Cheirolophus (Asteraceae) in Macaronesia constitutes a spectacular case of rapid diversification on oceanic islands. Twenty species – nine of them included in the IUCN Red List of Threatened Species – have been described to date inhabiting the Madeiran and Canarian archipelagos. A previous phylogenetic study revealed that the diversification of Cheirolophus in Macaronesia started less than 2 Ma. As a result of such an explosive speciation process, limited phylogenetic resolution was reported, mainly due to the low variability of the employed molecular markers. In the present study, we used highly polymorphic AFLP markers to i) evaluate species' boundaries, ii) infer their evolutionary relationships and iii) investigate the patterns of genetic diversity in relation to the potential processes likely involved in the radiation of Cheirolophus. One hundred and seventy-two individuals representing all Macaronesian Cheirolophus species were analysed using 249 AFLP loci. Our results suggest that geographic isolation played an important role in this radiation process. This was likely driven by the combination of poor gene flow capacity and a good ability for sporadic long-distance colonisations. In addition, we also found some traces of introgression and incipient ecological adaptation, which could have further enhanced the extraordinary diversification of Cheirolophus in Macaronesia. Last, we hypothesize that current threat categories assigned to Macaronesian Cheirolophus species do not reflect their respective evolutionary relevance, so future evaluations of their conservation status should take into account the results presented here.The radiation of the genus  Argyranthemum Webb, Sonchus L. alliance, Aeonium Webb & Berthel., Echium L., Tolpis Adans., In the last two decades, the Macaronesian archipelagos  have attracted much interest from researchers studying plant diversification and radiation processes Occasionally, island radiations occur over a short period of time, resulting in ecologically and morphologically distinct taxa, but leading to poor molecular differentiation Cheirolophus Cass. (Asteraceae) complex comprises 20 species (out of the 30 constituting the whole genus), with Cheirolophus massonianus (Lowe) A.Hansen & Sunding occurring in the Madeiran archipelago, and the remaining species distributed across the western Canary Islands  Holub from Tenerife), whereas others are found on two different islands (e.g. C. teydis (C.Sm.) G.López from Tenerife and La Palma and C. massonianus from Madeira and Porto Santo). However, most species are narrow endemics occurring in a small number of restricted localities with only a few hundred or less individuals. Consequently, nine Macaronesian species have been included in the IUCN Red List of Threatened Species The Macaronesian ands see . AlthougCheirolophusCheirolophus radiation. The age of this group was estimated to be 1.74 Ma (95%HPD 0.82–2.93), implying a diversification rate of 0.34–2.84 species Myr−1. Indeed, this diversification rate is comparable to those exhibited by the Hawaiian Bidens L. (0.3–2.3 species Myr−1) or Macaronesian Echium (0.4–1.5 species Myr−1), considered as the fastest plant radiations on volcanic islands documented to date CheirolophusCheirolophus.Several investigations based on morphological, cytogenetic, isozymes and DNA sequencing data have been previously used to infer evolutionary relationships and taxonomy for the 29 currently recognized species of Amplified fragment length polymorphism (AFLP) analyses have been found to provide insights into interspecific relationships in diverse animal and plant groups when other methodologies have failed in this attempt e.g. . Indeed,Cheirolophus underwent in the Canarian and Madeiran archipelagos. We applied phylogenetic and population genetic approaches to (i) evaluate the taxonomic identity of the Macaronesian species and to (ii) disentangle the evolutionary relationships between them. Additionally, we studied the patterns of genetic diversity within and between populations to (iii) infer the role of the evolutionary processes potentially involved with this explosive radiation .AFLP fingerprinting – complemented with morphological and other molecular data – was employed here with the main objective of unravelling the explosive radiation that Cheirolophus species were sampled, covering the whole taxonomic diversity recognized for the Madeiran and Canarian archipelagos (see C. dariasii (Svent.) Bramwell; C. cf. webbianus); (2) the inclusion of that particular population was essential to understand the distribution of the species ; or (3) the additional subpopulation completes the sampling of extremely local species (C. metlesicsii Parada). Leaf material for DNA extraction was collected from plants in the field, dried in silica-gel and stored at room temperature. Insular Cabildos of Tenerife, Gran Canaria, La Gomera, La Palma and El Hierro provided all the necessary permits to collect samples from protected natural areas in the respective islands. The Canarian Council of Education, University and Sustainability issued the authorization to collect samples of the protected species listed on C. massonianus were provided by the Botanical Garden of Madeira.One hundred and seventy-two individuals from 29 populations of 20 Macaronesian EcoRI and MseI with 500 ng of isolated genomic DNA per sample. Eighteen primer pair combinations were tested on six individuals from three different populations to screen those producing the most informative and readable profiles. Three pairs of primers were selected giving the most polymorphic and scorable polymorphic pattern: EcoRI-CTT/MseI-AC; EcoRI-CTC/MseI-AA; and EcoRI-CAG/MseI-AT. The success of each step was tested by running the PCR products on a 1.5% agarose gel. Fragments were run on an ABI Prism 3100 Genetic Analyzer (Applied Biosystems Inc.) with 10 µL of High Dye (deionized formamide) and 0.2 µL of GeneScan 500 ROX Size Standard per sample. Amplified fragments were genotyped as present/absent using GeneMarker AFLP/Genotyping software .Genomic DNA was extracted from fragments of silica-gel dried leaf tissue following the protocol of Doyle and Doyle For an initial scoring, all alleles within a range of 50 to 490 bp were considered. Afterwards, visual correction was carried out to eliminate erroneous peaks (low intensity or no reproducibility). AFLP error rates were calculated following Cheirolophus. Only those populations  for estimating allelic frequencies implies the consideration of an outcrossing mating system and near random mating. This means that those populations would be under Hardy-Weinberg equilibrium http://www.pierroton.inra.fr/genetics/labo/Software/Aflpdiv/). As a consequence, Br and PLP were not calculated for populations having less than three individuals. To assess whether genetic diversity indexes  differed among islands, diversity range values were compared in a non-parametric Kruskal-Wallis test using package RCMDR To estimate genetic diversity in each population showing more than one sampled individual, the following parameters were calculated: a) private alleles; b) rare alleles, present in <10% of the samples; and c) unbiased heterozygosity (Hj), calculated using TFPGA v.1.3 FST values were estimated for each pair of populations included in this study  and Bayesian inference methods. NJ trees were built using Nei-Li distances Additionally, non-tree-building approaches have been recommended to avoid conflicting phylogenetic signals in those cases in which the analyses of the data do not exhibit a bifurcating tree-like behaviour C. massonianus from Madeira – were constructed with FST values between populations, and geographical matrices were calculated by the spatial distance (X and Y coordinates) between populations using ArcGIS v.9.1 . Mantel tests were performed with the vegan package p-value limit of 0.05. Because most populations were from the Canary Islands and only two of them are from Madeiran archipelago, distant from the remainder (>500 km), the Mantel test analysis was repeated without these populations.We performed Mantel tests to evaluate the spatial effect in the genetic differences between populations using two similarity matrices. Genetic distance matrices – with and without K) from K = 1 to 29, using a burn-in period of 105 generations and run lengths of 5×105. To estimate the number of genetic groups (K) we selected the K value that maximizes the probability of the data L(K). We also considered the criterion proposed by Evanno et al. K for our data set, based on the rate of change in the probability between successive K values, ΔK. Bayesian analyses of the genetic structure were also conducted with BAPS  set from 1 to 29. Each run was replicated 10 times, and the results were averaged according to the resultant likelihood scores. The output of the mixture analyses were used as input for population admixture analysis Bayesian clustering analysis were carried out using STRUCTURE v.2.3 Some authors have warned about a degree of over-splitting in the genetic structure analysed with AFLP markers e.g.  and haveCheirolophus according to: i) their current taxonomic affiliation; ii) their island origin; iii) the most plausible model proposed by STRUCTURE; and, iv) the clustering proposed by BAPS. Pair-wise genetic distance between individuals using the square Euclidean distance was used for the AMOVA analyses, considering three levels: within populations, between populations within regions and between regions. Only two levels (within and between populations) were considered when no additional grouping structure was applied.Finally, we conducted analysis of molecular variance AMOVA;  using ARCheirolophus were also analysed in this study. Morphological traits were measured from herbarium vouchers, cultivated individuals and/or gathered from the literature depending on the species. In the present study, morphological data was only considered for a given species when at least three different individuals where available for measurements. We obtained accurate data from 16 species for six morphological variables widely employed to distinguish among Canarian Cheirolophus taxa  and six morphological traits (see above) was tested by running a regression matrix with a permutation test with 10000 repetitions.In order to correlate genetic AFLP data with morphological traits, we carried out Mantel tests and a generalized analysis of molecular variance GAMOVA; . Mantel e AMOVA;  that couInitially, 371 alleles were obtained from automatic genotyping. After manual correction, error rates calculation, elimination of small and troublesome alleles and low intensity peaks, a final matrix with 249 (67.1%) alleles were considered for subsequent analyses. The final data set obtained showed an error rate of 3.2%, which is below the maximum error rate percentage accepted for good AFLP reproducibility (5%) C. santos-abreui A.Santos, C. satarataensis (Svent.) Holub and C. tagananensis (Svent.) Holub populations. The frequency of rare fragments was, conversely, much higher (10.6%), but most of these were shared by two or more populations. Hj diversity values were similar in all populations, ranging between Hj = 0.0459 (C. duranii (Burchard) Holub), and Hj = 0.1539 (C. arboreus (Webb & Berthel.) Holub from Los Tilos) in populations with more than three sampled individuals, with a mean value of Hj = 0.07892. The frequency-down-weighted marker values (DW) index showed overall high values, but considerable differences were observed among populations (ranging from 8.65 in C. junonianus (Svent.) Holub var. isoplexiphyllus to 19.75 