Literature DB >> 17492959

Inferring purging from pedigree data.

Davorka Gulisija1, James F Crow.   

Abstract

The harmful effects of inbreeding can be reduced if deleterious recessive alleles were removed (purged) by selection against homozygotes in earlier generations. If only a few generations are involved, purging is due almost entirely to recessive alleles that reduce fitness to near zero. In this case the amount of purging and allele frequency change can be inferred approximately from pedigree data alone and are independent of the allele frequency. We examined pedigrees of 59,778 U.S. Jersey cows. Most of the pedigrees were for six generations, but a few went back slightly farther. Assuming recessive homozygotes have fitness 0, the reduction of total genetic load due to purging is estimated at 17%, but most of this is not expressed, being concealed by dominant alleles. Considering those alleles that are currently expressed due to inbreeding, the estimated amount of purging is such as to reduce the expressed load (inbreeding depression) in the current generation by 12.6%. That the reduction is not greater is due mainly to (1) generally low inbreeding levels because breeders in the past have tended to avoid consanguineous matings, and (2) there is essentially no information more than six generations back. The methods used here should be applicable to other populations for which there is pedigree information.

Entities:  

Mesh:

Year:  2007        PMID: 17492959     DOI: 10.1111/j.1558-5646.2007.00088.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  12 in total

1.  Understanding and predicting the fitness decline of shrunk populations: inbreeding, purging, mutation, and standard selection.

Authors:  Aurora García-Dorado
Journal:  Genetics       Date:  2012-01-31       Impact factor: 4.562

2.  A simple method to account for natural selection when predicting inbreeding depression.

Authors:  Aurora García-Dorado
Journal:  Genetics       Date:  2008-09-14       Impact factor: 4.562

3.  Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle.

Authors:  Jennie E Pryce; Mekonnen Haile-Mariam; Michael E Goddard; Ben J Hayes
Journal:  Genet Sel Evol       Date:  2014-11-18       Impact factor: 4.297

4.  Detection of genetic purging and predictive value of purging parameters estimated in pedigreed populations.

Authors:  Eugenio López-Cortegano; Diego Bersabé; Jinliang Wang; Aurora García-Dorado
Journal:  Heredity (Edinb)       Date:  2018-02-13       Impact factor: 3.821

5.  Genome-Wide Comprehensive Survey of the Subtilisin-Like Proteases Gene Family Associated With Rice Caryopsis Development.

Authors:  Kaifeng Zheng; Lu Pang; Xiuhua Xue; Ping Gao; Heping Zhao; Yingdian Wang; Shengcheng Han
Journal:  Front Plant Sci       Date:  2022-06-20       Impact factor: 6.627

6.  Microsatellite support for active inbreeding in a cichlid fish.

Authors:  Kathrin Langen; Julia Schwarzer; Harald Kullmann; Theo C M Bakker; Timo Thünken
Journal:  PLoS One       Date:  2011-09-30       Impact factor: 3.240

7.  Investigation of regions impacting inbreeding depression and their association with the additive genetic effect for United States and Australia Jersey dairy cattle.

Authors:  Jeremy T Howard; Mekonnen Haile-Mariam; Jennie E Pryce; Christian Maltecca
Journal:  BMC Genomics       Date:  2015-10-19       Impact factor: 3.969

8.  A simple strategy for managing many recessive disorders in a dairy cattle breeding program.

Authors:  John B Cole
Journal:  Genet Sel Evol       Date:  2015-11-30       Impact factor: 4.297

9.  A multivariate analysis with direct additive and inbreeding depression load effects.

Authors:  Luis Varona; Juan Altarriba; Carlos Moreno; María Martínez-Castillero; Joaquim Casellas
Journal:  Genet Sel Evol       Date:  2019-12-26       Impact factor: 4.297

10.  Inbreeding depression for kit survival at birth in a rabbit population under long-term selection.

Authors:  Ino Curik; György Kövér; János Farkas; Zsolt Szendrő; Róbert Romvári; Johann Sölkner; Istvan Nagy
Journal:  Genet Sel Evol       Date:  2020-07-08       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.