Biomedical subjects

Yuehua Cui

Publications and source records attributed to Yuehua Cui.

12 recordsLinked to original sources

PubMed2006

On the generalized poisson regression mixture model for mapping quantitative trait loci with count data.

Statistical methods for mapping quantitative trait loci (QTL) have been extensively studied. While most existing methods assume normal distribution of the phenotype, the normality assumption could be easily violated when phenotypes are measured in counts. One natural choice to deal with count traits is to apply the classical Poisson regression model. However, conditional on covariates, the Poisson assumption of mean-variance equality may not be valid when data are potentially under- or overdispersed. In this article, we propose an interval-mapping approach for phenotypes measured in counts. We model the effects of QTL through a generalized Poisson regression model and develop efficient likelihood-based inference procedures. This approach, implemented with the EM algorithm, allows for a genomewide scan for the existence of QTL throughout the entire genome. The performance of the proposed method is evaluated through extensive simulation studies along with comparisons with existing approaches such as the Poisson regression and the generalized estimating equation approach. An application to a rice tiller number data set is given. Our approach provides a standard procedure for mapping QTL involved in the genetic control of complex traits measured in counts.

Algorithms↗

PubMed2006

A statistical model for dissecting genomic imprinting through genetic mapping.

As a result of nonequivalent genetic contribution of maternal and paternal genomes to offsprings, genomic imprinting or called parent-of-origin effect, has been broadly identified in plants, animals and humans. Its role in shaping organism's development has been unanimously recognized. However, statistical methods for identifying imprinted quantitative trait loci (iQTL) and estimating the imprinted effect have not been well developed. In this article, we propose an efficient statistical procedure for genomewide estimating and testing the effects of significant iQTL underlying the quantitative variation of interested traits. The developed model can be applied to two different genetic cross designs, backcross and F(2) families derived from inbred lines. The proposed procedure is built within the maximum likelihood framework and implemented with the EM algorithm. Extensive simulation studies show that the proposed model is well performed in a variety of situations. To demonstrate the usefulness of the proposed approach, we apply the model to a published data in an F(2) family derived from LG/S and SM/S mouse stains. Two partially maternal imprinting iQTL are identified which regulate the growth of body weight. Our approach provides a testable framework for identifying and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗

PubMed2006

A statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci.

Non-equivalent expression of alleles at a locus results in genomic imprinting. In this article, a statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci (iQTL) underlying complex traits is developed based on experimental crosses of inbred line species in backcross populations. The joint likelihood function is composed of four component likelihood functions with each of them derived from one of four backcross families. The proposed approach models genomic imprinting effect as a probability measure with which one can test the degree of imprinting. Simulation results show that the model is robust for identifying iQTL with various degree of imprinting ranging from no imprinting, partial imprinting to complete imprinting. Under various simulation scenarios, the proposed model shows consistent parameter estimation with reasonable precision and high power in testing iQTL. When a QTL shows Mendelian effect, the proposed model also outperforms traditional Mendelian model. Extension to incorporate maternal effect is also given. The developed model, built within the maximum likelihood framework and implemented with the EM algorithm, provides a quantitative framework for testing and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗

PubMed2006

Functional mapping for genetic control of programmed cell death.

"Naturally occurring" or "programmed" cell death (PCD) in which the cell uses specialized cellular machinery to kill itself is a ubiquitous phenomenon that occurs early in organ development. Such a cell suicide mechanism that enables metazoans to control cell number and eliminate cells threatening the organism's survival has been thought to be under genetic control. In this report, we develop a novel statistical model for mapping specific genes or quantitative trait loci (QTL) that are responsible for the PCD process based on polymorphic molecular markers. This model incorporates the biological mechanisms of PCD that undergoes two different developmental stages, exponential growth and polynomial death. We derived a parametric approach to model the exponential growth and a nonparametric approach based on the Legendre function to model the polynomial death. A series of stationary and nonstationary models has been used to approximate the structure of the covariance matrix among cell numbers at a multitude of different times. The statistical behavior of our model is investigated through simulation studies and validated by a real example in rice.

Apoptosis↗

PubMed2006

Model for mapping imprinted quantitative trait loci in an inbred F2 design.

