A new AluI satellite DNA in the root-knot nematode Meloidogyne fallax: relationships with satellites from the sympatric species M. hapla and M. chitwoodi

A highly abundant satellite DNA comprising 20% of the Meloidogyne fallax (Nematoda, Tylenchida) genome was cloned and sequenced. The satellite monomer is 173 bp long and has a high A + T content of 72.3%, with frequent runs of A's and T's. The sequence variability of the monomers is 2.7%, mainly due to random distribution of single-point mutations. A search for evidence of internal repeated subunits in the monomer sequence revealed a 6-bp motif (AAATTT) for which five degenerated repeats, differing by just a single base pair, could be identified. Pairwise comparison of the M. fallax satellite with those from the sympatric species Meloidogyne chitwoodi and Meloidogyne hapla revealed a high sequence similarity (68.39%) with one satellite DNA subfamily in M. chitwoodi, which indicated an unexpected close relationship between them. Given the high copy number and the extreme sequence homogeneity among monomeric units, it may be assumed that the satellite DNA of M. fallax could have evolved through some recent and extensive amplification burst in the nematode genome. In this case, its relatively short life would not yet have allowed the accumulation of random mutations in independent amplified repeats. Considering the morphological resemblance between the two species and their ability to produce interspecific fertile hybrids under controlled conditions, these results indicate that M. fallax may share a common ancestor with M. chitwoodi, from which it could have diverged recently. All these data suggest that M. fallax could be the result of a recent speciation process and show that Meloidogyne satellite DNAs may be of interest to resolve phylogenetic relationships among closely related species from this genus.      

Lowering of blood pressure in hypertensive rats by SKF 64139 and SKF 72223

The effects of a centrally acting phenylethanolamine N-methyl-transferase (PNMT) inhibitor, SKF 64139, and of its analog, SKF 72223, which is devoid of PNMT inhibitory activity on blood pressure and heart rate, were investigated in spontaneously hypertensive rats (SHR) and in DOCA-salt hypertensive rats. SKF 64139 lowers blood pressure and decreases pulse rate, while SKF 72223 lowers blood pressure and transiently increases pulse rate in SH-rats and in DOCA-salt hypertensive rats. SKF 72223 has no effect on blood pressure or heart rate in normotensive Wister-Kyoto rats. These results suggest that the antihypertensive action elicited by these two tetrahydroisoquinoline (TIQ) derivatives is not due to lowering of central epinephrine (E) levels. To determine whether the cardiovascular response elicited by SKF 72223 is due to stimulation of presynaptic alpha 2-adrenoreceptors, or to blockade of alpha 1-adrenoreceptors, we have examined its effect in combination with the partial alpha 2-agonist clonidine, or with the alpha 1-antagonist prazosin. The administration of clonidine slightly decreases the antihypertensive action of SKF 72223. The clonidine induced reduction in pulse rate is reversed by SKF 72223. In animals pretreated with prazosin, SKF 72223 elicits an additional decrease in blood pressure. Since SKF 64139 and SKF 72223 interact with alpha 2-adrenoreceptors, it is suggested that blockade of peripheral vascular alpha 2-adrenoreceptors might be in part responsible for their antihypertensive action. However, the antihypertensive action of these two drugs might also be due to some central mechanisms.     

Can Zipf's law be adapted to normalize microarrays?

Background  

Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented.