Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle

Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbree...

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Published inGenetics Selection Evolution Vol. 52; no. 1; p. 64
Main Authors Doekes, Harmen P., Bijma, Piter, Veerkamp, Roel F., de Jong, Gerben, Wientjes, Yvonne C.J., Windig, Jack J.
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Published France Springer Science and Business Media LLC 28.10.2020
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Abstract Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH). Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations. Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found. Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
AbstractList Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).BACKGROUNDInbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.METHODSGenotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.RESULTSGenome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.CONCLUSIONSInbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
Background Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH). Methods Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations. Results Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found. Conclusions Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH). Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations. Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found. Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
AbstractBackgroundInbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).MethodsGenotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.ResultsGenome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.ConclusionsInbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
Abstract Background Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH). Methods Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations. Results Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found. Conclusions Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH). Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations. Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found. Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
ArticleNumber 64
Audience Academic
Author Wientjes, Yvonne C.J.
de Jong, Gerben
Doekes, Harmen P.
Veerkamp, Roel F.
Bijma, Piter
Windig, Jack J.
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Cites_doi 10.1186/s12711-018-0385-y
10.1016/j.ajhg.2015.01.001
10.1038/nrg2813
10.1111/age.12378
10.5713/ajas.2006.769
10.3168/jds.S0022-0302(00)75059-4
10.3168/jds.2010-3255
10.3168/jds.2007-0227
10.3168/jds.2017-13366
10.3168/jds.2016-12164
10.1534/genetics.111.130922
10.1038/s41598-020-59788-5
10.1086/519795
10.2527/jas2017.1664
10.1111/j.1439-0388.2009.00831.x
10.3389/fgene.2018.00078
10.1186/s12711-016-0271-4
10.1534/genetics.113.155176
10.1186/s12711-016-0186-0
10.3168/jds.2015-9564
10.3168/jds.S0022-0302(90)78900-X
10.1186/s12864-017-3821-4
10.3168/jds.2012-6435
10.1371/journal.pone.0103934
10.1186/s12711-014-0071-7
10.1534/genetics.113.151753
10.1186/s12711-015-0114-8
10.3168/jds.2017-12787
10.1111/j.2517-6161.1995.tb02031.x
10.1093/bioinformatics/btw012
10.1186/s12711-019-0497-z
10.1111/mec.12560
10.1002/jbmr.2558
10.1111/jbg.12466
10.3168/jds.2018-14805
10.3168/jds.S0022-0302(95)76735-2
10.3389/fgene.2019.00412
10.1186/1297-9686-41-16
10.1186/1471-2156-8-62
10.1534/genetics.111.134841
10.3168/jds.S0022-0302(91)78337-9
10.3168/jds.2016-11261
10.1371/journal.pone.0087666
10.3168/jds.S0022-0302(95)76734-0
10.1631/jzus.2007.B0815
10.1073/pnas.1714475115
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References 583_CR20
S Purcell (583_CR21) 2007; 81
MÁR de Cara (583_CR26) 2013; 22
F Miglior (583_CR37) 1995; 78
RJ Tempelman (583_CR41) 1990; 73
T Xiang (583_CR27) 2016; 48
K Meyer (583_CR29) 2012; 190
C Kuehn (583_CR51) 2007; 8
ZG Vitezica (583_CR13) 2013; 195
M Kardos (583_CR34) 2018; 115
SH Lee (583_CR23) 2016; 32
K Meyer (583_CR30) 2007; 8
PM VanRaden (583_CR25) 2008; 91
Z Zhu (583_CR46) 2015; 96
583_CR19
D Gianola (583_CR49) 2013; 194
AL Price (583_CR31) 2010; 11
583_CR33
M Ferenčaković (583_CR16) 2017; 100
TL Yang (583_CR52) 2015; 30
YL Bernal Rubio (583_CR48) 2016; 47
C Sun (583_CR35) 2014; 9
H Bovenhuis (583_CR50) 2015; 98
