PMID: 21551031;PMCID: PMC3166216;Abstract:
Vascular plants appeared ∼410 million years ago, then diverged into several lineages of which only two survive: the euphyllophytes (ferns and seed plants) and the lycophytes. We report here the genome sequence of the lycophyte Selaginella moellendorffii (Selaginella), the first nonseed vascular plant genome reported. By comparing gene content in evolutionarily diverse taxa, we found that the transition from a gametophyte- to a sporophyte-dominated life cycle required far fewer new genes than the transition from a nonseed vascular to a flowering plant, whereas secondary metabolic genes expanded extensively and in parallel in the lycophyte and angiosperm lineages. Selaginella differs in posttranscriptional gene regulation, including small RNA regulation of repetitive elements, an absence of the trans-acting small interfering RNA pathway, and extensive RNA editing of organellar genes.
PMID: 20525626;Abstract:
Polyploidy, the genome wide duplication of chromosome number, is a key feature in eukaryote evolution. Polyploidy exists in diverse groups including animals, fungi, and invertebrates but is especially prevalent in plants with most, if not all, plant species having descended from a polyploidization event. Polyploids often differ markedly from their diploid progenitors in morphological, physiological, and life history characteristics as well as rates of adaptation. The altered characteristics displayed by polyploids may contribute to their success in novel ecological habitats. Clearly, a better understanding of the processes underlying changes in the number of chromosomes within genomes is a key goal in our understanding of speciation and adaptation for a wide range of families and genera. Despite the fundamental role of chromosome number change in eukaryotic evolution, probabilistic models describing the evolution of chromosome number along a phylogeny have not yet been formulated. We present a series of likelihood models, each representing a different hypothesis regarding the evolution of chromosome number along a given phylogeny. These models allow us to reconstruct ancestral chromosome numbers and to estimate the expected number of polyploidization events and single chromosome changes (dysploidy) that occurred along a phylogeny. We test, using simulations, the accuracy of this approach and its dependence on the number of taxa and tree length. We then demonstrate the application of the method for the study of chromosome number evolution in 4 plant genera: Aristolochia, Carex, Passiflora, and Helianthus. Considering the depth of the available cytological and phylogenetic data, formal models of chromosome number evolution are expected to advance significantly our understanding of the importance of polyploidy and dysploidy across different taxonomic groups.
PMID: 23284684;PMCID: PMC3526535;Abstract:
The development of ultra-dense genetic maps has the potential to facilitate detailed comparative genomic analyses and whole genome sequence assemblies. Here we describe the use of a custom Affymetrix GeneChip containing nearly 2.4 million features (25 bp sequences) targeting 86,023 unigenes from sunflower (Helianthus annuus L.) and related species to test for single-feature polymorphisms (SFPs) in a recombinant inbred line (RIL) mapping population derived from a cross between confectionery and oilseed sunflower lines (RHA280×RHA801). We then employed an existing genetic map derived from this same population to rigorously filter out low quality data and place 67,486 features corresponding to 22,481 unigenes on the sunflower genetic map. The resulting map contains a substantial fraction of all sunflower genes and will thus facilitate a number of downstream applications, including genome assembly and the identification of candidate genes underlying QTL or traits of interest. © 2012 Bowers et al.
We briefly introduce R2G2, an R CRAN package to visualize spatially explicit biological data within the Google Earth interface. Our package combines a collection of basic graph-editing features, including automated placement of dots, segments, polygons, images (including graphs produced with R), along with several complex three-dimensional (3D) representations such as phylogenies, histograms and pie charts. We briefly present some example data sets and show the immediate benefits in communication gained from using the Google Earth interface to visually explore biological results. The package is distributed with detailed help pages providing examples and annotated source scripts with the hope that users will have an easy time using and further developing this package. R2G2 is distributed on http://cran.r-project.org/web/packages.
