Biomedical subjects

Per Unneberg

Publications and source records attributed to Per Unneberg.

3 recordsLinked to original sources

PubMed2003

Shotgun sequencing and microarray analysis of RDA transcripts.

Monitoring of differential gene expression is an important step towards understanding of gene function. We describe a comparison of the representational difference analysis (RDA) subtraction process with corresponding microarray analysis. The subtraction steps are followed in a quantitative manner using a shotgun cloning and sequencing procedure that includes over 1900 gene sequences. In parallel, the enriched transcripts are spotted onto microarrays facilitating large scale hybridization analysis of the representations and the difference products. We show by the shotgun procedure that there is a high diversity of gene fragments represented in the iterative RDA products (92-67% singletons) with a low number of shared sequences (<9%) between subsequent subtraction cycles. A non redundant set of 1141 RDA clones were immobilized on glass slides and the majority of these clones (97%) gave repeated good fluorescent signals in a subsequent hybridization of the labelled and amplified original cDNA. We observed only a low number of false positives (<2%) and a more than twofold differential expression for 32% (363) of the immobilized RDA clones. In conclusion, we show that by random sequencing of the difference products we obtained an accurate transcript profile of the individual steps and that large-scale confirmation of the obtained transcripts can be achieved by microarray analysis.

Cell Line↗

PubMed2003

Transcript identification by analysis of short sequence tags--influence of tag length, restriction site and transcript database.

There exist a number of gene expression profiling techniques that utilize restriction enzymes for generation of short expressed sequence tags. We have studied how the choice of restriction enzyme influences various characteristics of tags generated in an experiment. We have also investigated various aspects of in silico transcript identification that these profiling methods rely on. First, analysis of 14 248 mRNA sequences derived from the RefSeq transcript database showed that 1-30% of the sequences lack a given restriction enzyme recognition site. Moreover, 1-5% of the transcripts have recognition sites located less than 10 bases from the poly(A) tail. The uniqueness of 10 bp tags lies in the range 90-95%, which increases only slightly with longer tags, due to the existence of closely related transcripts. Furthermore, 3-30% of upstream 10 bp tags are identical to 3' tags, introducing a risk of misclassification if upstream tags are present in a sample. Second, we found that a sequence length of 16-17 bp, including the recognition site, is sufficient for unique transcript identification by BLAST based sequence alignment to the UniGene Human non-redundant database. Third, we constructed a tag-to-gene mapping for UniGene and compared it to an existing mapping database. The mappings agreed to 79-83%, where the selection of representative sequences in the UniGene clusters is the main cause of the disagreement. The results of this study may serve to improve the interpretation of sequence-based expression studies and the design of hybridization arrays, by identifying short tags that have a high reliability and separating them from tags that carry an inherent ambiguity in their capacity to discriminate between genes. To this end, supplementary information in the form of a web companion to this paper is located at http:// biobase.biotech.kth.se/tagseq.

Algorithms↗

PubMed2002

Gene expression analysis by signature pyrosequencing.

We describe a novel method for transcript profiling based on high-throughput parallel sequencing of signature tags using a non-gel-based microtiter plate format. The method relies on the identification of cDNA clones by pyrosequencing of the region corresponding to the 3'-end of the mRNA preceding the poly(A) tail. Simultaneously, the method can be used for gene discovery, since tags corresponding to unknown genes can be further characterized by extended sequencing. The protocol was validated using a model system for human atherosclerosis. Two 3'-tagged cDNA libraries, representing macrophages and foam cells, which are key components in the development of atherosclerotic plaques, were constructed using a solid phase approach. The libraries were analyzed by pyrosequencing, giving on average 25 bases. As a control, conventional expressed sequence tag (EST) sequencing using slab gel electrophoresis was performed. Homology searches were used to identify the genes corresponding to each tag. Comparisons with EST sequencing showed identical, unique matches in the majority of cases when the pyrosignature was at least 18 bases. A visualization tool was developed to facilitate differential analysis using a virtual chip format. The analysis resulted in identification of genes with possible relevance for development of atherosclerosis. The use of the method for automated massive parallel signature sequencing is discussed.

Base Sequence↗