined by plotting the estimated likelihood values [LnP(D)] as a function of KK) values were also calculated as proposed by The population structure of the 1485 landraces (Last 2.12 p-distance) between 1485 landraces were constructed using SplitsTree 4.13.1 Principal Component Analyses (PCA) were performed using Pe), were determined for all loci across the total population using Powermarker 3.25 rlequin 3.1 tructure inferred groups. Genetic differentiation among groups was calculated based on unbiased Fst estimators st) were determined among all groups as well as allelic richness, gene diversity (GD) and the number of alleles for each group were calculated using Fstat 2.9.3 The number and frequency of alleles, gene diversity and heterozygosity . Based on the 42 SSR markers considered, 372 alleles were obtained with fragment sizes ranging from 90 to 360 bp . The numtructure runs were performed for K = 1 to K = 20 based on the distribution of 372 alleles at 42 SSR loci among 1485 accessions. LnP(D) values increased slowly starting from K = 10, thus probably representing the most appropriate number of major clusters in this collection. However, the maximum delta (K) value was reached at K = 4 (Sat K = 4 .K = 2 was observed mainly between Ethiopian (Group 1) and non-Ethiopian landraces (Group 2) (G) considering the 60% membership coefficient (Q-matrix). The least number of admixtures  was observed at this K value.The primary division at Group 2) . Here 92K = 4, 91.1% of the landraces were assigned to one of the following groups – G1 (314): two-rowed and six-rowed barleys mainly from Southwest Asia; G2 (277): two-rowed and six-rowed landraces mostly from Ethiopia; G3 (439): mainly six-rowed hulled barleys from a wide geographical range including northern Africa; and G4 (323): mainly two-rowed hulled forms from Europe and Southwest Asia. The population structure inferred using PCA provided congruent results (At  results .K = 10 (G1 (194) consisted of naked barleys mostly from Ethiopia. G2 comprised of 66, mostly six-rowed landraces from a wide geographical range were hot desert climate is prevailing. G3 was the second largest group  and harboured the highest average number of alleles (252) and 78 group specific rare alleles. Allelic richness based on rarefaction provided the highest value for this group ; intermedium (4); and labile (7) genotypes. Gene diversity was lowest for G5 (0.258)  and Iran (7). Among nine naked barleys considered here, five were collected in Afghanistan. Ninety-seven, mainly two-rowed landraces from Minor Asia and the eastern part of the Fertile Crescent were assigned to G7 including lines from Turkey (29), Iraq (11), Iran (32), Afghanistan (5) and Georgia (7). Highest gene diversity value was found for this group (0.492) , and only 129 alleles  1 and 2 explained 9.90% and 8.58% of the variation, respectively, and separated most Structure inferred groups  indicating especially within G1, G2, G4, G5; G7 and G9 further substructure based on e.g. row type or geographical origin.Known key determinants of the population structure for barley like i) row type of the ear, ii) kernel coverage, and iii) geographical origin divided the collection at K = 10 . The cluK = 10 .. G1 (19is group . Mainly  (0.258) . Altoget (0.492) . G8, the alleles . Finallynean Sea , S4 Fig.d groups .. Relatist values among Structure inferred groups at K = 10 ranged from 0.196 (between G4 - from Georgia and G7) to 0.556 . Similarly pairwise Fst comparisons for inferred groups at K = 4 ranged from 0.187 to 0.388 (tructure inferred groupsK = 10) and the percentage within the populations ranged from 62.40% (Structure inferred groupsK = 10) to 93.62% . The values for the comparison of all Ethiopian naked vs. all non-Ethiopian naked barleys are interesting and possibly indicating two evolutionary lineages (Pairwise Fto 0.388 . Highly lineages .P <0.0001). The correlation between genetic distance and longitudinal distance  was high. The correlation between genetic distance and latitudinal differences  was 2-fold lower than the correlation between genetic and geographic distances. In the Mantel correlogram for genetic distance vs. geographic distance, the matrix was subdivided into 20 discrete distance classes. Within the distance class of 0-300 km between the collection sites of accessions, the correlation was highest (r = 0.523). The r - values (Mantel correlation) and their significances declined with increasing distances. Spatial Mantel correlograms provided similar trends   to fully humid boreal climates (Dfb). Most samples are located in warm temperate climates, either summer dry (Csa) or fully humid (Cfb). In more detail one can observe, that all accessions from G1 and G5 are located in winter dry climates in Ethiopia; G4 lines were only sampled from Georgia, where fully humid boreal climates (Dfb) prevail. G2 is mainly located in hot and dry desert climates (BWh) and G6 (six-rowed) prevails in wintercold steppe climates (BSk). G7 occurs along a narrow latitudinal range (30–43° N) in Minor Asia and the Fertile Crescent in warm temperate summer dry climates (Csa). G8 (two-rowed) and G10 (six-rowed) were sampled further north, majorly between 40–50°N  and 36–47°N , respectively.Se below) .. S6 Tabrc1485 collection, different sizes of core groups from n = 1 to n = 1485, with a step size increase of 50 accessions were computed using Mstrat and plotted against their diversity score calculated based on allelic richness. The M strategy performed better in efficiently capturing maximum allelic diversity than the random sampling approach (rc648 was established using Mstrat consisting of 308 two-rowed (242 hulled and 66 naked types) and 340 six-rowed (285 hulled and 55 naked types) genotypes (rc648 and a random set of landraces comprising the same number of accessions (Lrc648r)  .ex situ genebank collections The demand for higher yielding and better-adapted crop varieties has raised the need to exploit the large Most probably due to careful selection and accurate description of the material , very few geographical outliers were observed. Another reason for the good fit of accessions into geographical clusters could be that 1035 (69.7%) accessions were sampled during IPK collection missions . These accessions were probably not collected originally in these areas. We assume they were sampled elsewhere and then grown ex situ in these countries, or they may have been incorrectly recorded or mixed up during seed exchange and propagation. As recently shown by Few accessions appeared to be suspect and do not seem to represent their original collection site  of 8.95 alleles per locus, which is larger than in most other studies, including A total of 157 rare alleles were detected in the whole collection. Rare alleles were mostly detected at SSR loci, which displayed a high number of polymorphic alleles. The presence of 42% rare alleles highlights the potential of this collection for subsequent allele mining studies but could potentially limit GWAS.rc1485 for GWAS in more detail, genetic diversity values were directly compared to the potentially most diverse GWAS panel for barley comprising of 224 spring barley cultivars and landraces of worldwide origin (“Genobar” panel) rc1485, the CRS Lrc648 but also the subpanels of Lrc648 based on the row type of the ear - are all more diverse than the Genobar panel as indicated by e.g. the total number of alleles, number of unique alleles or average gene diversity. Unique alleles observed in the Genobar panel came from genotypes collected from East Asia as well as from the Americas. Such regions were not considered in Lrc1485 , which is not surprising due to the relatively low marker coverage (LD estimates between SSR markers were computed .. All pacoverage . and theK = 10 as the most appropriate number of major clusters in the Lrc1485 collection. Although the maximum delta (K) value was reached at K = 4, clusters at K = 10 were better defined based on geographical origin, row type of the ear and caryopsis type – and also associated to distinct Köppen climate zones.We assessed population structure by different approaches. Based on Bayesian clustering and PCA analyses we considered G1, G3, G4, G5 G8 and G10 were distinct and well supported. An intrinsic genetic substructure was visible for groups, which included accessions from a larger geographical range . PCA provided mostly congruent results for these clusters. However, PCA does not classify accessions into discrete clusters in all cases, especially not when admixed accessions and accessions of various geographical origins with a constant gene flow are included eighbor-Joining and Neighbor-Net analysis supported these findings. All clusters obtained by Structure analysis were distinguishable, although a high amount of reticulation was evident, owing to the fact that common alleles per locus were shared among geographic regions  materials sampled from a wide range of eco-geographical conditions around the Mediterranean Basin  (To explore the genetic diversity and relationships among and within Sassessed . Gene dititudes) , S4 Fig.G7, G8) or six-rowed  types, respectively  and G5 (from Ethiopia) containing both row types. However, within groups G1, G4, G5 and G9 subclusters can largely be explained by the row type of the ear.As expected for barley, the row type of the ear was an important determinant of the population structure ectively . KaryopsDetailed knowledge of environmental parameters at a certain collection site can help determining the role of relevant climatic factors influencing the genetic differentiation and adaptation of genotypes to their environments. Furthermore, this knowledge might help selecting most suitable parental lines for population development and breeding programs.vs. continental climates. Thus the general pattern of climate zones  is band along the latitudes.The distribution of accessions was found rather along the latitudes, meaning a wider W-E than N-S window. Just Ethiopia is the southern-most sampling area, i.e. stretching the latitudinal direction the most. In general, climatologically, climate zones are determined by i) incoming solar radiation ; ii) b) altitude ; and iii) proximity to the sea yielding maritime tructure inferred groups probably indicate a preferred distribution path rather zonal (W-E) than meridional (N-S), i.e. higher correlation with longitude and indeed this was observed for