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Results for “Functional Genomics”

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At least 811 records · Page 45Linked to original sources
PubMed2000

Targeted terminal deletions as a tool for functional genomics studies in Plasmodium.

We describe a transfection system that induces terminal deletions at specific chromosome ends in malaria parasites using a linear construct containing telomeric repeats at one end and plasmodial sequences able to drive homologous recombination at the other. A site-specific deletion was generated at one extremity of chromosome 5 of Plasmodium berghei, which was stably maintained in the parasite population selected after transfection. The telomeric repeat array introduced with the construct reached the average length observed in natural telomeres of Plasmodium, indicating that in vivo telomere addition occurred at the newly formed extremity. The expression of a mutant dhfr/ts gene conferring pyrimethamine resistance, used as a selectable marker, was not affected by the proximity to the telomeric sequences, either in the presence or absence of drug pressure. In addition, no transcriptional silencing was observed on insertion of the mutant dhfr/ts gene either in subtelomeric or internal positions that are transcriptionally silent in blood-stage parasites. This suggests that the activity of its promoter is not affected by the chromatin organization of the chromosomal context.

Animals↗
PubMed2005

Discovery, validation, and genetic dissection of transcription factor binding sites by comparative and functional genomics.

Completing the annotation of a genome sequence requires identifying the regulatory sequences that control gene expression. To identify these sequences, we developed an algorithm that searches for short, conserved sequence motifs in the genomes of related species. The method is effective in finding motifs de novo and for refining known regulatory motifs in Saccharomyces cerevisiae. We tested one novel motif prediction of the algorithm and found it to be the binding site of Stp2; it is significantly different from the previously predicted Stp2 binding site. We show that Stp2 physically interacts with this sequence motif, and that stp2 mutations affect the expression of genes associated with the motif. We demonstrate that the Stp2 binding site also interacts genetically with Stp1, a regulator of amino acid permease genes and, with Sfp1, a key regulator of cell growth. These results illuminate an important transcriptional circuit that regulates cell growth through external nutrient uptake.

Arylsulfotransferase↗
PubMed1999

Multiple independent defective suppressor-mutator transposon insertions in Arabidopsis: a tool for functional genomics.

A new system for insertional mutagenesis based on the maize Enhancer/Suppressor-mutator (En/Spm) element was introduced into Arabidopsis. A single T-DNA construct carried a nonautonomous defective Spm (dSpm) element with a phosphinothricin herbicide resistance (BAR) gene, a transposase expression cassette, and a counterselectable gene. This construct was used to select for stable dSpm transpositions. Treatments for both positive (BAR) and negative selection markers were applicable to soil-grown plants, allowing the recovery of new transpositions on a large scale. To date, a total of 48,000 lines in pools of 50 have been recovered, of which approximately 80% result from independent insertion events. DNA extracted from these pools was used in reverse genetic screens, either by polymerase chain reaction (PCR) using primers from the transposon and the targeted gene or by the display of insertions whereby inverse PCR products of insertions from the DNA pools are spotted on a membrane that is then hybridized with the probe of interest. By sequencing PCR-amplified fragments adjacent to insertion sites, we established a sequenced insertion-site database of 1200 sequences. This database permitted a comparison of the chromosomal distribution of transpositions from various T-DNA locations.

Arabidopsis↗
PubMed2001

Functional genomic analysis of the HY2 family of ferredoxin-dependent bilin reductases from oxygenic photosynthetic organisms.

Phytobilins are linear tetrapyrrole precursors of the light-harvesting prosthetic groups of the phytochrome photoreceptors of plants and the phycobiliprotein photosynthetic antennae of cyanobacteria, red algae, and cryptomonads. Previous biochemical studies have established that phytobilins are synthesized from heme via the intermediacy of biliverdin IX alpha (BV), which is reduced subsequently by ferredoxin-dependent bilin reductases with different double-bond specificities. By exploiting the sequence of phytochromobilin synthase (HY2) of Arabidopsis, an enzyme that catalyzes the ferredoxin-dependent conversion of BV to the phytochrome chromophore precursor phytochromobilin, genes encoding putative bilin reductases were identified in the genomes of various cyanobacteria, oxyphotobacteria, and plants. Phylogenetic analyses resolved four classes of HY2-related genes, one of which encodes red chlorophyll catabolite reductases, which are bilin reductases involved in chlorophyll catabolism in plants. To test the catalytic activities of these putative enzymes, representative HY2-related genes from each class were amplified by the polymerase chain reaction and expressed in Escherichia coli. Using a coupled apophytochrome assembly assay and HPLC analysis, we examined the ability of the recombinant proteins to catalyze the ferredoxin-dependent reduction of BV to phytobilins. These investigations defined three new classes of bilin reductases with distinct substrate/product specificities that are involved in the biosynthesis of the phycobiliprotein chromophore precursors phycoerythrobilin and phycocyanobilin. Implications of these results are discussed with regard to the pathways of phytobilin biosynthesis and their evolution.

Amino Acid Sequence↗
PubMedDate not supplied

Associative clustering for exploring dependencies between functional genomics data sets.

High-throughput genomic measurements, interpreted as cooccurring data samples from multiple sources, open up a fresh problem for machine learning: What is in common in the different data sets, that is, what kind of statistical dependencies are there between the paired samples from the different sets? We introduce a clustering algorithm for exploring the dependencies. Samples within each data set are grouped such that the dependencies between groups of different sets capture as much of pairwise dependencies between the samples as possible. We formalize this problem in a novel probabilistic way, as optimization of a Bayes factor. The method is applied to reveal commonalities and exceptions in gene expression between organisms and to suggest regulatory interactions in the form of dependencies between gene expression profiles and regulator binding patterns.

Algorithms↗
PubMed2003

Improving reliability of gene selection from microarray functional genomics data.

Constructing a classifier based on microarray gene expression data has recently emerged as an important problem for cancer classification. Recent results have suggested the feasibility of constructing such a classifier with reasonable predictive accuracy under the circumstance where only a small number of cancer tissue samples of known type are available. Difficulty arises from the fact that each sample contains the expression data of a vast number of genes and these genes may interact with one another. Selection of a small number of critical genes is fundamental to correctly analyze the otherwise overwhelming data. It is essential to use a multivariate approach for capturing the correlated structure in the data. However, the curse of dimensionality leads to the concern about the reliability of selected genes. Here, we present a new gene selection method in which error and repeatability of selected genes are assessed within the context of M-fold cross-validation. In particular, we show that the method is able to identify source variables underlying data generation.

Algorithms↗
PubMed2006

Functional genomics of cactus host shifts in Drosophila mojavensis.

Understanding the genetic basis of adaptation to novel environments remains one of the major challenges confronting evolutionary biologists. While newly developed genomic approaches hold considerable promise for addressing this overall question, the relevant tools have not often been available in the most ecologically interesting organisms. Our study organism, Drosophila mojavensis, is a cactophilic Sonoran Desert endemic utilizing four different cactus hosts across its geographical range. Its well-known ecology makes it an attractive system in which to study the evolution of gene expression during adaptation. As a cactophile, D. mojavensis oviposits in the necrotic tissues of cacti, therefore exposing larvae and even adults to the varied and toxic compounds of rotting cacti. We have developed a cDNA microarray of D. mojavensis to examine gene expression associated with cactus host use. Using a population from the Baja California population we examined gene expression differences of third instar larvae when reared in two chemically distinct cactus hosts, agria (Stenocereus gummosus, native host) vs. organpipe (Stenocereus thurberi, alternative host). We have observed differential gene expression associated with cactus host use in genes involved in metabolism and detoxification.

Animals↗