Chrysophyllum cainito (Sapotaceae), the star apple or caimito, is a semidomesticated tree widely cultivated for its edible fruits; it is known to be native to the neotropics, but its precise geographic origins have not been firmly established. Here, we report results of microsatellite marker analyses supporting the hypothesis that the center of domestication for caimito was the Isthmus of Panama, a region in which few crop species are believed to have originated, despite its importance as a crossroads for the dispersal of domesticated plants between North and South America. Our data suggest that caimito was domesticated in a geographically restricted area while incorporating a diverse gene pool. These results refute the generally accepted Antillean origin of caimito, as well as alternative hypotheses that the species was domesticated independently in the two areas or over a broad geographic range including both. Human-mediated dispersal from Panama to the north and east was accompanied by strong reductions in both genotypic and phenotypic diversity. Within Panama, cultivated and wild trees show little neutral genetic divergence, in contrast to striking phenotypic differentiation in fruit and seed traits. In addition to providing a rare example of data that support the hypothesis of a narrow geographic origin on the Isthmus of Panama for a now widespread cultivated plant species, this study is one of the first investigations of the origins of an edible species of the large pantropical family Sapotaceae.Species in the early stages of domestication, in which wild and cultivated forms co-occur, provide important opportunities to develop and test hypotheses about the origins of crop species.  On the Origin of Species (Darwin 1859). In recent years, the use of molecular markers to study cultivated species and their wild relatives has revolutionized our ability to address questions about the process of domestication, including the number and locations of geographic areas that gave rise to domesticates, the effects of human selection on genetic diversity, and the relationship between genotypic and phenotypic variation. Such studies shed light on the spatial dynamics of human influences on gene pools through selection and dispersal, and they can inform policies aimed at conserving wild and crop diversity and promoting regional food security.Crop domestication is a long-term evolutionary process whereby wild plant populations become exploited via human management practices, leading to phenotypic and/or genetic differences between domesticated forms and their wild progenitors. Differentiation between domesticated and undomesticated races occurs along a continuum from minor, as in the case of incipient domesticates, to extreme, as in the case of full domesticates  is a tree that grows to 25 m tall and is esteemed for its edible fruit and ornamental value. The fruits are high in polyphenolic antioxidants . Based on our observations of significant differences in fruit phenotypic traits between wild and cultivated trees in Panama  of domestication have not been established with certainty. The prevailing hypothesis for many years was that the species is native to the Greater Antilles and has naturalized into Central and South America, based in part on the widespread use of the Taino name “caimito”  that are cultivated for their edible fruits and/or their latex, but despite the importance of domestication in the family, very little is known about patterns of anthropogenic evolution in this group. Third, in spite of uncertainty about its origins, caimito has been used as a native species in reforestation projects in Panama; thus, clarifying the native range and domestication status of the species has important conservation implications.The objectives of the current study were to test competing hypotheses for the origins of wild and domesticated forms of caimito and to explore patterns of genetic diversity and structure of cultivated and wild trees in southern Mesoamerica , northern Mesoamerica , and the Antilles (Jamaica and the Dominican Republic). We chose to study the origins and domestication of In this study, we addressed the following specific questions using highly variable microsatellite marker data:C. cainito? Is genetic diversity greater in southern Mesoamerica than in northern Mesoamerica and the Antilles, indicating that the species is native to Panama and was domesticated there, while wild populations in the Antilles represent escapes from cultivation?What are the origins of extant wild and cultivated populations of How has human selection affected levels of genetic diversity in cultivated caimito? Do cultivated trees in the area(s) of origin demonstrate a strong genetic bottleneck driven by anthropogenic selection of a limited number of genotypes, or, alternatively, did the initial stages of the domestication process incorporate high levels of genetic diversity? Is there marked differentiation between wild and cultivated gene pools within Panama?Chrysophyllum cainito collected from localities in the Greater Antilles (Dominican Republic and Jamaica) and both northern  and southern (Costa Rica and Panama) Mesoamerica, as well as a total of 26 individuals of the congeneric species C. argenteum,C. mexicanum, and C. oliviforme from areas where they were growing in proximity to C. cainito . Individuals were genotyped using ten nuclear microsatellite loci developed in Na). Allelic richness (AR) and the number of private alleles (Pa) were obtained using a rarefaction method to correct for differing population sizes in the program HP-Rare  was investigated using analyses of molecular variance (AMOVA) , cultivation status (cultivated and wild), and geographic region (northern and southern), values were averaged over all loci to obtain the mean number of alleles . We performed an initial analysis to determine the number of gene pools represented by all of our samples of C. cainito and related species. The entire data set, a total of 232 individuals, was analyzed by performing multiple independent runs of STRUCTURE. We used the admixture model, allowing individuals to have mixed ancestry and to fractionally assign to more than one cluster, and the correlated allele frequencies option  replications. We used the program STRUCTURE HARVESTER (Earl and vonHoldt Ln P(D), the estimated posterior probability of the data for a given K  matrices of the replicate runs of each K value from STRUCTURE HARVESTER  was higher in the south than in the north , south 2.05, north 1.21, P = 0.021. There was no significant difference in allelic richness (AR) between wild and cultivated trees in either the south or the north (P > 0.3). The number of private alleles (Pa) was significantly higher in wild trees in the south (P = 0.021) but not in the north (P > 0.7).The mean number of alleles per locus in wild individuals of caimito collected from throughout the sample range was 10.0. Based on the STRUCTURE analysis, we divided the caimito samples into two groups; north and south (see below). Allelic richness (P(D), and Evanno's ΔK method (2005) returned an optimal K value of three for our STRUCTURE analysis that included C. cainito individuals and three congeneric species of Chrysophyllum, indicating that three gene pools best explained the highest level of genetic structuring in our data set , which measures the fraction of an individual's genome that came from each gene pool. We considered an individual to assign highly to one of the three gene pool clusters if its population membership coefficient, q, was ≥0.90 for that gene pool. We considered individuals whose population membership coefficients (q) were less than 0.90 for all gene pools to be admixed.Both the Pritcenterd method  and northern Mesoamerica  assigned highly to the first gene pool cluster  C. mexicanum (57.1%), and C. oliviforme (100%) individuals assigned highly to the third gene pool cluster  were obtained when only the individuals assigned to that species were included in the analysis (data not shown).The gene pool cluster to which each individual assigned was generally associated with its geographic origin Fig. . The majq ≥ 0.90) to the gene pool being analyzed , whereas individuals from Jamaica and Guatemala assigned more highly to individual gene pools .Based on these results, we divided the caimito individuals into two major groups; northern and southern Table . To testzed Fig. . Two indzed Fig. . The higK = 4, indicating four subclusters within the southern gene pool cluster. Most individuals exhibited genetic admixture with varying contributions from each of the four subclusters and generally low assignments (q < 0.50) to any one of them. The exception to this trend was observed in trees collected from three wild localities – Pipeline Road, Venta de Cruces, and especially Old Gamboa Road – where some individuals had relatively high proportions of assignment (q ranged from 0.76 to 0.92) to the subcluster that was least represented in any of the other populations  dendrogram, the sampled individuals generally formed species-unique clusters Fig. . Chrysopals Fig. .C. cainito, one including 65 of the 95 (68%) wild and cultivated trees collected in Panama, and a second that included the remaining wild and cultivated trees sampled from Panama as well as all of the trees sampled from Costa Rica, northern Mesoamerica , and the Antilles (Dominican Republic and Jamaica). Within the second group, most  of the remaining trees from Panama fell into three clusters that formed successive sister groups to a large cluster including the vast majority of trees from the north, suggesting that the latter were derived from the former. Throughout the dendrogram, cultivated trees were largely intermixed with wild trees and neither was resolved as a distinct group, either across all sampling localities or within specific geographic regions.Two principal groups were resolved within Three separate AMOVAs were conducted: one treating individuals from northern and southern localities, respectively, as separate populations, the second treating cultivated and wild trees from the north as separate populations, and the third treating cultivated and wild trees from the south as separate populations Table . In all C. cainito into two major groups, one comprised primarily of wild and cultivated individuals sampled from Panama in southern Mesoamerica, the other comprised primarily of individuals from the Antilles and northern Mesoamerica. Results from AMOVA mirrored those from the cluster analyses in revealing higher differentiation between trees from northern and southern localities than among individuals or between wild and cultivated trees within either area.Both Bayesian Figs  and 3 anC. cainito in northern Mesoamerica and the Antilles were derived from populations in southern Mesoamerica. Allelic richness and number of private alleles were significantly higher in the south than in the north, and the genetic diversity in the latter area represented a subset of that in the former. In the STRUCTURE analysis, more individuals collected from the south exhibited admixture with the primarily northern gene pool than the reverse, and two trees from Panama actually assigned highly to the primarily northern gene pool. Similarly, in the NJ tree based on genetic distances, the vast majority of trees from populations in the north formed a cluster nested within several clusters comprised of trees from populations in the south.Our analyses further suggested that populations of High levels of genetic admixture were observed across collecting localities within Panama Fig. . These rC. cainito is native to the Isthmus of Panama and that the cultivated and wild trees in the Antilles and northern Mesoamerica were originally derived from populations on the Isthmus. We predicted that if caimito were native to the Antilles, cultivated trees would be derived from those wild populations and thus would harbor a moderate to high degree of the diversity present in the local wild populations. Our genetic data do not exhibit this pattern. Furthermore, we did not observe any trees in the Antillean and northern Mesoamerican populations that we sampled with putative undomesticated phenotypes like those observed in Panama . These results suggest that the wild trees in the northern part of the distribution are most likely secondarily wild, that is, escapes from cultivation or feral trees. We cannot rule out the possibility that ancestral, wild-type trees do or once did occur in these areas and are now rare because of frequent hurricanes or habitat conversion; we did not find them, and they have not been previously collected or reported, to our knowledge. Our observations are more consistent with the hypothesis that the forms that migrated into the Antilles were already semidomesticated. A similar pattern was reported in Crescentia cujete (jícara) where a unique domesticated form migrated via cultivation into the Yucatan Peninsula of Mexico  contained close to 90% of the wild diversity  retained roughly 80% of the diversity present in wild progenitor populations  retained 80% of the allelic diversity of wild trees (Hollingsworth et al. Overall, cultivated individuals of caimito were slightly but not significantly less diverse than wild individuals. These results indicate that cultivated Additionally, our results provide a classic example of the lack of correspondence that is often observed between neutral genetic markers and phenotypic centeracters under selection (e.g., Papa et al. C. cainito trees in Panama, comprising individuals from the Pipeline Road, Venta de Cruces, and Old Gamboa sampling localities, that showed little admixture with the other three gene pools inferred for that region, indicating that some of the genetic variation in the wild is not well represented in cultivated material.In the NJ dendrogram, caimito trees collected in Panama fall into several clusters, all but one of which include both cultivated and wild trees Fig. . Thus, iCultivated individuals of caimito retain high levels of the diversity present in wild trees and reinforce the view that cultivated trees act as important reservoirs for genetic diversity, a fact that is particularly noteworthy because natural, wild populations are increasingly at risk due to fragmentation (e.g., Aldrich and Hamrick These results underscore the value of including phylogeographic analyses of genetic data well as morphological and ecological information in conservation efforts. The limitations of ex situ conservation strategies are exacerbated in cases such as caimito, which has a small, geographically restricted center of origin. Very few germplasm collections exist currently for this species, and material from Panama is poorly, if at all, represented in them (Gazel Filho The biota of neotropical forests are among the richest in the world. Future studies that examine the origins and diversity of semidomesticates in these regions will be important not only for expanding our understanding of evolution under domestication, but also for shedding light on long-and short-term processes that affect dynamic interactions between people and plants in these important ecosystems.


