Biomedical subjects

Zhao-Bang Zeng

Publications and source records attributed to Zhao-Bang Zeng.

11 recordsLinked to original sources

PubMed2007

eQTL Viewer: visualizing how sequence variation affects genome-wide transcription.

BACKGROUND: Expression Quantitative Trait Locus (eQTL) mapping methods have been used to identify the genetic basis of gene expression variations. To map eQTL, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations. These eQTL distribute in many chromosomal regions, each of which can include many genes. The large number of mapping results produced makes it difficult to consider simultaneously the relationships between multiple genomic regions and multiple expressional profiles. There is a need for informative bioinformatics tools to assist the visualization and interpretation of these mapping results. RESULTS: We have developed a web-based tool, called eQTL Viewer, to visualize the relationships between the expression trait genes and the candidate genes in the eQTL regions using Scalable Vector Graphics. The plot generated by eQTL Viewer has the capacity to display mapping results with high resolutions at a variety of scales, and superimpose biological annotations onto the mapping results dynamically. CONCLUSION: Our tool provides an efficient and intuitive way for biologists to explore transcriptional regulation patterns, and to generate hypotheses on the genetic basis of transcriptional regulations.

Algorithms↗

PubMed2006

Multiple-interval mapping for ordinal traits.

Many statistical methods have been developed to map multiple quantitative trait loci (QTL) in experimental cross populations. Among these methods, multiple-interval mapping (MIM) can map QTL with epistasis simultaneously. However, the previous implementation of MIM is for continuously distributed traits. In this study we extend MIM to ordinal traits on the basis of a threshold model. The method inherits the properties and advantages of MIM and can fit a model of multiple QTL effects and epistasis on the underlying liability score. We study a number of statistical issues associated with the method, such as the efficiency and stability of maximization and model selection. We also use computer simulation to study the performance of the method and compare it to other alternative approaches. The method has been implemented in QTL Cartographer to facilitate its general usage for QTL mapping data analysis on binary and ordinal traits.

Algorithms↗

PubMed2006

Models and partition of variance for quantitative trait loci with epistasis and linkage disequilibrium.

BACKGROUND: A genetic model about quantitative trait loci (QTL) provides a basis to interpret the genetic basis of quantitative traits in a study population, such as additive, dominance and epistatic effects of QTL and the partition of genetic variance. The standard quantitative genetics model is based on the least squares partition of genetic effects and also genetic variance in an equilibrium population. However, over years many specialized QTL models have also been proposed for applications in some specific populations. How are these models related? How to analyze and partition a QTL model and genetic variance when both epistasis and linkage disequilibrium are considered? RESULTS: Starting from the classical description of Cockerham genetic model, we first represent the model in a multiple regression setting by using indicator variables to describe the segregation of QTL alleles. In this setting, the definition of additive, dominance and epistatic effects of QTL and the basis for the partition of genetic variance are elaborated. We then build the connection between this general genetic model and a few specialized models (a haploid model, a diploid F2 model and a general two-allele model), and derive the genetic effects and partition of genetic variance for multiple QTL with epistasis and linkage disequilibrium for these specialized models. CONCLUSION: In this paper, we study extensively the composition and property of the genetic model parameters, such as genetic effects and partition of genetic variance, when both epistasis and linkage disequilibrium are considered. This is the first time that both epistasis and linkage disequilibrium are considered in modeling multiple QTL. This analysis would help us to understand the structure of genetic parameters and relationship of various genetic quantities, such as allelic frequencies and linkage disequilibrium, on the definition of genetic effects, and will also help us to understand and properly interpret estimates of the genetic effects and variance components in a QTL mapping experiment.

Algorithms↗

PubMed2006

A population-based latent variable approach for association mapping of quantitative trait loci.

A population-based latent variable approach is proposed for association mapping of quantitative trait loci (QTL), using multiple closely linked genetic markers within a small candidate region in the genome. By incorporating QTL as latent variables into a penetrance model, the QTL are flexible to characterize either alleles at putative trait loci or potential risk haplotypes/sub-haplotypes of the markers. Under a general likelihood framework, we develop an EM-based algorithm to estimate genetic effects of the QTL and haplotype frequencies of the QTL and markers jointly. Closed form solutions derived in the maximization step of the EM procedure for updating the joint haplotype frequencies of QTL and markers can effectively reduce the computational intensity. Various association measures between QTL and markers can then be derived from the haplotype frequencies of markers and used to infer QTL positions. The likelihood ratio statistic also provides a joint test for association between a quantitative trait and marker genotypes without requiring adjustment for the multiple testing. Extensive simulation studies are performed to evaluate the approach.

Algorithms↗

PubMed2005

Genetic architecture of transcript-level variation in differentiating xylem of a eucalyptus hybrid.

Species diversity may have evolved by differential regulation of a similar set of genes. To analyze and compare the genetic architecture of transcript regulation in different genetic backgrounds of Eucalyptus, microarrays were used to examine variation in mRNA abundance in the differentiating xylem of a E. grandis pseudobackcross population [E. grandis x F(1) hybrid (E. grandis x E. globulus)]. Least-squares mean estimates of transcript levels were generated for 2608 genes in 91 interspecific backcross progeny. The quantitative measurements of variation in transcript abundance for specific genes were mapped as expression QTL (eQTL) in two single-tree genetic linkage maps (F(1) hybrid paternal and E. grandis maternal). EQTL were identified for 1067 genes in the two maps, of which 811 were located in the F(1) hybrid paternal map, and 451 in the E. grandis maternal map. EQTL for 195 genes mapped to both parental maps, the majority of which localized to nonhomologous linkage groups, suggesting trans-regulation by different loci in the two genetic backgrounds. For 821 genes, a single eQTL that explained up to 70% of the transcript-level variation was identified. Hotspots with colocalized eQTL were identified in both maps and typically contained genes associated with specific metabolic and regulatory pathways, suggesting coordinated genetic regulation.

