PubMed Health⌕ Search

PubMed · 15983876

On the structural differences between markers and genomic AC microsatellites.

Abstract

AC microsatellites have proved particularly useful as genetic markers. For some purposes, such as in population biology, the inferences drawn depend on the quantitative values of their mutation rates. This, together with intrinsic biological interest, has led to widespread study of microsatellite mutational mechanisms. Now, however, inconsistencies are appearing in the results of marker-based versus non-marker-based studies of mutational mechanisms. The reasons for this have not been investigated, but one possibility, pursued here, is that the differences result from structural differences between markers and genomic microsatellites. Here we report a comparison between the CEPH AC marker microsatellites and the global population of AC microsatellites in the human genome. AC marker microsatellites are longer than the global average. Controlling for length, marker microsatellites contain on average fewer interruptions, and have longer segments, than their genomic counterparts. Related to this, marker microsatellites show a greater tendency to concentrate the majority of their repeats into one segment. These differences plausibly result from scientists selecting markers for their high polymorphism. In addition to the structural differences, there are differences in the base composition of flanking sequences, marker flanking regions being richer in C and G and poorer in A and T. Our results indicate that there are profound differences between marker and genomic microsatellites that almost certainly affect their mutation rates. There is a need for a unified model of mutational mechanisms that accounts for both marker-derived and genomic observations. A suggestion is made as to how this might be done.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fabio Pardi, Richard M Sibly, M J Wilkinson, John C Whittaker. 2005. On the structural differences between markers and genomic AC microsatellites.. https://doi.org/10.1007/s00239-004-0274-6

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Sp1 is essential for p16 expression in human diploid fibroblasts during senescence.

BACKGROUND: p16(INK4a) tumor suppressor protein has been widely proposed to mediate entrance of the cells into the senescent stage. Promoter of p16(INK4a) gene contains at least five putative GC boxes, named GC-I to V, respectively. Our previous data showed that a potential Sp1 binding site, within the promoter region from -466 to -451, acts as a positive transcription regulatory element. These results led us to examine how Sp1 and/or Sp3 act on these GC boxes during aging in cultured human diploid fibroblasts. METHODOLOGY/PRINCIPAL FINDINGS: Mutagenesis studies revealed that GC-I, II and IV, especially GC-II, are essential for p16(INK4a) gene expression in senescent cells. Electrophoretic mobility shift assays (EMSA) and ChIP assays demonstrated that both Sp1 and Sp3 bind to these elements and the binding activity is enhanced in senescent cells. Ectopic overexpression of Sp1, but not Sp3, induced the transcription of p16(INK4a). Both Sp1 RNAi and Mithramycin, a DNA intercalating agent that interferes with Sp1 and Sp3 binding activities, reduced p16(INK4a) gene expression. In addition, the enhanced binding of Sp1 to p16(INK4a) promoter during cellular senescence appeared to be the result of increased Sp1 binding affinity, not an alteration in Sp1 protein level. CONCLUSIONS/SIGNIFICANCE: All these results suggest that GC- II is the key site for Sp1 binding and increase of Sp1 binding activity rather than protein levels contributes to the induction of p16(INK4a) expression during cell aging.

Base Composition↗

Application of CE for determination of DNA base composition.

DNA base composition expressed as mol% of guanine plus cytosine (% GC) or GC content is a key parameter of bacterial taxonomy and genomic analyses. Direct chemical determination methods such as HPLC as well as indirect methods based on physical properties of deoxyribonucleic acid (DNA), melting point (T(m)), and buoyant density (B(d)) have been conventionally applied to determine the GC content. However, these methods require relatively large amounts of sample DNA, time, and labor. We have developed a protocol to determine the GC content by fine separation of nucleosides with CZE. Genomic DNAs with known GC content from 23 bacterial strains were determined by CE at the optimized conditions of 27 degrees C, 20 kV in 50 mM of NaHCO(3) (pH 9.0) and 70 mM SDS added. Nucleosides from <1 microg of DNA hydrolyzed with nuclease-P1 and bacterial alkaline phosphatase were separated in a 75 microm wide and 80 cm long silica capillary. The nucleoside peak areas were determined at 254 nm in less than 12 min. The CE-based determination of GC content requires only small amounts of DNA, and thus should be applicable to environmental genomics (metagenomics), as >90% of environmental micro-organisms are nonculturable and produce only small amounts of genomic DNA.

Base Composition↗