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Search Results: 1 - 10 of 159318 matches for " Charles H. Cannon "
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Evidence for a Trade-Off Strategy in Stone Oak (Lithocarpus) Seeds between Physical and Chemical Defense Highlights Fiber as an Important Antifeedant
Xi Chen, Charles H. Cannon, Nancy Lou Conklin-Brittan
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032890
Abstract: Trees in the beech or oak family (Fagaceae) have a mutualistic relationship with scatter-hoarding rodents. Rodents obtain nutrients and energy by consuming seeds, while providing seed dispersal for the tree by allowing some cached seeds to germinate. Seed predation and caching behavior of rodents is primarily affected by seed size, mechanical protection, macronutrient content, and chemical antifeedants. To enhance seed dispersal, trees must optimize trade-offs in investment between macronutrients and antifeedants. Here, we examine this important chemical balance in the seeds of tropical stone oak species with two substantially different fruit morphologies. These two distinct fruit morphologies in Lithocarpus differ in the degree of mechanical protection of the seed. For ‘acorn’ fruit, a thin exocarp forms a shell around the seed while for ‘enclosed receptacle’ (ER) fruit, the seed is embedded in a woody receptacle. We compared the chemical composition of numerous macronutrient and antifeedant in seeds from several Lithocarpus species, focusing on two pairs of sympatric species with different fruit morphologies. We found that macronutrients, particularly total non-structural carbohydrate, was more concentrated in seeds of ER fruits while antifeedants, primarily fibers, were more concentrated in seeds of acorn fruits. The trade-off in these two major chemical components was more evident between the two sympatric lowland species than between two highland species. Surprisingly, no significant difference in overall tannin concentrations in the seeds was observed between the two fruit morphologies. Instead, the major trade-off between macronutrients and antifeedants involved indigestible fibers. Future studies of this complex mutualism should carefully consider the role of indigestible fibers in the foraging behavior of scatter-hoarding rodents.
Identification of lignin genes and regulatory sequences involved in secondary cell wall formation in Acacia auriculiformis and Acacia mangium via de novo transcriptome sequencing
Melissa ML Wong, Charles H Cannon, Ratnam Wickneswari
BMC Genomics , 2011, DOI: 10.1186/1471-2164-12-342
Abstract: We sequenced transcriptomes of A. auriculiformis and A. mangium from non-normalized cDNA libraries synthesized from pooled young stem and inner bark tissues using paired-end libraries and a single lane of an Illumina GAII machine. De novo assembly produced a total of 42,217 and 35,759 contigs with an average length of 496 bp and 498 bp for A. auriculiformis and A. mangium respectively. The assemblies of A. auriculiformis and A. mangium had a total length of 21,022,649 bp and 17,838,260 bp, respectively, with the largest contig 15,262 bp long. We detected all ten monolignol biosynthetic genes using Blastx and further analysis revealed 18 lignin isoforms for each species. We also identified five contigs homologous to R2R3-MYB proteins in other plant species that are involved in transcriptional regulation of secondary cell wall formation and lignin deposition. We searched the contigs against public microRNA database and predicted the stem-loop structures of six highly conserved microRNA families (miR319, miR396, miR160, miR172, miR162 and miR168) and one legume-specific family (miR2086). Three microRNA target genes were predicted to be involved in wood formation and flavonoid biosynthesis. By using the assemblies as a reference, we discovered 16,648 and 9,335 high quality putative Single Nucleotide Polymorphisms (SNPs) in the transcriptomes of A. auriculiformis and A. mangium, respectively, thus yielding useful markers for population genetics studies and marker-assisted selection.We have produced the first comprehensive transcriptome-wide analysis in A. auriculiformis and A. mangium using de novo assembly techniques. Our high quality and comprehensive assemblies allowed the identification of many genes in the lignin biosynthesis and secondary cell wall formation in Acacia hybrids. Our results demonstrated that Next Generation Sequencing is a cost-effective method for gene discovery, identification of regulatory sequences, and informative markers in a non-model plant.Ne
