Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle

Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Fernando Flores Cardoso [verfasserIn] Oswald Matika [verfasserIn] Appolinaire Djikeng [verfasserIn] Ntanganedzeni Mapholi [verfasserIn] Heather M. Burrow [verfasserIn] Marcos Jun Iti Yokoo [verfasserIn] Gabriel Soares Campos [verfasserIn] Claudia Cristina Gulias-Gomes [verfasserIn] Valentina Riggio [verfasserIn] Ricardo Pong-Wong [verfasserIn] Bailey Engle [verfasserIn] Laercio Porto-Neto [verfasserIn] Azwihangwisi Maiwashe [verfasserIn] Ben J. Hayes [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	beef cattle genomic selection ticks tropical adaptation host resistance

Übergeordnetes Werk:	In: Frontiers in Immunology - Frontiers Media S.A., 2011, 12(2021)
Übergeordnetes Werk:	volume:12 ; year:2021

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fimmu.2021.620847

Katalog-ID:	DOAJ00130240X

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520			\|a Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
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allfields	10.3389/fimmu.2021.620847 doi (DE-627)DOAJ00130240X (DE-599)DOAJb77d3de2be9b4b2e8606bd4af2d44d02 DE-627 ger DE-627 rakwb eng RC581-607 Fernando Flores Cardoso verfasserin aut Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy Oswald Matika verfasserin aut Appolinaire Djikeng verfasserin aut Ntanganedzeni Mapholi verfasserin aut Heather M. Burrow verfasserin aut Marcos Jun Iti Yokoo verfasserin aut Gabriel Soares Campos verfasserin aut Claudia Cristina Gulias-Gomes verfasserin aut Valentina Riggio verfasserin aut Valentina Riggio verfasserin aut Ricardo Pong-Wong verfasserin aut Bailey Engle verfasserin aut Laercio Porto-Neto verfasserin aut Azwihangwisi Maiwashe verfasserin aut Ben J. Hayes verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 12(2021) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:12 year:2021 https://doi.org/10.3389/fimmu.2021.620847 kostenfrei https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021
spelling	10.3389/fimmu.2021.620847 doi (DE-627)DOAJ00130240X (DE-599)DOAJb77d3de2be9b4b2e8606bd4af2d44d02 DE-627 ger DE-627 rakwb eng RC581-607 Fernando Flores Cardoso verfasserin aut Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy Oswald Matika verfasserin aut Appolinaire Djikeng verfasserin aut Ntanganedzeni Mapholi verfasserin aut Heather M. Burrow verfasserin aut Marcos Jun Iti Yokoo verfasserin aut Gabriel Soares Campos verfasserin aut Claudia Cristina Gulias-Gomes verfasserin aut Valentina Riggio verfasserin aut Valentina Riggio verfasserin aut Ricardo Pong-Wong verfasserin aut Bailey Engle verfasserin aut Laercio Porto-Neto verfasserin aut Azwihangwisi Maiwashe verfasserin aut Ben J. Hayes verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 12(2021) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:12 year:2021 https://doi.org/10.3389/fimmu.2021.620847 kostenfrei https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021
allfields_unstemmed	10.3389/fimmu.2021.620847 doi (DE-627)DOAJ00130240X (DE-599)DOAJb77d3de2be9b4b2e8606bd4af2d44d02 DE-627 ger DE-627 rakwb eng RC581-607 Fernando Flores Cardoso verfasserin aut Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy Oswald Matika verfasserin aut Appolinaire Djikeng verfasserin aut Ntanganedzeni Mapholi verfasserin aut Heather M. Burrow verfasserin aut Marcos Jun Iti Yokoo verfasserin aut Gabriel Soares Campos verfasserin aut Claudia Cristina Gulias-Gomes verfasserin aut Valentina Riggio verfasserin aut Valentina Riggio verfasserin aut Ricardo Pong-Wong verfasserin aut Bailey Engle verfasserin aut Laercio Porto-Neto verfasserin aut Azwihangwisi Maiwashe verfasserin aut Ben J. Hayes verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 12(2021) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:12 year:2021 https://doi.org/10.3389/fimmu.2021.620847 kostenfrei https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021
allfieldsGer	10.3389/fimmu.2021.620847 doi (DE-627)DOAJ00130240X (DE-599)DOAJb77d3de2be9b4b2e8606bd4af2d44d02 DE-627 ger DE-627 rakwb eng RC581-607 Fernando Flores Cardoso verfasserin aut Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy Oswald Matika verfasserin aut Appolinaire Djikeng verfasserin aut Ntanganedzeni Mapholi verfasserin aut Heather M. Burrow verfasserin aut Marcos Jun Iti Yokoo verfasserin aut Gabriel Soares Campos verfasserin aut Claudia Cristina Gulias-Gomes verfasserin aut Valentina Riggio verfasserin aut Valentina Riggio verfasserin aut Ricardo Pong-Wong verfasserin aut Bailey Engle verfasserin aut Laercio Porto-Neto verfasserin aut Azwihangwisi Maiwashe verfasserin aut Ben J. Hayes verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 12(2021) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:12 year:2021 https://doi.org/10.3389/fimmu.2021.620847 kostenfrei https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021