Lrc1485 groups. As domesticated barley spread meridionally from the Fertile Crescent to north-western Europe, the crop encountered considerable ecological and environmental change. Natural mutation, selection and enrichment of favorable alleles at key loci such as Ppd-H1HvCENVRN-H1VRN-H2VRN-H3 , observed as deletions of a cluster of up to three ZCCT family genes, which contribute to the spring growth habit rc1485.However, based on the IPK genebank information system, we selected only spring barleys, which flowered at IPK without the need for any cold period to promote flowering. In Central Europe (such as at IPK), spring types are sown between early March and end of April depending on the weather conditions every year enobar collection, which harbors six haplotypes at PpdH1HvCEN studied by rc648. Thus, we suggest using the legacy CRS Lrc648 or their two subpanels in particular for allele mining and gene discovery studies.As already shown partly for the GAlthough altitude must be considered as an important factor influencing the genetic diversity distribution The initial Köppen analysis presented here does not give a very clear picture due to outliers and thus a rather high within-group-variability . HoweverK = 10, 277 Ethiopian landraces were assigned to either of two groups comprising naked  and hulled types . Both groups were further sub-structured according to their row type of the ear  predominated in genotypes assigned to G5 (89%) PpdH1 , most lines from G5 carry insensitive alleles, thus in combination with haplotype IV at HvCEN, providing favorable alleles for the two growing seasons of barley in Ethiopia - Meher and BelgAlthough morphologically diverse, Ethiopian hulled barleys harboured a relatively low level of nucleotide diversity as indicated by the lowest gene diversity value, the second lowest level for allelic richness and only five group specific rare alleles. These results provide further evidence that Ethiopian barleys went through a major genetic bottleneck followed by adaptation to climatic  and edaphic conditions in the Abyssinian highlands  [87], [9G1) harbored 57 group specific alleles (second largest number found) and higher value for allelic richness compared to G9. Pairwise comparison of Fst values between Structure inferred groups showed that G1 is most closely related to G5 (0.35) supporting a common origin of Ethiopian barleys. However, G1 and G9 (the two naked groups) are genetically less related (0.49), while G9 is closer connected to G7 (Fst 0.29). Thus, our data suggest at least two evolutionary lineages of naked barleys, both of which probably originated in the eastern Fertile Crescent from a monophyletic natural mutation (17 kb deletion harboring an ethylene response factor (ERF) family transcription factor gene) at the nud locus on chromosome 7H nud locus are required to test this hypothesis and to shed more light on the origin of naked barley. Interestingly, outside Ethiopia, two-rowed naked landraces were mainly sampled from Iraq and Iran, while six-rowed naked types were collected further east (Afghanistan) Interestingly, Ethiopian naked barleys  (and thus supporting two evolutionary lineages for naked barley), while all Ethiopian hulled vs. all non-Ethiopian hulled barleys explained only 18.50% . Also AMOVA of all hulled Ethiopian vs. all naked Ethiopian types (26.69) compared to all two-rowed Ethiopian vs. all six-rowed Ethiopian landraces (6.38) suggested that hulled and naked genepools are genetically more distant than the two-rowed and six-rowed clusters. Hulled and naked types probably evolved largely independent under cultivation and were domesticated for different end-use qualities Interestingly, the second highest variation explained among groups by AMOVA was found between y 18.50% . AMOVA orc1485 harbors great genetic diversity. However, the collection size of 1485 genotypes is not manageable in most phenotypic studies, and smaller panels are needed. The legacy CRS Lrc648 established here is best suited for multi-environmental field testing under various climates. However, to work with even more manageable sets, we suggest dividing the Lrc648 into two-rowed and six-rowed subpanels, depending on the trait of interest  procedure.Seeds of the LS1 FigDistribution of 45 SSR markers used across the seven linkage groups of barley.(TIF)Click here for additional data file.S2 FigScatter plot of 1485 barley landraces based on Principal Component Analysis calculated from 42 SSR data. a) for K = 4, b) for K = 10. Colours correspond to the different Structure inferred groups.(TIF)Click here for additional data file.S3 Figtructure inferred groups at Geographical distribution of 1485 landraces over Köppen climate zones according to SK = 4. Each group (G1-G4) and admixed types were separately plotted. (a)G1; (b)G2; (c)G3; (d)G4; (e) admixed types. Climate abbreviations are explained in (TIF)Click here for additional data file.S4 Figtructure inferred groups at Geographical distribution of 1485 landraces over various Köppen climate zones according to SK = 10. Each group (G1-G10) and admixed types were separately plotted. (a)G1; (b)G2; (c)G3; (d)G4; (e)G5; (f)G6; (g)G7; (h)G8; (i)G9; (j)G10; (k) admixed types. Abbreviations are explained in (TIF)Click here for additional data file.S5 Figtructure inferred group at Individual PCA's for each SK = 10. Each plot represents a single group: (a)G1, (b)G2, (c)G3, (d)G4, (e)G5, (f)G6, (g)G7, (h)G8, (i)G9, (j)G10. Blue circles indicate two-rowed and red circles six-rowed barleys.(TIF)Click here for additional data file.S6 FigCorrelograms showing spatial genetic autocorrelation patterns among: (a) genetic distance and geographical distance; (b) genetic distance and longitude; (c) genetic distance and latitude; (d) genetic distance and annual mean temperature; (e) genetic distance and mean diurnal range; (f) genetic distance and mean temperature of warmest quarter; (g) genetic distance and annual precipitation. The x-axis represents distinct classes and the y-axis represents the mantel r values.(TIF)Click here for additional data file.S7 Figstrat and random sampling to capture most efficiently genetic diversity to establish a core reference setComparing the sampling efficiency based on M. Average diversity score calculated based on allelic richness was plotted against the sample size. Red circles indicate scores of the core collection using the M strategy and blue circles indicate scores of randomly selected accessions.(TIF)Click here for additional data file.S8 Figrc1485 and Lrc648 based on PCA calculated from 42 SSR data.Scatter plot of L Landraces selected for Lrc648 are indicated in red colour.(TIF)Click here for additional data file.S9 FigLinkage Disequilibrium (LD) display of 1485 barley landraces using 42 SSR markers. LD was calculated in TASSEL 2.1(www.maizegenetics.net/tassel) using 1000 permutations. Markers are arranged according to the genetic positions on barley genome (see nome see ..(TIF)Click here for additional data file.S10 FigEvolutionary relationships of 1485 barley landraces I. The evolutionary history was inferred by a) a Neighbor-Joining tree, and b) a Neighbor-Joining strict consensus tree computed in SplitsTree software.(TIF)Click here for additional data file.S11 FigEvolutionary relationships of 1485 barley landraces II. The Neighbor-Net planar graph of uncorrected p-distances visualizes the high amount of reticulation in the collection .(TIF)Click here for additional data file.S1 Tablerc1485 collection.The La) Details of accession names, their taxonomical designations, row type and kernel coverage, collection sites, collection missions and all other information available from IPK genebank documentation System (GEBIS); and b) Structure assignments to groups K = 2 to K = 20, phenotypic data for Lrc648 and haplotype information for HvCEN obtained from rc648 are indicated. Six accessions were excluded from further analysis due to large extent of missing values. NS – not selected for core group of 648 genotypes; *lost during single seed descent and multiplication.(XLSX)Click here for additional data file.S2 TableFinal SSR data set for the whole collection of 1491 barley landraces investigated. Fragment sizes and 0/1 matrix are provided.(XLSX)Click here for additional data file.S3 Tablest values between the Structure inferred groups groups a)Pairwise comparison of F for K = 4 and b) for K = 10. Significance of P-values computed after 1000 permutations are represented above diagonal and the Fst values are presented below.(DOCX)Click here for additional data file.S4 TableAnalysis of Molecular Variance (AMOVA). Summary of partitioning of genetic variation among and within different groups of Lrc1485.(DOCX)Click here for additional data file.S5 TableMantel correlogram tables.a) Mantel correlogram tables between: genetic distance and geographic distance; b) genetic distance and longitude difference matrix; c) genetic distance and latitude difference matrix; d) genetic distance and annual mean temperature; e) genetic distance and mean diurnal range; f) genetic distance and temperature of warmest quarter; and g) genetic distance and annual precipitation. 1different distance classes are shown; 2lower and upper boundary values for each class; 3number of pairs for which the correlation was calculated within each distance class; 4the mantle correlation for each class; 5the significance of mantel correlation for each class.(DOCX)Click here for additional data file.S6 Tabletructure inferred groups.Overview of Köppen climates prevailing in S Variety - number of different climates within the group; *the few geographical outliers were not removed. (XLSX)(XLSX)Click here for additional data file.S7 Tablerc1485, Lrc1014, Lrc648 and Lrc648r using 42 SSR markers and climatic variables.Comparison of diversity statistics for different sample sizes of core groups generated from 1485 accessions as well as L N - number of accessions; AN - average allele number; GD - gene diversity; PIC - polymorphism information content; MAF - average major allele frequency.(DOCX)Click here for additional data file.S8 Tablerc648 (based on Mstrat) and the random set Lrc648r.Comparison of phenotypic diversity between the core set L Min. - minimum; Max. – maximum; SD. - standard deviation of the measured traits heading date (Hd) (in days to flowering), spike length (Sl) (in cm) and plant height (Ht) (cm).(DOCX)Click here for additional data file.


