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Biomedical subjects

Jennifer Tsai

Publications and source records attributed to Jennifer Tsai.

8 recordsLinked to original sources

Physiogenomic resources for rat models of heart, lung and blood disorders.

Cardiovascular disorders are influenced by genetic and environmental factors. The TIGR rodent expression web-based resource (TREX) contains over 2,200 microarray hybridizations, involving over 800 animals from 18 different rat strains. These strains comprise genetically diverse parental animals and a panel of chromosomal substitution strains derived by introgressing individual chromosomes from normotensive Brown Norway (BN/NHsdMcwi) rats into the background of Dahl salt sensitive (SS/JrHsdMcwi) rats. The profiles document gene-expression changes in both genders, four tissues (heart, lung, liver, kidney) and two environmental conditions (normoxia, hypoxia). This translates into almost 400 high-quality direct comparisons (not including replicates) and over 100,000 pairwise comparisons. As each individual chromosomal substitution strain represents on average less than a 5% change from the parental genome, consomic strains provide a useful mechanism to dissect complex traits and identify causative genes. We performed a variety of data-mining manipulations on the profiles and used complementary physiological data from the PhysGen resource to demonstrate how TREX can be used by the cardiovascular community for hypothesis generation.

Animals↗

Unique features of a highly pathogenic Campylobacter jejuni strain.

Campylobacter jejuni, a major human enteric pathogen, exhibits significant strain-to-strain differences which result in differences in pathogenic potential. C. jejuni 81-176 is a highly virulent strain that exhibits unique pathogenic features and is used by many research laboratories. We have determined the nucleotide sequence of its genome and compared it to the genomes of other sequenced C. jejuni strains. We identified a number of unique genetic features which may confer specific metabolic and pathogenic properties on this strain. We have also identified regions of the C. jejuni genome that are hot spots for the integration of horizontally acquired genetic material. This information should help the understanding of the pathogenesis of C. jejuni and, in particular, the unique features of this highly pathogenic strain.

Animals↗

Iterative microarray and RNA interference-based interrogation of the SRC-induced invasive phenotype.

Src kinase has long been recognized as a factor in the progression of colorectal cancer and seems to play a specific role in the development of the metastatic phenotype. In spite of numerous studies conducted to elucidate the exact role of Src in cancer progression, downstream targets of Src remain poorly understood. Gene expression profiling has permitted the identification of large sets of genes that may be functionally interrelated but it is often unclear as to which molecular pathways they belong. Here we have developed an iterative approach to experimentally reconstruct a network of gene activity regulated by Src and contributing to the invasive phenotype. Our strategy uses a combination of phenotypic anchoring of gene expression profiles and loss-of-function screening by way of RNA-mediated interference. Using a panel of human colon cancer cell lines exhibiting differential Src-specific activity and invasivity, we identify the first two levels of gene transcription responsible for the invasive phenotype, where first-tier genes are controlled by Src activity and the second-tier genes are under the influence of the first tier. Specifically, perturbation of first-tier gene activity by either pharmacologic inhibition of Src or RNA-mediated interference-directed knockdown leads to a loss of invasivity and decline of second-tier gene activity. The targeting of first-tier genes may be bypassed altogether because knockdown of second-tier genes led to a similar loss of invasive potential. In this manner, numerous members of a "transcriptional cascade" pathway for metastatic activity have been identified and functionally validated.

Biomarkers, Tumor↗

TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.

Cluster Analysis↗

Comparative analyses of potato expressed sequence tag libraries.

The cultivated potato (Solanum tuberosum) shares similar biology with other members of the Solanaceae, yet has features unique within the family, such as modified stems (stolons) that develop into edible tubers. To better understand potato biology, we have undertaken a survey of the potato transcriptome using expressed sequence tags (ESTs) from diverse tissues. A total of 61,940 ESTs were generated from aerial tissues, below-ground tissues, and tissues challenged with the late-blight pathogen (Phytophthora infestans). Clustering and assembly of these ESTs resulted in a total of 19,892 unique sequences with 8,741 tentative consensus sequences and 11,151 singleton ESTs. We were able to identify a putative function for 43.7% of these sequences. A number of sequences (48) were expressed throughout the libraries sampled, representing constitutively expressed sequences. Other sequences (13,068, 21%) were uniquely expressed and were detected only in a single library. Using hierarchal and k means clustering of the EST sequences, we were able to correlate changes in gene expression with major physiological events in potato biology. Using pair-wise comparisons of tuber-related tissues, we were able to associate genes with tuber initiation, dormancy, and sprouting. We also were able to identify a number of characterized as well as novel sequences that were unique to the incompatible interaction of late-blight pathogen, thereby providing a foundation for further understanding the mechanism of resistance.

