Thermolabile phenotype of carnitine palmitoyltransferase II variations as a predisposing factor for influenza-associated encephalopathy

To assess the etiology of influenza-associated encephalopathy (IAE), a surveillance effort was conducted during 2000-2003 in South-West Japan. All fatal and handicapped patients except one (4/34 patients) exhibited a disorder of mitochondrial beta-oxidation evoked by the inactivated carnitine palmitoyltransferase II (CPT II) with transiently elevated serum acylcarnitine ratios (C(16:0) + C(18:1))/C(2) > 0.09 during high-grade fever. Analyses of genotypes and allele compositions of CPT II revealed a thermolabile phenotype of compound heterozygotes for [1055T > G/F352C] and [1102G > A/V368I], which shows a higher frequency in IAE patients than healthy volunteers (P < 0.025). The thermolabile phenotype of CPT II variations may be a principal genetic background of IAE in Japanese.     

Intermittent altitude exposures improve muscular performance at 4,300 m.

Chronic altitude residence improves muscular performance at altitude, but the effect of intermittent altitude exposures (IAE) on muscular performance at altitude has not been defined. The purpose of this study was to determine the effects of 3 wk of IAE, in combination with rest and cycle training, on muscular performance at altitude. Six lowlanders (23 +/- 2 yr, 77 +/- 6 kg; means +/- SE) completed a cycle time trial and adductor pollicis endurance test at sea level and during a 30-h acute exposure to 4,300 m altitude equivalent (barometric pressure = 446 mmHg) once before (pre-IAE) and once after (post-IAE) a 3-wk period of IAE (4 h/day, 5 days/wk, 4,300 m). During each IAE, three subjects cycled for 45-60 min/day at 60%-70% of maximal O2 uptake and three subjects rested. Cycle training during each IAE did not appear to affect muscular performance at altitude. Thus data from all six subjects were combined. Three weeks of IAE resulted in 1) a 21 +/- 6% improvement (P < 0.05) in cycle time-trial performance (min) from pre-IAE (32.8 +/- 3.7) to post-IAE (24.8 +/- 1.2), 2) a 63 +/- 26% improvement (P < 0.05) in adductor pollicis endurance (min) from pre-IAE (9.2 +/- 2.8) to post-IAE (14.8 +/- 4.2), and 3) a 10 +/- 4% increase (P < 0.05) in resting arterial O2 saturation (%) from pre-IAE (82 +/- 2) to post-IAE (90 +/- 1). These improvements in muscular performance after IAE correlated strongly with increases in resting arterial O2 saturation and were comparable to those reported previously after chronic altitude residence. IAE may therefore be used as an alternative to chronic altitude residence to facilitate improvements in muscular performance in athletes, soldiers, mountaineers, shift workers, and others that are deployed to altitude.     

Comparative analysis of core collection sampling methods for mandarin germplasm based on molecular and phenotypic data

Gene banks have been established to conserve the genetic diversity of crop species. Large germplasm collections lead to management problems (space, maintenance costs, etc.), especially in collections involving species with recalcitrant seeds that must be maintained as growing plants. Core collections (CCs) are thus developed to reduce the size of large germplasm collections while keeping the maximum variability. This also facilitates fine phenotypic evaluation. In this study, several software packages (DARwin, PowerMarker and MSTRAT) and methods (Max length subtree, M strategy, simulated annealing and MinSD) were compared to define a mandarin (Citrus reticulata) CC. One hundred and sixty‐seven accessions were sampled from two germplasm collections, which were genotyped with 50 SSR, 24 InDel and 68 single nucleotide polymorphism markers. All the CC obtained were tested for the maintenance of the genetic variability parameters (Ho and He) of the initial collection, the level of linkage disequilibrium (LD) and the phenotypic diversity retention. The Max length subtree function from DARWin seemed to be the most appropriate method for establishing a CC in C. reticulata. It maintained 96.82% of the allelic richness and 17.96% of the size of the initial collection with only 30 accessions. Besides it did not increase the LD (r² value) of the initial collection and retained the vast majority of the phenotypic variability. However, a CC with 70 accessions would be more helpful for genetic association studies.     