in C. webbianus). The percentage of polymorphic loci (PLP %) ranged from 10.1% in C. duranii to 77.0% in C. arboreus (Los Tilos), and band richness (Br) ranged from 1.08 in C. junonianus var. junonianus to 1.46 in C. arboreus (Los Tilos). The DW was the only diversity index showing significant differences among islands ; La Palma populations showed the lowest DW values. Pair-wise FST comparisons were significant . The biggest difference was found between C. puntallanensis A.Santos and C. arbutifolius (Svent.) G.Kunkel (FST = 0.577). The pair-wise comparisons between populations of the same species were much smaller than those between species (e.g. mean FST = 0.055 between C. ghomerythus (Svent.) Holub populations).Within-population genetic diversity measures are shown in C. duranii from El Hierro  or species from the Teno mountains , in both cases from Tenerife. The phylogenetic analyses also confirmed the close relationship between C. satarataensis and C. dariasii (PP = 1.00), until recently considered as subspecies of the same species. The two populations of C. teydis from Tenerife and La Palma grouped together but were not embedded in a resolved clade. Similarly, C. arbutifolius and C. falcisectus Svent. ex Montelongo & Moraleda (both from Gran Canaria) appeared closely related (PP = 0.84) but their phylogenetic position in the genus was not fully resolved.Trees constructed with the combined AFLP data using NJ and Bayesian estimation had generally similar topologies. Tree-building analyses of AFLP data resulted in similar fully-resolved assignment of individuals into species classically identified by diagnostic morphological and ecological characters (e.g. Bayesian 50% majority rule tree in C. duranii). Those inhabiting eastern Tenerife  and western Tenerife (C. canariensis and C. burchardii) were also segregated into regional clades already resolved in the Bayesian and NJ phylogenetic analyses. Neighbor-Net analysis also revealed some phylogenetic conflicts not identified in the tree building analyses. For example, the species from El Hierro (C. duranii) showed clear reticulation, with an intermediate position between La Palma cluster and a lineage grouping two species from La Gomera (C. satarataensis and C. dariasii). Finally, NN analyses suggested a degree of reticulated connection between C. ghomerythus (from La Gomera) and C. massonianus (from Madeira), but this potential relationship was not supported by any Bayesian approach.The Neighbor-Net (NN) analysis, although indicating considerable reticulation in the data, resolved most of the species groups according to their current taxonomic boundaries . In addiFST distances, and the matrix of geographical distances in kilometres, the Mantel test indicated a significant correlation between genetic and geographical distances . Similar results were obtained if the Madeiran populations were excluded from the analysis .Using the matrix of inter-population K) and ΔK values for K = 2. This grouping separated La Palma species (plus C. duranii from El Hierro) – cluster A – from the rest of the species from Tenerife, La Gomera, Gran Canaria and Madeira  – cluster B –, showing high percentages of individual memberships  for these predefined groups  levels of admixture among the two genetic groups detected (between 14.9% and 34.3%). BAPS results showed a more fragmented distribution, with K = 11 as the most plausible number of clusters . Using geographical origin  as the grouping criterion revealed slightly lower, but also significant, genetic variance (23.59%) among sites. According to the structure proposed by the Bayesian clustering analyses, genetic differentiation among groups explained 18.73% of variation  and 33.29% of variation .The results of non-hierarchical AMOVA indicated a highly significant level of genetic structure among populations  with the first axis, led to the distinction of four discrete clusters of species from: i) Tenerife and Gran Canaria; ii) La Gomera; iii) La Palma and El Hierro; and iv) Madeira.The PCoA using the first three principal coordinates explained 32.8% of the total variation in the data and confirmed several relationships detected in the phylogenetic and cluster analyses . The firp-value>0.05), nor did any of the GAMOVA analysis show significant results for the morphological variables considered .The two first principal components represented 60% of the total morphological variation in the data set . The firThe analysis of nrDNA sequences from Cheirolophus in Macaronesia revealed different but complementary patterns, supporting the complex evolutionary history previously suggested for the genus in the archipelago Cheirolophus.The performance of diverse methods to analyse AFLP data sets has been found to be particularly important in evolutionary studies of plant radiations Cheirolophus, but assignment methods provided further evidence on the evolutionary relationship between different lineages. The model proposed by STRUCTURE (K = 2) identified a major geographical division, with the western islands  clustering independently from the Central-Eastern ones , that grouped together with Madeira (K = 11), suggesting as well significant influence of allopatric speciation in the evolutionary history of Macaronesian Cheirolophus. The species from Tenerife are grouped in three clusters corresponding to well differentiated regions of the island. One cluster comprised the taxa inhabiting mainly the eastern part of Tenerife . Another cluster groups C. canariensis and C. burchardii from the Teno mountains, at the western end of the island. This eastern/western pattern of geographic distribution in Tenerife has been recovered in other studies of several plant groups (see Cheirolophus lineages from eastern and western Tenerife could be related to connection-isolation cycles caused by volcanic activity during the last 2 My C. teydis from Tenerife (Las Cañadas) and La Palma, all of them living around the subalpine zone (1800–2200 m) on both islands. The representatives from Gran Canaria were placed together by BAPS in a separate cluster. This result may support the recent hypothesis of a single colonisation event for this island and the subsequent diversification process giving rise to C. arbutifolius and C. falcisectusC. ghomerythus from the northern coast of the island and the other one embedding C. satarataensis and its former subspecies C. dariasii, from the south and south-west of La Gomera. Certain evolutionary closeness among the two lineages from La Gomera was detected in the PCoA analyses, but their monophyly could not be confirmed. BAPS method also differentiated four geographically-related clusters of species in La Palma: C. junonianus from the south of the island; C. arboreus from the north and the west; C. santos-abreui, C. puntallanensis and C. sventenii (A.Santos) G.Kunkel from the north and north-eastern part of La Palma; and C. teydis from the summits of this island (and from Las Cañadas in Tenerife). Finally, C. duranii from El Hierro and C. massonianus from Madeira grouped in two separate clusters, suggesting as well that geographic isolation has been involved in the radiation of the genus.AFLP analyses were not able to thoroughly disentangle the phylogeny of Macaronesian  Madeira . This ge Madeira  and is s Madeira  and 3. CCheirolophus. Unfortunately, straightforward evidences of LDD are very difficult to obtain Cheirolophus might have the potential to undergo successful LDD events. Birds and lizards have been found to be involved in seed long- dispersal of multiple species in the Canary Islands Carduelis carduelis L.) has been observed in the Canary Islands feeding on Cheirolophus seeds Cheirolophus was also pointed by Garnatje et al. C. intybaceus (Lam.) Dostál. Finally, viable seeds from another Centaureinae species have been recovered from lizard guts discarded by predatory birds in the Canarian archipelago Cheirolophus. All these data suggest that Cheirolophus achenes may be able to be transported through long distances but, given the lack of strong direct evidences in our case study and the inherent stochasticity of LDD process According to these results, sporadic long-distance dispersal (LDD) events have to be considered to explain the numerous intra and inter-island colonisations resulting in the current distribution of genetic and taxonomic diversity in Macaronesian Cheirolophus could also be enhanced by certain intrinsic biological features showed by this group of plants. The genus presents a pseudo-self-compatible mating system Cheirolophus; a hypothesis apparently supported by additional bibliographic evidences suggesting a certain degree of ability for successful long-distance colonisation events in the genus.Furthermore, the capacity for successful long distance colonisation in Cheirolophus are influenced by geographic-genetic correlation across species. In particular, our results indicate that the more closely evolutionary-related species are as well geographically closer to each other, which is in good agreement with a gene flow scenario dominated by short distance events Cheirolophus has been reported to be limited to very short distances  could be related to the additive effect of poorly connected habitats with the limited seed dispersal capacity of Cheirolophus.Genetic isolation has been proposed as a major factor determining plant speciation on oceanic islands Cheirolophus revealed overall low levels of genetic diversity. This result is in accordance with the general expectation that endemic species, and particularly island endemics C. anagaensis, C. duranii, C. junonianus, C. massonianus, C. cf. sp. nova, or C. tagananensis) show lower genetic diversity levels than species with numerous, widely distributed populations . However, this expected pattern is contradicted by certain populations of widely distributed species  also showing lower genetic diversity values. Considering the limited number of sampled populations per species and the low number of individuals available, these indices could be underestimating genetic diversity, particularly in these widespread species. We found only three populations showing private fragments, probably due to the low sampling size within some populations and the strict choice of polymorphic bands.Our analysis across the whole distribution range of Macaronesian Cheirolophus can also be compared with the values reported by Garnatje et al. C. intybaceus, which includes some taxa distributed in the eastern Iberian Peninsula and the Balearic Islands. Diversification in the C. intybaceus complex presumably started in the same period as the Macaronesian radiation C. intybaceus complex. Lower genetic variation has been associated with species showing limited geographical distribution, smaller populations and exhibiting little gene flow Cheirolophus – distributed in small populations across islands with steeply dissected topography – have been comparatively more isolated than Mediterranean ones, thus contributing to their progressive genetic divergence. As it has been proposed for other plant groups by Ellis et al. Cheirolophus in Macaronesia.Some of the genetic diversity indices studied in the Macaronesian Cheirolophus in the Macaronesian archipelagos can be considered an example of non-adaptive radiation occurred on oceanic islands. Indeed, most species of this group exploit very similar niches in different islands, showing minor morphological differences. However, Macaronesian Cheirolophus present as well a few cases of taxa that have apparently adapted their morphology to the significantly diverse ecological conditions found on these archipelagos. Cheirolophus teydis is the only species of the genus that occupies the subalpine habitat, showing morphological adaptations to tougher ecological conditions . The species from Gran Canaria – C. arbutifolius and C. falcisectus – are the result of a diversification process originated after a single colonisation of the island (see above). These species have diverged into different niches allopatrically within the same island – C. falcisectus inhabits more xeric habitats and shows clear leaf reduction while C. arbutifolius occupies more humid locations and present an arborescent habit and a larger leaf surface – thus suggesting an additional example of ecological differentiation. A similar case of ecological adaptation can be found in La Palma, where C. junonianus – from the south of the island and inhabiting significantly more arid localities than the rest of species from the northern part of this island – shows parallel morphological adaptation in size and leaf shape to drought conditions. Equivalent eco-morphological responses have already been reported in other Macaronesian plant taxa that have undergone an adaptive radiation process , whilst species showing similar habitats and morphological features frequently belong to very different genetic clusters/lineages . These patterns suggest that the few cases of ecological adaptation (cited above) do not seem to be the result of a single eco-morphologic shift occurring at initial stages of the Macaronesian Cheirolophus diversification, but they may correspond to more recent, multiple and independent phenotype-environment differentiation processes.Geographic isolation may have been important for enhancing diversification but ecological adaptation is as well a common mechanism contributing – either in allopatry Cheirolophus. We only measured a few morphological traits usually employed to delimitate taxonomically the Macaronesian species  shows a different cpDNA haplotype from the rest of populations C. duranii. This species is grouped together with the rest of taxa from La Palma according to our phylogenetic, PCoA and clustering analyses , thus limiting our conclusions about the relative importance of reticulation in the evolutionary history of the group.These results suggest that introgression might have played certain role in the evolutionary history of aria see . The admCheirolophus is illustrating one of the largest plant radiations in the Canary Islands Cheirolophus shows the highest proportion of endangered taxa for any species-rich lineage in this archipelago. Thus, attending to the major conservational interest of the group, we consider capital to analyse the results of this study from a conservation point of view. Even though Macaronesian Cheirolophus are the result of an exceptionally recent diversification, phylogenetic analyses based on AFLP confirmed the evolutionary identity of currently described endemics. Generally, the genetic diversity indexes calculated for the different populations and species of the group were found to be relatively heterogeneous, reflecting the complexity of this radiation process (see above). However, the frequency-down-weighted fragment values per population (DW) provided interesting and useful information about conservation biology of the numerous endangered representatives of the genus. This rarity index (DW), has been employed to assess the genetic distinctiveness of populations and species Cheirolophus species do not reflect their uneven evolutionary differentiation. Cheirolophus taxa considered in higher extinction risk categories (CR and EN) in the Spanish Red List of Endangered Flora C. arboreus, C. duranii, C. metlesicsii, C. santos-abreui). In contrast, those species showing higher DW values - therefore considered more genetically distinct – are assigned to lower extinction risk categories (VU) or even considered unthreatened . As resources for conservation are limited, their optimal allocation is essential Cheirolophus. We suggest that future evaluations of the endangered status of Macaronesian Cheirolophus should take into account the evolutionary distinctiveness results presented here. Predictably, the prioritization in resources allocation among Cheirolophus species would change if their genetic differentiation level is considered during conservation assessment process.The genus Figure S1Principal coordinates (PCoA) plot of AFLP data for the MacaronesianCheirolophuspopulations included in this study. Different symbols correspond to different populations as shown in the legend in the right side. Some populations groups that are well-differentiated and/or mentioned in the text are circled and named.(TIF)Click here for additional data file.Table S1Sampling information and genetic diversity indexes assessed. Taxa, locality, code, number of sampled individuals (N), and genetic diversity indexes assessed by AFLP in 29 populations of Cheirolophus from Macaronesia. Genetic indices: number of private fragments (fu); heterozygosity (Hj); percentage of polymorphic loci for a standardised sample size of three (PLP 1%); band richness for a standardised sample size of three (Br); and frequency-down-weighted marker values index (DW).(DOC)Click here for additional data file.Table S2Polymorphic positions in nrDNA sequencing of some Canarian Cheirolophustaxa. Positions in ITS and ETS sequences of some Canarian Cheirolophus specimens where more than one base is represented in a single amplification product, seen as subequal multiple peaks on the electropherograms. Data of sequences from Vitales et al. (2014).(DOC)Click here for additional data file.Table S3Data from diagnostic morphological characters of Canarian Cheirolophus species. Character loadings in first two principal components for the analysis of Cheirolophus morphological data (high loadings are highlighted in boldface type).(DOC)Click here for additional data file.Table S4Pair-wise FST distances based on AFLP data calculated among the Macaronesian Cheirolophus populations included in this study.(XLS)Click here for additional data file.


Founder populations have an important role in the study of genetic diseases. Access to detailed genealogical records is often one of their advantages. These genealogical data provide unique information for researchers in evolutionary and population genetics, demography and genetic epidemiology. However, analyzing large genealogical datasets requires specialized methods and software. The GENLIB software was developed to study the large genealogies of the French Canadian population of Quebec, Canada. These genealogies are accessible through the BALSAC database, which contains over 3 million records covering the whole province of Quebec over four centuries. Using this resource, extended pedigrees of up to 17 generations can be constructed from a sample of present-day individuals.We have extended and implemented GENLIB as a package in the R environment for statistical computing and graphics, thus allowing optimal flexibility for users. The GENLIB package includes basic functions to manage genealogical data allowing, for example, extraction of a part of a genealogy or selection of specific individuals. There are also many functions providing information to describe the size and complexity of genealogies as well as functions to compute standard measures such as kinship, inbreeding and genetic contribution. GENLIB also includes functions for gene-dropping simulations.The goal of this paper is to present the full functionalities of GENLIB. We used a sample of 140 individuals from the province of Quebec (Canada) to demonstrate GENLIB’s functions. Ascending genealogies for these individuals were reconstructed using BALSAC, yielding a large pedigree of 41,523 individuals. Using GENLIB’s functions, we provide a detailed description of these genealogical data in terms of completeness, genetic contribution of founders, relatedness, inbreeding and the overall complexity of the genealogical tree. We also present gene-dropping simulations based on the whole genealogy to investigate identical-by-descent sharing of alleles and chromosomal segments of different lengths and estimate probabilities of identical-by-descent sharing.The R package GENLIB provides a user friendly and flexible environment to analyze extensive genealogical data, allowing an efficient and easy integration of different types of data, analytical methods and additional developments and making this tool ideal for genealogical analysis.The online version of this article (doi:10.1186/s12859-015-0581-5) contains supplementary material, which is available to authorized users. Studying founder or isolated populations is a major asset in reducing or taking into account the heterogeneity of genetic and environmental factors involved in complex diseases. Indeed, potential advantages of founder populations include greater genetic and environmental homogeneity and in some instances, the availability of extensive genealogical records . Many foThe BALSAC database is an example of a large genealogical database that has proven very valuable for genetic and demographic research in the Quebec founder population -23. BrieSpecialized software is required in order to optimally exploit the full potential of these well preserved, exhaustive and detailed genealogical data. The S-Plus library of functions GENLIB was originally developed to work with the BALSAC database to manage, describe and visualize genealogies as well as perform allele-dropping simulations. The GENLIB S-Plus library has been used to study the selective advantage to be on an expanding wave front during a range expansion , the genWe have extended and implemented GENLIB in R to provide a freely accessible version of the software within a user-friendly and flexible environment and to allow a more efficient and easier integration of different types of data and analytical methods, also facilitating future developments. Such flexibility is especially important in the context of integrating large-scale genomic data and genealogical data. While other pedigree software exist, few are comprehensive, free and specific to extended genealogical databases. For example, the PedHunter ,20 and Phttp://cran.r-project.org). Version 1.0 of the GENLIB package presented in this paper includes over 40 functions. GENLIB is included in the CRAN packages repository (http://cran.r-project.org/web/packages) and is also available on the BALSAC website . By installing the package, users also have access to the genealogical data described in this paper.GENLIB was originally written in the S programming language, integrating C++ functions to accelerate and extend S programming. We started with the same C++ functions in the translation of GENLIB into an R package and we extended both the C++ and R translation of the S code. Interaction between R and C++ is well supported and high quality R libraries are available to help implement such packages. The package is portable across Linux-like and Windows operating systems, and benefits from the advantages of the R environment, such as being open-source, available online under the GNU General Public License, and offering a wide range of complementary functions. All code has been tested using version 3.1.0 of R , the subject’s father ID, the subject’s mother ID and subject’s sex . All values must be numerical. Functions from the package are grouped into 4 categories: i) management, ii) description and visualisation, iii) computation and iv) simulations. Table The starting point for any genealogical analysis in GENLIB is the creation of a genealogical object using the g) relative to the maximum possible number of ancestors, i.e. assuming that all individuals at the previous generation have two known parents (2g) (see Table g) at a specified generation g [The first category includes functions allowing to track specific individuals  or to extract a part of a genealogy or a lineage. New functions to identify common founders and most recent common ancestors (MRCA) to a group of individuals have been implemented. In the second category, there are functions to count particular individuals, to compute the generational completeness and to describe the depth of the genealogical information and the number of paths linking two individuals. The completeness at a given generation (g) is the proportion of ancestors present in the genealogy , were cTwo genealogical datasets are provided with the package, one is a fictive example of genealogical data and the other is a true genealogical dataset from the province of Quebec. The fictive example is included in the package for educational purposes. Users can explore the functions using this example, which is not too big but still has interesting features. In order to illustrate what can be accomplished with the GENLIB package, we performed a complete description of the ascending genealogies available for the 140 individuals in the Quebec sample. These individuals come from various regions of Quebec and this information is also provided as a separate dataset within GENLIB. This sample has already been investigated to demonstrate the presence of population structure in genetic data, supported by genealogical information . We thenFor the Quebec sample, all participants gave informed written consent, provided family information necessary to reconstruct their genealogy using the BALSAC database, and agreed to the public distribution of their genealogy in coded form. The study was approved by the CHU Sainte-Justine Ethics Committee (reference number: 2684).The Quebec sample provided with GENLIB includes 140 individuals (probands) sampled from seven regional or ethno-cultural populations. The regions represented are Montreal, Quebec City area, Saguenay, North Shore and Gaspesia in which we distinguish 3 different populations . The whole genealogical corpus includes 41,523 individuals . We identified 21,230 nuclear families, including 5,994 full-sibships of sizes varying from 2 to 14 individuals. These are ascending genealogies, i.e., they are reconstructed for each of the 140 probands separately by identifying his/her ancestors and then linked together. Hence, the number and sizes of sibships are underestimated.Including the initial generation (generation 0), this corpus is 18 generations deep. We identified 7,399 founders, i.e., individuals without parents in the BALSAC database, among all individuals in the genealogy. A few founders are in the second generation, meaning that some lineages stop after grandparents. However, more than 90% of the founders are in the 7th generation or higher. The mean genealogical depth is 9.4, indicating that on average genealogical lineages are 9.4 generations deep. Computed values of completeness and implex indices are shown on Figure Figure The founders with the highest genetic contribution are not the ones with the highest coverage, i.e., linked to the maximum number of probands, because the genetic contribution is higher when an ancestor is closer while coverage increases as an individual is more distant. The high coverage individuals are all founders except one (who is the son of two of these high coverage founders) and each is linked to the same 121 probands out of all 140 probands in the data. The probands not covered by these prolific ancestors are mainly descendants of Loyalists, who arrived in Quebec after the American War of Independence, had little intermarriage with the surrounding French Catholic population and had less complete genealogical data. For distant ancestors, the genetic contribution is correlated with the number of occurrences of an ancestor within an individual’s genealogy, in other words how many different, but not necessarily mutually exclusive, paths link an ancestor to a descendant. The number of occurrences is maximal for a proband from Saguenay and some of its ancestors. Four founders and two of their children are linked 176 times trough different paths to this proband. These four founders also have the maximal genetic contribution in this genealogical corpus. All probands with ancestors occurring more than 60 times in their genealogies come from Saguenay and North Shore. Moreover, even if probands from the Acadian population have higher kinship values than those from the North Shore and Saguenay , we obseWe performed gene-dropping simulations to evaluate the odds of IBD sharing for two pairs of distantly related individuals. We selected individuals that had similar kinship coefficients but different patterns of genealogical links , so that patterns of IBD sharing are expected to differ between the pairs. For each pair of individuals, we identified all common ancestors and used these common ancestors as starting point for allele dropping simulations. We performed 10,000,000 simulations for each common ancestor and calculated the probability of IBD sharing as the proportion of simulations where at least one allele was shared. One pair of individuals is from the Saguenay population with a kinship coefficient of 0.0051 and shares 1628 common ancestors. The other pair of individuals is from the Acadian population with a kinship coefficient of 0.0044 and shares 261 common ancestors. Realized IBD sharing and genealogical measures have previously been compared between samples from the Saguenay and Acadian populations, indicating overall higher levels of IBD sharing in the Acadians in agreement with the observed smaller number of closer common ancestors . Our goaOne advantage of gene-dropping simulations is that they give a more accurate picture of an ancestor’s impact on the genome of two individuals than the genetic contribution does. As can be seen on Figure We extended the simulation functionalities of GENLIB to simulate the transmission of chromosomal segments for each pair of individuals. Using IBD sharing previously inferred from genome-wide genotype data available on the 140 individuals , we seleThe results of the segment-dropping simulations were concordant with expectations. Indeed we observed that the probability of sharing a segment IBD decreases compared to the probability of sharing only one allele IBD with the increasing length of segments Figure . Linear In this paper, we presented GENLIB, an R package for the analysis of complex genealogical data. GENLIB can handle large extended human pedigrees, extended genealogical data from human founder populations or extended animal pedigrees. We were able to read and describe a fictive pedigree with a size over 10,000,000 and a depth of 58 generations. Some memory limits may be encountered, depending on the computer used, when trying to perform calculations  for a large number of individuals at the same time in complex genealogies, but these issues can easily be fixed by performing calculations in batches instead.GENLIB is designed to be easily accessible and used by researchers familiar or not with genealogical information. The only requirement is a basic knowledge of the R environment. GENLIB includes functions to describe genealogies, to compute different genealogical indices and to perform simulations based on genealogical relationships. Given the flexibility of the R environment, users can also create their own functions to further describe, summarize and present  GENLIB results.We used genealogies from the Quebec founder population to illustrate the utility of GENLIB to describe and analyze genealogical data. In addition, we performed simulations to track the transmission of alleles or chromosomal segments through the genealogy. Allele-or segment-dropping simulations that consider the complete genealogical structure can help to predict the risk of sharing disease mutations introduced by founders, or to identify ancestral sources of variation in a trait of interest ,44. In oWe plan to continue to improve existing functions, for example by adding more flexible options for individual fitness in the simulations. We also plan to extend the range of functions available. Examples of planned additions include implementing more data importation and graphical functionalities, incorporating information about probands and ancestors, such as birth places and dates, implementing a function to flag unrelated components (subpedigrees) within a kindred, and implementing statistical tests to compare kinship and inbreeding distributions between different groups. Another planned addition is to include an option in the segment-dropping simulations to recover the length of transmitted segments instead of only its status (fully transmitted or not). With its flexibility, GENLIB provides an important contribution towards an improved and optimal way to combine information coming from genealogies and genetic material. These two sources of data are complementary and using them together could improve genetic data analysis in founder populations, for example in the context of estimating relatedness, imputing genomic data or haplotyping ,45,46.The GENLIB R package was developed to facilitate a broader and more extensive use of available genealogical data from founder populations across the world. The package provides a user friendly and flexible environment to analyze genealogical data, allowing a more efficient and easier integration of different types of data and analytical methods and making it ideal for further developments. Using GENLIB simply requires a minimal knowledge of R and provides many functions to manage, describe and analyze genealogical data. Our description of a Quebec genealogical sample and our simulation study illustrated the use of GENLIB and further highlighted regional differences present in the population. We also provided insight on factors influencing the resulting IBD sharing in founder populations. GENLIB is an improvement over existing software in that it provides gene- and segment-dropping simulations and other new functionalities and in that it can be used within R, which is a computing environment familiar to many statistical geneticists. Hence, it is a highly valuable tool to researchers studying extended genealogies.Project name: GENLIBProject home page:http://balsac.uqac.ca/Operating system(s): Linux, Microsoft WindowsProgramming languages: R, C++Other requirements: the package depends on the R packages: kinship2, methods, bootstrap, Matrix, lattice, quadprog, foreach, parallel, doParallel, RcppLicense: GNUGPLAny restrictions to use by non-academics: None


