Articles | Volume 65, issue 2
https://doi.org/10.5194/aab-65-207-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/aab-65-207-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review
| 
20 May 2022
Review |
| 20 May 2022
| 20 May 2022
Status quo of genetic improvement in local goats: a review
Glafiro Torres-Hernández
Colegio de Postgraduados-Campus Montecillo, 56230 Montecillo, Estado
de México, México
Jorge Alonso Maldonado-Jáquez
CORRESPONDING AUTHOR
Instituto Nacional de Investigaciones Forestales, Agrícolas y
Pecuarias, Centro de Investigación Regional Norte Centro, Campo
Experimental La Laguna, 27440 Matamoros, Coahuila, México
Colegio de Postgraduados-Campus Montecillo, 56230 Montecillo, Estado
de México, México
Lorenzo Danilo Granados-Rivera
Instituto Nacional de Investigaciones Forestales, Agrícolas y
Pecuarias, Centro de Investigación Regional Noreste, Campo Experimental
General Terán, 67400 General Terán, Nuevo León, México
Homero Salinas-González
Cooperative Extension and Research, Lincoln University, 65101
Jefferson City, MO, USA
Gabriela Castillo-Hernández
Facultad de Estudios
Superiores Cuautitlán, Universidad Nacional Autónoma de México, 54714 Cuautitlán Izcalli, Estado de
México, México
Colegio de Postgraduados-Campus Montecillo, 56230 Montecillo, Estado
de México, México
Related subject area
Subject: Quantitative genetics and estimation of breeding value | Animal: Goats
Population validation of reproductive gene mutation loci and association with the litter size in Nubian goat
Genetic analysis of lifetime productivity traits in goats
Associations between genetic variants of the POU1F1 gene and production traits in Saanen goats
The prediction of live weight of hair goats through penalized regression methods: LASSO and adaptive LASSO
Sanbao Zhang, Xiaotong Gao, Yuhang Jiang, Yujian Shen, Hongyue Xie, Peng Pan, Yanna Huang, Yingming Wei, and Qinyang Jiang
Arch. Anim. Breed., 64, 375–386, https://doi.org/10.5194/aab-64-375-2021, https://doi.org/10.5194/aab-64-375-2021, 2021
Short summary
Short summary
In this study, we found that 21 mutation loci and 3 haplotypes were significantly associated with litter size in Nubian goat. This would allow breeders to take more precise selection decisions, leading to significantly higher productivity and profitability within the Nubian goat.
Marie-Rosa Wolber, Henning Hamann, and Pera Herold
Arch. Anim. Breed., 64, 293–304, https://doi.org/10.5194/aab-64-293-2021, https://doi.org/10.5194/aab-64-293-2021, 2021
Short summary
Short summary
As part of the development of a breeding programme for dairy goats to support sustainable production, we aimed to identify selection traits measured in regular milk recording. In summary, the length of the animal's productive life, lifetime efficiency, and the milk yield efficiency with respect the total number of lactating days are suitable traits to indicate lifetime productivity in dairy goats. Breeding associations must now decide which traits to implement in the breeding programme.
Raziye Işık and Güldehen Bilgen
Arch. Anim. Breed., 62, 249–255, https://doi.org/10.5194/aab-62-249-2019, https://doi.org/10.5194/aab-62-249-2019, 2019
Short summary
Short summary
This study determined polymorphisms of the POU1F1 gene and their relationships to milk yield and components, litter size, birth weight, and weaning weight in goats. With the POU1F1/AluI locus, significant associations were found between genotypes with lactation milk yield and litter size. A significant relationship was determined between genotypes and birth weight and the POU1F1/PstI locus (p < 0.05). The POU1F1 gene can be used as a molecular marker for economic features.
Suna Akkol
Arch. Anim. Breed., 61, 451–458, https://doi.org/10.5194/aab-61-451-2018, https://doi.org/10.5194/aab-61-451-2018, 2018
Short summary
Short summary
This study was conducted to estimate the live weight of Hair goats from biometric measurements and to select variables in order to reduce the model complexity by using penalised regression methods, LASSO and Adaptive LASSO, for
γ = 0.5 and γ = 1. It was concluded that Adaptive LASSO (γ = 1) estimated the live weight with the highest accuracy for both male and female Hair goats when all the criteria were considered.
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Short summary
Important advances have been found in genetic improvement of local goats around the world; however, important limitations are still observed in basic aspects of nutrition, health, and genetics, among others.
Important advances have been found in genetic improvement of local goats around the world;...