Assessing genetic diversity and structure of fragmented populations of eastern white pine (Pinus strobus) and western white pine (P. monticola) for conservation management

Aims Many pine populations in Canada have fragmented distributions resulting from the effects of glaciations, overharvesting and white pine blister rust infections. Forest fragmentation can modify gene flow and reduce genetic diversity. Selective logging can reduce the density of trees, thereby altering mating patterns and increasing inbreeding. The hypothesis of the present study is that forest fragmentation will not increase inbreeding and will have no effect on genetic diversity parameters in the Canadian Pinus moniticola and P. strobus populations targeted because of (i) the long life span of the pine species, (ii) outbreeding and self-incompatibility of P. monticola and P. strobus and (iii) wind pollination resulting in high gene flow among populations. We studied the genetic diversity of P. strobus across its range in Canada, and we completed a detailed analysis of the genetic structure of P. monticola populations from western Canada using microsatellites genetic markers.Methods Seed samples from 10 P. monticola populations and 10 P. strobus populations were collected from western and eastern Canada, respectively. The mother trees included in seed lots were representative of each stand. Genomic DNA extracted from each sample was amplified with microsatellite primers. The intra- and interpopulation genetic diversity parameters were assessed using Popgene and Genepop softwares and the genetic distances among populations within each species using the PowerMarker software.Important findings Pinus monticola and P. strobus exhibited moderate to high genetic diversity. Also, both species showed low levels of inbreeding despite the geographic isolation and small stand size. Gene flow estimates were high and population differentiation values were relatively low for these fragmented forest sites.     

GenABEL: an R library for genome-wide association analysis

Here we describe an R library for genome-wide association (GWA) analysis. It implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures implemented in base R and special R libraries for genetic analysis. We evaluated GenABEL using one simulated and two real data sets. We conclude that GenABEL enables the analysis of GWA data on desktop computers. Availability: http://cran.r-project.org.     

Weighted gene coexpression network analysis strategies applied to mouse weight

Systems-oriented genetic approaches that incorporate gene expression and genotype data are valuable in the quest for genetic regulatory loci underlying complex traits. Gene coexpression network analysis lends itself to identification of entire groups of differentially regulated genes—a highly relevant endeavor in finding the underpinnings of complex traits that are, by definition, polygenic in nature. Here we describe one such approach based on liver gene expression and genotype data from an F₂ mouse intercross utilizing weighted gene coexpression network analysis (WGCNA) of gene expression data to identify physiologically relevant modules. We describe two strategies: single-network analysis and differential network analysis. Single-network analysis reveals the presence of a physiologically interesting module that can be found in two distinct mouse crosses. Module quantitative trait loci (mQTLs) that perturb this module were discovered. In addition, we report a list of genetic drivers for this module. Differential network analysis reveals differences in connectivity and module structure between two networks based on the liver expression data of lean and obese mice. Functional annotation of these genes suggests a biological pathway involving epidermal growth factor (EGF). Our results demonstrate the utility of WGCNA in identifying genetic drivers and in finding genetic pathways represented by gene modules. These examples provide evidence that integration of network properties may well help chart the path across the gene–trait chasm. Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users. Tova F. Fuller, Anatole Ghazalpour contributed equally to this work.     

Fischer Rats Consume 20% Ethanol in a Long-Term Intermittent-Access Two-Bottle-Choice Paradigm

The 20% ethanol intermittent-access (IAE) two-bottle-choice drinking procedure has been shown to produce high voluntary ethanol consumption in a number of rat strains. For this study, we applied this procedure to male Fischer (F344) rats, a strain previously reported to exhibit low levels of ethanol consumption. We also subjected these animals to a two-week ethanol-deprivation-period to see if they would exhibit an alcohol deprivation effect (ADE) signified by a transient increase in alcohol consumption following deprivation. Our data show a separation between high and low consuming animals within this strain, with high-consumers exhibiting an escalation in consumption. In contrast, Fischer rats did not show a significant separation between high and low consumers or any significant escalation in consumption, using the 20% ethanol continuous-access two-bottle-choice drinking protocol. Following the two-week deprivation period, animals in the high (but not the low) IAE group exhibited the transient increase in ethanol consumption and preference typically associated with an ADE. Together, the data suggest that the intermittent access protocol is a useful protocol for increasing ethanol consumption.     

SSR markers reveal the population structure of Sri Lankan yellow dwarf coconuts (<Emphasis Type="Italic">Cocos nucifera</Emphasis> L.)

World coconut germplasm has been classified broadly as tall and dwarf coconuts based on palm stature. Dwarf coconuts are predominantly self-breeding purelines hypothesised to have derived from tall coconuts. Dwarfs are categorized as yellow, green, red and brown on the colour of epicarp and are important as parents in hybridization of coconuts for desirable traits. Sri Lankan yellow dwarfs (SLYD) were observed to have uncommon phenotypes which were not previously reported for dwarf coconuts in the world, and this study was conducted to elucidate the population structure of SLYD. One hundred and two randomly selected SLYD individuals were categorized into three morphological groups and their genotypes were derived at 30 SSR loci. Genotypic data were analysed in PowerMarker 3.2.5 and Structure 2.3.4 software to derive the genetic diversity and the population structure. Unexpectedly high numbrs of alleles, genotypes, gene diversity and heterozygosity values were recorded for SLYD. Four populations were identified within SLYD under admixture model and their morphological variations were determined. Cross pollination between the dwarf and tall coconut varieties followed by the fixing of alleles by subsequent self-pollination was hypothesised to be the cause for the emergence of new genetic groups within dwarf populations. The study demonstrated the formation of new genotypes upon limited cross pollination of even naturally self-pollinating tree crops. The information will be useful for developing strategies for germplasm conservation, practical coconut breeding and determining the domestication and evolution of dwarf coconuts.     

Iberis amara Extract Induces Intracellular Formation of Reactive Oxygen Species and Inhibits Colon Cancer

Massively increasing global incidences of colorectal cancer require efficient treatment and prevention strategies. Here, we report unexpected anticancerogenic effects of hydroethanolic Iberis amara extract (IAE), which is known as a widely used phytomedical product for treating gastrointestinal complaints. IAE significantly inhibited the proliferation of HT-29 and T84 colon carcinoma cells with an inhibitory concentration (IC₅₀) of 6 and 9 μg/ml, respectively, and further generated inhibitory effects in PC-3 prostate and MCF7 breast cancer cells. Inhibition of proliferation in HT-29 cells was associated with a G2/M phase cell cycle arrest including reduced expression of various regulatory marker proteins. Notably, in HT-29 cells IAE further induced apoptosis by intracellular formation of reactive oxygen species (ROS). Consistent with predictions derived from our in vitro experiments, bidaily oral gavage of 50 mg/kg of IAE over 4 weeks resulted in significant inhibition of tumor growth in a mouse HT-29 tumor xenograft model. Taken together, Iberis amara extracts could become useful alternatives for preventing and treating the progression of colon cancer.     

Two statistical tests for meiotic breakpoint analysis.

Meiotic breakpoint analysis (BPA), a statistical method for ordering genetic markers, is increasing in importance as a method for building genetic maps of human chromosomes. Although BPA does not provide estimates of genetic distances between markers, it efficiently locates new markers on already defined dense maps, when likelihood analysis becomes cumbersome or the sample size is small. However, until now no assessments of statistical significance have been available for evaluating the possibility that the results of a BPA were produced by chance. In this paper, we propose two statistical tests to determine whether the size of a sample and its genetic information content are sufficient to distinguish between "no linkage" and "linkage" of a marker mapped by BPA to a certain region. Both tests are exact and should be conducted after a BPA has assigned the marker to an interval on the map. Applications of the new tests are demonstrated by three examples: (1) a synthetic data set, (2) a data set of five markers on human chromosome 8p, and (3) a data set of four markers on human chromosome 17q.     

Temporal and genomic analysis of additive genetic variance in breeding programmes

Genetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is therefore of high interest. Here, we extend a previously proposed framework for temporal analysis of genetic variance using the pedigree-based model, to a new framework for temporal and genomic analysis of genetic variance using marker-based models. To this end, we describe the theory of partitioning genetic variance into genic variance and within-chromosome and between-chromosome linkage-disequilibrium, and how to estimate these variance components from a marker-based model fitted to observed phenotype and marker data. The new framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values and (iii) calculating the variance of sampled genetic values by time and genome partitions. Analysing time partitions indicates breeding programme sustainability, while analysing genome partitions indicates contributions from chromosomes and chromosome pairs and linkage-disequilibrium. We demonstrate the framework with a simulated breeding programme involving a complex trait. Results show good concordance between simulated and estimated variances, provided that the fitted model is capturing genetic complexity of a trait. We observe a reduction of genetic variance due to selection and drift changing allele frequencies, and due to selection inducing negative linkage-disequilibrium.Subject terms: Genetic variation, Quantitative trait, Agricultural genetics, Plant breeding, Agriculture     

