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The software program TreeSAAP measures the selective influences on 31 structural and biochemical amino acid properties during cladogenesis, and performs goodness-of-fit and categorical statistical tests.
MOTIVATION: Identifying patterns of co-expression in microarray data by cluster analysis has been a productive approach to uncovering molecular mechanisms underlying biological processes under investigation. Using experimental replicates can generally improve the precision of the cluster analysis by reducing the experimental variability of measurements. In such situations, Bayesian mixtures allow for an efficient use of information by precisely modeling between-replicates variability. RESULTS: We developed different variants of Bayesian mixture based clustering procedures for clustering gene expression data with experimental replicates. In this approach, the statistical distribution of microarray data is described by a Bayesian mixture model. Clusters of co-expressed genes are created from the posterior distribution of clusterings, which is estimated by a Gibbs sampler. We define infinite and finite Bayesian mixture models with different between-replicates variance structures and investigate their utility by analyzing synthetic and the real-world datasets. Results of our analyses demonstrate that (1) improvements in precision achieved by performing only two experimental replicates can be dramatic when the between-replicates variability is high, (2) precise modeling of intra-gene variability is important for accurate identification of co-expressed genes and (3) the infinite mixture model with the 'elliptical' between-replicates variance structure performed overall better than any other method tested. We also introduce a heuristic modification to the Gibbs sampler based on the 'reverse annealing' principle. This modification effectively overcomes the tendency of the Gibbs sampler to converge to different modes of the posterior distribution when started from different initial positions. Finally, we demonstrate that the Bayesian infinite mixture model with 'elliptical' variance structure is capable of identifying the underlying structure of the data without knowing the 'correct' number of clusters. AVAILABILITY: The MS Windows based program named Gaussian Infinite Mixture Modeling (GIMM) implementing the Gibbs sampler and corresponding C++ code are available at http://homepages.uc.edu/~medvedm/GIMM.htm SUPPLEMENTAL INFORMATION: http://expression.microslu.washington.edu/expression/kayee/medvedovic2003/medvedovic_bioinf2003.html
Volcanic islands represent excellent models with which to study the effect of vicariance on colonization and dispersal, particularly when the evolution of genetic diversity mirrors the sequence of geological events that led to island formation. Phylogeographic inference, however, can be particularly challenging for recent dispersal events within islands, where the antagonistic effects of land bridge formation and vicariance can affect movements of organisms with limited dispersal ability. We investigated levels of genetic divergence and recovered signatures of dispersal events for 631 Galápagos giant tortoises across the volcanoes of Sierra Negra and Cerro Azul on the island of Isabela. These volcanoes are among the most recent formations in the Galápagos (<0.7 million years), and previous studies based on genetic and morphological data could not recover a consistent pattern of lineage sorting. We integrated nested clade analysis of mitochondrial DNA control region sequences, to infer historical patterns of colonization, and a novel Bayesian multilocus genotyping method for recovering evidence of recent migration across volcanoes using eleven microsatellite loci. These genetic studies illuminate taxonomic distinctions as well as provide guidance to possible repatriation programs aimed at countering the rapid population declines of these spectacular animals.
SUMMARY: Estimating divergence times and rates of substitution from sequence data is plagued by the problem of rate variation between lineages. R8s version 1.5 is a program which uses parametric, nonparametric and semiparametric methods to relax the assumption of constant rates of evolution to obtain better estimates of rates and times. Unlike most programs for rate inference or phylogenetics, r8s permits users to convert results to absolute rates and ages by constraining one or more node times to be fixed, minimum or maximum ages (using fossil or other evidence). Version 1.5 uses truncated Newton nonlinear optimization code with bound constraints, offering superior performance over previous versions. AVAILABILITY: The linux executable, C source code, sample data sets and user manual are available free at http://ginger.ucdavis.edu/r8s.
