Tylototriton shanjing was investigated from a mitochondrial perspective to address the role of the Quaternary ice ages in shaping phylogeographic history and genetic diversity of Yunnan. A total of 146 individuals from 19 populations across the entire range of the species were collected. We detected four maternal phylogenetic lineages corresponding to four population groups, and found that major glaciation events during the Pleistocene have triggered the intra-specific divergence. Coalescent simulations indicated that the populations retreated to different refugia located in southern Yunnan, northwestern Yunnan, the border region of western Yunnan with Myanmar, and middle-western Yunnan, respectively, during previous glacial periods in the Pleistocene, and these four refugia were not retained during the Last Glacial Maximum. Population expansions occurred during the last inter-glaciation, during which ice core and pollen data indicated that the temperature and precipitation gradually increased, and declines of population sizes started after the beginning of the Last Glacial Maximum when the climate became cooler and dryer. The paleo-drainage system had no contribution to the current genetic structure and the rivers were not dispersal barriers for this salamander.Factors that determine the genetic structure of species in southwestern China remain largely unknown. In this study, phylogeography and demography of  Quaternary climatic oscillations had profound effects on the geographical distribution and genetic structure of many species. Population genetic analyses have shown that during the Pleistocene, many floral and faunal species in the Northern Hemisphere migrated southward and survived in refugia during glacial periods and subsequently expanded northward from southern refugia during interglacial periods Yunnan is an ideal region to study ecology, distribution and evolution, especially historical geological events, climate oscillations and biological adaptations. Being characterized by dramatic variations in climate and topography, the montane regions of Yunnan support a wide array of habitats. Moreover, during the Quaternary, there was no large-scale continental glaciation in this region However, the mechanisms that shape the current genetic structure in Yunnan are still poorly understood, because different species may have different evolutionary trajectories and different response mechanisms to the same historical events. Some studies revealed that lineage divergence times were much earlier than the Pleistocene and genetic structures were shaped by orogenic events In addition, an accurate delimitation of glacial refugia is a high priority for conservation because these are key areas for the persistence and evolution of biodiversity Tylototriton shanjing) spans the Yunnan province of China, from the tropical south, through the subtropical center and west, to the temperate northwest Amphibians, being terrestrial poikilotherms with narrow habitat requirements and limited dispersal potentials, are useful model animals for population genetic studies. The range of Red Knobby Newt (T. shanjing to test hypotheses involving the following questions: (i) How did climatic changes during the Pleistocene affect the observed phylogeographic structure and demographic dynamics? (ii) Did historical or contemporary drainage systems contribute to the current patterns of genetic variation? Such information will improve our understanding of the historical and ongoing evolutionary driving forces for maintaining the extraordinarily high biodiversity of Yunnan, China.In this study, we examine the evolutionary history of All animal samples were collected following the regulations for the implementation of People’s Republic of China on the protection of terrestrial wildlife (State Council Decree [1992] No. 13) and approved by Wildlife Protection Office, the Forestry Department of Yunnan Province as well as the Ethics Committee of Kunming Institute of Zoology, Chinese Academy of Sciences.T. shanjing .A total of 146 individuals were sampled from 19 populations throughout the entire geographical range of shanjing . Animalsb (cyt b), control region (CR), tRNA-Phe, and 12S rRNA genes were amplified and sequenced. The cyt b fragment was amplified using primers MVZ15 and MVZ16 b) or 50°C  for 30 s, and one minute extension at 72°C, followed by a final extension step at 72°C for 5 min. PCR products were purified via spin columns. Sequencing of cyt b was performed directly using the corresponding PCR primers. For sequencing the fragment spanning CR, tRNA-Phe, and 12S rRNA, the corresponding PCR primers and four internal primers designed by this study were used  and rechecked by eye. Haplotypes were identified using DnaSP 5.0 Pleurodeles waltl from Iberia and Pleurodeles poireti from northern Africa was initiated by a vicariance event at the end of the Messinian salinity crisis, approximately 5.3 Mya P. waltl and P. poireti based on Vieites et al. 7 generations using the HKY+I+G model and sampled every 1000 generations, assuming a coalescent prior of constant population size. These four runs were then combined in Tracer 1.4 Time to the most recent common ancestor (TMRCA) was estimated using an uncorrelated lognormal relaxed molecular clock model as implemented in BEAST 1.6.2 Genetic diversity was estimated by haplotype diversity (h) and nucleotide diversity (π) in Arlequin 3.1 D statistics Fs test D and Fs values were assessed through 1000 simulations. Under demographic expansion, both of these indexes are expected to have significant negative values.Three commonly used methods were applied to examine demographic history. First, we traced population growth using Tajima’s PRag and PSSD, respectively, using a bootstrap approach (1000 replicates). The time at which the population expansion began (t) can be estimated from the relationship τ = 2utu is the estimated mutation rate of the sequences.Second, evidence for population expansion was tested by examining pairwise mismatch distributions in Arlequin. Under the null hypothesis of sudden expansion, the raggedness index quantifying the smoothness of the observed mismatch distribution 7 iterations of the MCMC chains were run, sampling every 1000 iterations and discarding the first 10% as burn-in. Other settings of Bayesian prior were default. Bayesian skyline plots were generated with Tracer 1.4.Third, past population dynamics were examined using Bayesian skyline plots S, the minimum number of sorting events required to explain population subdivision S-value of the BI genealogy and the S-values of the simulated genealogies.Coalescent simulations of genealogies constrained within models of population divergence provide a powerful means of assessing the fit of observed genetic patterns to different phylogeographic hypotheses Ne) for the simulations was estimated using the mutation parameter θ (Theta-W) calculated by DnaSP. We converted the theta to Ne using the equation θ = 2Neμ, with the estimated mean substitution rate. During coalescent simulations, the overall Ne was set to equal the empirical estimate, and the Ne of the refugial population was constrained to a size proportional to the overall Ne. Absolute time (years) was converted to coalescent time (generations), assuming a generation time of 4 years. TMRCA dates estimated from BEAST were used to construct hypotheses of more than one refugium (detailed in Results).Effective population size  to give a relative probability score for each locality of having harboured the MRCA of the clade.The number of times that each sampling site was inferred as the unique origin of the root was added over the 500 genealogies. When several b, CR, tRNA-Phe, and 12S rRNA were 753, 734, 69, and 817 bp in length, respectively. No insertions or deletions were observed for the protein-coding cyt b sequences. Among the 146 individuals, a total of 58 haplotypes were identified by 144 polymorphic sites when all fragments were combined. Sequences of these haplotypes and that of outgroup have been deposited in GenBank under accession numbers JX854457–JX854515, JX854517.The aligned sequences of cyt The HKY+G+I model was selected as the best-fit model of nucleotide substitution. MP and BI analyses obtained consistent tree topologies . MonophyThe divergence time of lineage A from all other lineages was estimated to be approximately 0.83 Mya  and genetic variations among population within groups and within populations are obviously higher than variation among groups when they were partitioned into three or five groups according to the river systems , being consistent with the four major lineages obtained by the phylogenetic analyses . SAMOVA to seven . Althougto seven , AMOVA r systems , indicatP<0.05, P>0.05, efN of sub-lineage D2 had a trend towards growth from about 0.175 Mya , then populations from middle-western Yunnan became isolated from populations from northwestern Yunnan and the border region of western Yunnan (c. 0.76 Mya), with populations from northwestern Yunnan and the border region of western Yunnan diverging into two further lineages  is sister to a clade consisted of the other lineages  do not cluster together with populations from northwestern Yunnan (lineage B)  was also found to be not shaped by the paleo-river system Nanorana yunnanensis) Terminalia franchetiiT. shanjing and B. pleuraden live in lentic environments, whereas N. yunnanensis and T. franchetii are associated with lotic environments. It is likely that the paleo-river system had no impact on the genetic structure of species preferring for standing water because standing water bodies can act as barriers to gene flow among populations Our data indicate that lineages . The uppneage B) . This fiAlthough lineage D is distributed across four large rivers , no effe2T. shanjing became restricted to four different regions that served as refugia with interrupted gene flow. With repeated range size changes, surviving populations have passed through genetic isolation, allowing lineages to diverge Geographically no significant east-west barrier exists between the southern lineage (lineage A) and other lineages. The divergence time between the southern lineage and other lineages is estimated to be approximately 0.83 Mya . This daT. shanjing located in southern Yunnan and the border region of western Yunnan, respectively during this harsh climatic period. Population LC has the highest haplotype diversity among the southern populations and the ancestral haplotype of this group (H5) is present at this site  and B. pleuraden, respectively. Being consistent with that there was no unified ice-sheet covering the whole plateau throughout the Quaternary glaciations On the basis of our date of the TMRCA for all lineages, it seems that all four refugia were not retained during the Last Glacial Maximum (0.023–0.018 Mya). This is supported by our coalescent simulation, which rejects the hypotheses of a single refugium, two refugia, three refugia, and four refugia at the end of the Last Glacial Maximum in favor of the hypothesis that current populations were derived from four refugia before the Last Glacial Maximum . Coalescc. 0.175 Mya and it was estimated to have expanded at about 0.13 Mya by Mismatch analysis. This estimation is earlier than the Last Glacial Maximum, being consistent with most recent studies of species from western China Garrulax elliotii by Qu et al. Climatic oscillations during the Pleistocene resulted in several glacial-interglacial cycles, which caused expansions and contractions of habitats c. 0.025 Mya  have also been suggested as glacial refugia for other species, meaning that these regions should be important for consideration when developing sound conservation policies in Yunnan. Population expansion occurred prior to the Last Glacial Maximum while declines of population sizes occurred after the beginning of the Last Glacial Maximum. Considering that this study is based entirely on mitochondrial data, nuclear data will be required to obtain a more comprehensive understanding of phylogeography of T. shanjing.In summary, Figure S1Networks of the 58 haplotypes from cytochrome b, control region, tRNA-Phe, and 12S rRNA sequences of T. shanjing.(TIF)Click here for additional data file.Table S1Primers used in this study to amplify and sequence.(DOC)Click here for additional data file.Table S2Estimations of the empirical theta values and effective population size.(DOC)Click here for additional data file.