Development of high-throughput SNP-based genotyping in Acacia auriculiformis x A. mangium hybrids using short-read transcriptome data
Wong Melissa ML,Cannon Charles H,Wickneswari Ratnam
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-726
Abstract: Background Next Generation Sequencing has provided comprehensive, affordable and high-throughput DNA sequences for Single Nucleotide Polymorphism (SNP) discovery in Acacia auriculiformis and Acacia mangium. Like other non-model species, SNP detection and genotyping in Acacia are challenging due to lack of genome sequences. The main objective of this study is to develop the first high-throughput SNP genotyping assay for linkage map construction of A. auriculiformis x A. mangium hybrids. Results We identified a total of 37,786 putative SNPs by aligning short read transcriptome data from four parents of two Acacia hybrid mapping populations using Bowtie against 7,839 de novo transcriptome contigs. Given a set of 10 validated SNPs from two lignin genes, our in silico SNP detection approach is highly accurate (100%) compared to the traditional in vitro approach (44%). Further validation of 96 SNPs using Illumina GoldenGate Assay gave an overall assay success rate of 89.6% and conversion rate of 37.5%. We explored possible factors lowering assay success rate by predicting exon-intron boundaries and paralogous genes of Acacia contigs using Medicago truncatula genome as reference. This assessment revealed that presence of exon-intron boundary is the main cause (50%) of assay failure. Subsequent SNPs filtering and improved assay design resulted in assay success and conversion rate of 92.4% and 57.4%, respectively based on 768 SNPs genotyping. Analysis of clustering patterns revealed that 27.6% of the assays were not reproducible and flanking sequence might play a role in determining cluster compression. In addition, we identified a total of 258 and 319 polymorphic SNPs in A. auriculiformis and A. mangium natural germplasms, respectively. Conclusion We have successfully discovered a large number of SNP markers in A. auriculiformis x A. mangium hybrids using next generation transcriptome sequencing. By using a reference genome from the most closely related species, we converted most SNPs to successful assays. We also demonstrated that Illumina GoldenGate genotyping together with manual clustering can provide high quality genotypes for a non-model species like Acacia. These SNPs markers are not only important for linkage map construction, but will be very useful for hybrid discrimination and genetic diversity assessment of natural germplasms in the future.
Molecular Evolutionary Analysis of the Alfin-Like Protein Family in Arabidopsis lyrata, Arabidopsis thaliana, and Thellungiella halophila
Yu Song, Jie Gao, Fengxi Yang, Chai-Shian Kua, Jingxin Liu, Charles H. Cannon
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0066838
Abstract: In previous studies, the Alfin1 gene, a transcription factor, enhanced salt tolerance in alfalfa, primarily through altering gene expression levels in the root. Here, we examined the molecular evolution of the Alfin-like (AL) proteins in two Arabidopsis species (A. lyrata and A. thaliana) and a salt-tolerant close relative Thellungiella halophila. These AL-like proteins could be divided into four groups and the two known DUF3594 and PHD-finger domains had co-evolved within each group of genes, irrespective of species, due to gene duplication events in the common ancestor of all three species while gene loss was observed only in T. halophila. To detect whether natural selection acted in the evolution of AL genes, we calculated synonymous substitution ratios (dn/ds) and codon usage statistics, finding positive selection operated on four branches and significant differences in biased codon usage in the AL family between T. halophila and A. lyrata or A. thaliana. Distinctively, only the AL7 branch was under positive selection on the PHD-finger domain and the three members on the branch showed the smallest difference when codon bias was evaluated among the seven clusters. Functional analysis based on transgenic overexpression lines and T-DNA insertion mutants indicated that salt-stress-induced AtAL7 could play a negative role in salt tolerance of A. thaliana, suggesting that adaptive evolution occurred in the members of AL gene family.
