Literature DB >> 19147924

Maintaining evolvability.

James F Crow1.   

Abstract

Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy is yet to be determined. It is likely that only a case-by-case analysis will provide the answers. Despite the difficulties that complex interactions cause for evolution in Mendelian populations, such populations nevertheless evolve very well. Longlasting species must have evolved mechanisms for coping with such problems. Since such difficulties do not arise in asexual populations, a comparison of epistatic patterns in closely related sexual and asexual species might provide some important insights.

Entities:  

Mesh:

Year:  2008        PMID: 19147924     DOI: 10.1007/s12041-008-0057-8

Source DB:  PubMed          Journal:  J Genet        ISSN: 0022-1333            Impact factor:   1.166


  17 in total

1.  Selection in animals: synthesis.

Authors:  A ROBERTSON
Journal:  Cold Spring Harb Symp Quant Biol       Date:  1955

2.  An advantage of sexual reproduction in a rapidly changing environment.

Authors:  J F Crow
Journal:  J Hered       Date:  1992 May-Jun       Impact factor: 2.645

3.  Genetics. A century of corn selection.

Authors:  William G Hill
Journal:  Science       Date:  2005-02-04       Impact factor: 47.728

4.  Attainment of Quasi Linkage Equilibrium When Gene Frequencies Are Changing by Natural Selection.

Authors:  M Kimura
Journal:  Genetics       Date:  1965-11       Impact factor: 4.562

5.  The evolution of epistasis and the advantage of recombination in populations of bacteriophage T4.

Authors:  R L Malmberg
Journal:  Genetics       Date:  1977-07       Impact factor: 4.562

6.  Genetic architecture of complex traits: large phenotypic effects and pervasive epistasis.

Authors:  Haifeng Shao; Lindsay C Burrage; David S Sinasac; Annie E Hill; Sheila R Ernest; William O'Brien; Hayden-William Courtland; Karl J Jepsen; Andrew Kirby; E J Kulbokas; Mark J Daly; Karl W Broman; Eric S Lander; Joseph H Nadeau
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-09       Impact factor: 11.205

7.  The influence of epistasis on homozygous viability depression in Drosophila melanogaster.

Authors:  R G Temin; H U Meyer; P S Dawson; J F Crow
Journal:  Genetics       Date:  1969-02       Impact factor: 4.562

8.  Predictions of response to artificial selection from new mutations.

Authors:  W G Hill
Journal:  Genet Res       Date:  1982-12       Impact factor: 1.588

Review 9.  Epistasis: too often neglected in complex trait studies?

Authors:  Orjan Carlborg; Chris S Haley
Journal:  Nat Rev Genet       Date:  2004-08       Impact factor: 53.242

Review 10.  Data and theory point to mainly additive genetic variance for complex traits.

Authors:  William G Hill; Michael E Goddard; Peter M Visscher
Journal:  PLoS Genet       Date:  2008-02-29       Impact factor: 5.917

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  13 in total

1.  Clan genomics and the complex architecture of human disease.

Authors:  James R Lupski; John W Belmont; Eric Boerwinkle; Richard A Gibbs
Journal:  Cell       Date:  2011-09-30       Impact factor: 41.582

Review 2.  On epistasis: why it is unimportant in polygenic directional selection.

Authors:  James F Crow
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

3.  Long-term impacts of genome-enabled selection.

Authors:  Nanye Long; Daniel Gianola; Guilherme J M Rosa; Kent A Weigel
Journal:  J Appl Genet       Date:  2011-05-17       Impact factor: 3.240

4.  The relation between the genetic architecture of quantitative traits and long-term genetic response.

Authors:  Rostam Abdollahi-Arpanahi; Abbas Pakdel; Ardeshir Nejati-Javaremi; Mohammad Moradi Shahrbabak; Farhad Ghafouri-Kesbi
Journal:  J Appl Genet       Date:  2014-03-27       Impact factor: 3.240

5.  The QTN program and the alleles that matter for evolution: all that's gold does not glitter.

Authors:  Matthew V Rockman
Journal:  Evolution       Date:  2011-11-06       Impact factor: 3.694

6.  Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod.

Authors:  David B Stern; Nathan W Anderson; Juanita A Diaz; Carol Eunmi Lee
Journal:  Nat Commun       Date:  2022-07-12       Impact factor: 17.694

Review 7.  Pitfalls of predicting complex traits from SNPs.

Authors:  Naomi R Wray; Jian Yang; Ben J Hayes; Alkes L Price; Michael E Goddard; Peter M Visscher
Journal:  Nat Rev Genet       Date:  2013-07       Impact factor: 53.242

8.  Genetic and environmental factors affecting cryptic variations in gene regulatory networks.

Authors:  Watal M Iwasaki; Masaki E Tsuda; Masakado Kawata
Journal:  BMC Evol Biol       Date:  2013-04-26       Impact factor: 3.260

9.  Understanding and using quantitative genetic variation.

Authors:  William G Hill
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-01-12       Impact factor: 6.237

10.  Fusion of large-scale genomic knowledge and frequency data computationally prioritizes variants in epilepsy.

Authors:  Ian M Campbell; Mitchell Rao; Sean D Arredondo; Seema R Lalani; Zhilian Xia; Sung-Hae L Kang; Weimin Bi; Amy M Breman; Janice L Smith; Carlos A Bacino; Arthur L Beaudet; Ankita Patel; Sau Wai Cheung; James R Lupski; Paweł Stankiewicz; Melissa B Ramocki; Chad A Shaw
Journal:  PLoS Genet       Date:  2013-09-26       Impact factor: 5.917

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