Zenaida V. Magbanua

Evolution of Genome Size and Complexity in Pinus

Background Genome evolution in the gymnosperm lineage of seed plants has given rise to many of the most complex and largest plant genomes, however the elements involved are poorly understood. Methodology/Principal Findings Gymny is a previously undescribed retrotransposon family in Pinus that is related to Athila elements in Arabidopsis. Gymny elements are dispersed throughout the modern Pinus genome and occupy a physical space at least the size of the Arabidopsis thaliana genome. In contrast to previously described retroelements in Pinus, the Gymny family was amplified or introduced after the divergence of pine and spruce (Picea). If retrotransposon expansions are responsible for genome size differences within the Pinaceae, as they are in angiosperms, then they have yet to be identified. In contrast, molecular divergence of Gymny retrotransposons together with other families of retrotransposons can account for the large genome complexity of pines along with protein-coding genic DNA, as revealed by massively parallel DNA sequence analysis of Cot fractionated genomic DNA. Conclusions/Significance Most of the enormous genome complexity of pines can be explained by divergence of retrotransposons, however the elements responsible for genome size variation are yet to be identified. Genomic resources for Pinus including those reported here should assist in further defining whether and how the roles of retrotransposons differ in the evolution of angiosperm and gymnosperm genomes.

Empirical comparison of ab initio repeat finding programs

Identification of dispersed repetitive elements can be difficult, especially when elements share little or no homology with previously described repeats. Consequently, a growing number of computational tools have been designed to identify repetitive elements in an ab initio manner, i.e. without using prior sequence data. Here we present the results of side-by-side evaluations of six of the most widely used ab initio repeat finding programs. Using sequence from rice chromosome 12, tools were compared with regard to time requirements, ability to find known repeats, utility in identifying potential novel repeats, number and types of repeat elements recognized and compactness of family descriptions. The study reveals profound differences in the utility of the tools with some identifying virtually their entire substrate as repetitive, others making reasonable estimates of repetition, and some missing almost all repeats. Of note, even when tools recognized similar numbers of repeats they often showed marked differences in the nature and number of repeat families identified. Within the context of this comparative study, ReAS and RepeatScout showed the most promise in analysis of sequence reads and assembled genomic regions, respectively. Our results should help biologists identify the program(s), if any, that is best suited for their needs.

Adventures in the Enormous: A 1.8 Million Clone BAC Library for the 21.7 Gb Genome of Loblolly Pine

Loblolly pine (LP; Pinus taeda L.) is the most economically important tree in the U.S. and a cornerstone species in southeastern forests. However, genomics research on LP and other conifers has lagged behind studies on flowering plants due, in part, to the large size of conifer genomes. As a means to accelerate conifer genome research, we constructed a BAC library for the LP genotype 7-56. The LP BAC library consists of 1,824,768 individually-archived clones making it the largest single BAC library constructed to date, has a mean insert size of 96 kb, and affords 7.6X coverage of the 21.7 Gb LP genome. To demonstrate the efficacy of the library in gene isolation, we screened macroarrays with overgos designed from a pine EST anchored on LP chromosome 10. A positive BAC was sequenced and found to contain the expected full-length target gene, several gene-like regions, and both known and novel repeats. Macroarray analysis using the retrotransposon IFG-7 (the most abundant repeat in the sequenced BAC) as a probe indicates that IFG-7 is found in roughly 210,557 copies and constitutes about 5.8% or 1.26 Gb of LP nuclear DNA; this DNA quantity is eight times the Arabidopsis genome. In addition to its use in genome characterization and gene isolation as demonstrated herein, the BAC library should hasten whole genome sequencing of LP via next-generation sequencing strategies/technologies and facilitate improvement of trees through molecular breeding and genetic engineering. The library and associated products are distributed by the Clemson University Genomics Institute (www.genome.clemson.edu).

Computational Approaches and Tools Used in Identification of Dispersed Repetitive DNA Sequences

It has become clear that dispersed repeat sequences have played multiple roles in eukaryotic genome evolution including increasing genetic diversity through mutation, inducing changes in gene expression, and facilitating generation of novel genes. Growing recognition of the importance of dispersed repeats has fueled development of computational tools designed to expedite discovery and classification of repeats. Here we review major existing repeat exploration tools and discuss the algorithms utilized by these tools. Special attention is devoted to ab initio programs, i.e., those tools that do not rely upon previously identified repeats to find new repeat elements. We conclude by discussing the strengths and weaknesses of current tools and highlighting additional approaches that may advance repeat discovery/characterization.