One hundred forty one basmati rice genotypes collected from different geographic regions of North Western Himalayas were characterized using 40 traits linked microsatellite markers. Number of alleles detected by the abovementioned primers were 112 with a maximum and minimum frequency of 5 and 2 alleles, respectively. The maximum and minimum polymorphic information content values were found to be 0.63 and 0.17 for the primers RM206 and RM213, respectively. The genetic similarity coefficient for the most number of pairs ranged between of 0.2-0.9 with the average value of 0.60 for all possible combinations, indicating moderate genetic diversity among the chosen genotypes. Phylogenetic cluster analysis of the SSR data based on distance divided all genotypes into four groups , whereas model based clustering method divided these genotypes into five groups . However, the result from both the analysis are in well agreement with each other for clustering on the basis of place of collection and geographic region, except the local basmati genotypes which clustered into three subpopulations in structure analysis comparison to two clusters in distance based clustering. The diverse genotypes and polymorphic trait linked microsatellites markers in the present study will be used for the identification of quantitative trait loci/genes for different economically important traits to be utilized in molecular breeding programme of rice in the future. Oryza sativa L.) occupies the premier place among the food crops cultivated around the world; thus rice production and improvement are of interest to the Indian economy. India has the largest acreage under rice (44 million hectares) with annual production of about 104 million tones and ranks second only to China [Rice  markers have become a method of choice owing to their high reproducibility, simplicity, easy scoring ability, reliability, co-dominant and multi-allelic nature. Microsatellites or SSR are sequences of a few repeated and adjacent base pairs and abundance throughout the eukaryotic genome . VariatiIn the present study, the genetic diversity and population structure of 141 genotypes including landraces, farmer’s varieties, elite cultivars and advanced breeding lines of basmati rice accession collected from NW Himalayas were analyzed using 40 highly polymorphic trait linked SSR markers. Our objectives were to estimate the levels of genetic diversity, and to characterize the population structure of the NW Himalayas basmati germplasm.The present study material consisted of 141 basmati rice accessions representing landraces, farmer’s varieties, elite cultivars and advanced breeding lines collected from different basmati growing regions of India . These aTwo grams fresh leaf samples were collected from each genotype for DNA extraction. Total genomic DNA was isolated from each genotype by CTAB method . Quantifwww.gramene.org/markers/microsat/. The primer pair was selected from each chromosome. PCR reaction was prepared with 50 ng of rice genomic DNA, 0.2 μg of 3’ and 5’ end primers, 200 mM of each dNTP, 10X PCR buffer containing 50 mM KCL, 10 mM Tris HCl (pH 8.9), 2.0 mM MgCl2 and one unit of Taq polymerase with a total of 25 μL solutions individually for all 40 primer pairs. PCR thermal cycler was programmed as one step at 94°C for 4min, followed by 1 min at 94°C, 1 min and 30 seconds at 55°C, 1 min at 72°C and a final cycle of 10 min at 72°C. PCR amplification with each primer was performed thrice and only reproducible and distinct bands were scored and subjected to analysis. Amplified products were separated on 3.5% of agarose gel followed by staining with ethidium bromide. A 100-bp DNA ladder (Life Technologies-GIBCO BRL) was used to estimate the size of each band.PCR amplification was performed on each of the 141 basmati rice genotypes using primers for each SSR locus. Total 40 pairs of rice primers flanking the microsatellite region were selected from previously developed and published . Detaileni = 1 P2ij [Amplified fragments of different sizes were considered as different alleles. DNA bands that were amplified by a given primer were scored as present (1) or absent (0) for all the samples under study. In order to determine the utility of these markers, number of amplicons/alleles per marker, major allele frequency, polymorphic information content (PIC), effective multiplex ratio (EMR) / resolving power (RP), discrimination power (DP) and marker index (MI) were calculated. The polymorphic information content values of individual primer were calculated based on the formula PIC = 1- Σ 1 P2ij . Marker  1 P2ij . Resolvi 1 P2ij , 29. The 1 P2ij  and this 1 P2ij  to deterModel based cluster analysis was performed to infer genetic structure and to define the number of clusters (gene pools) in the dataset using the software STRUCTURE version 2.3.4 . The numAll the 141 basmati rice accessions were genotyped with 40 traits linked microsatellite markers; and were selected for their ability to produce amplified product at optimum concentration, polymorphism level among the varieties and consistency of the pattern. Out of 40 traits linked microsatellite markers, two markers (RM130 and RM571) were found monomorphic revealing one allele at each locus in all the genotypes. Total 114 alleles were scored from these primer pairs, and 95 percent were found polymorphic. The gel picture showing banding pattern of 141 genotypes of basmati rice with RM3 marker is given in To find out the genetic relationship between different basmati rice genotypes, SSR data were used for analysis using NTSYSpc version 2.02e. The genetic similarity coefficients found in the genotype comparison matrix were relatively moderate. The distribution analysis of the 9870 pairwise comparisons  revealedA model without admixture were carried out by varying K from 2 to 10 with 5 iterations using all 141 genotypes and 38 polymorphic markers. The whole population was stratified into five sub-populations assigned to the corresponding A-E and the inferred population structure are given in The five populations generated from structural analysis were also subjected to analysis of variance (AMOVA) to estimate the percentage of variation among populations and within population. In the total genetic variance among populations based on structure, 39.40% was attributed to the populations based on structure, and the remaining 60.60% was explained by individual differences within populations . PairwisIn summary, the results of AMOVA and Fst analysis were in good agreement with the results obtained through phylogenetic tree-based, similarity coefficient distribution and stucture analysis, and confirmed the presence of statistically moderate genetic diversity and high population structure. A critical and important factor to consider before carrying out association mapping (AM) analysis.The genetic improvement of yield and other economically important traits in crop species depends upon the genetic diversity available within the crop species. The cultivated varieties of basmati rice arise as a result of human selection from the available genetic diversity in various environments and human cultures. Modern breeding in the last two centuries has resulted in the development of varieties that are more uniform, less stable and more adapted to better control and limited environments. This has resulted in the popularization of few genotypes among the farmers, including basmati rice leading to narrow genetic base. The crop had become more prone to biotic and abiotic stresses. The basmati rice improvement requires the identification of highly diverse germplasm and highly polymorphic molecular markers which in turn can be effectively utilized for the mapping of genes/QTLs for economically important traits and their subsequent use in molecular breeding. Hence the present study is initiated to know the genetic base of the basmati germplasm commonly grown in north western Himalayas. Identification of diverse genotypes using molecular markers is advantageous over the conventional approach . SSRs mojaponica rice accessions was also observed [In the present study, the average genetic similarity (GS) was observed (0.60) which mostly ranged between 0.2 and 0.9 , reflectobserved . Similarobserved . This isThe dendrogram showed that all 141 genotypes of basmati rice were grouped into four major clusters . The genThe population structure analysis revealed 5 subpopulations A, B, C, D and E. The grouping of the genotypes here also is well based on the place of collection and geographic region. The local basmati genotypes were grouped in three subpopulations A, B and E. The genotypes from Badyal, Chatha, Bishnah, Hansley Chak, Sarore, some from Ko Brahimna Samba and R. S. Pura were grouped in sub-population A. Similarly, the genotypes from Koul Ramgarh Samba, Kathua, Sainia, some from Ko Brahimna Samba and R. S. Pura were grouped in subpopulation E. Genotypes from Ramgarh and some from R. S. Pura were grouped in subpopulation B. The varieties from SKUAST-J, Kaul Haryana, some from PAU were grouped in subpopulation C. The varieties from Palampur, Meerut, GBPUAT, IARI and few from PAU were clustered in subpopulation D. Additionally, the presence of statistically significant population structure was confirmed by AMOVA and Fst analyses. These findings are in accordance with earlier studies in which the variation among groups (35.28%) and within groups (64.72%) with a pair-wise Fst estimate ranged from 0.204 and 0.680 . SimilarFrom the similarity coefficient distribution, dendrogram, structure, AMOVA and Fst analysis it is evident that the studied of NW Himalayas basmati rice germplasm has moderate diverse genetic base and high population structure. Hence the most divergent genotypes obtained in this study can be utilized for the future basmati rice breeding programme. Also the diverse genotypes and highly polymorphic functional SSR markers identified during this study can be used for the mapping of QTLs/genes for different biotic and abiotic stresses as well as for quality traits of basmati rice. The present studied basmati germplasm can also be effectively utilized in association mapping (AM) analysis for grain quality traits as is evident from there population structure analysis which is our future objective.S1 Text(DOC)Click here for additional data file.S2 Text(PDF)Click here for additional data file.


Sexual dichromatism is the tendency for sexes to differ in color pattern and represents a striking form of within-species morphological variation. Conspicuous intersexual differences in avian plumage are generally thought to result from Darwinian sexual selection, to the extent that dichromatism is often treated as a surrogate for the intensity of sexual selection in phylogenetic comparative studies. Intense sexual selection is predicted to leave a footprint on genetic evolution by reducing the relative genetic diversity on sex chromosome to that on the autosomes.In this study, we test the association between plumage dichromatism and sex-linked genetic diversity using eight species pairs with contrasting levels of dichromatism. We estimated Z-linked and autosomal genetic diversity for these non-model avian species using restriction-site associated (RAD) loci that covered ~3 % of the genome. We find that monochromatic birds consistently have reduced sex-linked genomic variation relative to phylogenetically-paired dichromatic species and this pattern is robust to mutational biases.Our results are consistent with several interpretations. If present-day sexual selection is stronger in dichromatic birds, our results suggest that its impact on sex-linked genomic variation is offset by other processes that lead to proportionately lower Z-linked variation in monochromatic species. We discuss possible factors that may contribute to this discrepancy between phenotypes and genomic variation. Conversely, it is possible that present-day sexual selection -- as measured by the variance in male reproductive success -- is stronger in the set of monochromatic taxa we have examined, potentially reflecting the importance of song, behavior and other non-plumage associated traits as targets of sexual selection. This counterintuitive finding suggests that the relationship between genomic variation and sexual selection is complex and highlights the need for a more comprehensive survey of genomic variation in avian taxa that vary markedly in social and genetic mating systems.The online version of this article (doi:10.1186/s12862-015-0480-4) contains supplementary material, which is available to authorized users. Biologists have generally assumed that sexual selection drives the evolution of sexual dimorphism, as proposed by Darwin  and it iWhile there is now extensive evidence that plumage-associated traits are the targets of sexual selection, the general assumption that species with greater intersexual plumage differences experience stronger sexual selection remains largely untested. The fact that many highly dichromatic bird species are socially monogamous and the existence of widespread extra-pair paternity  suggestsRZ:A), which can be calculated from neutral genetic diversity estimates . That is, if dichromatic species are experiencing stronger sexual selection, their RZ:A should be lower compared to monochromatic species.One direct measurement of sexual selection that is comparable between species is the variance in reproductive success among the sex with lower parental investment in offspring –15. WhilRZ:A using restriction-site associated DNA RAD; [RZ:A and plumage dichromatism across a set of phylogenetically-paired species of North American birds.We developed an approach to estimate DNA RAD;  markers DNA RAD; , 21. We Agelaius phoeniceus), Eastern Bluebird , and Eastern Meadowlark (Sturnella magna). After filtering and quality controls  might increase simply because of elevated mutation rates for Z-linked loci . This is a potential problem for our test, as the difference between species in RZ:A might reflect the difference in mutation rates rather than the effective sizes of breeding population. To correct for this potential male mutational bias, we estimated RZ:A as the ratio of effective population size (NZ/NA), which is the ratio of genetic diversity (θZ/θA) divided by the ratio of mutation rate (μZ/μA). We estimated the substitution rates (μ) from the divergence between RAD sequences and zebra finch genomes. As expected, we observed male mutation biases as previous studies—the substitution rate is 1.13 times higher for Z-linked loci estimates are 1.08 and 1.10 from [μ), and the overall pattern does not change , genetic diversity on the Z chromosome . In addition, we multiplexed samples for Illumina sequencing so that RAD loci only covered ~3.3 % of the genome for each individual. Thus, while our study included substantially more data than would have been possible using Sanger sequencing, we nonetheless examined a relatively small fraction of the genome of each species.Earlier theoretical work has proven the feasibility of accurately estimating genetic diversity with single individuals , 21. SevRZ:A estimates, we extended the maximum likelihood method in Lynch et al. [RZ:A estimates are robust to variety of data filtering criterions . Our use of a distantly related reference genome for linkage assignment is another potential issue leading to underestimated genetic diversity, because more variable RAD markers might be lost during linkage assignment. This problem is not specific to RAD sequencing but would also pertain to Sanger sequencing, which would tend to select for loci that are conserved enough to be amplified across species. However, it would equally affect the RZ:A estimates of a species pair given that both taxa are equally divergent from the zebra finches. Hence, estimation biases might exist, but is unlikely to contribute to the RZ:A difference between matching species pairs.One caveat with RAD sequencing that cannot be resolved with increased data quantity is allele dropout — mutations at enzyme cutting sites can result in underestimates of genetic diversity, and this problem is exacerbated as genetic diversity increases . In thisRZ:A estimates lower than the theoretical minimal of 9/16. This ratio arises as the limiting value of the breeding ratio for a polygynous system where a single male has access to a female breeding population of infinite size [RZ:A estimates than those we report here 0.20-0.36; [per se is not the only process that can deplete Z-linked genetic diversity in these species.Due to the unique mode of inheritance of sex chromosomes, many processes  affect sex-linked genetic diversity disproportionally. The default prediction is that the level of genetic diversity on Z or X chromosome should be 75 % of that on autosomes, but it is very difficult to pinpoint the exact cause for deviations in empirical studies because of confounding genetic processes e.g., , 31. Sevite size . Other s20-0.36; –36. ThisSelection is a process that can affect genetic diversity. Because RAD data are drawn from coding and non-coding regions alike, we could not assess the effects of selection . However, our dataset is composed of ~480,000 RAD loci per individual, anonymously selected by restriction enzymes and more or less evenly distributed across the genome , while population size increase leads to a more equal genetic diversity . One drawback of estimating RZ:A from one individual is that the effect of demographic history cannot be quantified without a recombination map. However, we obtained highly correlated RZ:A estimates among individuals from widely-separated geographic localities  and Black-throated Blue Warbler (Dendroica caerulescens)—both have samples from the state of New York and Michigan. There is a possibility that these species pairs chosen specifically for contrasting level of dichromatism somehow were also on contrasting trajectories in terms of past demographic history, and it would be an interesting hypothesis to test for future studies. Related to population demography, population structure is another factor that can influence Rz:A. For birds, female-biased dispersal is a common pattern [RZ:A as the genetic diversity of the Z chromosome would decrease more due to local inbreeding than that of the autosomes [Demographic history can differentially affect genetic diversity on the sex chromosomes and autosomes. In Pool and Nielsen , coalesc pattern , which cutosomes . How dicRz:A is negatively associated with dichromatism seems to be at odds with the current understanding of this trait. Among the eight dichromatic species in this study, the red-and-yellow shoulder badge (“epaulet”) on red-winged blackbirds is considered to have an important role in maintaining male territories, the quality of which is selected by females [Rz:A and dichromatism level, but cannot explain why we observe a significant negative correlation . These  females , 51, and females . ResultsθZ = 4NZμZ). Limited evidence suggests a correlation between plumage dimorphism and testis mass [RZ:A would become higher in dimorphic species with respect to the monomorphic species because of elevated substitution rates on Z chromosome. A faster-Z effect, in which the Z chromosome has elevated rates of substitution or a higher proportion of nonsynonymous changes, is often detected in studies of bird genome evolution e.g., [μZ/μA) is not a perfect method to correct for male mutation bias, but the pattern we observed is unlikely to be driven by male mutation bias.One possible explanation involves differential mutation rates, which could directly affect genetic diversity . Nevertheless, they suggest a possible mechanism: if ongoing natural selection is stronger for females in dichromatic species  resulting in fewer females in the breeding population, the species’ RZ:A would become higher than monochromatic species. However, this mechanism is not supported by studies on mortality rate, arguably the most salient outcome of natural selection. Studies have revealed that mortality is positively correlated with plumage brightness [Rz:A for dichromatic species. Admittedly, these two studies presented very weak, indirect evidences against present natural selection on female plumage as a possible mechanism, and more studies comparing the strength of natural selection across species using other outcomes  would be informative.Natural selection is another process that has long been proposed to associate with dichromatism in birds . In factightness , and thaightness . If thesSeveral life history traits have been shown to correlate with plumage dimorphism. The association between social mating system and dichromatism has been examined by many studies e.g., , 9, and RZ:A) for non-model avian species. We used this framework to test the association between sex-linked genomic variation and avian plumage dichromatism, a widely used surrogate for sexual selection. We documented an intriguing pattern of reduced RZ:A ratios in monochromatic species relative to phylogenetically-matched dichromatic species. If the patterns reported here are caused by reduced or even similar levels of sexual selection in dichromatic species, and if these results are generalizable to other avian taxa, then our results have broad implications for the comparative study of speciation rates in relation to sexual selection in birds. We are presently unable to explain this pattern, but we predict that the solution to the paradox lies in understanding the potentially complex tradeoffs between dichromatism and a host of ecological or life-history traits [Here, we developed a RAD-based approach to estimate neutral genetic diversity on sex chromosomes in relation to that on autosomes  according to museum records so that individual estimates of Z-chromosome genetic diversity could be obtained. As the first application of our approach, we focused on species with multiple samples from widely-separated geographic locations so that we can