Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)

Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which make...
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Autor*in:	Mertten, Daniel [verfasserIn] Baldwin, Samantha Cheng, Canhong H. McCallum, John Thomson, Susan Ashton, David T. McKenzie, Catherine M. Lenhard, Michael Datson, Paul M.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Best linear unbiased prediction Autopolyploid Genomic selection Accuracy Cross-validation

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Molecular breeding - Dordrecht : Springer Science + Business Media B.V., 1995, 43(2023), 10 vom: Okt.
Übergeordnetes Werk:	volume:43 ; year:2023 ; number:10 ; month:10

Links:	Volltext

DOI / URN:	10.1007/s11032-023-01419-8

Katalog-ID:	SPR05344664X

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100	1		\|a Mertten, Daniel \|e verfasserin \|0 (orcid)0009-0000-7131-825X \|4 aut
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520			\|a Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations.
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650		4	\|a Accuracy \|7 (dpeaa)DE-He213
650		4	\|a Cross-validation \|7 (dpeaa)DE-He213
700	1		\|a Baldwin, Samantha \|0 (orcid)0000-0002-8151-8850 \|4 aut
700	1		\|a Cheng, Canhong H. \|0 (orcid)0000-0003-0105-3924 \|4 aut
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700	1		\|a McKenzie, Catherine M. \|0 (orcid)0000-0002-3075-954X \|4 aut
700	1		\|a Lenhard, Michael \|0 (orcid)0000-0001-8661-6911 \|4 aut
700	1		\|a Datson, Paul M. \|4 aut
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author_variant	d m dm s b sb c h c ch chc j m jm s t st d t a dt dta c m m cm cmm m l ml p m d pm pmd
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publishDate	2023
allfields	10.1007/s11032-023-01419-8 doi (DE-627)SPR05344664X (SPR)s11032-023-01419-8-e DE-627 ger DE-627 rakwb eng Mertten, Daniel verfasserin (orcid)0009-0000-7131-825X aut Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213 Baldwin, Samantha (orcid)0000-0002-8151-8850 aut Cheng, Canhong H. (orcid)0000-0003-0105-3924 aut McCallum, John (orcid)0000-0002-7773-6732 aut Thomson, Susan (orcid)0000-0001-7127-9414 aut Ashton, David T. (orcid)0000-0002-0996-6368 aut McKenzie, Catherine M. (orcid)0000-0002-3075-954X aut Lenhard, Michael (orcid)0000-0001-8661-6911 aut Datson, Paul M. aut Enthalten in Molecular breeding Dordrecht : Springer Science + Business Media B.V., 1995 43(2023), 10 vom: Okt. (DE-627)270930671 (DE-600)1478220-0 1572-9788 nnns volume:43 year:2023 number:10 month:10 https://dx.doi.org/10.1007/s11032-023-01419-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 43 2023 10 10
spelling	10.1007/s11032-023-01419-8 doi (DE-627)SPR05344664X (SPR)s11032-023-01419-8-e DE-627 ger DE-627 rakwb eng Mertten, Daniel verfasserin (orcid)0009-0000-7131-825X aut Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213 Baldwin, Samantha (orcid)0000-0002-8151-8850 aut Cheng, Canhong H. (orcid)0000-0003-0105-3924 aut McCallum, John (orcid)0000-0002-7773-6732 aut Thomson, Susan (orcid)0000-0001-7127-9414 aut Ashton, David T. (orcid)0000-0002-0996-6368 aut McKenzie, Catherine M. (orcid)0000-0002-3075-954X aut Lenhard, Michael (orcid)0000-0001-8661-6911 aut Datson, Paul M. aut Enthalten in Molecular breeding Dordrecht : Springer Science + Business Media B.V., 1995 43(2023), 10 vom: Okt. (DE-627)270930671 (DE-600)1478220-0 1572-9788 nnns volume:43 year:2023 number:10 month:10 https://dx.doi.org/10.1007/s11032-023-01419-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 43 2023 10 10
