Mango: combining and analyzing heterogeneous biological networks.

BACKGROUND: Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing software for network analysis has limited scalability to large data sets or is only accessible to software developers as libraries. In addition, the polymorphic nature of the data sets requires a more standardized method for integration and exploration. RESULTS: Mango facilitates large network analyses with its Graph Exploration Language, automatic graph attribute handling, and real-time 3-dimensional visualization. On a personal computer Mango can load, merge, and analyze networks with millions of links and can connect to online databases to fetch and merge biological pathways. CONCLUSIONS: Mango is written in C++ and runs on Mac OS, Windows, and Linux. The stand-alone distributions, including the Graph Exploration Language integrated development environment, are freely available for download from http://www.complex.iastate.edu/download/Mango. The Mango User Guide listing all features can be found at http://www.gitbook.com/book/j23414/mango-user-guide.

Thermodynamically optimal whole-genome tiling microarray design and validation.

BACKGROUND: Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. FINDINGS: Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. CONCLUSIONS: This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

Rational Design of High-Number dsDNA Fragments Based on Thermodynamics for the Construction of Full-Length Genes in a Single Reaction.

Gene synthesis is frequently used in modern molecular biology research either to create novel genes or to obtain natural genes when the synthesis approach is more flexible and reliable than cloning. DNA chemical synthesis has limits on both its length and yield, thus full-length genes have to be hierarchically constructed from synthesized DNA fragments. Gibson Assembly and its derivatives are the simplest methods to assemble multiple double-stranded DNA fragments. Currently, up to 12 dsDNA fragments can be assembled at once with Gibson Assembly according to its vendor. In practice, the number of dsDNA fragments that can be assembled in a single reaction are much lower. We have developed a rational design method for gene construction that allows high-number dsDNA fragments to be assembled into full-length genes in a single reaction. Using this new design method and a modified version of the Gibson Assembly protocol, we have assembled 3 different genes from up to 45 dsDNA fragments at once. Our design method uses the thermodynamic analysis software Picky that identifies all unique junctions in a gene where consecutive DNA fragments are specifically made to connect to each other. Our novel method is generally applicable to most gene sequences, and can improve both the efficiency and cost of gene assembly.

Combinatorial RNA Interference Therapy Prevents Selection of Pre-existing HBV Variants in Human Liver Chimeric Mice.

Selection of escape mutants with mutations within the target sequence could abolish the antiviral RNA interference activity. Here, we investigated the impact of a pre-existing shRNA-resistant HBV variant on the efficacy of shRNA therapy. We previously identified a highly potent shRNA, S1, which, when delivered by an adeno-associated viral vector, effectively inhibits HBV replication in HBV transgenic mice. We applied the "PICKY" software to systemically screen the HBV genome, then used hydrodynamic transfection and HBV transgenic mice to identify additional six highly potent shRNAs. Human liver chimeric mice were infected with a mixture of wild-type and T472C HBV, a S1-resistant HBV variant, and then treated with a single or combined shRNAs. The presence of T472C mutant compromised the therapeutic efficacy of S1 and resulted in replacement of serum wild-type HBV by T472C HBV. In contrast, combinatorial therapy using S1 and P28, one of six potent shRNAs, markedly reduced titers for both wild-type and T472C HBV. Interestingly, treatment with P28 alone led to the emergence of escape mutants with mutations in the P28 target region. Our results demonstrate that combinatorial RNAi therapy can minimize the escape of resistant viral mutants in chronic HBV patients.

Molecular and cellular characterization of a zebrafish optic pathway tumor line implicates glia-derived progenitors in tumorigenesis.

