Parallel Greedy Triangulation of a Point Set

A greedy triangulation algorithm takes a set of points in the plane and returns a triangulation of the point set. The triangulation is built by adding the smallest line segment between points that does not intersect any line previously in the triangulation. The greedy triangulation is inexpensive computationally and gives an approximation of the minimum-weight triangulation problem, an NP-hard problem, which is computationally expensive. We present serial and parallel implementations of the greedy triangulation using the following approach: once a line is added to the triangulation, all intersecting lines are removed from consideration. This process is repeated until a triangulation is obtained. We present and analyze experimental wall-time data for the serial and parallel implementations. We show that the parallel version has strong and weak scaling properties, and that this algorithm benefits greatly from parallelism

Genetic and molecular analysis of the organellar genomes of cytoplasmically inherited mutants of soybean (Glycine max (L.) Merr)

A genetic analysis of a maternally inherited yellow foliage mutant (cyt-Y(,3)) was conducted. This mutant was characterized by pigment content determinations and by plastid ultrastructure analyses;A molecular analysis of soybean chloroplast DNA (ctDNA) was also conducted. The coding sequences of the genes for the atrazine receptor protein (PS II) and for the large subunit of Ribulose-1,5-bisphosphate carboxylase (LS) were located on the physical restriction map of the chloroplast genome;Nuclease activity associated with soybean chloroplasts was identified and was inhibited using high pH and various concentrations of spermidine, disodium ethylenediamine tetraacetic acid, and adenosine triphosphate. A ctDNA-enrichment procedure was developed and used to isolate ctDNA from cytoplasmically inherited mutants, cultivars, and Plant Introductions. Mitochondrial DNA (mtDNA) and ctDNA was isolated from yellow cotyledon lines (cyt-Y(,1)) and green cotyledon lines (cyt-G(,1)) and from a yellow foliage line (cyt-Y(,2)) and a normal green foliage line (cyt-G(,2)). Restriction fragment polymorphisms (RFP) were seen between organelle DNAs of yellow and green cotyledon lines but were not seen between yellow and green foliage lines. Five endonucleases were used to screen selections of the soybean germplasm collection for ctDNA diversity. The enzymes Cla I and Eco R I unveiled RFPs. Five plastome types were seen and intraspecific ctDNA variation was identified. Diverse cytoplasms can now be incorporated into soybean breeding programs

Identification and analysis of gene families from the duplicated genome of soybean using EST sequences

BACKGROUND: Large scale gene analysis of most organisms is hampered by incomplete genomic sequences. In many organisms, such as soybean, the best source of sequence information is the existence of expressed sequence tag (EST) libraries. Soybean has a large (1115 Mbp) genome that has yet to be fully sequenced. However it does have the 6th largest EST collection comprised of ESTs from a variety of soybean genotypes. Many EST libraries were constructed from RNA extracted from various genetic backgrounds, thus gene identification from these sources is complicated by the existence of both gene and allele sequence differences. We used the ESTminer suite of programs to identify potential soybean gene transcripts from a single genetic background allowing us to observe functional classifications between gene families as well as structural differences between genes and gene paralogs within families. The identification of potential gene sequences (pHaps) from soybean allows us to begin to get a picture of the genomic history of the organism as well as begin to observe the evolutionary fates of gene copies in this highly duplicated genome. RESULTS: We identified approximately 45,000 potential gene sequences (pHaps) from EST sequences of Williams/Williams82, an inbred genotype of soybean (Glycine max L. Merr.) using a redundancy criterion to identify reproducible sequence differences between related genes within gene families. Analysis of these sequences revealed single base substitutions and single base indels are the most frequently observed form of sequence variation between genes within families in the dataset. Genomic sequencing of selected loci indicate that intron-like intervening sequences are numerous and are approximately 220 bp in length. Functional annotation of gene sequences indicate functional classifications are not randomly distributed among gene families containing few or many genes. CONCLUSION: The predominance of single nucleotide insertion/deletions and substitution events between genes within families (individual genes and gene paralogs) is consistent with a model of gene amplification followed by single base random mutational events expected under the classical model of duplicated gene evolution. Molecular functions of small and large gene families appear to be non-randomly distributed possibly indicating a difference in retention of duplicates or local expansion