allfields_unstemmed	10.1007/s11032-023-01419-8 doi (DE-627)SPR05344664X (SPR)s11032-023-01419-8-e DE-627 ger DE-627 rakwb eng Mertten, Daniel verfasserin (orcid)0009-0000-7131-825X aut Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213 Baldwin, Samantha (orcid)0000-0002-8151-8850 aut Cheng, Canhong H. (orcid)0000-0003-0105-3924 aut McCallum, John (orcid)0000-0002-7773-6732 aut Thomson, Susan (orcid)0000-0001-7127-9414 aut Ashton, David T. (orcid)0000-0002-0996-6368 aut McKenzie, Catherine M. (orcid)0000-0002-3075-954X aut Lenhard, Michael (orcid)0000-0001-8661-6911 aut Datson, Paul M. aut Enthalten in Molecular breeding Dordrecht : Springer Science + Business Media B.V., 1995 43(2023), 10 vom: Okt. (DE-627)270930671 (DE-600)1478220-0 1572-9788 nnns volume:43 year:2023 number:10 month:10 https://dx.doi.org/10.1007/s11032-023-01419-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 43 2023 10 10
allfieldsGer	10.1007/s11032-023-01419-8 doi (DE-627)SPR05344664X (SPR)s11032-023-01419-8-e DE-627 ger DE-627 rakwb eng Mertten, Daniel verfasserin (orcid)0009-0000-7131-825X aut Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213 Baldwin, Samantha (orcid)0000-0002-8151-8850 aut Cheng, Canhong H. (orcid)0000-0003-0105-3924 aut McCallum, John (orcid)0000-0002-7773-6732 aut Thomson, Susan (orcid)0000-0001-7127-9414 aut Ashton, David T. (orcid)0000-0002-0996-6368 aut McKenzie, Catherine M. (orcid)0000-0002-3075-954X aut Lenhard, Michael (orcid)0000-0001-8661-6911 aut Datson, Paul M. aut Enthalten in Molecular breeding Dordrecht : Springer Science + Business Media B.V., 1995 43(2023), 10 vom: Okt. (DE-627)270930671 (DE-600)1478220-0 1572-9788 nnns volume:43 year:2023 number:10 month:10 https://dx.doi.org/10.1007/s11032-023-01419-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 43 2023 10 10
allfieldsSound	10.1007/s11032-023-01419-8 doi (DE-627)SPR05344664X (SPR)s11032-023-01419-8-e DE-627 ger DE-627 rakwb eng Mertten, Daniel verfasserin (orcid)0009-0000-7131-825X aut Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213 Baldwin, Samantha (orcid)0000-0002-8151-8850 aut Cheng, Canhong H. (orcid)0000-0003-0105-3924 aut McCallum, John (orcid)0000-0002-7773-6732 aut Thomson, Susan (orcid)0000-0001-7127-9414 aut Ashton, David T. (orcid)0000-0002-0996-6368 aut McKenzie, Catherine M. (orcid)0000-0002-3075-954X aut Lenhard, Michael (orcid)0000-0001-8661-6911 aut Datson, Paul M. aut Enthalten in Molecular breeding Dordrecht : Springer Science + Business Media B.V., 1995 43(2023), 10 vom: Okt. (DE-627)270930671 (DE-600)1478220-0 1572-9788 nnns volume:43 year:2023 number:10 month:10 https://dx.doi.org/10.1007/s11032-023-01419-8 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_211 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 43 2023 10 10
language	English
source	Enthalten in Molecular breeding 43(2023), 10 vom: Okt. volume:43 year:2023 number:10 month:10
sourceStr	Enthalten in Molecular breeding 43(2023), 10 vom: Okt. volume:43 year:2023 number:10 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Best linear unbiased prediction Autopolyploid Genomic selection Accuracy Cross-validation
isfreeaccess_bool	true
container_title	Molecular breeding
authorswithroles_txt_mv	Mertten, Daniel @@aut@@ Baldwin, Samantha @@aut@@ Cheng, Canhong H. @@aut@@ McCallum, John @@aut@@ Thomson, Susan @@aut@@ Ashton, David T. @@aut@@ McKenzie, Catherine M. @@aut@@ Lenhard, Michael @@aut@@ Datson, Paul M. @@aut@@
publishDateDaySort_date	2023-10-01T00:00:00Z
hierarchy_top_id	270930671
id	SPR05344664X
language_de	englisch
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author	Mertten, Daniel
spellingShingle	Mertten, Daniel misc Best linear unbiased prediction misc Autopolyploid misc Genomic selection misc Accuracy misc Cross-validation Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)
authorStr	Mertten, Daniel
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topic_title	Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta) Best linear unbiased prediction (dpeaa)DE-He213 Autopolyploid (dpeaa)DE-He213 Genomic selection (dpeaa)DE-He213 Accuracy (dpeaa)DE-He213 Cross-validation (dpeaa)DE-He213
