Tolerância ao calor em cavalos Pantaneiros sob diferentes regimes de exercício

The objective of this work was to determine how different types of gait affect the physiological and thermographic responses of Pantaneiro horses (Equus ferus caballus) subjected to field conditions under high environmental temperatures. Ten horses were evaluated in a double 5x5 Latin square experimental design, with five gait types: walk, trot, extended trot, gallop, and extended gallop. The following physiological measures were determined immediately after exercise: heart and respiratory rates, blood lactate content, and rectal temperature. Body surface temperatures were evaluated using an infrared camera. The walk, trot, and extended trot were the most adequate gaits for Pantaneiro horses to maintain thermoregulation within the physiological norms under conditions with a high air temperature. The temperatures obtained in the eye and elbow regions show the best predictive capacity for physiological parameters.O objetivo deste trabalho foi determinar como os diferentes tipos de andamento afetam as respostas fisiológicas e termográficas de cavalos Pantaneiro (Equus ferus caballus) submetidos a condições ambientais com alta temperatura. Dez cavalos foram avaliados em delineamento experimental de quadrado latino 5x5 duplo, com cinco andamentos: passo, trote, trote estendido, galope e galope estendido. As seguintes medidas fisiológicas foram determinadas logo após os exercícios: taxas cardíaca e respiratória, teor de lactato sanguíneo e temperatura retal. As imagens termográficas foram avaliadas por meio de câmera de infravermelho. O passo, o trote e o trote estendido foram os andamentos mais adequados para os cavalos Pantaneiros manterem a termorregulação dentro das normas fisiológicas em condições de alta temperatura do ar. As temperaturas obtidas nas regiões da área do olho e da axila mostram maior capacidade preditiva para os parâmetros fisiológicos

Variabilidade genética de raças de ovelhas deslanadas do Brasil

ABSTRACT: The objectives of this work were to investigate the genetic structure of the Brazilian hair sheep breeds and to determine the origin of the Santa Inês breed. Molecular similarity was determined using Randomly Amplified Polymorphic DNA - Polymerase Chain Reaction markers in 238 individuals from five naturalized sheep breeds: Santa Inês (48 animals), Rabo Largo (48), Somali (48), Morada Nova (48) and Bergamasca (46), collected in Goiás, Sergipe, Bahia, and Ceará States as well as in the Federal District. Fifty-four loci were selected from 19 primers, after a pilot test using 140 primers. Qualitative analyses indicate diagnostic markers for all breeds. All breeds were significantly different from each other. Interbreed differences were explained by 14.92% of the total variation. Santa Inês clustered with Bergamasca (97% bootstrap) and with Rabo Largo, composing the third member of the group (81% bootstrap) while Morada Nova and Somali breeds clustered separately. Each breed should be considered as a separate management and conservation unit, and special care should be taken with Rabo Largo, Morada Nova and Somali breeds, represented by small herds in Brazil. ___________________________________________________________________________________ RESUMOOs objetivos deste trabalho foram identificar a origem racial de ovinos Santa Inês e avaliar a unicidade das populações das principais raças naturalizadas brasileiras de ovinos deslanado. Foi realizado um estudo dos padrões de semelhança molecular a partir de marcadores RAPD-PCR, utilizando-se 238 indivíduos dos Estados de Goiás, Sergipe, Bahia, e Ceará assim como do Distrito Federal, distribuídos entre as raças Santa Inês (48 animais), Bergamácia (46), Rabo Largo (48), Morada Nova (48) e Somali (48). Após triagem com 140 primers, foram selecionados 54 locos a partir de 19 primers e todas as raças apresentaram marcadores específicos. Análises qualitativas mostraram a presença de marcadores diagnóstico-específicos para todas as raças. As diferenças inter-raciais foram significativas e responsáveis por 14,92% da variação total observada. Na análise de agrupamento, a raça Santa Inês ficou próxima à Bergamácia (com 97% de valor bootstrap). A raça Rabo Largo apresentou maior similaridade com este grupo (com 81% bootstrap) do que as raças Morada Nova e Somali. Cada raça deve ser considerada como unidade de conservação e manejo, especialmente as raças Rabo Largo, Morada Nova e Somali, as quais apresentam as menores populações no País

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Milhares de SNPS genotipados por sequenciamento de alto desempenho (GBS - "Genotyping By Sequencing") em espécies de Eucalyptus

Marcadores moleculares têm sido usados em diversas áreas, constituindo de variações na sequência de DNA, detectadas por meio de diferentes técnicas, como a reação em cadeia da polimerase (PCR), ou corte com enzimas de restrição, seguidas de eletroforese, ou o sequenciamento direto da molécula de DNA. Estas técnicas são analisadas no presente trabalho, em contraposição   metodologia de genotipagem por sequenciamento GbS ("genotyping by sequencing"). A GbS abre perspectivas fenomenais para a análise genética em qualquer espécie e foi testada em duas espécies de Eucalyptus L'Hér., em que apresentou um bom desempenho. Os resultados obtidos demonstraram o sucesso da construção da biblioteca e a capacidade de análise simultânea de indiví­duos. A GbS se caracteriza por não demandar o desenvolvimento prévio de marcadores, se basear em reagentes universais, permite o sequenciamento de centenas de amostras simultaneamente e a quantidade inicial de DNA necessário para cada amostra é pequena

Milhares de SNPS genotipados por sequenciamento de alto desempenho (GBS - "Genotyping By Sequencing") em espécies de Eucalyptus

Marcadores moleculares têm sido usados em diversas áreas, constituindo de variações na sequência de DNA, detectadas por meio de diferentes técnicas, como a reação em cadeia da polimerase (PCR), ou corte com enzimas de restrição, seguidas de eletroforese, ou o sequenciamento direto da molécula de DNA. Estas técnicas são analisadas no presente trabalho, em contraposição   metodologia de genotipagem por sequenciamento GbS ("genotyping by sequencing"). A GbS abre perspectivas fenomenais para a análise genética em qualquer espécie e foi testada em duas espécies de Eucalyptus L'Hér., em que apresentou um bom desempenho. Os resultados obtidos demonstraram o sucesso da construção da biblioteca e a capacidade de análise simultânea de indiví­duos. A GbS se caracteriza por não demandar o desenvolvimento prévio de marcadores, se basear em reagentes universais, permite o sequenciamento de centenas de amostras simultaneamente e a quantidade inicial de DNA necessário para cada amostra é pequena

Association between insulin-like growth factor I (IGF-I) microsatellite polymorphisms and important economic traits in pigs

This study investigated the association between IGF-I microsatellite marker in an F2 population (N=459) generated by mating of native boars to Brazilian commercial sows with performance, carcass cut, and meat quality traits. Association analyses were carried out using a statistical model that included genotype, sex, and group as fixed effects and sire as random effect. The IGF-I genotypes were significantly associated with different quantitative traits and these results corroborate with previous QTL analyses obtained for this chromosome region in swine. Additive and dominance effects, as well as a genotype-sex interaction, were estimated and discussed in the text. According to the results obtained, this marker is suitable for QTL search in the genotyped population