assess both the intra- and inter-species differences of RZ:A estimates. Eight pairs of species from seven different families , CUMV (Cornell University-Museum of Vertebrates) and MVZ (The Museum of Vertebrate Zoology at Berkeley). Our RAD-based approach estimates an PstI and MseI restriction enzymes. Digested fragments were barcoded and size-selected (150-250 bp) to generate a multiplexed Double Digested RADseq library [Genomic DNA of 41 selected tissue samples  was first used to confirm that the individual was the homogametic sex using DNA-based sex identification methods , 64, and library . SamplesAfter illumina sequencing, the raw data was de-multiplexed into individual datasets according to the barcodes. Analyses were the performed on each individual dataset separately, unless otherwise noted. Here, we briefly explain the basic approach, while the detailed steps, parameter settings and statistics are reported in the Additional file de novo assembly methods were used to identify putative RAD loci. The consensus sequences of de novo RAD loci were blasted against the Zebra Finch genome WUSTL v3.2.4 assembly [θZ and θA; where θ = 4Nμ; N is the effective population size and μ is the substitution rate) were co-estimated with the sequencing error rate using an extension of the maximum likelihood (ML) method in [θ and the sequencing error rate were jointly estimated across all loci; here we put in two parameters for θ— θZ and θA – according to the genomic locations of RAD loci, and jointly estimated the three parameters. We further applied several data filtering criterions to assess the robustness the estimates of the genetic diversity ratio (θZ/θA) are to assembling and mapping errors  for the RAD loci in two ways. The first approach is based on individual datasets. We calculated the substitution rates from the percentage of fixed differences between individual’s RAD loci and the reference genome. These individual estimates of substitution-rate ratio were used to correct the individual RZ:A estimates . Because we chose matched pairs of dichromatic and monochromatic species  while allowing different baseline RZ:A for different species pairs (βp), and accounting for the fact that individual estimates of the same species are not independent  using likelihood ratio test could assess whether the effect of dichromatism is significant . This mix-effect model was also used for testing whether species differ in substitution rate (μ) and ratio (μz/μA).This model estimates the effect of dichromatism . We estimated the amount of phylogenetic signal using Pagel’s λ [Lastly, we also used phylogenetic generalized least squares (PGLS) analysis  to expliagel’s λ , while fagel’s λ  in R [71agel’s λ .Additional Methods could be found in the Additional file


Vipera magnifica and Vipera orlovi are small vipers that have high conservation status due to their rarity and restricted distributions in an area of the Caucasus region where two other related species are present – V. kaznakovi and V. renardi. Despite numerous observations of hybridization between different species of small vipers, and the potential of a hybrid origin for V. magnifica and V. orlovi based on their distribution with respect to V. kaznakovi and V. renardi, hypotheses of a hybrid origin have not been formally tested. Here we generate genomic-scale data by performing next generation sequencing of double digest restriction-site associated DNA libraries, and use these multilocus data to test whether these two species are of hybrid origin.Studying patterns of introgression can illuminate the role of hybridization in speciation, and help guide decisions relevant to the conservation of rare taxa. V. renardi into V. kaznakovi. The average admixture proportion in individuals was low (6.39 %) in the case of V. magnifica, but was higher in V. orlovi (19.02 %). We also show that the specific individual samples used in D-statistic tests can have a significant impact on inferences regarding the magnitude of introgression, suggesting the importance of including multiple individuals in these analyses.We generated over nine hundred loci for 38 specimens of six taxa, and analysed the dataset using Bayesian clustering and multivariate methods, as well as Patterson D-statistics, which can distinguish between incomplete lineage sorting and introgression as explanations for shared polymorphism. The results demonstrate a pattern of historical admixture in the two purported hybrids that is consistent with past gene flow from V. orlovi and V. magnifica had formed through a hybridization event between V. kaznakovi and V. renardi. Given a low proportion of admixture and absence of clear ecological and morphological differences V. magnifica should be treated as a marginal population of V. kaznakovi. Further studies that include analyses of ecological segregation of V. orlovi from parental taxa and search for evolutionary consequences of hybridisation would clarify if V. orlovi is a distinct hybrid species. Until this we recommend preserving the current taxonomy and protection status of V. orlovi.Our results support the conclusion that both The online version of this article (doi:10.1186/s12862-016-0647-7) contains supplementary material, which is available to authorized users. Hybridization is increasingly recognized as an important evolutionary process that can have diverse outcomes with respect to biodiversity. For example, gene introgression can act to increase diversity by rapidly generating novel genetic variation upon which selection can act, potentially leading to speciation , 2. In cVipera in both nature and captivity, and may be especially common in the subgenus Pelias, a monophyletic group that consists of approximately 20 species of small venomous snakes found in the temperate zone of Eurasia [Pelias have been reported in a number of studies including those based on karyotype, osteological, and molecular methods [Vipera kaznakovi Nikolsky, 1909, V. darevskii Vedmederja, Orlov and Tuniyev, 1986, V. dinniki Nikolsky, 1913 and V. eriwanensis (Reuss 1933)), but as yet no direct evidence beyond similarities in external morphology has been provided [In snakes, there are increased observations of hybridization between species in phylogenetically-distinct groups –11. Hybr Eurasia . Hybridsprovided .V. renardi (Christoph 1861) and V. kaznakovi are two widely accepted complexes of viper species that have distributions that meet along the northern slope of the Caucasus [V. kaznakovi complex are endemic to the Caucasian region and are found in two different habitat types: forests of the northwestern and southern slopes of the Caucasus and high altitude open meadows of alpine zones. Snakes of the V. renardi complex consist of several taxa living in lowland or dry mountain grasslands which have expanded their range in Northern Caucasus through natural or artificial corridors resulting in a zone of contact between these two groups.Caucasus –29. SnakV. orlovi Tuniyev et Ostrovskikh, 2001 and V. magnifica Tuniyev et Ostrovskikh, 2001 were recently described on the basis of morphological differences and are considered part of the V. kaznakovi group [V. kaznakovi and V. renardi. In addition, mitochondrial DNA haplotypes from V. magnifica and V. orlovi are shared with V. kaznakovi [vi group . Both spaznakovi , furtherUnderstanding the evolutionary origin of these species would help to understand the role that interspecific gene flow may play in the process of radiation and local adaptation in vipers. In addition, since both species are included on the IUCN list of threatened species and are locally protected –33, clarde novo development for use in non-model species [Genetic markers traditionally used to assess hybridization between species  assay variation at few positions in the genome, can show limited levels of informative variation, and may require  species –37. The  species . This ha species . This ty species –44.Along with advances in methodologies for generating data have come novel analytical techniques that take advantage of genomic-scale datasets. These have great potential for studies of introgression because they provide the ability to distinguish between introgression and ancestral polymorphism, which is a significant issue when evaluating potential hybridization between closely related taxa. One example is Patterson’s D-statistic, which was first developed and applied to detect hybridization between different Hominid lineages based on genomic data , 46. ThiV. magnifica and V. orlovi. We assess these questions by 1) evaluating patterns of genetic structure among these groups using genetic clustering methods, and 2) testing for patterns of genetic introgression among the groups using ABBA/BABA tests and associated Patterson D-statistics. Our results support the hypothesis that these two groups arose through hybridization between the steppe viper V. renardi and the Caucasian viper V. kaznakovi. We discuss the results as they relate to the evolutionary history of these snakes and also in the context of their relevance to the conservation of these species.In this paper, we use the modification of RADSeq data – ddRAD (double digest restriction-site associated DNA) to investigate the evolutionary origin of the purported hybrid taxa 6 reads were obtained for the 38 individuals sequenced. Analyses with and without the Outgroup samples resulted in the identification of 3651 and 1959 polymorphic loci, respectively. Of the 3651 polymorphic loci obtained when outgroup samples were included, 977 were genotyped in all of the samples, and were used for analyses.Approximately 3.3 x 10V. renardi is characterized by the lowest allelic richness but the highest number of private alleles. At the same time, it is the only group with observed overall heterozygosity that is lower than expected. Both V. magnifica and V. orlovi have relatively low numbers of private alleles, but observed heterozygosity that is higher than expected when compared to V. kaznakovi and V. renardi. Finally both observed heterozygosity and allelic richness are highest in V. orlovi.The four taxa of vipers analysed in this study show slightly different patterns of genetic variation at RAD loci Table . V. renaV. kaznakovi, V. magnifica and V. orlovi are equally distinct from each other with Fst values close to 0.2, whereas V. renardi is much more distinct from all three of the other taxa .Fst values were significantly greater then zero for all pair-wise comparisons of taxa Table . Pairs wV. kaznakovi and V. renardi showed that the equivalent of genome average ancestry q [V. magnifica (7.5–7.9 %) and higher in V. orlovi . Values of inter-source population ancestry Q12 [A restricted dataset of 133 biallelic loci fixed between samples of cestry q  was lowestry Q12 , which iV. berus  and V. seoanei Lataste, 1879 placed in the outgroup position  showed evidence of relatively small but significant admixture of V. renardi genes into a genetic background largely characteristic of V. kaznakovi. Specifically, the proportion of genes characteristic of V. renardi in V. orlovi and V. magnifica ranged from 0.1–10.1, and the 95 % credible regions for the proportion of V. renardi-type genes did not overlap zero in nine out of twelve V. orlovi samples  of V. kaznakovi genes, but the 95 % confidence interval for admixture overlapped zero in all but one of these samples. In contrast, no V. renardi samples from the populations from Elbrus Mountain in Central Caucasus or Crimea had any traces of admixture.Interestingly, six out of seven V. renardi, ii) V. kaznakovi + V. magnifica and iii) V. orlovi. V. orlovi