Genetic variance and covariance patterns for body weight and energy balance characters in an advanced intercross population of mice

We estimated heritabilities and genetic correlations for a suite of 15 characters in five functional groups in an advanced intercross population of over 2000 mice derived from a cross of inbred lines selected for high and low heat loss. Heritabilities averaged 0.56 for three body weights, 0.23 for two energy balance characters, 0.48 for three bone characters, 0.35 for four measures of adiposity, and 0.27 for three organ weights, all of which were generally consistent in magnitude with estimates derived in previous studies. Genetic correlations varied from -0.65 to +0.98, and were higher within these functional groups than between groups. These correlations generally conformed to a priori expectations, being positive in sign for energy expenditure and consumption (+0.24) and negative in sign for energy expenditure and adiposity (-0.17). The genetic correlations of adiposity with body weight at 3, 6, and 12 weeks of age (-0.29, -0.22, -0.26) all were negative in sign but not statistically significant. The independence of body weight and adiposity suggests that this advanced intercross population is ideal for a comprehensive discovery of genes controlling regulation of mammalian adiposity that are distinct from those for body weight.     

Genome Annotator Light (GAL): A Docker-based package for genome analysis and visualization

Next generation sequencing techniques produce enormous data but its analysis and visualization remains a big challenge. To address this, we have developed Genome Annotator Light(GAL), a Docker based package for genome analysis and data visualization. GAL integrated several existing tools and in-house programs inside a Docker Container for systematic analysis and visualization of genomes through web browser. GAL takes varieties of input types ranging from raw Fasta files to fully annotated files, processes them through a standard annotation pipeline and visualizes on a web browser. Comparative genomic analysis is performed automatically within a given taxonomic class. GAL creates interactive genome browser with clickable genomic feature tracks; local BLAST-able database; query page, on-fly downstream data analysis using EMBOSS etc. Overall, GAL is an extremely convenient, portable and platform independent. Fully integrated web-resources can be easily created and deployed, e.g. www.eumicrobedb.org/cglab, for our in-house genomes. GAL is freely available at https://hub.docker.com/u/cglabiicb/.     

learnPopGen: An R package for population genetic simulation and numerical analysis

Here, I briefly present a new R package called learnPopGen that has been designed primarily for the purposes of teaching evolutionary biology, population genetics, and evolutionary theory. Functions of the package can be used to conduct simulations and numerical analyses of a wide range of evolutionary phenomena that would typically be covered in advanced undergraduate through graduate‐level curricula in population genetics or evolution. For instance, learnPopGen functions can be used to visualize gene frequency changes through time under multiple deterministic and stochastic processes, to compute and animate the changes in phenotypic trait values or distributions under natural selection, to numerically analyze and graph the outcome of simple game theory models, and to plot coalescence within a population experiencing genetic drift, along with a number of other things. Functions have been designed to be maximally didactic and frequently employ compelling animated visualizations. Furthermore, it is straightforward to export plots and animations from R in the form of flat or animated graphics, or as videos. For maximum flexibility, students working with the package can run functions directly in R; however, instructors may choose to guide students less adept in the R environment to one of various web interfaces that I have built for a number of the functions of the package and that are already available online.     

Genome analysis of Peromyscus (Rodentia,Cricetidae)

A satellite DNA fraction from P. eremicus, having a buoyant density of 1.705 g/ml in neutral CsCl density gradients, was isolated. In situ hybridization experiments, using 3H-RNA complementary to this DNA fraction indicated that the short (heterochromatic) arms of most of the autosomes contained this sequence. Conversely, in situ hybridization using 3H-complementary DNA (cDNA) synthesized from the cytoplasmic poly (A) RNA of P. eremicus (comprising a substantial fraction of total messenger RNA) showed that the number of silver grains in the long arms (euchromatin) was significantly higher than that in the short arms. The X chromosomes showed a distinct localization pattern of both sequences.     

CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure

MOTIVATION: Clustering of individuals into populations on the basis of multilocus genotypes is informative in a variety of settings. In population-genetic clustering algorithms, such as BAPS, STRUCTURE and TESS, individual multilocus genotypes are partitioned over a set of clusters, often using unsupervised approaches that involve stochastic simulation. As a result, replicate cluster analyses of the same data may produce several distinct solutions for estimated cluster membership coefficients, even though the same initial conditions were used. Major differences among clustering solutions have two main sources: (1) 'label switching' of clusters across replicates, caused by the arbitrary way in which clusters in an unsupervised analysis are labeled, and (2) 'genuine multimodality,' truly distinct solutions across replicates. RESULTS: To facilitate the interpretation of population-genetic clustering results, we describe three algorithms for aligning multiple replicate analyses of the same data set. We have implemented these algorithms in the computer program CLUMPP (CLUster Matching and Permutation Program). We illustrate the use of CLUMPP by aligning the cluster membership coefficients from 100 replicate cluster analyses of 600 chickens from 20 different breeds. AVAILABILITY: CLUMPP is freely available at http://rosenberglab.bioinformatics.med.umich.edu/clumpp.html.     

