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Genetics of aging is generally concerned with life extension associated with genetic alterations, rather than with accelerated aging diseases leading to reduction in lifespan. The first mutation found to increase longevity in an animal was the age-1 gene in Caenorhabditis elegans .
The somatic mutation theory of ageing states that accumulation of mutations in somatic cells is the primary cause of aging. A comparison of somatic mutation rate across several mammal species found that the total number of accumulated mutations at the end of lifespan was roughly equal across a broad range of lifespans. [ 16 ]
Genetic theories of aging propose that aging is programmed within each individual's genes. According to this theory, genes dictate cellular longevity. Programmed cell death, or apoptosis , is determined by a "biological clock" via genetic information in the nucleus of the cell.
Aging theories based on evolvability; Aging theories based on group selection; Antagonistic pleiotropy hypothesis; C. ... Genetic mutation theory of aging; I.
Strength of natural selection plot as a function of age. The antagonistic pleiotropy hypothesis (APT) is a theory in evolutionary biology that suggests certain genes may confer beneficial effects early in an organism's life, enhancing reproductive success, while also causing detrimental effects later in life, contributing to the aging process.
Despite Charles Darwin's completion of his theory of biological evolution in the 19th century, the modern logical framework for evolutionary theories of aging wouldn't emerge until almost a century later. Though August Weismann did propose his theory of programmed death, it was met with criticism and never gained mainstream attention. [3]
The mitochondrial theory of ageing has two varieties: free radical and non-free radical. The first is one of the variants of the free radical theory of ageing. It was formulated by J. Miquel and colleagues in 1980 [1] and was developed in the works of Linnane and coworkers (1989). [2] The second was proposed by A. N. Lobachev in 1978. [3]
Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population of programs. It applies the genetic operators selection according to a predefined fitness measure , mutation and crossover .