Keur

Biometrical Modeling In Mapping Quantitative Trait Genes By Using Genetic Markers

Mon, 01 Jan 1996 00:00:00 CET

No description abstract

QTL Analysis of seed dormancy in Arabidopsis using recombinant inbred lines and MQM mapping

Wed, 01 Jan 1997 00:00:00 CET

The genetic differences for seed germination between two commonly used Arabidopsis thaliana ecotypes Ler and Col, both showing a low level of seed dormancy, were investigated. The analysis was performed with 98 recombinant inbred lines (RILs) derived from the cross between the two ecotypes, and these lines had previously been analysed for molecular marker composition. The analysis of germination was performed on seeds grown in three different maternal environments and each seed batch was tested in three different germination environments: in light, in darkness and in the presence of the gibberellin inhibitor paclobutrazol. Fourteen loci were identified using the multiple-QTL-model (MQM) procedure for mapping quantitative trait loci. At nine loci no significant interaction between the detection of the locus and environmental factors could be detected. However, three other distinct loci controlling the germination behaviour in the presence of the gibberellin inhibitor paclobutrazol had a much lower or no effect when germination was tested in water either in light or darkness. Two other loci affecting germination in darkness and/or light had practically no effect on germination in the presence of paclobutrazol.

Dissection of a Synthesized Quantitative Trait to Characterize Transgene Interactions

Wed, 01 Jan 1997 00:00:00 CET

Six transgenic tobacco lines, each homozygous for the β-glucuronidase (GUS) gene at a different locus, and wild type were selfed and intercrossed to evaluate GUS activity in all possible hemizygous, homozygous and dihybrid combinations of GUS alleles. The transgenic lines are characterized by their GUS activity (two low, three intermediate, one high), T-DNA complexity (four single-copy, two more complex single-locus) and the presence of the chicken lysozyme matrix-associated region (MAR) around the full T-DNA (two lines). Gene action and interaction was analyzed by weighted linear regression with parameters for additivity, dominance and epistasis. The analysis showed that each of the four single-copy lines acted fully additively. In contrast, the two complex single-locus lines showed classical singlelocus overdominance and were epistatic dominant over all other GUS alleles. The latter is manifested in severe suppression of GUS activity in dihybrid lines, irrespective of the presence of MAR elements around the GUS gene. Such elements apparently do not protect against epistatic dominance. The quantitative data suggested that the epistatic dominance and overdominance are based on the same molecular mechanism. Our approach of a genetic analysis of quantitative variation in well-characterized transgenic lines provides a powerful tool to gain insight into complex plant traits.

Freezing Tolerance of Bulb Scales of Lily Cultivars: Effects of Freezing and Storage Duration and Partial Dehydration

Wed, 01 Jan 1997 00:00:00 CET

Effects of freezing duration, previous storage duration of bulbs at -2 °C, and partial dehydration of scales on freezing tolerance of lily (Lilium hybrids) scales were studied for a series of cultivars. Freezing tolerance of scales was estimated by measuring ion leakage and recording scale bulblet regeneration. Both methods gave similar results. Freezing tolerance decreased with freezing duration. A longer previous storage duration of the bulbs at -2 °C tended to reduce freezing tolerance of the scales. Dehydration of the scales to 10-20 % loss of water content significantly increased freezing tolerance. Further dehydration to 30-40 % loss of water content did not further increase freezing tolerance. Nucleation temperatures, temperatures during crystallisation and melting temperatures of the scales were recorded for the cultivar . Nucleation occurred at higher temperatures after a longer previous storage duration of bulbs, indicating a reduced capacity to remain supercooled. The increased freezing tolerance of dehydrated lily scales could partly be explained by a decreased melting temperature of the scales. We conclude long term storage of lily bulbs at -2 °C to be safer after partial dehydration to 10-20 % loss of the original water content.

Genetics of refractoriness to Plasmodium falciparum in the mosquito Anopheles stephensi

Thu, 01 Jan 1998 00:00:00 CET

We previously selected a line of the malaria vector mosquito Anopheles stephensi refractory (resistant) to the human malaria parasite Plasmodium falciparum, using in vitro infections with P. falciparum gametocytes. This report presents data on the genetic background of refractoriness to P. falciparum in our A. stephensi line is autosomal and semi-dominant to susceptibility. The expression of refractoriness is apparently affected by a cytoplasmic factor. Interpretation of data from the crosses by quantative trait locus analysis shows that one gene or two unlinked interacting autosomal genes, or groups of closely linked genes, are involved.

