Telomeres, the ends of linear chromosomes, are composed of simple tandem repeats which are usually G·C rich. Telomeres are essential for chromosome stability, organizing the nuclear architecture and ensuring complete replication of the chromosomal terminus. To understand how telomeres carry out these fundamental cellular roles, one must understand the structural and dynamic properties of telomeric repeat sequences. Structural and genetic approaches were taken to learn more about telomeric nucleic acids;The structural portion of my research concerned an unusual DNA structure formed by the C-rich strand of telomeric DNA. Telomeric C-strand sequences form non-Watson-Crick structures in supercoiled plasmids at low pH. Absorbance thermal denaturation, chemical modification and non-denaturing gel electrophoresis showed that telomeric C-strand oligonucleotides form stable structures at low pH. H1[superscript]'-H1[superscript]' nuclear Overhauser effects indicated that these structures were four-stranded. In addition, these four-stranded C-structures were shown to mediate recognition and binding of identical nucleic acid sequences. Thus, a novel nucleic acid dimerization motif was discovered;The genetic portion of my research concerned analysis of a Tetrahymena mutant with short telomeres. This mutant was heterozygous for a telomerase RNA mutation. Telomerase is a ribonucleoprotein that uses its RNA component as a template for addition of telomeric repeats to chromosome termini. Therefore, telomerase is involved in telomere length regulation, a process that has been implicated in both aging and cancer. The mutant telomerase RNA gene caused telomere shortening when introduced into wildtype cells, and thus identifies a functionally important domain of the telomerase RNA. Although mutant telomerase activity was indistinguishable from wildtype activity in vitro, cells expressing high levels of the mutant telomerase RNA exhibited lethal phenotypes that were due to the presence of very short telomeres.

The G-quadruplex (G4) elements comprise a class of nucleic acid structures formed by stacking of guanine base quartets in a quadruple helix. This G4 DNA can form within or across single-stranded DNA molecules and is mutually exclusive with duplex B-form DNA. The reversibility and structural diversity of G4s make them highly versatile genetic structures, as demonstrated by their roles in various functions including telomere metabolism, genome maintenance, immunoglobulin gene diversification, transcription, and translation. Sequence motifs capable of forming G4 DNA are typically located in telomere repeat DNA and other non-telomeric genomic loci. To investigate their potential roles in a large-genome model plant species, we computationally identified 149,988 non-telomeric G4 motifs in maize (Zea mays L., B73 AGPv2), 29% of which were in non-repetitive genomic regions. G4 motif hotspots exhibited non-random enrichment in genes at two locations on the antisense strand, one in the 5′ UTR and the other at the 5′ end of the first intron. Several genic G4 motifs were shown to adopt sequence-specific and potassium-dependent G4 DNA structures in vitro. The G4 motifs were prevalent in key regulatory genes associated with hypoxia (group VII ERFs), oxidative stress (DJ-1/GATase1), and energy status (AMPK/SnRK) pathways. They also showed statistical enrichment for genes in metabolic pathways that function in glycolysis, sugar degradation, inositol metabolism, and base excision repair. Collectively, the maize G4 motifs may represent conditional regulatory elements that can aid in energy status gene responses. Such a network of elements could provide a mechanistic basis for linking energy status signals to gene regulation in maize, a model genetic system and major world crop species for feed, food, and fuel.

Hypericum perforatum (Hp) is commonly known for its antiviral, antidepressant, and cytotoxic properties, but traditionally Hp was also used to treat inflammation. In this study, the anti-inflammatory activity and cytotoxicity of different Hp extractions and accessions and constituents present within Hp extracts were characterized. In contrast to the antiviral activity of Hp, the anti-inflammatory activity observed with all Hp extracts was light-independent. When pure constituents were tested, the flavonoids, amentoflavone, hyperforin, and light-activated pseudohypericin, displayed anti-inflammatory activity, albeit at concentrations generally higher than the amount present in the Hp extracts. Constituents that were present in the Hp extracts at concentrations that inhibited the production of prostaglandin E₂ (PGE₂) were pseudohypericin and hyperforin, suggesting that they are the primary anti-inflammatory constituents along with the flavonoids, and perhaps the interactions of these constituents and other unidentified compounds are important for the anti-inflammatory activity of the Hp extracts.

