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Raymond L Rodriguez

Publications and source records attributed to Raymond L Rodriguez.

5 recordsLinked to original sources

Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm.

BACKGROUND: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets. RESULTS: Isomap discovered low-dimensional structures embedded in the Affymetrix microarray data sets. These structures correspond to and help to interpret biological phenomena present in the data. This analysis provides examples of temporal, spatial, and functional processes revealed by the Isomap algorithm. In a spinal cord injury data set, Isomap discovers the three main modalities of the experiment--location and severity of the injury and the time elapsed after the injury. In a multiple tissue data set, Isomap discovers a low-dimensional structure that corresponds to anatomical locations of the source tissues. This model is capable of describing low- and high-resolution differences in the same model, such as kidney-vs.-brain and differences between the nuclei of the amygdala, respectively. In a high-throughput drug screening data set, Isomap discovers the monocytic and granulocytic differentiation of myeloid cells and maps several chemical compounds on the two-dimensional model. CONCLUSION: Visualization of Isomap models provides useful tools for exploratory analysis of microarray data sets. In most instances, Isomap models explain more of the variance present in the microarray data than PCA or MDS. Finally, Isomap is a promising new algorithm for class discovery and class prediction in high-density oligonucleotide data sets.

Algorithms↗

The case for strategic international alliances to harness nutritional genomics for public and personal health.

Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene-nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient-genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries.

Animals↗

Nutritional genomics: the next frontier in the postgenomic era.

The interface between the nutritional environment and cellular/genetic processes is being referred to as "nutrigenomics." Nutrigenomics seeks to provide a molecular genetic understanding for how common dietary chemicals (i.e., nutrition) affect health by altering the expression and/or structure of an individual's genetic makeup. The fundamental concepts of the field are that the progression from a healthy phenotype to a chronic disease phenotype must occur by changes in gene expression or by differences in activities of proteins and enzymes and that dietary chemicals directly or indirectly regulate the expression of genomic information. We present a conceptual basis and specific examples for this new branch of genomic research that focuses on the tenets of nutritional genomics: 1) common dietary chemicals act on the human genome, either directly or indirectly, to alter gene expression or structure; 2) under certain circumstances and in some individuals, diet can be a serious risk factor for a number of diseases; 3) some diet-regulated genes (and their normal, common variants) are likely to play a role in the onset, incidence, progression, and/or severity of chronic diseases; 4) the degree to which diet influences the balance between healthy and disease states may depend on an individual's genetic makeup; and 5) dietary intervention based on knowledge of nutritional requirement, nutritional status, and genotype (i.e., "individualized nutrition") can be used to prevent, mitigate, or cure chronic disease.

Chronic Disease↗

Expression of functional recombinant human lysozyme in transgenic rice cell culture.

Using particle bombardment-mediated transformation, a codon-optimized synthetic gene for human lysozyme was introduced into the calli of rice (Oryza sativa) cultivar Taipei 309. The expression levels of recombinant human lysozyme in the transformed rice suspension cell culture approached approximately 4% of total soluble protein. Recombinant human lysozyme was purified to greater than 95% homogeneity using a two-step chromatography process. Amino acid sequencing verified that the N-terminus of the mature recombinant human lysozyme was identical to native human lysozyme. This indicates that the rice RAmy3D signal peptide was correctly cleaved off from the human lysozyme preprotein by endogenous rice signal peptidase. Recombinant human lysozyme was found to have the same molecular mass, isoelectric point and specific activity as native human lysozyme. The bactericidal activity of recombinant human lysozyme was determined by turbidimetric assay using Micrococcus lysodeikticus in 96-well microtiter plates. The bactericidal activity of lysozyme on gram-negative bacteria was examined by adding purified lysozyme to mid-log phase cultures of E. coli strain JM109. In this study, significant bactericidal activity was observed after E. coli cells were exposed to recombinant human lysozyme for 60 min. Both native and recombinant human lysozyme displayed the same thermostability and resistance to degradation by low pH. The potential for using rice-derived lysozyme as an antimicrobial food supplement, particularly for infant formula and baby foods, is discussed.

Biolistics↗

Expression and inheritance of nine transgenes in rice.

A total of 66 transgenic rice cell lines were produced by simultaneously transforming rice callus with nine different plasmids/genes. PCR analysis indicated that the co-transformation frequency of each gene was about 70%. All the cell lines carried at least three genes and 11 cell lines carried all nine genes. Thirty-two fertile transgenic plants (R0) were generated from the transgenic cell lines and seeds of 32 transgenic R1 lines and 5 R2 lines were harvested and analyzed for gene inheritance and protein expression. Progeny segregation analysis indicated that the multiple transgenes were integrated into the same locus of the rice genome, resulting in a 3:1 segregation ratio of the transgenes. Expression analysis of all nine transgenes revealed that the transgenes were expressed in all generations (R0, R1, and R2) and about half of the transgenes from each line were expressed. The expression of one transgene appears to have no effect on the expression of another transgene. Among the 66 cell lines, six lines (9.1%) expressed seven or eight transgenes out of the nine transformed genes. All together, our results showed that multiple genes could be delivered into rice cells simultaneously and cell lines expressing multiple genes could be generated. The results and procedures reported here should be useful in designing multi-plasmid transformation experiments such as those required for plant metabolic engineering.

Acetyltransferases↗