High Frequency of Interactions between Lung Cancer Susceptibility Genes in the Mouse: Mapping of Sluc5 to Sluc14

Thu, 01 Jan 1998 00:00:00 CET

Although several genes that cause monogenic familial cancer syndromes have been identified, susceptibility to sporadic cancer remains unresolved. Animal experiments have demonstrated multigenic control of tumor susceptibility. Recently, we described four mouse lung cancer susceptibility (Sluc) loci, the main effects of which are masked by their mutual interactions. Because such interactions can considerably affect the strategies for identification of cancer susceptibility genes in humans, it is necessary to establish whether they are common or rare. Here, we report the mapping of 10 additional Sluc loci and show that 13 of the 14 Sluc loci are involved in one or more interactions, demonstrating that interactions of tumor susceptibility genes are frequent and that they probably form complex networks.

A Mixture Model Approach to the Mapping of Quantitative Trait Loci in Complex Populations With an Apllication to Multiple Cattle Families

Thu, 01 Jan 1998 00:00:00 CET

A mixture model approach is presented for the mapping of one or more quantitative trait loci (QTLs) in complex populations. In order to exploit the full power of complete linkage maps the simultaneous likelihood of phenotype and a multilocus (all markers and putative QTLs) genotype is computed. Maximum likelihood estimation in our mixture models is implemented via an Expectation-Maximization algorithm: exact, stochastic or Monte Carlo EM by using a simple and flexible Gibbs sampler. Parameters include allele frequencies of markers and QTLs, discrete or normal effects of biallelic or multiallelic QTLs, and homogeneous or heterogeneous residual variances. As an illustration a dairy cattle data set consisting of twenty half-sib families has been reanalyzed. We discuss the potential which our and other approaches have for realistic multiple-QTL analyses in complex populations.

Mapping quantitative trait loci in a selectively genotyped outbred population using a mixture model approach

Fri, 01 Jan 1999 00:00:00 CET

A mixture model approach is employed for the mapping of quantitative trait loci (QTL) for the situation where individuals, in an outbred population, are selectively genotyped. Maximum likelihood estimation of model parameters is obtained from an Expectation-Maximization (EM) algorithm facilitated by Monte Carlo sampling using a Gibbs sampler. All individuals with phenotypes, whether genotyped or not, are included in the analysis where both putative QTLs and missing marker genotypes are sampled conditional on known marker information and phenotype. A simulation of a half-sib family structure demonstrates that this mixture model approach will yield unbiased estimates of the allelic effects of a QTL affecting the trait on which selective genotyping is based. Unbiased estimates were also obtained for the QTL effect on a correlated trait provided both traits were analysed jointly in a bivariate model. The procedure is also compared with a standard linear model approach. The application of these methods is demonstrated for bovine chromosome six, the data arising from two Holstein-Friesian families selectively genotyped for protein yield in a daughter design.

Mapping multiple QTL of different effects: comparision of a simple sequential testing strategy and multiple QTL mapping

Sat, 01 Jan 2000 00:00:00 CET

The aim of this study was to explore, by computer simulation, the mapping of QTLs in a realistic but complex situation of many (linked) QTLs with different effects, and to compare two QTL mapping methods. A novel method to dissect genetic variation on multiple chromosomes using molecular markers in backcross and F2 populations derived from inbred lines was suggested, and its properties tested using simulations. The rationale for this sequential testing method was to explicitly test for alternative genetic models. The method consists of a series of four basic statistical tests to decide whether variance was due to a single QTL, two QTLs, multiple QTLs, or polygenes, starting with a test to detect genetic variance associated with a particular chromosome. The method was able to distinguish between different QTL configurations, in that the probability to ‘detect’ the correct model was high, varying from 0.75 to 1. For example, for a backcross population of 200 and an overall heritability of 50%, in 78% of replicates a polygenic model was detected when that was the underlying true model. To test the method for multiple chromosomes, QTLs were simulated on 10 chromosomes, following a geometric series of allele effects, assuming positive alleles were in coupling in the founder lines For these simulations, the sequential testing method was compared to the established Multiple QTL Mapping (MQM) method. For a backcross population of 400 individuals, power to detect genetic variance was low with both methods when the heritability was 0.40. For example, the power to detect genetic variation on a chromosome on which 6 QTLs explained 12.6% of the genetic variance, was less than 60% for both methods. For a large heritability (0.90), the power of MQM to detect genetic variance and to dissect QTL configurations was generally better, due to the simultaneous fitting of markers on all chromosomes. It is concluded that when testing different QTL configurations on a single chromosome using the sequential testing procedure, regions of other chromosomes which explain a significant amount of variation should be fitted in the model of analysis. This study reinforces the need for large experiments in plants and other species if the aim of a genome scan is to dissect quantitative genetic variation.