Schistocephalus solidus reflects the habits of intermediate threespine stickleback hosts or those of its definitive hosts, semi-aquatic piscivorous birds, to better understand complex host-parasite interactions. Seventeen lakes in the Cook Inlet region of south-central Alaska were sampled, including ten in the Matanuska-Susitna Valley, five on the Kenai Peninsula, and two in the Bristol Bay drainage. We analyzed sequence variation across a 759 bp region of the mitochondrial DNA (mtDNA) cytochrome oxidase I region for 1,026 S. solidus  individuals sampled from 2009-2012. We also analyzed allelic variation at 8 microsatellite loci for 1,243 individuals. Analysis of mtDNA haplotype and microsatellite genotype variation recovered evidence of significant population genetic structure within S. solidus. Host, location, and year were factors in structuring observed genetic variation. Pairwise measures revealed significant differentiation among lakes, including a pattern of isolation-by-distance. Bayesian analysis identified three distinct genotypic clusters in the study region, little admixture within hosts and lakes, and a shift in genotype frequencies over time. Evidence of fine-scale population structure in S. solidus indicates that movement of its vagile, definitive avian hosts has less influence on gene flow than expected based solely on movement potential. Observed patterns of genetic variation may reflect genetic drift, behaviors of definitive hosts that constrain dispersal, life history of intermediate hosts, and adaptive specificity of S. solidus to intermediate host genotype.The nature of gene flow in parasites with complex life cycles is poorly understood, particularly when intermediate and definitive hosts have contrasting movement potential. We examined whether the fine-scale population genetic structure of the diphyllobothriidean cestode  Gene flow can be a key determinant of evolutionary potential, particularly for organisms engaging in interactions shaped by adaptation  and pocket gopher hosts (Thomomys bottae) show similarly high levels of genetic differentiation, as gene flow and dispersal of G. actuosi is constrained by infrequent host-host contact [Heligmosmoides polygyrus, a nematode infecting field mice (Apodemus sylvaticusi), reflects the genetic structure of its host, the nematode exhibits higher levels of genetic diversity and differentiation [Amblyomma americanum, a widespread tick, has been attributed to low host specificity and high capacity for dispersal in its mammalian host [The genetic structure and connectivity of parasite populations can be strongly influenced by host dispersal, particularly when parasites lack free-living stages or exhibit strong host specificity –11. Pock contact ,12. Althntiation . In contian host ,15.It is less clear how connectivity among parasite populations corresponds to host dispersal potential when parasites have complex life cycles involving multiple hosts that differ in movement potential ,16–19. FSchistocephalus solidus in the threespine stickleback (Gasterosteus aculeatus). The Schistocephalus-stickleback model system affords opportunities for examining relationships between host dispersal and population connectivity in parasites with complex life cycles because the threespine stickleback—which serves as the second intermediate host of S. solidus—has lower dispersal potential than the piscivorous birds that serve as definitive hosts [S. solidus populations exhibit little to no genetic structure, as prior studies suggest that parasites cycling through both freshwater and more vagile terrestrial hosts tend to have less structured populations with higher gene flow than parasites with life cycles restricted to freshwater hosts [vagile host hypothesis; S. solidus exhibits signatures of intraspecific genetic structure and host specificity in intermediate stickleback hosts, suggesting that the movement potential of definitive hosts may not define the genetic structure of S. solidus or that the movement potential of definitive hosts is not fully realized [S. solidus exhibits pronounced population genetic structure, reflecting the habits of threespine stickleback. Understanding the fine-scale genetic structure of S. solidus populations will help clarify how host movement can influence the evolutionary potential of parasites, and further illustrate how gene flow can shape the geography of host-parasite interactions.Here we evaluate spatial and temporal patterns of mitochondrial and multilocus nuclear genetic variation among populations of the parasitic tapeworm ve hosts ,23,24. Wrealized ,25,26. ASchistocephalus solidus is a diphyllobothriidean cestode that exhibits a complex lifecycle involving cyclopoid copepods and threespine stickleback fish as first and second intermediate hosts, respectively, and piscivorous birds from any one of over 40 species as definitive hosts [ve hosts ,24,27. Tve hosts . Once esve hosts ,29. Infeve hosts ,24,30. Rve hosts ,24. Birdve hosts ,24,31.Gavia immer), which are dominant predators of threespine stickleback in southern Alaska, average around 70 ha and are frequently held by the same mating pair over several years [Threespine sticklebacks likely have more constrained movement potential than definitive bird hosts. The stickleback hosts sampled in this study were all residents of freshwater lakes, which typically remain in the lake of origin throughout life, unless connecting freshwater drainages allow movement among proximate lakes . Threespal years ,40–42. Aal years ,40,41.Infected threespine sticklebacks were sampled in late May to early June in 2009–2012 from 17 lakes in south-central and south-west Alaska. Collections were specifically approved by annual Fish Resource Permits from the Alaska Department of Fish and Game and animal care protocols from Tulane University Institutional Animal Care and Use Committee (protocols 0304R-UT-C and 0304R2) and the University of Washington Institutional Animal Care and Use Committee (protocol 3142–01). Fish were captured from ten lakes in the Matanuska-Susitna Valley (MatSu) north of Cook Inlet, five lakes on the Kenai Peninsula (Kenai) east of Cook Inlet, and two lakes west of Cook Inlet in Bristol Bay drainages BB; ; Fig 1. S. solidus specimens was extracted using the DNeasy Blood & Tissue extraction kit following the manufacturer’s standard protocol . Polymerase chain reactions (PCRs) were performed to amplify 759 base pairs (bp) of the mitochondrial cytochrome oxidase 1 gene (CO1) region for 1,026 individuals (CTAATTGGTGTGTGATCTGG TTTTG) and CYTW3R5 (GGAGTGGGAGCCCAACACAAG) [2O, and purified PCR product. Sequencing reactions were purified using Sephadex  according to manufacturer protocols. An ABI 3730xl DNA sequencer  was used to electrophorese cycle-sequencing products. Sequencher v4.9 and Genalex v6.5 [Genomic DNA from ividuals  using prlex v6.5  softwareST values and pairwise ΦST values between each lake and region.DNAsp v5.10.1 and Arlequin v3.5 were used to estimate the total number of haplotypes, haplotype diversity, pairwise differences among haplotypes, nucleotide diversity among haplotypes, and effective number of haplotypes for each lake, region, and year ,45. EffeST values were compared to the between-lake linear and riverine distance matrices with Mantel’s tests to evaluate the strength of relationships and to detect signatures of isolation-by-distance. Mantel’s tests were performed in Genalex v6.5 with 10,000 permutations [To determine whether patterns of genetic differentiation reflect the movement potential or habits of hosts, pairwise routes of potential movement between all lakes were calculated using Google Earth. The most parsimonious pathways for travel were measured as straight line distances between lakes, as compared to river distances between lakes within and among watersheds. Pairwise Φutations .A total of 1,243 individuals  were gene) and observed (HO) heterozygosity, average number of alleles , and average rarefied allelic richness (R) were calculated for each lake, region, and year using Arlequin v3.5; Shannon’s Index (I) also was calculated using MSA software [IS values were calculated to test for equilibrium and to detect signatures of the Wahlund effect. HWE and FIS values were calculated in Arlequin v3.5. Tests for LD were performed in Genepop v4.3, and p-values were compared following a Bonferroni correction (p < 0.0018) [ST values were also calculated using Arlequin v3.5.Genetic diversity statistics, including expected  . To exam 0.0018) . Samplesa priori hypotheses of population structure [Structure v2.1 was used to assess patterns of genetic differentiation without tructure . We usedST values were compared to between-lake distance matrices (as described above) with Mantel’s tests to evaluate the strength of relationships and to detect signatures of isolation-by-distance. Mantel’s tests were performed in Genalex 6.5 with 10,000 permutations [To determine whether patterns of genetic differentiation reflect the movement potential or habits of hosts, pairwise linearized Futations .CO1 gene recovered 248 unique haplotypes in 1,026 individuals. Twelve polymorphisms separated the most divergent haplotypes from the most common haplotype (H1), which was found in all lakes except Hall Lake, and in all regions, years, and genotype clusters. Excluding Hall and Pollard lakes, which were not considered due to small sample sizes, the greatest haplotype diversity was detected in Big Beaver Lake  to 0.142  were not significant when distance was measured by stream length or straight line distances.Significant pairwise Φ 0.0087; . Mantel’IS values were present in ten lakes, ranging from 0.04  to 0.167  than by straight line distances . When Hall and Pollard lakes were removed from the calculation to control for small sample sizes, highly significant relationships were detected, with distance based on stream length  being a stronger predictor than straight line distances ) at K = 2, and ΔK values also detected the coarsest level of genetic structure at K = 2 , S2 Fig.enotypes , S2 Fig.S. solidus reflects the habits of its intermediate host or, alternatively, those of its definitive hosts. We evaluated spatial and temporal patterns of genetic variation and found evidence of significant population genetic structure in S. solidus infecting threespine sticklebacks in lakes throughout south-central Alaska. The observed patterns of genetic differentiation and diversity showed that gene flow is constrained, and that variability over space and time likely reflects factors other than the movement of the most vagile host. We recovered significant mtDNA and microsatellite-based estimates of genetic differentiation, with genetic structure recovered in frequency-based and Bayesian clustering analysis  recovered phylogenetic evidence indicating that continental patterns of genetic differentiation in Schistocephalus parasites reflect specificity between threespine and ninespine stickleback intermediate hosts [S. solidus may also exhibit adaptive specificity to evolutionary lineages of threespine stickleback [S. solidus are consistent with this scenario, further study is warranted to determine the likelihood of adaptive host specificity in mediating gene flow in S. solidus [The observed patterns of restricted gene flow may also be an outcome of intermediate host specificity within te hosts ,64. Evidckleback ,66. If sckleback ,65,67,68 solidus ,55,65,69S1 FigMinimum spanning networks were constructed in Network and colored by (a) lake, (b) year collected, and (c) genotypic cluster assignment (K = 3). Lines represent one base pair difference between haplotypes, and black nodes represent transitional mutations.(TIFF)Click here for additional data file.S2 FigGrouped by lake, with (a) K = 2, (b) K = 5, by (c) year collected K = 2, (d) fish host, with only hosts with greater than seven parasites, K = 2, (e) cluster one K = 2, (f) cluster two K = 2, and (g) mean ln P(D) plot.(TIFF)Click here for additional data file.S1 TableST values are above the diagonal and FST values are below the diagonal. Significant values are bold (p>0.05). MatSu = Matanuska-Susitna Valley; Kenai = Kenai Peninsula; BB = Bristol Bay region.Φ(DOCX)Click here for additional data file.S2 TableE: expected heterozygosity; HO: observed heterozygosity; FIS: inbreeding coefficient. Bolded HO values indicate significant departures from Hardy-Weinberg Equilibrium (p<0.05).N: number of individuals per lake; H(DOCX)Click here for additional data file.