Salvelinus alpinus), introduced 20 generations ago, across and within two subalpine lakes separated by a dam with a subterranean tunnel and spill gates after 7 generations. Due to water flow regime, the time window for fish migration is highly restricted.Animal feeding and spawning migrations may be limited by physical barriers and behavioral interactions. Dam constructions (e.g. hydropower) commonly include gateways for fish migrations to sustain ecological connectivity. Relative genetic impacts of fish passage devices versus natural processes (e.g. hybrid inferiority) are, however, rarely studied. We examined genetic (i.e. microsatellite) population connectivity of highly migrating lake-dwelling Arctic char (0) = 10.8%) and initial site fidelity. Simulations indicated that genetic drift among relatively small effective populations (mean e N= 62) may have caused the observed contemporary differentiation. Novel Bayesian analyses indicated mean contributions of 71% F0 population hybrids in spawning populations, of which 76% had maternal or paternal native origin.Char populations, with similar genetic structuring and diversity observed across and within lakes, were admixed across the dam with fishways during feeding. For spawning, however, statistically significant, but very low population differentiation  was found in nine out of ten reproductive site comparisons, reflecting interactions between extensive migration (mean first generation (FEcological connectivity between lakes separated by a dam has been retained through construction of fishways for feeding migration. Considerable survival and homing to ancestral spawning sites in hybrid progeny was documented. Population differentiation despite preceding admixture is likely caused by contemporary reduced reproductive fitness of population hybrids. The study documents the beginning stages of population divergence among spatial aggregations with recent common ancestry. Genetic differentiation, fundamental to population genetics, is initiated by restricted gene flow and reproductive isolation mechanisms within gene pools ,2. HabitNatural ecological connectivity may fluctuate in time and space, but anthropogenic alterations (e.g. water regulation) typically exaggerate this variation. Human impacted water flows and water habitat fragmentation expanded greatly worldwide in the twentieth century . In EuroGenetic drift and behavior may induce reproductive isolation mechanisms operating on fine scales. Genetic microstructure even within continuous habitat is reported ,19, althMicro-scale studies under initial admixture introduce challenges concerning sampling design and analytical approaches. For obvious reasons, sample sizes are often restricted both in numbers and temporal replicates. In continuous habitats sampling units may be difficult to delineate. Widely used Bayesian methods to infer cryptic population structure -40 may nReproductive isolation may be reinforced by homing, as documented within a wide range of species ,42. SuccSalvelinus alpinus), introduced around 1920 (i.e. 20 generations ago), across and within two lakes: Pålsbufjorden (PAL) and the downstream Tunhovdfjorden (TUN) . No deviations from HW were found, but nonrandom association of alleles from different loci was indicated in 12 and 9  of 45 tests uncorrected and after false discovery rate (FDR) correction .e N(30 - 90), for 5 populations in 20 generations following panmixia (m = 1.0) with maximum variation and 15 allelic states, assuming random mating, equal sex ratio and an island migration model. Observed pairwise population differentiation from our sample was compared with matrix scenarios of migration and e Nindicating similar FST estimates (above) from simulations. Ten independent replicates were obtained for the most likely model to address simulation variation. Similar backward modeling was run in SIMCOAL2 [Forward modeling of population differentiation was performed with EASYPOP v.2.0.1.  to evaluSIMCOAL2  to test All authors; JW, JH and KH conceived the study and participated in the project design. JW conducted the field and laboratory work, and did the genetic analyses. All authors wrote and approved the final manuscript.Summary statistics. Sample sites, number of analyzed individuals (n), number of amplified individuals (N), number of alleles , expected and observed (direct count) heterozygosity (He and Ho). Significant departures from HW (P < 0.05) within sites after FDR correction are marked *.Click here for fileCoalescent simulated population differentiation. Backward simulations in SIMCOAL2 supporting the findings of genetic drift as a contemporary driver for observed site fidelity.Click here for file


Didemnum vexillum. Analyses based on mitochondrial cytochrome oxidase I (COI) partial coding sequences revealed two distinct D. vexillum clades. One COI clade appears to be restricted to the probable native region , while the other clade is present in widely dispersed temperate coastal waters around the world. This clade structure was supported by 18S ribosomal DNA (rDNA) sequence data, which revealed a one base-pair difference between the two clades. Recently established populations of D. vexillum in New Zealand displayed greatly reduced COI genetic diversity when compared with D. vexillum in Japan. In association with this reduction in genetic diversity was a significantly higher inter-colony fusion rate between randomly paired New Zealand D. vexillum colonies  when compared with colonies found in Japan . The results of this study add to growing evidence that for colonial organisms reductions in population level genetic diversity may alter colony interaction dynamics and enhance the invasive potential of newly colonizing species.Considerable progress in our understanding of the population genetic changes associated with biological invasions has been made over the past decade. Using selectively neutral loci, it has been established that reductions in genetic diversity, reflecting founder effects, have occurred during the establishment of some invasive populations. However, some colonial organisms may actually gain an ecological advantage from reduced genetic diversity because of the associated reduction in inter-colony conflict. Here we report population genetic analyses, along with colony fusion experiments, for a highly invasive colonial ascidian,  Human mediated transfer of species into regions beyond their native range, and the resulting ecosystem perturbations, are major contributors to currently accelerating rates of indigenous biodiversity loss and species extinction Such non-adaptive changes in the genetics of newly colonizing species are expected to have both genotypic and phenotypic consequences, possibly including deleterious inbreeding depression Didemnum vexillum, within both its probable native region (Japan) and a recently established, non-native region .Biological explanations for the invasive success of particular species can be elusive and general ecological parameters such as release from predation Linepithema humile) which displays both reduced genetic diversity and reduced inter-colony aggression in non-native regions Genetic loci that strongly influence the structure and functioning of biological colonies have been characterized to the molecular level from a diverse range of phyla: Arthropoda Botryllus schlosseri, fusion to produce a chimeric colony is a well-described and complex process involving both the tunic and the vascular system that connects the individual zooids that comprise the colony B. schlosseri a single highly polymorphic locus has been shown to strongly influence colony allorecognition Taxonomically diverse groups of colonial ascidians have been shown to have allorecognition mechanisms that distinguish closely related colonies from unrelated colonies Didemnum sp., from diverse geographical temperate regions have been reported: New Zealand Didemnum species along with two entirely new species designations for New Zealand  and New Hampshire  Didemnum vexillum Kott, 2002 D. vexillum was likely to be in the northwest Pacific D. vexillum is considered non-native (e.g. the east coast of North America), D. vexillum often forms very large colonies that may smother other marine invertebrates including commercially valuable aquaculture species D. vexillum colonies now extend over very large areas - in 2005 estimated as >230 km2Over the past decade, morphologically similar colonies of an ascidian, Didemnum vexillum was first reported in New Zealand in 2001 within two adjacent harbours on the North Island, Tauranga and Whangamata D. vexillum was identified in the Marlborough Sounds (South Island), initially on a single barge that had earlier been moved from Tauranga harbour D. vexillum is not native to New Zealand including; a well-defined history of spread, the strong correlation between the distribution of D. vexillum in New Zealand and the infested barge, and that D. vexillum arguably meets all ten of the accepted criteria for designating a species as non-native D. vexillum in New Zealand to form large, biofouling colonies D. vexillum was associated with a significant reduction in its genetic diversity and in consequence New Zealand populations may exhibit increased rates of inter-colony fusion. To test this hypothesis, we examined genetic diversity within the D. vexillum mitochondrial cytochrome oxidase I (COI) coding region, comparing samples collected from New Zealand with those from Japan. In parallel we assessed the frequencies with which randomly selected D. vexillum colonies fused in experimental cut surface assays, comparing populations in New Zealand and Japan.D. vexillum were obtained: Japan, four locations, n = 37 colonies; New Zealand, five locations, n = 61 colonies  between clades A and B is 0.032.The percentages of polymorphic sites within clades A and B were 1.9% and 2.6%, respectively, while the percentage polymorphic sites within the combined COI sequence dataset was 6.8%. Divergence between clades A and B, as estimated by D. vexillum COI sequence based clade structure was reflected in the nuclear genome, 18S rDNA sequences were amplified from DNA preparations corresponding to the thirteen COI haplotypes found in this study . All 18S ribosomal DNA (rDNA) sequences amplified were identical except at position 705; the 18S rDNA sequences amplified from clade A genomic DNA  were A705 while the clade B haplotypes (i.e. H9–H17) were G705 (coordinates of GenBank accession number JF738070).To investigate if the D. vexillum COI sequences from both this work and Stefaniak et al. (2009) For population genetic analyses, the D. vexillum to the Marlborough Sounds H3 was the only COI haplotype found in all five geographical regions and appears to be the most common world wide . In thisP = 0.00). There was no significant difference between fusion rates for any experiments within either NZ or Japan. Amplified COI sequences established that all the colonies used in the CSA fusion experiments were from D. vexillum clade A  with an average of eleven CSA pairings (range 21–3), excluding positive controls, for each experiment , Table 2Didemnum vexillum COI haplotype diversity within New Zealand is significantly less than within D. vexillum's putative native region in Japan. The New Zealand D. vexillum populations sampled contained as few as three COI haplotypes. These data suggest an interpretation that D. vexillum experienced a significant reduction in genetic diversity when colonizing New Zealand, presumably due to a founder effect. Other putatively introduced populations  also display reduced diversity when compared to Japan, although sample sizes from these regions are small. Reduced genetic diversity is a common, but by no means universal, feature of invasive populations D. vexillum populations will increase with time as