GeneticStudio: a suite of programs for spatial analysis of genetic-marker data

The analysis of genetic marker data is increasingly being conducted in the context of the spatial arrangement of strata (e.g. populations) necessitating a more flexible set of analysis tools. GeneticStudio consists of four interacting programs: (i) Geno a spreadsheet-like interface for the analysis of spatially explicit marker-based genetic variation; (ii) Graph software for the analysis of Population Graph and network topologies, (iii) Manteller, a general purpose for matrix analysis program; and (iv) SNPFinder, a program for identifying single nucleotide polymorphisms. The GeneticStudio suite is available as source code as well as binaries for OSX and Windows and is distributed under the GNU General Public License.     

Path analysis in genetic epidemiology: a critique

Path analysis, a form of general linear structural equation models, is used in studies of human genetics data to discern genetic, environmental, and cultural factors contributing to familial resemblance. It postulates a set of linear and additive parametric relationships between phenotypes and genetic and cultural variables and then essentially uses the assumption of multivariate normality to estimate and perform tests of hypothesis on parameters. Such an approach has been advocated for the analysis of genetic epidemiological data by D. C. Rao, N. Morton, C. R. Cloninger, L. J. Eaves, and W. E. Nance, among others. This paper reviews and evaluates the formulations, assumptions, methodological procedures, interpretations, and applications of path analysis. To give perspective, we begin with a discussion of path analysis as it occurs in the form of general linear causal models in several disciplines of the social sciences. Several specific path analysis models applied to lipoprotein concentrations, IQ, and twin data are then reviewed to keep the presentation self-contained. The bulk of the critical discussion that follows is directed toward the following four facets of path analysis: (1) coherence of model specification and applicability to data; (2) plausibility of modeling assumptions; (3) interpretability and utility of the model; and (4) validity of statistical and computational procedures. In the concluding section, a brief discussion of the problem of appropriate model selection is presented, followed by a number of suggestions of essentially model-free alternative methods of use in the treatment of complex structured data such as occurs in genetic epidemiology.     

土生空团菌的遗传多样性分析

为了研究土生空团菌的遗传多样性,对来自中国、美国、瑞士和法国等菌株的rDNA ITS区进行序列分析,利用Popgene32和phylip软件进行数据计算和聚类分析。序列分析表明土生空团菌rDNA ITS区的序列长度为422–447bp,遗传距离在0.000–0.051之间。居群结构和聚类分析结果表明:(1)土生空团菌有一定的遗传多样性,且遗传差异主要来自于居群内;(2)基因流Nm>1,遗传漂变不是导致土生空团菌居群遗传分化的主要因素;(3)土生空团菌的遗传分化受到地理环境的影响,而与宿主来源没有明显相关性。     

GeneMerge--post-genomic analysis,data mining,and hypothesis testing

SUMMARY: GeneMerge is a web-based and standalone program written in PERL that returns a range of functional and genomic data for a given set of study genes and provides statistical rank scores for over-representation of particular functions or categories in the data set. Functional or categorical data of all kinds can be analyzed with GeneMerge, facilitating regulatory and metabolic pathway analysis, tests of population genetic hypotheses, cross-experiment comparisons, and tests of chromosomal clustering, among others. GeneMerge can perform analyses on a wide variety of genomic data quickly and easily and facilitates both data mining and hypothesis testing. AVAILABILITY: GeneMerge is available free of charge for academic use over the web and for download from: http://www.oeb.harvard.edu/hartl/lab/publications/GeneMerge.html.     

GGT 2.0: versatile software for visualization and analysis of genetic data

Ever since its first release in 1999, the free software package for visualization of molecular marker data, graphical genotype (GGT), has been constantly adapted and improved. The GGT package was developed in a plant-breeding context and thus focuses on plant genetic data but was not intended to be limited to plants only. The current version has many options for genetic analysis of populations including diversity analyses and simple association studies. A second release of the GGT package, GGT 2.0 (available through http://www.plantbreeding.wur.nl), is therefore presented in this paper. An overview of existing and new features that are available within GGT 2.0, and a case study in which GGT 2.0 is applied to analyze an existing set of plant genetic data, are presented and discussed.     

