Genetic influence on the variance in P3 amplitude and latency

The P3(00) event-related potential (ERP) component is widely used as a measure of cognitive functioning and provides a sensitive electrophysiological index of the attentional and working memory demands of a task. This study investigated what proportion of the variance in the amplitude and latency of the P3, elicited in a delayed response working memory task, could be attributed to genetic factors. In 335 adolescent twin pairs and 48 siblings, the amplitude and latency of the P3 were examined at frontal, central, and parietal sites. Additive genetic factors accounted for 48% to 61% of the variance in P3 amplitude. Approximately one-third of the genetic variation at frontal sites was mediated by a common genetic factor that also influenced the genetic variation at parietal and central sites. Familial resemblance in P3 latency was due to genetic influence that accounted for 44% to 50% of the variance. Genetic covariance in P3 latency across sites was substantial, with a large part of the variance found at parietal, central, and frontal sites attributed to a common genetic factor. The findings provide further evidence that the P3 is a promising phenotype of neural activity of the brain and has the potential to be used in linkage and association analysis in the search for quantitative trait loci (QTLs) influencing cognition.

Genetic covariance among measures of information processing speed, working memory, and IQ

The genetic relationship between lower (information processing speed), intermediate (working memory), and higher levels (complex cognitive processes as indexed by IQ) of mental ability was studied in a classical twin design comprising 166 monozygotic and 190 dizygotic twin pairs. Processing speed was measured by a choice reaction time (RT) task (2-, 4-, and 8-choice), working memory by a visual-spatial delayed response task, and IQ by the Multidimensional Aptitude Battery. Multivariate analysis, adjusted for test-retest reliability, showed the presence of a genetic factor influencing all variables and a genetic factor influencing 4- and 8-choice RTs, working memory, and IQ. There were also genetic factors specific to 8-choice RT, working memory, and IQ. The results confirmed a strong relationship between choice RT and IQ (phenotypic correlations: -0.31 to -0.53 in females, -0.32 to -0.56 in males; genotypic correlations: -0.45 to -0.70) and a weaker but significant association between working memory and IQ (phenotypic: 0.26 in females, 0.13 in males; genotypic: 0.34). A significant part of the genetic variance (43%) in IQ was not related to either choice RT or delayed response performance, and may represent higher order cognitive processes.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

Identification of causal relationships among traits related to drought resistance in Stylosanthes scabra using QTL analysis

Previous studies have shown that a negative relationship exists between transpiration efficiency (TE) and carbon isotope discrimination (Delta) and between TE and specific leaf area (SLA) in Stylosanthes scabra, A glasshouse experiment was conducted to confirm these relationships in an F-2 population and to study the causal nature of these relationships through quantitative trait loci (QTL) analysis, One hundred and twenty F-2 genotypes from a cross between two genotypes within S. scabra were used. Three replications for each genotype were maintained through vegetative propagation, Water stress was imposed by maintaining plants at 40% of field capacity for about 45 d. To facilitate QTL analysis, a genetic linkage map consisting of 151 RAPD markers was developed, Results from this study show that Delta was significantly and negatively correlated with TE and biomass production. Similarly, SLA showed significant negative correlation with TE and biomass production, Most of the QTL for TE and Delta were present on linkage groups 5 and 11. Similarly, QTL for SLA, transpiration and biomass productivity traits were clustered on linkage groups 13 and 24, One unlinked marker was also associated with these traits, There were several markers coincident between different traits, At all the coincident QTL, the direction of QTL effects was consistent with phenotypic data, At the coincident markers between TE and Delta, high alleles of TE were associated with low alleles of Delta. Similarly, low alleles of SLA were associated with high alleles of biomass productivity traits and transpiration. At the coincident markers between trans-4-hydroxy-N-methyl proline (MHP) and relative water content (RWC), low alleles of MHP were associated with high alleles of RWC, This study suggests the causal nature of the relationship between TE and Delta. Phenotypic data and QTL, data show that SLA was more closely associated with biomass production than with TE, This study also shows that a cause-effect relationship may exist between SLA and biomass production.