further colonization events augment existing genetic variation, although this may not be always be the case D. vexillum clade A population are potentially associated with reductions in allelic diversity at nuclear loci D. vexillum COI haplotypes revealed a well-supported monophyletic D. vexillum species grouping, composed of two distinct well-supported clades, termed A and B. Clade A included haplotypes from all five widely-separated geographical regions defined in this study while clade B was composed of haplotypes found solely in Japan. A previously published COI based D. vexillum phylogeny D. vexillum clades A and B correspond to cryptic, sibling species or to intra-specific subtypes D. vexillum clades A and B, as estimated by percentage of polymorphic sites, are at the lower end of comparable values reported for other ascidian species . Repeated Pleistocene glaciations profoundly affected the oceans around the present day Japanese archipelago D. vexillum clade B appears to be restricted to Japan.The lack of an adequate ascidian fossil record prevents calibration of ascidian COI sequence divergence against geological time B. schlosseri (fam. Styelidae) has been extensively studied Didemnum moseleyi (fam. Didemnidae) whereas Bishop and Sommerfeldt (1999) Diplosoma listerianum (fam. Didemnidae). Rates of chimeric colonies in natural populations of D. listerianum were also found to be extremely common D. vexillum possesses some form of colony recognition mechanism – with autogeneic assays always fusing and some inter-colony fusions resulting in non-fusion reactions. New Zealand populations of D. vexillum clade A displayed higher rates of fusion between paired, randomly-selected colonies than was found in Japan. An average of 80% (standard deviation ±18%) of the New Zealand inter-colony CSAs resulted in fusions compared with a value of 27% (standard deviation ±15%) for Japan. Note that in Japan the D. vexillum colonies were all from clade A and were collected from within a small bay (i.e. Shizugawa Bay) – a sampling strategy which would bias the sampling of related colonies and thereby inflate the CSA fusion rates. These CSA findings are consistent with a model in which reduction of the allelic diversity at D. vexillum's putative allorecognition loci enhances the probability that two randomly selected D. vexillum colonies in recently established populations will be genetically similar enough to fuse.While the fusion biology and associated colony allorecognition genetics of the colonial ascidian D. vexillum is correlated with increased rates of fusion between colonies. Such an enhanced tendency towards forming large chimeric colonies might explain the extreme propensity for biofouling that D. vexillum displays outside its putative native range D. vexillum. In addition, work investigating the frequency of chimeric colonies in both the New Zealand and Japanese D. vexillum populations is currently underway. The results of the combined population molecular genetic and phenotype-level study reported here suggest a model by which reductions in genetic diversity may enhance the invasiveness and biofouling propensity of D. vexillum. This model also suggests that a potential biocontrol method for D. vexillum outside its native range could be the introduction of additional genetic diversity into the invasive populations. Such introductions of additional genetic diversity would not remove D. vexillum from non-native regions, an undertaking now widely accepted as impossible, but may attenuate D. vexillum's propensity of biofouling that negatively impacts on aquaculture.A major challenge facing invasion biology is the description of biological features that may help predict the chances of invasion success and the delineation of the selective advantage(s) such features provide in novel environments No specific permits were required for the described field studies. No locations were privately-owned or protected in any way and the studies did not involve endangered or protected species.D. vexillum in New Zealand  and Japan  between April 2008 and July 2009  were macerated using a sterile scalpel blade. Total genomic DNA was extracted using i-genomic CTB DNA extraction mini kits . An approximately 600 bp section of the COI gene was amplified using tunicate primers (Tun_forward and Tun_reverse2) Didemnum psammatode , D. albidum  and Didemnum sp. B  were used as outgroups. Bayesian phylogenetic analyses were performed using MrBayes 3.1.2 6 generations, with four chains each and trees were sampled every 100 generations. Of the 5×104 trees sampled the latter 4.9×103, were used to construct a 50% majority-rule consensus tree.The initial data for phylogenetic analyses consisted of the 98 new COI sequences generated as part of this study and 71 previously published sequences p-distances were calculated using MEGA 4.0 Da) was calculated in DnaSP 5.0 Pairwise distances (the proportion of nucleotide sites that differ between two sequences) and average Mitochondrial COI sequences were first grouped into five broad geographical areas; New Zealand (NZ), Japan, West Coast North America (WCNA), East Coast North America (ECNA) and Europe. For each geographical region four measures of genetic diversity were calculated using ARLEQUIN 3.01 D. vexillum, cut surface assays (CSA) D. vexillum.To assess the rates of inter-colony fusion within populations of Figure S1Didemnum vexillum colony collection sites for DNA sampling and/or cut surface assays (CSA) in New Zealand (A) and Japan (B). (A) New Zealand sites: Marlborough Sounds ; Port Nelson; Wellington Harbour; Port Lyttelton; Whangamata. (B) Japan sites: Shizugawa Bay; Misaki Bay; Izu Peninsula; Ise Bay. Maps are not to scale.(TIF)Click here for additional data file.Table S1Source and sequence details, including GenBank accession numbers, of the Didemnum vexillum cytochrome oxidase I (COI) sequences from this study.(DOC)Click here for additional data file.Table S2Results of cut surface assays (CSA) of Didemnum vexillum colonies from New Zealand (A) and Japan (B). Collection sites are indicated with the bracketed letters corresponding to locations in (DOC)Click here for additional data file.


The mainland of the Americas is home to a remarkable diversity of languages,and the relationships between genes and languages have attractedconsiderable attention in the past. Here we investigate to which extentgeography and languages can predict the genetic structure of Native Americanpopulations.The Ethnologue classifications ofAmerindian languages. We report that The Ethnologueclassification provides a better genetic proxy than Greenberg'sclassification at the stock and at the group levels. Although highpredictive values can be achieved from The Ethnologueclassification, we nevertheless emphasize that Choco, Chibchan and Tupilinguistic families do not exhibit a univocal correspondence with geneticclusters.Our approach is based on a Bayesian latent cluster regression model in whichcluster membership is explained by geographic and linguistic covariates.After correcting for geographic effects, we find that the inclusion oflinguistic information improves the prediction of individual membership togenetic clusters. We further compare the predictive power ofGreenberg's and The Bayesian latent class regression model described here is efficient atpredicting population genetic structure using geographic and linguisticinformation in Native American populations. Cavalli-Sforza et al.et al.To investigate the relationships between genes and languages, the previous studiesmade use of tree-based or distance-based methods. Hunley and Long By definition, the results obtained from tree-based and distance-based methods areinfluenced by specific choices of tree reconstruction methods or particular geneticand linguistic distances. The validity of population trees depends on thereliability of their reconstruction method and on the hypothesis that geneticdifferentiation results from population fission. Whereas trees are well-suited fordescribing evolutionary relationships of non-recombining sequences like mtDNA, theymay be sensitive to distortion due to gene flow between populations when nucleardata are analyzed latent classregression models In this study, we introduce a novel method for investigating the relationshipsbetween genes and languages that avoids genetic and linguistic distances as well astree reconstruction methods. We consider Bayesian etal.Several Bayesian model-based approaches have been proposed to assign individuals togenetic clusters et al.Consider a genotypic data set, multinomial probit modelFor algorithmic reasons, the latent regression model was implemented through ahidden referencecluster.In the multinomial probit model the role of the clusters is not symmetric. Theestimates of the regression coefficients are defined with respect to theGiven the above latent class model framework, we used a Markov Chain Monte Carlo(MCMC) algorithm based on Gibbs sampling to compute the joint posteriordistribution on individual cluster labels, regression coefficients and allelefrequenciesIn this equation, the likelihood For each subset of covariates, we additionally computed a matrix of posteriorpredictive membership probabilities using a Monte Carlo method. To perform thecomputations, we simulated cluster labels from the generative model described inequation (1) and (2) where the regression coefficients are sampled from theirposterior distribution. To display predicted and inferred membershipprobabilities graphically, we used barplot representations. In these graphics,each individual is represented by To investigate whether a particular subset of covariates is a suitable proxy forgenetic assignment, we used two distinct measures. Both measures are based onthe posterior of regression coefficients and cluster labels. The first measureis a Pearson correlation coefficient, The computation of predictive scores is detailed in Appendix B. Another series of50 scores was computed after exchanging the role of the validation and trainingsets, and a cross-validation score was obtained by averaging the resultingWe ran a first series of simulations using the generating model of the programPOPS. Assuming three clusters, cluster labels of 300 individuals were simulatedusing the following regression equationsIn the second series of simulations, we extended the model by including a factorwith five levels representing five languages. The hidden regression equationswere defined asIn the third series of experiments, we studied two previously published data setssimulated from a five-island model The Ethnologue (www.ethnologue.com) The Ethnologueclassification at the family level (16 levels).We applied POPS to 512 Native American individuals from the Human GenomeDiversity Panel (HGDP) data set For the simulated data, the runs of POPS used 2,000 sweeps with an initialburn-in period of 1,000 sweeps. For the human data, the runs used 5,000 sweepswith an initial burn-in period of 2,500 sweeps. These values ensured that thelikelihoods stabilized around their stationary values. For the HGDP data and foreach model, we ran a total of 500 MCMC runs. We retained the 50 runs with thelargest likelihood values, and we averaged the resulting estimated and predictedmembership coefficients using the computer program clumpp The number of clusters was set to Using simulated data sets, we investigated whether including geographic andlinguistic covariates can improve the estimation of membership probabilities ornot, and we evaluated which subsets of variables best predict the estimatedpopulation genetic structure.For the simulations where latitude was influential (equations (3) and (4)), wefound that the true values of the regression coefficients were close to the modeof the posterior distributions . The inff loci , . Themisvariates . With , Finally, we studied the variable selection criteria for the data where latitudewas influential (equations (3) and (4)) as well as linguistic covariates(equations (5) and (6)). Whatever the number of loci we considered, the increaseof the correlation coefficient was larger when including latitude rather thanlongitude in the regression model. For the five-island data with a level of differentiation ofss than . The worTo investigate the relationships between geography, languages and genes in NativeAmerican populations, we applied POPS to a multilocus genotype data setincluding 512 individuals from the HGDP. We compared the posterior membershipcoefficients predicted by four different models that use distinct linguisticclassifications and we computed two variable selection criteria in order todiscriminate among models . Using a quadratic trend surface to correct for geographic effects, we comparedthe predictions of a model without languages (Model A) to the predictions of amodel using Greenberg's classification at the stock level (Model B), amodel using Greenberg's classification at the group level (Model C), and amodel using . ,  to  , and the. ,  to  .For sevThe Ethnologue classifications (Models B–D), groupingpopulations with the same linguistic taxon. At the exception of the Andean andGe-Pano-Carib stocks, Greenberg's linguistic stocks were associated withmultiple clusters (The Ethnologue classification (Model D),the Equatorial group split into the Arawakan and Tupi families. This separationimproved the prediction of genetic clusters since the Arawakan family wasassociated with a unique genetic cluster. In contrast, the separation of thePenutian group into the Mixe-Zoque and Mayan families did not improve thecharacterization of genetic groups. Overall The Ethnologueclassification provided better predictions of genetic groups thanGreenberg's classification. Among the 16 families of TheEthnologue classification, only the Tupi, Choco and Chibchanfamilies were not associated to a unique genetic cluster (The Ethnologue(Model D). The values of the cross-validation scores are approximately equal toThe Ethnologue leads to betterpredictions of genetic structure than Greenberg's classification at thestock or group levels.clusters . Refininclusters . At the  cluster . SupportWe proposed a Bayesian latent class regression model to investigate to which extentgeographic and linguistic information can predict population genetic structure inNative American populations. The originality of this approach was to modelindividual responses, i.e., the unobserved genetic cluster labels for eachindividual, using spatial and linguistic variables.Our simulation study provided evidence that a hidden regression layer can improve theinference of genetic structure in addition to allowing their predictions fromcovariates. We also tested two criteria of variable selection based on correlationcoefficients and cross-validation scores and found that these statistical indicesreached a plateau when the true set of covariates was included in the POPS model.With small numbers of loci, the use of covariates decreased the misclassificationrates of the clustering program significantly. For large numbers of loci, theestimation performances were hard to improve, especially when the likelihooddominated the prior distribution. However, using large numbers of loci madepredictions and the use of the variable selection criteria reliable.TheEthnologue classification. We did not consider Greenberg'stripartite classification  because, in additionto being controversial The Ethnologue providedbetter predictions of population genetic structure than Greenberg'sclassification.Using 678 microsatellite markers from the HGDP data set, we evaluated the suitabilityof geographic and linguistic predictors for Native American population geneticstructure. Geography predicted genetic clusters rather accurately. Howeverconsidering linguistic origin in addition to geographic origin improved theprediction of genetic structure. After correcting for geographic effects, weevaluated the predictive capabilities of three linguistic classifications:Greenberg's classification at two distinct levels and The Ethnologue classification provided a better genetic proxythan Greenberg's classification, some linguistic families were not perfectlycharacterized in terms of genetic clustering. The Chibchan and Choco families weregrouped in a Chibchan-Paezan stock by Greenberg et al.Though et al.Despite the intrinsic difference between methods, our analysis confirmed previousfindings that a sizeable correspondence between genetic and linguisticdifferentiation may exist only below a certain level of linguistic differentiation.The tests of treeness indicated that language classifications provide the best fitto mitochondrial data when they included external features of languageclassification trees and no deeper internal relationships between languages TheEthnologue classification increased the correlation coefficient fromTo further investigate potential scale effects, we applied POPS to 77 world-widepopulation samples from the HGDP data set excluding two language isolates (Basqueand Burushaski) and grouping the sub-Saharian samples in a reference cluster . ThegenThe examination of linguistic and genetic relationships in the Americas wouldobviously benefit from a more extensive sampling from the Na-Dene linguistic stockand from the inclusion of the Eskimo-Aleut stock. In a regression framework, a largedispersion of the explanatory variables is preferable. Though the sampling design ofthe HGDP was not optimal in our framework, our approach provided evidence thatlinguistic proxies improved the prediction of Native American population geneticstructure. As human genomic data expand in genetic and geographic coverage Figure S1Estimated and predicted genetic structure of Native American populations,with (TIF)Click here for additional data file.Figure S2Genetic structure at a worldwide scale as predicted by geographicalcovariates when K = 7. Geographical covariates includelatitude, longitude and distance to the Addis Abeba, which is computed byincluded five obligatory waypoints. The three barplots correspond to 1) thegenetic structure as inferred with genetic data and both spatial andlinguistic covariates, 2) the structure as predicted with spatialinformation and 3) the structure as predicted with spatial and linguisticinformation. The linguistic variable is a qualitative variable correspondingto The Ethnologue classification.(TIF)Click here for additional data file.Table S1Coordinates and linguistic entities of 28 Native American populations fromthe Human Genome Diversity Panel.(PDF)Click here for additional data file.Table S2Coordinates, distance to Addis-Abeba, and linguistic families of 77 worldwidepopulations from the Human Genome Diversity Panel.(PDF)Click here for additional data file.Appendix S1Gibbs sampler.(PDF)Click here for additional data file.Appendix S2Computation of the predictive score for cross-validation.(PDF)Click here for additional data file.


Cryptosporidium hominis, the predominant species responsible for human cryptosporidiosis. We conducted sequence analyses of 32 genetic loci of 53 C. hominis specimens isolated from a longitudinally followed cohort of children living in a small community. We identified by linkage disequilibrium and recombination analyses only limited genetic recombination, which occurred exclusively within the 60-kDa glycoprotein gene subtype IbA10G2, a predominant subtype for outbreaks in industrialized nations and a virulent subtype in the study community. Intensive transmission of virulent subtype IbA10G2 in the study area might have resulted in genetic recombination with other subtypes. Moreover, we identified selection for IbA10G2 at a 129-kb region around the 60-kDa glycoprotein gene in chromosome 6. These findings improve our understanding of the origin and evolution of C. hominis subtypes and the spread of virulent subtypes.Little is known about the emergence and spread of virulent subtypes of  Cryptosporidium spp. are emerging pathogens of humans and a variety of vertebrates, and cause severe diarrhea in immunocompetent and immunocompromised persons  identified by sequence analysis of the 60-kDa glycoprotein (gp60) gene, the Ib subtype is the major subtype responsible for waterborne and foodborne outbreaks of cryptosporidiosis in many countries. Subtype IbA10G2 has been found in ≈50% of C. hominis–associated outbreaks in the United States, including the massive outbreak in Milwaukee, Wisconsin, USA, in 1993  of 32 genetic markers. Data obtained should be useful in understanding emergence and spread of virulent C. hominis subtypes.We conducted a comparative population genetic analysis of virulent Cryptosporidium spp. were collected during a longitudinal cohort study of enteric diseases in children living in a periurban shantytown in Lima, Peru, during 2004–2006. The field study was conducted in the same community used in a previous longitudinal cohort study of enteric pathogens and had a similar study design  belonging to 4 gp60 subtype groups were selected for MLST analysis: Ia (9 specimens of IaA13R8 and 1 specimen of IaA13R7), Ib (26 specimens of IbA10G2), Id (6 specimens of IdA10 and 5 specimens of IdA20), and Ie (6 specimens of IeA11G3T3). No specimens used in the study had mixed C. hominis subtypes.DNA was extracted from 200 μL of microscopy-positive specimens by using the FastDNA SPIN Kit for Soil . Cryptosporidium spp., chromosome 6 was fully sequenced for 2 C. parvum specimens and 1 C. hominis specimen, which facilitated search for additional microsatellite and minisatellite markers for population genetics analysis. The 8 polymorphic markers on chromosome 6  used in several MLST and population genetic analyses of C. hominis and C. parvum (http://tandem.bu.edu/trf/trf.html). Of 325 short tandem repeat sequences identified, 46 loci were initially selected at spaced intervals that covered the entire chromosome 6. A nested PCR approach was used for amplification of all potential targets. After an initial evaluation of primers by PCR and DNA sequencing of IaA15R3, IaA20R3, IbA10G2, IdA10, and IeA11G3T3 subtypes of C. hominis from the United States and Peru, 24 polymorphic loci (Among the 8 chromosomes of C. parvum IIaA16G2R1 subtype) were used in each PCR. PCR products of the expected size were sequenced in both directions by using an ABI 3130 Genetic Analyzer . Sequences obtained from each locus were edited and aligned by using BioEdit 7.04 version (www.mbio.ncsu.edu/BioEdit/bioedit.html) and ClustalX version 1.81 , respectively. Nucleotide sequences of all haplotypes of polymorphic loci were deposited in GenBank under accession nos. JX088398–JX088417 and JX088427–JX088501.Conditions for nested PCR analysis of each marker were similar to those described , number of haplotypes, number of polymorphic and segregating sites, intragenic linkage disequilibrium (LD), and intragenic recombination rates by using DnaSP version 5.10.00 (www.ub.es/dnasp/). The ratio of nonsynonymous substitutions per nonsynonymous site to synonymous substitutions per synonymous site was calculated for gp60 and several nearby loci  by using DnaSP. Thereafter, sequences of polymorphic loci were concatenated as a single multilocus contig to calculate gene diversity, interlocus LD, and recombination rates by using DnaSP. Pairwise intergenic LD was also evaluated among polymorphic loci by using the Fisher exact test and Markov chain parameters in Arlequin version 3.1 (http://cmpg.unibe.ch/software/arlequin3/).For each marker, sequences of 53 http://pritch.bsd.uchicago.edu/structure.html). Conversion of microsatellite and minisatellite sequences to allelic data was performed by using the Excel Microsatellite Tool Kit 3.1.1  and Genepop version 4.0 (http://genepop.curtin.edu.au/). Several analyses of allelic data were performed by using K (likely populations) ranging from 2 to 8 and 50,000 iterations after a burn-in of 50,000 iterations. Output at K = 2–5 provided the best fit to MLST data and were used in further analyses. To provide an alternative view of substructuring, a median-joining algorithm analysis (www.fluxus-ngineering.com/sharenet.htm). Each gp60 subtype was further analyzed for LD and recombination by using DnaSP and Arlequin. Population differentiation (FST) between IbA10G2 and non-IbA10G2 subtypes was also assessed at each genetic locus by using Arlequin.Population substructures were analyzed by using the Bayesian analysis tool STRUCTURE version 2.2 , an Hd of 0.9898, and a nucleotide diversity of 0.339. The frequency of MLGs ranged from 7.5% (1 MLG with 4 specimens), 5.7% (1 MLG with 3 specimens), and 3.8% (5 MLGs each with 2 specimens) to 1.9% (36 MLGs each with 1 specimen). Because 431/968 polymorphic sites and 297/362 segregating sites occurred within the gp60 locus, a second analysis was performed by using concatenated sequences excluding gp60  with 537 polymorphic sites, including 65 segregating sites and 472 indel sites. A lower nucleotide diversity of 0.289 was observed. However, the number of MLGs (43) and haplotype diversity (0.9898) remained the same.Intragenic LD between pairs of segregating sites was assessed for each polymorphic locus. The analysis was possible only for 7 loci  that had at ≥3 segregating sites. Incomplete intragenic LD (|D′| Y = 0.9729 + 0.0130X), where Y is the LD value and X is the nucleotide distance in kb, was observed at the gp60 locus, and complete intragenic LD (|D′| Y = 1.0000 + 0.0000X) was found at each of the 6 remaining loci . An intrns) value of 0.2711 . Of 47,895 pairwise comparisons, 25,904 were significant by Fisher exact test, and 8,714 were significant after Bonferroni correction . Of 2,080 pairwise comparisons, 921 were significant by Fisher exact test, and 333 were significant after Bonferroni correction. Incomplete LD (|D′| Y = 0.7886 + 0.0051X) was also observed in LD analysis per site  was observed in subtype IbA10G2, suggesting recombination within this subtype. In contrast, all other subtypes showed complete LD (|D′| Y = 1.0000 + 0.0000X) among all sites, indicative of no genetic recombination within these subtypes . In addiTo validate these observations, recombination tests were conducted for all gp60 subtypes. Using full multilocus sequences, we found that among 33 potential Rms observed in overall recombination analysis, 4 Rms were detected in subtype IbA10G2 but no Rm was found within each of the remaining subtypes . When anFST analysis showed highly significant differentiation between the IbA10G2 subtype and non-IbA10G2 subtypes at 4 loci around gp60, C6–1000′ (p<0.00001), gp60 (p<0.00001), CP47 (p<0.00001), and C6–2600 (p<0.001). The only other locus that showed such a level of differentiation between the 2 groups was C6–3520 (The genetic determinant for differences between IbA10G2 and non-IbA10G2 subtypes was assessed by comparison of haplotype diversity of the 2 groups at all 25 polymorphic loci in chromosome 6. At most of the genetic loci, the haplotype diversity of the 2 groups was similar, and there was no clear population differentiation at these loci , Table 4Cryptosporidium spp. has a sexual phase, during which sexual recombination can occur between genetically distinct strains (C. parvum, the species that infects humans and some animals, undergoes meiotic recombination between different lineages in genetic-crossing experiments (C. parvum populations have also shown genetic recombination in most study areas (C. hominis is primarily infectious to humans, and previous MLST studies showed a clonal population structure. Genetic recombination was believed to be rare or nonexistent in C. hominis (C. hominis. In the present study, we examined population substructure of C. hominis in a cohort of children living in a small study area by using 32 genetic markers.Like other apicomplexan parasites, the life cycle of C. hominis. A recombination test showed only limited genetic recombination at the gp60 locus. Thus, the high level of LD and limited recombination found in the overall population could be explained by an essential clonal population structure of C. hominis in the field site in Peru, which is consistent with information on C. hominis population genetics in other countries (On the basis of multilocus sequence data and allelic profiles for 53 specimens, analysis showed strong LD among 25 polymorphic loci, suggesting an overall nonpanmictic population structure of C. hominis occurred mostly at gp60 or loci around gp60. Thus far, the gp60 gene is the most polymorphic marker identified in the Cryptosporidium genome. Because of its high sequence heterogeneity, gp60 has become the most widely used gene in Cryptosporidium spp. subtyping, which categorizes C. hominis and C. parvum into several subtype groups and various subtypes within each subtype group (Results of LD and recombination analyses suggest that limited recombination in the study population of C. hominis subtype IbA10G2 was shown to be more virulent than other subtypes in the study community (Recent studies have suggested that telomeric/subtelomeric regions are highly polymorphic and might encode putative virulence factors (FST analysis of 25 polymorphic loci in chromosome 6 between the virulent IbA10G2 subtype and non-IbA10G2 subtypes showed population differentiation at 4 loci around gp60. When a locus shows extraordinary levels of genetic population differentiation compared with other loci, this finding might be interpreted as evidence for positive selection (Pairwise Plasmodium falciparum chloroquine-resistance transporter gene in chromosome 7 as the result of selection for chloroquine resistance. Nair et al. (P. falciparum in association with pyrimethamine resistance. Consistent with these findings, we detected reduced sequence variation around gp60 in virulent subtype IbA10G2, suggesting that the 129-kb region surrounding gp60 in chromosome 6, perhaps gp60 itself, might be involved in selection for virulent gp60 subtype IbA10G2 in C. hominis. In a comparison of the number of nonsynonymous substitutions per nonsynonymous site to the number of synonymous substitutions per synonymous site analysis of loci around gp60, we confirmed the presence of positive section at least at the CP47 locus.One explanation for this pattern of genetic diversity is that the region surrounding gp60 was probably affected by selective sweep or genetic hitchhiking caused by selection of the virulence subtype. A hallmark of a selective sweep is a chromosomal region with reduced diversity associated with a specific phenotype. In previous studies of other apicomplexan parasites, similar patterns of reduced genetic variations were observed in chromosomal regions surrounding sites under selection pressure. Wootton et al. (C. hominis responsible for numerous waterborne and foodborne outbreaks of cryptosporidiosis in many countries (C. hominis infections are caused mostly by IbA10G2 and imported cases by other subtypes (C. hominis subtypes and subsequent spread of the recombinant parasite with the fitness gene. Recently, genetic recombination was shown to be a key strategy for selection of virulent clones of Toxoplasma gondii, an apicomplexan parasite with a largely clonal population structure in North America and Europe (The reason for exclusive occurrence of genetic recombination in IbA10G2 is not clear. Because IbA10G2 is the major subtype of C. hominis population in a cohort of children living in a small community in Peru. Although C. hominis from the community has an overall clonal population structure, genetic recombination occurs within subtype IbA10G2 around the gp60 locus, which might be involved in pathogenicity. Common occurrence of its parental subtypes and biologic fitness of the recombinant subtype with the IbA10G2 trait have probably facilitated genetic exchange and spread of the virulent subtype. In addition, we were able to localize selection for the virulent subtype IbA10G2 to a 129-kb region surrounding gp60 in chromosome 6. These observations could improve our understanding of emergence and spread of virulent C. hominis subtypes.In conclusion, we have shown complex substructures in a natural


Microsatellites are the most popular and versatile genetic marker with myriads of applications in population genetics, conservation biology, and evolutionary biology. These are the arrays of DNA sequences, consisting of tandemly repeating mono-, di-, tri-, and tetranucleotide units, which are distributed throughout the genomes of most eukaryotic species. Microsatellites are codominant in nature, highly polymorphic, easily typed, and Mendelian inherited, all properties which make them very suitable for the study of population structure and pedigree analysis and capable of detecting differences among closely related species. PCR for microsatellites can be automated for identifying simple sequence repeat polymorphism. Small amount of blood samples or alcohol preserved tissue is adequate for analyzing them. Most of the microsatellites are noncoding, and therefore variations are independent of natural selection. These properties make microsatellites ideal genetic markers for conservation genetics and fisheries management. This review addresses the applications of microsatellite markers in conservation genetics and recent advances in population structure analysis in the context of fisheries management. Organisms are incessantly undergoing micro- and macroevolutionary processes both at molecular and organismal levels. In fact, the process of evolution starts at the molecular level, more precisely from a single base of the DNA molecule, and ends up in variations at the organismal level. Genes are the factors, which determine the phenotypic characters of any organism. Thus, the variations that happen to the genes in turn produce individuals, which are different either at the molecular level or at the organismal level. These individuals may form separate groups within the species itself and such groups are the fundamental genetic units of evolution. These intraspecific groups were called as “stocks” and fishery biologists started using these stocks as a basis to manage commercially important marine organisms. Shaklee et al.  defined Genetic variation in populations became a subject of scientific enquiry in the late nineteenth century prior even to the rediscovery of Mendel's paper in 1900. Genetic variation, in the form of multiple alleles of many genes, exists in most natural populations. In most sexually reproducing populations, no two organisms  can be expected to have the same genotype for all genes . In 1990Genetic markers are basically two types—protein and DNA (molecular). In the beginning of 1960s, the proteins such as haemoglobin and transferrin were involved in all studies. In protein markers, allozyme markers are very popular and most of the genetic variation studies have been conducted based on this marker . MoleculDetection of polymorphisms at the nucleotide sequence level represents a new area for genetic studies, especially as technologies become available, which allow routine application with relative ease and low cost. From the 1990s an increasing number of studies have been published making use of random parts of a genome. With the advent of thermocyclers, the amplification of small fragment of DNA through polymerase chain reaction (PCR) gained popularity. The PCR technique was discovered in 1985 and the development of DNA amplification using the PCR technique has opened the possibility of examining genetic changes in fish populations over the past 100 years or more using archive materials such as scales  and