Automating data manipulation for genetic analysis using a data base management system

Inefficient coding and manipulation of pedigree data have often hindered the progress of genetic studies. In this paper we present the methodology for interfacing a data base management system (DBMS) called MEGADATS with a linkage analysis program called LIPED. Two families that segregate a dominant trait and one test marker were used in a simulated exercise to demonstrate how a DBMS can be used to automate tedious clerical steps and improve the efficiency of a genetic analysis. The merits of this approach to data management are discussed. We conclude that a standardized format for genetic analysis programs would greatly facilitate data analysis.     

群体遗传学研究中的数据处理方法I．RAPD数据的AMOVA分析

近年来,RAPD数据和AMOVA分析广泛地应用于群体遗传学和保护遗传学研究。然而,由于RAPD标记具显性特点。加上目前进行AMOVA分析所依赖的RAPDistance软件不完善,使得对RAPD数据进行AMOVA分析时存在许多不足。本文介绍了AMOVA分析的基本过程,同时引入一个新的程序DCFA用以替代RADistance并详述了将DCFA与WINAMOVA联用,对RAPD数据进行AMOVA分析的具体步骤与注意事项,最后,以产自中国和巴西8个普通野生稻（Oryza furipogon)天然群体为例,演示了对RAPD表型数据进行AMOVA分析的过程,讨论了AMOVA分析结果在群体遗传结构上的意义。通过对AMOVA算法的分析,同时比较4种距离系数所得AMOVA结果,我们认为在进行AMOVA分析时选择NEI－LI距离和欧氏距离平方较为合适,而目前国内使用较多的JACCARD系数不适合AMOVA分析。     

The effects of encoding data in diversity studies and the applicability of the weighting index approach for data analysis from different molecular markers

The use of molecular markers to study genetic diversity represents a breakthrough in this area, because of the increase in polymorphism levels and phenotypic neutrality. Codominant markers, such as microsatellites (SSR), are sensitive enough to distinguish the heterozygotes in genetic studies. Despite this advantage, there are some studies that ignore this feature and work with encoded data because of the simplicity of the evaluation, existence of polyploids and need for the combined analysis of different types of molecular markers. Thus, our study aims to investigate the consequences of these encodings on simulated and real data. In addition, we suggest an alternative analysis for genetic evaluations using different molecular markers. For the simulated data, we proposed the following two scenarios: the first uses SNP markers, and the second SSR markers. For real data, we used the SSR genotyping data from Coffea canephora accessions maintained in the Embrapa Germplasm Collection. The genetic diversity was studied using cluster analysis, the dissimilarity index, and the Bayesian approach implemented in the STRUCTURE software. For the simulated data, we observed a loss of genetic information to the encoded data in both scenarios. The same result was observed in the coffee studies. This loss of information was discussed in the context of a plant-breeding program, and the consequences were weighted to germplasm evaluations and the selection of parents for hybridization. In the studies that involved different types of markers, an alternative to the combined analysis is discussed, where the informativeness, coverage and quality of markers are weighted in the genetic diversity studies.     

Large-scale analysis of microRNA evolution

ABSTRACT: BACKGROUND: In animals, microRNAs (miRNA) are important genetic regulators. Animal miRNAs appear to have expanded in conjunction with an escalation in complexity during early bilaterian evolution. Their small size and high-degree of similarity makes them challenging for phylogenetic approaches. Furthermore, genomic locations encoding miRNAs are not clearly defined in many species. A number of studies have looked at the evolution of individual miRNA families. However, we currently lack resources for large-scale analysis of miRNA evolution. RESULTS: We addressed some of these issues in order to analyse the evolution of miRNAs. We perform syntenic and phylogenetic analysis for miRNAs from 80 animal species. We present synteny maps, phylogenies and functional data for miRNAs across these species. These data represent the basis of our analyses and also act as a resource for the community. CONCLUSIONS: We use these data to explore the distribution of miRNAs across phylogenetic space, characterise their birth and death, and examine functional relationships between miRNAs and other genes. These data confirm a number of previously reported findings on a larger scale and also offer novel insights into the evolution of the miRNA repertoire in animals, and it's genomic organization.