Genomic selection in wheat breeding using genotyping-by-sequencing

Genomic selection (GS) uses genome-wide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat genome. With GBS we discovered 41K SNPs in a set of 254 advanced breeding lines from CIMMYT?s semi-arid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate-normal expectation maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, though no significant differences were observed in the accuracy of genomic-estimated breeding values (GEBVs). GEBV prediction accuracies with GBS were 0.28 ? 0.45 for grain yield, an improvement of 0.1-0.2 over an established marker platform for wheat. GBS combines marker discovery and genotyping of large populations making it an excellent marker platform for breeding applications even in the absence of reference genome sequence or previous polymorphism discovery. In addition, the flexibility and low-cost of GBS make this an ideal approach for genomics-assisted breeding.

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Main Authors: Poland, J.A., Endelman, J.B., Dawson, J., Rutkoski, J., Shuangye Wu, Manes, Y., Dreisigacker, S., Crossa, J., Sanchez-Villeda, H., Sorrells, M.E., Jannink, J.L.
Format: Article biblioteca
Language:English
Published: Crop Science Society of America 2012
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, ARTIFICIAL SELECTION, GENETIC MARKERS, SINGLE NUCLEOTIDE POLYMORPHISM,
Online Access:http://hdl.handle.net/10883/2933
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spelling dig-cimmyt-10883-29332023-12-01T16:41:30Z Genomic selection in wheat breeding using genotyping-by-sequencing Poland, J.A. Endelman, J.B. Dawson, J. Rutkoski, J. Shuangye Wu Manes, Y. Dreisigacker, S. Crossa, J. Sanchez-Villeda, H. Sorrells, M.E. Jannink, J.L. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY ARTIFICIAL SELECTION GENETIC MARKERS SINGLE NUCLEOTIDE POLYMORPHISM Genomic selection (GS) uses genome-wide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat genome. With GBS we discovered 41K SNPs in a set of 254 advanced breeding lines from CIMMYT?s semi-arid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate-normal expectation maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, though no significant differences were observed in the accuracy of genomic-estimated breeding values (GEBVs). GEBV prediction accuracies with GBS were 0.28 ? 0.45 for grain yield, an improvement of 0.1-0.2 over an established marker platform for wheat. GBS combines marker discovery and genotyping of large populations making it an excellent marker platform for breeding applications even in the absence of reference genome sequence or previous polymorphism discovery. In addition, the flexibility and low-cost of GBS make this an ideal approach for genomics-assisted breeding. 103-113 2013-06-07T21:12:56Z 2013-06-07T21:12:56Z 2012 Article http://hdl.handle.net/10883/2933 10.3835/plantgenome2012.06.0006 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 Crop Science Society of America https://www.crops.org/publications/tpg/abstracts/5/3/103 3 5 The Plant Genome
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
ARTIFICIAL SELECTION
GENETIC MARKERS
SINGLE NUCLEOTIDE POLYMORPHISM
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
ARTIFICIAL SELECTION
GENETIC MARKERS
SINGLE NUCLEOTIDE POLYMORPHISM
spellingShingle AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
ARTIFICIAL SELECTION
GENETIC MARKERS
SINGLE NUCLEOTIDE POLYMORPHISM
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
ARTIFICIAL SELECTION
GENETIC MARKERS
SINGLE NUCLEOTIDE POLYMORPHISM
Poland, J.A.
Endelman, J.B.
Dawson, J.
Rutkoski, J.
Shuangye Wu
Manes, Y.
Dreisigacker, S.
Crossa, J.
Sanchez-Villeda, H.
Sorrells, M.E.
Jannink, J.L.
Genomic selection in wheat breeding using genotyping-by-sequencing
description Genomic selection (GS) uses genome-wide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat genome. With GBS we discovered 41K SNPs in a set of 254 advanced breeding lines from CIMMYT?s semi-arid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate-normal expectation maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, though no significant differences were observed in the accuracy of genomic-estimated breeding values (GEBVs). GEBV prediction accuracies with GBS were 0.28 ? 0.45 for grain yield, an improvement of 0.1-0.2 over an established marker platform for wheat. GBS combines marker discovery and genotyping of large populations making it an excellent marker platform for breeding applications even in the absence of reference genome sequence or previous polymorphism discovery. In addition, the flexibility and low-cost of GBS make this an ideal approach for genomics-assisted breeding.
format Article
topic_facet AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
ARTIFICIAL SELECTION
GENETIC MARKERS
SINGLE NUCLEOTIDE POLYMORPHISM
author Poland, J.A.
Endelman, J.B.
Dawson, J.
Rutkoski, J.
Shuangye Wu
Manes, Y.
Dreisigacker, S.
Crossa, J.
Sanchez-Villeda, H.
Sorrells, M.E.
Jannink, J.L.
author_facet Poland, J.A.
Endelman, J.B.
Dawson, J.
Rutkoski, J.
Shuangye Wu
Manes, Y.
Dreisigacker, S.
Crossa, J.
Sanchez-Villeda, H.
Sorrells, M.E.
Jannink, J.L.
author_sort Poland, J.A.
title Genomic selection in wheat breeding using genotyping-by-sequencing
title_short Genomic selection in wheat breeding using genotyping-by-sequencing
title_full Genomic selection in wheat breeding using genotyping-by-sequencing
title_fullStr Genomic selection in wheat breeding using genotyping-by-sequencing
title_full_unstemmed Genomic selection in wheat breeding using genotyping-by-sequencing
title_sort genomic selection in wheat breeding using genotyping-by-sequencing
publisher Crop Science Society of America
publishDate 2012
url http://hdl.handle.net/10883/2933
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