Genetic diversity is the main source of variability in any crop improvement program. It serves as a reservoir for identifying superior alleles controlling key agronomic and quality traits through allele mining/association mapping. Association mapping based on LD (Linkage dis-equilibrium), non-random associations between causative loci and phenotype in natural population is highly useful in dissecting out genetic basis of complex traits. For any successful association mapping program, understanding the population structure and assessing the kinship relatedness is essential before making correlation between superior alleles and traits. The present study was aimed at evaluating the genetic variation and population structure in a collection of 192 rice germplasm lines including local landraces, improved varieties and exotic lines from diverse origin.A set of 192 diverse rice germplasm lines were genotyped using 61 genome wide SSR markers to assess the molecular genetic diversity and genetic relatedness. Genotyping of 192 rice lines using 61 SSRs produced a total of 205 alleles with the PIC value of 0.756. Population structure analysis using model based and distance based approaches revealed that the germplasm lines were grouped into two distinct subgroups. AMOVA analysis has explained that 14 % of variation was due to difference between with the remaining 86 % variation may be attributed by difference within groups.Based on these above analysis viz., population structure and genetic relatedness, a core collection of 150 rice germplasm lines were assembled as an association mapping panel for establishing marker trait associations.The online version of this article (doi:10.1186/s12284-015-0062-5) contains supplementary material, which is available to authorized users. Rice, being the staple food crop for more than 50 % of the world population is cultivated in 163 million hectares with the production of 491 million tonnes. About 90 % of the world’s rice is produced in Asia and India contributes 20 % of the world’s production. This record level production and productivity is due to the availability and exploitation of rich genetic diversity existing in rice germplasm of India. For precise genetic manipulation of complex quantitative traits like, yield, tolerance against biotic/abiotic stresses, quality etc., understanding the genetic/molecular basis of target traits needs to be investigated thoroughly.The genetic basis of important agronomic traits has been unraveled through Quantitative Trait Loci (QTL) mapping either through linkage mapping  or through LD mapping . Although traditional linkage based QTL-mapping has become an important tool in gene tagging of crops, it has few limitations viz., 1) classical linkage mapping involves very high cost; 2) it has low resolution as it can resolve only a few alleles and 3) it has limitations towards fine mapping of QTLs as it needs BC-NILs. These limitations can be overcome by the LD based approach of “Association Mapping” using the natural populations. Association mapping serves as a tool to mine the elite genes by structuring the natural variation present in a germplasm. It was successfully exploited in various crops such as rice, maize, barley, durum wheat, spring wheat, sorghum, sugarcane, sugarbeet, soybean, grape, forest tree species and forage grasses  computed according to Nei (All the 192 rice germplasm lines were genotyped using 61 SSR (microsatellite) markers which produced a total of 205 alleles . Similarly the maximum of adhoc measure ΔK was found to be K = 2  method using DARwin separated the accessions into two main groups which showed similar results as STRUCTURE analysis. The group I in UPGMA tree consists of both indigenous and agronomically improved varieties whereas the other group consists of exotic accessions. In UPGMA tree, the accessions within group 1 and 2 clustered into smaller sub groups based on their origin and types. Most of the landraces and varieties have been clustered in upper branches of the tree whereas the exotic accessions have been clustered in lower branches of the tree Fig . Hence tIS was 0.50 and FIT was 0.56. Determination of FST for the polymorphic loci across all accessions has shown FST as 0.14 which implies high genetic variation . Sixty one SSR primer pairs which produce polymorphic allele amplification were chosen to genotype the entire set of germplasm collection.DNA was extracted from leaf tissue by grinding with liquid nitrogen using CTAB method  polyacrylamide gel according to Sambrook et al.  was estimated using the program POWERMARKER Ver3.25  by Arlequin (Excoffier et al.  Nei Nei  distance Nei Nei .


The genetic diversity of cowpea was analyzed, and the population structure was estimated in a diverse set of 768 cultivated cowpea genotypes from the USDA GRIN cowpea collection, originally collected from 56 countries. Genotyping by sequencing was used to discover single nucleotide polymorphism (SNP) in cowpea and the identified SNP alleles were used to estimate the level of genetic diversity, population structure, and phylogenetic relationships. The aim of this study was to detect the gene pool structure of cowpea and to determine its relationship between different regions and countries. Based on the model-based ancestry analysis, the phylogenetic tree, and the principal component analysis, three well-differentiated genetic populations were postulated from 768 worldwide cowpea genotypes. According to the phylogenetic analyses between each individual, region, and country, we may trace the accession from off-original, back to the two candidate original areas (West and East of Africa) to predict the migration and domestication history during the cowpea dispersal and development. To our knowledge, this is the first report of the analysis of the genetic variation and relationship between globally cultivated cowpea genotypes. The results will help curators, researchers, and breeders to understand, utilize, conserve, and manage the collection for more efficient contribution to international cowpea research. Vigna unguiculata L. Walp.), an annual crop, is one of the most important and widely cultivated legumes in the world, particularly in Africa, Latin America, and some parts of Asia and the United States. According to the data from the Food and Agriculture Organization (FAO) (http://www.fao.org), approximately 5.8 million tons of dry cowpea cereal is produced annually with a minimum of 11 million hectares planted all over the world. Cowpea cereal is a very important source of carbohydrates (63%) and proteins (25%), with low fat content (1.5%), and is rich in vitamins, minerals , folate, thiamin, and riboflavin. Cowpea is chiefly used as a grain crop; however, it also finds use as animal fodder or as a vegetable  SNP type had 270 SNPs (25.7%); [CT] 246 (23.5%); [GT] 149 (14.2%); [AT] 139 (13.3%); [AC] 127 (12.1%); and [CG] 118 (11.2%). Among the 1,048 SNP loci, the major allele frequency, gene diversity, heterozygosity, and PIC averaged 0.77, 0.32, 0.06 and 0.26, respectively, and also showed large ranges of; 0.50–0.95, 0.09–0.52, 0.0–0.68, and 0.08–0.41, respectively, indicating the existence of SNP variations and mutations (gene flow) and also genetic diversity among the 768 cowpea genotypes.The population structure of the 768 cowpea accessions/cultivars was inferred using STRUCTURE 2.3.4  and the Neighbor-joined cluster analysis from MEGA 6  also cleIn this study, the tested 768 cowpea accessions, except the Indian accessions, were divided into 9 groups based on their original geographical regions: South Africa, West Africa, Central East Africa, East Asia, Central West Asia, Europe, Oceania, North America, and Latin America; the germplasm accessions from India was listed as a special group called “India” because West Africa and the Indian Sub-continent were considered to be the origin of cowpea domestication according the earlier studies , 26; andBased on the 11 groups, the genetic parameters of each of the 11 groups were estimated for the number of cowpea accessions, number of countries, the major allele frequency, gene diversity, heterozygosity, and PIC . Nine ofThe genetic distance among the 11 groups was calculated using CS Chord 1967  method iThe population structure in each of the 11 groups was further analyzed based on the results from STRUCTURE 2.3.1 . Three cFor each of the 11 groups, the majority of accessions were sectored into different structured populations (clusters). For the two groups; America Cultivar and West Africa, the majority of accessions were divided into two populations (cluster Q1 and Q2) with nearly half each; in the other three groups: North America, Latin America, and Central East Africa, the majority of accessions belonged to Q1 with nearly 50% accessions, and the other half were distributed in Q2 and Q3; Europe had 100% accessions in Q1; for the East Asia, Central West Asia, and South Africa group, nearly half to more than half were in Q2; a total of half the accessions in India were located in Q3 (50.0%), and 88.9% accessions in Oceania were in Q3 , furtherBased on the percentage of accessions in the structured population 3 (Q3) in each of the 11 groups, two larger groups can be constructed: i) a high Q3 ratio group including North America (21.6%), Latin America (25.4%), Oceania (88.9%), India (50.0%), Central East Africa (24.0%), and South Africa (27.1%), and ii) a low Q3 ratio group consisting of America Cultivar (4.1%), Europe (0%), East Asia (0%), Central west Asia (9.1%), and West Africa (7.1%), which is similar to the phylogenetic relationship in The genetic diversity was further analyzed by country in all 768 tested cowpea genotypes originally collected from 56 countries with 22 out of the 56 countries showing 5 or more cowpea accessions . A sub-tThe genotyping by sequencing (GBS) using the Illumina HiSeq showed high levels of SNP variations among the cowpea samples. The percentage of each SNP type in our study was 25.7, 23.5, 14.2, 13.3, 12.1, and 11.2% for [AG], [CT], [GT], [AT], [AC], and [CG], respectively, which complied with previously reported research [The majority of genetic variance exists within instead of among geographic regions and within instead of among countries in the USDA cowpea world collection. Compared to the study by Zannouou et al.  with accPopulation structure analyses divided the 768 cultivated cowpea genotypes into 3 gene pools  based on the peak of delta K (DK) at K = 3. While the DK had a high score at K = 2  B, in acBased on PIC values, the accessions in the cowpea collection that originated in India and East Africa are most highly diversified (3.2 and 3.0), followed by Oceania, America, South and West Africa with medium high diversity, then the American Cultivar, East and Central West Asia with medium and Europe with lowest PIC (0.17). Different growing environments, availability of genetic stocks, and diverse cowpea consumption behaviors may be responsible for diversity differences among the regions. In our study the diversity degree compared to prior landrace study have been slightly reduced , which mIn general, the degree of genetic diversity tends to have a positive correlation with the number of countries from which the accessions were collected. The more the number of origins of accessions, the more is the genetic diversity detected . Truly, sesquipedalis and biflora, which can only be found in India and East Asia. These two types differ from the African domesticated forms. The possible assumption is that when cowpea moved farther east into East Asia and encountered more humid environments with less sunshine, unsuitable for drying pods and grains it made people prefer the immature pods as vegetable in Asia [In the African continent, the populations belonging to each region have very low genetic distance, but the populations between West and South, and the Central East have an obvious difference in Q3 accessions ratio. One possibility for this paradox is that the Q3 accessions have high homology with Q1. This is also authenticated by the phylogenetic result  which sh in Asia . During  in Asia . The cluThe wield distribution of countries from West Africa was found in the Country Cluster Analysis , which cThe closest relation was found between North and Latin America, also having a highly similar genetic structure and PIC, which reveals a high accordance in variety import and localization. In addition, low Q3 ratio in America Cultivar implies that breeding programs in America might import and employ a large number of the accessions from West Africa or Asia. A similar report was also brought out by Fang et al  who indiBreeding projects could generally narrow the genetic variation of crop resources. If there were no germplasm introduced into the programs, genetic diversity would be reduced over time. In our study, we came to the same conclusion that breeding dramatically reduces the genetic variations of cowpea. We also found that some new cowpea resources were created when it was moved or domesticated into new environments, for example, in East Asia, which may increase the genetic diversity of the breeding groups. Now geographical barrier has now drastically reduced when the germplasm involved into whole cultivation system in the world during the globalization, which is the chance to help us improve the breeding resources. We have to consider both phenotype and genotype aspects in understanding germplasm resources, especially in breeding programs.Three well-differentiated genetic populations called structured populations or clusters were postulated from this study in the 768 world-wide cowpea genotypes based on genome-wide SNPs. The populations (clusters) were associated with the regions and countries where the cowpea genotypes were collected. Cluster 1 mainly consisted of the cowpea genotypes from Asia , West Africa (Cameroon and Niger), and Europe (Hungary) plus the American Cultivars; Cluster 2 was composed of accessions from South Africa, India, and US; and Cluster 3 was from Latin America , South Africa , Central East Africa (Kenya) and Oceania . This study supports the two candidate theory of the original areas (West and East of Africa) as the first domestication regions of cowpea and India as a sub- domestication region of cultivated cowpea.S1 Table(XLSX)Click here for additional data file.


