Fitting genetic mapping functions based on sperm typing: results for three chromosomal segments in cattle

Genetic mapping functions translate the observed recombination rate between two loci into the corresponding map distance in Morgan units. Different mapping functions give different weights to multiple crossing overs and therefore lead to different results. This points out that not every function is best suited to fit a data set. The data used in this study originated from 2214 sperm from 37 Norwegian bulls, which were genotyped for 11 markers. The optimal functions for the chromosomes 6, 23 and the sex chromosome of cattle were derived using the maximum likelihood method, the likelihood ratio test and empirical discriminant analysis. It became apparent that for each chromosome a different function fitted the data best. These were the function of Rao et al. (Human Heredity 1977, 27, 99–104) with p = 0·63 for chromosome 6, the function of Goldgar & Fain (American Journal of Human Genetics 1988, 43, 38–45) with c₀ = 0·42, c₁ = 0·47, c₂ = 0·07 and c₃ = 0·04 for chromosome 23 and the function of Felsenstein (Genetics 1979, 91, 769–75) with K = 0·23 for the sex chromosome. The well known functions of Haldane (Journal of Genetics 1919, 8, 299–309) and Kosambi (Annals of Eugenics 1944, 12, 172–5) were shown to be suboptimal in most cases. A function is said to be multilocus feasible if the evaluation of the probability of all possible recombination events does not lead to negative values. The optimal function for chromosome 23 turned out to be multilocus feasible, whereas the functions for chromosome 6 and the sex chromosome were not. The choice of the correct mapping function is shown to have a considerable impact in mapping studies, when double recombinations have to be taken into account. Since there is no unique best mapping function, it is argued that it might be useful to use a simple parametric mapping function (like the one of Felsenstein 1979) and to estimate the respective parameter specifically for a given data set.     

A Simplified Newton Method for Computing the Factor Loadings in Maximum Likelihood Factor Analysis

A simplified Newton iteration scheme for computation of factor loadings in maximum likelihood factor analysis is described. It operates in the space of factor loadings and avoids eigenvalue problems. From this, a comparatively small computational effort results. Besides of the case of positive unique variances, also the Heywood case is considered, where some unique variances vanish. The ability of the proposed method is demonstrated in three examples, results and iteration process are compared with data given in literature.     

Mapping tsetse habitat suitability in the common fly belt of Southern Africa using multivariate analysis of climate and remotely sensed vegetation data

Abstract The distribution of Glossina morsitans centralis, Glossina morsitans morsitans and Glossina pallidipes are described in part of southern Africa, using a range of multivariate techniques applied to climate and remotely sensed vegetation data. Linear discriminant analysis is limited in its predictive power by the assumption of common co-variances in the classes within multivariate environment space. Maximum likelihood classification is one of a variety of alternative methods that do not have this constraint, and produce a better prediction, particularly when a priori probabilities of presence and absence are taken into account. The best predictions are obtained when the habitat is subdivided, prior to classification, on the basis of a bimodality detected on the third component axis of a principal component analysis. The results of the predictions were good, particularly for G.m.centralis and G.m.morsitans , which gave overall correct predictions of 92.8% and 85.1 %, with a Kappa index of agreement between the predion and the training data of 0.7305 and 0.641 respectively. For G.pallidipes , 91.7% of predictions were correct but the value of Kappa was only 0.549. Very clear differences are demonstrated between the habitats of the two subspecies Gmxentralis and G.m.morsitans.     

富营养化城市湖泊武汉东湖沉积物微生物群体结构及空间变化研究

【目的】城市湖泊沉积物中的微生物群体是富营养环境生物修复的重要因素。本研究拟对中型富营养化湖泊——武汉东湖沉积物细菌群体结构及空间变化规律进行研究。加深对富营养湖泊微生物群体结构的理解,并为城市湖泊的保护和污染控制提供参考。【方法】采用16S r RNA基因RFLP分析和序列分析技术获得细菌群体系统发育信息。采用PCoA法分析武汉东湖沉积物细菌群体内以及与其它湖泊沉积物细菌群体间的相似性。采用CCA法分析环境因素对细菌群体的影响。【结果】武汉东湖沉积物细菌群体包含13个门和2个未知种群。PCoA分析进一步表明来自东湖3个子湖的细菌群体与其它地域富营养化湖泊的微生物种群结构相似,并区别于重度富营养化子湖庙湖的细菌群体。在庙湖中,我们发现了Thermogymnomonas类古菌的含量显著偏高。CCA分析表明细菌的分布与沉积物中碳、氮和磷元素的含量显著相关。【结论】本研究进一步确证了环境因素对细菌群体组成和分布的调节作用,加深了对富营养水体微生物群体结构的理解,并为城市湖泊的保护和污染控制提供了参考。     