In this study we describe the molecular and cellular characterization of a zebrafish mutant that develops tumors in the optic pathway. Heterozygous Tg(flk1:RFP)is18 transgenic adults develop tumors of the retina, optic nerve and optic tract. Molecular and genetic mapping demonstrate the tumor phenotype is linked to a high copy number transgene array integrated in the lincRNA gene lincRNAis18/Zv9_00007276 on chromosome 3. TALENs were used to isolate a 147 kb deletion allele that removes exons 2-5 of the lincRNAis18 gene. Deletion allele homozygotes are viable and do not develop tumors, indicating loss of function of the lincRNAis18 locus is not the trigger for tumor onset. Optic pathway tumors in the Tg(flk1:RFP)is18 mutant occur with a penetrance of 80-100% by 1 year of age. The retinal tumors are highly vascularized and composed of rosettes of various sizes embedded in a fibrous matrix. Immunohistochemical analysis showed increased expression of the glial markers GFAP and BLBP throughout retinal tumors and in dysplastic optic nerve. We performed transcriptome analysis of pre-tumorous retina and retinal tumor tissue and found changes in gene expression signatures of radial glia and astrocytes (slc1a3), activated glia (atf3, blbp, apoeb), proliferating neural progenitors (foxd3, nestin, cdh2, her9/hes1), and glioma markers (S100ß, vim). The transcriptome also revealed activation of cAMP, Stat3 and Wnt signal transduction pathways. qRT-PCR confirmed >10-fold overexpression of the Wnt pathway components hbegfa, ascl1a, and insm1a. Together the data indicate Müller glia and/or astrocyte-derived progenitors could contribute to the zebrafish Tg(flk1:RFP)is18 optic pathway tumors.

MicroRNA-target binding structures mimic microRNA duplex structures in humans.

Traditionally, researchers match a microRNA guide strand to mRNA sequences using sequence comparisons to predict its potential target genes. However, many of the predictions can be false positives due to limitations in sequence comparison alone. In this work, we consider the association of two related RNA structures that share a common guide strand: the microRNA duplex and the microRNA-target binding structure. We have analyzed thousands of such structure pairs and found many of them share high structural similarity. Therefore, we conclude that when predicting microRNA target genes, considering just the microRNA guide strand matches to gene sequences may not be sufficient--the microRNA duplex structure formed by the guide strand and its companion passenger strand must also be considered. We have developed software to translate RNA binding structure into encoded representations, and we have also created novel automatic comparison methods utilizing such encoded representations to determine RNA structure similarity. Our software and methods can be utilized in the other RNA secondary structure comparisons as well.

Holocarboxylase synthetase 1 physically interacts with histone h3 in Arabidopsis.

Biotin is a water-soluble vitamin required by all organisms, but only synthesized by plants and some bacterial and fungal species. As a cofactor, biotin is responsible for carbon dioxide transfer in all biotin-dependent carboxylases, including acetyl-CoA carboxylase, methylcrotonyl-CoA carboxylase, and pyruvate carboxylase. Adding biotin to carboxylases is catalyzed by the enzyme holocarboxylase synthetase (HCS). Biotin is also involved in gene regulation, and there is some indication that histones can be biotinylated in humans. Histone proteins and most histone modifications are highly conserved among eukaryotes. HCS1 is the only functional biotin ligase in Arabidopsis and has a high homology with human HCS. Therefore, we hypothesized that HCS1 also biotinylates histone proteins in Arabidopsis. A comparison of the catalytic domain of HCS proteins was performed among eukaryotes, prokaryotes, and archaea, and this domain is highly conserved across the selected organisms. Biotinylated histones could not be identified in vivo by using avidin precipitation or two-dimensional gel analysis. However, HCS1 physically interacts with Arabidopsis histone H3 in vitro, indicating the possibility of the role of this enzyme in the regulation of gene expression.

Whole-genome thermodynamic analysis reduces siRNA off-target effects.