was positioned close to the V. kaznakovi + V. magnifica group along the first two discriminant functions (DF), but was shifted towards V. renardi along the axis of the first DF  of this distance. The distance between V. orlovi and V. kaznakovi along the axis of the second DF demonstrates the presence of differentiation between these two groups. However the much lower eigenvalues of the second DF (F-statistics 1680 versus 64600) shows that magnitude of this differentiation is much lower.Discriminant Analysis of Principal Components (DAPC) analysis was performed on the first eleven principal components, which accounted for 69 % of the total genetic variation. Bayesian Information Criteria (BIC) suggested that these data are best partitioned into three clusters which consisted of i)  DF Fig. . If we mV. kaznakovi and V. renardi representing pure parental taxa, but these analyses did not recognize differentiation of V. magnifica and V. orlovi at a comparable level. Both of these putative hybrid groups appear to be genetically most similar to V. kaznakovi, but also exhibit patterns consistent with introgression of genes from V. renardi.In summary, results from both clustering algorithms are consistent with V. magnifica and 0.50 for V. orlovi, supporting the hypothesis of introgression for each taxon (Table f) were 6.39 and 19.02 % for V. magnifica and V. orlovi, respectively  produced D-statistic values close to zero on average , while those representing maximal gene flow (V. renardi as P2), produced high mean D-statistic values , and the range of D-statistics from resampled datasets did not include zero for either group , though the overall magnitude of the mean differences was generally low and did not exceed 0.03 for the Outgroup specimens, and 0.09 and 0.08 for P1 and P3 samples, respectively. However, two notable outliers were V. kaznakovi individuals Kaz17 and Kaz3 in the P1 group, which increase this difference to 0.2939 and 0.1775, respectively, demonstrating that specimen choice can have substantial effects on the signal of introgression.To evaluate the effect that variation among samples representing the P1, P3, and the Outgroup taxa may have on D-statistics, we tested for bias in D-statistics associated with including individual samples in P1, P3, and the Outgroup taxa. Specifically, we obtained D-statistics for all runs that contained a given sample in one of these groups. We then tested whether any of the samples representing P1, P3, or the Outgroup samples were associated with biased D-statistics. The choice of individual in each reference group  had a significant effect on D  alleles between the two parental species all support the hypothesis that genetic introgression has influenced the evolution of the currently-described viper species a priori hypotheses about patterns of hybridization.Previous studies have demonstrated how clustering methods and more direct approaches such as ABBA/BABA tests can complement each other in testing for historical introgression i.e. . For exaOne drawback to ABBA/BABA tests is that nucleotide site patterns useful for this test are uncommon in the genome, and even with genomic-scale SNP data, the number of ABBA/BABA sites for a test can be limited. In these cases, statistical power for inferring historical introgression on a sample-by-sample basis can be low (often measured with Z-statistics that are based on bootstrap resampling of loci). In previous studies, when the number of sites was sufficient, the authors did not include sites which were heterozygous . In contV. kaznakovi samples were included as the P1 taxon, the average D-statistics over all P2 samples analyzed were biased as compared to all of the remaining P1, P3, and the Outgroup sample combinations. The specific reason for this bias is not clear, but it could be due to the use of introgressed specimens or geographically isolated subpopulations of V. kaznakovi themselves. For example, sample Kaz17, when tested as a possible hybrid (assigned as the P2 taxon in the ABBA/BABA test) has a mean D higher than V. magnifica (0.35 ± 0.24)  in Southern Europe [V. berus s. l. and V. renardi in Eastern Europe [V. dinniki and V. lotievi Nilson et al. 1995 in Northern Caucasus [V. darevskii and V. eriwanensis in Transcaucasia [V. ammodytes , V. aspis  and V. berus in Slovenia [V. aspis, V. latasteiBoscá, 1878, and the more distantly related V. seoanei in Spain [Most species of small vipers have allopatric distributions, and species complexes are ecologically linked to different habitat types, which together with geographic isolation lead to the development of reproductive barriers between species , 32, 33.n Europe , V. beruCaucasus , V. darecaucasia , and V. Slovenia . The conin Spain , where tin Spain .V. orlovi covers a considerable geographic range, no migrants representing pure parental species were found in sympatry with the hybrids, and are unlikely to be present due to the size of the range of V. orlovi compared to the activity range of individual snakes in vipers. In addition to this, several lines of genetic evidence argue against the occurrence of ongoing gene flow. For example, there was no pronounced clinal variation in the admixture proportion across V. orlovi localities, and also no evidence of a hybrid swarm in either V. orlovi or V. magnifica , resulting in hybridization, and/or may have established novel niches where hybrid specimens are more fit compared to parental individuals [In contrast to ongoing hybridization, these data broadly point to historical hybridization and introgression as factors in the evolution of ructions  indicateividuals .V. renardi that was associated with increases in secondary open grasslands (pastures) after anthropogenic deforestation of edge territories along the range of V. kaznakovi. Consequently, after the displacement and expulsion of local Circassians (Adygs) by the Russian Empire in 1864 [V. renardi and V. kaznakovi. Indeed, the habitat occupied by V. orlovi and V. magnifica in the northwestern Caucasus is a mosaic of drier sub-Mediterranean xerophyte forests, meadows, and mountain steppes that has experienced significant anthropogenic impacts, and has undergone succession after a change in the prevailing type of human activity over the past two centuries [Though it appears to have happened in the past, the specific timescale for the hybridization is not clear from the data presented here. The earliest time at which hybridization likely could have occurred coincides with the time when steppe vipers first colonized the Northern Caucasus region, which was recently estimated at approximately 380,000 ybp . Neverth in 1864 , forests in 1864 , which menturies . TendencV. orlovi which has originated through hybridization may possess a specific combination of parental genetic features that make it more fit in the particular environmental conditions. If this assumption is confirmed by additional ecological data and evidence of non-random introgression and fixation of adaptive alleles , V. orlV. orlovi is a critically endangered species according to the IUCN classification [V. magnifica is listed as an endangered species [V. orlovi and V. magnifica may be listed as regional populations within V. kaznakovi, with which they share the most genetic material and contain a considerable part of the genetic diversity of this species [V. orlovi, it should be protected; this would mean that it may be recognized as a taxon of hybrid origin and that the official recommendations of The International Code of Zoological Nomenclature regarding hybrids must be changed, as well as the more general view of species as monophyletic groups in animals. However, V. magnifica has a more restricted distribution, a marginal signal of admixture, and non-distinct habitat differences, making this taxon equivalent to isolated V. kaznakovi populations, and so we believe it therefore should be synonymised with the latter.fication  and V. m species , with bo species . In turn species , 60. At  species . If we fV. kaznakovi and V. renardi contributed to genetic diversity that currently characterizes V. orlovi, which occurs in an intermediate habitat type relative to the two parental species. Contact zones between grasslands, which are typical habitats of V. renardi, and humid forest, which are typical habitats of V. kaznakovi, and/or human-mediated environmental disturbance, may have facilitated the formation of this hybrid group. Relative to V. orlovi, a smaller amount of introgression was detected in V. magnifica. Given this result, and an absence of ecological specialization associated with V. magnifica, we suggest that from both a taxonomic and conservation perspective it may best be treated as a marginal population of V. kaznakovi.According to our results, a hybridization event between We sampled tissues from ethanol-preserved museum collection or dry shed skin obtained from alive snakes after shedding in a research collection of Tula Exotarium  were assigned to taxa based on previously described species ranges, as reliable diagnostic morphological characters are not available [V. kaznakovi samples (N = 8) were from low-altitude forest habitats in northwestern Caucasus just to the southeast of the range of V. orlovi  came from south of the type locality, within the area of the Western Caucasus occupied by V. orlovi according to the original description [V. magnifica (N = 2) belong to the type series (holotype and paratype) from the Sochi National Park Museum collection.Samples within the vailable . V. kaznovi Fig. . Specimecription . SpecimeV. renardi s. l., including V. lotievi sensu Tuniyev et al. [V. kaznakovi complex, as it typically has one apical shield and a sharp snout [V. renardi samples (N = 13) were collected from populations in Southern Russia and Ukraine, including five specimens of V. lotievi from Elbrus Mountain in Central Caucasus and one specimen from Dagestan in Eastern Caucasus  and V. seoanei , which occur in a clade sister to the clade containing V. renardi and V. kaznakovi [v et al. , could brp snout . V. renasus Fig. . Samplesaznakovi , 28, werDNA was extracted from blood, scale clips, shed skin, or ethanol fixed tissue using DNeasy Blood & Tissue Kits (Qiagen). DNA concentrations were measured on a Qubit 2.0 fluorometer (Invitrogen) and adjusted to a working concentration of 15 ng/uL.Double-digest RADSeq libraries were generated with the protocol described in Sovic et al. . BrieflyBasic genetic statistics and pairwise Fst values was calculated using GENEPOP and Arelquin software , 65.V. kaznakovi and V. renardi. The admixture proportion q (similar to those obtained in STRUCTURE) was directly calculated from these allele frequencies in each individual. Knowing the admixture proportion q we can calculate the proportion of heterozygous loci . The maWe constructed a Maximum Likelihood phylogenetic tree using RAxML v 8.2.4  using alV. lotievi from Dagestan because the entire separate clade of V. lotievi from Dagestan [Genetic clustering was performed on 34 samples  was identified using Structure Harvester . No prioFor DAPC runs, the number of retained principal components was chosen based on the cumulative variance explained. The optimal number of clusters was then identified using Bayesian information criteria .A weakness of clustering approaches in hybridization studies is that they do not account for incomplete lineage sorting (ILS) as a cause of similarity between groups. Therefore we also applied the Patterson D-statistic (ABBA/BABA) test  to more V. kaznakovi and V. renardi as the P1 and P3 groups, respectively, and