Permutation methods for the structured exploratory data analysis (SEDA) of familial trait values.

A collection of functions that contrast familial trait values between and across generations is proposed for studying transmission effects and other collateral influences in nuclear families. Two classes of structured exploratory data analysis (SEDA) statistics are derived from ratios of these functions. SEDA-functionals are the empirical cumulative distributions of the ratio of the two contrasts computed within each family. SEDA-indices are formed by first averaging the numerator and denominator contrasts separately over the population and then forming their ratio. The significance of SEDA results are determined by a spectrum of permutation techniques that selectively shuffle the trait values across families. The process systematically alters certain family structure relationships while keeping other familial relationships intact. The methodology is applied to five data examples of plasma total cholesterol concentrations, reported height values, dermatoglyphic pattern intensity index scores, measurements of dopamine-beta-hydroxylase activity, and psychometric cognitive test results.     

Model-free analysis and permutation tests for allelic associations

In this short report, we address some practical problems in performing likelihood-based allelic association analysis of case-control data. Model-free statistics are proposed and their properties assessed by simulation, and procedures based on permutation tests are described for marker-marker as well as marker-disease associations. A memory-efficient algorithm is developed which enables several highly polymorphic markers to be analysed.     

ScreenClust: Advanced statistical software for supervised and unsupervised high resolution melting (HRM) analysis

Background: High resolution melting (HRM) is an emerging new method for interrogating and characterizing DNA samples. An important aspect of this technology is data analysis. Traditional HRM curves can be difficult to interpret and the method has been criticized for lack of statistical interrogation and arbitrary interpretation of results. Methods: Here we report the basic principles and first applications of a new statistical approach to HRM analysis addressing these concerns. Our method allows automated genotyping of unknown samples coupled with formal statistical information on the likelihood, if an unknown sample is of a known genotype (by discriminant analysis or “supervised learning”). It can also determine the assortment of alleles present (by cluster analysis or “unsupervised learning”) without a priori knowledge of the genotypes present. Conclusion: The new algorithms provide highly sensitive and specific auto-calling of genotypes from HRM data in both supervised an unsupervised analysis mode. The method is based on pure statistical interrogation of the data set with a high degree of standardization. The hypothesis-free unsupervised mode offers various possibilities for de novo HRM applications such as mutation discovery.     

Genome Information Broker (GIB): data retrieval and comparative analysis system for completed microbial genomes and more

Genome Information Broker (GIB) is a powerful tool for the study of comparative genomics. GIB allows users to retrieve and display partial and/or whole genome sequences together with the relevant biological annotation. GIB has accumulated all the completed microbial genome and has recently been expanded to include Arabidopsis thaliana genome data from DDBJ/EMBL/GenBank. In the near future, hundreds of genome sequences will be determined. In order to handle such huge data, we have enhanced the GIB architecture by using XML, CORBA and distributed RDBs. We introduce the new GIB here. GIB is freely accessible at http://gib.genes.nig.ac.jp/.     

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular protein's structure, its function, and its relationships with other proteins. SGD can be accessed through the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/     

种群生存力分析（PVA）的方法与应用

随着人们对资源的加速利用,生境丧失和破碎化导致物种濒危问题日益严重.以岛屿生物地理学为理论起源的种群生存力分析（PVA）,通过分析和模拟种群动态过程并建立灭绝概率与种群数量之间的关系,为濒危物种保护提供了重要的理论依据和研究途径.在过去的几十年中,种群生存力分析已成为保护生物学中一项重要的研究内容.目前种群生存力分析发展稳定,但对其实际预测能力和准确性尚存质疑,应用方面也有待进一步发展.种群生存力分析的进一步完善还需要在理论和方法上的创新,特别是籍于景观生态学和可持续性科学的理念,将空间分析手段、经济社会因素纳入到物种和种群的预测和管理上,从而使其具有更完整的理论基础和更高的实用价值.为此,本文对种群生存力分析的历史、基本概念、研究方法、模型应用和准确性进行了综述,并提出了有关的研究展望.     

Energy flow and the persistence of a human population: A simulation analysis

A human ecosystem model, NUÑOA, simulates the yearly energy balance of individuals, families, and extended families in a hypothetical farming and herding community of Quechua Indians in the high Andes. The yearly energy demand of each family, based on the caloric requirements of its members, is computed by simulation of agricultural and herding activities in response to stochastic environmental conditions. The family energy balance is used in determining births, deaths, marriages, and resource sharing. The model user has the opportunity to investigate the effect of changes in marriage patterns, resource sharing patterns, or subsistence activities on the ability of the human population to survive in the harsh Andean environment. Results from the model suggest that the substructuring of a population into extended families provides a mechanism for sheltering the population from control by exogenous influences. A population without substructures for resource sharing is shown to be unstable in such an unpredictable environment.Research supported by the National Science Foundation's Ecosystem Studies Program under Interagency Agreement No. DEB-77-25781 with the U.S. Department of Energy under contract W-7405-eng-26 with Union Carbide Corporation.Publication No. 1966, Environmental Science Division, ORNL.     