SparseAssembler: de novo Assembly with the Sparse de Bruijn Graph
Chengxi Ye,Zhanshan Sam Ma,Charles H. Cannon,Mihai Pop,Douglas W. Yu
Computer Science , 2011,
Abstract: de Bruijn graph-based algorithms are one of the two most widely used approaches for de novo genome assembly. A major limitation of this approach is the large computational memory space requirement to construct the de Bruijn graph, which scales with k-mer length and total diversity (N) of unique k-mers in the genome expressed in base pairs or roughly (2k+8)N bits. This limitation is particularly important with large-scale genome analysis and for sequencing centers that simultaneously process multiple genomes. We present a sparse de Bruijn graph structure, based on which we developed SparseAssembler that greatly reduces memory space requirements. The structure also allows us to introduce a novel method for the removal of substitution errors introduced during sequencing. The sparse de Bruijn graph structure skips g intermediate k-mers, therefore reducing the theoretical memory space requirement to ~(2k/g+8)N. We have found that a practical value of g=16 consumes approximately 10% of the memory required by standard de Bruijn graph-based algorithms but yields comparable results. A high error rate could potentially derail the SparseAssembler. Therefore, we developed a sparse de Bruijn graph-based denoising algorithm that can remove more than 99% of substitution errors from datasets with a \leq 2% error rate. Given that substitution error rates for the current generation of sequencers is lower than 1%, our denoising procedure is sufficiently effective to safeguard the performance of our algorithm. Finally, we also introduce a novel Dijkstra-like breadth-first search algorithm for the sparse de Bruijn graph structure to circumvent residual errors and resolve polymorphisms.
SparseAssembler2: Sparse k-mer Graph for Memory Efficient Genome Assembly
Chengxi Ye,Charles H. Cannon,Zhanshan Sam Ma,Douglas W. Yu,Mihai Pop
Computer Science , 2011,
Abstract: The formal version of our work has been published in BMC Bioinformatics and can be found here: http://www.biomedcentral.com/1471-2105/13/S6/S1 Motivation: To tackle the problem of huge memory usage associated with de Bruijn graph-based algorithms, upon which some of the most widely used de novo genome assemblers have been built, we released SparseAssembler1. SparseAssembler1 can save as much as 90% memory consumption in comparison with the state-of-art assemblers, but it requires rounds of denoising to accurately assemble genomes. In this paper, we introduce a new general model for genome assembly that uses only sparse k-mers. The new model replaces the idea of the de Bruijn graph from the beginning, and achieves similar memory efficiency and much better robustness compared with our previous SparseAssembler1. Results: We demonstrate that the decomposition of reads of all overlapping k-mers, which is used in existing de Bruijn graph genome assemblers, is overly cautious. We introduce a sparse k-mer graph structure for saving sparse k-mers, which greatly reduces memory space requirements necessary for de novo genome assembly. In contrast with the de Bruijn graph approach, we devise a simple but powerful strategy, i.e., finding links between the k-mers in the genome and traversing following the links, which can be done by saving only a few k-mers. To implement the strategy, we need to only select some k-mers that may not even be overlapping ones, and build the links between these k-mers indicated by the reads. We can traverse through this sparse k-mer graph to build the contigs, and ultimately complete the genome assembly. Since the new sparse k-mers graph shares almost all advantages of de Bruijn graph, we are able to adapt a Dijkstra-like breadth-first search algorithm to circumvent sequencing errors and resolve polymorphisms.
Inference of Markovian Properties of Molecular Sequences from NGS Data and Applications to Comparative Genomics
Jie Ren,Kai Song,Minghua Deng,Gesine Reinert,Charles H. Cannon,Fengzhu Sun
Quantitative Biology , 2015,
Abstract: Next Generation Sequencing (NGS) technologies generate large amounts of short read data for many different organisms. The fact that NGS reads are generally short makes it challenging to assemble the reads and reconstruct the original genome sequence. For clustering genomes using such NGS data, word-count based alignment-free sequence comparison is a promising approach, but for this approach, the underlying expected word counts are essential. A plausible model for this underlying distribution of word counts is given through modelling the DNA sequence as a Markov chain (MC). For single long sequences, efficient statistics are available to estimate the order of MCs and the transition probability matrix for the sequences. As NGS data do not provide a single long sequence, inference methods on Markovian properties of sequences based on single long sequences cannot be directly used for NGS short read data. Here we derive a normal approximation for such word counts. We also show that the traditional Chi-square statistic has an approximate gamma distribution, using the Lander-Waterman model for physical mapping. We propose several methods to estimate the order of the MC based on NGS reads and evaluate them using simulations. We illustrate the applications of our results by clustering genomic sequences of several vertebrate and tree species based on NGS reads using alignment-free sequence dissimilarity measures. We find that the estimated order of the MC has a considerable effect on the clustering results, and that the clustering results that use a MC of the estimated order give a plausible clustering of the species.
