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 in | Genetics Selection Evolution Vol. 52; no. 1; p. 64 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Springer Science and Business Media LLC
28.10.2020
BioMed Central Ltd BioMed Central BMC |
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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. |
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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 |
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