Genetic variability of the symbiotic dinoflagellates from the wide ranging coral species Seriatopora hystrix and Acropora longicyathus in the Indo-West Pacific

The scleractinian coral species, Seriatopora hystrix and Acropora longicyathus, are widely distributed throughout the latitudinal range of the tropical west Pacific. These 2 coral species live in a mutually beneficial relation with symbiotic dinoflagellates (zooxanthellae), which are passed to their progeny by vertical transmission (zooxanthellate eggs or larvae) and horizontal transmission (eggs or larvae that acquire symbionts from the environment), respectively. For S. hystrix, vertical transmission might create biogeographically isolated and genetically differentiated symbiont populations because the extent of its larval migration is known to be limited. On the other hand, horizontal transmission in corals such as A. longicyathus may result in genetically connected symbiont populations, especially if its zooxanthellae taxa are widely distributed. To examine these hypotheses, symbionts were collected from colonies of S. hystrix and A. longicyathus living in the Great Barrier Reef (Australia), South China Sea (Malaysia) and East China Sea (Ryukyus Archipelago, Japan), and were examined using restriction fragment length polymorphism and sequence analysis of large and small subunit rRNA genes. Phylogenetic analysis assigned the symbionts to 1 of 3 taxonomically distinct groups, known as clades. Symbionts from Australian and Japanese S. hystrix were placed in Clade C, and Malaysian S. hystrix symbionts in the newly described Clade D. Seven of 11 Australian and all Japanese and Malaysian colonies of A. longicyathus had symbiotic dinoflagellates that also grouped with Clade C, but symbionts from the remaining Australian colonies of A. longicyathus grouped with Clade A. Analysis of molecular variance of Clade C symbionts found significant genetic variation in 1 or more geographic groups (69.8%) and to a lesser extent among populations within geographic regions (13.6%). All populations of Clade C symbionts from S. hystrix were genetically differentiated according to geographic region. Although Clade C symbionts of A. longicyathus from Japan resolved into a distinct geographic group, those from Australia and Malaysia did not and were genetically connected. We propose that these patterns of genetic connectivity correlate with differences in the dispersal range of the coral or symbiont propagules and are associated with their respective modes of symbiont transmission.

Genetic organization of Pasteurella multocida cap Loci and development of a multiplex capsular PCR typing system

Current serotyping methods classify Pasteurella multocida into five capsular serogroups (serogroups A, B, D, E, and F) and 16 somatic serotypes (serotypes 1 to 16). In the present study, we have developed a multiplex PCR assay as a rapid alternative to the conventional capsular serotyping system. The serogroup-specific primers used in this assay were designed following identification, sequence determination, and analysis of the capsular biosynthetic loci of each capsular serogroup. The entire capsular biosynthetic loci of P. multocida A:1 (X-73) and B:2 (M1404) have been cloned and sequenced previously (J. Y. Chung, Y. M. Zhang, and B. Adler, FEMS Microbiol. Lett. 166:289-296, 1998; J. D. Boyce, J. Y. Chung, and B. Adler, Vet. Microbiol. 72:121-134, 2000). Nucleotide sequence analysis of the biosynthetic region (region 2) from each of the remaining three serogroups, serogroups D, E, and F, identified serogroup-specific regions and gave an indication of the capsular polysaccharide composition. The multiplex capsular PCR assay was highly specific, and its results, with the exception of those for some serogroup F strains, correlated well with conventional serotyping results. Sequence analysis of the strains that gave conflicting results confirmed the validity of the multiplex PCR and indicated that these strains were in fact capsular serogroup A. The multiplex PCR will clarify the distinction between closely related serogroups A and F and constitutes a rapid assay for the definitive classification of P. multocida capsular types

Genetic Covariation between Serum {gamma}-Glutamyltransferase Activity and Cardiovascular Risk Factors