allfieldsSound	10.3389/fimmu.2021.620847 doi (DE-627)DOAJ00130240X (DE-599)DOAJb77d3de2be9b4b2e8606bd4af2d44d02 DE-627 ger DE-627 rakwb eng RC581-607 Fernando Flores Cardoso verfasserin aut Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy Oswald Matika verfasserin aut Appolinaire Djikeng verfasserin aut Ntanganedzeni Mapholi verfasserin aut Heather M. Burrow verfasserin aut Marcos Jun Iti Yokoo verfasserin aut Gabriel Soares Campos verfasserin aut Claudia Cristina Gulias-Gomes verfasserin aut Valentina Riggio verfasserin aut Valentina Riggio verfasserin aut Ricardo Pong-Wong verfasserin aut Bailey Engle verfasserin aut Laercio Porto-Neto verfasserin aut Azwihangwisi Maiwashe verfasserin aut Ben J. Hayes verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 12(2021) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:12 year:2021 https://doi.org/10.3389/fimmu.2021.620847 kostenfrei https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2021
language	English
source	In Frontiers in Immunology 12(2021) volume:12 year:2021
sourceStr	In Frontiers in Immunology 12(2021) volume:12 year:2021
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	beef cattle genomic selection ticks tropical adaptation host resistance Immunologic diseases. Allergy
isfreeaccess_bool	true
container_title	Frontiers in Immunology
authorswithroles_txt_mv	Fernando Flores Cardoso @@aut@@ Oswald Matika @@aut@@ Appolinaire Djikeng @@aut@@ Ntanganedzeni Mapholi @@aut@@ Heather M. Burrow @@aut@@ Marcos Jun Iti Yokoo @@aut@@ Gabriel Soares Campos @@aut@@ Claudia Cristina Gulias-Gomes @@aut@@ Valentina Riggio @@aut@@ Ricardo Pong-Wong @@aut@@ Bailey Engle @@aut@@ Laercio Porto-Neto @@aut@@ Azwihangwisi Maiwashe @@aut@@ Ben J. Hayes @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	657998354
id	DOAJ00130240X
language_de	englisch
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Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. 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callnumber-first	R - Medicine
author	Fernando Flores Cardoso
spellingShingle	Fernando Flores Cardoso misc RC581-607 misc beef cattle misc genomic selection misc ticks misc tropical adaptation misc host resistance misc Immunologic diseases. Allergy Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle
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topic_title	RC581-607 Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle beef cattle genomic selection ticks tropical adaptation host resistance
topic	misc RC581-607 misc beef cattle misc genomic selection misc ticks misc tropical adaptation misc host resistance misc Immunologic diseases. Allergy
topic_unstemmed	misc RC581-607 misc beef cattle misc genomic selection misc ticks misc tropical adaptation misc host resistance misc Immunologic diseases. Allergy
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title	Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle
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title_full	Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle
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author_browse	Fernando Flores Cardoso Oswald Matika Appolinaire Djikeng Ntanganedzeni Mapholi Heather M. Burrow Marcos Jun Iti Yokoo Gabriel Soares Campos Claudia Cristina Gulias-Gomes Valentina Riggio Ricardo Pong-Wong Bailey Engle Laercio Porto-Neto Azwihangwisi Maiwashe Ben J. Hayes
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title_sort	multiple country and breed genomic prediction of tick resistance in beef cattle
callnumber	RC581-607
title_auth	Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle
abstract	Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
abstractGer	Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
abstract_unstemmed	Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
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title_short	Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle
url	https://doi.org/10.3389/fimmu.2021.620847 https://doaj.org/article/b77d3de2be9b4b2e8606bd4af2d44d02 https://www.frontiersin.org/articles/10.3389/fimmu.2021.620847/full https://doaj.org/toc/1664-3224
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author2Str	Oswald Matika Appolinaire Djikeng Ntanganedzeni Mapholi Heather M. Burrow Marcos Jun Iti Yokoo Gabriel Soares Campos Claudia Cristina Gulias-Gomes Valentina Riggio Ricardo Pong-Wong Bailey Engle Laercio Porto-Neto Azwihangwisi Maiwashe Ben J. Hayes
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Multiple Country and Breed Genomic Prediction of Tick Resistance in Beef Cattle

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