Tongde Hospital of Zhejiang Province
Publishes on Neuroscience and Neuropharmacology Research, Receptor Mechanisms and Signaling, Genetic Mapping and Diversity in Plants and Animals. 27 papers and 8.1k citations.
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A complementary DNA for the Aequorea victoria green fluorescent protein (GFP) produces a fluorescent product when expressed in prokaryotic (Escherichia coli) or eukaryotic (Caenorhabditis elegans) cells. Because exogenous substrates and cofactors are not required for this fluorescence, GFP expression can be used to monitor gene expression and protein localization in living organisms.
A major challenge in DNA microarray analysis is to effectively dissociate actual gene expression values from experimental noise. We report here a detailed noise analysis for oligonuleotide-based microarray experiments involving reverse transcription, generation of labeled cRNA (target) through in vitro transcription, and hybridization of the target to the probe immobilized on the substrate. By designing sets of replicate experiments that bifurcate at different steps of the assay, we are able to separate the noise caused by sample preparation and the hybridization processes. We quantitatively characterize the strength of these different sources of noise and their respective dependence on the gene expression level. We find that the sample preparation noise is small, implying that the amplification process during the sample preparation is relatively accurate. The hybridization noise is found to have very strong dependence on the expression level, with different characteristics for the low and high expression values. The hybridization noise characteristics at the high expression regime are mostly Poisson-like, whereas its characteristics for the small expression levels are more complex, probably due to cross-hybridization. A method to evaluate the significance of gene expression fold changes based on noise characteristics is proposed.
The POU-type homeodomain protein UNC-86 and the LIM-type homeodomain protein MEC-3, which specify neuronal cell fate in the nematode Caenorhabditis elegans, bind cooperatively as a heterodimer to the mec-3 promoter. Heterodimer formation increases DNA binding stability and, therefore, increases DNA binding specificity. The in vivo significance of this heterodimer formation in neuronal differentiation is suggested by (i) a loss-of-function mec-3 mutation whose product in vitro binds DNA well but forms heterodimers with UNC-86 poorly and (ii) a mec-3 mutation with wild-type function whose product binds DNA poorly but forms heterodimers well.
A method of analyzing DNA microarray data based on the physical modeling of hybridization is presented. We demonstrate, in experimental data, a correlation between observed hybridization intensity and calculated free energy of hybridization. Then, combining hybridization rate equations, calculated free energies of hybridization, and microarray data for known target concentrations, we construct an algorithm to compute transcript concentration levels from microarray data. We also develop a method for eliminating outlying data points identified by our algorithm. We test the efficacy of these methods by comparing our results with an existing statistical algorithm, as well as by performing a cross-validation test on our model.