应用激光显微切割技术检测单个结肠细胞的基因表达

目的：探讨检测单个结肠细胞的基因表达的方法。方法：应用激光显微切割技术(1aser micmdissection)从冰冻切片上将单个结肠细胞切下,提取总RNA,将RNA逆转录成cDNA,采用巢式逆转录聚合酶链反应(nested RT—PCR)检测mRNA的表达。结果：在显微镜下用紫外激光显微切割机,将单个结肠细胞成功切下,提取RNA后,逆转录成cDNA,经过巢式RT—PCR扩增后,扩增产物在琼脂糖凝胶上清晰可见。结论：联合应用激光显微切割和巢式RT—PCR可以检测单个结肠细胞的基因表达。     

RNA Amplification in Brain Tissues

Recent developments in gene array technologies, specifically cDNA microarray platforms, have made it easier to try to understand the constellation of gene alterations that occur within the CNS. Unlike an organ that is comprised of one principal cell type, the brain contains a multiplicity of both neuronal (e.g., pyramidal neurons, interneurons, and others) and noneuronal (e.g., astrocytes, microglia, oligodendrocytes, and others) populations of cells. An emerging goal of modern molecular neuroscience is to sample gene expression from similar cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subtypes and noneuronal cells. At present, an optimal methodology to assess gene expression is to evaluate single cells, either identified physiologically in living preparations, or by immunocytochemical or histochemical procedures in fixed cells in vitro or in vivo. Unfortunately, the quantity of RNA harvested from a single cell is not sufficient for standard RNA extraction methods. Therefore, exponential polymerase-chain reaction (PCR) based analyses and linear RNA amplifications, including a newly developed terminal continuation (TC) RNA amplification methodology, have been used in combination with single cell microdissection procedures to enable the use of cDNA microarray analysis within individual populations of cells obtained from postmortem brain samples as well as the brains of animal models of neurodegeneration.     

Assessing the significance of quantitative trait loci in replicable mapping populations

Replicable populations, such as panels of recombinant inbred or doubled haploid lines, are convenient resources for the mapping of QTL. To increase mapping power, replications are often collected within each RI line and a common way to analyze such data is to include in the QTL model only a single measurement from each line that represents the average among the replicates (a line means model). An obvious, but seldom explored, alternative, is to include every replicate in the model (a full data model). Here, we use simulations to compare these two approaches. Further, we propose an extension of the standard permutation procedure that is required to correctly control the type I error in mapping populations with nested structure.     

Nested clade analyses of phylogeographic data: testing hypotheses about gene flow and population history

Since the 1920s, population geneticists have had measures that describe how genetic variation is distributed spatially within a species' geographical range. Modern genetic survey techniques frequently yield information on the evolutionary relationships among the alleles or haplotypes as well as information on allele frequencies and their spatial distributions. This evolutionary information is often expressed in the form of an estimated haplotype or allele tree. Traditional statistics of population structure, such as F statistics, do not make use of evolutionary genealogical information, so it is necessary to develop new statistical estimators and tests that explicitly incorporate information from the haplotype tree. One such technique is to use the haplotype tree to define a nested series of branches (clades), thereby allowing an evolutionary nested analysis of the spatial distribution of genetic variation. Such a nested analysis can be performed regarding the geographical sampling locations either as categorical or continuous variables (i.e. some measure of spatial distance). It is shown that such nested phylogeographical analyses have more power to detect geographical associations than traditional, nonhistorical analyses and, as a consequence, allow a broader range of gene-flow parameters to be estimated in a precise fashion. More importantly, such nested analyses can discriminate between phylogeographical associations due to recurrent but restricted gene flow vs. historical events operating at the population level (e.g. past fragmentation, colonization, or range expansion events). Restricted gene flow and historical events can be intertwined, and the cladistic analyses can reconstruct their temporal juxtapositions, thereby yielding great insight into both the evolutionary history and population structure of the species. Examples are given that illustrate these properties, concentrating on the detection of range expansion events.     

Avian leukosis virus-induced tumors have common proviral integration sites and synthesize discrete new RNAs: oncogenesis by promoter insertion

Unlike other RNA tumor viruses, avian leukosis viruses (which cause lymphomas and occasionally other neoplasms) lack discrete "transforming genes". We have analyzed the virus-related DNA and RNA of avian leukosis virus (ALV)-induced tumors in an attempt to gain insight into the mechanism of ALV oncogenesis. Our results show that viral gene products are not required for maintenance of neoplastic transformation. Primary and metastatic tumors are clonal and thus presumably derived from a single infected cell. Most importantly, tumors from different birds have integration sites in common. Tumor cells synthesize discrete new poly(A) RNAs consisting of viral sequences covalently linked to cellular sequences. These RNA species are expressed at high levels in tumor cells. Our results suggest that in lymphoid tumors, an ALV provirus is integrated adjacent to a specific cellular gene, and the insertion of the viral promoter adjacent to this gene results in its enhanced expression, leading to neoplasia. These results have potentially important implications for the mechanism of non-viral carcinogenesis.