Identification of the SAAT Gene Involved in Strawberry Flavor Biogenesis by Use of DNA Microarrays

Sat, 01 Jan 2000 00:00:00 CET

Fruit flavor is a result of a complex mixture of numerous compounds. The formation of these compounds is closely correlated with the metabolic changes occurring during fruit maturation. Here, we describe the use of DNA microarrays and appropriate statistical analyses to dissect a complex developmental process. In doing so, we have identified a novel strawberry alcohol acyltransferase (SAAT) gene that plays a crucial role in flavor biogenesis in ripening fruit. Volatile esters are quantitatively and qualitatively the most important compounds providing fruity odors. Biochemical evidence for involvement of the SAAT gene in formation of fruity esters is provided by characterizing the recombinant protein expressed in Escherichia coli. The SAAT enzyme showed maximum activity with aliphatic medium-chain alcohols, whose corresponding esters are major components of strawberry volatiles. The enzyme was capable of utilizing short- and medium-chain, branched, and aromatic acyl-CoA molecules as cosubstrates. The results suggest that the formation of volatile esters in fruit is subject to the availability of acyl-CoA molecules and alcohol substrates and is dictated by the temporal expression pattern of the SAAT gene(s) and substrate specificity of the SAAT enzyme(s).

Linkage And QTL Mapping In Related Full Sib Families- A Case Study

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

A Comment on Codominant Scoring of AFLP Markers

Mon, 01 Jan 2001 00:00:00 CET

No description abstract

Mapping Epistatic Quantitative Trait Loci With One-Dimensional Genome Searches

Mon, 01 Jan 2001 00:00:00 CET

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.

Genetical genomics: the added value from segregation

Mon, 01 Jan 2001 00:00:00 CET

The recent successes of genome-wide expression profiling in biology tend to overlook the power of genetics. We here propose a merger of genomics and genetics into ‘genetical genomics’. This involves expression profiling and marker-based fingerprinting of each individual of a segregating population, and exploits all the statistical tools used in the analysis of quantitative trait loci. Genetical genomics will combine the power of two different worlds in a way that is likely to become instrumental in the further unravelling of metabolic, regulatory and developmental pathways.

Using complex plant pedigrees to map valuable genes

Mon, 01 Jan 2001 00:00:00 CET

Statistical methods pioneered by human and animal geneticists use marker and pedigree information to detect quantitative trait loci within complex pedigrees. These methods, adapted to plants, promise to expand the range of data useful for identifying the genetic factors influencing plant growth, development and evolutionary responses, and to increase the relevance and cost effectiveness of quantitative trait loci mapping in applied contexts.

MapQTL 4.0: Software For The Calculation Of QTL Positions On Genetic Maps

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Statistical Analysis of 2n and 4n Pollen Formation in Lolium perenne Using Pollen Diameters

Tue, 01 Jan 1991 00:00:00 CET

No description abstract

Discussion on the meeting on 'Statistical modelling and analysis of genetic data'

Tue, 01 Jan 2002 00:00:00 CET

No description abstract

Mapping Quantitative Trait Loci in Plant Breeding Populations: Use of Parental Haplotype Sharing

Wed, 01 Jan 2003 00:00:00 CET

Applied breeding programs evaluate large numbers of progeny derived from multiple related crosses for a wide range of agronomic traits and for tens to hundreds of molecular markers. This study was conducted to determine how these phenotypic and genetic data could populabe used for routinely mapping quantitative trait loci (QTLs). With dense maps, haplotype sharing of parents in a certain region is a good indicator for QTL-allele sharing, albeit not 100% perfect. With this in mind, an approximate and simple method has been developed where ancestral genome blocks in the parents of the crosses can be identified via haplotype analysis and where the effect of a putative QTL is then modeled and estimated per ancestral genome block. A simulation of an early-generation maize breeding scheme demonlyzed strates the potential of the present approach for QTL detection in existing breeding programs. With this new QTL mapping strategy, the power, precision, and accuracy associated with large numbers of progeny may be attained, inferences about QTLs can be drawn across the breeding program rather than being limited to the sample of progeny from a single cross, and results may bemuch more valuable for marker-assisted breeding because the QTLs apply to agronomically challenging situations in the field.

