[
1987]
The concept of developmentally programmed senescence has been outlined by Leonard Hayflick (this volume), and examples from development have been used as exemplars of "developmentally programmed senescence" (Richard Russell, this volume). Unlike development, senescence has probably evolved in the absence of direct selection for increased longevity, perhaps as a direct result of the absence of such selection. (For an excellent review see Charlesworth.) A popular evolutionary model that has received experimental support suggests that senescence may result from pleiotropic effects of selection for adaptive life history characteristics. In the literature on aging, less rigorous arguements have been used to suggest that in human evolution, a delay in the age of senescence has been indirectly selected for by means of so-called longevity assurance or longevity-determinant genes. However, all explanations for the evolution of senescence are theoretical, and, with few exceptions, remain largely untested. Like Dr. Hayflick and Russell, I will assume that by developmental programming we mean genetic specification. I will use a general definition so as not to preclude examples that fail to meet one or more of the rigid criteria defined by Russell (this volume). This less rigid definition of programmed aging is necessary, because unlike development, where genetics has been successfully applied for 50 years, examples of genetic specification of senescent processes are quite few. In the literature on aging, it is still not widely accepted that mutants can alter fundamental patterns of senescent events in well-defined ways. One purpose of this presentation is to outline a few examples. In senescence, large batteries of new genes are not differentially regulated; this is quite unlike development, where many genes are differentially regulated. The molecular etiology of senescence is unknown in almost every instance and, as such, makes the study of aging a fascinating area for inquiry. If senescence is unlike development in lacking differential gene regulation, what are the approaches that are likely to yield useful results in the analysis of senescence and the aging process? The developmental genetic paradigm is a useful, indeed essential, theoretical construct for approaching the aging process in an experimental context. The lack of a suitable model organism in which classical and molecular genetics can be productively combined with other experimental techniques has impeded our understanding of senescence. Despite a general lack of evidence for genetic specification, there are instances where genetic specification is clearly evident; the analysis of mutational events that alter normal senescence in well-defined ways demonstrates this point. These instances also provide experimental models for dissecting the aging
[
Methods Cell Biol,
1995]
ACeDB (A Caenorhabditis elegans Data Base) is a data management and display system that contains a wide range of genomic and other information about C. elegans. This chapter provides an overview of ACeDB for the C. elegans user, focusing in particular on the Macintosh version Macace. Previous reviews of AceDB include those of Thierry-Mieg and Durbin (1992) and Durbin and Thierry-Mieg (1994), which describe the general properties of the whole system, and that by Dunham et al. (1994), which discussed the use of AceDB for physical map data collection and assembly. ACeDB was developed by Jean Thierry-Mieg and Richard Durbin primarily for the C. elegans project, when the genomic sequencing project was just beginning in 1990. The original aim was to create a single database that integrated the genetic and physical maps with both genomic sequence data and the literature references. The forerunner of ACeDB was the program CONTIG9 (Sulston et al., 1988), which was developed to maintain and edit the physical map. CONTIG9 served researchers around the world by providing critical on-line access to the current physical map as it was being constructed (Coulson et al., 1986). This policy of immediate access allowed members of the worm community to see the same data as the people making the map, and proved very successful in maximizing use of the map. The same approach was adopted as a template for ACeDB. These two principles, developing a comprehensive database for all types of genomic and related data and providing public access to the data in the same form as used by the data-collecting laboratories, have continued to underlie developments of ACeDB. Over the last 5 years, a wide range of genome projects relating to other organisms have taken the ACeDB program and used it to develop databases for their own data. ACeDB has been used both in public projects designed to redistribute public data in a coordinated fashion and laboratory-based projects for collecting new data. Others, such as the C. elegans ACeDB, have used the database for both purposes. The reason it has been possible to adapt ACeDB so widely is that its flexible data structure allows new types of objects and new types of information about these objects to be added easily. This chapter describes (1) how to obtain ACeDB and documentation for it, (2) how to access and use the information in ACeDB, and (3) how to use ACeDB as a laboratory-based data managing system. Some of what we discuss is specific to the nematode database, but other information applies to the basic computer software program and, hence, to any database using the ACeDB program.