Aconitum is a medicinal treasure trove that grows extensively on fertile pastures in Xinjiang Province (China); however, its molecular genetic characteristics are still poorly studied. We studied Aconitum kusnezoffii Reichb., Aconitum soongaricum Stapf., Aconitum carmichaelii Debx. and Aconitum leucostomum Worosch, using random amplified polymorphic DNA (RAPD) and inter-simple sequence repeat (ISSR) techniques, to evaluate their genetic relationship and potential medicinal value. Our results showed that A.kusnezoffii Reichb. and A.soongaricum Stapf. have close genetic relationship and cluster together. Polymorphism rates of 97.25% and 98.92% were achieved by using 15 RAPD and 15 ISSR primers, respectively. Based on Nei's gene diversity (H) and Shannon's index (I), the inter-population diversity (sH) was higher when compared with the intra-population diversity (pH). Among the three Aconitum populations, the coefficient of gene differentiation (stG) was 0.4358 when evaluated by RAPD and 0.5005 by ISSR. The genetic differentiation among the three Aconitum populations was highly significant, suggesting low gene flow (mN). This was confirmed by the estimates of gene flow . Comparing the RAPD and ISSR results, the two DNA markers proved similarly effective in the assessment of the genetic characteristics of the studied Aconitum populations and could be used for reliable fingerprinting and mapping in studies on Aconitum diversity in view of Aconitum suitability for development and protection. Aconitum sinomontanum for inhibiting ageing and growth of cancer cells [Acontium flavum Hand-Mazz for anti-inflammation and local anaesthesia.[Aconite is a valuable traditional Chinese herb of the family Ranunculaceae. The root of this plant is usually used for treating rheumatoid arthritis and easing of pain. In recener cells  or totalesthesia.Aconitum has 10 species and 5 varieties, and grows on fertile pastures in Xinjiang Province of China. The wild populations of this plant are a real treasure trove as a medicinal resource, but its overgrowth has become a grave threat to ranching in recent years, because aconitine is toxic to animals. To reduce the harm to ranches and at the same time enhance the medicinal utilization of aconite is a highly desired goal. In our previous work,[Aconitum carmichaelii Debx. and Aconitum kusnezoffii Reichb. and different Aconitum species from Xinjiang, we found some similarities and differences in the chemical composition. Therefore, further investigation on the genetic relationship between aconite in Xinjiang and common aconite (A.carmichaelii Debx. and A.kusnezoffii Reichb.) would be important for developing its potential medicinal value.Genus ous work, we analyMolecular marker techniques are powerful and valuable tools used in the analysis of medicinal plants. Among the markers, RAPD (random amplified polymorphic DNA) and ISSR (inter-simple sequence repeat) are generally preferred because of their sensitivity, simplicity and cost-effectiveness. Both RAPD and ISSR markers have been successfully applied to detect genetic similarities or differences in various herbs. As theseAconitum in Xinjiang and A.carmichaelii Debx. and A.kusnezoffii Reichb., by RAPD and ISSR markers. The obtained information about the genetic characteristics will be valuable for screening a variety of Xinjiang representatives of genus Aconitum.The aim of the present study was to assess the genetic identity between representatives of genus Aconitum leucostomum Worosch., Aconitum soongaricum Stapf., A.carmichaelii Debx. and A.kusnezoffii Reichb. The details of the accessions and their geographic origin are listed in Fifteen aconite plants belonging to four species were chosen: 2), 2.5 mmol/L of MgCl2, 0.2 mmol/L of each deoxyribonucleoside triphosphate (dNTP), 0.4 μmol/L primer and 2 U of Taq DNA polymerase, by means of a thermal cycler . The cycling programme began with an initial 7 min at 95 °C, followed by 45 cycles at 95 °C for 45 s, 34 °C for 30 s and 72 °C for 90 s, plus a final 10 min at 72 °C and storage at 4 °C. Amplification products were separated by electrophoresis in 1.5% agarose gels. A total of 120 single primers  were used in the PCR programme, and as a result, 15 primers that amplified polymorphic bands were selected. The sequences of the 15 primers are shown in For polymerase chain reaction (PCR), 20 ng of genomic DNA were amplified in a volume of 50 μL containing 10X PCR buffer , 2.5 mmol/L of MgCl2, 0.2 mmol/L of each dNTP, 0.4 μmol/L primer and 2 U of Taq DNA polymerase, by means of a thermal cycler . PCR amplification was performed as follows: initial denaturation at 95 °C for 7 min, followed by 45 cycles at 95 °C for 30 s, 48 °C–60 °C for 45 s and 72 °C for 90 s and a final 10 min extension at 72 °C. Amplification products were separated by electrophoresis in 1.5% agarose gels. A total of 100 primers  were used in the PCR programme, and as a result, 15 primers that amplified polymorphic bands were selected. The sequences of the 15 primers are shown in ISSR reactions were performed in a volume of 50 μL containing 25 ng of template DNA, 10X PCR buffer , the number of observed alleles (aN), the mean number of effective alleles (eN), mean Nei's gene diversity index (H), the Shannon index (I) and the level of gene flow (mN) [sH), total gene diversity (tH) and Nei's coefficient of gene differentiation (stG) [stG = (1 − sH/tH); m,N estimate of gene flow from stG, mN = 0.5 × (1° Gst)/Gst.. The level of similarity among individuals was established as a percentage of polymorphic bands, and a matrix of genetic similarity was compiled using Dice's coefficient.[Aconitum were generated by applying the unweighted pair-group arithmetic average (UPGMA) method.[For the two types of molecular markers, several independent samples from each lication. The polylow (Nm) ,9 were don (Gst)  were calfficient. Dendrogr) method.Aconitum species by RAPD and ISSR. The other primers did not generate any amplification products or stable bands. The results from the amplification obtained using the 15 selected primers, the total number of amplification products and the total number of polymorphic fragments, are summarized in Aconitum specimens analysed, a total of 182 bands and a polymorphism index (P) of 97.25% were obtained by RAPD, and a total of 185 bands and a polymorphism index (P) of 99.02%, by ISSR , respectively (I) values for the three populations, based on RAPD and ISSR, were similar: 0.4686 and 0.4654, respectively. These high I values at the population level indicate that the populations belong to different species.Based on genetic identity, the 15 ectively . The eststG) was 0.4358 and 0.5005, respectively, for RAPD and ISSR, among the three Aconitum populations .The average coefficient of genetic differentiation (ulations . This hiAconitumcarmichaeli Debx, and more precisely its lateral roots, is used in one of the traditional Chinese medicine herbs, Radix Aconiti Lateralis Preparata. Due to their wide range of clinical applications, aconite plants have become an important medicine resource. Aconitum kusnezoffii Reichb., A.soongaricum Stapf., A.leucostomum Worosch., Aconitum karakolicum Rapaics and Aconitum leucostomum var. nalatiensis are widespread in several regions in Xinjiang Province.[A.carmichaelii and A.kusnezoffii, and are used frequently in traditional medicine in the Northwest Territories. However, their quality and purity must meet the market requirements. Aconite products have complex sources, with high-quality medicinal material sometimes mixed together with inferior varieties. It is difficult to classify and genetically analyse them, using traditional morphological characteristics and pedigree analysis. Both RAPD and ISSR technology are valid and useful tools for classification and genetic analysis and have been successfully used for the identification of Aconitum species.[These results are interesting, as cultivated Province. Such med species. These meAconitum spp. medicinal material. They can effectively reveal the genetic relationship between medicinal plant materials. In this way, inter- and intra-species DNA variability can be analysed at the molecular level, which is particularly important in breeding and cultivation of new varieties.Both RAPD and ISSR are effective techniques for assessment of the genetic diversity of Aconitum leucostomum Worosch. was clustered separately, suggesting that it could be considered as a relatively independent Xinjiang aconite species, because it has farther genetic distance than other species. That is why it may be a promising target for future investigations into its medicinal value. The obtained results are also relevant in view of the suitability of the used sets of RAPD and ISSR primers for development and protection of traditional Chinese medicinal material, and regulation of the Chinese medicinal material market.This study is, to the best of our knowledge, the first report on the genetic characteristics of such a range of aconite germplasm in Xinjiang Province. The obtained RAPD and ISSR data indicated high level of genetic differentiation and low gene flow among the studied species.