Errors in genomics and proteomics

Tue, 01 Jan 2002 00:00:00 CET

No description abstract

Dissection Of Genetic Variance Via Bayesian Analysis - Application To Pig Selection Lines.

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

The Diallel Mating Design For Mapping Interacting QTLs

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Linkage And QTL Mapping In Related Full Sib Families - A Case Study

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Assembly of Two Transgenes in an Artificial Chromatin Domain Gives Highly Coordinated Expression in Tobacco

Tue, 01 Jan 2002 00:00:00 CET

The chromatin loop model predicts that genes within the same chromatin domain exhibit coordinated regulation. We here present the first direct experimental support for this model in plants. Two reporter genes, the E. coli β-glucuronidase gene and the firefly luciferase gene, driven by different promoters, were placed between copies of the chicken lysozyme A element, a member of the matrix-associated region (MAR) group of chromatin boundary elements, and introduced in tobacco (Nicotiana tabacum). In plants carrying A elements, quantitative enzyme activities and mRNA levels of both genes show high correlations compared to control plants. The A element thus creates an artificial chromatin domain that yields coordinated expression. Surprisingly, enzyme activities correlated poorly with their respective mRNA levels. We hypothesize that this indicates the occurrence of “error pipelines” in data generation: systematic errors of a given analytical method will point in the same direction and cancel out in correlation analysis, resulting in better correlations. In combining different methods of analysis, however, such errors do not cancel out and as a result relevant correlations can be masked. Such error pipelines will have to be taken into account when different types of (e.g., whole-genome) data sets are combined in quantitative analyses.

Bayesian versus frequentist analysis of multiple quantitative trait loci with an application to an outbred apple cross

Mon, 01 Jan 2001 00:00:00 CET

Two methods, following different statistical paradigms for mapping multiple quantitative trait loci (QTLs), were compared: the first is a frequentist, the second a Bayesian approach. Both methods were applied to previously published experimental data from an outbred progeny of a single cross between two apple cultivars (Malus pumila Mill.). These approaches were compared with respect to (1) the models used, (2) the number of putative QTLs, (3) their estimated map positions and accuracies thereof and (4) the choice of cofactor markers. In general, the strongest evidence for QTLs, provided by both methods, was for the same linkage groups and for similar map positions. However, some differences were found with respect to evidence for QTLs on other linkage groups. The effect of using cofactor markers which were selected differently was also somewhat different.

Multiple QTL mapping in related plant populations via a pedigree-analysis approach

Tue, 01 Jan 2002 00:00:00 CET

QTL mapping experiments in plant breeding may involve multiple populations or pedigrees that are related through their ancestors. These known relationships have often been ignored for the sake of statistical analysis, despite their potential increase in power of mapping. We describe here a Bayesian method for QTL mapping in complex plant populations and reported the results from its application to a (previously analysed) potato data set. This Bayesian method was originally developed for human genetics data, and we have proved that it is useful for complex plant populations as well, based on a sensitivity analysis that was performed here. The method accommodates robustness to complex structures in pedigree data, full flexibility in the estimation of the number of QTL across multiple chromosomes, thereby accounting for uncertainties in the transmission of QTL and marker alleles due to incomplete marker information, and the simultaneous inclusion of non-genetic factors affecting the quantitative trait.