Bacterial leaf streak of rice, caused by Xanthomonas oryzae pv. oryzicola (Xoc) is an increasingly important yield constraint in this staple crop. A mesophyll colonizer, Xoc differs from X. oryzae pv. oryzae (Xoo), which invades xylem to cause bacterial blight of rice. Both produce multiple distinct TAL effectors, type III-delivered proteins that transactivate effector-specific host genes. A TAL effector finds its target(s) via a partially degenerate code whereby the modular effector amino acid sequence identifies nucleotide sequences to which the protein binds. Virulence contributions of some Xoo TAL effectors have been shown, and their relevant targets, susceptibility (S) genes, identified, but the role of TAL effectors in leaf streak is uncharacterized. We used host transcript profiling to compare leaf streak to blight and to probe functions of Xoc TAL effectors. We found that Xoc and Xoo induce almost completely different host transcriptional changes. Roughly one in three genes upregulated by the pathogens is preceded by a candidate TAL effector binding element. Experimental analysis of the 44 such genes predicted to be Xoc TAL effector targets verified nearly half, and identified most others as false predictions. None of the Xoc targets is a known bacterial blight S gene. Mutational analysis revealed that Tal2g, which activates two genes, contributes to lesion expansion and bacterial exudation. Use of designer TAL effectors discriminated a sulfate transporter gene as the S gene. Across all targets, basal expression tended to be higher than genome-average, and induction moderate. Finally, machine learning applied to real vs. falsely predicted targets yielded a classifier that recalled 92% of the real targets with 88% precision, providing a tool for better target prediction in the future. Our study expands the number of known TAL effector targets, identifies a new class of S gene, and improves our ability to predict functional targeting.

Background

The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach.

Results

We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N > 2 groups.

Conclusions

The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies.

Methods to automatically integrate sequence information with physical and genetic maps are scarce. The Locus Lookup tool enables researchers to define windows of genomic sequence likely to contain loci of interest where only genetic or physical mapping associations are reported. Using the Locus Lookup tool, researchers will be able to locate specific genes more efficiently that will ultimately help them develop a better maize plant. With the availability of the well-documented source code, the tool can be easily adapted to other biological systems.

Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0;https://boglab.plp.iastate.edu/) that enables design of custom TAL effector repeat arrays for desired targets and prediction of TAL effector binding sites, ranked by likelihood, in a genome, promoterome or other sequence of interest. Search parameters can be set by the user to work with any TAL effector or TAL effector nuclease architecture. Applications range from designing highly specific DNA targeting tools and identifying potential off-target sites to predicting effector targets important in plant disease.

Programmed cell death (PCD) is a biological process that shapes human development. Yet, cancer cells are insusceptible to this process leading to the proliferation of tumors. Research on PCD can produce cancer therapies which increase tumor susceptibility to PCD for tumor eradication.

The exact mechanisms of PCD are currently unknown. My research aims to uncover the role of the gene outsiders in the scheme of PCD in Drosophila melanogaster (fruit fly) embryos. During embryogenesis, Drosophila germ cells travel across the embryo to the gonads for proper development. Mutants with the outsiders gene respond less to PCD resulting in the correct number of germ cells in the gonads, but an excess outlying the peripherals.

To decipher the mechanisms involved in PCD, outsiders will be excised from the genome using the CRISPR-Cas9 genetic engineering technique. This knock-out phenotype will provide insight on the network of PCD for human health applications.

Background

Rab GTPases are important regulators of endomembrane trafficking, regulating exocytosis, endocytosis and membrane recycling. Many Rab-like proteins exist in plants, but only a subset have been functionally characterized.

Results

Here we report that AtRabD2b and AtRabD2c play important roles in pollen development, germination and tube elongation. AtrabD2b and AtrabD2c single mutants have no obvious morphological changes compared with wild-type plants across a variety of growth conditions. An AtrabD2b/2c double mutant is also indistinguishable from wild-type plants during vegetative growth; however its siliques are shorter than those in wild-type plants. Compared with wild-type plants, AtrabD2b/2c mutants produce deformed pollen with swollen and branched pollen tube tips. The shorter siliques in the AtrabD2b/2c double mutant were found to be primarily due to the pollen defects. AtRabD2b and AtRabD2c have different but overlapping expression patterns, and they are both highly expressed in pollen. Both AtRabD2b and AtRabD2c protein localize to Golgi bodies.

Conclusions

These findings support a partially redundant role for AtRabD2b and AtRabD2c in vesicle trafficking during pollen tube growth that cannot be fulfilled by the remaining AtRabD family members.

Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks. In this paper, we present an approach to biological sequence labeling that takes into account the global similarity between biological sequences. Our approach combines unsupervised and supervised learning techniques. Given a set of sequences and a similarity measure defined on pairs of sequences, we learn a mixture of experts model by using spectral clustering to learn the hierarchical structure of the model and by using bayesian approaches to combine the predictions of the experts. We evaluate our approach on two important biological sequence labeling problems: RNA-protein and DNA-protein interface prediction problems. The results of our experiments show that global sequence similarity can be exploited to improve the performance of classifiers trained to label biological sequence data.