Cluster Analysis↗

The Schistosoma mansoni gene index: gene discovery and biology by reconstruction and analysis of expressed gene sequences.

Expressed sequence tag (EST) sequencing and analysis is a primary research tool to identify and characterize the Schistosoma mansoni transcriptome. As part of our gene discovery effort, a total of 5,793 ESTs have been generated from clones selected randomly from complementary DNA (cDNA) libraries constructed from male and female adult worms. Assembly analysis of all the 16,813 public S. mansoni ESTs has identified 1,920 distinct tentative consensus sequences (TCs) and 5,571 nonoverlapping ESTs (singletons). Of these, 376 TCs (20%) and 1,449 singletons (26%) are unique to the SUNY/TIGR sequencing effort. Tentative consensus sequences and singletons were distributed into various categories of biological roles associated with cell structure, metabolism, protein fate, signal transduction, transcription, protein synthesis, transporters, and cell growth. The TCs and singletons represent transcripts that can be used as a resource for functional annotation of genomic sequence data, comparative sequence analysis, and cDNA clone selection for microarray projects. The utility of EST analysis is demonstrated by identifying new protease genes, which may be involved in hemoglobin degradation.

Amino Acid Sequence↗

Identification of Src transformation fingerprint in human colon cancer.

We used a classical rodent model of transformation to understand the transcriptional processes, and hence the molecular and cellular events a given cell undergoes when progressing from a normal to a transformed phenotype. Src activation is evident in 80% of human colon cancer, yet the myriad of cellular processes effected at the level of gene expression has yet to be fully documented. We identified a Src 'transformation fingerprint' within the gene expression profiles of Src-transformed rat 3Y1 fibroblasts demonstrating a progression in transformation characteristics. To evaluate the role of this gene set in human cancer development and progression, we extracted the orthologous genes present on the Affymetrix Hu95A GeneChip (12k named genes) and compared expression profiles between the Src-induced rodent cell line model of transformation and staged colon tumors where Src is known to be activated. A similar gene expression pattern between the cell line model and staged colon tumors for components of the cell cycle, cytoskeletal associated proteins, transcription factors and lysosomal proteins suggests the need for co-regulation of several cellular processes in the progression of cancer. Genes not previously implicated in tumorigenesis were detected, as well as a set of 14 novel, highly conserved genes with here-to-fore unknown function. These studies define a set of transformation associated genes whose up-regulation has implications for understanding Src mediated transformation and strengthens the role of Src in the development and progression of human colon cancer. Supportive Supplemental Data can be viewed at http://pga.tigr.org/PGApubs.shtml.

Animals↗

Cross-referencing eukaryotic genomes: TIGR Orthologous Gene Alignments (TOGA).

Comparative genomics promises to rapidly accelerate the identification and functional classification of biologically important human genes. We developed the TIGR Orthologous Gene Alignment (TOGA; ) database to provide a cross-reference between fully and partially sequenced eukaryotic transcribed sequences. Starting with the assembled expressed sequence tag (EST) and gene sequences that comprise the 28 TIGR Gene Indices, we used high-stringency pair-wise sequence searches and a reflexive, transitive closure process to associate sequence-specific best hits, generating 32,652 tentative ortholog groups (TOGs). This has allowed us to identify putative orthologs and paralogs for known genes, as well as those that exist only as uncharacterized ESTs and to provide links to additional information including genome sequence and mapping data. TOGA provides an important new resource for the analysis of gene function in eukaryotes. In addition, an analysis of the most widely represented sequences can begin to provide insight into eukaryotic biological processes.

Algorithms↗