Background: Several studies have shown that variation in serum gamma-glutamyltransferase (GGT) in the population is associated with risk of death or development of cardiovascular disease, type 2 diabetes, stroke, or hypertension. This association is only partly explained by associations between GGT and recognized risk factors. Our aim was to estimate the relative importance of genetic and environmental sources of variation in GGT as well as genetic and environmental sources of covariation between GGT and other liver enzymes and markers of cardiovascular risk in adult twin pairs. Methods: We recruited 1134 men and 2241 women through the Australian Twin Registry. Data were collected through mailed questionnaires, telephone interviews, and by analysis of blood samples. Sources of variation in GGT, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) and of covariation between GGT and cardiovascular risk factors were assessed by maximum-likelihood model-fitting. Results: Serum GGT, ALT, and AST were affected by additive genetic and nonshared environmental factors, with heritabilities estimated at 0.52, 0.48, and 0.32, respectively. One-half of the genetic variance in GGT was shared with ALT, AST, or both. There were highly significant correlations between GGT and body mass index; serum lipids, lipoproteins, glucose, and insulin; and blood pressure. These correlations were more attributable to genes that affect both GGT and known cardiovascular risk factors than to environmental factors. Conclusions: Variation in serum enzymes that reflect liver function showed significant genetic effects, and there was evidence that both genetic and environmental factors that affect these enzymes can also affect cardiovascular risk. (C) 2002 American Association for Clinical Chemistry.

Identity and genetic diversity of the sorghum ergot pathogen in Australia

Sorghum ergot was first discovered in Australia in 1996. It affects seed production and grain usage in stock feed due to concerns of animal toxicity. Three species of Claviceps are known to cause ergot of sorghum with different epidemiological, animal toxicity, and management implications. Claviceps africana was identified as the causal agent but morphological differences between isolates raised the possibility of more than one species being involved. The major aim of this study was to identify the Claviceps species causing sorghum ergot and to determine the genetic diversity among isolates of the ergot pathogen from Australia and overseas. Symptom development, sequencing of the ITS1 region, and radiolabelled DNA amplification fingerprints (RAF) were used to confirm that ergot of sorghum in Australia is caused by C. africana. The morphology of sphacelia, microconidia, macroconidia, and secondary conidia of all 36 Australian isolates studied matched the description for C. africana and the DNA sequence of the ITS1 region of 2 selected Australian isolates was identical to that of C. africana. Based on RAF analysis of 110 Australian and overseas isolates of Claviceps spp., C. africana isolates could be clearly distinguished (

Genetic differentiation between Australian and North American populations of the monarch butterfly Danaus plexippus (L.) (Lepidoptera : Nymphalidae): an exploration using allozyme electrophoresis

Allozyme analysis was used to address the question of the source of the Australian populations of the monarch butterfly Danaus plexippus (L.). The study had three major aims: (1) To compare the levels of diversity of Australian and Hawaiian populations with potential source populations. (2) To determine whether eastern and western North American populations were sufficiently divergent for the Australian populations to be aligned to a source population. (3) To compare the differentiation among regions in Australia and North America to test the prediction of greater genetic structure in Australia, as a consequence of reduced migratory behaviour. The reverse was found, with F-ST values an order of magnitude lower in Australia than in North America. Predictably, Australian and Hawaiian populations had lower allelic diversity, but unexpected higher heterozygosity values than North American populations. It was not possible to assign the Australian populations to a definitive source, although the high levels of similarity of Australian populations to each other suggest a single colonization event. The possibility that the Australian populations have not been here long enough to reach equilibrium is discussed. (C) 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437-452.

