Biomedical subjects

Tatiana Subkhankulova

Publications and source records attributed to Tatiana Subkhankulova.

3 recordsLinked to original sources

PubMed2006

Electrophysiological and gene expression profiling of neuronal cell types in mammalian neocortex.

It is a challenging question to understand how different neuronal types are organized into a complex architecture in the cortex, an architecture which is also adapted in different regions to subserve very different functions. Recent developments in genetic and molecular techniques have opened up the possibility of using gene expression profiling for neuronal cell typing, with the aim of uncovering novel cell types and the underlying mechanisms which generate and maintain neuronal heterogeneity in the cortex. This review introduces some current ideas about neuronal cell types in the cortex and describes recent approaches to expression profiling for defining cortical neuronal cell types.

Animals↗

PubMed2006

Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level.

BACKGROUND: Single-cell microarray expression profiling requires 108-109-fold amplification of the picogram amounts of total RNA typically found in eukaryotic cells. Several methods for RNA amplification are in general use, but little consideration has been given to the comparative analysis of those methods in terms of the overall validity of the data generated when amplifying from single-cell amounts of RNA, rather than their empirical performance in single studies. RESULTS: We tested the performance of three methods for amplifying single-cell amounts of RNA under ideal conditions: T7-based in vitro transcription; switching mechanism at 5' end of RNA template (SMART) PCR amplification; and global PCR amplification. All methods introduced amplification-dependent noise when mRNA was amplified 108-fold, compared with data from unamplified cDNA. PCR-amplified cDNA demonstrated the smallest number of differences between two parallel replicate samples and the best correlation between independent amplifications from the same cell type, with SMART outperforming global PCR amplification. SMART had the highest true-positive rate and the lowest false-positive rate when comparing expression between two different cell types, but had the lowest absolute discovery rate of all three methods. Direct comparison of the performance of SMART and global PCR amplification on single-cell amounts of total RNA and on single neural stem cells confirmed these findings. CONCLUSION: Under the conditions tested, PCR amplification was more reliable than linear amplification for detecting true expression differences between samples. SMART amplification had a higher true-positive rate than global amplification, but at the expense of a considerably lower absolute discovery rate and a systematic compression of observed expression ratios.

3T3 Cells↗

PubMed2005

A 1 Mb minimal amplicon at 8p11-12 in breast cancer identifies new candidate oncogenes.

Amplification of 8p11-12 is a well-known alteration in human breast cancers but the driving oncogene has not been identified. We have developed a high-resolution comparative genomic hybridization array covering 8p11-12 and analysed 33 primary breast tumors, 20 primary ovarian tumors and 27 breast cancer cell lines. Expression analysis of the genes in the region was carried out by using real-time quantitative PCR and/or oligo-microarray profiling. In all, 24% (8/33) of the breast tumors, 5% (1/20) of the ovary tumors and 15% (4/27) of the cell lines showed 8p11-12 amplification. We identified a 1 Mb segment of common amplification that excludes previously proposed candidate genes. Some of the amplified genes did not show overexpression, whereas for others, overexpression was not specifically attributable to amplification. The genes FLJ14299, C8orf2, BRF2 and RAB11FIP, map within the 8p11-12 minimal amplicon, two have a putative function consistent with an oncogenic role, these four genes showed a strong correlation between amplification and overexpression and are therefore the best candidate driver oncogenes at 8p12.

Breast Neoplasms↗