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 | Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha : |
11/09/2014 |
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Actualizado : |
13/05/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
DE BARBIERI, I.; HEGARTY, R.S.; ODDY, V.H.; BARNETT, M.C.; LI, L.; NOLAN, J.V. |
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Afiliación : |
LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROGER S. HEGARTY, School of Environmental and Rural Science, University of New England, Trevenna Road, Armidale, NSW 2351, Australia; V. HUTTON ODDY, Beef Industry Centre, Department of Primary Industries NSW, Trevenna Road, Armidale, NSW 2351, Australia; MARK BARNETT, School of Environmental and Rural Science, University of New England, Trevenna Road, Armidale, NSW 2351, Australia; L. LI, School of Environmental and Rural Science, University of New England, Trevenna Road, Armidale, NSW 2351, Australia; JOHN V. NOLAN, School of Environmental and Rural Science, University of New England, Trevenna Road, Armidale, NSW 2351, Australia. |
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Título : |
Sheep of divergent genetic merit for wool growth do not differ in digesta kinetics while on restricted intakes. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Animal Production Science, May 2014, v. 54, no. 9, p. 1243-1247. DOI: https://doi.org/10.1071/AN14319 |
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DOI : |
10.1071/AN14319 |
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Idioma : |
Inglés |
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Notas : |
Received 12 March 2014; accepted 12 May 2014; published online 10 July 2014. Acknowledgements: The authors thank Evelyn Osborne, Jose Velazco, Alistair Donaldson, Carolina Silveira, Gary Cluley, Leanne Lisle, Sue Mortimer and Andrew Blakely for their technical support. Ignacio De Barbieri was supported by National Institute for Agricultural Research (INIA Uruguay). |
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Contenido : |
Sheep selected for high wool growth were previously shown to exhibit higher microbial protein outflow from the rumen and higher uptake of amino nitrogen in portal blood than those selected for low wool growth. This suggests that genetic selection for wool growth may induce changes in foregut physiology. This study was undertaken to determine whether differences in digesta kinetics, especially mean retention mime (MRT), are associated with differences in fleece production between sheep with low or high estimated breeding values (EBVs) for fleece weight. Twenty mature Merino wethers with uniform EBVs for liveweight were allocated to two groups of 10 animals on the basis of high or low EBVs for yearling fleece weight. Five sheep with low-EBVs and five sheep with high-EBVs for fleece weight groups were allocated in a crossover design to low and high feeding-level treatments, which comprised a blended hay diet fed at maintenance or 1.5 times maintenance. All sheep were given single doses of chromium-mordanted fibre and cobalt-EDTA as inert, non-digestible markers. Digesta kinetics was determined by analysis of the faecal marker excretion patterns using
a compartmental model. Higher feed intakes from animals fed 1.5 times maintenance were associated with higher rates of wool growth and higher masses of indigestible fibre in the gut, but reduced MRT of digesta. Although sheep with higher EBVs for fleece weight had higher wool growth rates, there was no indication that these wool growth differences were associated with differences in digesta kinetics. The lack of interaction between feeding level and genotype suggests that MRT did not contribute to genotype differences in wool growth in sheep fed restricted intakes. The differences in wool growth among commercial Merino sheep with divergent fleece weight EBVs achieved by multi-trait selection are not attributable to differences in digesta kinetics, at least when feed is not available ad libitum. MenosSheep selected for high wool growth were previously shown to exhibit higher microbial protein outflow from the rumen and higher uptake of amino nitrogen in portal blood than those selected for low wool growth. This suggests that genetic selection for wool growth may induce changes in foregut physiology. This study was undertaken to determine whether differences in digesta kinetics, especially mean retention mime (MRT), are associated with differences in fleece production between sheep with low or high estimated breeding values (EBVs) for fleece weight. Twenty mature Merino wethers with uniform EBVs for liveweight were allocated to two groups of 10 animals on the basis of high or low EBVs for yearling fleece weight. Five sheep with low-EBVs and five sheep with high-EBVs for fleece weight groups were allocated in a crossover design to low and high feeding-level treatments, which comprised a blended hay diet fed at maintenance or 1.5 times maintenance. All sheep were given single doses of chromium-mordanted fibre and cobalt-EDTA as inert, non-digestible markers. Digesta kinetics was determined by analysis of the faecal marker excretion patterns using
a compartmental model. Higher feed intakes from animals fed 1.5 times maintenance were associated with higher rates of wool growth and higher masses of indigestible fibre in the gut, but reduced MRT of digesta. Although sheep with higher EBVs for fleece weight had higher wool growth rates, there was no indication that these wool gr... Presentar Todo |
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Palabras claves : |
ESTIMATED BREEDING VALUES; FEED INTAKE; FLEECE WEIGHT; MEAN RETENTION TIME. |
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Thesagro : |
OVINOS. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
LEADER 03128naa a2200265 a 4500
001 1050143
005 2020-05-13
008 2014 bl uuuu u00u1 u #d
024 7 $a10.1071/AN14319$2DOI
100 1 $aDE BARBIERI, I.
245 $aSheep of divergent genetic merit for wool growth do not differ in digesta kinetics while on restricted intakes.
