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J T Gene Hwang

Publications and source records attributed to J T Gene Hwang.

4 recordsLinked to original sources

A multi-treatment experimental system to examine photosynthetic differentiation in the maize leaf.

BACKGROUND: The establishment of C4 photosynthesis in maize is associated with differential accumulation of gene transcripts and proteins between bundle sheath and mesophyll photosynthetic cell types. We have physically separated photosynthetic cell types in the leaf blade to characterize differences in gene expression by microarray analysis. Additional control treatments were used to account for transcriptional changes induced by cell preparation treatments. To analyse these data, we have developed a statistical model to compare gene expression values derived from multiple, partially confounded, treatment groups. RESULTS: Differential gene expression in the leaves of wild-type maize seedlings was characterized using the latest release of a maize long-oligonucleotide microarray produced by the Maize Array Project consortium. The complete data set is available through the project web site. Data is also available at the NCBI GEO website, series record GSE3890. Data was analysed with and without consideration of cell preparation associated stress. CONCLUSION: Empirical comparison of the two analyses suggested that consideration of stress helped to reduce the false identification of stress responsive transcripts as cell-type enriched. Using our model including a stress term, we identified 8% of features as differentially expressed between bundle sheath and mesophyll cell types under control of false discovery rate of 5%. An estimate of the overall proportion of differentially accumulating transcripts (1-pi0) suggested that as many as 18% of the genes may be differentially expressed between B and M. The analytical model presented here is generally applicable to gene expression data and demonstrates the use of statistical elimination of confounding effects such as stress in the context of microarray analysis. We discuss the implications of the high degree of differential transcript accumulation observed with regard to both the establishment and engineering of the C4 syndrome.

Botany↗

Improved statistical tests for differential gene expression by shrinking variance components estimates.

Combining information across genes in the statistical analysis of microarray data is desirable because of the relatively small number of data points obtained for each individual gene. Here we develop an estimator of the error variance that can borrow information across genes using the James-Stein shrinkage concept. A new test statistic (FS) is constructed using this estimator. The new statistic is compared with other statistics used to test for differential expression: the gene-specific F test (F1), the pooled-variance F statistic (F3), a hybrid statistic (F2) that uses the average of the individual and pooled variances, the regularized t-statistic, the posterior odds statistic B, and the SAM t-test. The FS-test shows best or nearly best power for detecting differentially expressed genes over a wide range of simulated data in which the variance components associated with individual genes are either homogeneous or heterogeneous. Thus FS provides a powerful and robust approach to test differential expression of genes that utilizes information not available in individual gene testing approaches and does not suffer from biases of the pooled variance approach.

Animals↗

Investigating the probability of sign inconsistency in the regression coefficients of markers flanking quantitative trait loci.

Estimates of the locations and effects of quantitative trait loci (QTL) can be obtained by regressing phenotype on marker genotype. Under certain basic conditions, the signs of regression coefficients flanking QTL must be the same. There is no guarantee, however, that the signs of the regression coefficient estimates will be the same. We use sign inconsistency to describe the situation in which there is disagreement between the signs of the estimated regression coefficients flanking QTL. The presence of sign inconsistency can undermine the effectiveness of QTL mapping strategies that presume intervals whose markers have regression coefficient estimates of differing sign to be devoid of QTL. This article investigates the likelihood of sign inconsistency under various conditions. We derive an analytic expression for the approximate probability of sign inconsistency in the single-QTL case. We also examine sign inconsistency probabilities when multiple QTL are present through simulation. We have discovered that the probability of sign inconsistency can be unacceptably high, even when the conditions for QTL detection are otherwise quite favorable.

Computer Simulation↗