tested for evidence of gene flow from V. renardi into each of the purported hybrid groups, V. orlovi and V. magnifica  and maximum (V. renardi) levels of introgression. The tests in which V. renardi was included as the P2 group were also used to obtain the maximum potential number of introgressed sites for calculations of conservative minimum estimates of the admixture proportion f for V. magnifica and V. orlovi, according to equation 8 of Durand et al. [We assigned P2, Fig. . We alsod et al. .f statistics were obtained for each sample as the average over all runs for which the specific sample was included as the P2 taxon. This approach utilizes all of the information in the data, in contrast to previous treatments, which have either excluded all heterozygous loci from the analyses [f statistics were then averaged over all samples representing each P2 taxon or for each individual to draw inference regarding the occurrence of introgression, and to estimate admixture proportion. We used combination of dstat.R script (https://gist.github.com/coleoguy/6886683) modified by us and two Perl scripts to automate the process of generation of alignments from individual sequences and calculation of D statistic for each of these alignments.Because we had multiple samples representing each of our taxa, we explored the impact that individual variation had on values of D by generating D-statistics for all possible combinations of individuals representing the P1, P3, and Outgroup taxa for each P2 sample tested. Each combination was run twice to account for both alleles in the diploid samples. Mean D and analyses  or randoanalyses . The meaThe D statistic was also calculated from population allele frequencies according to Equation 2 in Durand et al . The derRaw Illumina reads of ddRAD libraries, barcode information and scripts to calculate individual and population D statistic are available from the Dryad Digital Repository: doi:10.5061/dryad.c5232.Not applicable.Not applicable.


Labeo rohita) originated from three major rivers—the Jamuna, the Padma and the Halda. A total of 28 alleles were detected in 90 individuals with an average of 4.6 alleles per locus. The average observed heterozygosity ranged from 0.655 to 0.705 and the expected heterozygosity ranged from 0.702 to 0.725. The mean FIS values were 0.103, 0.106 and 0.018 for the Jamuna, Padma and Halda fishes respectively. The population pair-wise FST values ranged from 0.0057 to 0.0278. Structure analysis grouped the fishes of the three rivers into two clusters. The numbers of half-sib families were 5, 5 and 4 and the numbers of full-sib families were 12, 10 and 18 for the Halda, Jamuna and the Padma samples respectively. Bottleneck was detected in all the river samples. We recommend to collect more fish from different locations of the major rivers to broaden the genetic variability of the founder stocks of the Brood bank.The founder stock of a captive breeding program is prone to changes in genetic structure due to inbreeding and genetic drift. Genetic characterization of the founder population using suitable molecular markers may help monitor periodic changes in the genetic structure in future. To develop benchmark information about the genetic structure we analyzed six microsatellite loci in the Brodbank collections of rohu ( Labeo rohita (Hamilton), a member of the Indian major carps group of the family Cyprinidae is naturally distributed in the rivers of Bangladesh, India, Pakistan and Myanmar , along with the surface feeder catla, Catla catla (Hamilton) and bottom feeder mrigal, Cirrhinus cirrhosus (Hamilton) constitutes an important and popular aquaculture practice in the region named carp polyculture system. L. rohita is the highest contributing single species in aquaculture production of Bangladesh sharing 22.0 % of the country’s pond production , Government of Bangladesh initiated a Brood Bank Establishment project for the three Indian major carps species in 2008. The objective of the project is to ensure supply of good quality juvenile brood to the hatcheries to develop broodstock. The founder stocks of the broodbank were developed by collecting spawn of L. rohita  (n = 500), the Padma stock was maintained in Rajshahi Farm (n = 500) and the Halda stock was maintained Jangalia Farm (Comilla) (n = 400). A small clip from the caudal fin of 30 randomly selected fish of each of the three river sources was collected and immediately preserved in 95 % ethanol until used for isolation of genomic DNA.We collected We extracted genomic DNA using the standard proteinase-K digestion, phenol: chloroform: isoamyl alcohol extraction and alcohol precipitation method as described in Islam and Alam . DNA quaLr1, Lr3, Lr6, Lr12, Lr14b and Lr21) developed from L. rohita by Das et al.  with the following temperature profile: 3 min initial denaturation at 94 °C followed by 35 cycles, each of 30 s at 94 °C, 30 s at respective annealing temperature and 1 min at 72 °C. Finally, an additional one cycle of 7 min at 72 °C was added to allow complete elongation of the amplified products. For genotyping, the PCR products were separated on 6 % denaturing polyacrylamide gel containing 19:1 acrylamide:bis-acrylamide and 6 M urea using a Sequi Gen GT sequencing electrophoresis system  and visualized by staining with silver nitrate following the Promega  protocol. The stained gel plates were scanned and saved in GPEG format and the bands representing particular alleles at the microsatellite loci were scored based on the sizes estimated by the AlphaEase FC, 1D gel image analysis software.For genetic diversity analysis, we used six pairs of microsatellite primers , observed heterozygosity (Ho) and expected heterozygosity (He)  was subjected to sequential Bonferroni corrections  Nei  at each (He) Nei . The exaons Rice .For inferring the number of sub-populations, the software STRUCTUE 2.3.2  to six (Lr1 and Lr21) with an average of 4.66 alleles per locus (Table P95) and the polymorphic information contents ranged from 0.646 to 0.808.A total of 28 alleles were detected at six microsatellite loci in the three rohu populations. Examination of genotyping errors using MicroChecker revealed no evidence for null alleles and large allele dropout or stutter-band scoring at any of the six loci. The number of alleles ranged from three Lr4b to sixHo) ranged from 0.500 to 0.833 and the expected heterozygosity (He) ranged from 0.598 to 0.808  were detected in 11 of the 18 tests (Table The observed heterozygosity (08 Table . The aveFST) value between the Padma and the Halda population was the highest (0.0278) and that between the Halda and the Jamuna population was the lowest (0.0057) . The Nei’s . The mean estimated log-likelihood value was found to be the highest for k = 2  while the Wilcoxon sign rank test and the mode-shift test detected recent bottlenecks in all populations under the three mutation models (P < 0.01667) Table .Table 3RWe reconstructed full-sib and half-sib families using Wang’s  method wEstablishing a brood bank for aquaculture species may serve two purposes: preserving the genetic variation of the population by maintaining a large random mating population and supporting genetic improvement programs for important production traits. Maintaining genetic variation is very important because the potentials for genetic improvement and fitness of a population are dependent on the existence of genetic variation. Genetic characterization of the founder population would allow monitoring of the brood bank stocks in future to assess the impact of captive breeding on the genetic structure.L. rohita of the Brood bank stocks collected from three major rivers- the Halda, the Jamuna, and the Padma. The six markers were found to be highly informative as the PICs were >0.500  values were higher than the respective heterozygosity (He) values expected from observed number of alleles at 50.00 % of the loci in the populations indicating the probability of recent severe reduction in effective population size, a phenomenon popularly termed as genetic bottleneck. The tests for genetic bottlenecks under the assumption of mutation drift equilibrium though not conclusive revealed signs of decline of the individuals in all the populations of L. rohita. Bottlenecks were also detected in populations of the other three major carps species Catla catla  should be at least 344 and for five generations, the Ne should be at least 309 (Tave Inbreeding and genetic drift are two major consequences that may deteriorate the genetic quality of a captive population maintained in a hatchery or a brood bank. No inbreeding was detected in the brood bank stocks of 309 Tave .Catla catla.According to Hansen and Jensen , the famL. rohita broodbank originated from three major river sources. These three rivers are considered the principal sources of the Indian major carps. So, the samples are representative of the species from Bangladesh. We have detected genetic bottlenecks in all three river samples of the broodbank collections meaning that the populations apparently have experienced drastic reduction in the recent past. The numbers of families in the sample of all three river were also low indicating a close relationship among the individuals which is not positive for a founder stock. Therefore, it is recommended to collect new batches of fish from various locations of the respective rivers that may broaden the genetic variability of the base population of the brood bank. As some negative points have been exposed from this study, it is strongly recommended to analyze at least 100 fish from each of the rivers with fifteen microsatellite DNA markers to obtain more precise information on genetic status of the brood bank stocks of L. rohita. This genetic data would serve as baseline information of the brood bank collections and enable efficient monitoring of the impact of natural and/or human interferences on the river populations of L. rohita in future.In conclusion, we have characterized the population genetic structure of the founder stocks of


