Background: The economy of Rio Grande do Sul (RS) relies majorly on agriculture; among the livestock production chains, cattle production has the largest economic, historical, and cultural importance in RS. The cattle industry is the main zootechnical activity in RS. Due to this, there is an actual need for updated characterization of the animal population, considering the population dynamics and the requirements imposed by the Official Veterinary Service (SVO) to meet certain characteristics. This would facilitate appropriate policies and measures to safeguard the health of the cattle in RS, as well as safeguard public health, and consequently avoid the economic impacts of possible health events. Materials, Methods & Results: Based on data from the livestock survey of 2013 from the Department of Animal Health (DDA), the Secretariat of Agriculture, Livestock, and Agribusiness of the State of Rio Grande do Sul (SEAPA-RS), descriptive and spatial analyses of the cattle population were performed using software R and ArcMap TM 10, respectively. It was observed that the state has more than 13 million cattle distributed over approximately 346,000 farms. The majority of the bovine population consists of females over the age of 36 months. The predominant function of these farms is a complete cycle (breeding to fattening). Beef production is the predominant activity, followed by a mix of beef production and dairy production, and then sole dairy production. These characteristics differ depending on the state’s region. Regarding the number of animals per property, 88% of properties are small having up to 50 cattle, and about 1% of properties have more than 500 animals. The general average in the state for the proportion of T:V (calf: cow) is 57 calves per 100 cows, and this is close to the national average. Discussion: About 60.62% of cattle herds consisted of animals aged over 24 months, and most of this group were females over 36 months of age (38.95%). About 50% of properties have up to 10 animals, demonstrating a large proportion of small farms. RS has an imbalance in its production system, with a large number of breeding females for the activity of beef production. The cattle in RS are mostly bred for the production of beef in a full cycle system (with all stages of production on the property), and only 10% of cattle raised in RS are bred solely for milk production. With regard to the proportion of T:V, we concluded that the state’s beef production shows modest productivity and needs to improve production rates to increase financial returns for producers and enable competitiveness in the domestic and international markets. Furthermore, this information correlates with previous studies that have reported that farms in the business of beef production use low technology and low performance animals. Dairy farming, in contrast with beef farming, has been modernizing and developing in recent years by increasing co-operatives and agribusinesses, which has led to greater knowledge through technical assistance to the farms. Extensive farming is dependent on field areas and is historically associated with the natural fields in the campaign region, since dairy farming is dependent on areas where there is a supply of specialized food. Thus, despite the state having a greater concentration of animals in the south-southwest, production indices are similar to other regions, and the type of farming undertaken exerts a great influence on the regional animal population structure.
ABSTRACT A Nextclade data set for PRRSV-1 ORF5 based on a global nomenclature for standardized lineage classification was developed. This tool enables rapid sequence analysis, visualization, and comparison with reference strains and vaccines. By providing accessibility, it facilitates broader adoption of PRRSV-1 classification frameworks for research and surveillance.
Influenza A viruses (IAV) in swine constitute a major economic burden to an important global agricultural sector, impact food security, and are a public health threat. Despite significant improvement in surveillance for IAV in swine over the past 10 years, sequence data have not been integrated into a systematic vaccine strain selection process for predicting antigenic phenotype and identifying determinants of antigenic drift.
