Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle
CONCLUSIONS: Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.PMID:38491422 | PMC:PMC10943865 | DOI:10.1186/s12711-024-00887-6 (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 16, 2024 Category: Genetics & Stem Cells Authors: Marina Mart ínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Sabor ío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A Cleveland Mick Watson Rainer Roehe Source Type: research
Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle
CONCLUSIONS: Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.PMID:38491422 | PMC:PMC10943865 | DOI:10.1186/s12711-024-00887-6 (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 16, 2024 Category: Genetics & Stem Cells Authors: Marina Mart ínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Sabor ío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A Cleveland Mick Watson Rainer Roehe Source Type: research
Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle
CONCLUSIONS: Our work sheds light on the role of the microbial metabolism in the growth trajectory of beef cattle at the genomic level and provides insights into the potential benefits of using microbiome information in future genomic breeding programs to accurately estimate GEBV and increase ADG at each finishing stage in beef cattle.PMID:38491422 | DOI:10.1186/s12711-024-00887-6 (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 16, 2024 Category: Genetics & Stem Cells Authors: Marina Mart ínez-Álvaro Jennifer Mattock Óscar González-Recio Alejandro Sabor ío-Montero Ziqing Weng Joana Lima Carol-Anne Duthie Richard Dewhurst Matthew A Cleveland Mick Watson Rainer Roehe Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
Confidence intervals for validation statistics with data truncation in genomic prediction
CONCLUSIONS: Estimating the sampling variation of predictivity and the statistics in the LR method without replication or bootstrap is possible for any dataset with the formulas presented in this study.PMID:38459504 | DOI:10.1186/s12711-024-00883-w (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 8, 2024 Category: Genetics & Stem Cells Authors: Matias Bermann Andres Legarra Alejandra Alvarez Munera Ignacy Misztal Daniela Lourenco Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values
CONCLUSIONS: GWABLUP uses GWAS results to differentially weigh all the SNPs in a weighted GBLUP genomic prediction analysis. GWABLUP yielded up to 10% and 13% more reliable genomic predictions than GBLUP for single and multitrait analyses, respectively. Extension of GWABLUP to single-step analyses is straightforward.PMID:38429665 | DOI:10.1186/s12711-024-00881-y (Source: Genet Sel Evol)
Source: Genet Sel Evol - March 1, 2024 Category: Genetics & Stem Cells Authors: Theo Meuwissen Leiv Sigbjorn Eikje Arne B Gjuvsland Source Type: research