Genome sizes of cranes (Aves: Gruiformes)

The DNA content of blood cell nuclei of 15 species of cranes was determined by Feulgen-DNA cytophotometry. Genome sizes agree with values reported elsewhere for several crane species analyzed by flow cytometry. Males have more DNA per cell than females in several species. A karyotype where 2n = 80 is reported for a male greater sandhill crane.     

Genome constitution for Musa beccarii (Musaceae) varieties

Borneo is a large island in Southeast Asia. It is divided politically into three parts: the kingdom of Brunei on the north central coast; the Malaysian states of Sarawak and Sabah to the west and east; with Kalimantan of Indonesia making up the larger par…     

Important population viability analysis parameters for giant pandas (Aliuropoda melanoleuca)

Population viability analysis(PVA) is a tool to evaluate the risk of extinction for endangered species and aid conservation decision-making.The quality of PVA output is dependent on parameters related to population dynamics and life-history;however,it has been difficult to collect this information for the giant panda(Aliuropoda melanoleuca),a rare and endangered mammal native to China,confined to some 30 fragmented habitat patches.Since giant pandas are long-lived,mature late,have lower reproductive rates,and show little sexual dimorphism,obtaining data to perform adequate PVA has been difficult.Here,we develop a parameter sensitivity index by modeling the dynamics of six giant panda populations in the Minshan Mountains,in order to determine the parameters most influential to giant panda populations.Our data shows that the giant panda populations are most sensitive to changes in four female parameters:initial breeding age,reproductive rate,mortality rate between age 0 and 1,and mortality rate of adults.The parameter sensitivity index strongly correlated with initial population size,as smaller populations were more sensitive to changes in these four variables.This model suggests that demographic parameters of females have more influence on the results of PVA,indicating that females may play a more important role in giant panda population dynamics than males.Consequently,reintroduction of female individuals to a small giant panda population should be a high priority for conservation efforts.Our findings form a technical basis for the coming program of giant panda reintroduction,and inform which parameters are crucial to successfully and feasibly monitoring wild giant panda populations.     

Backcross and partial advanced intercross analysis of nonobese diabetic gene-mediated effects on collagen-induced arthritis reveals an interactive effect by two major loci

Genetic segregation analysis between NOD and C57BL strains have been used to identify loci associated with autoimmune disease. Only two loci (Cia2 and Cia9) had earlier been found to control development of arthritis, whereas none of the previously identified diabetes loci was of significance for arthritis. We have now made a high-powered analysis of a backcross of NOD genes on to the B10.Q strain for association with collagen-induced arthritis. We could confirm relevance of both Cia2 and Cia9 as well as the interaction between them, but we did not identify any other significant arthritis loci. Immune cellular subtyping revealed that Cia2 was also associated with the number of blood macrophages. Congenic strains of the Cia2 and Cia9 loci on the B10.Q background were made and used to establish a partial advanced intercross (PAI). Testing the PAI mice for development of collagen-induced arthritis confirmed the loci and the interactions and also indicated that at least two genes contribute to the Cia9 locus. Furthermore, it clearly showed that Cia2 is dominant protective but that the protection is not complete. Because these results may indicate that the Cia2 effect on arthritis is not only due to the deficiency of the complement C5, we analyzed complement functions in the Cia2 congenics as well as the PAI mice. These data show that not only arthritis but also C5-dependent complement activity is dominantly suppressed, confirming that C5 is one of the major genes explaining the Cia2 effect.     

A simulation study of population interaction between the greenhouse whitefly,Trialeurodes vaporariorum Westwood (Homoptera: Aleyrodidae) and the parasitoidEncarsia formosa Gahan (Hymenoptera: Aphelinidae) II. Simulation analysis of population dynamics and strategy of biological control

Simulation studies were performed to analyze factors affecting the population dynamics of the system with the greenhouse whitefly (Trialeurodes vaporariorumWestwood ) and the parasitoid Encarsia formosaGahan and to develop strategies for the introduction of E. formosa. The reduction of parasitization efficiency with an increase in parasitoid density promotes the stability of the system, which coincides with the prediction from current theory. The stability of the system is also shown to be promoted by the effect of host feeding. The population levels of the system are remarkably suppressed with an increase in searching efficiency and a decrease in host oviposition. The control effect of the parasitoids is enhanced when the number of parasitoids is divided among many introductions. An optimal time, an optimal density ratio of parasitoids to hosts and optimal densities of hosts and parasitoids exist in the introduction programme of parasitoids.