Cultivated cotton fiber has undergone transformation from short, coarse fibers found in progenitor wild species to economically important, long, fine fibers grown globally. Morphological transformation requires understanding of development of wild fiber and developmental differences between wild and cultivated fiber.We examined early development of fibers, including abundance and placement on seed surface, nucleus position, presence of vacuoles, and fiber size and shape. Four species were studied using microscopic, morphometric, and statistical methods: Gossypium raimondii (wild D genome), Gossypium herbaceum (cultivated A genome), Gossypium hirsutum (wild tetraploid), and Gossypium hirsutum (cultivated tetraploid). Early fiber development is highly asynchronous in G. raimondii but more synchronous in other taxa. Significant changes associated with domestication include pronounced synchronization of fiber development in G. hirsutum relative to other taxa studied, implicating unconscious selection that shaped early molecular and cellular events, and a delay in some developmental features in fibers of G. herbaceum, including delayed vacuole formation and nuclear migration. Increased fiber cover and synchronized development selection in cultivated cotton may have facilitated both yield and uniformity of the crop. However, for the taxa and developmental timeframe studied, phylogeny is found to play a more important role than domestication in determining early fiber size and shape.

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web.

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.

The effect of the chelator 1,10-phenanthroline on the DNA-binding of 1,25-dihydroxyvitamin D receptor was demonstrated. Increasing concentrations of the chelator, up to 3 mM, decreased receptor binding to DNA-cellulose. This effect was specific for the chelating function because the nonchelating analog, 1,7-phenanthroline, did not inhibit DNA-cellulose binding of the receptor. The cations, Cd[superscript]2+ and Zn[superscript]2+, were able to block chelator-mediated inhibition. These cations were unable to reverse the inhibition unless 1,10-phenanthroline was removed by dialysis;The rat osteosarcoma 17/2.8 cells were shown to express both the cellular retinoic acid binding protein and the nuclear retinoic acid receptor. These two proteins exhibit saturable binding of retinoic acid with estimated equilibrium dissociation constants of 51 nM and 0.95 nM, respectively. The binding of various analogs to the nuclear receptor correlates with their ability to up-regulate the 1,25-dihydroxyvitamin D receptor. Northern blot analysis confirmed that these cells express mRNA for retinoic acid receptors [alpha] and [beta];The concentration of retinoic acid receptor [beta] mRNA was essentially unaffected by retinoic acid treatment. A rapid (2 h) increase in retinoic acid receptor [alpha] mRNA concentration was seen with retinoic acid treatment. This increase reached as high as 5-fold by 24 h. 1,25-Dihydroxyvitamin D[subscript]3 did not affect retinoic acid receptor mRNA concentration. Both 1,25-dihydroxyvitamin D[subscript]3 and parathyroid hormone decreased retinoic acid receptor concentration by 50% after 20 h of treatment. Thyroid hormone slightly increased 1,25-dihydroxyvitamin D receptor concentration, whereas retinoic acid substantially increased this receptor concentration in rat osteosarcoma 17/2.8 cells. The retinoic acid increase in 1,25-Dihydroxyvitamin D receptor concentration was attenuated in the presence of thyroid hormone. This effect of thyroid hormone was specific for retinoic acid because thyroid hormone did not alter the 1,25-Dihydroxyvitamin D[subscript]3-mediated regulation of either the 1,25-Dihydroxyvitamin D or the retinoic acid receptors.

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.

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.

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.

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.

Background

Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need for computational methods for checking consistency of such annotations against independent sources of evidence and detecting potential annotation errors. We show how a machine learning approach designed to automatically predict a protein's Gene Ontology (GO) functional class can be employed to identify potential gene annotation errors.

Results

In a set of 211 previously annotated mouse protein kinases, we found that 201 of the GO annotations returned by AmiGO appear to be inconsistent with the UniProt functions assigned to their human counterparts. In contrast, 97% of the predicted annotations generated using a machine learning approach were consistent with the UniProt annotations of the human counterparts, as well as with available annotations for these mouse protein kinases in the Mouse Kinome database.

Conclusion

We conjecture that most of our predicted annotations are, therefore, correct and suggest that the machine learning approach developed here could be routinely used to detect potential errors in GO annotations generated by high-throughput gene annotation projects.

The cellular responses that allow a cell to survive and adapt to hypoxic stress (low oxygen) are largely conserved. The Hypoxia-Inducible Factor transcription factors (HIFs) are the primary transcription factors mediating responses to hypoxic stress. HIFs are composed of alpha and beta subunits. HIF-α is only stable in hypoxic conditions. The pathway for oxygen-dependent degradation of HIF-α includes a prolyl-hydroxylase (PHD) and the VHL E3 ligase. The Drosophila homlogs of HIF-α, HIF-β, PHD, and VHL are encoded by the similar, tango, fatiga/Hph, and Vhl genes, respectively. Previous studies have demonstrated that similar has roles in Drosophila tracheal development as well as border cell migration. Here I have used the development of germ cells in Drosophila as a tool to study the effects of low oxygen stress, and to explore the potential roles of hypoxic response genes in germ cell development. Utilizing low oxygen culture conditions and loss-of-function mutants I have observed that Drosophila embryogenesis is sensitive to oxygen tension and the zygotic loss of Drosophila HIF-1α is not sufficient to induce primordial germ cell defects. Further examination of the complete loss-of-function of other Drosophila HIF components, such as fatiga, could reveal whether it is the HIF hypoxic response pathway or a HIF independent hypoxia induced pathway that mediates Drosophila primordial germ cell development in wild-type embryos exposed to hypoxic conditions.