Genetic and geographical integration for ruminant production under climate change with particular emphasis on Brazil

Concepta McManus; Helder  Louvandini; Potira Hermuche; Renato Guimarães; Osmar Abilio de Carvalho Junior; Felipe Pimentel; Daniel Pimentel; Samuel Paiva; Vanessa  Peripolli

doi:10.31893/avr.2022009

Keywords:

georeferencing

landscape genetics

molecular markers

stressful environments

Abstract

The use of georeferencing technologies and genetic information has increased to integrate management and planning of livestock production systems, predict adaptive capacities, and aid in developing strategies for national Animal Genetic Resource Conservation Programs. Researchers and farmers can use this information to define conservation objectives for individual breeds and examine environmental factors that affect extinction risk, such as disease threats. Molecular markers and geographic information come together in landscape genetics, a combination of landscape ecology and population genetics, to provide information on the interaction between landscape and evolutionary processes. Results reveal attributes that affect genetic adaptation to specific environmental stressors such as diseases, parasites, extreme heat, vegetation type, lack of water, or combinations. Recent preliminary studies in Brazil used these tools to identify the regional usage patterns for animal production based on environmental criteria and breed distribution data. The results have been used as a further criterion to optimise in situ, and ex situ conservation schemes and plan expansion and adaptation of production systems. The use of production environment descriptors and climatic and genetic information will help maintain animal production systems in a changing world.
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How to cite

McManus, C., Louvandini, H., Hermuche, P., Guimarães, R., de Carvalho Junior, O. A., Pimentel, F., Pimentel, D., Paiva, S., & Peripolli, V. . (2022). Genetic and geographical integration for ruminant production under climate change with particular emphasis on Brazil. Applied Veterinary Research, 1(2), 2022009. https://doi.org/10.31893/avr.2022009

[1] Al-Araimi NA, Al-Atiyat RM, Gaafar OM, Vasconcelos R, Luzuriaga-Neira A, Eisa MO, Amir N, Benaissa MH, Alfaris AA, Aljumaah RS, Elnakhla SM, Salem MMI, Ishag IA, Khasmi ME, Beja-Pereira A (2017) Maternal genetic diversity and phylogeography of native Arabian goats. Livestock Science 206:88-94. https://doi.org/10.1016/j.livsci.2017.09.017.

[2] Amane A, Belay G, Nasser Y, Kyalo M, Dessie T, Kebede A. Getachew T, Domelevo Entfellner J-B, Edea Z, Hanotte O, Mekuriaw G (2020) Genome wide insights of Ethiopian indigenous sheep populations reveal the population structure related to tail morphology and phylogeography. Genes and Genomics. 42:1169-1178. doi: 10.1007/s13258-020-00984-y.

[3] Angers B, Magnan P, Plante M, Bernatchez L (1999) Canonical correspondence analysis for estimating spatial and environmental effects on microsatellite gene diversity in brook charr (Salvelinus fontinalis). Molecular Ecology 8:1043–1053.

[4] Avise JC (1998) The history and purview of phylogeography: a personal reflection. Molecular Ecology. 7:371–379

[5] Avise JC, Arnold J, Ball RM, Bermingham E, Lamb T, Neigel JE, Reeb CA, Saunders NC (1987) Intraspecific Phylogeography: The Mitochondrial DNA Bridge Between Population Genetics and Systematics. Annual Review of Ecology and Systematics 18: 489–522.

[6] Bajardi P, Barrat A, Savini L, Colizza V (2012) Optimising surveillance for livestock disease spreading through animal movements. Journal of the Royal Society Interface 9:2814-2825.

[7] Berners-Lee M, Kennelly C, Watson R, Hewitt CN, Kapuscinski AR, Locke KA, Peters CJ (2018) Current global food production is sufficient to meet human nutritional needs in 2050 provided there is radical societal adaptation. Elementa: Science of the Anthropocene 6:52.

[8] Bricarello PA, Gennari SM, Oliveira-Sequeira TCG, Vaz CMSL, Goncalves de Goncalves I, Echevarria FAM (2004) Worm burden and immunological responses in Corriedale and Crioula Lanada sheep following natural infection with Haemonchus contortus. Small Ruminant Research 51:75-83.

[9] Campos E, Cuéllar J, Slavador O, García-Trejo EA, Pereira F (2020) The genetic diversity and phylogeography of Mexican domestic sheep. Small Ruminant Research 187:106109

[10] Carvalho LFR, Melo CB, McManus C, Haddad JP (2012) Use of satellite images for geographical localisation of livestock holdings in Brazil. Preventative Veterinary Medicine 103:74–77. doi: 10.1016/j.prevetmed.2011.08.006. pmid:21917345

[11] Castanheira M, Paiva SR, Louvandini H, Landim A, Fiorvanti MCS, Dallago BS, Correa PS, McManus C (2010) Use of heat tolerance traits in discriminating between groups of sheep in central Brazil. Tropical Animal Health and Production42:1821–1828. doi:10.1007/s11250-010-9643-x

[12] Cavalli-Sforza LL, Menozzi P, Piazza A. (1994) The History and Geography of Human Genes (Princeton University Press, Princeton, New Jersey, USA.

[13] Cesconeto RJ, McManus CM, Paiva SR, Cobuci JA, Joost S, Braccini Neto J (2017) Landscape Genomic Approach to Detect Selection Signatures in Locally Adapted Brazilian Swine Genetic Groups. Ecology and Evolution, 7:9544-9556.

[14] Ciani E, Ciampolini R, D'Andrea M, Castellana E, Cecchi F, Incoronato C, d'Angelo F, Albenzio M, Pilla F, Matassino D, Cianci D (2013) Analysis of genetic variability within and among Italian sheep breeds reveals population stratification and suggests the presence of a phylogeographic gradient, Small Ruminant Research 112:21-27, https://doi.org/10.1016/j.smallrumres.2012.12.013.

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