Isolation of Unknown Genes from Human Bone Marrow by Differental Screening and Single-Pass cDNA Sequences Determination

A cDNA sequencing project was initiated to characterize gene expression in human bone marrow and develop strategies to isolate novel genes. Forty-eight random cDNAs from total human bone marrow were subjected to single-pass DNA sequence analysis to determine a limited complexity of mRNAs expressed in the bone marrow. Overall, 8 cDNAs (17%) showed no similarity to known sequences. Information from DNA sequence analysis was used to develop a differential prescreen to subtract unwanted cDNAs and to enrich for unknown cDNAs. Forty-eight cDNAs that were negative with a complex probe were subject to single-pass DNA sequence determination. Of these prescreened cDNAs, the number of unknown sequences increased to 23 (48%). Unknown cDNAs were also characterized by RNA expression analysis using 25 different human leukemic cell lines. Of 13 unknown cDNAs tested, 10 were expressed in all cell types tested and 3 revealed a hematopoietic lineage-restricted expression pattern. Interestingly, while a total of only 96 bone marrow cDNAs were sequenced, 31 of these cDNAs represent sequences from unknown genes and 12 showed significant similarities to sequences in the data bases. One cDNA revealed a significant similarity to a serine/threonine-protein kinase at the amino acid level (56% identity for 123 amino acids) and may represent a previously unknown kinase. Differential screening techniques coupled with single-pass cDNA sequence analysis may prove to be a powerful and simple technique to examine developmental gene expression

Single nucleotide polymorphism genotyping and its application on mapping and marker-assisted plant breeding

The nucleotide diversity across a genome is the source of most phenotypic variation. Such DNA polymorphism is the basis for the development of molecular markers, an indispensable tool in geneticmapping studies. In general, the high resolution fine mapping of genes is often limited by lack of sufficient number of polymorphic molecular markers. This problem is compounded with traits controlled by multi-genes because in several such studies, QTL cannot be resolved to a workable resolution that could be feasible for predicting the candidate gene(s) associated with traits of interests. The availability of abundant, high-throughput sequence-based markers is the key for detailed genomewide trait analysis. Single-nucleotide polymorphisms (SNP) are the most common sequence variation and a significant amount of effort has been invested in re-sequencing alleles to discover SNPs. In fully sequenced small-genome model organisms, SNP discovery is relatively straight forward, although highthroughputSNP discovery in natural populations remains both expensive and time-consuming. Here five central biochemical reaction principles that underlie SNP-genotyping methods specifically for large panel sizes and an intermediate number of SNPs are reviewed

PrimerStation: a highly specific multiplex genomic PCR primer design server for the human genome

PrimerStation () is a web service that calculates primer sets guaranteeing high specificity against the entire human genome. To achieve high accuracy, we used the hybridization ratio of primers in liquid solution. Calculating the status of sequence hybridization in terms of the stringent hybridization ratio is computationally costly, and no web service checks the entire human genome and returns a highly specific primer set calculated using a precise physicochemical model. To shorten the response time, we precomputed candidates for specific primers using a massively parallel computer with 100 CPUs (SunFire 15 K) about 3 months in advance. This enables PrimerStation to search and output qualified primers interactively. PrimerStation can select highly specific primers suitable for multiplex PCR by seeking a wider temperature range that minimizes the possibility of cross-reaction. It also allows users to add heuristic rules to the primer design, e.g. the exclusion of single nucleotide polymorphisms (SNPs) in primers, the avoidance of poly(A) and CA-repeats in the PCR products, and the elimination of defective primers using the secondary structure prediction. We performed several tests to verify the PCR amplification of randomly selected primers for ChrX, and we confirmed that the primers amplify specific PCR products perfectly

Custom Design and Analysis of High-Density Oligonucleotide Bacterial Tiling Microarrays

Not until recently have custom made high-density oligonucleotide microarrays been available at an affordable price. The aim of this thesis was to design microarrays and analysis algorithms for DNA repair and DNA damage detection, and to apply the methods in real experiments. Thomassen et al. have used their custom designed whole genome-tiling microarrays for detection of transcriptional changes in Escherichia coli after exposure to DNA damageing reagents. The transcriptional changes in E. coli treated with UV light or the methylating reagent MNNG were shown to be larger and to include far more genes than previously reported. To optimize the data analysis for the custom made arrays, Thomassen and coworkers designed their own normalization and analysis algorithms, and showed these more suitable than established methods that are currently applied on custom tiling arrays. Among other findings several novel stress-induced transcripts were detected, of which one is predicted to be a UV-induced short transmembrane protein. Additionally, no upregulation of the previously described UV-inducible aidB is shown. In the MNNG study several genes are shown as downregulated in response to DNA damage although having upstream regulatory sequences similar to the established LexA box A and B. This indicates that the LexA regulon also might control gene repression and that the box A and B sequence can not alone answer for the LexA controlled gene regulation. Thomassen et al. have also custom designed a microarray for oncogenic fusion gene detection. Cancer specific fusion genes are often used to subgroup cancers and to define the optimal treatment, but currently the laboratory detection procedure is both laborious and tedious. In a blinded study on six cancer cell lines proof of principle was shown by detection of six out of six positive controls. The design and analysis methods for this microarray are now being refined to make a diagnostic fusion gene detection tool

Fluorescent Calcium Imaging and Subsequent In Situ Hybridization for Neuronal Precursor Characterization in Xenopus laevis

Spontaneous intracellular calcium activity can be observed in a variety of cell types and is proposed to play critical roles in a variety of physiological processes. In particular, appropriate regulation of calcium activity patterns during embryogenesis is necessary for many aspects of vertebrate neural development, including proper neural tube closure, synaptogenesis, and neurotransmitter phenotype specification. While the observation that calcium activity patterns can differ in both frequency and amplitude suggests a compelling mechanism by which these fluxes might transmit encoded signals to downstream effectors and regulate gene expression, existing population-level approaches have lacked the precision necessary to further explore this possibility. Furthermore, these approaches limit studies of the role of cell-cell interactions by precluding the ability to assay the state of neuronal determination in the absence of cell-cell contact. Therefore, we have established an experimental workflow that pairs time-lapse calcium imaging of dissociated neuronal explants with a fluorescence in situ hybridization assay, allowing the unambiguous correlation of calcium activity pattern with molecular phenotype on a single-cell level. We were successfully able to use this approach to distinguish and characterize specific calcium activity patterns associated with differentiating neural cells and neural progenitor cells, respectively; beyond this, however, the experimental framework described in this article could be readily adapted to investigate correlations between any time-series activity profile and expression of a gene or genes of interest

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure