Genetics and Biology: A Comment on the Significance of the Elston-Stewart Algorithm

Abstract

This article recounts the background to the development of the Elston-Stewart algorithm for the genetic analysis of pedigree data. The algorithm can be used in the context of two contrasting research programmes. The first approach is analytical and reductionist. Traditional biological disciplines, such as physiology, embryology and comparative biology, describe phenomenological domains in which biological organisms are treated as complex systems with emergent properties. In the reductionist approach, these biological domains are largely abandoned in favour of descriptions in the domain of the component elements of these systems, resulting in a concentration on molecular genetics as the central object of biological science. In the second approach, it is explicitly recognized that genes and molecules, per se, cannot be explanatory with respect to emergent systemic properties. However, since the genetic variation which occurs in natural populations can influence virtually every aspect and level of biological organization, from cell lineages to ecology, the study of such variation opens new possibilities for establishing meaningful articulations between the various biological disciplines. The author’s expressed preference is for the second alternative.

The potential role for emergence in autism

“…A number of researchers have promoted the value of viewing psychiatric problems and mental disorders in the context of complexity science [Merikangas et al, 2006;Stewart, 1992]. The concept of emergence is implicit in much of the thinking about how behavioral styles and patterns of cognition arise from the non-linear interaction of underlying factors ranging from the molecular, anatomical, and symptom levels.…”

Towards the Genetic Analysis of Mulfactorial Diseases: The Estimation of Allele Frequency and Epistasis

“…As mentioned in the introduction, the perspective of this paper has been to enrol formal genetics in order to frame questions that it may only be possible to answer by articulating the genetics with experimental physiology [4,7]. More specifically, the major conclusion of this paper is that susceptibility alleles for multifactorial genetic diseases appear to be high, 20% or even more; if correct, this calls for a substantial shift in perspective.…”

“…However, this does not exactly correspond to the original motivation of one of its authors. As explained by Stewart [4], the initial impetus for developing the E-S algorithm came from the work of Thoday [5], who showed that the 'polygenes' responsible for quantitative variation in Drosophila were limited in number and could be individually identified. Building on this, Spickett [6] showed that the 'polygenes' thus identified each had distinct, characteristic developmental and physiological effects.…”