Fuzzy Mating Behavior Enhances Species Coexistence and Delays Extinction in Diverse Communities
Charles Cannon,Manuel Lerdau
Quantitative Biology , 2013,
Abstract: Current theories about mechanisms promoting species co-existence in diverse communities assume that species only interact ecologically. Species are treated as discrete evolutionary entities, even though abundant empirical evidence indicates that patterns of gene flow such as selfing and hybridization frequently occur in plant and animal groups. Here, we allow mating behavior to respond to local species composition and abundance in a data-driven meta-community model of species co-existence. While individuals primarily out-cross, they also maintain some small capacity for selfing and hybridization. Mating choice is treated as a 'fuzzy' behavior, determined by an interaction between intrinsic properties affecting mate choice and extrinsic properties of the local community, primarily the density and availability of sympatric inter-fertile species. When mate choice is strongly limited, even low survivorship of selfed offspring (<10%) can prevent extinction of rare species. With increasing mate choice, low hybridization success rates (~20%) maintain community level diversity for substantially longer periods of time. Given the low species densities and high diversity of tropical tree communities, the evolutionary costs of competition among sympatric congeneric species are negligible because direct competition is infrequent. In diverse communities, many species are chronically rare and thus vulnerable to stochastic extinction, which occurs rapidly if species are completely reproductively isolated. By incorporating fuzzy mating behavior into models of species co-existence, a more realistic understanding of the extinction process can be developed. Fuzzy mating strategies, potentially an important mechanism for rare species to escape extinction and gain local adaptations, should be incorporated into forest management strategies.
Reference-Free Comparative Genomics of 174 Chloroplasts
Chai-Shian Kua, Jue Ruan, John Harting, Cheng-Xi Ye, Matthew R. Helmus, Jun Yu, Charles H. Cannon
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0048995
Abstract: Direct analysis of unassembled genomic data could greatly increase the power of short read DNA sequencing technologies and allow comparative genomics of organisms without a completed reference available. Here, we compare 174 chloroplasts by analyzing the taxanomic distribution of short kmers across genomes [1]. We then assemble de novo contigs centered on informative variation. The localized de novo contigs can be separated into two major classes: tip = unique to a single genome and group = shared by a subset of genomes. Prior to assembly, we found that ~18% of the chloroplast was duplicated in the inverted repeat (IR) region across a four-fold difference in genome sizes, from a highly reduced parasitic orchid [2] to a massive algal chloroplast [3], including gnetophytes [4] and cycads [5]. The conservation of this ratio between single copy and duplicated sequence was basal among green plants, independent of photosynthesis and mechanism of genome size change, and different in gymnosperms and lower plants. Major lineages in the angiosperm clade differed in the pattern of shared kmers and de novo contigs. For example, parasitic plants demonstrated an expected accelerated overall rate of evolution, while the hemi-parasitic genomes contained a great deal more novel sequence than holo-parasitic plants, suggesting different mechanisms at different stages of genomic contraction. Additionally, the legumes are diverging more quickly and in different ways than other major families. Small duplicated fragments of the rrn23 genes were deeply conserved among seed plants, including among several species without the IR regions, indicating a crucial functional role of this duplication. Localized de novo assembly of informative kmers greatly reduces the complexity of large comparative analyses by confining the analysis to a small partition of data and genomes relevant to the specific question, allowing direct analysis of next-gen sequence data from previously unstudied genomes and rapid discovery of informative candidate regions.
VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data
Elena S Peterson, Lee Ann McCue, Alexandra C Schrimpe-Rutledge, Jeffrey L Jensen, Hyunjoo Walker, Markus A Kobold, Samantha R Webb, Samuel H Payne, Charles Ansong, Joshua N Adkins, William R Cannon, Bobbie-Jo M Webb-Robertson
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-131
Abstract: VESPA is a desktop Java? application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data.VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php webcite.High throughput (HTP) molecular technologies are at the core of new capabilities to derive genomic-level profiles oforganisms [1,2]. One challenge often not addressed in the context of HTP technologies is the relationship of the analyses to the defined structural annotation of the genome. For example, the accuracy of global bottom-up proteomics is directly dependent upon accurately defined open reading frames (ORFs), because spectra are matched directly to an in silico enzymatic digest of the predicted proteins. Although a well-annotated genome is typically needed to anal
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