asseRecently, attention has turned to another type of genetic variation that of differences in the number of repeated copies of a segment of DNA. These sequences can be classified based on decreasing sizes into satellites, minisatellites, and microsatellites . SatelliMicrosatellites are short tandemly arrayed di-, tri-, or tetranucleotide repeat sequences with repeat size of 1–6 bp repeated several times flanked by regions of nonrepetitive unique DNA sequences . Polymorn or (GATA)n where n lies between 5 and 50 [Generally, microsatellite loci are abundant and distributed throughout the eukaryotic genome  and each5 and 50 . Within 5 and 50 . Study o5 and 50  showed sThe major advantages of microsatellite markers are codominant transmission (the heterozygotes can be distinguished from homozygotes), locus-specific in nature, highly polymorphic and hypervariable, high information content and providing considerable pattern, relative abundance with uniform genome coverage, higher mutation rate than standard, and easy to sample preparation. Advantages of microsatellites such as short size range, uninterrupted stretches of identical repeat units, high proportion of polymorphisms, insights gained in understanding the mutational process which helps in developing statistical procedures for interpopulation comparisons, their abundance in fish genomes, the availability of methodologies for cloning of microsatellites have all resulted in their abundant use in fisheries research. Tetranucleotide microsatellites are also very useful for paternity and forensic investigations in humans. The advantageous properties of microsatellites have led to modern developments such as digital storage and automated detection and scoring systems such as automated DNA sequences and fluorescent-imaging devices . DisadvaThe high variability, ease, and accuracy of assaying microsatellites make them the marker of choice for high-resolution population analysis . Microsa Dissostichus eleginoides, has been reported by [Gadus morhua). Drinan et al. [ Oncorhynchus clarkia lewisii in 25 populations from four rivers. Davies et al. [ Thunnus and investigated genetic polymorphism at these loci in North Atlantic and Mediterranean Sea populations. In a cichlid, Eretmodus cyanostictus, Taylor et al. [ Channa striata, from Malaysia [ Pseudoplatystoma reticulatum [ Clupea pallasi, collected from 6 sites in Kodiak Island. Similarly, many others have reported studies of polymorphic microsatellite loci to evaluate population structure of different fish species. Thus microsatellite markers have wide range of applications in population genetics and fisheries management.Various authors have reported microsatellite polymorphisms and sequences in some marine and freshwater fish species for population genetic analysis , 50–55. orted by , 57. Simorted by  examinedorted by . Recentlorted by  showed dn et al.  reporteds et al.  identifir et al.  determinMalaysia . SimilarMalaysia ; in neotMalaysia ; in Pseuiculatum . O'Conneiculatum  reported Morone saxatilis that was used to distinguish the four other species. Neff et al. [Lepomis macrochirus) and discussed their evolution within the family Centrarchidae. Kellogg et al.[ Oreochromis niloticus by Lee and Kocher [ Oncorhynchus kisutch [ Salmo trutta [ Catla catla, as potential DNA markers for stock identification. Gopalakrishnan et al. [ Labeo rohita.Salzburger et al.  reportedf et al.  describegg et al. applied d Kocher , while Bd Kocher  reportedd Kocher  reported kisutch , Atlanti kisutch , and in o trutta . Microsao trutta  studied n et al.  and Das n et al.  carried Although microsatellite DNA analysis via PCR is an ideal technique for answering many population genetic questions, the development of species-specific primers for PCR amplification of alleles can be expensive and time-consuming, as it involves construction of genomic libraries, screening of clones with microsatellite sequences, and designing microsatellite primers. However, there are reports which point to the fact that flanking sequences of some microsatellite loci are conserved among related taxa so that primers developed for one species can be used to amplify homologous loci in related species. The method of microsatellite markers development by cross-species amplification is shown in Setaria italica L) were used in studies of other millets and nonmillets species [Schlotterer et al.  found th species . Similar species . Notopterus notopterus, by cross-species amplification of primers developed in 3 fish species of families notopteridae and osteoglossidae. Polymerase chain reaction (PCR) microsatellite multiplex assays were established for genetic studies of the population structure, hybridization and conservation status of European whitefish, Coregonus lavaretus L., and cross-species amplification and rearrangement of the same loci analyzed in C. albula L [ Chondrostoma nasus, Chondrostoma toxostoma, and Leuciscus leuciscus) for the individuals from other different European cyprinid species.A number of attempts have been made to study the cross-species amplification of microsatellite loci in fishes. Recently, Gupta et al.  developealbula L . Dubut ealbula L  have dev Horabagrus brachysoma, an endangered yellow catfish, we have developed eight microsatellite markers from other catfish of order Siluriformes [ Horabagrus brachysoma from the primer developed in African catfish, Clarias gariepinus [ Horabagrus, by using the primers of Siluriformes and Osteoglossiformes [ Acipenser and Scaphirhynchus. Takagi et al. [ Thunnus. Microsatellites from rainbow trout Oncorhynchus mykiss have been used for the genetic study of salmonids [ Salvelinus species using primers of Salvelinus fontinalis, for Brook charr [ Oreochromis shiranus and O. shiranus chilwae by using primers of Nile tilapia [ Oreochromis niloticus microsatellite markers from 15 different African cichlid species was successfully tested and analyzed [ Merlangius merlangus (Gadidae) [ Coregonus nasus [ Carassius auratus, in nine species of cyprinids [ Carassius auratus gibelio and reported eleven out of 15 primer pairs cross-amplified in the genome of common carp (Cyprinus carpio). Zardoya et al. [ C. catla G1 primer in Catla catla from Gobind Sagar, Labeo dero, L. dyocheilus, L. rohita, and Morulius calbasu, and sequenced the loci in these species. Das et al. [ Labeo rohita. Recently, we successfully developed polymorphic microsatellite markers for Gonoproktopterus curmuca through cross-species amplification of primers from other cyprinid fishes [Carassius auratus gibelio) and its successful cross-species amplification have been reported in crucian carp (Carassius auratus) [We have developed several microsatellite markers in different fresh water species by cross-species amplification. Inriformes , 52.  Firiepinus . In addisiformes . May et siformes  reportedi et al.  reportedalmonids , 92. Hetalmonids , for sevok charr  and Oreo tilapia . The croanalyzed . There aGadidae) , that ofus nasus , and priyprinids . Yue et yprinids  developea et al.  through a et al.  have cars et al.  also card fishes , 102. Thauratus) .Microsatellites have become the genetic markers of choice for studies of population differentiation and parentage determination. However, several microsatellite loci are required for such studies in order to obtain an appropriate amount of genetic polymorphism , 104. FoThe microsatellite markers study generate important information on the genetic variation and stock structure of fish species and it is a significant step towards realizing the goal of management of fishery and conservation of the species in their natural populations. The differentiation of a species into genetically distinct populations is a fundamental part of the process of evolution and it depends upon physical and biological forces such as migration, selection, genetic drift, and geographic barriers. Endangered species will have small and/or declining populations, so inbreeding and loss of genetic diversity are unavoidable in them. Since inbreeding reduces reproduction and survival rates and loss of genetic diversity reduces the ability of populations to evolve to cope with environmental changes, Frankham  suggesteFIS) show consequence of genetic bottleneck, resulting from overexploitation and habitat [The effective population size (Ne) should be maintained as large as possible to maximize the contribution of a large number of adults for reproduction so as to maintain natural genetic variability.The causative factors that reduce the effective population size such as overexploitation should be controlled at the earliest.No artificial gene flow between distinct stocks should be created by means of haphazard stocking and rehabilitation programs.The rehabilitation strategy should also include means  to monitor impact of such program.In population genetic analysis, low genetic variability (heterozygote deficiency and deviation from Hardy-Weinberg equilibrium) coupled with inbreeding  or state imposed (formulation and implementation of suitable laws),imposing ban on fishing practices particularly during breeding seasons,stock assessment of different rivers and imposing quota systems for maintaining the population size,banning the sale of undersized specimens,restricting the fishing gear for not catching small and immature fish species and preventing the use of explosives and chemicals for fishing,maintaining minimum water level in the rivers (in case there are dams and weirs) and declaring certain stretches of rivers as sanctuaries.To attain these objectives, it is essential (i) to protect the populations and habitat against anthropogenic stress and (ii) enhance the population through propagation assisted stock-specific rehabilitation programs:Brood stock of fish species collected from different rivers must be tagged and maintained in separate ponds in the holding facility.Effective breeding population size and sex ratio should not be restricted. To achieve this, collection of different size/year classes at different time intervals is to be preferred over the same size/year class.Use of cryopreserved milt, collected from different males and pooled, would be useful for increasing the effective population size and recovery of endangered populations of fish species. In comparison to the captive breeding program, the gene banking through sperm cryopreservation is relatively cheaper, easy to maintain, and less prone to risk due to system failure or mortality due to diseases. Therefore, it should serve as a useful adjunct to the captive breeding program.Different genetic stocks should be bred separately and ranched in the same rivers from where they are collected.Stretches of rivers harbouring resident population or that can serve as a potential sanctuary, may be selected for ranching of fish populations.Assessing the impact of ranching through monitoring the parameters like catch per unit effort/area through experimental fishing should be done.Changes in genetic variation, that is, allele frequencies, especially the occurrence of rare alleles over a course of time , 24 shouThe natural populations of the endangered species can be enhanced by “supportive breeding.” In this program, a fraction of the wild parents are bred in captivity and the progeny are released in natural waters.Microsatellites are very powerful genetic markers for identifying fish stock structure and pedigree analysis and to study the genetic variation of closely related species. Microsatellite markers analysis provides essential information for formulating meaningful conservation strategies for fisheries and aquaculture management. This along with the other technologies like captive breeding and sperm cryopreservation can be integrated into a package for conserving genetic diversity and rehabilitation of the natural populations of fish species.