A Penalized Likelihood Method for Mapping Epistatic Quantitative Trait Loci With One-Dimensional Genome Searches

Tue, 01 Jan 2002 00:00:00 CET

Epistasis is a common and important phenomenon, as indicated by results from a number of recent experiments. Unfortunately, the discovery of epistatic quantitative trait loci (QTL) is difficult since one must search for multiple QTL simultaneously in two or more dimensions. Such a multidimensional search necessitates many statistical tests, and a high statistical threshold must be adopted to avoid false positives. Furthermore, the large number of (interaction) parameters in comparison with the number of observations results in a serious danger of overfitting and overinterpretation of the data. In this article we present a new statistical framework for mapping epistasis in inbred line crosses. It is based on reducing the high dimensionality of the problem in two ways. First, epistatic QTL are mapped in a one-dimensional genome scan for high interactions between QTL and the genetic background. Second, the dimension of the search is bounded by penalized likelihood methods. We use simulated backcross data to illustrate the new approach.

Matching Computers With Genetics.

Thu, 01 Jan 1998 00:00:00 CET

No description abstract

MapQTL 4.0. Software for the calculation Of QTL positions on genetic maps

Tue, 01 Jan 2002 00:00:00 CET

No description abstract

Application Of Multiple QTL Mapping In Complex Plant Crosses To Partial Resistance To Late Blight (phytophthora Infestans) In Potato: Better Insight By Using A Design-independent Method

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Dissection Of Genetic Variance Via Bayesian Analysis - Application To Pig Selection Lines

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

The Diallel Mating Design For Mapping Interacting QTLs

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Specific Genes Selected From Doubled Haploids.

Fri, 01 Jan 1993 00:00:00 CET

No description abstract

Genetic Mapping Of Quantitative Trait Loci In Plants - A Novel Statistical approach

Sun, 01 Jan 1995 00:00:00 CET

No description abstract

Moleculaire Merkers Worden Alledaags Gereedschap

Wed, 01 Jan 1997 00:00:00 CET

No description abstract

Molecular Markers In Research And Application

Wed, 01 Jan 1997 00:00:00 CET

No description abstract

MQM Mapping Using Putative QTL Haplotypes: A Simple Approach For Mapping QTLs In Plant Breeding Populations

Sat, 01 Jan 2000 00:00:00 CET

No description abstract

Mapping of quantitative trait loci by using genetic markers: an overview of biometrical models used

Sat, 01 Jan 1994 00:00:00 CET

In crop plants quantitative variation is a feature of many important traits, such as yield, quality or disease resistance. Means of analyzing quantitative variation and especially of uncovering its potential genetic basis are therefore of prime importance for breeding purposes. It has been demonstrated in the early 20th century that such quantitative variation results from the combined action of multiple segregating genes and environmental factors. An intrinsic feature of such traits is, however, that the individual genes contributing to quantitative variation can hardly be distinguished. The genetics of such complex traits is therefore studied in general terms (population means and variances, covariances between progenies, heritabilities and so on) of classical quantitative genetics, rather than in terms of individual gene effects. Only by the use of genetically marked chromosomes, is it possible to detect and locate the loci affecting quantitative traits ("quantitative trait loci" or "QTLs"). Linkage between QTLs and morphological markers has been reported, but accurate and systematic genetic mapping has been hampered by the lack of a sufficient number of genetic markers covering an entire genome. Recently, new tooh have become available by the advent of molecular markers, such as restriction fragment length polymorphisms (RFLPs). Now, dense genetic linkage maps exist for many plant and animal species, which heralds a new era for quantitative genetics. Powerful and accurate biometrical methods are needed, so as to make possible the dissection of quantitative variation of complex characters into individual QTL effects. Mapped QTLs can be traced in breeding programmes, for instance, indirectly by selection for linked markers, or they can be cloned and introgressed via molecular or cell-biological techniques. The traditional methods for mapping of QTLs are, however, neither powerful nor accurate and the development of better methods is an area open to research. Not surprisingly, the detection and mapping of QTLs is gaining rapidly growing attention from biometrical geneticists.

Mapping QTLs In Experimental And Breeding Populations

Wed, 01 Jan 1997 00:00:00 CET

No description abstract

Quantitative Trait Loci in Inbred Lines

Mon, 01 Jan 2001 00:00:00 CET

Quantitative traits result from the influence of multiple genes (quantitative trait loci) and environmental factors. Detecting and mapping the individual genes underlying such 'complex' traits is a difficult task. Fortunately, populations obtained from crosses between inbred lines are relatively ideal for this - at least far more ideal than livestock and human populations - and true multigenic models are now available and have been applied successfully. In this chapter we will introduce the reader to statistical tools for segregation analysis and genetic mapping with the aid of molecular markers.