Structure and the Genome of the Netherlands project, I will argue that bioinformatics and its tools can be understood as ‘infrastructure’ as described by Bowker and Star. A number of value decisions are involved in the development of such tools. However, once the tools are ready for use, these values tend to blend into the background of the research. This may lead to the ‘naturalisation’ and ‘essentialisation’ of value-imbued aspects of population identities such as nationality, ethnicity and race.In the life sciences, where large data sets are increasingly setting the stage for research, the role of bioinformatics is expanding. This has far-reaching consequences, not only for the way research is done, but also for the way this research affects our understanding of human identity. Using two case studies of practices involving bioinformatics, the software program  Bioinformatics is a core discipline of the life sciences in general and of genomics in particular. Regardless of whether it is seen as ‘just’ a toolset or as a driving force for research, in view of the increasing complexity of the research of molecular connections, the role of bioinformatics as a technology and as a discipline is clearly intensifying.As Rose  has argupractices by which this knowledge is produced, looking at how certain specific population identities are shaped or ‘enacted’1.Zwart  has argu‘Population identities’ refers to those elements of individual identity that are based on membership of a group that lays claim to a shared origin.In genetics discourses this shared origin is enacted as a genetic connection between humans and our ancestors, human as well as non-human. In population genetics, a genetic connection is made between current human inhabitants of certain locations, whose ancestors are presumed to have lived there as well (indigenous populations), and humans who might share this ancestry but live elsewhere. In this way the latter’s connection to this place is thus enacted as ‘origin’.In this paper I will analyse the role of bioinformatics in the enactment of these origins. More specifically, I will argue that specific enactments of population identities as genetic categories are materially embedded in bioinformatics tools. When these tools become part of the infrastructure, they tend to blend into the background, including the values (in this case population identities) that they incorporate. This often results in the naturalisation of these incorporated values, that is, they are taken for granted and no longer questioned  sciences internally M’charek  and in tTo address this issue, I have made use of three sources of information. First, I took part in a number of activities where bioinformatics is practised: two courses in applied bioinformatics (as a student) and three bioinformatics conferences . While functioning mainly as a background for my analysis, this source of information has been vital for writing the paper. It shaped my view of, and familiarity with, bioinformatics in terms of the technical aspects of the field as well as current developments and discussions.2 with researchers working in the field of bioinformatics or in close collaboration with it. To be precise: six interviews were conducted with bioinformatics researchers, one with a population geneticist and one with a human geneticist. Rather than asking them directly about the role of bioinformatics in shaping identity, I asked the interviewees to describe what they do as a researcher, taking the interview from there.Second, I conducted a series of interviewsThird, to substantiate the analysis, I analysed a selection of published materials such as scientific publications, project websites and published interviews related to the case studies.Two central concepts deserve further explanation: ‘enactment’ and ‘naturalisation’.practices they are part of  representations, but as part of specific practices, that can thus also be arranged differently. That is not to say that questions of technical and biological validity are not important in discussing issues of population identities, but these are not the questions that I aim to address in this paper.Using the concept of enactment also enables me to look at the connections between population identities as enacted in bioinformatics and genomics, and enactments of population identities in different practices. While these enactments are necessarily different since they are an integral part of the practices in which they occur, they are still connected in different ways as part of a phenomenon Mol .Naturalisation, as theorised by several authors  and that they are thus totally independent from each other for the frequency with which they occur  can either be used to improve accuracy at assigning individuals to populations, or can be left out to improve validity. In the case of using the information, it is assumed that sampling location is usually connected to population membership, detecting immigrants through that assumption. It is suggested however, that data should at first be clustered These assumptions are the choices forming the base for the algorithm. For the algorithm to work, the ‘reality’ it ‘represents’ needs to be subjected to certain assumptions that serve to reconcile mathematical and material reality. This means that not only mathematical considerations find their way into the algorithm through these assumptions, but also included is the way the authors perceive the material reality that they are trying to model.Structure: ‘[I]t may be difficult to know whether a given assignment of individuals to populations based on these subjective criteria represents a natural assignment in genetic terms, and it would be useful to be able to confirm that subjective classifications are consistent with genetic information and hence appropriate for studying the questions of interest.’  from the Human Genome Diversity Project (HGDP) was used, containing so called ‘microsatellite loci’ (short stretches of highly variable DNA) from several indigenous populationsStructure to divide the datasets into a given number of clusters (K) with genetic difference as the only criterion. At K = 2 up to K = 5 the clustering shows a clear resemblance to major geographical regions with natural barriers such as oceans and high mountains. At K = 2 Africa, Europe, the Middle East and Central/South Asia were clustered together; within the other cluster was East Asia, Oceania and America. Each successive clustering, increasing K with one cluster, split one of the previous clusters in two. An ‘unambiguous’ set of clusters was still found at K = 6 but here an isolated single population, not resembling a major geographical region split off. Further clustering of the entire dataset resulted in multiple clustering solutions  It has such an impact, because it says more than a table with numbers. So it is wildly popular.’‘Look, the program In an interview with a population geneticist, he referred to the ease of use of does to the data. Moreover, as the same population geneticist pointed out in the interview, since samples used with Structure are usually aimed at selecting for difference, conclusions that are drawn about genetic differences between populations nearly always contain overstatements about these relations. In the Rosenberg study, the choice for a panel with indigenous populations is already a choice for clustered populations. The outcome of their study is a clustering of already clustered individuals, rather than of a random sample, thus overstating the continental clustering. And while Rosenberg et al. were undoubtedly well aware of the technical details of the program, the seemingly simple visualisations helps the reader of their study to read the outcomes of the software without much knowledge of how the software works. The visualisations can thus add to easy acceptance of the connections between existing populations and newly created genetic categories as established by the software.So the attractively visualised output leads to less attention as to what the program really Structure a model-free program is that Structure can infer population structures from genetic data without predefining populations based on non-genetic data. It does not mean that there is no model underlying the software. This lack of pre-definition positions the software as a more or less unbiased mediator, giving the impression that the data can speak for themselves, conveying their meaning through the software with a minimum of biased mediation by human interpretations.What the population geneticist quoted above refers to when calling ‘The only thing that could still be interesting, is of course to what extent this kind of thing can all be automated… the whole scientific process. So induction and hypothesis testing, because you would prefer the data to make its own definition of function… (…) a natural definition, a natural ontology. So that it does not come from our interpretation of how a cell functions but from how the data itself thinks it looks like.’I encountered this idea of the computer or its software as an unbiased mediator in different contexts during my research, under a variety of names such as ‘unbiased grouping’ or ‘the data speaking for themselves’. One of the bioinformatics experts I interviewed, addressing the diversity of the concept ‘function’, expressed it as follows: were to be fully automated, the data could speak for themselves. In other words, automation is the process of rendering the results more natural, with the computer as an unbiased neutral agent, reading nature directly, without conceptual mediations. This could strengthen essentialisation, because the outcomes tend to be regarded as facts from nature, rather than as human created and thus contestable narratives.While this is a description of an ideal rather than of an existing reality, it implies that if the scientific process What we see here, then, is the naturalisation of population structures through the naturalisation of technology, as M’charek described it M’charek . The comThis case study shows how bioinformatics software can contribute to specific enactments of population identities through assumptions that become embedded in an algorithm. In these enactments, populations as biological and genetic phenomena are naturalised, resulting in the essentialisation of differences between populations. These essentialised biological differences reconnect with notions of ethnicity and race.Fujimura and Rajagopalan have suggested a way of avoiding essentialisation of identity in the context of genomics. Focussing on circumventing the use of racial categorisations in biomedicine, they argue for a rigorous separation of existing population identities and genetic clustering, by creating new ‘categories of genetic similarities’ for biomedical purposes. They took this idea from their ethnographic fieldwork on bioinformatics in biomedical practices, where some researchers are already arguing for and implementing such an approach. In this approach, in which the possibilities of bioinformatics play a central role, new categories should be based on genetic data only and leave out information on shared ancestry, race and ethnicity ’  in the Netherlands. This is done using imputation  That is made up out of three different people whose genome has been determined and that is now used as the “normal human”.’Question: ‘is that still the genome of the Human Genome Project?’‘There have been some updates but it is still based on it. And there are different versions (…). There is for example one specific part on chromosome 17, which is very often different in the European population from the rest of the world. And that, for example, is now an alternative bit, added for that region. (…) So these things are increasingly added and are put as much as possible in one thing, in one form. So that is what we have to compare it with every time.’The main genetic reference for humans is largely based on the sequence created by the Human Genome Project. As one bioinformatics researcher told me: 5, you can find variants that are very rare in populations, less than five percent for example. And if you then make a Venn-diagram6 of, say, Africans and Europeans and Asians, you see that they are pulling apart, because there are simply so many unique variants.’‘[B]efore, those populations did not seem to be so far apart but now that they have started to measure much deeperThus, already in the Human Genome itself some population differentiation is taking place, based on geographical regions. Apparently, one reference genome for defining all humans genetically is deemed by researchers to be not always specific enough for research purposes. One bioinformatics researcher, himself involved in the Genome of the Netherlands project, phrased the need for differentiation as follows: The rationale behind the creation of more differentiated reference genomes that select people into genetic proximate clusters, is that with a higher genetic proximity of reference genomes to research subjects, more meaningful differences can be found. Using existing population categories as selection criteria is one way of creating differentiation, a way that is used in many genome projects. A well known example is the 1000 Genome project, an effort to sequence a thousand complete genomes from (mostly indigenous) populations all over the world  is paired in the Dutch context with its opposite allochtoon . Both terms are widely used in Dutch political and public debates on issues like migration, asylum policies and crime. The Dutch statistical bureau (CBS) has defined them as follows: ‘For autochtonen both parents were born in the Netherlands, while allochtonen have at least one parent that was not born in the Netherlands.’ For allochtonen born in the Netherlands (2nd generation) the mother’s country of birth counts as country of origin, unless she was born in the Netherlands, in which case it is the father’s country of birth. Subsequently, there is a division between western  and non-western  allochtonen  are known, but not the nucleotides in between. SNPs from the GWAS data and SNPs in the fully sequenced genomes are matched and subsequently the ‘gaps’ in the GWAS data are inferred statistically from the data in the known genomes. In this process, SNPs on the reference and the GWAS data are matched and only where there is a match, imputation will be possible. The imputation process is thus a process in which the Genome of the Netherlands data, as reference, is connected to existing databases in an attempt to find more local genetic variants.autochtoon from allochtoon, not the chip itself as technology. However, the specific connections enabled by bioinformatics practices and technology, connecting the chip to the Genome of the Netherlands, create the conditions in which this selection is part of a practice where it can be naturalised and possibly essentialised.The next step, as Wijmenga suggested, could be the creation of chips for specific local variants. That means that micro array chips will be created, which can detect the presence of specific variations in the genome of an individual, thus matching the individual to the known variation in the database. Since these chips will focus on genetic local populations, they will specifically serve an indigenous population. It could be argued that it is the selection of individuals to whom the chip is applicable that separates autochoon and allochtoon distinctions. Essential in this biologisation is the connection between database and individual, a connection that is enabled by relating in silico sequences to DNA in the cell, a practice in which bioinformatics plays a crucial role. This relation may seem self-evident. After all, the four-letter sequence (ATCG) in the computer or database reflects the order of nucleic acids in the cellular DNA. However, rendering the order of nucleic acids computer-readable as an in silico sequence or four letters involves technology and human work. In the process, the order of nucleic acids in the cell is enacted as a base for the computation of genetic functions and genetic connections. The meaning that is given to sequences in this process is naturalised by the seemingly self-evidence of this relation. With the advent of Next generation sequencing, the work is increasingly automated in an informatics process running in the background from the point of view of biologists and thus getting out of view from their perspective, further naturalising the meaning of connections between in silico sequences and living bodies.As M’charek has argued, reference databases tend to become naturalised. As a result, the work and choices that go into making them are often not considered in their routine use as a reference. Through the naturalisation of the reference genomes, the objects they help create, such as individual genomes, tend to be naturalised as well M’charek . It is nStructure and the reference database Genome of the Netherlands. In both cases, information technology and bioinformatics as a discipline play a role in the enactment of population identities in a different manner.In this article, I have tried to tease out the ways in which bioinformatics, as a discipline, is involved in the enactment of population identities. I presented two cases of bioinformatics technologies that play a role in such enactments: the software program Structure software, a priori presuppositions about populations find their way into the algorithm, such as the assumption of clustered populations as well as a sense of origin, be it mixed or not. The purpose of the software is to see if categorisations according to so called ‘subjective’ criteria such as linguistic, cultural or physical characteristics agree with genetic clusters. While this purpose is not directly built into the algorithm, it is reflected in the possibilities of the software as well as in the article that accompanies the software. These aspects of algorithm, software and the accompanying narrative, are essential ingredients for an enactment of a division of populations according to continental barriers in the Rosenberg study, that are reminiscent of racial divisions. This is not to say that the way the study is conducted does not matter for the outcome, the selected data for the study in the form of an HGDP panel is an important element too. I am rather arguing that bioinformatics plays a significant part in this enactment and certainly not a neutral one.In the constituting part of the research and the values contained in this research. The supposed neutrality of computers within genomics can create the idea that data speak for themselves, that through them nature can be perceived without inevitable human bias, black boxing and naturalising implicit assumptions that are part of not only the tools but also of the broader discourses surrounding genetics. These naturalisations can easily lead to essentialisations of differences that are located in the bodies of people who can be identified as a group in everyday life.Showing that bioinformatics is not neutral in these enactments is important. Bioinformatics and computers are not only relevant because they can embody certain assumptions, but they also play a role in the naturalisation of connections between genetic and ‘subjective’ populations. While acknowledged as an important enabler of life science research, bioinformatics is regularly regarded as infrastructure for this research. As a result, its contributions and the values contained in them get easily overlooked as While the Structure case thus shows the role of bioinformatics in the re-enactment of biological differences in racial and ethnic categories as genetic differences, the Genome of the Netherlands shows the role of bioinformatics in the biologisation of a different origin narrative: that of nationality. Here, it is the database itself that, through its contents of 750 sequenced genomes, enacts Dutchness as a genetic category by representing the genomic variation within the Dutch indigenous population. This could be regarded as a purely statistical representation. However, the connection of individual genomes to, in many ways, a naturalised common sense definition of indigenous Dutchness, is more than ‘just’ statistical. Through these connections the database materially connects this naturalised definition to individual genomes and thus bodies, enacting (Dutch) nationality as a genetic category. It is in these connections that bioinformatics plays a crucial role.Next to being a constituting factor in the enactment of genetic Dutchness, as a reference, the database also stabilises this enactment. Embodying genetic Dutchness as represented by 750 full genomes and identified local variants, its repeated use as a reference database can further stabilise this enactment.In the case studies that I presented in this paper, bioinformatics is not the only constituting factor in the enactments of population identities as biological. What I wanted to show is how bioinformatics is an essential element in these enactments and how its tools and practices do not only enable the research, but also contribute to enactments that are related to research results, be it by the embodiment of certain enactments in algorithms and databases or through the naturalising effect of supposed neutrality of computers, bioinformatics is not a neutral element in the enactment of population identities as biological.Bioinformatics as a research practice is an important player in genomics as well as other fields within the life sciences. Not many projects in genomics can do without its support. Acknowledgment of the work of bioinformatics as a research field that has an important influence on how research is done in the life sciences, should go together with the acknowledgment of the ways in which bioinformatics, far from being neutral, entails values and specific enactments of specific human identities.Sorting things out  the documentation accompanying a program like Structure, b) its graphics and c) the studies it is used for. Tishkoff and Kidd for example, have shown how such a gradual perspective can lead to a diversified view in which complex individual ancestry can play a role but in which a crude division by race or a simplified use of ethnicity does not make sense (Tishkoff and Kidd Keeping identities flexible in a software program like autochtone Dutch population(s) is based on common sense ideas of origin and belonging that are repeated through this focus. If the focus would be on genetic sameness and difference within the entire current Dutch population, that would mean there is more room for contingency and surprise, rather than of staying within the boundaries of the expected. Some variants might show some connection to a diverse ancestry, while other variants might overlap or follow other patterns. This could aid the diversification of stories of origin for different ethnic groups, while possibly fragmenting individual stories of origin, thus creating flexibility.In the case of the Genome of the Netherlands, keeping identity flexible could mean considering to what extent a Dutch reference database would be feasible that somehow reflects the genetic diversity of the entire current Dutch population, without losing its effectiveness as a reference. The focus on the uniqueness of the indigenous or With this kind of adaptation, the connection between identities as they are enacted through bioinformatics tools and actual living individuals could interfere with other enactments of population identity in interesting ways, enlarging the potential for diversification, thus countering rather than furthering essentialisation.1The concept ‘enactment’ is elaborated on in the ‘Methods and concepts’ section.2All interviews were conducted in Dutch; quotes are translated by the author.3Rosenberg et al. did not explicitly mention the indigenous origin of the samples in their article, nor was it mentioned in the original publication of the panel (Cann et al. 4The Netherlands has consisted of 11 provinces between 1840 and 1986, when Flevoland was added by way of a land re-claim. The reference to the original 11 provinces presumably means that Flevoland was not included in the sample.5Measuring deeper means that larger sequences are used for the research.6A Venn diagram shows the relationship between sets. African, European and Asian pulling apart thus means that these ‘sets’ are mutually divergent on the basis of genetic variance.Jan van Baren-Nawrocka obtained his master degree at the University for Humanistics in Utrecht, the Netherlands. Currently he works as a PhD researcher on a CSG project on Bioinformation and human identity at the Radboud University Nijmegen, the Netherlands.