The current study was the first of its kind taken upon indigenous ecotypes of the Karnataka in order to unravel the diversity details at 20 chicken microsatellite regions.210 indigenous chicken belonging to six districts of Bangalore and Mysore division formed the target sample for the present study. The genomic deoxyribonucleic acid was isolated by phenol chloroform isoamyl alcohol method. A panel of 20 microsatellite regions, including 14 recommended by FAO and six identified from published scientific literature became the targeted chicken genomic region. 27-33 samples were successfully genotyped in each of the six ecotypes through simplex or multiplex polymerase chain reactions, polyacrylamide gel electrophoresis and silver staining for the selected microsatellite panel.The chickens of Ramanagara and Chamrajnagara were most distant with a Nei’s genetic distance value of 0.22. The chickens of Bangalore rural and Mysore were least distant with a value of 0.056. The Ramanagara and Chamrajnagara pair had Nei’s genetic identity value of 0.802, which is least among all pairs of ecotypes. There were five main nodes from which the six ecotypes evolved on the basis 20 microsatellite markers used in this study. This study indicates that the four ecotypes Ramnagara, Bangalore Rural, Chickaballapura and Mysore are genetically identical due to their common ancestral evolution while, Mandya and Chamrajnagara ecotypes formed a relatively different cluster due to a separate common ancestral chicken population and less number of generations since drifting from bifurcation node.ST values compared to the distinguished breeds reported. There were two main clusters, which differentiated into six ecotypes. They may differentiate into more distinct varieties if bred in isolation for a longer number of generations.Twenty microsatellite markers based genetic diversity study on six indigenous ecotypes indicated lower genetic distances as well as lower F Characterization of animal genetic resources (AnGR) involves activities associated with the identification, quantitative and qualitative description, documentation of breed populations, the natural habitats and production systems to which they are not adapted. Since the beginning of the 1990s, molecular data have become more and more relevant for the characterization of genetic diversity [Indigenous chicken have an inherent scavenging and nesting habit. Years of natural selection under scavenging conditions, has made them tough and resistant to various diseases, especially to those caused by bacteria, and protozoa and other internal and external parasites; they have better survival than the commercial hybrid strains under village production conditions. However, the village chicken is a poor egg producer, laying on average 40-60 eggs per year in three or four clutches, with an average egg weight of around 35-45 g. They generally have small body size; for various chicken breeds, mature body weight varies between 1.3 and 1.9 kg for males and between 1.0 and 1.4 kg for females.Molecular genetic characterization explores polymorphism in selected protein molecules and deoxyribonucleic acid (DNA) markers in order to measure genetic variation at the population level. To obtain a better knowledge of AnGR, of their present and potential future uses for food and agriculture in defined environments, and their current state as distinct breed populations. In poultry, different genetic marker systems have successfully been used for estimation of genetic variability. They were DNA fingerprints, RAPDs, and microsatellites. Recently, the determination of heterozygosity and genetic distances based on microsatellite markers is regarded as a most convenient tool, and many microsatellite loci are available in chicken. These tandem repeated DNA segments show extensive allelic differences in length based mainly on variation in the number of repeats and, partly, in adjacent regions. These studies are important for understanding the history of species, and for testing hypotheses regarding evolutionary processes. Currently, microsatellites are most commonly used, and successful application of this sort of markers in diversity studies has been reported for all major livestock species -6. MicroThe Indian chicken ecotypes consisted of different phenotypes of almost centuries of natural selection and reared by smallholder farmers across distinct agro-ecological regions. To date, however, no investigation has yet been directed toward the use of microsatellite markers to study the genetic variability of these ecotypes, despite a large number of microsatellite primers published in scientific literature. Despite the importance of native chicken in tribal/rural areas, information is lacking on their genetic makeup with respect to genetic variability, genetic relationships, performance, adaptability and resistance to diseases. In this context, this study of diversity in indigenous chicken ecotypes based on appropriate microsatellite panel in Karnataka was taken up.This research was approved by the Local Ethics Committee of Veterinary College, Bangalore, Karnataka Veterinary, Animal and Fisheries sciences University, as per LPM/IAEC/77/2011 dated 20-01-2011.The indigenous chicken belonging to Ramnagara, Bangalore rural and Chikkaballapur districts of Bangalore division and Chamarajnagara, Mysore and Mandya districts of Mysore division of Karnataka state  maintainThe birds belonging to the six districts were wing banded at the hatch from randomly collected fertile eggs in respective districts. The birds chosen in each district belonged to three hatches and were badged while allocating to breeding pens after growing phase. The wing bands and serial numbers were noted down at the time of blood collection from each bird. The serial numbers for each district were maintained on the 2 ml Eppendorf tubes and subsequent tubes until the successful amplification of desired segment in each marker. The numbers were maintained until genotyping and further statistical analysis.et al. [20 primer pairs corresponding to microsatellite regions of chicken autosomes 1, 2, 3, 4, 5, 6, 7, 8, 10, 13, 14, 17, and 23 were identified by review of literature . The proPCR reactions were set up on clean benches with autoclaved lab disposables like micro tips, PCR tubes, 1.5-2.0 ml Eppendorf tubes and autoclaved milliq water ensuring proper thawing, mixing of PCR reaction components and cold chain of around 4°C. The standard PCR protocol was followed for amplifying all the microsatellite regions. The standard 12% non-denaturing polyacrylamide gel (PAGE) was performed for detection of allele size on all PCR products belonging to 20 microsatellite loci.et al. [The silver staining was adopted for staining of PAGEs in this study. The improved staining method developed by Halima et al. . The samThe data obtained regarding genotypes of 20 microsatellite regions for six ecotypes of Bangalore and Mysore divisions in base pair format was utilized as input file for GenAlex 6.5b5 in order to obtain genetic distances, and Wright’s F-statistics. The dendrogram was obtained from the POPGENE software. The Polymorhic information for each marker was obtained from MS tools programme.The PIC values of 20 loci for all the six ecotypes are presented in the 0 over all loci was lowest for Bangalore Rural with a value of 0.855 and highest for Chickaballapura with a value of 0.868. The mean He over all loci was lowest for Bangalore rural with a value of 0.685 and highest for Chamrajnagara with a value of 0.803. The mean uHe over all loci was lowest for Bangalore Rural with a value of 0.698 and highest for Chamrajnagara with a value of 0.815. The mean ‘F’ value over all loci was lowest for Bangalore Rural with a value of −0.256 and highest for Chamrajnagara with a value of −0.066.The heterozygosity values are depicted in Among the 15 pairs of ecotypes studied, the chickens of Ramanagara and Chamrajnagara were most distant with a Nei’s genetic distance value of 0.22. The chickens of Bangalore rural and Mysore were least distant with a value of 0.056. The Ramanagara and Chamrajnagara pair had Nei’s genetic identity value of 0.802, which is least among all pairs of ecotypes. The Bangalore Rural and Mysore had maximum Nei’s genetic identity with a value of 0.946 among all the pairs of ecotypes .et al. [et al. [Among the 15 pairs of ecotypes studied, the chicken of Ramanagara and Chamrajnagara were most distant with an unbiased Nei’s genetic distance value of 0.159. The chicken of Ramanagara and Bangalore Rural were least distant with a value of 0.011. The Ramanagara and Chamrajnagara pair had Unbiased Nei’s genetic identity value of 0.852 which is least among all pairs of ecotypes. The Ramanagara and Bangalore Rural had maximum unbiased Nei’s genetic identity with a value of 0.989 among all the pairs of ecotypes . The genet al.  were mod [et al.  were in The dendrogram was constructed on the basis of genetic distance  and neigIS was in the range of −0.475 in MCW123 to 0.551 in MCW183. The FIT was in the range of −0.430 in MCW123 to 0.598 in MCW183. The FST was in the range of 0.012 in MCW123 to 0.104 in MCW183. The FST values calculated by frequency option (m) between the ecotype pairs was lowest (7.587) for Bangalore Rural and Chamrajnagara pair, while highest (around 22) for Mandya’s pairing with two other districts of Mysore division. Fixation indices give an idea about the population structure in terms of the inbreeding coefficient and population differentiation. The F and FIS measures “the Ho expressed as a fraction of He and deviation from 1” for each of the locus/all loci in each ecotype and over all populations for each locus, respectively. The former takes into account individual locus H0 and He values while later considers mean H0 and He values of all ecotypes for each of the locus. They are influenced by the deviation of He from H0. The values were on the positive side for loci with lower H0 than He and are on the negative side for loci with higher H0 than He. The values indicate the extent of fixation of alleles in each of the loci. The F values were positive for only three loci namely MCW183, MCW067 and MCW014 indicating relatively better allele fixation in these loci compared to remaining seventeen loci which had negative F values. The mean F per ecotype over all loci was lowest for Bangalore Rural with a value of −0.256 and highest for Chamrajnagara with a value of −0.066 indicating better allele fixation in Chamrajnagara ecotype among all ecotypes. The values were in conformity with the ranges reported by Pirany et al. [IS was in the range of −0.475 in MCW123 to 0.551 in MCW183. The range of FIS in the present study was wider compared to the reports of −0.29 to 0.38 and −0.135 to 0.137 by Pirany et al. [t is similar to He except that the former is a measure of expected heterozygosity over all the ecotypes while later is restricted to one population. The behavior of Ht values is similar to that of He. The values are directly proportional to the polymorphism of loci. The similar range of Ht values was reported by Pirany et al. [IS, FIT and FST give an idea about the population structure in terms of inbreeding coefficient and population differentiation [The Fy option  was highy et al. . The FISy et al. , respecty et al. . FixatioIT was in the range of −0.430 in MCW123 to 0.598 in MCW183 with a mean of −0.101 over all loci and ecotypes in the present study. For the interpretation of FST, it has been suggested that a value lying in the range 0-0.05 indicates little genetic differentiation; a value between 0.05 and 0.15, moderate differentiation; a value between 0.15 and 