Allopolyploidization, i.e., concomitant merging and doubling of two or more divergent genomes in a common nucleus/cytoplasm, is known to instantly alter genome-wide transcriptome dynamics, a phenomenon referred to as “transcriptomic shock”. However, the immediate effects of transcriptomic alteration in generating phenotypic diversity at the population level remain under-investigated. Here, we employed the MassARRAY-based Sequenom platform to assess and compare orthologous, allelic, and homeologous gene expression status in two tissues (leaf and root) of a set of randomly chosen individuals from populations of parental rice subspecies (indica and japonica), in vitro “hybrids” (parental mixes), reciprocal F1 hybrids and reciprocal tetraploids at the 5th-selfed generation (S5). We show that hybridization and whole genome duplication (WGD) have opposing effects on allelic and homeologous expression in the F1 hybrids and tetraploids, respectively. Whereas hybridization exerts strong attenuating effects on allelic expression differences in diploid hybrids, WGD augments the intrinsic parental differences and generates extensive and variable homeolog content which triggers diversification in expression patterning among the tetraploid plants. Coupled with the vast phenotypic diversity observed among the tetraploid individuals, our results provide experimental evidence in support of the notion that allopolyploidy catalyzes rapid phenotypic diversification in higher plants. Our data further suggest that largely stochastic homeolog content reshuffling rather than alteration in total expression level may be an important feature of evolution in young segmental allopolyploids, which underlies rapid expression diversity at the population level.

Polyploidy is a widespread phenomenon throughout eukaryotes, with important ecological and evolutionary consequences. Although genes operate as components of complex pathways and networks, polyploid changes in genes and gene expression have typically been evaluated as either individual genes or as a part of broad-scale analyses. Network analysis has been fruitful in associating genomic and other 'omic'-based changes with phenotype for many systems. In polyploid species, network analysis has the potential not only to facilitate a better understanding of the complex 'omic' underpinnings of phenotypic and ecological traits common to polyploidy, but also to provide novel insight into the interaction among duplicated genes and genomes. This adds perspective to the global patterns of expression (and other 'omic') change that accompany polyploidy and to the patterns of recruitment and/or loss of genes following polyploidization. While network analysis in polyploid species faces challenges common to other analyses of duplicated genomes, present technologies combined with thoughtful experimental design provide a powerful system to explore polyploid evolution. Here, we demonstrate the utility and potential of network analysis to questions pertaining to polyploidy with an example involving evolution of the transgressively superior cotton fibres found in polyploid Gossypium hirsutum. By combining network analysis with prior knowledge, we provide further insights into the role of profilins in fibre domestication and exemplify the potential for network analysis in polyploid species.

We examined three parallel data sets with respect to qualities relevant to phylogenetic analysis of 20 exemplar monocotyledons and related dicotyledons. The three data sets represent restriction site variation in the inverted repeat region of the chloroplast genome, and nucleotide sequence variation in the chloroplast-encoded gene rbcL and in the mitochondrion-encoded gene atpA, the latter of which encodes the *-subunit of mitochondrial ATP synthase. The plant mitochondrial genome has been little-used in plant systematics, in part because nucleotide sequence evolution in enzyme-encoding genes of this genome evolve relatively slowly. The three data sets were examined in separate and combined analyses, with a focus on patterns of congruence, homoplasy, and data decisiveness. Data decisiveness (described by P. Goloboff) is a measure of robustness of support for most-parsimonious trees by a data set in terms of the degree to which those trees are shorter than the average length of all possible trees. Because indecisive data sets require relatively fewer additional steps than decisive ones to be optimized on nonparsimonious trees, they will have a lesser tendency to be incongruent with other data sets. One consequence of this relationship between decisiveness and character incongruence is that if incongruence is used as a criterion of noncombinability, decisive data sets, which provide robust support for relationships, are more likely to be assessed as noncombinable with other data sets than are indecisive data sets, which provide weak support for relationships. For the sampling of taxa in this study, the atpA data set has about half as many cladistically informative nucleotides as the rbcL data set per site examined, and is less homoplastic and more decisive. The rbcL data set, which is the least decisive of the three, exhibits the lowest levels of character incongruence. Whatever the molecular evolutionary cause of this phenomenon, it seems likely that the poorer performance of rbcL than atpA, in terms of data decisiveness, is due to both its higher overall level of homoplasy and the fact that it is performing especially poorly at nonsynonymous sites.