Optimal Design and Analysis of Genetic Studies on Gene Expression

Sun, 01 Jan 2006 00:00:00 CET

Whole-genome profiling of gene expression in a segregating population has the potential to identify the regulatory consequences of natural allelic variation. Costs of such studies are high and require that resources—microarrays and population—are used as efficiently as possible. We show that current studies can be improved significantly by a new design for two-color microarrays. Our ‘‘distant pair design’’ profiles twice as many individuals as there are arrays, cohybridizes individuals with dissimilar genomes, gives more weight to known regulatory loci if wished, and therewith maximizes the power for decomposing expression variation into regulatory factors. It can also exploit a large population (larger than twice the number of available microarrays) as a useful resource to select the most dissimilar pairs of individuals from. Our approach identifies more regulatory factors than alternative strategies do in computer simulations for realistic genome sizes, and similar promising results are obtained in an application on Arabidopsis thaliana. Our results will aid the design and analysis of future studies on gene expression and will help to shed more light on gene regulatory networks.

Sequence Polymorphisms Cause Many False cis eQTLs

Mon, 01 Jan 2007 00:00:00 CET

Many investigations have reported the successful mapping of quantitative trait loci (QTLs) for gene expression phenotypes (eQTLs). Local eQTLs, where expression phenotypes map to the genes themselves, are of especially great interest, because they are direct candidates for previously mapped physiological QTLs. Here we show that many mapped local eQTLs in genetical genomics experiments do not reflect actual expression differences caused by sequence polymorphisms in cis-acting factors changing mRNA levels. Instead they indicate hybridization differences caused by sequence polymorphisms in the mRNA region that is targeted by the microarray probes. Many such polymorphisms can be detected by a sensitive and novel statistical approach that takes the individual probe signals into account. Applying this approach to recent mouse and human eQTL data, we demonstrate that indeed many local eQTLs are falsely reported as ‘‘cis-acting’’ or ‘‘cis’’ and can be successfully detected and eliminated with this approach.

Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci

Mon, 01 Jan 2007 00:00:00 CET

Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genomewide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation in expression could be explained by expression quantitative trait loci (eQTLs). The nature and consequences of this variation are discussed based on additional genetic parameters, such as heritability and transgression and by examining the genomic position of eQTLs versus gene position, polymorphism frequency, and gene ontology. Furthermore, we developed an approach for genetic regulatory network construction by combining eQTL mapping and regulator candidate gene selection. The power of our method was shown in a case study of genes associated with flowering time, a well studied regulatory network in Arabidopsis. Results that revealed clusters of coregulated genes and their most likely regulators were in agreement with published data, and unknown relationships could be predicted.

Beyond standardization: dynamic software infrastructures for systems biology

Mon, 01 Jan 2007 00:00:00 CET

Progress in systems biology is seriously hindered by slow production of suitable software infrastructures. Biologists need infrastructure that easily connects to work that is done in other laboratories, for which standardization is helpful. However, the infrastructure must also accommodate the specifics of their biological system, but appropriate mechanisms to support variation are currently lacking. We argue that a minimal computer language, and a software tool called a generator, can be used to quickly produce customized software infrastructures that ‘systems biologists really want to have'.

MetaNetwork: a computational protocol for the genetic study of metabolic networks

Mon, 01 Jan 2007 00:00:00 CET

We here describe the MetaNetwork protocol to reconstruct metabolic networks using metabolite abundance data from segregating populations. MetaNetwork maps metabolite quantitative trait loci (mQTLs) underlying variation in metabolite abundance in individuals of a segregating population using a two-part model to account for the often observed spike in the distribution of metabolite abundance data. MetaNetwork predicts and visualizes potential associations between metabolites using correlations of mQTL profiles, rather than of abundance profiles. Simulation and permutation procedures are used to assess statistical significance. Analysis of about 20 metabolite mass peaks from a mass spectrometer takes a few minutes on a desktop computer. Analysis of 2,000 mass peaks will take up to 4 days. In addition, MetaNetwork is able to integrate high-throughput data from subsequent metabolomics, transcriptomics and proteomics experiments in conjunction with traditional phenotypic data. This way MetaNetwork will contribute to a better integration of such data into systems biology.