Is Catalase Activity One of the Factors Associated with Maize Resistance to Aspergillus flavus

Plant responses to biotic and abiotic stresses are usually accompanied by the release of reactive oxygen species including hydrogen peroxide. Hydrogen peroxide plays a direct role in defense and is involved in many signal transduction pathways that lead to the proliferation of other defenses. Because catalase helps to maintain reactive oxygen homeostasis during biotic and abiotic stress, its activity was measured in various cob tissues during maize ear development. Catalase activity was determined in immature and mature embryos, pericarp, and rachis tissues of maize lines that are resistant and susceptible to Aspergillus flavus infection. The effect of fungal inoculation on catalase activity was also measured. Over two years of field experimentation, a correlation was observed between resistance and the level of catalase-specific activity in immature embryos, which was significantly higher in resistant lines (P < 0.0001). Furthermore, catalase activity in the resistant lines was significantly higher in immature embryos from inoculated ears (P = 0.0199). No correlation was observed between resistance and catalase activity in other ear tissues. Levels of hydrogen peroxide, the catalase substrate, and salicylic acid in the embryo were also determined. The resistant lines showed lower levels of H2O2 (P < 0.0001) and higher levels of salicylic acid (P < 0.0001) as compared with the susceptible lines. Catalase 3 was sequenced from the aflatoxin-resistant (Mp313E) and susceptible (SC212m) inbreds. The predicted amino acid sequence indicated that there was a 20-aa deletion in the resistant inbred that might affect enzymatic activity. Unlike many plant-pathogen interactions, it appears that lowering H2O2 levels helps to prevent A. flavus infection and subsequent aflatoxin accumulation.

Genome Sequence of the Oleaginous Yeast Rhodotorula glutinis ATCC 204091.

ABSTRACT Rhodotorula glutinis ATCC 204091 is an oleaginous oxidative red yeast that can accumulate lipids to >50% of its biomass when grown with appropriate carbon and nitrogen ratios. It produces a red pigment consisting of useful antioxidants, such as carotenoids, torulene, and torularhodin, when cultivated under carbon-deficient conditions.

Transcriptomic dissection of the rice – Burkholderia glumae interaction

BackgroundBacterial panicle blight caused by the bacterium Burkholderia glumae is an emerging disease of rice in the United States. Not much is known about this disease, the disease cycle or any source of disease resistance. To understand the interaction between rice and Burkholderia glumae, we used transcriptomics via next-generation sequencing (RNA-Seq) and bioinformatics to identify differentially expressed transcripts between resistant and susceptible interactions and formulate a model for rice resistance to the disease.ResultsUsing inoculated young seedlings as sample tissues, we identified unique transcripts involved with resistance to bacterial panicle blight, including a PIF-like ORF1 and verified differential expression of some selected genes using qRT-PCR. These transcripts, which include resistance genes of the NBS-LRR type, kinases, transcription factors, transporters and expressed proteins with functions that are not known, have not been reported in other pathosystems including rice blast or bacterial blight. Further, functional annotation analysis reveals enrichment of defense response and programmed cell death (biological processes); ATP and protein binding (molecular functions); and mitochondrion-related (cell component) transcripts in the resistant interaction.ConclusionTaken together, we formulated a model for rice resistance to bacterial panicle blight that involves an activation of previously unknown resistance genes and their activation partners upon challenge with B. glumae. Other interesting findings are that 1) though these resistance transcripts were up-regulated upon inoculation in the resistant interaction, some of them were already expressed in the water-inoculated control from the resistant genotype, but not in the water- and bacterium-inoculated samples from the susceptible genotype; 2) rice may have co-opted an ORF that was previously a part of a transposable element to aid in the resistance mechanism; and 3) resistance may have existed immediately prior to rice domestication.

Discovering relationships among dispersed repeats using spatial association rule mining

Address: 1Institute for Digital Biology, Mississippi State University, Mississippi State, MS 39762, USA, 2Department of Computer Science and Engineering, Mississippi State University, Mississippi State, MS 39762, USA, 3Mississippi Genome Exploration Laboratory, Mississippi State University, Mississippi State, MS 39762, USA and 4Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762, USA