The Czechoslovakian Wolfdog is a unique dog breed that originated from hybridization between German Shepherds and wild Carpathian wolves in the 1950s as a military experiment. This breed was used for guarding the Czechoslovakian borders during the cold war and is currently kept by civilian breeders all round the world. The aim of our study was to characterize, for the first time, the genetic composition of this breed in relation to its known source populations. We sequenced the hypervariable part of the mtDNA control region and genotyped the Amelogenin gene, four sex-linked microsatellites and 39 autosomal microsatellites in 79 Czechoslovakian Wolfdogs, 20 German Shepherds and 28 Carpathian wolves. We performed a range of population genetic analyses based on both empirical and simulated data. Only two mtDNA and two Y-linked haplotypes were found in Czechoslovakian Wolfdogs. Both mtDNA haplotypes were of domestic origin, while only one of the Y-haplotypes was shared with German Shepherds and the other was unique to Czechoslovakian Wolfdogs. The observed inbreeding coefficient was low despite the small effective population size of the breed, possibly due to heterozygote advantages determined by introgression of wolf alleles. Moreover, Czechoslovakian Wolfdog genotypes were distinct from both parental populations, indicating the role of founder effect, drift and/or genetic hitchhiking. The results revealed the peculiar genetic composition of the Czechoslovakian Wolfdog, showing a limited introgression of wolf alleles within a higher proportion of the dog genome, consistent with the reiterated backcrossing used in the pedigree. Artificial selection aiming to keep wolf-like phenotypes but dog-like behavior resulted in a distinctive genetic composition of Czechoslovakian Wolfdogs, which provides a unique example to study the interactions between dog and wolf genomes. Canis lupus), were probably an inherent character of the whole process [Recent genomic studies indicate that dogs were domesticated via a commensal pathway and that repeated admixtures between the domesticated lineage and its wild ancestors, the grey wolves  hybrids (F1) obtained in 1958 as a military project in the former Czechoslovakia [The latter originated from first-generation German Shepherd (GS) slovakia ,9,10.In this paper, we aimed to i) quantify the proportions of parental wolf and dog genomes retained in the CSW after 25 years of backcrossing by comparing the current breed’s genetic data with genotypes sampled from their ancestral founder populations, that is, the wild Carpathian wolves and the domestic German Shepherd dogs; ii) ascertain parameters of variation; (iii) assess the role of hybridization with wolves as a potential compensation for the loss of genetic variation; and iv) study the potential role of artificial selection (genetic hitchhiking) on the studied loci.N = 22), or obtained from the Prague Zoo (N = 3), and three tissue samples from Slovakia. Wolf stool samples were collected by Friends of the Earth organization (FoE CZ), which is monitoring the wolf population in the Carpathian Mountains. There are no restrictions for the use of stool samples in the Czech Republic. In Slovakia, FoE CZ has permission to collect non-invasive samples of wolves, issued by Regional Office Trenčín, Department of Environment, No. OU-TN-OSZP1-2014/49/3475.In total, 79 individuals of CSW, 20 individuals of GS and 28 individuals of CW were analyzed. Cheek swab samples of CSW and GS were collected during dog shows in the Czech Republic. Only animals in healthy condition with permission and assistance of the owners were sampled, with every effort made to minimize their stress. One individual per litter was analyzed to avoid biases in genetic variability measurements. Wolf samples consisted of 25 non-invasive stool samples collected in the western Carpathians (st–January 15th) in Slovakia within a quota set by the local authorities, in conformity with regulation No. 344/2009 Coll. The wolves were shot during individual patrols or collective hunts. The use of poisoned bait or leg-hold traps is strictly forbidden according to hunting law. All hunters had permission for hunting, and we confirmed that the culls were reported before quota fulfillment. No animals were sacrificed for the purposes of this study. Our laboratory has approval (No CZ 11712934) to storage and use of animal material according to § 48(1)(i) of Act No 166/1999 concerning veterinary care and amending certain related laws, as amended, pursuant to Article 17(1) of Regulation of the European Parliament and of the Council (EC) No 169/2009 and Article 27(1) of Commission Regulation (EU) No 142/2011. Tissue and stool samples were stored at −20°C in 10 volumes of 95% ethanol. Saliva samples were dry-stored.The three tissue samples were derived from wolves that were legally culled during the open hunting season  for tissue and saliva or the QIAamp Stool Mini Kit  for stool samples. DNA from stool samples was extracted, amplified, and genotyped in separate rooms reserved for low-template DNA samples, under sterile ultraviolet laminar flow hoods, following a multiple-tube protocol  includinSamples were thus genotyped based on the following: i) the Amelogenin gene ; ii) 39 autosomal microsatellites  and four sex-linked microsatellites ; and iii) the hypervariable part of the mtDNA control region .Genotyping of the Amelogenin gene, 39 autosomal and four Y-linked microsatellites was performed as described in Randi et al. .www.softgenetics.com) and binned using raw size in Autobin (http://www4.bordeaux-aquitaine.inra.fr/biogeco/Ressources/Logiciels/Autobin).Amplifications were replicated twice for tissue and salivary samples and from four to eight times for fecal material. Allele sizes were manually scored in GeneMarker v.1.85  simulations of expected allele-size differences using 1000 randomizations in Micro-Checker .The hypervariable domain of the mtDNA control region was amplified using polymerase chain reaction (PCR) according to Vilà et al. . SequencNA), mean number of effective alleles per locus (NE), expected (HE) and observed (HO) heterozygosity, estimations of the inbreeding coefficient (FIS) and allelic richness with correction to equal sample size (AR) were computed in FSTAT 2.9.3.2 [N of the smallest group in the data set, which is 20 in this study. The number of private alleles (NP) was determined in GenAlEx 6.5 [K) was set by running the program from K = 1 to K = 5, with 10 repetitions of 1 000 000 MCMC chain steps after a burn-in period of 100 000 steps for each K. STRUCTURE results were visualized in STRUCTURE HARVESTER [Genetic diversity measurements such as the mean number of different alleles per locus  and 95% confidence intervals (CI) for CSW were estimated using, as single-sample estimator, a bias-corrected version of the linkage disequilibrium method [NeEstimator v.2.0 [Ne with non-overlapping generations by using 10–20 microsatellite loci  and samples of at least 25–50 individuals, if the effective population size is less than approximately 500 [NeEstimator was run using the 79 CSW and considering a PCrit value  of 0.02, which was recommended as the value ensuring the most precise and less biased results when working with microsatellites [Contemporary effective population size  in CSW were simulated using the program BottleSim v.2.6 [The effects of a population bottleneck on genetic variability parameters  and their AR is the highest among the studied groups (AR = 4.626), they have the largest differences between HE (HE = 0.6404) and HO (HO = 0.691); thus, their FIS (FIS = 0.069) is slightly elevated compared to GS and CSW  was 0.993). However, at K = 3, all individuals were correctly assigned to their own breed (CSW or GS) or wolf clusters with qì values > 0.80 (mean Qi was 0.981) and any internal substructure was detected among CSW  but a lower NE (NE = 2.38 vs. 2.69) and heterozygosity values  compared with simulated data (25th generation).The scenario obtained using yzed see  as CSW sNeEstimator, the effective CSW population sizes we observed, considering PCrit = 0 and PCrit = 0.02, were Ne = 94.4 (95% CI: 87.8–101.6) and Ne = 92.8 (95% CI: 86.0–100.2), respectively, which are values, that are slightly higher than those obtained with real data. This difference could suggest a change in the maintenance of the genetic variation because of the non-random mating applied in the origin of the breed.When we used the 339 simulated genotypes obtained after 25 generations of mating in NA), mean number of effective alleles per locus (NE), number of private alleles (NP), allelic richness (AR), expected (HE) and observed (HO) heterozygosity, inbreeding coefficient (FIS), and Hardy-Weinberg equilibrium (HWE) deviations, in the recent Czechoslovakian Wolfdog breed that were compared to those obtained from the breed’s ancestral founder populations, the wild Carpathian wolves and the domestic German Shepherd dogs.In this study, we obtained estimates of genetic diversity parameters, including mean number of alleles per locus  it was very fast compared to the natural domestication process, which possibly lasted thousands of years, and therefore, selection pressures were presumably intense; and ii) it included direct selection for morphological traits, whereas during the first domestication phase, the main selective pressures presumably acted on behavioral  traits, with phenotypic variants originating as by-products of these changes [In the present study, we have described the impact of processes such as hybridization between dogs and wolves, population bottlenecks and artificial selection on the genetic diversity patterns in the Czechoslovakian Wolfdog. It seems that hybridization with the dog’s wild ancestors may have compensated for the loss of genetic variation caused by bottleneck demography. The phase of artificial selection applied to mosaic wolf  changes . To concS1 Table(XLSX)Click here for additional data file.S2 Table(XLS)Click here for additional data file.