topic	misc Best linear unbiased prediction misc Autopolyploid misc Genomic selection misc Accuracy misc Cross-validation
topic_unstemmed	misc Best linear unbiased prediction misc Autopolyploid misc Genomic selection misc Accuracy misc Cross-validation
topic_browse	misc Best linear unbiased prediction misc Autopolyploid misc Genomic selection misc Accuracy misc Cross-validation
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title	Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)
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title_full	Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)
author_sort	Mertten, Daniel
journal	Molecular breeding
journalStr	Molecular breeding
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author_browse	Mertten, Daniel Baldwin, Samantha Cheng, Canhong H. McCallum, John Thomson, Susan Ashton, David T. McKenzie, Catherine M. Lenhard, Michael Datson, Paul M.
container_volume	43
format_se	Elektronische Aufsätze
author-letter	Mertten, Daniel
doi_str_mv	10.1007/s11032-023-01419-8
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title_sort	implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (actinidia arguta)
title_auth	Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)
abstract	Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. © The Author(s) 2023
abstractGer	Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. © The Author(s) 2023
abstract_unstemmed	Abstract In dioecious crops such as Actinidia arguta (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding. In this study, we used a linear mixed model approach to estimate narrow sense heritability for one vine-related trait and five fruit-related traits for two incomplete factorial crossing designs. We obtained BLUPs for all genotypes, taking into consideration whether the relationship was pedigree-based or marker-based. Owing to the high cost of genome sequencing, it is important to understand the effects of different sources of relationship matrices on estimating breeding values across a breeding population. Because of the increasing implementation of genomic selection in crop breeding, we compared the effects of incorporating different sources of information in building relationship matrices and ploidy levels on the accuracy of BLUPs’ heritability and predictive ability. As kiwiberries are autotetraploids, multivalent chromosome formation and occasionally double reduction can occur during meiosis, and this can affect the accuracy of prediction. This study innovates the breeding programme of autotetraploid kiwiberries. We demonstrate that the accuracy of BLUPs of male siblings, without phenotypic observations, strongly improved when a tetraploid marker-based relationship matrix was used rather than parental BLUPs and female siblings with phenotypic observations. © The Author(s) 2023
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container_issue	10
title_short	Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)
url	https://dx.doi.org/10.1007/s11032-023-01419-8
remote_bool	true
author2	Baldwin, Samantha Cheng, Canhong H. McCallum, John Thomson, Susan Ashton, David T. McKenzie, Catherine M. Lenhard, Michael Datson, Paul M.
author2Str	Baldwin, Samantha Cheng, Canhong H. McCallum, John Thomson, Susan Ashton, David T. McKenzie, Catherine M. Lenhard, Michael Datson, Paul M.
ppnlink	270930671
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1007/s11032-023-01419-8
up_date	2024-07-03T19:35:43.418Z
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Implementation of different relationship estimate methodologies in breeding value prediction in kiwiberry (Actinidia arguta)

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