UNLABELLED: The aim of the MCQTL software package is to perform QTL mapping in multi-cross designs. It allows the analysis of the usual populations derived from inbred lines and can link the families by assuming that the QTL locations are the same in all of them. Moreover, a diallel modelling of the QTL genotypic effects is allowed in multiple related families. The implemented model is a linear regression model. A composite interval mapping and an iterative QTL mapping are implemented to deal with multiple QTL models. Marker cofactor selections by forward or backward stepwise methods are implemented as well as computation of threshold test value by permutation. AVAILABILITY: The program is available on request after signing a licence agreement; free of charge for academic and non-profit organizations at http://www.genoplante.org (Bioinformatics products).
The identification of genes contributing to variation in complex phenotypes requires genetic data of high fidelity. Thus, the identification of pedigree and genotyping errors is a crucial prerequisite to the analysis of data from a genome scan for disease genes. The problem has been given little attention in most gene hunting papers; the focus has often been on eliminating mendelian inconsistencies in order that the analysis may proceed, rather than on achieving the best possible data. Though a number of computer programs are available to assist in the identification of genotyping and pedigree errors, the process is still not completely automated. While the Collaborative Study on the Genetics of Alcoholism (COGA) data set for GAW11 is completely compatible with Mendel's rules, there are still some errors present. We inspected the COGA data for the presence of additional errors, and identified five possible pedigree errors.
PURPOSE: Advances in and diffusion of genetic technology mean that nongeneticist health professionals have an increasing need to develop and maintain genetic competencies. This has been recognized by patient support groups and the European Commission. As the first phase of the GenEd (Genetic Education for Nongenetic Health Professionals) project, we investigated health professional education at undergraduate, postgraduate, and continuing levels in terms of genetic content and delivery. METHODS: Information was collected in the five GenEd partner countries (France, Germany, Netherlands, Sweden, and the UK) by reviewing published curricula and web sites and by directly contacting educational and regulatory organizations. Information was also requested from a further six South and East European collaborators (Greece, Hungary, Italy, Lithuania, Poland, and Spain). RESULTS: Health professional education and training differed in structure with wide variation in the content and duration of genetic education provided. France and Germany have national undergraduate medical curricula but with minimal overt genetic content, mainly confined to basic science courses. In Sweden, Netherlands, and the UK, the content is largely at the discretion of individual universities. Evidence from the UK, France, and Germany indicates that genetic professionals are influencing the genetic content of medical curricula. In postgraduate training, some specialist regulators have adopted specific genetic educational requirements, but many programs lack any explicit genetics. Within each country many organizations have responsibility for setting, assessing, and delivering medical and midwifery education. CONCLUSIONS: Due to the multiplicity of organizations involved in the provision of genetic education, changing professional education is likely to be challenging. However, it may be that development of a multiprofessional consensus across Europe is achievable. The strategy adopted by the US National Coalition for Health Professional Education in Genetics may be helpful.
