Fluorescent RNA cytochemistry: tracking gene transcripts in living cells

The advent of jellyfish green fluorescent protein and its spectral variants, together with promising new fluorescent proteins from other classes of the Cnidarian phylum (coral and anemones), has greatly enhanced and promises to further boost the detection and localization of proteins in cell biology. It has been less widely appreciated that highly sensitive methods have also recently been developed for detecting the movement and localization in living cells of the very molecules that precede proteins in the gene expression pathway, i.e. RNAs. These approaches include the microinjection of fluorescent RNAs into living cells, the in vivo hybridization of fluorescent oligonucleotides to endogenous RNAs and the expression in cells of fluorescent RNA-binding proteins. This new field of ‘fluorescent RNA cytochemistry’ is summarized in this article, with emphasis on the biological insights it has already provided. These new techniques are likely to soon collaborate with other emerging approaches to advance the investigation of RNA birth, RNA–protein assembly and ribonucleoprotein particle transport in systems such as oocytes, embryos, neurons and other somatic cells, and may even permit the observation of viral replication and transcription pathways as they proceed in living cells, ushering in a new era of nucleic acids research in vivo.

The Molecular Biology Database Collection: an updated compilation of biological database resources

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists’ attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries of each of the databases included in the Collection are available through the Nucleic Acids Research Web site, at http://www.nar.oupjournals.org.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

Mathematical approaches to comparative linguistics‡

The inference of the evolutionary history of a set of languages is a complex problem. Although some languages are known to be related through descent from common ancestral languages, for other languages determining whether such a relationship holds is itself a difficult problem. In this paper we report on new methods, developed by linguists Johanna Nichols (University of California, Berkeley), Donald Ringe and Ann Taylor (University of Pennsylvania, Philadelphia), and me, for answering some of the most difficult questions in this domain. These methods and the results of the analyses based on these methods were presented in November 1995 at the Symposium on the Frontiers of Science held by the National Academy of Sciences.

Genetic analysis of type 1 diabetes using whole genome approaches.

Whole genome linkage analysis of type 1 diabetes using affected sib pair families and semi-automated genotyping and data capture procedures has shown how type 1 diabetes is inherited. A major proportion of clustering of the disease in families can be accounted for by sharing of alleles at susceptibility loci in the major histocompatibility complex on chromosome 6 (IDDM1) and at a minimum of 11 other loci on nine chromosomes. Primary etiological components of IDDM1, the HLA-DQB1 and -DRB1 class II immune response genes, and of IDDM2, the minisatellite repeat sequence in the 5' regulatory region of the insulin gene on chromosome 11p15, have been identified. Identification of the other loci will involve linkage disequilibrium mapping and sequencing of candidate genes in regions of linkage.

Gene targeting approaches to complex genetic diseases: atherosclerosis and essential hypertension.

Gene targeting allows precise, predetermined changes to be made in a chosen gene in the mouse genome. To date, targeting has been used most often for generation of animals completely lacking the product of a gene of interest. The resulting "knockout" mice have confirmed some hypotheses, have upset others, but have rarely been uninformative. Models of several human genetic diseases have been produced by targeting--including Gaucher disease, cystic fibrosis, and the fragile X syndrome. These diseases are primarily determined by defects in single genes, and their modes of inheritance are well understood. When the disease under study has a complex etiology with multiple genetic and environmental components, the generation of animal models becomes more difficult but no less valuable. The problems associated with dissecting out the individual genetic factors also increases substantially and the distinction between causation and correlation is often difficult. To prove causation in a complex system requires rigorous adherence to the principle that the experiments must allow detection of the effects of changing only a single variable at one time. Gene targeting experiments, when properly designed, can test the effects of a precise genetic change completely free from the effects of differences in any other genes (linked or unlinked to the test gene). They therefore allow proofs of causation.