Application of spatial analysis techniques to adjust for fertility trends and identify interplot competition in early stage sugarcane selection trials

Most sugarcane breeding programs in Australia use large unreplicated trials to evaluate clones in the early stages of selection. Commercial varieties that are replicated provide a method of local control of soil fertility. Although such methods may be useful in detecting broad trends in the field, variation often occurs on a much smaller scale. Methods such as spatial analysis adjust a plot for variability by using information from immediate neighbours. These techniques are routinely used to analyse cereal data in Australia and have resulted in increased accuracy and precision in the estimates of variety effects. In this paper, spatial analyses in which the variability is decomposed into local, natural, and extraneous components are applied to early selection trials in sugarcane. Interplot competition in cane yield and trend in sugar content were substantial in many of the trials and there were often large differences in the selections between the spatial and current method used by the Bureau of Sugar Experiment Stations. A joint modelling approach for tonnes sugar per hectare in response to fertility trends and interplot competition is recommended.

Genetic variability in cultivated common bean beyond the two major gene pools

It is generally accepted that two major gene pools exist in cultivated common bean (Phaseolus vulgaris L.), a Middle American and an Andean one. Some evidence, based on unique phaseolin morphotypes and AFLP analysis, suggests that at least one more gene pool exists in cultivated common bean. To investigate this hypothesis, 1072 accessions from a common bean core collection from the primary centres of origin, held at CIAT, were investigated. Various agronomic and morphological attributes (14 categorical and 11 quantitative) were measured. Multivariate analyses, consisting of homogeneity analysis and clustering for categorical data, clustering and ordination techniques for quantitative data and nonlinear principal component analysis for mixed data, were undertaken. The results of most analyses supported the existence of the two major gene pools. However, the analysis of categorical data of protein types showed an additional minor gene pool. The minor gene pool is designated North Andean and includes phaseolin types CH, S and T; lectin types 312, Pr, B and K; and mostly A5, A6 and A4 types alpha-amylase inhibitor. Analysis of the combined categorical data of protein types and some plant categorical data also suggested that some other germplasm with C type phaseolin are distinguished from the major gene pools.

Future contributions of crop modelling - from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement

Crop modelling has evolved over the last 30 or so years in concert with advances in crop physiology, crop ecology and computing technology. Having reached a respectable degree of acceptance, it is appropriate to review briefly the course of developments in crop modelling and to project what might be major contributions of crop modelling in the future. Two major opportunities are envisioned for increased modelling activity in the future. One opportunity is in a continuing central, heuristic role to support scientific investigation, to facilitate decision making by crop managers, and to aid in education. Heuristic activities will also extend to the broader system-level issues of environmental and ecological aspects of crop production. The second opportunity is projected as a prime contributor in understanding and advancing the genetic regulation of plant performance and plant improvement. Physiological dissection and modelling of traits provides an avenue by which crop modelling could contribute to enhancing integration of molecular genetic technologies in crop improvement. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Revisiting the question of limited genetic variation within Schistosoma japonicum

Recent electrophoretic data have indicated that Schistosoma japonicum in mainland China may be a species complex, with the existence of a cryptic species being predicted from the analysis of schistosome populations from Sichuan province. To investigate the Sichuan form of S. japonicum, 4.9 kbp of mitochondrial DNA from each of three samples of the parasite from China (two from Sichuan and one from Hunan) and one from Sorsogon in the Philippines were amplified, sequenced and characterized. The sequence data were compared with those from the related South-east Asian species of S. mekongi (Khong Island, Laos) and S. malayensis (Baling, Malaysia) and that from S. japonicum from Anhui (China). At both the nucleotide and amino-acid levels, the variation among the five S. japonicum samples was limited ( < 1%). This was consistent with the conclusions drawn from previous molecular studies, in which minimal variation among S. japonicum populations was also detected. In contrast, S. mekongi and S. malayensis, species recognized as separate but closely related, differ from each other by about 10%, and each differs by 25%-26% from S. japonicum. Phylogenetic trees provided a graphic representation of these differences, showing all S. japonicum sequences to be very tightly clustered and distant from S. mekongi and S. malayensis, the last two being clearly distinct from each other. The results thus indicate no significant intraspecific genetic variation among S. japonicum samples collected from different geographical areas and do not support the idea of a distinct form in Sichuan.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.