Literature DB >> 18073292

Changes in connectedness over time in alternative sheep sire referencing schemes.

L A Kuehn1, D R Notter, G J Nieuwhof, R M Lewis.   

Abstract

A statistic to measure the level of connectedness achieved among flocks would help producers to assess the risk of comparing EBV of animals from different flocks. The objectives of this research were to evaluate the pattern of change over time in selected connectedness measures and to determine how effectively these measures quantify the level of risk due to potential bias in EBV comparisons across production units. Connectedness was evaluated using simulated sheep populations, with connections established using sire referencing schemes (SRS). Pedigree and performance data for a single trait with a within-flock heritability of 0.25 were simulated (50 replications) for 15 flocks with 40 to 140 ewes per flock. Genetic means for each flock were sampled from a normal distribution with mean 0 and SD equal to the trait's genetic SD. After 10 yr of random mating, flocks had opportunity to join a SRS and selection began for the simulated trait. Yearling rams were chosen as reference sires randomly from the top one-sixth of the population ranked on BLUP EBV. Every year, in each flock, 3 reference sires were mated to 10 ewes each. Six sire referencing scenarios (including no SRS) and 2 sources of nonreference sires were simulated. Connectedness was measured in 2 ways: (i) as the average prediction error correlation (r(ij)) of the flock genetic means (flock r(ij)) or the EBV for the current crop of ram lambs (lamb r(ij)) or (ii) as the average scaled prediction error variance of differences (PEVD) in flock genetic means (flock PEVD) or in lamb EBV in the current crop of ram lambs (lamb PEVD). Flock r(ij) increased linearly in all scenarios while SRS was underway and leveled off if the flocks discontinued SRS. Lamb r(ij) increased rapidly as soon as SRS began but decreased substantially if the flocks discontinued SRS. Behavior of flock PEVD and lamb PEVD measures were similar but in the opposite direction (i.e., PEVD decreased with increasing r(ij)). Within scenarios, both flock r(ij) and flock PEVD had a nonlinear relationship with bias in comparing animals across flocks. However, only flock r(ij) exhibited a consistent relationship across simulation scenarios. When flock r(ij) reached 0.05 and 0.10, approximately 20 and 10%, respectively, of the bias due to initial differences in flock genetic means remained. These levels of flock r(ij) are suggested as benchmark levels for minimizing the risk of comparing animal EBV among units.

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Year:  2007        PMID: 18073292     DOI: 10.2527/jas.2007-0256

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  8 in total

1.  Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).

Authors:  R Rincent; D Laloë; S Nicolas; T Altmann; D Brunel; P Revilla; V M Rodríguez; J Moreno-Gonzalez; A Melchinger; E Bauer; C-C Schoen; N Meyer; C Giauffret; C Bauland; P Jamin; J Laborde; H Monod; P Flament; A Charcosset; L Moreau
Journal:  Genetics       Date:  2012-08-03       Impact factor: 4.562

2.  The genetic connectedness calculated from genomic information and its effect on the accuracy of genomic prediction.

Authors:  Suo-Yu Zhang; Babatunde Shittu Olasege; Deng-Ying Liu; Qi-Shan Wang; Yu-Chun Pan; Pei-Pei Ma
Journal:  PLoS One       Date:  2018-07-31       Impact factor: 3.240

3.  GCA: an R package for genetic connectedness analysis using pedigree and genomic data.

Authors:  Haipeng Yu; Gota Morota
Journal:  BMC Genomics       Date:  2021-02-15       Impact factor: 3.969

4.  Genomic Relatedness Strengthens Genetic Connectedness Across Management Units.

Authors:  Haipeng Yu; Matthew L Spangler; Ronald M Lewis; Gota Morota
Journal:  G3 (Bethesda)       Date:  2017-10-05       Impact factor: 3.154

5.  Quantifying genomic connectedness and prediction accuracy from additive and non-additive gene actions.

Authors:  Mehdi Momen; Gota Morota
Journal:  Genet Sel Evol       Date:  2018-09-17       Impact factor: 4.297

6.  Do stronger measures of genomic connectedness enhance prediction accuracies across management units?

Authors:  Haipeng Yu; Matthew L Spangler; Ronald M Lewis; Gota Morota
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

7.  Genome-wide association study to identify genetic loci associated with gastrointestinal nematode resistance in Katahdin sheep.

Authors:  G M Becker; K M Davenport; J M Burke; R M Lewis; J E Miller; J L M Morgan; D R Notter; B M Murdoch
Journal:  Anim Genet       Date:  2020-01-03       Impact factor: 3.169

8.  Across-country genetic evaluation of meat sheep from Ireland and the United Kingdom.

Authors:  Shauna Fitzmaurice; Joanne Conington; Kevin McDermott; Noirin McHugh; Georgios Banos
Journal:  J Anim Breed Genet       Date:  2022-02-01       Impact factor: 3.271

  8 in total

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