The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.

Hybridization of rRNAs to microarrays is a promising approach for prokaryotic and eukaryotic species identification. Typically, the amount of bound target is measured by fluorescent intensity and it is assumed that the signal intensity is directly related to the target concentration. Using thirteen different eukaryotic LSU rRNA target sequences and 7693 short perfect match oligonucleotide probes, we have assessed current approaches for predicting signal intensities by comparing Gibbs free energy (ΔG°) calculations to experimental results. Our evaluation revealed a poor statistical relationship between predicted and actual intensities. Although signal intensities for a given target varied up to 70-fold, none of the predictors were able to fully explain this variation. Also, no combination of different free energy terms, as assessed by principal component and neural network analyses, provided a reliable predictor of hybridization efficiency. We also examined the effects of single-base pair mismatch (MM) (all possible types and positions) on signal intensities of duplexes. We found that the MM effects differ from those that were predicted from solution-based hybridizations. These results recommend against the application of probe design software tools that use thermodynamic parameters to assess probe quality for species identification. Our results imply that the thermodynamic properties of oligonucleotide hybridization are by far not yet understood.

The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of Staphylococcus epidermidis (38 nucleotides) and Nitrosomonas eutropha (39 nucleotides) were hybridized to perfectmatch probes (18-mer and 19-mer) and to a set of probes having all possible single-base-pair mismatches. The melting profiles of all probe-target duplexes were determined in parallel by using an imposed temperature step gradient. We derived an optimum wash temperature for each probe and target by using a simple formula to calculate a discrimination index for each temperature of the step gradient. This optimum corresponded to the output of an independent analysis using a customized neural network program. These results together provide an experimental and analytical framework for optimizing mismatch discrimination among all probes on a DNA microarray.DNA microarray technology provides parallel nucleic acid hybridizations for a large number of immobilized oligonucleotides or larger DNA fragments on a small surface area (21). In clinical and environmental microbiology, this technology has been used for assessing gene expression (19), characterizing whole genomes (5), identifying bacteria (8, 10, 28), and monitoring microbial populations (12,22). We anticipate that, in the next several years, the application of DNA microarrays to environmental microbiology will greatly improve the understanding of complex microbial communities, which are typically composed of many microbial species.In general, oligonucleotide DNA microarrays containing 15-to 25-mer oligonucleotide probes provide greater discrimination than microarrays composed of larger PCR-amplified DNA fragments. However, a central challenge to the application of DNA microarrays in environmental microbiology is achieving the specificity needed to resolve complex microbial populations, including discriminating between target and nontarget populations that differ by a single nucleotide (10). This level of specificity is needed to resolve variants of highly conserved genes (e.g., those encoding the rRNAs) and to distinguish between closely related target and nontarget microorganisms.In conventional hybridization assays, single-base-pair discrimination is achieved by adjusting the hybridization conditions (e.g., temperature, ionic strength, or formamide concentration) or washing conditions (dissociation) of the probe-target duplex (31). In DNA microarray assays, however, this approach is difficult to use since one set of hybridization and wash conditions does not provide optimal target discrimination for all probes on the microarray. We therefore have developed an alternative approach that uses differences in thermal dissociation rates of probe-target duplexes to resolve matched and mismatched probe-target duplexes (13,25).The oligonucleotide DNA microarray used ...

In life, genetic and epigenetic networks precisely coordinate the expression of genes—but in death, it is not known if gene expression diminishes gradually or abruptly stops or if specific genes and pathways are involved. We studied this by identifying mRNA transcripts that apparently increase in relative abundance after death, assessing their functions, and comparing their abundance profiles through postmortem time in two species, mouse and zebrafish. We found mRNA transcript profiles of 1063 genes became significantly more abundant after death of healthy adult animals in a time series spanning up to 96 h postmortem. Ordination plots revealed non-random patterns in the profiles by time. While most of these transcript levels increased within 0.5 h postmortem, some increased only at 24 and 48 h postmortem. Functional characterization of the most abundant transcripts revealed the following categories: stress, immunity, inflammation, apoptosis, transport, development, epigenetic regulation and cancer. The data suggest a step-wise shutdown occurs in organismal death that is manifested by the apparent increase of certain transcripts with various abundance maxima and durations.

> Abstract Diazotroph assemblage compositions were assessed in rhizosphere sediments from the tall and short form Spartina alterniflora growth zones over an annual cycle. Sediment cores were collected for DNA extraction and nitrogenase (acetylene reduction) activity assays, and porewater samples were analyzed for several chemical parameters in March, June, September, and December 1997. These data were collected to determine if within- or between-zone differences in the diazotroph assemblage composition correlated with differences in key environmental variables or acetylene reduction activity. Acetylene reduction rates differed between zones and within a zone over an annual period. Soluble sulfide concentrations were higher in the short form S. alterniflora zone on all dates except those in June and differed within both zones on different sample dates. nifH sequences were recovered from rhizosphere sediment DNA by PCR amplification using nifH specific primers. These amplimers were analyzed using denaturing gradient gel electrophoresis (DGGE), and the resulting patterns were compared by neural network and linear discriminant analyses. Ten prominent amplimers, four of which were apparent heteroduplexes, were observed. DGGE banding profiles showed minor differences among sampling dates and between sample zones, but the overall banding pattern was remarkably consistent. This reflects overall similarity between the amplifiable diazotroph assemblages in the tall and short S. alterniflora growth zones and substantial seasonal stability in assemblage composition.http://link.springer-ny.com/link/service/journals/00248/bibs/38n2p157.html