Small interfering RNAs (siRNAs) are important tools for knocking down targeted genes, and have been widely applied to biological and biomedical research. To design siRNAs, two important aspects must be considered: the potency in knocking down target genes and the off-target effect on any nontarget genes. Although many studies have produced useful tools to design potent siRNAs, off-target prevention has mostly been delegated to sequence-level alignment tools such as BLAST. We hypothesize that whole-genome thermodynamic analysis can identify potential off-targets with higher precision and help us avoid siRNAs that may have strong off-target effects. To validate this hypothesis, two siRNA sets were designed to target three human genes IDH1, ITPR2 and TRIM28. They were selected from the output of two popular siRNA design tools, siDirect and siDesign. Both siRNA design tools have incorporated sequence-level screening to avoid off-targets, thus their output is believed to be optimal. However, one of the sets we tested has off-target genes predicted by Picky, a whole-genome thermodynamic analysis tool. Picky can identify off-target genes that may hybridize to a siRNA within a user-specified melting temperature range. Our experiments validated that some off-target genes predicted by Picky can indeed be inhibited by siRNAs. Similar experiments were performed using commercially available siRNAs and a few off-target genes were also found to be inhibited as predicted by Picky. In summary, we demonstrate that whole-genome thermodynamic analysis can identify off-target genes that are missed in sequence-level screening. Because Picky prediction is deterministic according to thermodynamics, if a siRNA candidate has no Picky predicted off-targets, it is unlikely to cause off-target effects. Therefore, we recommend including Picky as an additional screening step in siRNA design.

Shared probe design and existing microarray reanalysis using PICKY.

BACKGROUND: Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. RESULTS: PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. CONCLUSIONS: Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

Direct calibration of PICKY-designed microarrays.

BACKGROUND: Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. RESULTS: Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. CONCLUSION: PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

A two-genome microarray for the rice pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola and its use in the discovery of a difference in their regulation of hrp genes.

BACKGROUND: Xanthomonas oryzae pv. oryzae (Xoo) and X. oryzae pv. oryzicola (Xoc) are bacterial pathogens of the worldwide staple and grass model, rice. Xoo and Xoc are closely related but Xoo invades rice vascular tissue to cause bacterial leaf blight, a serious disease of rice in many parts of the world, and Xoc colonizes the mesophyll parenchyma to cause bacterial leaf streak, a disease of emerging importance. Both pathogens depend on hrp genes for type III secretion to infect their host. We constructed a 50-70 mer oligonucleotide microarray based on available genome data for Xoo and Xoc and compared gene expression in Xoo strains PXO99A and Xoc strain BLS256 grown in the rich medium PSB vs. XOM2, a minimal medium previously reported to induce hrp genes in Xoo strain T7174. RESULTS: Three biological replicates of the microarray experiment to compare global gene expression in representative strains of Xoo and Xoc grown in PSB vs. XOM2 were carried out. The non-specific error rate and the correlation coefficients across biological replicates and among duplicate spots revealed that the microarray data were robust. 247 genes of Xoo and 39 genes of Xoc were differentially expressed in the two media with a false discovery rate of 5% and with a minimum fold-change of 1.75. Semi-quantitative-RT-PCR assays confirmed differential expression of each of 16 genes each for Xoo and Xoc selected for validation. The differentially expressed genes represent 17 functional categories. CONCLUSION: We describe here the construction and validation of a two-genome microarray for the two pathovars of X. oryzae. Microarray analysis revealed that using representative strains, a greater number of Xoo genes than Xoc genes are differentially expressed in XOM2 relative to PSB, and that these include hrp genes and other genes important in interactions with rice. An exception was the rax genes, which are required for production of the host resistance elicitor AvrXa21, and which were expressed constitutively in both pathovars.

Nearly identical paralogs: implications for maize (Zea mays L.) genome evolution.

As an ancient segmental tetraploid, the maize (Zea mays L.) genome contains large numbers of paralogs that are expected to have diverged by a minimum of 10% over time. Nearly identical paralogs (NIPs) are defined as paralogous genes that exhibit > or = 98% identity. Sequence analyses of the "gene space" of the maize inbred line B73 genome, coupled with wet lab validation, have revealed that, conservatively, at least approximately 1% of maize genes have a NIP, a rate substantially higher than that in Arabidopsis. In most instances, both members of maize NIP pairs are expressed and are therefore at least potentially functional. Of evolutionary significance, members of many NIP families also exhibit differential expression. The finding that some families of maize NIPs are closely linked genetically while others are genetically unlinked is consistent with multiple modes of origin. NIPs provide a mechanism for the maize genome to circumvent the inherent limitation that diploid genomes can carry at most two "alleles" per "locus." As such, NIPs may have played important roles during the evolution and domestication of maize and may contribute to the success of long-term selection experiments in this important crop species.

GRAMA: genetic mapping analysis of temperature gradient capillary electrophoresis data.

Temperature gradient capillary electrophoresis (TGCE) is a high-throughput method to detect segregating single nucleotide polymorphisms and InDel polymorphisms in genetic mapping populations. Existing software that analyzes TGCE data was, however, designed for mutation analysis rather than genetic mapping. Genetic recombinant analysis and mapping assistant (GRAMA) is a new tool that automates TGCE data analysis for the purpose of genetic mapping. Data from multiple TGCE runs are analyzed, integrated, and displayed in an intuitive visual format. GRAMA includes an algorithm to detect peaks in electropherograms and can automatically compare its peak calls with those produced by another software package. Consequently, GRAMA provides highly accurate results with a low false positive rate of 5.9% and an even lower false negative rate of 1.3%. Because of its accuracy and intuitive interface, GRAMA boosts user productivity more than twofold relative to previous manual methods of scoring TGCE data. GRAMA is written in Java and is freely available at http://www.complex.iastate.edu .

VECT: an automatic visual Perl programming tool for nonprogrammers.

Modern high-throughput biological research produces enormous amount of data that must be processed by computers, but many biologists dealing with these data are not professional programmers. Despite increased awareness of interdisciplinary training in bioinformatics, many biologists still find it difficult to create their own computational solutions. VECT, the Visual Extraction and Conversion Tool, has been developed to assist nonprogrammers to create simple bioinformatics without having to master a programming language. VECT provides a unified graphical user interface for data extraction, data conversion, output composition, and Perl code generation. Programming using VECT is achieved by visually performing the desired data extraction, conversion, and output composition tasks using some sample user data. These tasks are then compiled by VECT into an executable Perl program, which can be saved for later use and can carry out the same computation independently of VECT. VECT is released under the GNU General Public License and is freely available for all major computing platforms including Macintosh OS X, Linux, and Microsoft Windows at www.complex.iastate.edu.

Picky: oligo microarray design for large genomes.

MOTIVATION: Many large genomes are getting sequenced nowadays. Biologists are eager to start microarray analysis taking advantage of all known genes of a species, but existing microarray design tools were very inefficient for large genomes. Also, many existing tools operate in a batch mode that does not assure best designs. RESULTS: Picky is an efficient oligo microarray design tool for large genomes. Picky integrates novel computer science techniques and the best known nearest-neighbor parameters to quickly identify sequence similarities and estimate their hybridization properties. Oligos designed by Picky are computationally optimized to guarantee the best specificity, sensitivity and uniformity under the given design constrains. Picky can be used to design arrays for whole genomes, or for only a subset of genes. The latter can still be screened against a whole genome to attain the same quality as a whole genome array, thereby permitting low budget, pathway-specific experiments to be conducted with large genomes. Picky is the fastest oligo array design tool currently available to the public, requiring only a few hours to process large gene sets from rice, maize or human.

LUCY2: an interactive DNA sequence quality trimming and vector removal tool.

UNLABELLED: Lucy2 is a raw DNA sequence trimming and visualization tool based on the popular command-line Lucy1. Users can change parameters, trim multiple sequences and visualize the results within an integrated, easy-to-use graphical user interface. Lucy2 is designed specifically for non-programmers to use, and is currently available on Windows, Linux and MacOS X. Source code is also available for porting to the other platforms. AVAILABILITY: Lucy2 is distributed under the GNU General Public License and can be downloaded from www.complex.iastate.edu

Efficient combination of multiple word models for improved sequence comparison.

MOTIVATION: Studies of efficient and sensitive sequence comparison methods are driven by a need to find homologous regions of weak similarity between large genomes. RESULTS: We describe an improved method for finding similar regions between two sets of DNA sequences. The new method generalizes existing methods by locating word matches between sequences under two or more word models and extending word matches into high-scoring segment pairs (HSPs). The method is implemented as a computer program named DDS2. Experimental results show that DDS2 can find more HSPs by using several word models than by using one word model. AVAILABILITY: The DDS2 program is freely available for academic use in binary code form at http://bioinformatics.iastate.edu/aat/align/align.html and in source code form from the corresponding author.