A DH population containing 81 DH lines from an indica-japonica cross of rice and an RFLP linkage map consisting of 232 markers were used to map quantitative trait loci(QTLs) for harvest index, biomass, grain yield, sink capacity and plant height by a computer program QTLMapper1.0 based on mixed linear models. A total of 21 significant main-effect QTLs and 9 pairs of epistatic loci were detected. Of these, three detected QTLs for grain yield collectively accounted for 42% of the phenotypic variation with a LOD of 7.10. These three grain yield QTLs were corresponded either to QTLs for harvest index or QTLs for biomass in both locations and directions of additive effects, which sheds light on the genetic basis of the formula 'grain yield = biomass x harvest index'. Four detected QTLs for harvest index collectively explained 46% of the total phenotypic variation and four QTLs for biomass jointly accounted for 64% of the trait variation. No coincidence of harvest index QTLs with any biomass QTLs was found, therefore indicating the possibility of pyramiding favorable alleles for both traits through gene recombination so as to obtain a genotype possessing both high harvest index and heavy plant biomass. Five QTLs for plant height were detected that cumulatively explained 64% of the phenotypic variation with a LOD of 11.62. Among these, three with smaller effects respectively co-located with some of the QTLs for biomass, sink capacity and/or grain yield, but not with any of harvest index QTLs, thus suggesting that plant height was to some extent directly associated with 'source' and 'sink' but not with 'transportation' of the 'source-transportation-sink' concept, at least in this genetic background and environment. In view of a somewhat low resolution of the genetic map used in the study and the fact that when plant height QTLs co-located with those for yield and/or yield related traits, these co-located QTLs were all in the same directions of additive effects, it is more likely that these QTLs co-located in a same chromosomal region might be a single QTL which have effects on multiple traits. If this is true, the above observation have led us to assume that QTLs which have pleotropic effects on yield and/or yield related traits and plant height are very different from those which had relatively large effects only on plant height. The former contribute strongly to yield and/or yield related traits but weakly to plant height while the later contribute mainly to plant height. Obviously, due to that an increase of plant height is always coupled with an increase in lodging susceptibility, discriminating between above two types of QTLs is critical in breaking the traits' undesired association in breeding for improved yield potential of rice. In addition, based on the co-location analysis of main-effect QTLs for the studied traits, five genomic regions were found to be highly associated with harvest index, biomass, sink capacity and grain yield.
The problem addressed is that of determining the similarities and differences appearing in a sequence of two-dimensional polyacrylamide gels where we have no a priori knowledge of the intensity and spatial distribution of the protein spots. It is assumed that the gels are not in precise registration. An attempt is being made to develop a completely automatic program for use in genetic studies, which will compare a sequence of three gels run on samples from father, mother, and child. The program constructs a graph by using as nodes those spot cues that exceed a given intensity threshold. The graphs are then compared to determine an initial subset of spots that are common to all three gels. From this subset of common spots the program then determines whether the remaining graph differences are real or result from quantitative variation causing spots to fall below threshold.
The long arm of the human Y chromosome is flecked with various fractions of repetitive DNA. DYZ1 is one such fraction, which is organized tandemly as an array of a 3.4-kb repeat ranging from 2000-4000 copies in normal males. We have studied the organizational variation of the DYZ1 fraction on the human Y chromosome using DNA samples from CEPH family members and the random population employing the RFLP approach, fluorescence in situ hybridization (FISH), and conducted a similarity search with GenBank sequences. Typing of genomic DNA using DYZ1 as a probe showed an allele length and copy number variations even between two male siblings. Hybridization of DNA from monochromosome hybrids with this probe showed its presence on chromosome 15 in addition to the Y chromosome. Fluorescence in situ hybridization of metaphase chromosomes from an apparently normal male showed DYZ1 sequences in the proximal region of chromosome 11 in addition to the long arm of the Y chromosome. Typing of sets of semen and blood DNA samples from the same human individuals showed discernible allelic variation between the two samples, indicating tissue-specific programmed sequence modulation. DYZ1 seems to be the first probe having the unique potential to discriminate unequivocally the difference between the DNA originating from semen and blood samples, and may be exploited in forensic cases. This probe may also be used as a diagnostic tool to ascertain Y chromosome mosaicism in patients (e.g., Turner), its aberrant status in somatic cells, and possible sequence modulation/rearrangement in the germline samples. Additionally, this can be used to uncover sequence polymorphism in the human population.
Biological control of insects that feed on our crops has become more practical in recent years by mass release of egg parasitoid microhymenoptera. Trichogramma species are now commercially reared and spread in commercial fields to control specific insect pests. Microhymenoptera species are, however, very small and morphologically indistinguishable within species, although strains of a given species differ in their efficiency to control specific insect pests. Traditional taxonomy is unable to differentiate microhymenoptera species at the strain level. It is becoming increasingly important to develop a reliable system to monitor genetic variations both within and between strains of commercially important microhymenoptera, to detect genetic drift occurring during several generations of multiplication, to protect patents, and to certify the lots of commercially released microhymenoptera. We have developed a system based on DNA markers to rapidly characterize individuals of five species of microhymenoptera from the genus Anaphes and Trichogramma including a new species of Anaphes not previously described. The main components of our system are a rapid and simple DNA micro-extraction method and fast DNA polymorphism analyses based on random amplified polymorphic DNA markers.