SELDI-TOF mass spectra: A view on sources of variation

Mon, 01 Jan 2007 00:00:00 CET

Adequate interpretation of mass spectrometry data can yield valuable biomarkers. However, spectrum interpretation is a complicated task. This paper reviews the various factors that determine a sample’s spectrum and demonstrates the role of these factors in the interpretation process. We derive a simulation model that adequately predicts the expected spectrum based on known sample content and, in the reverse mode, obtain an analysis model that adequately fits an observed spectrum based on the hypothesized sources of variation.

Mapping Determinants of Gene Expression Plasticity by Genetical Genomics in C. elegans

Sun, 01 Jan 2006 00:00:00 CET

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 gr. C and 24 gr 8 C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 8C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.

Peak quantification in surface-enhanced laser desorption/ionization by using mixture models

Sun, 01 Jan 2006 00:00:00 CET

Surface-enhanced laser desorption/ionization (SELDI) time of flight (TOF) is a mass spectrometry technology for measuring the composition of a sampled protein mixture. A mass spectrum contains peaks corresponding to proteins in the sample. The peak areas are proportional to the measured concentrations of the corresponding proteins. Quantifying peak areas is difficult for existing methods because peak shapes are not constant across a spectrum and because peaks often overlap. We present a new method for quantifying peak areas. Our method decomposes a spectrum into peaks and a baseline using so-called statistical finite mixture models.We illustrate our method in detail on 8 samples from culture media of adipose tissue and globally on 64 samples from serum to compare our method to the standard Ciphergen method. Both methods give similar estimates for singleton peaks, but not for overlapping peaks. The Ciphergen method overestimates the heights of such peaks while our method still gives appropriate estimates. Peak quantification is an important step in pre-processing SELDI-TOF data and improvements therein will pay off in the later biomarker discovery phase.

SIMAGE: simulation of DNA-microarray gene expression data. Software

Sun, 01 Jan 2006 00:00:00 CET

Background: Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other researchers by making them aware of the many factors influencing DNA microarray experiments. Results: Our model has multiple layers of factors influencing the experiment. The relative influence of such factors can differ significantly between labs, experiments within labs, etc. Therefore, we have added a module to roughly estimate their parameters from a given data set. This guarantees that our simulated data mimics real data as closely as possible. Conclusion: We introduce a model for the simulation of dual-dye cDNA-microarray data closely resembling real data and coin the model and its software implementation "SIMAGE" which stands for simulation of microarray gene expression data.

Analysis of human serum by liquid chromatography–mass spectrometry: Improved sample preparation and data analysis

Sun, 01 Jan 2006 00:00:00 CET

Discovery of biomarkers is a fast developing field in proteomics research. Liquid chromatography coupled on line to mass spectrometry (LC–MS) has become a powerful method for the sensitive detection, quantification and identification of proteins and peptides in biological fluids like serum. However, the presence of highly abundant proteins often masks those of lower abundance and thus generally prevents their detection and identification in proteomics studies. To perform future comparative analyses of samples from a serum bank of cervical cancer patients in a longitudinal and cross-sectional manner, methodology based on the depletion of high-abundance proteins followed by tryptic digestion and LC–MS has been developed. Two sample preparation methods were tested in terms of their efficiency to deplete high-abundance serum proteins and how they affect the repeatability of the LC–MS data sets. The first method comprised depletion of human serum albumin (HSA) on a dye ligand chromatographic and immunoglobulin G (IgG) on an immobilized Protein A support followed by tryptic digestion, fractionation by cation-exchange chromatography, trapping on a C18 column and reversed-phase LC–MS. The second method included depletion of the six most abundant serum proteins based on multiple immunoaffinity chromatography followed by tryptic digestion, trapping on a C18 column and reversed-phase LC–MS. Repeatability of the overall procedures was evaluated in terms of retention time and peak area for a selected number of endogenous peptides showing that the second method, besides being less time consuming, gave more repeatable results (retention time: <0.1% RSD; peak area: <30% RSD). Application of an LC–MS component detection algorithm followed by principal component analysis (PCA) enabled discrimination of serum samples that were spiked with horse heart cytochrome C from non-spiked serum and the detection of a concentration trend, which correlated to the amount of spiked horse heart cytochrome C to a level of 5 pmol cytochrome C in 2 µl original serum.