Biomedical subjects

Hongying Jiang

Publications and source records attributed to Hongying Jiang.

4 recordsLinked to original sources

PubMed2005

Functional genomics analysis of foliar condensed tannin and phenolic glycoside regulation in natural cottonwood hybrids.

Regulation of leaf condensed tannins (CT) and salicylate-derived phenolic glycosides (PG) in fast- and slow-growing cottonwood backcrosses was analyzed by metabolic profiling and cDNA microarray hybridization. Seven hybrid lines of Populus fremontii L. and P. angustifolia James exhibiting growth/CT-PG phenotypes ranging from fast/low (Lines 18 and 1979) to slow/high (Lines 1012 and RL2) and intermediate (Lines NUL, 3200 and RM5) were investigated. Methanol-extractable leaf metabolites were analyzed by gas chromatography-mass spectrometry, and the results evaluated by principal component analysis. The hybrid lines formed separate clusters based on their primary metabolite profiles, with cluster arrangement also reflecting differences in CT-PG phenotype. Nitrogen (N) supply was manipulated to alter CT-PG partitioning and to obtain molecular insights into how primary metabolism interfaces with CT-PG accumulation. Three backcross lines (RM5, 1012, 18) exhibiting differential CT-PG responses to a 10-day hydroponic N-deprivation treatment were chosen for metabolite and gene expression analyses. The fast- growing Line 18 showed a minimal CT-PG response to N deprivation, and a reduction in photosynthetic gene expression. Line 1012 exhibited a strong phenylpropanoid response to N deprivation, including a doubling in phenylalanine ammonia-lyase (PAL) gene expression, and a shift from CT accumulation in the absence of stress toward PG accumulation under N-deprivation conditions. Amino acid concentrations were depressed in Lines 18 and 1012, as was expression of nitrate-sensitive genes coding for transketolase (TK), and malate dehydrogenase (MDH). Genes associated with protein synthesis and fate were down-regulated in Line 1012 but not in Line 18. Line RM5 exhibited a comparatively large increase in CT in response to N deprivation, but did not sustain decreases in amino acid concentrations, or changes in PAL, TK or MDH gene expression. Molecular characterization of the variable CT-PG responses shows promise for the identification and future testing of candidate genes for CT-PG trait selection or manipulation.

Gas Chromatography-Mass Spectrometry↗

PubMed2004

Metabolic profiling of the sink-to-source transition in developing leaves of quaking aspen.

Profiles of small polar metabolites from aspen (Populus tremuloides Michx.) leaves spanning the sink-to-source transition zone were compared. Approximately 25% of 250 to 300 routinely resolved peaks were identified, with carbohydrates, organic acids, and amino acids being most abundant. Two-thirds of identified metabolites exhibited greater than 4-fold changes in abundance during leaf ontogeny. In the context of photosynthetic and respiratory measurements, profile data yielded information consistent with expected developmental trends in carbon-heterotrophic and carbon-autotrophic metabolism. Suc concentration increased throughout leaf expansion, while hexose sugar concentrations peaked at mid-expansion and decreased sharply thereafter. Amino acid contents generally decreased during leaf expansion, but an early increase in Phe and a later one in Gly and Ser reflected growing commitments to secondary metabolism and photorespiration, respectively. The assimilation of nitrate and utilization of stored Asn appeared to be marked by sequential changes in malate concentration and Asn transaminase activity. Principal component and hierarchical clustering analysis facilitated the grouping of cell wall maturation (pectins, hemicelluloses, and oxalate) and membrane biogenesis markers in relation to developmental changes in carbon and nitrogen assimilation. Metabolite profiling will facilitate investigation of nitrogen use and cellular development in Populus sp. varying widely in their growth and pattern of carbon allocation during sink-to-source development and in response to stress.

Amino Acids↗

PubMed2004

Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes.

BACKGROUND: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very few common identified marker genes among different studies involving patients with the same disease. Therefore, it is of great interest and challenge to merge data sets from multiple studies to increase the sample size, which may in turn increase the power of statistical inferences. In this study, we combined two lung cancer studies using microarray GeneChip, employed two gene shaving methods and a two-step survival test to identify genes with expression patterns that can distinguish diseased from normal samples, and to indicate patient survival, respectively. RESULTS: In addition to common data transformation and normalization procedures, we applied a distribution transformation method to integrate the two data sets. Gene shaving (GS) methods based on Random Forests (RF) and Fisher's Linear Discrimination (FLD) were then applied separately to the joint data set for cancer gene selection. The two methods discovered 13 and 10 marker genes (5 in common), respectively, with expression patterns differentiating diseased from normal samples. Among these marker genes, 8 and 7 were found to be cancer-related in other published reports. Furthermore, based on these marker genes, the classifiers we built from one data set predicted the other data set with more than 98% accuracy. Using the univariate Cox proportional hazard regression model, the expression patterns of 36 genes were found to be significantly correlated with patient survival (p < 0.05). Twenty-six of these 36 genes were reported as survival-related genes from the literature, including 7 known tumor-suppressor genes and 9 oncogenes. Additional principal component regression analysis further reduced the gene list from 36 to 16. CONCLUSION: This study provided a valuable method of integrating microarray data sets with different origins, and new methods of selecting a minimum number of marker genes to aid in cancer diagnosis. After careful data integration, the classification method developed from one data set can be applied to the other with high prediction accuracy.

Adenocarcinoma↗

PubMed2004

Suppression subtractive hybridization-mediated transcriptome analysis from multiple tissues of aspen (Populus tremuloides) altered in phenylpropanoid metabolism.

A PCR-based suppression subtractive hybridization (SSH) technique was used to identify differentially expressed genes in developing tissues of control and transgenic aspen (Populus tremuloides Michx.) with down-regulated 4CL1 (4-coumarate:coenzyme A ligase) expression and enhanced growth. A total of 11,308 expressed sequence tags (ESTs) representing 5,028 non-redundant transcripts encoding 4,224 unique proteins was obtained from shoot apex, young stem, young leaf and root tip SSH libraries. Putative functions can be assigned to 60% of these transcripts. Approximately 14% of the ESTs are not represented among the 111,000 entries already present in Populus EST databases. In general, ESTs of the metabolism class occurred at a higher frequency in control- than transgenic-enriched libraries of all tissues, whereas protein synthesis and protein fate ESTs were over-represented in meristematic tissues of transgenics where 4CL1 was relatively strongly suppressed. Among all tissues, leaves yielded the highest percentage of ESTs with either unknown protein function or insignificant similarity to other protein/DNA/EST sequences in existing databases. Of particular interest was a large number of ESTs (16%) associated with signal transduction in transgenic leaves. Among these were several leucine-rich-repeat receptor-like protein kinases with markedly elevated expression in transgenic leaves. We also identified homologs of transposable elements that were up-regulated in transgenic tissues, providing the first experimental data for active expression of DNA mobile elements in long-lived tree species.

DNA Transposable Elements↗