Search

Evolutionary mechanisms underlying innovation of cell types have remained largely unclear. In multicellular eukaryotes, the evolutionary molecular origin of sperm differentiation is unknown in most lineages. Here, we report that in algal ancestors of land plants, changes in the DNA-binding domain of the ancestor of the MYB transcription factor DUO1 enabled the recognition of a new cis-regulatory element. This event led to the differentiation of motile sperm. After neo-functionalization, DUO1 acquired sperm lineage-specific expression in the common ancestor of land plants. Subsequently the downstream network of DUO1 was rewired leading to sperm with distinct morphologies. Conjugating green algae, a sister group of land plants, accumulated mutations in the DNA-binding domain of DUO1 and lost sperm differentiation. Our findings suggest that the emergence of DUO1 was the defining event in the evolution of sperm differentiation and the varied modes of sexual reproduction in the land plant lineage.

The life cycles of eukaryotes alternate between haploid and diploid phases, which are initiated by meiosis and gamete fusion, respectively. In both ascomycete and basidiomycete fungi and chlorophyte algae, the haploid-to-diploid transition is regulated by a pair of paralogous homeodomain protein encoding genes. That a common genetic program controls the haploid-to-diploid transition in phylogenetically disparate eukaryotic lineages suggests this may be the ancestral function for homeodomain proteins. Multicellularity has evolved independently in many eukaryotic lineages in either one or both phases of the life cycle. Organisms, such as land plants, exhibiting a life cycle whereby multicellular bodies develop in both the haploid and diploid phases are often referred to as possessing an alternation of generations. We review recent progress on understanding the genetic basis for the land plant alternation of generations and highlight the roles that homeodomain-encoding genes may have played in the evolution of complex multicellularity in this lineage.

The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Glycosyltransferases (GTs) (EC 2.4.x.y) catalyze the transfer of sugar moieties to a wide range of acceptor molecules, such as sugars, lipids, proteins, nucleic acids, antibiotics and other small molecules, including plant secondary metabolites. These enzymes can be classified into at least 92 families, of which family 1 glycosyltransferases (GT1), often referred to as UDP glycosyltransferases (UGTs), is the largest in the plant kingdom. To understand how UGTs expanded in both number and function during evolution of land plants, we screened genome sequences from six plants (Physcomitrella patens, Selaginella moellendorffii, Populus trichocarpa, Oryza sativa, Arabidopsis thaliana and Arabidopsis lyrata) for the presence of a conserved UGT protein domain. Phylogenetic analyses of the UGT genes revealed a significant expansion of UGTs, with lineage specificity and a higher duplication rate in vascular plants after the divergence of Physcomitrella. The UGTs from the six species fell into 24 orthologous groups that contained genes derived from the common ancestor of these six species. Some orthologous groups contained multiple UGT families with known functions, suggesting that UGTs discriminate compounds as substrates in a lineage-specific manner. Orthologous groups containing only a single UGT family tend to play a crucial role in plants, suggesting that such UGT families may have not expanded because of evolutionary constraints., (© 2011 The Authors. The Plant Journal © 2011 Blackwell Publishing Ltd.)

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

As more plant genome sequences become available, researchers are increasingly using comparative genomics to address some of the major questions in plant biology. Such questions include the evolution of photosynthesis and multicellularity, the developmental genetic changes responsible for alterations in body plan, and the origin of important plant innovations such as roots, leaves, and vascular tissue.

Neofunctionalization following gene duplication is thought to be one of the key drivers in generating evolutionary novelty. A gene duplication in a common ancestor of land plants produced two classes of KNOTTED-like TALE homeobox genes, class I (KNOX1) and class II (KNOX2). KNOX1 genes are linked to tissue proliferation and maintenance of meristematic potentials of flowering plant and moss sporophytes, and modulation of KNOX1 activity is implicated in contributing to leaf shape diversity of flowering plants. While KNOX2 function has been shown to repress the gametophytic (haploid) developmental program during moss sporophyte (diploid) development, little is known about KNOX2 function in flowering plants, hindering syntheses regarding the relationship between two classes of KNOX genes in the context of land plant evolution. Arabidopsis plants harboring loss-of-function KNOX2 alleles exhibit impaired differentiation of all aerial organs and have highly complex leaves, phenocopying gain-of-function KNOX1 alleles. Conversely, gain-of-function KNOX2 alleles in conjunction with a presumptive heterodimeric BELL TALE homeobox partner suppressed SAM activity in Arabidopsis and reduced leaf complexity in the Arabidopsis relative Cardamine hirsuta, reminiscent of loss-of-function KNOX1 alleles. Little evidence was found indicative of epistasis or mutual repression between KNOX1 and KNOX2 genes. KNOX proteins heterodimerize with BELL TALE homeobox proteins to form functional complexes, and contrary to earlier reports based on in vitro and heterologous expression, we find high selectivity between KNOX and BELL partners in vivo. Thus, KNOX2 genes confer opposing activities rather than redundant roles with KNOX1 genes, and together they act to direct the development of all above-ground organs of the Arabidopsis sporophyte. We infer that following the KNOX1/KNOX2 gene duplication in an ancestor of land plants, neofunctionalization led to evolution of antagonistic biochemical activity thereby facilitating the evolution of more complex sporophyte transcriptional networks, providing plasticity for the morphological evolution of land plant body plans. [ABSTRACT FROM AUTHOR]

The MS/MS spectral tag (MS2T) library-based peak annotation procedure was developed for informative non-targeted metabolic profiling analysis using LC-MS. An MS2T library of Arabidopsis metabolites was created from a set of MS/MS spectra acquired using the automatic data acquisition function of the mass spectrometer. By using this library, we obtained structural information for the detected peaks in the metabolic profile data without performing additional MS/MS analysis; this was achieved by searching for the corresponding MS2T accession in the library. In the case of metabolic profile data for Arabidopsis tissues containing more than 1000 peaks, approximately 50% of the peaks were tagged by MS2Ts, and 90 peaks were identified or tentatively annotated with metabolite information by searching the metabolite databases and manually interpreting the MS2Ts. A comparison of metabolic profiles among the Arabidopsis tissues revealed that many unknown metabolites accumulated in a tissue-specific manner, some of which were deduced to be unusual Arabidopsis metabolites based on the MS2T data. Candidate genes responsible for these biosyntheses could be predicted by projecting the results to the transcriptome data. The method was also used for metabolic phenotyping of a subset of Ds transposon-inserted lines of Arabidopsis, resulting in clarification of the functions of reported genes involved in glycosylation of flavonoids. Thus, non-targeted metabolic profiling analysis using MS2T annotation methods could prove to be useful for investigating novel functions of secondary metabolites in plants. [ABSTRACT FROM AUTHOR]