0.25, great differentiation; and values above 0.25, very great genetic differentiation. Balloux et al. [ST of 0.05 will generally be considered as reasonably low, and investigators may interpret that structuring between sub populations is weak. While such an interpretation may turn out to be correct, it may also not be representative at all of the real population differentiation because of the fact that expectation of FST, under complete differentiation will not always be one. In fact, in the great majority of cases, it will not be one because the effect of polymorphism (due to mutations) drastically deflates FST expectations. Hence, a seemingly low FST of 0.05 may, in fact, indicate very important genetic differentiation. This point was already stressed by Barton and Hewitt [ST is as small as 0.05 or even less. The FST was in the range of 0.012 in MCW123 to 0.104 in MCW183 with a mean of 0.033 over all loci and ecotypes. The mean FIS, FIT and FST for all the microsatellites together in the overall population was −0.18, −0.085 and 0.083, respectively for five chicken populations including two indigenous breeds and three pure lines of Indian Rural synthetics in the reports of Chatterjee et al. [ST values in the present study were lower than those reported by FAO and Nei [The Fe et al. . The FST and Nei .ST values compared to those values between distinguished breeds reported. There were two main clusters, which differentiated into six ecotypes. They may differentiate into more distinct varieties if bred in isolation for a longer number of generations.Twenty microsatellite markers based genetic diversity study on six indigenous ecotypes indicated lower genetic distances as well as lower FThis is part of the Ph.D. thesis submitted by the first author, consequently research, analysis and manuscript preparation was done by the same. HNNM suggested material collection plan, MRJ instructed format for recording of laboratory data, CSN suggested PCR trouble shooting methods, AMK helped in caliberating Thermal cycler for all primer pairs and SMB provided the key information for interpretation of laboratory results. All authors read and approved the final manuscript.


Ipomoea batatas L.) is the seventh most important food crop due to its distinct advantages, such as adaptability to different environmental conditions and high nutritional value. Assessing the genetic diversity of this important crop is necessary due to the constant increase of demand for food and the need for conservation of agricultural and genetic resources. In Puerto Rico (PR), the genetic diversity of sweet potato has been poorly understood, although it has been part of the diet since Pre-Columbus time. Thus, 137 landraces from different localities around PR were collected and subjected to a genetic diversity analysis using 23 SSR-markers. In addition, 8 accessions from a collection grown in Gurabo, PR at the Agricultural Experimental Station (GAES), 10 US commercial cultivars and 12 Puerto Rican accessions from the USDA repository collection were included in this assessment. The results of the analysis of the 23 loci showed 255 alleles in the 167 samples. Observed heterozygosity was high across populations (0.71) while measurements of total heterozygosity revealed a large genetic diversity throughout the population and within populations. UPGMA clustering method revealed two main clusters. Cluster 1 contained 12 PR accessions from the USDA repository collection, while cluster 2 consisted of PR landraces, US commercial cultivars and the PR accessions from GAES. Population structure analysis grouped PR landraces in five groups including four US commercial cultivars. Our study shows the presence of a high level of genetic diversity of sweet potato across PR which can be related to the genetic makeup of sweet potato, human intervention and out-crossing nature of the plant. The history of domestication and dispersal of sweet potato in the Caribbean and the high levels of genetic diversity found through this study makes sweet potato an invaluable resource that needs to be protected and further studied.Sweet potato ( The conservation of crop genetic resources is vital for food security. The on-going abuse of urbanization and construction is responsible for the everyday loss of valuable land for agricultural production with wild-relatives of important crops being lost forever due to deforestation. These wild-relatives could have important traits useful for crop improvement, bio-fortification programs or the conservation of genetic resources. Maintaining a healthy genetic pool and preventing genetic erosion can positively impact the economy and overall food production. There is immense uncertainty as to whether the increase in world food production could be met without studying and protecting this diversity Ipomoea batatas (L.) Lam.) is the seventh most important food crop after wheat, rice, maize, potato, barley and cassava Sweet potato  in Griffin, GA Sweet potato leaf samples were collected from subsistence farmers and land-owners voluntarily. Root samples were not collected. Any access leaf samples left-over after DNA extraction was destroyed. Since this study did not involve any endangered or protected species specific governmental permission was not required to collect the leaf samples. The sweet potato plant material was obtained from 3 different sources. First, a group comprising 8 known Puerto Rican accessions  was collected from the Agricultural Experimental Station in Gurabo, PR (GAES). Second, twenty two samples comprised of 10 known US commercial cultivars  and 12 known Puerto Rican accessions  were obtained from DNA extractions were performed using leaf tissue according to the method described by Doyle and Doyle (1990) with some modifications et al.et al., (unpublished data CIP 2005 to 2006), Tumwegamire et al.et al.2, 4 mM KCl, 0.4 mM dNTP′s, 2 µM from each forward and reverse primers, M13 F/d 1 pmol/µL fluorescent primer , 1 U Taq polymerase and 20 ng/µL DNA template. For SSR R03, 9 mM MgCl2 and 30 ng/µL DNA template were used. For SSR R08, 8 mM MgCl2 and 40 ng/µL DNA template was used. PCR conditions for amplification were 94°C for 7 minutes followed by 35 cycles of 94°C for 30 seconds, 50–63°C for 90 seconds of annealing temperature depending on the SSR marker , and inbreeding coefficient (Gis)] and allele frequencies. Since in a hexaploid is not possible to determine the actual genotype of an individual based on molecular markers, GenoDive program uses a maximum likelihood method to correct for the unknown dosage of alleles. Briefly, for every incomplete genotype information of an individual, all possible underlying genotypes are considered, new alleles frequencies for this particular locus are determined, and the genotype that end in producing the most likelihood allele frequencies is selected. Thus, this algorithm was employed for every SSR locus in our study. From the weight data, a binary matrix was constructed based on presence and absence of alleles  The scored data for the 23 SSR markers were converted into a weight matrix in Microsoft Excel and further converted into text using TextPad ver. 6.2.2 . The GenoDive program was used to determine the genetic diversity estimators [i.e. observed and total heterozygosity  followed by the PR accessions from PGRCU (0.71) and the PR landraces (0.66)  was low with a value of 0.05, however, it suggests some level of inbreeding across the groups . In addition, it has the highest percentage of unique alleles (20%) among the 8 groups reflecting the genetic diversity of the collection and its adequate preservation. In this group a trend could be inferred with most of the accessions that grouped more closely share morphological traits such as root skin, flesh color and their genetic distance grouping them closely together with a mean value of 73% similarity. ‘Miguela-Arecibo’ was the first accession to be introduced to the PGRCU germplasm in 1986, interestingly it is the only sample with purple flesh (root skin color is red) in cluster 1 and grouped separately from the rest. Others such as Tapato, Amanecer, Pepa de Oro, Frita, Wart and Francia have yellow/golden root skin color. Accessions with red/orange fleshed roots such as Macana and Sunny also grouped together. Bugs Bunny and Papota have cream colored root flesh, while Mojave is the only white skin/flesh accession.The accessions of cluster 1 (group 1) were strategically selected to represent the genetic diversity present in PR and has been maintained O and HT values . The lower percentage of unique alleles and genetic diversity in comparison to group 1 could be the result of genetic drift and inbreeding since this collection is maintained in open pollinated field. Another explanation could be that the collection localities of the original accessions are in close proximity to each other. Even though accessions from PR collection at GAES are also closely related to the PR landraces, they grouped separately.The PR collection at GAES (cluster 2A: group 2) is being maintained in the field through vegetative propagation and gene flow among them is constantly occurring by cross pollination. This group had 10% of unique alleles, and high levels of genetic diversity reflected by the high HO and HT values of 0.67 and 0.70, respectively. Likewise, the percentages of unique alleles in group 4 to 8, which comprise PR landraces and four US cultivars, were lower than the observed in PGRCU and GAES collection. The HO values across these five groups ranged from 0.54 to 0.71, while the total heterozygosity ranged from 0.66 to 0.71. The PR landraces are outcrossing in the field and maintained by natural selection. Thus, the low percentages of rare alleles and the observed population structure might be the result of hundreds of years of natural selection. Remarkably, PR landraces did not exhibit any kind of grouping pattern according to their geographical location. This phenomenon has been observed previously in almost all genetic diversity analysis of sweet potato et al.The US cultivars from GAES (group 3) are widely consumed and grown by small scale farmers. The genetic variation of this group is lower than group 1 and 2 with only 2% of unique alleles, and HMost of the commercial varieties from the US grouped closely with the PR landraces . Some ofIn conclusion, from our study it can be observed that the ability of dispersal of a vegetatively propagated crop can lead to genetic diversity preservation and increase. Farmers and landowners are fundamental in the diffusion of such crops. Unconsciously, the farmers maintain healthy levels of plant genetic diversity, when introducing different accessions into the field , and later by gene flow, recombination and somatic variation the genetic diversity of the crop increases and is preserved by natural and agronomic selection. High levels of genetic diversity found in sweet potato in Puerto Rico, the history of domestication and the methods of dispersal of sweet potato suggest that Puerto Rico may be one of the secondary centers for diversity of sweet potato. This adds to the importance of protecting and further studying these genetic resources in the Caribbean.S1 TableInformation of the sweet potato samples used to study the genetic diversity present in Puerto Rico. Name (ID), source, collection site, and status of sweet potato materials used are shown. Eight accessions are from the agricultural experimental station in Gurabo, Puerto Rico (GAES), 22 from the USDA plant genetic resources conservation unit (PGRCU) in Griffin, GA  and 137 Puerto Rico landraces are from across the island.(DOCX)Click here for additional data file.


