Literature DB >> 32665691

Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait.

Xiang Ma1,2,3, Ole F Christensen3, Hongding Gao3, Ruihua Huang1, Bjarne Nielsen4, Per Madsen3, Just Jensen3, Tage Ostersen4, Pinghua Li1, Mahmoud Shirali3, Guosheng Su5.   

Abstract

Records on groups of individuals could be valuable for predicting breeding values when a trait is difficult or costly to measure on single individuals, such as feed intake and egg production. Adding genomic information has shown improvement in the accuracy of genetic evaluation of quantitative traits with individual records. Here, we investigated the value of genomic information for traits with group records. Besides, we investigated the improvement in accuracy of genetic evaluation for group-recorded traits when including information on a correlated trait with individual records. The study was based on a simulated pig population, including three scenarios of group structure and size. The results showed that both the genomic information and a correlated trait increased the accuracy of estimated breeding values (EBVs) for traits with group records. The accuracies of EBV obtained from group records with a size 24 were much lower than those with a size 12. Random assignment of animals to pens led to lower accuracy due to the weaker relationship between individuals within each group. It suggests that group records are valuable for genetic evaluation of a trait that is difficult to record on individuals, and the accuracy of genetic evaluation can be considerably increased using genomic information. Moreover, the genetic evaluation for a trait with group records can be greatly improved using a bivariate model, including correlated traits that are recorded individually. For efficient use of group records in genetic evaluation, relatively small group size and close relationships between individuals within one group are recommended.

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Mesh:

Year:  2020        PMID: 32665691      PMCID: PMC7852592          DOI: 10.1038/s41437-020-0339-3

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.821


  27 in total

1.  Single-step methods for genomic evaluation in pigs.

Authors:  O F Christensen; P Madsen; B Nielsen; T Ostersen; G Su
Journal:  Animal       Date:  2012-04-05       Impact factor: 3.240

2.  Estimation of heritability and breeding values for early egg production in laying hens from pooled data.

Authors:  F Biscarini; H Bovenhuis; E D Ellen; S Addo; J A M van Arendonk
Journal:  Poult Sci       Date:  2010-09       Impact factor: 3.352

3.  Estimation of variance components and prediction of breeding values using pooled data.

Authors:  F Biscarini; H Bovenhuis; J A M van Arendonk
Journal:  J Anim Sci       Date:  2008-06-06       Impact factor: 3.159

4.  Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score.

Authors:  I Aguilar; I Misztal; D L Johnson; A Legarra; S Tsuruta; T J Lawlor
Journal:  J Dairy Sci       Date:  2010-02       Impact factor: 4.034

5.  Improving genetic evaluation of litter size and piglet mortality for both genotyped and nongenotyped individuals using a single-step method.

Authors:  X Guo; O F Christensen; T Ostersen; Y Wang; M S Lund; G Su
Journal:  J Anim Sci       Date:  2015-02       Impact factor: 3.159

6.  Model comparison on genomic predictions using high-density markers for different groups of bulls in the Nordic Holstein population.

Authors:  H Gao; G Su; L Janss; Y Zhang; M S Lund
Journal:  J Dairy Sci       Date:  2013-05-06       Impact factor: 4.034

7.  The upper esophageal sphincter in the cat: the role of central innervation assessed by transient vagal blockade.

Authors:  R P Reynolds; G W Effer; M P Bendeck
Journal:  Can J Physiol Pharmacol       Date:  1987-01       Impact factor: 2.273

8.  Prediction of genetic values for feed intake from individual body weight gain and total feed intake of the pen.

Authors:  A J Cooper; C L Ferrell; L V Cundiff; L D Van Vleck
Journal:  J Anim Sci       Date:  2010-02-26       Impact factor: 3.159

9.  Genomic prediction when some animals are not genotyped.

Authors:  Ole F Christensen; Mogens S Lund
Journal:  Genet Sel Evol       Date:  2010-01-27       Impact factor: 4.297

10.  Comparison of single-trait and multiple-trait genomic prediction models.

Authors:  Gang Guo; Fuping Zhao; Yachun Wang; Yuan Zhang; Lixin Du; Guosheng Su
Journal:  BMC Genet       Date:  2014-03-04       Impact factor: 2.797

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