Solanum lycopersium L.) is the most widely grown vegetable in the world. It was domesticated in Latin America and Italy and Spain are considered secondary centers of diversification. This food crop has experienced severe genetic bottlenecks and modern breeding activities have been characterized by trait introgression from wild species and divergence in different market classes.The tomato  using a custom-made Illumina SNP-panel. Most of the 175 successfully scored SNP loci were found to be polymorphic. Population structure analysis and estimates of genetic differentiation indicated that landraces constitute distinct sub-populations. Furthermore, contemporary varieties could be separated in groups  that are consistent with the recent breeding aimed at market-class specialization. In addition, at the 95% confidence level, we identified 30, 34 and 37 loci under positive selection between landraces and each of the groups of commercial variety . Their number and genomic locations imply the presence of some extended regions with high genetic variation between landraces and contemporary varieties.Our work provides knowledge concerning the level and distribution of genetic variation within cultivated tomato landraces and increases our understanding of the genetic subdivision of contemporary varieties. The data indicate that adaptation and selection have led to a genomic signature in cultivated landraces and that the subpopulation structure of contemporary varieties is shaped by directed breeding and largely of recent origin. The genomic characterization presented here is an essential step towards a future exploitation of the available tomato genetic resources in research and breeding programs.The online version of this article (doi:10.1186/1471-2164-14-835) contains supplementary material, which is available to authorized users. Solanum lycopersicum L.) was probably domesticated in Mexico from wild species that originated in the Andean region, although other hypotheses have been also put forward  for each K value. (JPEG 723 KB)Additional file 7: Figure S1: Estimation of the optimum number of clusters. Estimation of the optimum number of clusters of tomato accessions according to the analysis of variance of the log-likelihood values  of the genotypes based on STRUCTURE and CLUMPP analyses. (XLSX 52 KB)Additional file 9: Table S8: Pairwise estimates of Fst and Nei’s standard genetic distance (Dst) between predefined groups or between groups of tomato accessions as inferred by the Bayesian analysis implemented in the STRUCTURE software. (XLSX 16 KB)Additional file 10: Table S9: Heterogeneity in F-Statistics among loci. (XLSX 11 KB)Additional file 11: Table S10: Candidate loci under positive selection between landraces varieties and the different market-classes of contemporary varieties. (XLSX 10 KB)Additional file 12: Table S11: Marker names and their genomic information. (XLSX 22 KB)


Acropora millepora. Bayesian cluster analysis and assignment tests indicated gene flow is restricted, but not absent, between the outer and inner Keppel Island groups, and that extensive gene flow exists within each of these island groups. Comparison of the Keppel Island data with results from a previous GBR-wide study that included a single Keppel Island population, confirmed that A. millepora in the Keppel Islands is genetically distinct from populations elsewhere on the GBR, with exception of the nearby inshore High Peak Reef just north of the Keppel Islands. We compared patterns of genetic diversity in the Keppel Island populations with those from other GBR populations and found them to be slightly, but significantly lower, consistent with the archipelago being geographically isolated, but there was no evidence for recent bottlenecks or deviation from mutation-drift equilibrium. A high incidence of private alleles in the Keppel Islands, particularly in the outer islands, supports their relative isolation and contributes to the conservation value of the archipelago. The lack of evidence for genetic erosion, in combination with our observation that the North Keppel Island population samples collected in 2002 and 2008, respectively, exhibited a pairwise genetic distance of zero, supports previous published work indicating that, following bleaching, Acropora corals in the Keppel Islands predominantly recover from regrowth of small amounts of remaining live tissue in apparently dead coral colonies. This is likely supplemented by recruitment of larvae from genetically similar, less disturbed populations at nearby reefs, particularly following extreme flood events.Coral reefs surrounding the islands lying close to the coast are unique to the Great Barrier Reef (GBR) in that they are frequently exposed to disturbance events including floods caused by cyclonic rainfall, strong winds and occasional periods of prolonged above-average temperatures during summer. In one such group of islands in the southern GBR, the Keppel Island archipelago, climate-driven disturbances frequently result in major coral mortality. Whilst these island reefs have clearly survived such dramatic disturbances in the past, the consequences of extreme mortality events may include the loss of genetic diversity, and hence adaptive potential, and a reduction in fitness due to inbreeding, especially if new recruitment from external sources is limited. Here we examined the level of isolation of the Keppel Island group as well as patterns of gene flow within the Keppel Islands using 10 microsatellite markers in nine populations of the coral,  Acropora spp. down to 1.3 m below lowest tide level  is comprised of the fringing reefs surrounding the 15 islands of Keppel Bay, located ∼12 km from the mainland coast. The Keppel Islands are renowned for their high disturbance regime, causing repeated widespread coral mortality. A major flooding event occurred here in 1991 , which cde level . Thermalde level , particude level .Acropora spp. in the Keppel Islands , in the Keppel Islands using a population genetics approach. Specifically, we explore genetic structure, connectivity and diversity on nine shallow reefs throughout the Keppel Island region using high-resolution DNA microsatellite markers. We also compare population genetic diversity and local population genetic structure of A. millepora in the Keppel Islands to that of 19 reefs spanning much of the latitudinal range of the GBR and including one of the nine Keppel Island reefs sampled six years earlier , grows prolifically between 0–6.0 m  forming shallow, expansive reef flats on the leeward shores of islands in the Bay  was used to determine the fragment sizes  of all samples. All automatic scoring was checked manually, and samples that yielded ambiguous or no signal were re-amplified and re-run or removed from the analysis. The new data acquired in this study were first analysed separately and subsequently combined with previously obtained data on the same species and using the same loci, but from 20 GBR locations spanning 12° of latitude  and inclThe probabilities of identity by random sexual mating  were calp-values using the Markov chain method (A. millepora using the same loci that included one site (Nth Keppel) from the Keppel Islands, showed that despite the presence of null alleles, heterozygote deficits were mostly due to biological rather than methodological factors (Genotypic Linkage Disequilibrium (LD) was assessed in GENEPOP (web version 4.0.10) by estimation of exact n method  using de factors . Despite factors , all anaOH) and expected (EH) heterozygosities and private alleles. Differences in rarefacted allelic richness  between the nine Keppel Island sites and the 19 other sites from throughout the GBR were assessed in FSTAT 2.9.3 using a Mann–Whitney U test , allelic richness (Ar), allelic evenness (Ae), observed (y U test .OH) excess at polymorphic loci compared to that under HWE (EH)  . If HWE HWE (HE) . The hetHWE (HE) . TherefoSTF values calculated using an AMOVA approach  was computed in SMOGD version1.2.5  Josact test  actual mion1.2.5 . To visu Service .n = 370) and Keppel Islands plus the GBR  datasets. STRUCTURE analyses were conducted using both the admixture and no-admixture models, each with correlated allele frequencies, using the sampling sites as prior (LOCPRIOR), which has been shown to better resolve genetic structure when there is low genetic divergence , which was set to the default value of 0.6 for analysis. TESS was run with a burn-in of 10,000 sweeps followed by 25,000 sweeps, with 20 independent runs conducted for each value of K from K of 2 to 9 for the KI data and K of 2 to 15 for the combined KI plus GBR data . For each value of K, the ten runs with the lowest DIC scores were used to calculate the average DIC and evaluate the most likely number of genetic clusters. The coefficient of ancestry was calculated for each individual across all runs for the most likely value of K in CLUMPP version 1.1.2 . Plots of allelic evenness  of which occurred in the Keppel Islands. Given the relatively small sample size from Keppel Island populations , private alleles are overrepresented in this archipelago. Twenty-one of the 23 Keppel Island samples with private alleles were from the outer island group.Private alleles were found in 54 out of 1,292 colonies of STF = 0.055, p < 0.001). Pairwise STF values were significant for all comparisons  except for Halfway Island-Miall Island, Halfway Island-Nth Keppel Island and Miall Island-Nth Keppel Island  was smaller than for K = 2 (ΔK = 230) and K = 3 (ΔK = 35), all were much larger than for all other values of K . Given that TESS clearly delineated three genetic clusters for the Keppel Islands alone, we present K = 5 for the combined dataset. All sites in the Keppel Island archipelago were genetically distinct from GBR populations in the far northern, northern and central GBR reefs, as well as most southern GBR reefs except High Peak .For the combined GBR plus Keppel Island data set, STRUCTURE results showed that Δe slowly . Althougigh Peak , which migh Peak . In partigh Peak  and had estD values ranging from 0.175 to 0.253   . Larval 00 days) , likely 00 days) . While t00 days)  that expA. millepora populations in the Keppel Island archipelago are genetically isolated from most other populations on the GBR  and these reefs therefore unlikely serve as a source of larvae for the Keppel Island populations. A. millepora has a relatively high dispersal potential due to its broadcast-spawning mode of reproduction and long larval competency period. We hypothesise that, in the Keppel Islands, other coral species with similarly high dispersal potential to A. millepora, as well as species that disperse over shorter spatial distances, will also consist of primarily self-sustaining populations . This suggests that the archipelago is vulnerable to perturbations that cause widespread high coral mortality, as recovery through the arrival of recruits from reefs outside the Keppel Islands will be slow. the GBR  and are  the GBR . The neaSTF value not significantly different from zero when compared with the 2008 sample from the same location. In addition to the 2002 bleaching event, a mass bleaching episode occurred in the Keppel Islands in 2006, causing ∼40% loss in coral cover (Acropora spp. (Acropora spp. in the Keppel Islands (The 2002 Nth Keppel Island sample (collected prior to the 2002 bleaching event) exhibited no evidence of a genetic bottleneck, which was unexpected given the high mortality experienced during the 1998 mass bleaching event . The samal cover . Given tal cover , and thaora spp. , there wora spp.  and inst Islands  appear tAcropora spp. down to 1.3 m below lowest tide . Further, populations of this species in the Keppel Island archipelago are self-sustaining and receive very little input from populations elsewhere on the GBR. Genetic diversity analyses suggest coral recovery in the Keppel Islands often occurs from surviving colony regrowth rather than by recruitment from external sources, especially following bleaching. However, when whole colony mortality is widespread within a reef but variable among reefs (as is the case with floods), recruitment from external, nearby reefs that suffered low mortality can facilitate recovery.Our microsatellite genotyping results demonstrate that populations of the common reef builder, 10.7717/peerj.1092/supp-1Table S1Click here for additional data file.10.7717/peerj.1092/supp-2Table S2N, number of samples per locus and population after removal of repeated MLGs; A, number of alleles; EH, expected heterozygosity; OH observed heterozygosity; ISF, inbreeding coefficient. Italic font indicates statistical significance after FDR correction.Click here for additional data file.10.7717/peerj.1092/supp-3Table S3Adjusted alpha was 0.011; significant values are highlighted in yellow.Click here for additional data file.10.7717/peerj.1092/supp-4Table S4p-values larger than adjusted α are printed in bold face (adjusted α = 0.012).Most values are statistically significant; non-significant values have shaded background, and Click here for additional data file.10.7717/peerj.1092/supp-5Table S5Assignment probabilities >0.1 are highlighted.Click here for additional data file.10.7717/peerj.1092/supp-6Figure S1Click here for additional data file.10.7717/peerj.1092/supp-7Figure S2Click here for additional data file.10.7717/peerj.1092/supp-8Figure S3Click here for additional data file.10.7717/peerj.1092/supp-9Figure S4Click here for additional data file.10.7717/peerj.1092/supp-10Figure S5Click here for additional data file.10.7717/peerj.1092/supp-11Figure S6Click here for additional data file.10.7717/peerj.1092/supp-12Data S1Click here for additional data file.