G (genetic variance–covariance) matrices between native and introduced ranges, and stabilizing selection on fitness-related traits in all populations. We tested these predictions comparing three populations of the worldwide pest Myzus persicae from the Middle East (native range) and the UK and Chile (separately introduced ranges). In general, our results provide mixed support for this idea, but further comparisons of other species are needed. In particular, we found that there has been some limited evolution in the studied traits, with the Middle East population differing from the UK and Chilean populations. This was reflected in the structure of the G-matrices, in which Chile differed from both UK and Middle East populations. Furthermore, the amount of genetic variation was massively reduced in Chile in comparison with UK and Middle East populations. Finally, we found no detectable selection on any trait in the three populations, but clones from the introduced ranges started to reproduce later, were smaller, had smaller offspring, and had lower reproductive fitness than clones from the native range.Most evolutionary research on biological invasions has focused on changes seen between the native and invaded range for a particular species. However, it is likely that species that live in human-modified habitats in their native range might have evolved specific adaptations to those environments, which increase the likelihood of establishment and spread in similar human-altered environments. From a quantitative genetic perspective, this hypothesis suggests that both native and introduced populations should reside at or near the same adaptive peak. Therefore, we should observe no overall changes in the  Biodiversity on Earth is undergoing unprecedented transformation as the result of the effects of human activities on all kinds of ecosystems Vitousek . AlthougG, the additive genetic covariance matrix  selection acting on heritable variation. Furthermore, when different traits share a genetic basis, summarized by genetic covariation, both the direction and rate of evolution can be facilitated or constrained Schluter . The infrix Roff  that shoMost evolutionary research on biological invasions has focused on changes seen between the native and invaded range for a particular species. However, it is likely that species that live in human-modified habitats in their native range might have evolved specific adaptations to those environments, which increase the likelihood of establishment and spread in similar human-altered environments in the new range. Although to the best of our knowledge direct tests of this idea are lacking, good candidate systems to evaluate it are crop pests.Myzus persicae is recognized as one of the most important agricultural pests in the world , associated with the presence of its primary host, the peach Prunus persica  are among the most successful herbivorous pest insects , the UK (introduced range), and Chile, where M. persicae was introduced less than 100 years ago, probably in the central part of the country . Thus, we assume that the ME genotypes belonged to the native and both UK and Chile are “invaded” ranges.We tested those predictions using M. persicae can be found elsewhere . Each lineage was established from a single adult parthenogenetic wingless female. Aphid lineages were reared at 20 ± 1°C and LD 16:8 to ensure parthenogenetic reproduction, by transferring five wingless adults to new seven-day-old pepper seedlings every 10 days. Aphid colonies were reared on pepper seedlings for at least 10 generations before the experiments were done.Detailed information regarding sampling locations, maintenance conditions, and microsatellite genotyping for Chilean Myz2, Myz3, Myz25, M35, M37, and M40)  followed Castañeda et al. . From earm) was determined according to Wyatt and White /AFR, where 0.74 is a correction factor.The intrinsic rate of natural increase (nd White . We detehttp://rsb.info.nih.gov/ij/). The average of those 3–5 offspring was used in all statistical analyses. Adult body mass was determined on a MXA5 microbalance . Aphids were cooled on ice for a few seconds and weighed to the nearest microgram.Size at birth was determined in 3–5 offspring individuals of the F4 generation. Each offspring was put on their back on a glass slide, and a digital picture of the right hind tibia was captured at 40X magnification (Olympus SZ6145TR Optics). Tibia lengths were obtained using the public software Image-J . Family means among regions  were compared using a general linear model. Multiple comparisons of means were carried out with Tukey's contrasts, and results are presented as difference in standard deviations ± SE. As the Chilean data contain only two aphid genotypes with a widespread distribution  or not . Thus, linear (β) and quadratic (γ) selection gradients were estimated by a forward stepwise regression model selection. Terms were added to the final model if they significantly contributed to a reduction in residual variation using F-tests. All analyses were carried out using R 2.15.0 , therefore suggesting that there is no evidence for a latitudinal cline  and Chile , and marginally lower in Chile than in ME . As age of first reproduction is negatively correlated with individual rm, then the ME clones matured earlier , but there was no significant difference between the UK and Chilean clones . The ME clones were larger than both the UK and Chilean clones , while there is no evidence to suggest that the UK and Chilean clones differed significantly . Finally, the average size at birth was smaller in the Chilean clones , but there was no significant difference between the clones from UK and the ME . Overall, the ME clones started to reproduce earlier, got bigger, had bigger offspring, and had higher reproductive fitness than both the UK and Chilean clones , with a clear pattern that follows the time since the original colonization: Mean heritability was 0.56 in ME, 0.35 in UK, and 0.13 in Chile. Genetic covariances were small, which resulted in low correlation estimates with wide credible intervals that included zero in all cases. It is likely that these results reflect low statistical power due to the small number of clonal families used .Genetic variances and covariances are presented in Table We found a significant Ovaskainen D between Chile and UK, which indicates that, in overall, matrices were different Table . However2 for size at birth is lowest for this trait. Third, the genetic variance associated with each tensor is, as revealed in the matrix comparisons, highest in the ME site  these changes are largely tied to changes in size at birth.The tensor analysis Table  revealedP > 0.05), which suggests that all phenotypic variation for these traits in the introduced regions is at, or practically at, the optimum. For the Middle East, the best-supported model was the one that included directional selection on size at birth .For Chile and the UK, there was no evidence for directional or stabilizing selection on any trait . Thus, it may be that our hypothesis should be more nuanced regarding change.We evaluated the hypothesis that species that live in human-modified habitats in their native range might have evolved specific adaptations to such environments, which increase the likelihood for establishment and spread in similar altered environments in the new range. If true, under a quantitative genetic framework we should observe no overall changes in the structure of M. persicae through the country, we compared the means of the 4 fitness-related traits among the three geographic zones in Chile, which encompass the whole distributional range of the species. We found no information to suggest a genetically based latitudinal cline in any of the studied traits. Interestingly, these results support aspects of the hypothesis at a local scale, namely that populations are at a similar adaptive peak. In this context, it does not seem that rapid evolution within the introduced range was required for the invasion success of this species. Adaptive evolution during the expansion phase depends on the current amount of genetic variation in founder populations and the relative role of other factors at the founding processes . Although we lack molecular data, our results strongly suggest a strong founder effect, as the overall amount of genetic and phenotypic variation for all traits in Chile is extremely low in comparison with populations in the Old World (see below).Evolutionary inferences can be blurred when latitude is a confounding factor , particularly in Chile. However, our results also indicate that evolutionary change might be occurring in the native M. persicae range as we detected directional selection for smaller size at birth in the Middle East clones. The cause of that selection and why it differs from the introduced populations remains unclear.It is difficult to unambiguously determine the direction of evolutionary change in our populations, as there was not a clear pattern of change in the means of the studied traits. Furthermore, there are several selective factors that might vary either temporally or spatially  and thus that might be responsible for genotypic selection in the field  may affect the phenotypic expression of the studied traits and thus the estimated differences between regions and their biological interpretation  while both have much more variation than Chile  (Margaritopoulos et al. Comparison of the genetic architecture complements well the previous findings and offers no strong support for the hypothesis evaluated; ile Fig. . Thus, oile Fig. . Therefo


Low cost genotyping of individuals using high density genomic markers were recently introduced as genomic selection in genetic improvement programs in dairy cattle. Most implementations of genomic selection only use marker information, in the models used for prediction of genetic merit. However, in other species it has been shown that only a fraction of the total genetic variance can be explained by markers. Using 5217 bulls in the Nordic Holstein population that were genotyped and had genetic evaluations based on progeny, we partitioned the total additive genetic variance into a genomic component explained by markers and a remaining component explained by familial relationships. The traits analyzed were production and fitness related traits in dairy cattle. Furthermore, we estimated the genomic variance that can be attributed to individual chromosomes and we illustrate methods that can predict the amount of additive genetic variance that can be explained by sets of markers with different density.The amount of additive genetic variance that can be explained by markers was estimated by an analysis of the matrix of genomic relationships. For the traits in the analysis, most of the additive genetic variance can be explained by 44 K informative SNP markers. The same amount of variance can be attributed to individual chromosomes but surprisingly the relation between chromosomal variance and chromosome length was weak. In models including both genomic (marker) and familial (pedigree) effects most (on average 77.2%) of total additive genetic variance was explained by genomic effects while the remaining was explained by familial relationships.Most of the additive genetic variance for the traits in the Nordic Holstein population can be explained using 44 K informative SNP markers. By analyzing the genomic relationship matrix it is possible to predict the amount of additive genetic variance that can be explained by a reduced (or increased) set of markers. For the population analyzed the improvement of genomic prediction by increasing marker density beyond 44 K is limited. Low cost genotyping of individuals or families using genomic markers with constantly increasing density is currently being introduced in genetic improvement programs for agricultural animal and crop species. Use of dense genomic markers can increase the accuracy of predicting additive genetic merit especially for selection of candidates that do not yet have own or progeny records . Such apThe current industry standard in dairy cattle breeding is use of 50 K chips such as the Illumina Bovine SNP50 BeadChip  but otheIn human genetics very high density chips have been used in large scale studies . HoweverAs mentioned above the total variance explained by previously identified causal loci is usually only a small fraction of total genetic variance in the populations investigated. In GWAS very stringent significance thresholds are necessary due to the very large number of statistical tests that are conducted when searching the whole genome using high density SNP marker panels. This will only allow loci with large effects to become statistically significant. However,  showed tIf not