S Bolormaa (583_CR10) 2015; 47
S Mc Parland (583_CR7) 2007; 90
J Jiang (583_CR43) 2017; 18
H Aliloo (583_CR47) 2017; 100
MPL Calus (583_CR15) 2018; 101
T Druet (583_CR18) 2010; 93
HP Doekes (583_CR22) 2018; 50
JE Pryce (583_CR2) 2014; 46
MC Keller (583_CR17) 2011; 189
T Kawahara (583_CR39) 2006; 19
Y Benjamini (583_CR32) 1995; 57
F Miglior (583_CR38) 1995; 78
H Aliloo (583_CR14) 2016; 48
JT Howard (583_CR9) 2017; 100
583_CR54
J Jiang (583_CR11) 2019; 10
I Hoeschele (583_CR42) 1991; 74
DW Bjelland (583_CR3) 2013; 96
K Alves (583_CR44) 2020; 137
583_CR6
MPL Calus (583_CR24) 2013
K Martikainen (583_CR4) 2018; 101
JT Howard (583_CR53) 2017; 95
HP Doekes (583_CR8) 2019; 51
L Varona (583_CR28) 2018; 9
Y Da (583_CR36) 2014; 9
X Mao (583_CR45) 2020; 10
S Mc Parland (583_CR5) 2009; 41
I MacLeod (583_CR12) 2010; 127
DS Falconer (583_CR1) 1996
CP Van Tassell (583_CR40) 2000; 83
References_xml – volume: 50
  start-page: 15
  year: 2018
  ident: 583_CR22
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-018-0385-y
– volume: 96
  start-page: 377
  year: 2015
  ident: 583_CR46
  publication-title: Am J Hum Genet
  doi: 10.1016/j.ajhg.2015.01.001
– volume: 11
  start-page: 459
  year: 2010
  ident: 583_CR31
  publication-title: Nat Rev Genet
  doi: 10.1038/nrg2813
– volume: 47
  start-page: 36
  year: 2016
  ident: 583_CR48
  publication-title: Anim Genet
  doi: 10.1111/age.12378
– volume: 19
  start-page: 769
  year: 2006
  ident: 583_CR39
  publication-title: Asian-Australas J Anim Sci
  doi: 10.5713/ajas.2006.769
– ident: 583_CR33
– volume: 83
  start-page: 1873
  year: 2000
  ident: 583_CR40
  publication-title: J Dairy Sci
  doi: 10.3168/jds.S0022-0302(00)75059-4
– volume: 93
  start-page: 5443
  year: 2010
  ident: 583_CR18
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2010-3255
– volume: 90
  start-page: 4411
  year: 2007
  ident: 583_CR7
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2007-0227
– volume: 101
  start-page: 4279
  year: 2018
  ident: 583_CR15
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2017-13366
– volume: 100
  start-page: 4721
  year: 2017
  ident: 583_CR16
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2016-12164
– volume: 189
  start-page: 237
  year: 2011
  ident: 583_CR17
  publication-title: Genetics
  doi: 10.1534/genetics.111.130922
– volume: 10
  start-page: 2953
  year: 2020
  ident: 583_CR45
  publication-title: Sci Rep
  doi: 10.1038/s41598-020-59788-5
– volume: 81
  start-page: 559
  year: 2007
  ident: 583_CR21
  publication-title: Am J Hum Genet
  doi: 10.1086/519795
– volume: 95
  start-page: 4318
  year: 2017
  ident: 583_CR53
  publication-title: J Anim Sci
  doi: 10.2527/jas2017.1664
– volume: 127
  start-page: 133
  year: 2010
  ident: 583_CR12
  publication-title: J Anim Breed Genet
  doi: 10.1111/j.1439-0388.2009.00831.x
– volume: 91
  start-page: 4414
  year: 2008
  ident: 583_CR25
  publication-title: Efficient methods to compute genomic predictions
– volume: 9
  start-page: 78
  year: 2018
  ident: 583_CR28
  publication-title: Front Genet
  doi: 10.3389/fgene.2018.00078
– volume: 48
  start-page: 92
  year: 2016
  ident: 583_CR27
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-016-0271-4
– volume: 195
  start-page: 1223
  year: 2013
  ident: 583_CR13
  publication-title: Genetics
  doi: 10.1534/genetics.113.155176
– volume: 48
  start-page: 8
  year: 2016
  ident: 583_CR14
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-016-0186-0
– volume: 98
  start-page: 6572
  year: 2015
  ident: 583_CR50
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2015-9564
– volume: 73
  start-page: 2206
  year: 1990
  ident: 583_CR41
  publication-title: J Dairy Sci
  doi: 10.3168/jds.S0022-0302(90)78900-X
– ident: 583_CR20
– volume-title: Calc_grm—a programme to compute pedigree, genomic, and combined relationship matrices
  year: 2013
  ident: 583_CR24
– volume: 18
  start-page: 425
  year: 2017
  ident: 583_CR43
  publication-title: BMC Genomics
  doi: 10.1186/s12864-017-3821-4
– volume: 96
  start-page: 4697
  year: 2013
  ident: 583_CR3
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2012-6435
– volume: 9
  start-page: e103934
  year: 2014
  ident: 583_CR35
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0103934
– volume: 46
  start-page: 71
  year: 2014
  ident: 583_CR2
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-014-0071-7
