Biomedical subjects
Naomi Altman
Publications and source records attributed to Naomi Altman.
Expression pattern shifts following duplication indicative of subfunctionalization and neofunctionalization in regulatory genes of Arabidopsis.
Gene duplication plays an important role in the evolution of diversity and novel function and is especially prevalent in the nuclear genomes of flowering plants. Duplicate genes may be maintained through subfunctionalization and neofunctionalization at the level of expression or coding sequence. In order to test the hypothesis that duplicated regulatory genes will be differentially expressed in a specific manner indicative of regulatory subfunctionalization and/or neofunctionalization, we examined expression pattern shifts in duplicated regulatory genes in Arabidopsis. A two-way analysis of variance was performed on expression data for 280 phylogenetically identified paralogous pairs. Expression data were extracted from global expression profiles for wild-type root, stem, leaf, developing inflorescence, nearly mature flower buds, and seedpod. Gene, organ, and gene by organ interaction (G x O) effects were examined. Results indicate that 85% of the paralogous pairs exhibited a significant G x O effect indicative of regulatory subfunctionalization and/or neofunctionalization. A significant G x O effect was associated with complementary expression patterns in 45% of pairwise comparisons. No association was detected between a G x O effect and a relaxed evolutionary constraint as detected by the ratio of nonsynonymous to synonymous substitutions. Ancestral gene expression patterns inferred across a Type II MADS-box gene phylogeny suggest several cases of regulatory neofunctionalization and organ-specific nonfunctionalization. Complete linkage clustering of gene expression levels across organs suggests that regulatory modules for each organ are independent or ancestral genes had limited expression. We propose a new classification, regulatory hypofunctionalization, for an overall decrease in expression level in one member of a paralogous pair while still having a significant G x O effect. We conclude that expression divergence specifically indicative of subfunctionalization and/or neofunctionalization contributes to the maintenance of most if not all duplicated regulatory genes in Arabidopsis and hypothesize that this results in increasing expression diversity or specificity of regulatory genes after each round of duplication.
Genome-wide expression profiling and identification of gene activities during early flower development in Arabidopsis.
We have used oligonucleotide microarrays to detect Arabidopsis gene expression during early flower development. Among the 22,746 genes represented on the Affymetrix ATH1 chip, approximately 14,660 (approximately 64.5%) genes were expressed with signal intensity at or more than 50 in each of the six organs/structures examined, including young inflorescences (floral stages 1-9), stage-12 floral buds, developing siliques, leaves, stems, and roots. 17,583 genes were expressed with an intensity at or above 50 in at least one tissue, including 12,245 genes that were expressed in all the six tissues. Comparison of genes expressed between young inflorescence or stage-12 floral buds with other tissues suggests that relatively large numbers of genes are expressed at similar levels in tissues that are related morphologically and/or developmentally, as supported by a cluster analysis with data from two other studies. Further analysis of the genes preferentially expressed in floral tissues has uncovered new genes potentially involved in Arabidopsis flower development. One hundred and four genes were determined to be preferentially expressed in young inflorescences, including 22 genes encoding putative transcription factors. We also identified 105 genes that were preferentially expressed in three reproductive structures (the young inflorescences, stage-12 floral buds and developing siliques), when compared with the vegetative tissues. RT-PCR results of selected genes are consistent with the results from these microarrays and suggest that the relative signal intensities detected with the Affymetrix microarray are reliable estimates of gene expression.
Replication, variation and normalisation in microarray experiments.
INTRODUCTION: Microarray experiments often have complex designs that include sample pooling, biological and technical replication, sample pairing and dye-swapping. This article demonstrates how statistical modelling can illuminate issues in the design and analysis of microarray experiments, and this information can then be used to plan effective studies. METHODS: A very detailed statistical model for microarray data is introduced, to show the possible sources of variation that are present in even the simplest microarray experiments. Based on this model, the efficacy of common experimental designs, normalisation methodologies and analyses is determined. RESULTS: When the cost of the arrays is high compared with the cost of samples, sample pooling and spot replication are shown to be efficient variance reduction methods, whereas technical replication of whole arrays is demonstrated to be very inefficient. Dye-swap designs can use biological replicates rather than technical replicates to improve efficiency and simplify analysis. When the cost of samples is high and technical variation is a major portion of the error, technical replication can be cost effective. Normalisation by centreing on a small number of spots may reduce array effects, but can introduce considerable variation in the results. Centreing using the bulk of spots on the array is less variable. Similarly, normalisation methods based on regression methods can introduce variability. Except for normalisation methods based on spiking controls, all normalisation requires that most genes do not differentially express. Methods based on spatial location and/or intensity also require that the nondifferentially expressing genes are at random with respect to location and intensity. Spotting designs should be carefully done so that spot replicates are widely spaced on the array, and genes with similar expression patterns are not clustered. DISCUSSION: The tools for statistical design of experiments can be applied to microarray experiments to improve both efficiency and validity of the studies. Given the high cost of microarray experiments, the benefits of statistical input prior to running the experiment cannot be over-emphasised.
Genome-wide analysis of the cyclin family in Arabidopsis and comparative phylogenetic analysis of plant cyclin-like proteins.
Cyclins are primary regulators of the activity of cyclin-dependent kinases, which are known to play critical roles in controlling eukaryotic cell cycle progression. While there has been extensive research on cell cycle mechanisms and cyclin function in animals and yeasts, only a small number of plant cyclins have been characterized functionally. In this paper, we describe an exhaustive search for cyclin genes in the Arabidopsis genome and among available sequences from other vascular plants. Based on phylogenetic analysis, we define 10 classes of plant cyclins, four of which are plant-specific, and a fifth is shared between plants and protists but not animals. Microarray and reverse transcriptase-polymerase chain reaction analyses further provide expression profiles of cyclin genes in different tissues of wild-type Arabidopsis plants. Comparative phylogenetic studies of 174 plant cyclins were also performed. The phylogenetic results imply that the cyclin gene family in plants has experienced more gene duplication events than in animals. Expression patterns and phylogenetic analyses of Arabidopsis cyclin genes suggest potential gene redundancy among members belonging to the same group. We discuss possible divergence and conservation of some plant cyclins. Our study provides an opportunity to rapidly assess the position of plant cyclin genes in terms of evolution and classification, serving as a guide for further functional study of plant cyclins.