Historically, the first calls to conservation were based on the economic, ecological and scientific values of the AnGR. While the historical arguments are valid and still commonly proposed values for conservation, the AnGR have become highly politicized since the adoption of the Convention of Biological Diversity (CBD), the subsequent Interlaken Declaration, the Global Plan for Action (GPA) and the Nagoya Protocol. The scientific and political definitions of the AnGRs were creatively reshuffled within these documents and the key criteria by which they are now identified and valued today were essentially redefined. The criteria of “ The sovereign rights over GRs have been subsequently re-enforced with the adoption of the Nagoya Protocol on Access and Benefit-sharing2 entering into force on October 2014. The Nagoya Protocol is the legally binding protocol guiding how to interpret and act upon the genetic resources issues presented in the CBD over 20 years earlier.Animal genetic resources (AnGRs) have become a topic of renewed interest in international politics taking agricultural species as its object of concern for the last decade. The reasons for this point to a number of intertwined reasons. The first has to do with the unclear legal status and the scope of regulation stemming from biodiversity agreements targeting a wide range of animal species from wild to agricultural, their biological materials and genetic resources within the global politics of late 20th and early 21st century. Here, states, nations and indigenous communities have become new key stakeholders of genetic resources as they have been granted sovereign rights over territorially bound, native “3. All these Committees—specifically established for different types of genetic resources—demonstrate how difficult the policy, ownership and access and benefit sharing issues related to GRs, and especially to AnGRs, are to understand, let alone to manage in practice.The second, and inherently nested interest relates to the way in which access and animal could, or should, be regulated internationally under biodiversity frameworks, including debates on how different kinds of genetic resources from plants to animals and from wild to agricultural species differ from each other and how the difference might have to inform the practical execution of their global governance. The Food and Agriculture Organization of the United Nations (FAO) established a Commission on Plant Genetic Resources in 1983 to deal with policy, access and benefit sharing issues related plant genetic resources. FAO did broaden the mandate of the Commission in 1995 to cover all aspects after the CBD entered into force and after recognizing “that broadening the coverage of the Commission would allow the Organization to deal in a more integrated manner with agrobiodiversity issues” , p. 66. Three examples from international analyses from the last 10 years will clarify some of the difficult aspects related to global agreements and governance on agricultural AnGRs and open up good questions how did the AnGRs become so politically contested objects of agricultural nature.[c]lassical ownership’ of AnGR includes physical ownership and communal ‘law of the land’ affecting livestock keeping and breeding. There is an increasing tension with developments in the realms of biodiversity law and intellectual property rights protection. Demarcation of these different rights systems and maintaining equity among different stakeholders is crucial to avoiding conflict and increased transaction costs. In this context, it is important to consider the rights of livestock keepers/breeders vis-à-vis national level sovereign rights, as well as obligations between patent holders and breeders/livestock keepers.” First, why are the issues of AnGRs for agriculture debated alongside more general issues of biological diversity;and(2)Second, how should we understand that idea of sovereignty over genetic resources given to the signatory states of the CBD and the Nagoya Protocol in the context of AnGRs?The first hypothesis builds on the cultural history of AnGRs movement in the political institutions, most notably in the FAO. I claim that early warnings about the need for the conservation and coordinated management of AnGRs for agriculture did not lead to action and resulted in a failure to mobilize larger communities to action. This, in turn, lead the animal geneticists affiliated with FAO and other interests parties to join forces with environmental conservation movement, especially United Nations’ Environmental Programme (UNEP), to gain international support to the issue of conservation then seen as a agenda priority.Second, and following from the historical reason explained above, the way in which CBD and to certain extent the subsequent Nagoya Protocol defined and understood genetic resources owes much to the world of plant genetic resources (PGR). Defining the right and obligations of signatories through the PGR leads implicitly to the world of plant breeding, which operates differently from animal breeding practices, the key economic relations, and related biological processes. This is also why the key articles and provisions in the biodiversity conventions are couched in strong terms under national governments’ sovereign powers.I claim that this has resulted in a world, where we have moved from a system where animals once were part of a seamless universal nature without political boundaries, to a world that is a collection of discrete “national genetic landscapes” safeguarded by state policies and legal provisions.already carried out activities relating to animal genetic resources…and the Organization’s involvement in this work dates back to 1946” (The management of farm AnGRs become a topic immediately after the establishment of the United Nation’s Food and Agriculture Organization (FAO), however, the concerns related to genetic resources were first identified as a challenge for developing countries. The negative consequences of modern animal production aiming at increasing animal productivity started to raise doubts within the scientific community, and the first calls for genetic conservation followed quickly. Phillips, the first Deputy Director-General for the FAO remembers how he, as the first employeed of the animal section for FAO, had all his career “to 1946” , p. 5. FThe present era of frozen semen…has reactualized the problem of gene losses…The problem arises mainly from the fact that an effective utilization of the best animals of today automatically means setting aside the poorer animals, strains, breeds and even species”  launched a joint project in 1974 with the title of “inction” , p. 17. I am pleased to bid you welcome here, on behalf of the Director—General. It is indeed heartening to see such a distinguished group of animal geneticists assembled to consider the problems of identification, conservation and effective management of animal genetic resources. This is matter critical to man’s future, yet it has had little recognition and little real attention , adopted in 2007, and the Guidelines on the Preparation of national strategies and action plans for AnGRs, published in 2009.Given the half-century history of AnGR’s as a matter of concern for animal geneticists and long and idle wait for political action, the key question is why did the wide scale political traction to save genetic resources only emerge with the introduction of the CBD, leading to the global and national action plans and guidelines specific to AnGRs over a decade later?The reason why the FAO and the regional institutions such as the EAAP failed in gaining political traction with their early alarms about the need for conservation measures relates to two shortcomings in the definition and the valuation of AnGRs.First shortcoming was the lack of consensus in scientific definition, valuation and prioritization of AnGRs that would lead into simple and uniform action recommendations. The question on what is it exactly that needs to be conserved and how to prioritize the required conservation actions was left open, or at best was illustrated through a case of a few particular breeds. The second, and more important shortcoming was the failure of global political and legal identification of the responsible parties and beneficiaries of any value deriving from the costly conservation actions. This, in turn, relates to the fact that up until the CBD, AnGRs were treated as a mixture of “private” and “commons,” or as “club commons”  to be shAfter the introduction of the CBD the legal status of AnGRs changed globally as they were politically identified falling under the sovereign power of the signatory parties to the Convention—a major change and complication in access and benefit sharing relations that was later affirmed by the GPA in 2007 and later by the Nagoya Protocol. Understanding the latter is especially important as this understanding exposes the new overarching paradigm under which the value most of the AnGRs today are to be governed.First, the failure to provide a clear direction for conservation relates to the arguments about the overall role of different kinds of AnGRs in animal production. When the concept of AnGRs were first introduced among the animal scientist, they were framed in and through two different ways  of demonstrating the role of AnGRs in animal production. The two ways—the “utilizationist” and “conservationist” standpoints—literally attributed the value of AnGRs in animal production in two incommensurable ways (and to some extent this debate still continues even today). The utilizationist’s primary concern is the immediate usefulness of available genetic resources to improve livestock populations…The loss of breeds as distinct identities is not generally a concern, as long as the genes that make these breeds potentially useful are retained in the commercial stocks…The preservationist’s primary objective is long-term conservation of genetic resources for future use. This view emphasizes the value of preserving the widest possible spectrum of genetic diversity to be prepared for unpredictable changes of future needs. The greatest possible number of breeds are to be preserved as purebreds.”  to be held in Brazil in about eight weeks time” . This definition bridged the two different views on the valuable material to conserve, or the “utilitizationist” and “preservationist” standpoints. Genetic resources become genetic material that could be attributed with demonstrable or imaginable value. But the question then arises: who has the right to attribute any value claims to AnGRs?in situ” within the territory of a signatory were identified as belonging under the sovereign power of signatory states representing the nations of the world, reframing their ownership relationships globally. This is how CBD enacted an important political redefinition of genetic resources: previous problems in the definition of the value of nonhuman life were re-articulated through the politics of nationhood, in the idea of national differences found within the CBD’s vision of genetic nature.The other reframing answered to this question. Under the definitions of the Article 2 and the Article 15, genetic resources found “With the convention, also AnGRs became tightly nested within the sovereignty of nation-states and their geography. A reversal of the old idea of nations being rooted in natural differences of human populations took place—nonhuman populations, conceptualized as “genetic resources,” could now be identified and placed under national or international jurisdiction in terms of their geographical location and the political powers that represented the nationhood that governed that geographical area. A global cartographic demarcation of nonhuman life took place as these novel objects of nature were grafted to the foundations of national sovereignty. They became a new part of the body of nations, a novel form of nonhuman nationhood.The CBD presupposes the right of a country to exercise sovereign