This study focuses on the standardization of techniques across laboratories to enable multiple datasets to be compared and combined in order to obtain reliable and robust wide-scale patterns of diversity. A set of protocols using a core collection of simple sequence repeat (SSR) markers, reference lines and standard alleles, plus a common system of allele nomenclature, was adopted in the study of maize genetic diversity in a network of laboratories in Asia. Pair-wise allele comparisons of the reference lines, done to assess the general agreement between datasets from four laboratories, showed error rates (raw) ranging from 5.8% to 9.7%, which were reduced to less than 8% after adjustments of correctable errors, and further reduced to less than 6% after the exclusion of all markers with greater than 10% individual error rates. Overall, 45% of the total mismatches were due to frameshift errors, 39% to wrong allele size, 15% to failed amplification and 1% to "extra" alleles. Higher genetic similarity values of the reference lines were achieved using fewer markers with data of higher quality rather than with more markers of questionable quality. Cluster analysis of the merged datasets showed the lines from southern China to be highly diverse, falling into six of the seven clusters observed and all well represented by tester lines. The lines from Indonesia fell into five of six groups, with two main groups represented by tester lines. The CIMMYT lines developed for the Asian region showed a relatively narrow genetic base, falling in two out of seven and in three out of six clusters in China and Indonesia, respectively. In contrast to the case in southern China where 95% of the lines clustered separately from the CIMMYT lines, lines in the Indonesian breeding program show a closer relationship with the CIMMYT lines, reflecting a long history of germplasm exchange.
Genetic diversities based on the mtDNA control region were measured for both a wild population (n = 26) and a captive population (n = 18) of the black muntjac. In total, nine haplotypes were obtained from 44 samples. The wild population exhibited a low nucleotide diversity (pi = 0.00562), which suggests that the black muntjac had a small effective population size historically. In contrast to its low nucleotide diversity, haplotype diversity (h = 0.862) of the wild population was relatively high. Haplotype distribution among local samples shows a distinct difference. As anticipated because of the paucity of available founders, nucleotide diversity (pi = 0.00214) of the captive population was very low. Additionally, a high degree of haplotype identity and an obvious haplotype frequency bias was revealed in the captive population, which implies that the current breeding program should be readjusted to balance distributions of haplotypes, and some new founders should be introduced to the captive population to alleviate potential inbreeding depression.
Eighteen Trypanosoma cruzi strains isolated from naturally infected triatomines were studied genetically. The majority of the strains were from Triatoma brasiliensis, the principal vector of Chagas disease in the northeast of Brazil. Multilocus enzyme electrophoresis (MLEE) and randomly amplified polymorphic DNA (RAPD) analyses were used to investigate the genotypic diversity and the spread of the T. cruzi genotypes in different environments. MLEE clearly distinguished two distinct isoenzyme profiles, and RAPD analysis revealed 10 different genotypes circulating in rural areas. The strains could be typed as isoenzyme variants of the T. cruzi principal zymodeme Z1 (T. cruzi I). An effective program of epidemiological vigilance is required to prevent the spread of T. cruzi I strains into human dwellings.
The domestication of the dog from its wolf ancestors is perhaps the most complex genetic experiment in history, and certainly the most extensive. Beginning with the wolf, man has created dog breeds that are hunters or herders, big or small, lean or squat, and independent or loyal. Most breeds were established in the 1800s by dog fanciers, using a small number of founders that featured traits of particular interest. Popular sire effects, population bottlenecks, and strict breeding programs designed to expand populations with desirable traits led to the development of what are now closed breeding populations, with limited phenotypic and genetic heterogeneity, but which are ideal for genetic dissection of complex traits. In this review, we first discuss the advances in mapping and sequencing that accelerated the field in recent years. We then highlight findings of interest related to disease gene mapping and population structure. Finally, we summarize novel results on the genetics of morphologic variation.