all genetic variance can be explained by markers then, in order to ensure optimal predictions, the remaining genetic variance should be accounted for in other ways. A simple approach is to combine predicted breeding values based on genomic information with traditional breeding values based on pedigree using selection index theory . An alteRecently, ,20, propThe purpose of this study was to evaluate the amount of additive genetic variation in production and fitness related traits in dairy cattle, to quantify the amount of additive genetic variation that can be explained using genomic markers with different density, and to quantify the amount of genomic variance that can be ascribed to individual chromosomes. The value of increasing the density of marker information for predicting genetic merit was also assessed using subsets of available markers.DRP) were used as response variable in the present study, which were derived from the Nordic Holstein genetic evaluations official spring 2011 run. Production traits included milk production (milk), fat production (fat), protein production (protein). Fitness related traits included female fertility (fertility), other diseases than mastitis , and mastitis (mastitis). The specific trait definitions and recording procedures are detailed in http://www.nordicebv.info/Forside.htm and G) do notprotein to 106.3% for mastitis  were run. In this model the covariance among animals due to additive genetic relationships and due to genomic relationships (markers) both were included. Averaged across all traits total genetic variance estimated in model (3) was 101.7% of total genetic variance estimated in the animal model (1) with a range from 98.4% for Results from analysis using model (4), where genomic variance due to individual chromosomes were estimated, is also summarized in Table milk and fat were found on chromosome 14 where it is known that a gene of very large effect segregates in the Holstein population [R2 values for a linear regression model of chromosomal variance on chromosome length varied between 0.11 and 0.21  by varying the number of markers used to compute the genomic relationship matrix. Results averaged over all traits are shown in Table  by varyiDRPs which were derived from the routine genetic evaluations of dairy cattle in Denmark, Sweden and Finland. Such DRPs are similar to progeny group means adjusted for non-genetic effects. Therefore, a very large proportion of phenotypic variance in analyzed DRP was due to additive genetic effects. For all traits analyzed more than 92% of all additive genetic variance could be explained using 44 K SNP markers. For models including both polygenic additive genetic (pedigree) effects and genomic (marker) effects, the latter accounted for between 71% and 85% of all additive genetic variance. Estimation of genomic variance of each individual chromosome showed that 96%–97% of all genomic (marker) variance could be attributed to individual chromosomes. Inclusion of polygenic familial effects in the models ensured that potential linkage disequilibrium across chromosomes was already taken into account. Most of the additive genetic variance in the population analyzed could be explained by genetic markers. The effect of reducing (increasing) the number of genetic markers on genomic prediction could be predicted by estimating the accuracy of the genomic relationship matrix.The records analyzed in this paper were milk, fat, and protein) the additive genetic variance was between 91% and 97% of total phenotypic variance. The high level is expected because of the large sizes of progeny group used in the testing procedures for dairy bulls in all the Nordic countries and because of the high heritability of the underlying traits. For the fitness related traits  the relative amount of additive genetic variance is lower reflecting the lower accuracy of fitness related DRP.Most of the total phenotypic variance in the traits analyzed was additive genetic due to the use of deregressed proofs, which average out any dominance deviations across multiple daughters. Such proofs, of course, are functions of the procedures and definitions used in the recording system and methods used in the genetic evaluation. For production traits  yields unbiased estimates of population additive genetic variance. Comparing results from model (2) (genomic model) with results from model (1)  clearly illustrates this. For the traits milk and fat 97% of the additive genetic variance can be explained by markers. The estimates of additive genetic variance due to individual chromosomes clearly show that these traits are influenced by a major gene that contributes to the large proportion of additive genetic variance. Statistical models fitting effects of individual marker genes might be a better alternative in these cases.protein and fertility the amount of additive genetic variance that can be explained by markers is somewhat lower than for milk and fat. This indicate that models used for these traits should include an effect to account for additive genetic effects not accounted for by markers or alternatively more markers are needed to ensure that most of the additive genetic variance can be explained by markers. This is clearly seen from the results of model (3) where both marker effects and classical polygenic familial additive genetic effects were included in the model. However, in general, a large proportion of the total additive genetic variance was explained by markers in this study. This is in considerable contrast to [e = 49 [For trast to  who foun Ne = 49 , whereasWhen summing over chromosomes the estimates of genomic variance due to individual chromosomes yielded total genomic variances that were similar to the total genomic variance in model (2) where this quantity was estimated directly. The method therefore seems able to yield estimates of genomic variance due to individual chromosomes. Surprisingly the estimates of variance due to individual chromosomes only showed a weak relationship with chromosome length Figure . The resObviously genetic markers cannot explain more than all the total (additive) genetic variation present in the population. The analysis of the genomic relationship matrices revealed that a large proportion of the total additive genetic variance in the Nordic Holstein population was expected to be explained by a set of 44 K markers. Analysis of both production and fitness related traits showed that the amount of variance accounted for by markers in the Nordic Holstein population was close to the expectations from regression based analysis of the genomic relationship matrix. Estimates of genomic variance closely followed expectation when the number of markers included in computation of genomic relationship matrix was varied. The amount of additive genetic variance that can be explained by genomic markers depends on several factors: Number of markers on causative sites, markers in linkage disequilibrium with causative genes due to close “historical” linkage at population level, and finally linkage disequilibrium among markers and genes at family level, due to the family structure in the population. With 44 K markers spread over the genome the number of markers within causative sites probably is limited. The linkage disequilibrium between markers and causative genes is very dependent on effective population size . The HolThe analysis of genomic relationship matrices showed that a high proportion of additive genetic variance can be expected to be explained using 44 k genomic markers in this population of dairy cattle. This leaves limited room for further improvements of predictive ability of genomic models by including more markers. One of the current trends in use of genomic markers is to move from 50 K marker chips to 800 K marker chips or even complete sequencing of whole genomes for individual animals. Our results indicate that the advantages of this route may be limited. In fact including several orders of more markers than used in this study may turn out to be counterproductive. Extremely dense markers will include more markers on most causative sites and given knowledge of variation in the causative genes there is no extra information in the remaining markers. Alternative models that better can distinguish between causative genes and non informative markers might be of great value in futureAnalysis of the structure of the genomic relationship matrices might be of considerable value in deciding on avenue for future development of typing strategies when using genomic markers. Such analysis also could give extra insight in the effects of population structure and population history on effectiveness of future selection programs using genomic selection in other breeds or in other species.In summary we estimated the amount of additive genetic variance that can be explained using dense SNP marker panels. In the Holstein population analyzed, almost all the additive genetic variance could be explained using 44 K SNP markers. The amount of additive genetic variance that is expected to be explained by markers could be predicted from analysis of the genomic relationship matrix. Further increases in marker density will have limited effects on predictive accuracy unless better methods distinguishing between markers with real effects and markers with no effect are used. Results presented in this study can be used to determine the weight given to marker relationships and to familial relationships in one step prediction methods where these sources of relationships are combined and in two step methods where information based on genomic relationships must be combined with information form polygenic relationships.Milk: Milk production; Fat: Fat production; Protein: Protein production; Fertility: Female fertility; Health: Veterinary treatments for diseases other than mastitis; Mastitis: Mastitis.GS: Genomic selection; DRP: Deregressed proof; The authors declare no competing interests.JUJ conceived the study and conducted all analysis, GS developed and implemented algorithms for computing genomic relationship matrices and PM maintained the DMU software package used in the statistical analysis. JUJ edited the manuscript based on extensive input from all authors who have read and approved the final manuscript.


Eucalyptus parent trees and indicated those to be preferentially crossed in a recombination process to potentially maximize variation in the offspring for individual selection of clones.To obtain genetically superior cultivars in a breeding program, methods and procedures are necessary to allow the identification of selected individuals over several cycles of selection while at the same time maintain broad genetic base of the breeding populations. This is crucial to guarantee continuous genetic gains along the program. The establishment of efficient breeding strategies depends on methods and analytical tools. The assessment of genetic diversity with molecular markers of parents used in mating designs could aid optimizing the recombination phase. Microsatellites provide good information content and require small amounts of DNA and may be transferable between species of the same genus. In this study we evaluated the genetic diversity in a set of Eucalyptus grandis and E.urophylla. Genomic DNA was extracted from leaves and amplified with microsatellites developed during the Genolyptus project and previously used for Eucalyptus spp[A total of 20 genotypes were selected from 44 families obtained by crossing 24 parents in different types of hybridizations of populations of yptus spp. The ampThis study showed wide genetic diversity among the 20 genotypes under evaluation; all nine SSR loci analyzed were polymorphic, with a total of 77 alleles. The number of alleles per locus ranged from 5 (EMBRA 646) to 10 (Embra 645) averaging 9.1. The lowest value of polymorphism was obtained for marker EMBRA 915 (PIC = 0.59) and higher for the marker EMBRA 645 (PIC = 0.89). The expected heterozygosity ranged from 0.66 to 0.89, averaging 0.80. Based on genetic distances, the 20 genotypes were clustered into six distinct groups. The greatest genetic distance was observed between genotypes C022H (GIV) and M4320G (GVI), and the smallest among genotypes P023H (GI) and C407 (GII). Group II clustered the largest number of genotypes , consistent with the fact that these genotypes are considered to belong to the same "heterotic" group by the breeders. Based on the genetic distances, the following trees were selected to be preferentially crossed: M4320H, P4295H, P082G, VR3709H, C053H, C219H, C041H and C022H. It remains to be seen if the progenies derived form these crosses will in fact display a wider segregation and allow, as expected, effective selection of extreme phenotypes for growth and wood quality.