Chapter 6. Constrained linear genomic selection indices

The constrained linear genomic selection indices are null restricted and predetermined proportional gain linear genomic selection indices (RLGSI and PPG-LGSI respectively), which are a linear combination of genomic estimated breeding values (GEBVs) to predict the net genetic merit. They are the results of a direct application of the restricted and the predetermined proportional gain linear phenotypic selection index theory to the genomic selection context. The RLGSI can be extended to a combined RLGSI (CRLGSI) and the PPG-LGSI can be extended to a combined PPG-LGSI (CPPG-LGSI); the latter indices use phenotypic and GEBV information jointly in the prediction of net genetic merit. The main difference between the RLGSI and PPG-LGSI with respect to the CRLGSI and the CPPG-LGSI is that although the RLGSI and PPG-LGSI are useful in a testing population where there is only marker information, the CRLGSI and CPPG-LGSI can be used only in training populations when there are joint phenotypic and marker information. The RLGSI and CRLGSI allow restrictions equal to zero to be imposed on the expected genetic advance of some traits, whereas the PPG-LGSI and CPPG-LGSI allow predetermined proportional restriction values to be imposed on the expected trait genetic gains to make some traits change their mean values based on a predetermined level. We describe the foregoing four indices and we validated their theoretical results using real and simulated data.

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Main Authors: Ceron Rojas, J.J., Crossa, J.
Format: Book Chapter biblioteca
Language:English
Published: Springer 2018
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, LINEAR MODELS, SELECTION CRITERIA, GENETICS,
Online Access:https://hdl.handle.net/10883/19805
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spelling dig-cimmyt-10883-198052021-03-31T14:27:06Z Chapter 6. Constrained linear genomic selection indices Ceron Rojas, J.J. Crossa, J. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY LINEAR MODELS SELECTION CRITERIA GENETICS The constrained linear genomic selection indices are null restricted and predetermined proportional gain linear genomic selection indices (RLGSI and PPG-LGSI respectively), which are a linear combination of genomic estimated breeding values (GEBVs) to predict the net genetic merit. They are the results of a direct application of the restricted and the predetermined proportional gain linear phenotypic selection index theory to the genomic selection context. The RLGSI can be extended to a combined RLGSI (CRLGSI) and the PPG-LGSI can be extended to a combined PPG-LGSI (CPPG-LGSI); the latter indices use phenotypic and GEBV information jointly in the prediction of net genetic merit. The main difference between the RLGSI and PPG-LGSI with respect to the CRLGSI and the CPPG-LGSI is that although the RLGSI and PPG-LGSI are useful in a testing population where there is only marker information, the CRLGSI and CPPG-LGSI can be used only in training populations when there are joint phenotypic and marker information. The RLGSI and CRLGSI allow restrictions equal to zero to be imposed on the expected genetic advance of some traits, whereas the PPG-LGSI and CPPG-LGSI allow predetermined proportional restriction values to be imposed on the expected trait genetic gains to make some traits change their mean values based on a predetermined level. We describe the foregoing four indices and we validated their theoretical results using real and simulated data. 121-147 2019-01-17T23:30:41Z 2019-01-17T23:30:41Z 2018 Book Chapter 978-3-319-91222-6 (Print) 978-3-319-91223-3 (Online) https://hdl.handle.net/10883/19805 10.1007/978-3-319-91223-3_6 English CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose. Open Access PDF Switzerland Springer Linear selection indices in modern plant breeding
institution CIMMYT
collection DSpace
country México
countrycode MX
component Bibliográfico
access En linea
databasecode dig-cimmyt
tag biblioteca
region America del Norte
libraryname CIMMYT Library
language English
topic AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
LINEAR MODELS
SELECTION CRITERIA
GENETICS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
LINEAR MODELS
SELECTION CRITERIA
GENETICS
spellingShingle AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
LINEAR MODELS
SELECTION CRITERIA
GENETICS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
LINEAR MODELS
SELECTION CRITERIA
GENETICS
Ceron Rojas, J.J.
Crossa, J.
Chapter 6. Constrained linear genomic selection indices
description The constrained linear genomic selection indices are null restricted and predetermined proportional gain linear genomic selection indices (RLGSI and PPG-LGSI respectively), which are a linear combination of genomic estimated breeding values (GEBVs) to predict the net genetic merit. They are the results of a direct application of the restricted and the predetermined proportional gain linear phenotypic selection index theory to the genomic selection context. The RLGSI can be extended to a combined RLGSI (CRLGSI) and the PPG-LGSI can be extended to a combined PPG-LGSI (CPPG-LGSI); the latter indices use phenotypic and GEBV information jointly in the prediction of net genetic merit. The main difference between the RLGSI and PPG-LGSI with respect to the CRLGSI and the CPPG-LGSI is that although the RLGSI and PPG-LGSI are useful in a testing population where there is only marker information, the CRLGSI and CPPG-LGSI can be used only in training populations when there are joint phenotypic and marker information. The RLGSI and CRLGSI allow restrictions equal to zero to be imposed on the expected genetic advance of some traits, whereas the PPG-LGSI and CPPG-LGSI allow predetermined proportional restriction values to be imposed on the expected trait genetic gains to make some traits change their mean values based on a predetermined level. We describe the foregoing four indices and we validated their theoretical results using real and simulated data.
format Book Chapter
topic_facet AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
LINEAR MODELS
SELECTION CRITERIA
GENETICS
author Ceron Rojas, J.J.
Crossa, J.
author_facet Ceron Rojas, J.J.
Crossa, J.
author_sort Ceron Rojas, J.J.
title Chapter 6. Constrained linear genomic selection indices
title_short Chapter 6. Constrained linear genomic selection indices
title_full Chapter 6. Constrained linear genomic selection indices
title_fullStr Chapter 6. Constrained linear genomic selection indices
title_full_unstemmed Chapter 6. Constrained linear genomic selection indices
title_sort chapter 6. constrained linear genomic selection indices
publisher Springer
publishDate 2018
url https://hdl.handle.net/10883/19805
work_keys_str_mv AT ceronrojasjj chapter6constrainedlineargenomicselectionindices
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