The role of imprinting in shaping development has been ubiquitously observed in plants, animals, and humans. However, a statistical method that can detect and estimate the effects of imprinted quantitative trait loci (iQTL) over the genome has not been extensively developed. In this article, we propose a maximum likelihood approach for testing and estimating the imprinted effects of iQTL that contribute to variation in a quantitative trait. This approach, implemented with the EM algorithm, allows for a genome-wide scan for the existence of iQTL. This approach was used to reanalyze published data in an F(2) family derived from the LG/S and SM/S mouse strains. Several iQTL that regulate the growth of body weight by expressing paternally inherited alleles were identified. Our approach provides a standard procedure for testing the statistical significance of iQTL involved in the genetic control of complex traits.

Algorithms↗

PubMed2006

Modelling epistatic effects of embryo and endosperm QTL on seed quality traits.

Coordinated expression of embryo and endosperm tissues is required for proper seed development. The coordination among these two tissues is controlled by the interaction between multiple genes expressed in the embryo and endosperm genomes. In this article, we present a statistical model for testing whether quantitative trait loci (QTL) active in different genomes, diploid embryo and triploid endosperm, epistatically affect a trait expressed on the endosperm tissue. The maximum likelihood approach, implemented with the EM algorithm, was derived to provide the maximum likelihood estimates of the locations of embryo- and endosperm-specific QTL and their main effects and epistatic effects. This model was used in a real example for rice in which two QTL, one from the embryo genome and the other from the endosperm genome, exert a significant interaction effect on gel consistency on the endosperm. Our model has successfully detected Waxy, a candidate gene in the embryo genome known to regulate one of the major steps of amylose biosynthesis in the endosperm. This model will have great implications for agricultural and evolutionary genetic research.

Algorithms↗

PubMed2006

Soy isoflavones alter expression of genes associated with cancer progression, including interleukin-8, in androgen-independent PC-3 human prostate cancer cells.

High consumption of soy isoflavones in Asian diets has been correlated with a lower incidence of clinically important cases of prostate cancer. The chemopreventive properties of these diets may result from an interaction of several types of isoflavones, including genistein and daidzein. The present study investigated the effects of a soy isoflavone concentrate (ISF) on growth and gene expression profiles of PC-3 human prostate cancer cells. Trypan blue exclusion and [3H]-thymidine incorporation assays showed that ISF decreased cell viability and caused a dose-dependent inhibition of DNA synthesis, respectively, with 50% inhibition (IC50) of DNA synthesis at 52 mg/L (P = 0.05). The glucoside conjugates of genistein and daidzein in ISF were converted to bioactive free aglycones in cell culture in association with the inhibition of DNA synthesis. Flow cytometry and Western immunoblot analyses showed that ISF at 200 mg/L caused an accumulation of cells in the G2/M phase of the cell cycle (P < 0.05) and decreased cyclin A by 20% (P < 0.05), respectively. The effect of ISF on the gene expression profile of PC-3 cells was analyzed using Affymetrix oligonucleotide DNA microarrays that interrogate approximately 17,000 human genes. Of the 75 genes altered by ISF, 28 were upregulated and 47 were downregulated (P < 0.05). Further analysis showed that IL-8, matrix metalloproteinase 13, inhibin beta A, follistatin, and fibronectin mRNA levels were significantly reduced, whereas the expression of p21(CIP1), a major cell cycle inhibitory protein, was increased. The effects of ISF on the expression of IL-8 and p21(CIP1) mRNA and protein were validated at high and low ISF concentrations. Our data show that ISF inhibits the growth of PC-3 cells through modulation of cell cycle progression and the expression of genes involved in cell cycle regulation, metastasis, and angiogenesis.

DNA↗

PubMed2005

Environmental stress alters genes expression and induces ovule abortion: reactive oxygen species appear as ovules commit to abort.