Adaptation and speciation of Dolichopoda cave crickets (Orthoptera, Rhaphidophoridae): geographic variation of morphometric indices and allozyme frequencies

Morphometric analyses were carried out for 14 cave dwelling populations of Dolichopoda (Orthoptera, Rhaphidophoridae) from peninsular Italy belonging to the laetitiae-geniculata complex. The selected set of variables includes linear measures of body parts and appendages whose variation is expected to be adaptive and to reflect the degree of specialization to the cave environment.
Inter-population morphometric variation was compared with the patterns of allozyme variation, investigated electrophoretically in a previous paper, by means of ordination and classification multivariate analyses. Results from this comparison reject the hypothesis of parallel geographic variation of morphometric indices and allele frequencies, revealing independent trends for the two sets of characters.     

Codon substitution models based on residue similarity and their applications

Codon models are now widely used to draw evolutionary inferences from alignments of homologous sequence data. Incorporating physicochemical properties of amino acids into codon models, two novel codon substitution models describing the evolution of protein-coding DNA sequences are presented based on the similarity scores of amino acids. To describe substitutions between codons a continue-time Markov process is used. Transition/transversion rate bias and nonsynonymous codon usage bias are allowed in the models. In our implementation, the parameters are estimated by maximum-likelihood (ML) method as in previous studies. Furthermore, instantaneous mutations involving more than one nucleotide position of a codon are considered in the second model. Then the two suggested models are applied to five real data sets. The analytic results indicate that the new codon models considering physicochemical properties of amino acids can provide a better fit to the data comparing with existing codon models, and then produce more reliable estimates of certain biologically important measures than existing methods.     

Genome-wide association to fine-scale ecological heterogeneity within a continuous population of Biscutella laevigata (Brassicaceae)

Gene flow, drift and selection can be detected through different signatures across the genome and the landscape. Genetic discontinuities along with their correlation to environmental features can be used to tease out isolation-by-distance and isolation-by-time from processes related to selection. Using spatial statistics (spatial autocorrelation methods, canonical correspondence analysis and partial Mantel tests) dealing with genome-wide amplified fragment length polymorphism (AFLP) under unlikely Hardy-Weinberg assumptions, this study investigates 124 individuals within a continuous population of the autopolyploid Biscutella laevigata (Brassicaceae). Fine-scale spatial genetic structure was strong and the mosaic-like distribution of AFLP genotypes was consistently associated with habitat factors, even when controlled for geographical distances. The use of multivariate analyses enabled separation of the factors responsible for the repartition of the genetic variance and revealed a composite effect of isolation by distance, phenological divergence and local adaptation to habitats characterised by different solar radiation regimes. These results suggest that the immigrant inviability barrier facilitated the maintenance of adapted subpopulations to distinct environmental conditions at the local scale.     

Population genetic structure and trait associations in forest savory using molecular,morphological and phytochemical markers

In this investigation, morphological, phytochemical and ISSR markers were used to estimate the relationships among and within seven populations of white savory (Satureja mutica), belonging to four provinces in Iran. The individuals were phenotypically diverse, which stamen length, corolla length, corolla diameter, calyx length, bract length, inflorescence length, calyx length and bracteole width were characteristics with the highest variation. Leaf dimensions were in significant correlation with flower and inflorescence characteristics. Chemical compounds of essential oils were found variable in various individuals and all samples were principally composed of phenolic constituents (carvacrol and/or thymol). As a consequence, the plants were classified into two major chemotypes including carvacrol and thymol. A total of 197 band positions were produced by 14 ISSR primers, of which 176 were found polymorphic with 88.91% polymorphism. ISSR genetic similarity values among individuals ranged between 0.45 and 0.94 which was indicative of a high level of genetic variation. Multiple regression analysis (MRA) revealed that phytochemical compositions as dependent variable, showed statistically significant correlation and in association with leaf and flower traits as independent variable, indicating a main role of leaf and flower on production of these compounds. Also, several ISSR fragments were found associated with some morphological traits and phytochemical compositions. The high diversity within and among populations of S. mutica according to different data systems could provide useful information for conservation and selection of cross-parents in breeding programs.     

A General Computing Algorithm for Factor Analysis

A general algorithm for the factor analysis is developed, which contains the alpha factor analysis, the maximum likelihood method and the minres method as special cases. This algorithm, which is a multidimensional NEWTON algorithm, uses the partial derivatives of the reproduced communalities with respect to the inserted ones. The partial derivatives are got by means of the perturbation theory.