ABSTRACT Existing genetic classification systems for porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2), such as restriction fragment length polymorphisms and sub-lineages, are unreliable indicators of close genetic relatedness or lack sufficient resolution for epidemiological monitoring routinely conducted by veterinarians. Here, we outline a fine-scale classification system for PRRSV-2 genetic variants in the United States. Based on >25,000 U.S. open reading frame 5 (ORF5) sequences, sub-lineages were divided into genetic variants using a clustering algorithm. Through classifying new sequences every 3 months and systematically identifying new variants across 8 years, we demonstrated that prospective implementation of the variant classification system produced robust, reproducible results across time and can dynamically accommodate new genetic diversity arising from virus evolution. From 2015 to 2023, 118 variants were identified, with ~48 active variants per year, of which 26 were common (detected >50 times). Mean within-variant genetic distance was 2.4% (max: 4.8%). The mean distance to the closest related variant was 4.9%. A routinely updated webtool ( https://stemma.shinyapps.io/PRRSLoom-variants/ ) was developed and is publicly available for end users to assign newly generated sequences to a variant ID. This classification system relies on U.S. sequences from 2015 onward; further efforts are required to extend this system to older or international sequences. Finally, we demonstrate how variant classification can better discriminate between previous and new strains on a farm, determine possible sources of new introductions into a farm/system, and track emerging variants regionally. Adoption of this classification system will enhance PRRSV-2 epidemiological monitoring, research, and communication, and improve industry responses to emerging genetic variants. IMPORTANCE The development and implementation of a fine-scale classification system for PRRSV-2 genetic variants represent a significant advancement for monitoring PRRSV-2 occurrence in the swine industry. Based on systematically applied criteria for variant identification using national-scale sequence data, this system addresses the shortcomings of existing classification methods by offering higher resolution and adaptability to capture emerging variants. This system provides a stable and reproducible method for classifying PRRSV-2 variants, facilitated by a freely available and regularly updated webtool for use by veterinarians and diagnostic labs. Although currently based on U.S. PRRSV-2 ORF5 sequences, this system can be expanded to include sequences from other countries, paving the way for a standardized global classification system. By enabling accurate and improved discrimination of PRRSV-2 genetic variants, this classification system significantly enhances the ability to monitor, research, and respond to PRRSV-2 outbreaks, ultimately supporting better management and control strategies in the swine industry.
Nexus format phylogenetic tree. Hemagglutinin H1 Subtype Reference Sequences. Reference sequences used for determining the clade an H1 subtype hemagglutinin sequence falls into. (TXT 21 kb)
We evaluated an active participatory design for the regional surveillance of notifiable swine pathogens based on testing 10 samples collected by farm personnel in each participating farm. To evaluate the performance of the design, public domain software was used to simulate the introduction and spread of a pathogen among 17,521 farms in a geographic region of 1,615,246 km
Abstract Swine are a primary source for the emergence of pandemic influenza A viruses. The intensification of swine production, along with global trade, has amplified the transmission and zoonotic risk of swine influenza virus (swIAV). Effective surveillance is essential to uncover emerging virus strains, however gaps remain in our understanding of the swIAV genomic landscape in Southeast Asia. By collecting more than 4,000 nasal swabs and 4,000 sera from pigs in Cambodia, we unmasked the co-circulation of multiple lineages of genetically diverse swIAV of pandemic concern. Genomic analyses revealed a novel European avian-like H1N2 swine reassortant variant with North American triple reassortant internal genes, that emerged approximately seven years before its first detection in pigs in 2021. Using phylogeographic reconstruction, we identified south central China as the dominant source of swine viruses disseminated to other regions in China and Southeast Asia. We also identified nine distinct swIAV lineages in Cambodia, which diverged from their closest ancestors between two to 15 years ago, indicating significant undetected diversity in the region, including reverse zoonoses of human H1N1/2009 pandemic and H3N2 viruses. A similar period of cryptic circulation of swIAVs occurred in the decades before the H1N1/2009 pandemic. The hidden diversity of swIAV observed here further emphasizes the complex underlying evolutionary processes present in this region, reinforcing the importance of genomic surveillance at the human-swine interface for early warning of disease emergence to avoid future pandemics.
RESUMO: Foi realizado um levantamento nos arquivos do Laboratório de Patologia Veterinária (LPV) da Universidade Federal de Mato Grosso (UFMT) das doenças de bovinos registradas entre os anos 2005 a 2014. Foram revisados 1124 casos. Destes, 27,6% foram amostras obtidas de necropsias realizadas por técnicos do LPV-UFMT e 72,3% foram amostras encaminhadas ao LPV-UFMT por veterinários de campo. Em 49,38% dos casos (555/1124) o diagnóstico da doença foi feito através da análise morfológica de lesões e/ou através de exames complementares. Raiva foi a principal causa de morte de bovinos neste estudo (7,82%). As doenças inflamatórias e parasitárias foram as mais prevalentes sendo diagnosticadas em 27,49% dos casos, seguida das doenças tóxicas e toxiinfecções com 9,78%. As demais categorias foram distribuídas em ordem decrescente em: neoplasmas e lesões tumoriformes (4%), doenças degenerativas (3,02%), distúrbios causados por agentes físicos (2,84%), distúrbios metabólicos e nutricionais (1,42%) e outras categorias (0,71%).
Nexus format phylogenetic tree. Hemagglutinin H3 Subtype Reference Sequences. Reference sequences used for determining the clade an H3 subtype hemagglutinin sequence falls into. (TXT 29 kb)
