Circadian Fluctuations Of Period Protein Immunoreactivity In The CNS And Visual System Of Drosophila

When the protein encoded by the period (per) gene, which influences circadian rhythms in Drosophila melanogaster, was labeled with an anti- per antibody in adult flies sectioned at different times of day, regular fluctuations in the intensity of immunoreactivity were observed in cells of the visual system and central brain. These fluctuations persisted in constant darkness. Time courses of the changing levels of staining were altered in the per-short mutant: in light/dark cycles, the phase was earlier than in wild-type, and in constant darkness the period was shorter. In a per-long mutant and in behaviorally subnormal germline transformants (involving transduced per DNA), staining intensities were much fainter than in wild-type. Factors involved in initiating or maintaining the per protein cycling were investigated by examining the immunoreactivity in visual system mutants and by exposing wild-type flies to altered light/dark regimes. These genetic and environmental manipulations affected the expression of the per protein in ways that usually parallelled their effects on circadian behaviors

A common core RNP structure shared between the small nuclear box C/D RNPs and the spliceosomal U 4 snRNP.

AbstractThe box C/D snoRNAs function in directing 2′-O-methylation and/or as chaperones in the processing of ribosomal RNA. We show here that Snu13p (15.5kD in human), a component of the U4/U6.U5 tri-snRNP, is also associated with the box C/D snoRNAs. Indeed, genetic depletion of Snu13p in yeast leads to a major defect in RNA metabolism. The box C/D motif can be folded into a stem-internal loop-stem structure, almost identical to the 15.5kD binding site in the U4 snRNA. Consistent with this, the box C/D motif binds Snu13p/15.5kD in vitro. The similarities in structure and function observed between the U4 snRNP (chaperone for U6) and the box C/D snoRNPs raises the interesting possibility that these particles may have evolved from a common ancestral RNP

Genome-Wide Analysis of Light- and Temperature-Entrained Circadian Transcripts in Caenorhabditis elegans

Transcriptional profiling experiments identify light- and temperature-entrained circadian transcripts in C. elegans

High-Resolution Positional Tracking for Long-Term Analysis of Drosophila Sleep and Locomotion Using the “Tracker” Program

Drosophila melanogaster has been used for decades in the study of circadian behavior, and more recently has become a popular model for the study of sleep. The classic method for monitoring fly activity involves counting the number of infrared beam crosses in individual small glass tubes. Incident recording methods such as this can measure gross locomotor activity, but they are unable to provide details about where the fly is located in space and do not detect small movements (i.e. anything less than half the enclosure size), which could lead to an overestimation of sleep and an inaccurate report of the behavior of the fly. This is especially problematic if the fly is awake, but is not moving distances that span the enclosure. Similarly, locomotor deficiencies could be incorrectly classified as sleep phenotypes. To address these issues, we have developed a locomotor tracking technique (the “Tracker” program) that records the exact location of a fly in real time. This allows for the detection of very small movements at any location within the tube. In addition to circadian locomotor activity, we are able to collect other information, such as distance, speed, food proximity, place preference, and multiple additional parameters that relate to sleep structure. Direct comparisons of incident recording and our motion tracking application using wild type and locomotor-deficient (CASK-β null) flies show that the increased temporal resolution in the data from the Tracker program can greatly affect the interpretation of the state of the fly. This is especially evident when a particular condition or genotype has strong effects on the behavior, and can provide a wealth of information previously unavailable to the investigator. The interaction of sleep with other behaviors can also be assessed directly in many cases with this method

Gene and genon concept: coding versus regulation: A conceptual and information-theoretic analysis of genetic storage and expression in the light of modern molecular biology

We analyse here the definition of the gene in order to distinguish, on the basis of modern insight in molecular biology, what the gene is coding for, namely a specific polypeptide, and how its expression is realized and controlled. Before the coding role of the DNA was discovered, a gene was identified with a specific phenotypic trait, from Mendel through Morgan up to Benzer. Subsequently, however, molecular biologists ventured to define a gene at the level of the DNA sequence in terms of coding. As is becoming ever more evident, the relations between information stored at DNA level and functional products are very intricate, and the regulatory aspects are as important and essential as the information coding for products. This approach led, thus, to a conceptual hybrid that confused coding, regulation and functional aspects. In this essay, we develop a definition of the gene that once again starts from the functional aspect. A cellular function can be represented by a polypeptide or an RNA. In the case of the polypeptide, its biochemical identity is determined by the mRNA prior to translation, and that is where we locate the gene. The steps from specific, but possibly separated sequence fragments at DNA level to that final mRNA then can be analysed in terms of regulation. For that purpose, we coin the new term “genon”. In that manner, we can clearly separate product and regulative information while keeping the fundamental relation between coding and function without the need to introduce a conceptual hybrid. In mRNA, the program regulating the expression of a gene is superimposed onto and added to the coding sequence in cis - we call it the genon. The complementary external control of a given mRNA by trans-acting factors is incorporated in its transgenon. A consequence of this definition is that, in eukaryotes, the gene is, in most cases, not yet present at DNA level. Rather, it is assembled by RNA processing, including differential splicing, from various pieces, as steered by the genon. It emerges finally as an uninterrupted nucleic acid sequence at mRNA level just prior to translation, in faithful correspondence with the amino acid sequence to be produced as a polypeptide. After translation, the genon has fulfilled its role and expires. The distinction between the protein coding information as materialised in the final polypeptide and the processing information represented by the genon allows us to set up a new information theoretic scheme. The standard sequence information determined by the genetic code expresses the relation between coding sequence and product. Backward analysis asks from which coding region in the DNA a given polypeptide originates. The (more interesting) forward analysis asks in how many polypeptides of how many different types a given DNA segment is expressed. This concerns the control of the expression process for which we have introduced the genon concept. Thus, the information theoretic analysis can capture the complementary aspects of coding and regulation, of gene and genon

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them