An experiment was conducted to estimate genetic parameters in six experimental and five commercial primary breeding turkey lines using DNA fingerprinting. Eighteen individual DNA samples per line were digested with an HaeIII restriction enzyme and hybridized with Jeffreys' 33.6 probe. The DNA fingerprints were analyzed with computer programs to measure band sharing (BS) and band frequencies. Within lines, BS ranged from 0.39 to 0.62 and reflected the history of the experimental lines. Among lines, BS ranged from 0.21 to 0.33 with an average of 0.26. The BS among the experimental lines reflected known relationships. All lines were subdivided based on indices of population subdivision. About 26 hypervariable loci were estimated from band frequencies. Average heterozygosity and genetic variability estimated from band frequencies were significantly different among lines and displayed a result very similar to the BS among lines. Genetic distance indices among lines were also significantly different and reflected known relationships between the experimental lines. The experimental selected lines displayed lower genetic diversity than did the other lines. The parameters measuring genetic diversity within lines had higher correlation coefficients among them than did the parameters between lines. The computer program used in this study made DNA fingerprinting easier to use in population analysis.
Random Amplified Polymorphic DNA (RAPD) and Inter-simple Sequence Repeat (ISSR) methods were used to detect the genetic diversity of 57 allelopathic rice accessions which were introduced from 10 countries or areas. A total of 12 RAPD primers and seven ISSR primers were indentified with polymorphism among the entries. For RAPD markers, 85 polymorphic bands were produced, percentage of polymorphic bands (PPB) were 69.4%. For ISSR marker, 34 polymorphic bands were generated, PPB were 53.0%. The result from the clustering analysis by UPGMA indicated that those accessions from the same geographical location were clustered into one group. It was also found that some rice accessions with higher allelopathic potential were clustered together, implying that the genes conferring allelopathy in those rice accessions might be isolocus. However, some rice accessions with different allelopathic potential clustered into the same group performed lower level of generic polymorphism which was attributed to oriented selection for other traits in breeding program. The estimates of correlation coefficient of RAPD and ISSR based on the genetic similarity matrices were significantly correlated.
Seventy cocoyam accessions collected from the eastern and Volta regions of Ghana were studied using RAPD technique. Ten primers were used to study the genetic diversity and structure of the experimental material and a total of 120 different bands were detected. Levels of polymorphic fragments detected by the ten primers ranged from 69.2% to 100%. In the accessions from the eastern region, the mean observed and effective number of alleles per individual per population and mean Nei's gene diversity were 1.99+/-0.01, 1.53+/-0.12 and 0.312+/-0.05, respectively. Mean observed and effective number of alleles per individual per population and Nei's gene diversity were 1.76+/-0.17, 1.44+/-0.16 and 0.264+/-0.08, respectively for the accessions from the Volta region. Considering the entire collections, the mean observed and effective number of alleles per individual per population and Nei's gene diversity for primers were 1.99+/-0.02, 1.54+/-0.12 and 0.319+/-0.05, respectively. In terms of Nei's F-statistics in the subdivided populations for all primers, the overall gene diversity (Ht) ranged from 0.230 to 0.396 with a mean of 0.313+0.06, within sample gene diversity (Hs) ranged from 0.214 to 0.372 with a mean of 0.286+0.06, gene differentiation (Gst) ranged between 0.005 and 0.178 with a mean of 0.086. Geneflow estimate ranged between 2.309 and 99.500 with a mean of 5.314. The accessions grouped into three main clusters. Accession BD96/183 was the most diverse and may be incorporated into cocoyam breeding programs. The 70 accessions did not cluster into their distinct geographical regions suggesting that there may have been movement of germplasm across the two regions.