Cell Differentiation↗

PubMed2005

Modeling quantitative trait Loci and interpretation of models.

A quantitative genetic model relates the genotypic value of an individual to the alleles at the loci that contribute to the variation in a population in terms of additive, dominance, and epistatic effects. This partition of genetic effects is related to the partition of genetic variance. A number of models have been proposed to describe this relationship: some are based on the orthogonal partition of genetic variance in an equilibrium population. We compare a few representative models and discuss their utility and potential problems for analyzing quantitative trait loci (QTL) in a segregating population. An orthogonal model implies that estimates of the genetic effects are consistent in a full or reduced model in an equilibrium population and are directly related to the partition of the genetic variance in the population. Linkage disequilibrium does not affect the estimation of genetic effects in a full model, but would in a reduced model. Certainly linkage disequilibrium would complicate the detection of QTL and epistasis. Using different models does not influence the detection of QTL and epistasis. However, it does influence the estimation and interpretation of genetic effects.

Gene Frequency↗

PubMed2005

QTL mapping and the genetic basis of adaptation: recent developments.

Quantitative trait loci (QTL) mapping has been used in a number of evolutionary studies to study the genetic basis of adaptation by mapping individual QTL that explain the differences between differentiated populations and also estimating their effects and interaction in the mapping population. This analysis can provide clues about the evolutionary history of populations and causes of the population differentiation. QTL mapping analysis methods and associated computer programs provide us tools for such an inference on the genetic basis and architecture of quantitative trait variation in a mapping population. Current methods have the capability to separate and localize multiple QTL and estimate their effects and interaction on a quantitative trait. More recent methods have been targeted to provide a comprehensive inference on the overall genetic architecture of multiple traits in a number of environments. This development is important for evolutionary studies on the genetic basis of multiple trait variation, genotype by environment interaction, host-parasite interaction, and also microarray gene expression QTL analysis.

Adaptation, Biological↗

PubMed2003

Genetic dissection of hybrid incompatibilities between Drosophila simulans and D. mauritiana. II. Mapping hybrid male sterility loci on the third chromosome.

Hybrid male sterility (HMS) is a rapidly evolving mechanism of reproductive isolation in Drosophila. Here we report a genetic analysis of HMS in third-chromosome segments of Drosophila mauritiana that were introgressed into a D. simulans background. Qualitative genetic mapping was used to localize 10 loci on 3R and a quantitative trait locus (QTL) procedure (multiple-interval mapping) was used to identify 19 loci on the entire chromosome. These genetic incompatibilities often show dominance and complex patterns of epistasis. Most of the HMS loci have relatively small effects and generally at least two or three of them are required to produce complete sterility. Only one small region of the third chromosome of D. mauritiana by itself causes a high level of infertility when introgressed into D. simulans. By comparison with previous studies of the X chromosome, we infer that HMS loci are only approximately 40% as dense on this autosome as they are on the X chromosome. These results are consistent with the gradual evolution of hybrid incompatibilities as a by-product of genetic divergence in allopatric populations.

Alleles↗

PubMed2002

Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing species.

With the advent of new molecular marker technologies, it is now feasible to initiate genome projects for outcrossing plant species, which have not received much attention in genetic research, despite their great agricultural and environmental value. Because outcrossing species typically have heterogeneous genomes, data structure for molecular markers representing an entire genome is complex: some markers may have more alleles than others, some markers are codominant whereas others are dominant, and some markers are heterozygous in one parent but fixed in the other parent whereas the opposite can be true for other markers. A major difficulty in analyzing these different types of marker at the same time arises from uncertainty about parental linkage phases over markers. In this paper, we present a general maximum-likelihood-based algorithm for simultaneously estimating linkage and linkage phases for a mixed set of different marker types containing fully informative markers (segregating 1:1:1:1) and partially informative markers (or missing markers, segregating 1:2:1, 3:1, and 1:1) in a full-sib family derived from two outbred parent plants. The characterization of linkage phases is based on the posterior probability distribution of the assignment of alternative alleles at given markers to two homologous chromosomes of each parent, conditional on the observed phenotypes of the markers. Two- and multi-point analyses are performed to estimate the recombination fraction and determine the most likely linkage phase between different types of markers. A numerical example is presented to demonstrate the statistical properties of the model for characterizing the linkage phase between markers.

Algorithms↗

PubMed2002

Linkage mapping of sex-specific differences.

Most current linkage analyses assume identical fractions of meiotic recombination between homologous marker loci of the two sexes. This assumption is not realistic, because considerable sex-related differences have been observed in recombination fraction. In this paper, a general EM-based algorithm is presented to estimate sex-specific recombination fractions for a mixed set of molecular markers segregating differently in a full-sib family derived from two heterozygous parents. The asymptotic variances of the estimates of linkage specifically for each of the parents are evaluated using a numerical analysis based on information functions. This approach will have important implications for precise gene mapping based on sex-specific linkage maps.

Algorithms↗

PubMed2002

Modeling epistasis of quantitative trait loci using Cockerham's model.

We use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.

Analysis of Variance↗