A database of 209 Drosophila introns was extracted from Genbank (release number 64.0) and examined by a number of methods in order to characterize features that might serve as signals for messenger RNA splicing. A tight distribution of sizes was observed: while the smallest introns in the database are 51 nucleotides, more than half are less than 80 nucleotides in length, and most of these have lengths in the range of 59 -67 nucleotides. Drosophila splice sites found in large and small introns differ in only minor ways from each other and from those found in vertebrate introns. However, larger introns have greater pyrimidine-richness in the region between 11 and 21 nucleotides upstream of 3' splice sites. The Drosophila branchpoint consensus matrix resembles C T A A T (in which branch formation occurs at the underlined A), and differs from the corresponding mammalian signal in the absence of G at the position immediately preceding the branchpoint. The distribution of occurrences of this sequence suggests a minimum distance between 5' splice sites and branchpoints of about 38 nucleotides, and a minimum distance between 3' splice sites and branchpoints of 15 nucleotides. The methods we have used detect no information in exon sequences other than in the few nucleotides immediately adjacent to the splice sites. However, Drosophila resembles many other species in that there is a discontinuity in A+ T content between exons and introns, which are A + T rich.

We recently described a new approach for the rapid characterization of expressed genes by partial DNA sequencing to generate 'expressed sequence tags'. From a set of 600 human brain complementary DNA clones, 348 were informative nuclear-encoded messenger RNAs. We have now partially sequenced 2,672 new, independent cDNA clones isolated from four human brain cDNA libraries to generate 2,375 expressed sequence tags to nuclear-encoded genes. These sequences, together with 348 brain expressed sequence tags from our previous study, comprise more than 2,500 new human genes and 870,769 base pairs of DNA sequence. These data represent an approximate doubling of the number of human genes identified by DNA sequencing and may represent as many as 5% of the genes in the human genome.

A human infant brain cDNA library, made specifically for production of expressed sequence tags (ESTs) was evaluated by partial sequencing of over 1,600 clones. Advantages of this library, constructed for EST sequencing, include the use of directional cloning, size selection, very low numbers of mitochondrial and ribosomal transcripts, short polyA tails, few non-recombinants and a broad representation of transcripts. 37% of the clones were identified, based on matches to over 320 different genes in the public databases. Of these, two proteins similar to the Alzheimer's disease amyloid precursor protein were identified.

Small-subunit rRNA (SSU rRNA) sequencing is a powerful tool to detect, identify, and classify prokaryotic organisms, and there is currently an explosion of SSU rRNA sequencing in the microbiology community. We report unexpectedly high levels of intraspecific variation (within and between strains) of prokaryote SSU rRNA sequences deposited in GenBank. A total of 82% of the prokaryote species with two published SSU rRNA sequences had more variable positions than a 0.1% random sequencing error would predict, and 48% of these sequence pairs had more variable positions than predicted by a 1.0% random sequencing error. Other sources of sequence variability must account for some of this intraspecific variation. Given these results, phylogenetic studies and biodiversity estimates obtained by using prokaryotic SSU rRNA sequences cannot proceed under the assumption that rRNA sequences of single operons from single isolates adequately represent their taxa. Sequencing SSU rRNA molecules from multiple operons and multiple isolates is highly recommended to obtain meaningful phylogenetic hypotheses, as is careful attention to accurate strain identification.The technological advances that have made sequencing rRNA feasible are revolutionizing prokaryotic systematics (22). Because small-subunit rRNA (SSU rRNA) is present in all cells and because it is of sufficient size and variability to provide information, SSU rRNA sequences (16s rRNA sequences in prokaryotes) are currently the most widely used informational macromolecules used in tracing evolution. rRNA sequences obtained from uncultured environmental samples have made the discovery of novel groups of microorganisms possible (5, 13-16). Because so much SSU rRNA sequence information has already been analyzed, it is now possible for microbiologists to sequence the SSU rRNA of an unknown isolate and, by comparing it with the sequences aligned by the Ribosomal Database Project (17), identify the most similar species. Amann et al. (2) call rRNA sequencing the "gold standard" of bacterial identification and classification. The International Journal of Systematic Bacteriology provides a representative view of how SSU rRNA sequences are being used in bacterial systematics. Volume 42 (1992) contained 26 articles (out of 102 articles; 25%) in which SSU rRNA sequence data were used to substantiate a systematic conclusion; volume 43 (1993) contained 40 SSU rRNA articles (out of 130 articles; 31%); and volume 44 (1994) contained 66 SSU rRNA articles (out of 119 articles; 55%). SSU rRNA sequence analyses now dominate bacterial systematic studies at the family, genus, species, and subspecies levels.Interpretation of these analyses depends critically on the informative utility of SSU rRNA sequences at shallow divergence and on the assumption that the rRNA sequences obtained from reference strains represent functional rRNA molecules typical of their taxa. The level of intraspecific variability in SSU rRNA is generally assumed to be low (9, 11, 15, 27).Where differences in published sequences...

