The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock
Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are als...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/11/10/2833 |
| _version_ | 1827680391468679168 |
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| author | Matilde Maria Passamonti Elisa Somenzi Mario Barbato Giovanni Chillemi Licia Colli Stéphane Joost Marco Milanesi Riccardo Negrini Monia Santini Elia Vajana John Lewis Williams Paolo Ajmone-Marsan |
| author_facet | Matilde Maria Passamonti Elisa Somenzi Mario Barbato Giovanni Chillemi Licia Colli Stéphane Joost Marco Milanesi Riccardo Negrini Monia Santini Elia Vajana John Lewis Williams Paolo Ajmone-Marsan |
| author_sort | Matilde Maria Passamonti |
| collection | DOAJ |
| description | Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios. |
| first_indexed | 2024-03-10T06:47:11Z |
| format | Article |
| id | doaj.art-551eb78babef48f58d4f114c35b40ba9 |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-10T06:47:11Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-551eb78babef48f58d4f114c35b40ba92023-11-22T17:09:51ZengMDPI AGAnimals2076-26152021-09-011110283310.3390/ani11102833The Quest for Genes Involved in Adaptation to Climate Change in Ruminant LivestockMatilde Maria Passamonti0Elisa Somenzi1Mario Barbato2Giovanni Chillemi3Licia Colli4Stéphane Joost5Marco Milanesi6Riccardo Negrini7Monia Santini8Elia Vajana9John Lewis Williams10Paolo Ajmone-Marsan11Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyDepartment for Innovation in Biological, Agro-Food and Forest Systems–DIBAF, Università Della Tuscia, Via S. Camillo de Lellis snc, 01100 Viterbo, ItalyDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyLaboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, SwitzerlandDepartment for Innovation in Biological, Agro-Food and Forest Systems–DIBAF, Università Della Tuscia, Via S. Camillo de Lellis snc, 01100 Viterbo, ItalyDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyImpacts on Agriculture, Forests and Ecosystem Services (IAFES) Division, Fondazione Centro Euro-Mediterraneo Sui Cambiamenti Climatici (CMCC), Viale Trieste 127, 01100 Viterbo, ItalyLaboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, SwitzerlandDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyDepartment of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, ItalyLivestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.https://www.mdpi.com/2076-2615/11/10/2833climate changelivestockadaptation |
| spellingShingle | Matilde Maria Passamonti Elisa Somenzi Mario Barbato Giovanni Chillemi Licia Colli Stéphane Joost Marco Milanesi Riccardo Negrini Monia Santini Elia Vajana John Lewis Williams Paolo Ajmone-Marsan The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock Animals climate change livestock adaptation |
| title | The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock |
| title_full | The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock |
| title_fullStr | The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock |
| title_full_unstemmed | The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock |
| title_short | The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock |
| title_sort | quest for genes involved in adaptation to climate change in ruminant livestock |
| topic | climate change livestock adaptation |
| url | https://www.mdpi.com/2076-2615/11/10/2833 |
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