260 $c2014
500 $aReceived 12 March 2014; accepted 12 May 2014; published online 10 July 2014. Acknowledgements: The authors thank Evelyn Osborne, Jose Velazco, Alistair Donaldson, Carolina Silveira, Gary Cluley, Leanne Lisle, Sue Mortimer and Andrew Blakely for their technical support. Ignacio De Barbieri was supported by National Institute for Agricultural Research (INIA Uruguay).
520 $aSheep selected for high wool growth were previously shown to exhibit higher microbial protein outflow from the rumen and higher uptake of amino nitrogen in portal blood than those selected for low wool growth. This suggests that genetic selection for wool growth may induce changes in foregut physiology. This study was undertaken to determine whether differences in digesta kinetics, especially mean retention mime (MRT), are associated with differences in fleece production between sheep with low or high estimated breeding values (EBVs) for fleece weight. Twenty mature Merino wethers with uniform EBVs for liveweight were allocated to two groups of 10 animals on the basis of high or low EBVs for yearling fleece weight. Five sheep with low-EBVs and five sheep with high-EBVs for fleece weight groups were allocated in a crossover design to low and high feeding-level treatments, which comprised a blended hay diet fed at maintenance or 1.5 times maintenance. All sheep were given single doses of chromium-mordanted fibre and cobalt-EDTA as inert, non-digestible markers. Digesta kinetics was determined by analysis of the faecal marker excretion patterns using a compartmental model. Higher feed intakes from animals fed 1.5 times maintenance were associated with higher rates of wool growth and higher masses of indigestible fibre in the gut, but reduced MRT of digesta. Although sheep with higher EBVs for fleece weight had higher wool growth rates, there was no indication that these wool growth differences were associated with differences in digesta kinetics. The lack of interaction between feeding level and genotype suggests that MRT did not contribute to genotype differences in wool growth in sheep fed restricted intakes. The differences in wool growth among commercial Merino sheep with divergent fleece weight EBVs achieved by multi-trait selection are not attributable to differences in digesta kinetics, at least when feed is not available ad libitum.
650 $aOVINOS
653 $aESTIMATED BREEDING VALUES
653 $aFEED INTAKE
653 $aFLEECE WEIGHT
653 $aMEAN RETENTION TIME
700 1 $aHEGARTY, R.S.
700 1 $aODDY, V.H.
700 1 $aBARNETT, M.C.
700 1 $aLI, L.
700 1 $aNOLAN, J.V.
773 $tAnimal Production Science, May 2014$gv. 54, no. 9, p. 1243-1247. DOI: https://doi.org/10.1071/AN14319
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INIA Tacuarembó (TBO) |
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
30/06/2021 |
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Actualizado : |
30/06/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
MISZTAL, I.; AGUILAR, I.; LOURENCO, D.; MA, L.; STEIBEL, J.P. |
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Afiliación : |
IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.; LI MA, Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA.; JUAN PEDRO STEIBEL, Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA. |
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Título : |
Emerging issues in genomic selection. |
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Complemento del título : |
Animal Genetics and Genomics. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Journal of Animal Science, June 2021, Volume 99, Issue 61, skab092. OPEN ACCESS. Doi: https://doi.org/10.1093/jas/skab092 |
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ISSN : |
1525-3163 |
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DOI : |
10.1093/jas/skab092 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 23 January 2021; Accepted 26 March 2021; Advance Access publication March 27, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
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Contenido : |
ABSTRACT. - Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface.
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. MenosABSTRACT. - Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for import... Presentar Todo |
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Palabras claves : |
Genomic evaluation; Genomic selection; Genomwide association studies; Large data; Stability of genomic predictions. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
https://academic.oup.com/jas/article-pdf/99/6/skab092/38539545/skab092.pdf
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Marc : |
LEADER 03992naa a2200265 a 4500
001 1062206
005 2021-06-30
008 2021 bl uuuu u00u1 u #d
022 $a1525-3163
024 7 $a10.1093/jas/skab092$2DOI
100 1 $aMISZTAL, I.
245 $aEmerging issues in genomic selection.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 23 January 2021; Accepted 26 March 2021; Advance Access publication March 27, 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
520 $aABSTRACT. - Genomic selection (GS) is now practiced successfully across many species. However, many questions remain, such as long-term effects, estimations of genomic parameters, robustness of genome-wide association study (GWAS) with small and large datasets, and stability of genomic predictions. This study summarizes presentations from the authors at the 2020 American Society of Animal Science (ASAS) symposium. The focus of many studies until now is on linkage disequilibrium between two loci. Ignoring higher-level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, the selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make the computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWASs using small genomic datasets frequently find many marker-trait associations, whereas studies using much bigger datasets find only a few. Most of the current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit the computation of P-values from genomic best linear unbiased prediction (GBLUP), where models can be arbitrarily complex but restricted to genotyped animals only, and single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top-ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as 1 SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. Although many issues in GS have been solved, many new issues that require additional research continue to surface. © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science.
653 $aGenomic evaluation
653 $aGenomic selection
653 $aGenomwide association studies
653 $aLarge data
653 $aStability of genomic predictions
700 1 $aAGUILAR, I.
700 1 $aLOURENCO, D.
700 1 $aMA, L.
700 1 $aSTEIBEL, J.P.
773 $tJournal of Animal Science, June 2021, Volume 99, Issue 61, skab092. OPEN ACCESS. Doi: https://doi.org/10.1093/jas/skab092
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