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We show that regenerating planarians' normal anterior-posterior pattern can be permanently rewritten by a brief perturbation of endogenous bioelectrical networks. Temporary modulation of regenerative bioelectric dynamics in amputated trunk fragments of planaria stochastically results in a constant ratio of regenerates with two heads to regenerates with normal morphology. Remarkably, this is shown to be due not to partial penetrance of treatment, but a profound yet hidden alteration to the animals' patterning circuitry. Subsequent amputations of the morphologically normal regenerates in water result in the same ratio of double-headed to normal morphology, revealing a cryptic phenotype that is not apparent unless the animals are cut. These animals do not differ from wild-type worms in histology, expression of key polarity genes, or neoblast distribution. Instead, the altered regenerative bodyplan is stored in seemingly normal planaria via global patterns of cellular resting potential. This gradient is functionally instructive, and represents a multistable, epigenetic anatomical switch: experimental reversals of bioelectric state reset subsequent regenerative morphology back to wild-type. Hence, bioelectric properties can stably override genome-default target morphology, and provide a tractable control point for investigating cryptic phenotypes and the stochasticity of large-scale epigenetic controls.

We present the results of the partial sequencing of over 3,400 expressed sequence tags (ESTs) from human brain cDNA clones, which increases the number of distinct genes expressed in the brain, that are represented by ESTs, to about 6,000. By choosing clones in an unbiased manner, it is possible to construct a profile of the transcriptional activity of the brain at different stages. Proteins that comprise the cytoskeleton are the most abundant; however, a large variety of regulatory proteins are also seen. About half of the ESTs predicted to contain a protein-coding region have no matches in the public peptide databases and may represent new gene families.

In addition to the immediate microenvironment, long-range signaling may be an important component of cancer. Molecular-genetic analyses have implicated gap junctions—key mediators of cell-cell communication—in carcinogenesis. We recently showed that the resting voltage potential of distant cell groups is a key determinant of metastatic transformation and tumor induction. Here, we show in the Xenopus laevis model that gap junctional communication (GJC) is a modulator of the long-range bioelectric signaling that regulates tumor formation. Genetic disruption of GJC taking place within tumors, within remote host tissues, or between the host and tumors significantly lowers the incidence of tumors induced by KRAS mutations. The most pronounced suppression of tumor incidence was observed upon GJC disruption taking place farther away from oncogene-expressing cells, revealing a role for GJC in distant cells in the control of tumor growth. In contrast, enhanced GJC communication through the overexpression of wild-type connexin Cx26 increased tumor incidence. Our data confirm a role for GJC in tumorigenesis, and reveal that this effect is non-local. Based on these results and on published data on movement of ions through GJs, we present a quantitative model linking the GJC coupling and bioelectrical state of cells to the ability of oncogenes to initiate tumorigenesis. When integrated with data on endogenous bioelectric signaling during left-right patterning, the model predicts differential tumor incidence outcomes depending on the spatial configurations of gap junction paths relative to tumor location and major anatomical body axes. Testing these predictions, we found that the strongest influence of GJ modulation on tumor suppression by hyperpolarization occurred along the embryonic left-right axis. Together, these data reveal new, long-range aspects of cancer control by the host's physiological parameters.