Environmental stress dramatically reduces plant reproduction. Previous results showed that placing roots in 200 mM NaCl for 12 h caused 90% of the developing Arabidopsis ovules to abort (Sun et al. in Plant Physiol 135:2358-2367, 2004). To discover the molecular responses that occur during ovule abortion, gene expression was monitored using Affymetrix 24k genome arrays. Transcript levels were measured in pistils that were stressed for 6, 12, 18, and 24 h, then compared with the levels in healthy pistils. Over the course of this experiment, a total of 535 salt-responsive genes were identified. Cluster analysis showed that differentially expressed genes exhibited reproducible changes in expression. The expression of 65 transcription factors, some of which are known to be involved in stress responses, were modulated during ovule abortion. In flowers, salt stress led to a 30-fold increase in Na+ ions and modest, but significant, decreases in the accumulation of other ions. The expression of cation exchangers and ion transporters were induced, presumably to reestablish ion homeostasis following salt stress. Genes that encode enzymes that detoxify reactive oxygen species (ROS), including ascorbate peroxidase and peroxidase, were downregulated after ovules committed to abort. These changes in gene expression coincided with the synthesis of ROS in female gametophytes. One day after salt stress, ROS spread from the gametophytes to the maternal chalaza and integuments. In addition, genes encoding proteins that regulate ethylene responses, including ethylene biosynthesis, ethylene signal transduction and ethylene-responsive transcription factors, were upregulated after stress. Hypotheses are proposed on the basis of this expression analysis, which will be evaluated further in future experiments.

Arabidopsis↗

PubMed2005

Mapping genome-genome epistasis: a high-dimensional model.

MOTIVATION: The proper development of any organ or tissue requires the coordinated expression of its underlying genes that can be located on different genomes present in an organism. For instance, each step in the development of seed for a higher plant is the consequence of gene interactions from the maternal, embryo and endosperm genomes. RESULTS: We present a multivariate statistical model for mapping quantitative trait loci (QTL) by incorporating two important aspects of seed development in plants-QTL interactions derived from different genomes, the maternal, embryo and endosperm, and genetic correlations among phenotypic traits expressed in different genome-specific tissues. This model, which has a high dimensionality, is constructed within the maximum-likelihood context based on a finite mixture model. The implementation of the expectation-maximization algorithm allows for the efficient estimation of QTL positions, their action and interaction effects and pleiotropic effects. The application of this high-dimensional model to a real rice dataset has validated its usefulness. CONCLUSIONS: Our model was derived for self-pollinated plants, but it can be extended to cross-pollinated plants and to animals. With the burgeoning of genetic and genomic data, this high-dimensional model will have many implications for agricultural and evolutionary genetic research. AVAILABILITY: A package of software will be provided from the corresponding author upon request.

Chromosome Mapping↗

PubMed2005

Statistical model for characterizing epistatic control of triploid endosperm triggered by maternal and offspring QTLs.

To study the effects of maternal and endosperm quantitative trait locus (QTL) interaction on endosperm development, we derive a two-stage hierarchical statistical model within the maximum-likelihood context, implemented with an expectation-maximization algorithm. A model incorporating both maternal and offspring marker information can improve the accuracy and precision of genetic mapping. Extensive simulations under different sampling strategies, heritability levels and gene action modes were performed to investigate the statistical properties of the model. The QTL location and parameters are better estimated when two QTLs are located at different intervals than when they are located at the same interval. Also, the additive effect of the offspring QTLs is better estimated than the additive effect of the maternal QTLs. The implications of our model for agricultural and evolutionary genetic research are discussed.

Algorithms↗

PubMed2004

A multilocus likelihood approach to joint modeling of linkage, parental diplotype and gene order in a full-sib family.

BACKGROUND: Unlike a pedigree initiated with two inbred lines, a full-sib family derived from two outbred parents frequently has many different segregation types of markers whose linkage phases are not known prior to linkage analysis. RESULTS: We formulate a general model of simultaneously estimating linkage, parental diplotype and gene order through multi-point analysis in a full-sib family. Our model is based on a multinomial mixture model taking into account different diplotypes and gene orders, weighted by their corresponding occurring probabilities. The EM algorithm is implemented to provide the maximum likelihood estimates of the linkage, parental diplotype and gene order over any type of markers. CONCLUSIONS: Through simulation studies, this model is found to be more computationally efficient compared with existing models for linkage mapping. We discuss the extension of the model and its implications for genome mapping in outcrossing species.

Alleles↗

PubMed2004

Mapping quantitative trait Loci interactions from the maternal and offspring genomes.

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.

Animals↗