– volume: 194
  start-page: 573
  year: 2013
  ident: 583_CR49
  publication-title: Genetics
  doi: 10.1534/genetics.113.151753
– volume: 47
  start-page: 26
  year: 2015
  ident: 583_CR10
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-015-0114-8
– ident: 583_CR19
– ident: 583_CR54
– volume: 100
  start-page: 6009
  year: 2017
  ident: 583_CR9
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2017-12787
– volume: 57
  start-page: 289
  year: 1995
  ident: 583_CR32
  publication-title: J R Stat Soc Series B Stat Methodol
  doi: 10.1111/j.2517-6161.1995.tb02031.x
– volume: 32
  start-page: 1420
  year: 2016
  ident: 583_CR23
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btw012
– ident: 583_CR6
– volume-title: Introduction to quantitative genetics
  year: 1996
  ident: 583_CR1
– volume: 51
  start-page: 54
  year: 2019
  ident: 583_CR8
  publication-title: Genet Sel Evol
  doi: 10.1186/s12711-019-0497-z
– volume: 22
  start-page: 6091
  year: 2013
  ident: 583_CR26
  publication-title: Mol Ecol
  doi: 10.1111/mec.12560
– volume: 30
  start-page: 2119
  year: 2015
  ident: 583_CR52
  publication-title: J Bone Miner Res
  doi: 10.1002/jbmr.2558
– volume: 137
  start-page: 316
  year: 2020
  ident: 583_CR44
  publication-title: J Anim Breed Genet
  doi: 10.1111/jbg.12466
– volume: 101
  start-page: 11097
  year: 2018
  ident: 583_CR4
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2018-14805
– volume: 78
  start-page: 1174
  year: 1995
  ident: 583_CR37
  publication-title: J Dairy Sci
  doi: 10.3168/jds.S0022-0302(95)76735-2
– volume: 10
  start-page: 412
  year: 2019
  ident: 583_CR11
  publication-title: Front Genet.
  doi: 10.3389/fgene.2019.00412
– volume: 41
  start-page: 16
  year: 2009
  ident: 583_CR5
  publication-title: Genet Sel Evol
  doi: 10.1186/1297-9686-41-16
– volume: 8
  start-page: 62
  year: 2007
  ident: 583_CR51
  publication-title: BMC Genet
  doi: 10.1186/1471-2156-8-62
– volume: 190
  start-page: 275
  year: 2012
  ident: 583_CR29
  publication-title: Genetics
  doi: 10.1534/genetics.111.134841
– volume: 74
  start-page: 1743
  year: 1991
  ident: 583_CR42
  publication-title: J Dairy Sci
  doi: 10.3168/jds.S0022-0302(91)78337-9
– volume: 100
  start-page: 1203
  year: 2017
  ident: 583_CR47
  publication-title: J Dairy Sci
  doi: 10.3168/jds.2016-11261
– volume: 9
  start-page: e87666
  year: 2014
  ident: 583_CR36
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0087666
– volume: 78
  start-page: 1168
  year: 1995
  ident: 583_CR38
  publication-title: J Dairy Sci
  doi: 10.3168/jds.S0022-0302(95)76734-0
– volume: 8
  start-page: 815
  year: 2007
  ident: 583_CR30
  publication-title: J Zhejiang Univ Sci B
  doi: 10.1631/jzus.2007.B0815
– volume: 115
  start-page: E2492
  year: 2018
  ident: 583_CR34
  publication-title: Proc Natl Acad Sci USA
  doi: 10.1073/pnas.1714475115
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Snippet Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced...
Background Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity...
BACKGROUND: Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity...
AbstractBackgroundInbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in...
Abstract Background Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in...
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SubjectTerms [SDV]Life Sciences [q-bio]
accounting
additive effect
Analysis
Animal culture
Animals
Cattle
Cattle - genetics
Cattle - physiology
Chromosome 5
Chromosomes
cows
Dairy cattle
Dominance
evolution
Fertility
Gene frequency
Gene loci
Genes, Dominant
Genetic Load
Genetic research
Genetics
genome
Genomes
Genomics
Genotypes
Holstein
Homozygosity
Homozygote
Inbreeding
Inbreeding Depression
Life Science
Life Sciences
loci
methodology
Milk
Milk - standards
Milk production
milk yield
Pedigree
Phenotype
Phenotypes
phenotypic variation
Phenotypic variations
Polymorphism, Single Nucleotide
QH426-470
Research Article
SF1-1100
Udder
udders
variance
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Title Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle
URI https://cir.nii.ac.jp/crid/1870865117698933376
https://www.ncbi.nlm.nih.gov/pubmed/33115403
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Volume 52
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