NOG gene resides, have been reported leading to the NOG-related symphalangism spectrum disorder (NOG-SSD), intellectual disability and other developmental abnormalities. In this study we reported a dominant Chinese Han family segregating with typical NOG-SSD symptoms including proximal symphalangism, conductive hearing loss, amblyopia and strabismus, but not intellectual disability. Sanger sequencing identified no pathogenic mutation in the coding regions of candidate genes NOG, GDF5 and FGF9. SNP genotyping in the genomic region surrounding NOG identified loss of heterozygosity in the affected family members. By array comparative genomic hybridization and quantitative real-time polymerase chain reaction, we identified and mapped the breakpoints of a novel 1.6-Mb microdeletion in chromosome 17q22 that included NOG and twelve other genes. It is the first microdeletion reported in chromosome 17q22 that is associated with NOG-SSD only but not with intellectual disability. Our results may help identifying the dosage sensitive genes for intellectual disability and other developmental abnormalities in chromosome 17q22. Our study also suggested that genomic deletions in chromosome 17q22 should be screened in the NOG-SSD patients in which no pathogenic mutation is identified by conventional sequencing methods.Microdeletions in chromosome 17q22, where the  NOG encodes noggin, the first identified bone morphogenetic protein (BMP) antagonist [NOG may lead to a series of autosomal dominant disorders called the NOG-related symphalangism spectrum disorder (NOG-SSD). NOG-SSD is mainly characterized by symphalangism, the ankylosis of the joints in fingers or toes. Other symptoms of NOG-SSD may include conductive hearing impairment due to stapes ankylosis, fusion of the carpals and tarsals, brachydactyly, abnormal faces, hyperopia and strabismus. In addition to NOG, GDF5 and FGF9 are two other genes associated with NOG-SSD [tagonist . It playtagonist . Mutatio NOG-SSD ,4.NOG resides, have been reported causing NOG-SSD, intellectual disability (ID) and other developmental abnormalities in a dominant manner [NOG is clearly the key pathogenic mechanism for NOG-SSD, gene(s) in chromosome 17q22 that are directly involved in the etiology of ID and other developmental abnormalities remain elusive.Genomic disorders are caused by complete loss, gain or disruption of one or multiple dosage sensitive genes. Over ten microdeletions in the chromosome 17q22 region, where t manner –10. ThosNOG-SSD in a dominant Chinese Han family. The affected family members did not have ID or other developmental abnormalities commonly seen in patients with chromosome 17q22 microdeletions. Our results may provide new insights into the pathogenic mechanism for the ID associated with the chromosome 17q22 microdeletions.In the present study, we identified a novel 1.6-Mb microdeletion in chromosome 17q22 as the cause of NOG-SSD was recruited from Shanghai, China including five affected subjects and two unaffected subjects . Exons and flanking introns of escribed ,4,11.NOG were selected to identify the potential loss of heterozygosity (LOH) in the affected family members. The SNPs were genotyped by PCR amplification and Sanger sequencing.Five SNPs  within 150 kb in distance to Array-CGH was performed for proband F13-2. Briefly, genomic DNA was digested, ligated, PCR amplified, labeled and hybridized to the Affymetrix Genome-Wide Human SNP Nsp/Sty 6.0 chip following the manufacture’s guide . Arrays were scanned by GeneChip Scanner 3000 and analyzed by Command Console Software 3.1 with default settings. Raw data that passed the quality control were further analyzed by Genotyping Console Software to obtain genotype call of each SNP locus. SNP call rate of sample F13-2 was 94.67%.http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi). Each reaction was repeated tree times and the average Ct was recorded.Real-time PCR was performed for proband F13-2 and a normal hearing control on the 7300 Realtime PCR System (Applied Biosystems) using SYBR Premix Ex Taq (Takara Bio Company). The primers were designed by the PRIME3 software online  and Reverse-Del (5’-AGGGGAAGAGCGAACGGAACT-3’). The breakpoints were determined by Sanger sequencing. PCR amplification of the 1.2-kb product was subsequently used to detect the microdeletion in other family members and 200 ethnically matched normal hearing controls.NOG-SSD symptoms including congenital conductive hearing loss  including er genes . The poser genes  or 200 eNOG-SSD. To date, over 10 heterozygous microdeletions in the chromosome 17q22 region have been reported causing the NOG-SSD-associated disorders, demonstrating that genomic deletions in chromosome 17q22 may be a relatively frequent cause for NOG-SSD. Since heterozygous microdeletion cannot be readily detected by the conventional sequencing-based mutation screening methods, alternative tests such as the LOH analysis should be offered to the NOG-SSD patients without pathogenic mutations identified in the candidate genes. In a broader sense, genome-wide analysis using the SNP array may be recommended for patients with multiple congenital anomalies.In this study, we identified a novel 1.6-Mb microdeletion in chromosome 17q22 in a dominant Chinese Han Family segregating with NOG-SSD. Other major abnormalities, observed in some but not all patients, included developmental delay, vertebral anomalies and deficiencies in the reproductive organs such as micropenis, cryptorchidism, absent uterus and rudimentary vagina [NOG-SSD only. None of the five affected family members showed ID or any other developmental abnormalities.All previously reported microdeletions in chromosome 17q22 were associated with ID in addition to y vagina –10. On tNOG-SSD, resulting in a single copy deletion in thirteen genes—TMEM100, PCTP, ANKFN1, C17orf67, DGKE, MTVR2, MIR3614, TRIM25, COIL, SCPEP1, RNF126P1, AKAP1 and NOG. Of the twelve genes other than NOG, only DGKE is associated with human disorders, as the recessive loss-of-function mutations in DGKE may result in atypical hemolytic-uremic syndrome characterized with microangiopathic hemolytic anemia, thrombocytopenia and renal failure [NOG is clearly the key pathogenic mechanism for NOG-SSD, which has been supported by studies of the heterozygous Nog-deficient mouse model [The 1.6-Mb microdeletion identified in Family F13 is among the smallest ones associated with TOM1L1, COX11, STXBP4, HLF and MMD. Similarly, another candidate interval is present on the telomeric side including MSI2, CUEDC1, VEZF1 and SRSF1. Interestingly, searching of the DECIPHER database  identified two additional patients with ID but without NOG-SSD, who have genomic microdeletions within (patient #288846) or overlapping with (patient #250690) the telomeric candidate interval. These mapping data supported MSI2 (patient #288846), CUEDC1, VEZF1 and SRSF1 (patient #250690) as positional candidate genes for ID  showed that all nine candidate genes in the refined intervals are expressed in the brain. HLF and MSI2 in the centromeric and telomeric candidate interval, respectively, are of particular interest based on their function. HLF encodes Hepatic leukemia factor, a PAR bZIP (proline and acidic amino acid-rich basic leucine zipper) transcription factor that is increasingly expressed during brain development and plays a role in the function of differentiated neurons [Hlf, Tef and Dbp, all three PAR bZIP transcription factor genes, resulted in decreased brain levels of pyridoxal-5-phosphate, serotonin, and dopamine and spontaneous epilepsy in mice [MSI2 encodes musashi-2, an RNA-binding protein that is concurrently expressed with MSI1 during development of the central nervous system (CNS) [Msi2 and Msi1 suppressed the proliferation and maintenance of the CNS stem cells [Searching of the Unigene database ( neurons . Triple  in mice . MSI2 enem (CNS) . Down-reem cells . Overall