Cargando…

Changes in genomic predictions when new information is added

The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The object...

Descripción completa

Detalles Bibliográficos
Autores principales: Hidalgo, Jorge, Lourenco, Daniela, Tsuruta, Shogo, Masuda, Yutaka, Miller, Stephen, Bermann, Matias, Garcia, Andre L S, Misztal, Ignacy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867035/
https://www.ncbi.nlm.nih.gov/pubmed/33544869
http://dx.doi.org/10.1093/jas/skab004
_version_ 1783648210865094656
author Hidalgo, Jorge
Lourenco, Daniela
Tsuruta, Shogo
Masuda, Yutaka
Miller, Stephen
Bermann, Matias
Garcia, Andre L S
Misztal, Ignacy
author_facet Hidalgo, Jorge
Lourenco, Daniela
Tsuruta, Shogo
Masuda, Yutaka
Miller, Stephen
Bermann, Matias
Garcia, Andre L S
Misztal, Ignacy
author_sort Hidalgo, Jorge
collection PubMed
description The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The objective of this study was to investigate changes in estimated breeding values (EBV) and genomic EBV (GEBV) across monthly evaluations for 1 yr in a large genotyped population of beef cattle. The American Angus data used included 8.2 million records for birth weight, 8.9 for weaning weight, and 4.4 for postweaning gain. A total of 10.1 million animals born until December 2017 had pedigree information, and 484,074 were genotyped. A truncated dataset included animals born until December 2016. To mimic a scenario with monthly evaluations, 2017 data were added 1 mo at a time to estimate EBV using best linear unbiased prediction (BLUP) and GEBV using single-step genomic BLUP with the algorithm for proven and young (APY) with core group fixed for 1 yr or updated monthly. Predictions from monthly evaluations in 2017 were contrasted with the predictions of the evaluation in December 2016 or the previous month for all genotyped animals born until December 2016 with or without their own phenotypes or progeny phenotypes. Changes in EBV and GEBV were similar across traits, and only results for weaning weight are presented. Correlations between evaluations from December 2016 and the 12 consecutive evaluations were ≥0.97 for EBV and ≥0.99 for GEBV. Average absolute changes for EBV were about two times smaller than for GEBV, except for animals with new progeny phenotypes (≤0.12 and ≤0.11 additive genetic SD [SDa] for EBV and GEBV). The maximum absolute changes for EBV (≤2.95 SDa) were greater than for GEBV (≤1.59 SDa). The average(maximum) absolute GEBV changes for young animals from December 2016 to January and December 2017 ranged from 0.05(0.25) to 0.10(0.53) SDa. Corresponding ranges for animals with new progeny phenotypes were from 0.05(0.88) to 0.11(1.59) SDa for GEBV changes. The average absolute change in EBV(GEBV) from December 2016 to December 2017 for sires with ≤50 progeny phenotypes was 0.26(0.14) and for sires with >50 progeny phenotypes was 0.25(0.16) SDa. Updating the core group in APY without adding data created an average absolute change of 0.07 SDa in GEBV. Genomic evaluations in large genotyped populations are as stable and persistent as the traditional genetic evaluations, with less extreme changes.
format Online
Article
Text
id pubmed-7867035
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-78670352021-02-16 Changes in genomic predictions when new information is added Hidalgo, Jorge Lourenco, Daniela Tsuruta, Shogo Masuda, Yutaka Miller, Stephen Bermann, Matias Garcia, Andre L S Misztal, Ignacy J Anim Sci Animal Genetics and Genomics The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The objective of this study was to investigate changes in estimated breeding values (EBV) and genomic EBV (GEBV) across monthly evaluations for 1 yr in a large genotyped population of beef cattle. The American Angus data used included 8.2 million records for birth weight, 8.9 for weaning weight, and 4.4 for postweaning gain. A total of 10.1 million animals born until December 2017 had pedigree information, and 484,074 were genotyped. A truncated dataset included animals born until December 2016. To mimic a scenario with monthly evaluations, 2017 data were added 1 mo at a time to estimate EBV using best linear unbiased prediction (BLUP) and GEBV using single-step genomic BLUP with the algorithm for proven and young (APY) with core group fixed for 1 yr or updated monthly. Predictions from monthly evaluations in 2017 were contrasted with the predictions of the evaluation in December 2016 or the previous month for all genotyped animals born until December 2016 with or without their own phenotypes or progeny phenotypes. Changes in EBV and GEBV were similar across traits, and only results for weaning weight are presented. Correlations between evaluations from December 2016 and the 12 consecutive evaluations were ≥0.97 for EBV and ≥0.99 for GEBV. Average absolute changes for EBV were about two times smaller than for GEBV, except for animals with new progeny phenotypes (≤0.12 and ≤0.11 additive genetic SD [SDa] for EBV and GEBV). The maximum absolute changes for EBV (≤2.95 SDa) were greater than for GEBV (≤1.59 SDa). The average(maximum) absolute GEBV changes for young animals from December 2016 to January and December 2017 ranged from 0.05(0.25) to 0.10(0.53) SDa. Corresponding ranges for animals with new progeny phenotypes were from 0.05(0.88) to 0.11(1.59) SDa for GEBV changes. The average absolute change in EBV(GEBV) from December 2016 to December 2017 for sires with ≤50 progeny phenotypes was 0.26(0.14) and for sires with >50 progeny phenotypes was 0.25(0.16) SDa. Updating the core group in APY without adding data created an average absolute change of 0.07 SDa in GEBV. Genomic evaluations in large genotyped populations are as stable and persistent as the traditional genetic evaluations, with less extreme changes. Oxford University Press 2021-02-05 /pmc/articles/PMC7867035/ /pubmed/33544869 http://dx.doi.org/10.1093/jas/skab004 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Animal Genetics and Genomics
Hidalgo, Jorge
Lourenco, Daniela
Tsuruta, Shogo
Masuda, Yutaka
Miller, Stephen
Bermann, Matias
Garcia, Andre L S
Misztal, Ignacy
Changes in genomic predictions when new information is added
title Changes in genomic predictions when new information is added
title_full Changes in genomic predictions when new information is added
title_fullStr Changes in genomic predictions when new information is added
title_full_unstemmed Changes in genomic predictions when new information is added
title_short Changes in genomic predictions when new information is added
title_sort changes in genomic predictions when new information is added
topic Animal Genetics and Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867035/
https://www.ncbi.nlm.nih.gov/pubmed/33544869
http://dx.doi.org/10.1093/jas/skab004
work_keys_str_mv AT hidalgojorge changesingenomicpredictionswhennewinformationisadded
AT lourencodaniela changesingenomicpredictionswhennewinformationisadded
AT tsurutashogo changesingenomicpredictionswhennewinformationisadded
AT masudayutaka changesingenomicpredictionswhennewinformationisadded
AT millerstephen changesingenomicpredictionswhennewinformationisadded
AT bermannmatias changesingenomicpredictionswhennewinformationisadded
AT garciaandrels changesingenomicpredictionswhennewinformationisadded
AT misztalignacy changesingenomicpredictionswhennewinformationisadded