Biotechnology for the Control of Soybean Diseases

Approximately 80% of the total soybean production in the United States occurs in the North Central States. Ten of the 12 most productive states are located in this region (Doupnik 1993). During a three-year period (1989- 1991) soybean production and disease loss for the North Central States was estimated at 13.17% or 236,730,000 bu (Doupnik 1993). At the current price of$7.00/bu that level of loss corresponds to a loss to the North Central States soybean growers of$552,370,000 per year! Soybean cyst nematode and Phytophthora root and stem rot are two major diseases of soybeans and often cause the greatest loss in production. Brown stem rot and the seed disease caused by Soybean Mosaic Virus also cause profit losses to the growers. Some soybean plants contain natural resistance or tolerance to these diseases which breeders have taken advantage of in developing new varieties. Biotechnology offers an array of tools that may help to control soybean diseases. Biotechnology can help us to clone the genes that provide natural resistance or tolerance and can help us to understand how these genes work. Once we understand how the resistance mechanisms work we can use these new technologies to engineer novel forms of resistance into the soybean. A team of researchers at Iowa State University have joined together, with collaborators from across the United States, to use molecular biological techniques to develop methods by soybean diseases can be controlled. This team studies the diseases caused by Soybean cyst nematode, Phytopthora root and stem rot, Brown stem rot, and Soybean Mosaic Virus, and attacks the problems of disease control by studying the pathogen as well as the plant. This paper will discuss some approaches used in the efforts to clone the genes conferring resistance to the fungal pathogen Phytophthora sojae, the pathogen causing Phytophthora root and stem rot

Gene Expression: Sizing It All Up

Genomic architecture appears to be a largely unexplored component of gene expression. That architecture can be related to chromatin domains, transposable element neighborhoods, epigenetic modifications of the genome, and more. Although surely not the end of the story, we are learning that when it comes to gene expression, size is also important. We have been surprised to find that certain patterns of expression, tissue specific versus constitutive, or high expression versus low expression, are often associated with physical attributes of the gene and genome. Multiple studies have shown an inverse relationship between gene expression patterns and various physical parameters of the genome such as intron size, exon size, intron number, and size of intergenic regions. An increase in expression level and breadth often correlates with a decrease in the size of physical attributes of the gene. Three models have been proposed to explain these relationships. Contradictory results were found in several organisms when expression level and expression breadth were analyzed independently. However, when both factors were combined in a single study a novel relationship was revealed. At low levels of expression, an increase in expression breadth correlated with an increase in genic, intergenic, and intragenic sizes. Contrastingly, at high levels of expression, an increase in expression breadth inversely correlated with the size of the gene. In this article we explore the several hypotheses regarding genome physical parameters and gene expression

Research Notes : Genetic analysis of a chlorophyll deficient, tan-saddle mutant

In the 1961 Uniform Soybean Test II, seeds with a tan-saddle pattern were found among normally yellow-seeded \u27Harosoy\u27 plants. The tan-saddle pattern was found to breed true, and is now designated k2. The Harosoy line from which k2 was derived is designated T239 in the Genetic Type Collection

Intrinsic Mesh Simplification

This paper presents a novel simplification method for removing vertices from an intrinsic triangulation corresponding to extrinsic vertices lying on near-developable (i.e., with limited Gaussian curvature) and general surfaces. We greedily process all intrinsic vertices with an absolute Gaussian curvature below a user selected threshold. For each vertex, we repeatedly perform local intrinsic edge flips until the vertex reaches the desired valence (three for internal vertices or two for boundary vertices) such that removal of the vertex and incident edges can be locally performed in the intrinsic triangulation. Each removed vertex's intrinsic location is tracked via (intrinsic) barycentric coordinates that are updated to reflect changes in the intrinsic triangulation. We demonstrate the robustness and effectiveness of our method on the Thingi10k dataset and analyze the effect of the curvature threshold on the solutions of PDEs

Accessing Soybase and Other Genome Databases Via the Internet

The Internet or World Wide Web is increasingly in the news. It seems to be much like Mark Twain\u27s comment about the weather - everyone talks about the Internet but no one knows much about it. In fact the Internet is full of useful information if one only can find it. This paper (and associated computer demonstration) will first describe some of the genome databases that are accessible via the Internet and then give some strategies for searching the Internet for other types of information

Application of Chromosome Maps to Soybean Improvements

The mention of a trademark or proprietary product does not constitute a guarantee or warranty of the product by the United Sates Department of Agriculture or Iowa State University and does not imply its approval to the exclusion of other products that may be suitable

Meeting Report: Soybean Genomics Assessment and Strategy Workshop

http://www.soybiotechcenter.org/archives/?id=195&id2=12On July 19 - 20, 2005, approximately 50 researchers and administrators with expert knowledge of soybean genomics participated in a workshop in St.Louis, MO, which was hosted by the Soybean Genetics Executive Committee and supported by the United Soybean Board. The workshop began with a series of presentations by experts in the topics discussed below. Each presentation was designed to update the audience on the current status of soybean resources and related genomics technologies. Following the presentations the participants divided into discussion groups to assess the status of soybean genomics, identify needs, and identify milestones to achieve objectives. The discussion groups included the general areas of Functional Genomics A (Transcriptome and Proteome), Functional Genomic B (Reverse Genetics), Physical and Genetic Maps, and Bioinformatics. After each discussion section the entire group reconvened to hear group reports and to further discuss each topic. The following is the report from this Workshop. It represents a consensus of the participants of the Workshop and it is structured to integrate with a White Paper generated in 2003 so that progress can be better monitored over time. The results of this report are consistent with those of a National Science Foundation soybean genomics workshop held in 2004 (St. Louis, MO) and a Cross-Legume workshop also held in 2004 (Santa Fe, NM).National Science Foundatio