control over its AnGR (accompanied by a number of responsibilities). From the perspective of an exporting country, one of its main concerns is to maintain any property rights it may wish to retain over the AnGR after the resources have left the country. Similarly, it may wish to ensure that the rights of the exporter are respected by the buyer/importer of the AnGR. The most prominent rationale for a country to regulate export of AnGR would be to secure a right over that particular material in the future, including preventing that countries or companies gain control over these resources , which might reduce the value of it in the exporting country.”The convention assumes significant amount of power over AnGR and their governance to signatory nation-states. in situ.” In the CBD, these are the “conditions where genetic resources exist within ecosystems and natural habitats, and, in the case of domesticated or cultivated species, in the surroundings where they have developed their distinctive properties.” (CBD Article 2). This “in situ” condition of valuable genetic resources has tremendous effects into how AnGRs are seen within the post-CBD world, especially as AnGRs were now removed from the idea of being freely circulated or tradable objects of nature. They stopped being global commons and instead become subject to the political powers of the Convention parties, many who did not have, and still today do not have, a clear stance what are “valuable” AnGRs to them, and how they will enact their sovereign powers over the access and benefit sharing to the valuable AnGRs. A definitional and legal disorientation followed.This reframing introduced a whole new system where the value of any animal breed will be decided by the nations signatory to the parties but without any common reference what consists legitimate value claim over the material, except the condition of “The third re-framing of AnGR’s happened as they were presented through ideas derived from the plant and crop worlds. The FAO background study in the CBD on the “Exchange, Use and Conservation of Animal Genetic Resources” acknowledged this as a major problem. It explained:[a]lthough current debates regarding agricultural genetic resources have largely had a crop/plant focus, these discussions, and the international instruments or agreements that are emerging have tended to frame the debate for AnGR as well. At first sight plant breeding does not differ much from animal breeding. The genetics of plants and animals are based on the same principles. Plant and animal breeders both need genetic diversity in order to advance and the genetics determine adaptation to particular agro-ecological circumstances, as well as product qualities to a large extent. However, plant varieties can be protected by plant breeder’s rights (UPOV), which is not the case for animal breeds/strains. Plant breeders aim at the development of new uniform varieties that are defined by certain phenotypic traits that can identify them from other varieties. Farm animal breeding is largely based on the selection of individuals within populations rather than selection between populations or strains. Farm animal breeders are interested in individual animals (within populations/breeds), while the whole population of a plant variety (clones) is the main focus of plant breeders.” These re-framings of the AnGR dictate much of how global action now unfolds. 15 years after the CBD, in 2007, the state representatives adopted the first “Global Plan of Action for Animal Genetic Resources” (GPA) at the Interlaken Conference held in Switzerland, something that was called a “historical breakthrough” by the FAO Director General Jacques Diouf , p. iii.The fact that animals can move across politically established boundaries created a potential problem to these sovereign rights, however, and led to new politically innovated categories of AnGRs, such as “transboundary” species for criss-cross institutionalized country borders. The GPA explained: “Assessing the status of animal genetic resources on a global scale presents some methodo-logical difficulties. In the past, analysis of the Global Databank to identify breeds that are globally at risk was hampered by the structure of the system, which is based on breed populations at the national level. To address this problem…a new breed classification system was developed. Breeds are now classified as either local or transboundary, and further as regional or international transboundary” , p. 13.With these political documents not only did animals considered as genetic resources become “national” pertaining to a state, but some of them also became “transboundary,” regionally and internationally. The result of this is that political categories infuse with conservation science categories because of the political economy involved in the ownership rights over the actually or potentially valuable genetic resources.in situ” or “transboundary” are inherently related to the political cartographic demarcation of the natural ecologies of domesticated animals, pointing to the deep connection between politics of value and the science of conservation of farm genetic animal resources. This is what eventually created the incentive for nation-states to act upon the issue of genetic erosion of animal populations, but is now, at the same token, generating new challenges that are beyond the scope of animal scientists or even international organizations to solve.These categories are as much politically informed as they are scientifically true. The definitions of “[t]he complex subject matter of ABS, its potentially far reaching impact on uses of genetic resources and related information as well as the lack of detail in Articles…have all combined to result in a very low level of domestic implementation by Contracting Parties to the CBD. By 2007, only 39 of the then 189 Contracting Parties had established domestic legislation or were in the process of doing so.”  must be met before it can be provided to a third party for research and development” What is the true scope of the CBD and Nagoya Protocol in terms of AnGR types? Are there types of AnGRs that remain totally unaffected by and reside outside of the scope of the global conventions?(2)Do the signatory parties (nation-states) have prototypical reactions to—or at least broadly identifiable patterns in—the implementation of their sovereign powers over AnGR?(3)If the signatory parties do exhibit identifiable patterns, a guiding typology of CBD and Nagoya Protocol implementation at national level would help to make sense of how governments are adopting the global agreements  at large.Addressing these three points would already give a much richer and much more coherent overview of AnGRs’ status in the post-CBD and post-Nagoya Protocol world than is currently available for public. We do suggest that the institutions driving the global framework on genetic resources provide it soon.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The intra- and interpopulation progenies were evaluated in a 10 × 10 triple lattice design in two separate locations. The data for unhusked ear weight (ear weight without husk) and plant height were collected. All genetic variance and covariance components were estimated from the expected mean squares. The breakdown of additive variance into intrapopulation and interpopulation additive deviations (στ2) and the covariance between these and their intrapopulation additive effects (CovAτ) found predominance of the dominance effect for unhusked ear weight. Plant height for these components shows that the intrapopulation additive effect explains most of the variation. Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs.This study was carried out to obtain the estimates of genetic variance and covariance components related to intra- and interpopulation in the original populations (C0) and in the third cycle (C3) of reciprocal recurrent selection (RRS) which allows breeders to define the best breeding strategy. For that purpose, the half-sib progenies of intrapopulation (P Reciprocal recurrent selection (RRS) was originally proposed by Comstock et al.  to improSince the RRS has been proposed, numerous studies in the literature have been designed to clarify particular aspects of this selection method, such as a suggestion for changes in the original method –6, compaOne of the main points to be attentive to in reciprocal recurrent selection is maintenance of the variability of the population in each breeding cycle. Thus, estimates of genetic variance components are useful for breeding purposes because they allow the use of appropriate strategies to achieve success in breeding programs. n) and verifying their magnitude and changes from selection. In the few cases in which these components were estimated, only the original populations (C0) and the interpopulation hybrid between them were involved d and CovA2τ21 = 2rs(r − p)[a + (1 − 2r)d]d}, where a is the deviation of homozygotes in relation to the midpoint. Therefore, it is expected that, for a location to contribute to these covariances, genetic divergence (p ≠ r) and the presence of dominance are necessary, and, consequently, the covariance would be positive for the population with a higher average frequency of favorable alleles and negative for the population with a lower average frequency for these alleles. However, there are a large number of loci which one can cancel another. There are some cases in which loci are fixed in both populations (p = 1.0 and r = 1.0 or p = 1.0 and r = 0.0) [Regarding the covariance of additive effects with their intra- by interpopulation deviations in cycle zero, all estimates were negative and in some cases with high levels of error . Arias a Ramalho  obtainedy Júnior  {CovA1τ1Comparing the estimates for intrapopulation additive genetic variances in cycle zero to the ones in cycle three, a reduction in ear weight in population 2 and an increase in population 1 were observed. However, the estimates for C0 and C3 were within the limits of standard error only in population 1 and thus did not differ from each other. As for PH, Hallauer  reportedHallauer .The results obtained here, together with those reported in the literature, show that, during an RRS program, intrapopulation genetic variances can vary in magnitude without compromising the genetic variability of populations, thus leading to success of the populations involved in breeding programs.As for the interpopulation additive variances of C3 , it may Maintenance of genetic variability during the recurrent selection process is important. In this respect, the results described in the literature and these obtained in this study showed an increase in this variability, especially in the initial cycles. One explanation for this is that, at the recombination stages, gene blocks are broken up and, with each recombination, greater genetic variability is generated in populations of advanced cycles compared to the initial populations.Aτ) and those of C3 are justified only for the ear production trait. It may be noted that the magnitudes in module increased for population 1 and decreased for population 2 after three selection cycles. Unfortunately, no reports of these components  and, for characters with d/a near or below 0.5 , the components may be disregarded. Overall, the results obtained in this study are consistent with expectations. Estimates of According to a theoretical study, Júnior  showed tIt is possible that the progeny by environment interaction, in this case, has impaired the accuracy of Estimates for intrapopulation and interpopulation additive genetic variances confirm that populations derived from single-cross hybrids have potential for recurrent selection programs.There was an increase in the mean values of additive effects for EW in population 2 and a decrease in population 1 after three RRS cycles.RRS improved the complementarity of the interpopulational hybrid such that heterosis increased from 12.3% to 24.9% after three cycles.