PubMed Health⌕ Search

Biomedical subjects

Zheng Lian

Publications and source records attributed to Zheng Lian.

6 recordsLinked to original sources

Assessing the performance of different high-density tiling microarray strategies for mapping transcribed regions of the human genome.

Genomic tiling microarrays have become a popular tool for interrogating the transcriptional activity of large regions of the genome in an unbiased fashion. There are several key parameters associated with each tiling experiment (e.g., experimental protocols and genomic tiling density). Here, we assess the role of these parameters as they are manifest in different tiling-array platforms used for transcription mapping. First, we analyze how a number of published tiling-array experiments agree with established gene annotation on human chromosome 22. We observe that the transcription detected from high-density arrays correlates substantially better with annotation than that from other array types. Next, we analyze the transcription-mapping performance of the two main high-density oligonucleotide array platforms in the ENCODE regions of the human genome. We hybridize identical biological samples and develop several ways of scoring the arrays and segmenting the genome into transcribed and nontranscribed regions, with the aim of making the platforms most comparable to each other. Finally, we develop a platform comparison approach based on agreement with known annotation. Overall, we find that the performance improves with more data points per locus, coupled with statistical scoring approaches that properly take advantage of this, where this larger number of data points arises from higher genomic tiling density and the use of replicate arrays and mismatches. While we do find significant differences in the performance of the two high-density platforms, we also find that they complement each other to some extent. Finally, our experiments reveal a significant amount of novel transcription outside of known genes, and an appreciable sample of this was validated by independent experiments.

Cell Line↗

Two types of precursor cells in a multipotential hematopoietic cell line.

The biochemistry of early stages of hematopoietic differentiation is difficult to study because only relatively small numbers of precursor cells are available. The murine EML cell line is a multipotential cell line that can be used to model some of these steps. We found that the lineage- EML precursor cells can be separated into two populations based on cell surface markers including CD34. Both populations contain similar levels of stem cell factor (SCF) receptor (c-Kit) but only the CD34+ population shows a growth response when treated with SCF. Conversely, the CD34- population will grow in the presence of the cytokine IL-3. The human beta-globin locus control region hypersensitive site 2 plays different roles on beta-globin transcription in the CD34+ and CD34- populations. The two populations are present in about equal amounts in culture, and the CD34+ population rapidly regenerates the mixed population when grown in the presence of SCF. We suggest that this system may mimic a normal developmental transition in hematopoiesis.

Animals↗

Lineage specificity of gene expression patterns.

The hematopoietic system offers many advantages as a model for understanding general aspects of lineage choice and specification. Using oligonucleotide microarrays, we compared gene expression patterns of multiple purified hematopoietic cell populations, including neutrophils, monocytes, macrophages, resting, centrocytic, and centroblastic B lymphocytes, dendritic cells, and hematopoietic stem cells. Some of these cells were studied under both resting and stimulated conditions. We studied the collective behavior of subsets of genes derived from the Biocarta database of functional pathways, hand-tuned groupings of genes into broad functional categories based on the Gene Ontology database, and the metabolic pathways in the Kyoto Encyclopedia of Genes and Genomes database. Principal component analysis revealed strikingly pervasive differences in relative levels of gene expression among cell lineages that involve most of the subsets examined. These results indicate that many processes in these cells behave differently in different lineages. Much of the variation among lineages was captured by the first few principal components. Principal components biplots were found to provide a convenient visual display of the contributions of the various genes within the subsets in lineage discrimination. Moreover, by applying tree-constructing methodologies borrowed from phylogenetics to the expression data from differentiated cells and stem cells, we reconstructed a tree of relationships that resembled the established hematopoietic program of lineage development. Thus, the mRNA expression data implicitly contained information about developmental relationships among cell types.

Cell Lineage↗

A panorama of lineage-specific transcription in hematopoiesis.

The hematopoietic system consists of more than ten differentiated cell types, all of which are derived from a single type of hematopoietic stem cell. The accessibility and interest of this system have made it a model for understanding normal and abnormal differentiation of mammalian cells. Newer techniques have generated a mass of data that requires integrative approaches for analysis and interpretation. The traditional view of the differentiation program holds that a small number of regulators are involved in each stage of cell specification. However, this may not be the case. Recent analyses have shown that almost all substantial subsets of genes, including the set of broadly expressed transcription factors, are expressed in patterns that are unique for each lineage. Further, much of this difference between lineages can be captured in two-dimensional graphs. Understanding the biologic significance, mechanisms and constraints underlying these differences is a challenge for experimentalists and computational biologists alike.

Animals↗

Gene expression in human neutrophils during activation and priming by bacterial lipopolysaccharide.

Circulating neutrophils play a key role both in the systemic inflammatory response and in complications of bacterial infection such as septic shock and septic multiple organ dysfunction syndrome. We have analyzed gene expression patterns in human neutrophils stimulated by E. coli lipopolysaccharide (LPS), with or without prior exposure to LPS, using differential display and oligonucleotide chip techniques. We identified 307 genes that were activated or repressed after treatment with LPS at 10 ng/ml and 385 genes after LPS at 100 ng/ml, compared with untreated neutrophils. The two sets included many transcription factors, cytokines, chemokines, interleukins, and surface antigens, as well as members of the toll-like receptor, Rel/NF-kappaB, and immune mediator gene families. Time course analysis showed that the early and late neutrophil responses to LPS share some common mechanisms, but many changes in gene expression are transient or late to develop. Neutrophils also showed a priming response to LPS, in which 97 genes significantly changed expression on re-exposure to lower dose LPS and were analyzed by unsupervised hierarchical clustering. These findings indicate that the neutrophil is a transcriptionally active cell responsive to environmental stimuli and capable of a complex series of both early and late changes in gene expression. Supplementary material for this article can be found on the Journal of Cellular Biochemistry website (http://jws-edci.interscience.wiley.com:8998/jpages/0730-2312/suppmat/89/v89.page.html).

Cluster Analysis↗

Genomic and proteomic analysis of the myeloid differentiation program: global analysis of gene expression during induced differentiation in the MPRO cell line.

We have used an approach using 2-dimensional gel electrophoresis with mass spectrometry analysis combined with oligonucleotide chip hybridization for a comprehensive and quantitative study of the temporal patterns of protein and mRNA expression during myeloid development in the MPRO murine cell line. This global analysis detected 123 known proteins and 29 "new" proteins out of 220 protein spots identified by tandem mass spectroscopy, including proteins in 12 functional categories such as transcription factors and cytokines. Bioinformatic analysis of these proteins revealed clusters with functional importance to myeloid differentiation. Previous analyses have found that for a substantial number of genes the absolute amount of protein in the cell is not strongly correlated to the amount of mRNA. These conclusions were based on simultaneous measurement of mRNA and protein at just a single time point. Here, however, we are able to investigate the relationship between mRNA and protein in terms of simultaneous changes in their levels over multiple time points. This is the first time such a relationship has been studied, and we find that it gives a much stronger correlation, consistent with the hypothesis that a substantial proportion of protein change is a consequence of changed mRNA levels, rather than posttranscriptional effects. Cycloheximide inhibition also showed that most of the proteins detected by gel electrophoresis were relatively stable. Specific investigation of transcription factor mRNA representation showed considerable similarity to those of mature human neutrophils and highlighted several transcription factors and other functional nuclear proteins whose mRNA levels change prominently during MPRO differentiation but which have not been investigated previously in the context of myeloid development. Data are available online at http://bioinfo.mbb.yale.edu/expression/myelopoiesis.

Animals↗