Literature DB >> 20308103

Mutation and the evolution of ageing: from biometrics to system genetics.

Kimberly A Hughes1.   

Abstract

A notable success for evolutionary genetics during the past century was to generate a coherent, quantitative explanation for an apparent evolutionary paradox: the tendency for multicellular organisms to show declining fitness with age (senescence, often referred to simply as 'ageing'). This general theory is now widely accepted and explains most of the features of senescence that are observed in natural and laboratory populations, but specific instantiations of that theory have been more controversial. To date, most of the empirical tests of these models have relied on data generated from biometric experiments. Modern population genetics and genomics provide new, and probably more powerful, ways to test ideas that are still controversial more than half a century after the original theory was developed. System-genetic experiments have the potential to address both evolutionary and mechanistic questions about ageing by identifying causal loci and the genetic networks with which they interact. Both the biometrical approaches and the newer approaches are reviewed here, with an emphasis on the challenges and limitations that each method faces.

Mesh:

Year:  2010        PMID: 20308103      PMCID: PMC2871812          DOI: 10.1098/rstb.2009.0265

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  62 in total

1.  Sex-specific quantitative trait loci affecting longevity in Drosophila melanogaster.

Authors:  S V Nuzhdin; E G Pasyukova; C L Dilda; Z B Zeng; T F Mackay
Journal:  Proc Natl Acad Sci U S A       Date:  1997-09-02       Impact factor: 11.205

2.  Quantitative trait loci with age-specific effects on fecundity in Drosophila melanogaster.

Authors:  Jeff Leips; Paul Gilligan; Trudy F C Mackay
Journal:  Genetics       Date:  2005-11-04       Impact factor: 4.562

Review 3.  Toward a unified theory of caloric restriction and longevity regulation.

Authors:  David A Sinclair
Journal:  Mech Ageing Dev       Date:  2005-09       Impact factor: 5.432

4.  Hamilton's indicators of the force of selection.

Authors:  Annette Baudisch
Journal:  Proc Natl Acad Sci U S A       Date:  2005-05-26       Impact factor: 11.205

5.  Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster.

Authors:  Stuart J Macdonald; Anthony D Long
Journal:  Genetics       Date:  2007-04-15       Impact factor: 4.562

Review 6.  Separating cause from effect: how does insulin/IGF signalling control lifespan in worms, flies and mice?

Authors:  M D W Piper; C Selman; J J McElwee; L Partridge
Journal:  J Intern Med       Date:  2008-02       Impact factor: 8.989

7.  From genotype to phenotype: systems biology meets natural variation.

Authors:  Philip N Benfey; Thomas Mitchell-Olds
Journal:  Science       Date:  2008-04-25       Impact factor: 47.728

8.  Adaptive evolution of a candidate gene for aging in Drosophila.

Authors:  P S Schmidt; D D Duvernell; W F Eanes
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-26       Impact factor: 11.205

9.  Phenotypic variation and natural selection at catsup, a pleiotropic quantitative trait gene in Drosophila.

Authors:  Mary Anna Carbone; Katherine W Jordan; Richard F Lyman; Susan T Harbison; Jeff Leips; Theodore J Morgan; Maria DeLuca; Philip Awadalla; Trudy F C Mackay
Journal:  Curr Biol       Date:  2006-05-09       Impact factor: 10.834

10.  Age-specific patterns of genetic variance in Drosophila melanogaster. I. Mortality.

Authors:  D E Promislow; M Tatar; A A Khazaeli; J W Curtsinger
Journal:  Genetics       Date:  1996-06       Impact factor: 4.562

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  13 in total

1.  The population genetics of mutations: good, bad and indifferent.

Authors:  Laurence Loewe; William G Hill
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

Review 2.  What can whole genome expression data tell us about the ecology and evolution of personality?

Authors:  Alison M Bell; Nadia Aubin-Horth
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-12-27       Impact factor: 6.237

3.  Age-specific variation in immune response in Drosophila melanogaster has a genetic basis.

Authors:  Tashauna M Felix; Kimberly A Hughes; Eric A Stone; Jenny M Drnevich; Jeff Leips
Journal:  Genetics       Date:  2012-05-02       Impact factor: 4.562

Review 4.  Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses.

Authors:  Kimberly A Hughes; Jeff Leips
Journal:  Ann N Y Acad Sci       Date:  2016-12-09       Impact factor: 5.691

5.  Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli.

Authors:  Sandra Trindade; Lilia Perfeito; Isabel Gordo
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

6.  Genomic basis of aging and life-history evolution in Drosophila melanogaster.

Authors:  Silvia C Remolina; Peter L Chang; Jeff Leips; Sergey V Nuzhdin; Kimberly A Hughes
Journal:  Evolution       Date:  2012-06-27       Impact factor: 3.694

7.  Genome-wide association study of extreme longevity in Drosophila melanogaster.

Authors:  Molly K Burke; Elizabeth G King; Parvin Shahrestani; Michael R Rose; Anthony D Long
Journal:  Genome Biol Evol       Date:  2014-01       Impact factor: 3.416

8.  Vitellogenin family gene expression does not increase Drosophila lifespan or fecundity.

Authors:  Yingxue Ren; Kimberly A Hughes
Journal:  F1000Res       Date:  2014-06-10

Review 9.  Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster.

Authors:  Thomas Flatt
Journal:  Genetics       Date:  2020-01       Impact factor: 4.562

10.  Fitness is strongly influenced by rare mutations of large effect in a microbial mutation accumulation experiment.

Authors:  Karl Heilbron; Macarena Toll-Riera; Mila Kojadinovic; R Craig MacLean
Journal:  Genetics       Date:  2014-05-08       Impact factor: 4.562

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